UNITED STATES ENVIRONMENTAL PROTECTION AGENCY
OFFICE OF ENFORCEMENT AND COMPLIANCE MONITORING
EPA-330/9-89-004
PCB ANALYTICAL PROGRAM
STANDARD OPERATING PROCEDURES
May 1989
Dean F. Hill
Arturo Palomares
NATIONAL ENFORCEMENT INVESTIGATIONS CENTER
Denver Colorado
-------
CONTENTS
I. INTRODUCTION 1
II. PROGRAM MANAGEMENT 2
III. SAMPLING AND FIELD ACTIVITIES 3
IV. SAMPLE RECEIPT, STORAGE, AND CUSTODY 4
INTRODUCTION 4
SAMPLE CUSTODIAN 4
Laboratory Number Assignment 4
LABORATORY SAMPLE HISTORY FORM 5
LOG-IN PROCEDURE 5
Sample Log-in 5
Project Log-In 7
Sample Storage 10
Custody During and After Analysis 10
V. METHODOLOGY 11
VI. DATA RECORDING AND REVIEW 13
DATA RECORDING 13
Data Worksheets 13
Gas Chromotograph (GC) Logbook 17
Gas Chromatograms and Other Raw Data 19
DATA REVIEW 19
Recordkeeping 21
VII. INSTRUMENTATION 24
GAS CHROMATOGRAPHS 24
BALANCE 25
OTHER EQUIPMENT 26
REAGENTS/SOLVENTS 26
SOURCES 27
INVENTORY 27
STANDARD PREPARATION 29
-------
CONTENTS (cont.)
VIII. QUALITY ASSURANCE 31
BACKGROUND 31
IX. TRAINING 34
REFERENCES
APPENDICES
A MEMORANDUM OF UNDERSTANDING
B NEIC SAMPLING GUIDANCE
C NEIC ANALYTICAL METHOD
D EPA ANALYTICAL METHOD
E NEIC QUALITY ASSURANCE PROJECT PLAN
F EPA QUALITY CONTROL GUIDELINES
FIGURES
IV-1 LABORATORY SAMPLE HISTORY FORM 6
IV-2 DISK OPERATING SYSTEM (DOS) MENU 8
IV-3 BLANK SAMPLE LOG-IN RECORD 9
VI-1 OIL DATA WORKSHEET 14
VI-2 SOIL DATA WORKSHEET 15
VI-3 WIPE DATA WORKSHEET 16
VI-4 GAS CHROMATOGRAPH LOGBOOK 18
VI-5 GAS CHROMATOGRAPH AND OTHER RAW DATA 20
VI-6 ANALYTICAL REPORT 22
VI-7 COVER REPORT 23
VIII-1 ORDER FORM 28
-------
I. INTRODUCTION
This document prescribes in detail the operation of the NEIC
polychlorinated biphenyl (PCB) analysis program, particularly those aspects
that represent routine and ongoing tasks. These specific procedures are
derived from past successful experience and are intended to: (1) provide for
consistency of laboratory operations, (2) serve as a training guide and
(3) assure a high degree of accurate and defensible results.
The NEIC Policies and Procedures Manual1 is to be followed for NEIC
derived investigations, or wherever there is doubt as to what procedures to
follow with respect to custody, document handling and sample control.
-------
II. PROGRAM MANAGEMENT
Polychiorinated biphenyl (PCB) enforcement samples will derive
primarily from compliance inspections and incident investigations conducted by
EPA Regional Offices. Other samples may also derive from states, the EPA
Office of Compliance Monitoring, the EPA Office of Criminal Investigation or the
Operations Division of NEIC.
PCB analyses in support of the EPA Regional compliance programs are
governed by a memorandum of understanding (MOU) negotiated periodically
between the U.S. EPA Office of Compliance Monitoring (OCM) and NEIC. The
most recent MOU may be found in Appendix A. This MOU includes target
sample allocations by Region.
Criminal investigation samples will be analyzed in similar fashion as
those analyzed for compliance purposes; however, every effort will be made to
assure that only one analyst handles all samples for each case from its receipt
into the laboratory on through analyses and reporting. Procedures for handling,
analysis, and reporting of criminal case samples will be consistent with those
given in the NEIC Policies and Procedures Manual.1
-------
b
I
III. SAMPLING AND FIELD ACTIVITIES
The guidance given in Appendix B has been provided to the EPA
regional office personnel to assure receipt of PCB-related samples which are
meaningful, representative, and defensible. Further details regarding sampling
in the field are given in the EPA TSCA Inspection Manual^and the PCB Spill
Cleanup Poligy.3 Additional directions regarding sample identification and
chain-of-custody are provided in the NEIC Policies and Procedures Manual7
and the NEIC Multi-Media Compliance Audit Procedures.4 Sampling
guidelines are also given in a recent analytical manual on PCBs.5
EPA, state, and/or contracting personnel should contact the NEIC PCB
analytical staff directly if there are any questions or concerns regarding the type,
number, or quantity of material to be collected, or proper technique to be
employed, particularly when nonroutine situations are encountered.
-------
IV. SAMPLE RECEIPT, STORAGE, AND CUSTODY
INTRODUCTION
All compliance samples received at the NEIC laboratory for
polychlorinated biphenyl (PCB) analyses will be handled by following standard
chain-of-custody procedures. Chain-of-custody may be subject to challenge in
any subsequent legal proceedings, thus, strict sample control procedures are
imperative. It is the duty of the sample custodian, analytical staff and the
laboratory supervisor to ensure that prescribed procedures are followed. All
official samples received at the NEIC laboratory should already be under
custody. Custody implies both actual control of a physical sample and
documentation attesting to such control.
SAMPLE CUSTODIAN
Two individuals (primary sample custodian and an alternate) will be
designated by the supervisor to officially receive PCB compliance samples into
the NEIC laboratory. Once a sample has been officially received (logged in) it is
the responsibility of the assigned analyst to assume and maintain custody.
The sample custodian will inspect each sample and note information on
the condition of the shipping container(s), official seal, identification tag,
chain-of-custody record and the sample itself. Any potential problems, such as
an incompletely filled out tag or seal, or discrepancy in identification, shall be
fully noted. If the sample is leaking, broken or there are other signs of disturbed
sample integrity, senior laboratory personnel will be immediately notified for
resolution.
Laboratory Number Assignment
The sample custodian will access the program "LOG" on the IBM (or
equivalent) personal computer (PC), to obtain the last NEIC sample number
entered for the particular EPA region. He or she will then assign the next
consecutive NEIC sample number for that region to the sample. This number
indicates the region, sequence, fiscal year, PCB project number, and matrix.
-------
Thus, if five samples are received from Region V, the numbers "05-001-87-1-0,"
"05-002-87-1 -W," "05-003-87-1-S," "05-004-87-1-M," and "05-005-87-1-H"
would reflect EPA Region V, the sample sequence 001, 002, 003, 004 and 005,
the FY87, and the first (1) project from Region V. The last letter represents the
matrix [i.e., oil (0), wipe (W), soil (S), aqueous (H), or miscellaneous (M)]. This
unique nine-digit number will be written on each sample label (if present), on
the chain-of-custody, and on the "Laboratory Sample History" form. It will also
be written on a sticker that is to be placed on the cap of each sample container.
If unable to write the number, or place the sticker on the container because the
sample is sealed in a plastic bag, then the sticker with the NEIC number will be
placed conspicuously on the outer surface of the bag.
LABORATORY SAMPLE HISTORY FORM
The sample custodian will initiate an NEIC "Laboratory Sample History"
for each official sample including field blanks, if not already initiated on an
equivalent field form. Items 1 through 16 are to be filled out by the custodian
upon receipt. See Figure IV-1 as an example of a completed form. Apparent
custody or sample integrity problems or discrepancies are to be brought to the
attention of the senior staff or supervisor for resolution. Any discrepancies
between the sample seal, tags, or chain-of-custody form should be further
described under "Remarks", ltem-23. The NEIC sample number will be written
in the space labeled "NEIC Sample No." located on the upper right-hand corner
of the form. The sample container with all its contents including seals, tags, etc.,
will be weighed on a top-loading balance and the gross weight recorded in
Item 4.
LOG-IN PROCEDURE
Sample Loa-in
The sample custodian will log the samples into the IBM (or compatible)
PC system. Once all the samples for a particular project have been logged in,
the custodian will provide the senior chemist with an updated sample list.
-------
I
I
f
I
Figure IV-1
LABORATORY SAMPLE HISTORY FORM
I
:::?r RICSPD
5. Laboratory
I
Dace Received
Received Bv
Official Seal or Evicerca Tare
' On
Cor.tai-er
Received "ran
Sent Via
1,1. Sanple Description
K. Sanole Condition
13. Custody Seal(s) Yes_
Ifc. Dace Sealed
I
. Field Cujcody She«c
. Plac* Scored
LABORATORY RECORD
I
E. Assigned By
. Assigned To
«. Date Seal Broken
. Analysis Completed
21. Dace Stored
•?.. Place Scored
original
aliquot
original
aliquot
original
aliquoc
f
I
1
I
3. Remarks:
-------
Instructions
After the computer is turned on, the date is typed in, as prompted. At this
point, the Disk Operating System (DOS) menu will appear on the screen
[Figure IV-2]. Next the F1 key is pressed and a direction will be displayed to
insert the DBASE system diskette into "Drive A." The diskette is inserted, as
prompted, and the drive door is closed. Press any key to continue. When the
red light on drive A goes off, the diskette is removed from the drive and the door
closed. At the dot prompt, "do log" is typed in. The operator should now see an
instruction menu on the screen. The ordinal number corresponding to the
appropriate region is then pressed. At this point, the screen will show the last
consecutive NEIC sample number and regional sample number that was
assigned. Press any key to continue. A blank record will appear on the screen
[Figure IV-3]. The information is then typed in on the record, as prompted. Once
the entire record is completely filled in, the next blank record will appear. When
finished with all samples from one region, the return key is pressed (this is a
must!). The printer is turned on and any key is pressed to continue. The paper
on the printer will be advanced to the top of the next page. A complete listing of
all samples on record will be printed. At this point, the computer will return to
the "log" menu. One may then log in more samples from another region or may
exit. To exit, press "Q". The DOS menu [Figure IV-2] will appear on your
screen.
Project Log-In
The project log-in program, "Mushroom," can be accessed by pressing
the function key F1 (DBASE III). At the dot prompt, "do mushroom" is typed in.
The operator should now see an instruction menu on the screen. The ordinal
number corresponding to the appropriate region is then pressed. At this point,
the date the sample(s) were received (DR), the date analyses was initiated
(DS), the date the analyses was completed (DC), the name of the project
(PROJECT), the name of the analyst (CHEM), and the Region from which the
samples were received (R) will appear. After all the data has been displayed, a
prompt will appear asking if a hard copy is desired. A hard copy can be
obtained after the "Y" is pressed, a "no" answer will return the analyst to the
Mushroom menu. To exit, press "Q".
-------
I
I
I
I
I
I
I
I
B
i
i
i
i
i
i
Figure IV-2
DISK OPERATING SYSTEM (DOS) MENU
••[ WORKSTATION MENU ] =
Fl DATABASE |
F2 SPREADSHEET
F3 WORDPROCESSING
F4 COMMUNICATIONS / LAN ACCESS
F5 USER PROGRAMS
F6 DISK & FILE UTILITIES
F7 PROGRAMMING LANGUAGES
F8 EXIT TO DOS
= [ Menu 1 Of 11 ] =
-------
Figure IV-3
BLANK SAMPLE LOG-IN RECORD
NEIC_NUM
REG_NUM
RECEIVED / /
SAMPLED / /
PROJ
WT
CUSTODY
STORAGE
PROJNUM
-------
10
To add records, at the dot prompt, "use pcbtrk" is typed in. Another dot
prompt will appear. "Append" is typed in. A blank record will appear. When
finished entering all the necessary data "CTRL W" is pressed. To exit, "quit" is
typed in. The DOS menu will appear on the screen.
Sample Storage
The sample custodian is responsible for ensuring that all samples are
properly stored, prior to analyses. The samples will be stored in the locked
refrigerator until they are needed for analyses. The refrigerator will remain
locked at all times when not in active use, and only designated individuals will
have access to the key.
Custody During and After Analysis
PCB samples will normally be assigned for analyses on a complete
project basis by the senior chemist or supervisor. The analyst will then assume
responsibility for maintaining chain-of-custody for all samples for that project.
Thus, the analyst will complete the Laboratory Sample History form
[Figure IV-1).
After removing the sample(s) from the refrigerator, the NEIC sample
numbers on the sample containers will be verified by the analyst, assuring that
the NEIC sample number matches the number recorded on the chain-of-
custody form. The regional sample numbers on the sample containers are also
to be checked to assure that they match the numbers recorded on the chain-of-
custody records. Any discrepancies are to be reported to senior personnel for
resolution. Corrections are to be initialed by two individuals, preferably the
analyst and the senior staff person. The sample matrix recorded on the chain-
of-custody record is also to be verified as being consistent with that noted for the
actual sample.
Upon completion of analysis, all samples will be stored in the sample
storage room. The last analyst having custody of the sample(s), will place the
analyzed sample(s) in the appropriate storage cooler (by EPA region) and will
record the NEIC sample number on the sheet provided. All coolers, when full,
will be transferred to building 11.
-------
11
V. METHODOLOGY
The primary method to be used for analysis of oil, soil, and/or surface
collected samples will be the NEIC procedure titled "The Determination of
Polychlorinated Biphenyls in Oil, Soil, and Surface Samples." This method was
adapted directly from the standard Agency method "The Determination of
Polychlorinated Biphenyls in Transformer Fluids and Waste Oils," available as
EPA Publication Number EPA-600/4-81-045. The NEIC adaption was
developed and documented to address specific NEIC instrumentation and
equipment, screening techniques, and calculation procedures. The standard
procedure was also expanded to cover commonly encountered soil and surface
samples, as well as liquids other than transformer and waste oils, such as
capacitor, hydraulic, and heat exchange fluids. Otherwise, there is little
substantive difference between the two methods.
The NEIC procedure will be followed in all applicable cases unless
specific instructions to the contrary are provided by senior or supervisory
personnel.
The NEIC method is given in Appendix C and the referenced standard
Agency method from which it was reproduced as Appendix D.
The analysis of PCBs in other matrices will follow the referenced
procedures listed below to the extent possible, and any deviations from these
procedures will be fully documented.
Agricultural Commodities - FDA Pesticides Analytical Manual6
Water - EPA Method 60S7
Air (ambient) - High volume sampling8
Air (Workplace/high level) - NIOSH Method P & CAM 244$ and
low volume sampling 1°
Pigments - Dyestuffs Manufacturing Industry Method11
As By-Products - EPA Method12
Treatment Wastes - and EPA Solid Waste Office13
-------
Other methods are available that may find use in analyses of samples
involving diverse matrices or where interferences are encountered that are not
amenable to the usual approaches. Many of these procedures are listed in an
extensive summary of PCB analyses prepared by M. Erickson.14
-------
13
VI. DATA RECORDING AND REVIEW
DATA RECORDING
Data Worksheets
An appropriate worksheet [Figures VI-1 through VI-3] is to be filled out by
the analyst for each sample. The assigned NEIC Sample Number is entered as
it is to appear on all subsequent chromatograms, logbooks, and other data. The
Project Name is completed as it appears on the Chain-of-Custody form or on
the Laboratory Sample History form. A brief description of the sample is given
in the box titled "Sample Description." The name of the analyst is recorded in
the box labeled "Name of the Analyst." In the "Date Analysis Initiated" box the
date that the sample was taken out of storage to be analyzed is entered. In the
"Project Code" box enter the generic code (B-28) or other designations, as
appropriate. The "Screening Summary" box is to be completely filled out when
the analytical screening step is performed. Once analysis for the quantitative
determination is initiated, the sample weight (in grams) is recorded in the
"Weight of Sample" box.
If a duplicate is to be analyzed, its weight is recorded in the "Weight of Sample-
D" box. If a triplicate is analyzed its weight is entered in the "Weight of Sample-
T" box. If spiked samples are to be analyzed for recovery purposes, the sample
weights are recorded in the "Weight of Sample S-1" and in the "Weight of
Sample S-2" boxes (spikes are always analyzed in duplicate). In the "Solvent"
box, record the solvent used to extract or dilute the sample (i.e., 50/50 acetone-
hexane, hexane, etc.). In the "Solvent Vol." box, the volume (in ml) of solvent
used to extract or dilute the sample is entered. In the "Date" box record the date
the sample was weighed. The analyst's initials are entered in the box labeled
"Initials." For spiked samples record the concentration (in |ig/ml_) of the stock
standard used to spike the sample in the "Cone. Stock Std." box. In the "Spike
Vol." box enter the volume (in mL) of stock standard taken to spike the sample.
In the "Date" and "Analyst" boxes record the date and initials of the analyst,
respectively. In the "CLEAN-UP" box, an "X" is placed in the appropriate box
describing the clean-up technique used (i.e., sulfuric acid or
-------
I
I
I
Figure VI-1
OIL DATA WORKSHEET
• Imp r;ir,c.x Sid Prepared
[
H Con of SIOCK Sid (tig/mL)
1
Dale intermediate S!d Prepared
Con of Intermediate Sid
Dale Worx Sid Prepared
Con of Working Sid
^
Name of Analyst
1
1
1
1
Dale Analysis Initialed
Project Code
SCREENING SUMMARY
I
I
I
I
I
I
Solvent
Solv-vol
Oilulion
Date
Screening Procedure Followed
Analyst
YES
COMMENTS
NEIC SAMPLE NUMBER
PROJECT NAME
SAMPLE DESCRPTION
Sieved
Mined
Oat*
Initials
^Weight of Sample
-------
I
I
I
Figure VI-2
SOIL DATA WORKSHEET
1 Oaia Slock Sid Prepareo
!
Con ol Slock Sid ((ig/mL)
1
O,ji8 Intermediate Sid Prepared
Con ol Innrmediale SkJ
Dale Work Sid Prepared
Con of Working Sid
Name of Analyst
Dale Analyst* Initialed
Protect Cod*
SCflEENWG SUMvWTY
Solvent Solv vol Dilution Dale
Analyst
Screening Procedure Followed I
YES
COMMENTS:
Weight ol Wet Sample . Wwghl of Dry Sampto* W«gM oi «M Sampto x 100
Dak*
Analyst
NEIC SAMPLE NUMBER
PROJECT NAAC
SAM>1£ OESCWT10N
S»v«d Mined Dal* Initials
W«ghl ol Sampto
-------
Figure VI-3
WIPE DATA WORKSHEET
Pile SIOCK Sid Prepared
Con ot Slock Sid i^g/mL)
Oa'e intermediate Sid Prepared
Con ol Intermediate Sid
Dale Work Sid Prepared
Con of Working Sid
SCREENING SUMMARY
Solvent Solv-vol Dilution Date
Screening Procedure Followed
Analyst
YES
COMMENTS:
Name ol Analyst
Date Analysis Initiated
Proiect Code
Solvent
w
Solvent Vol.
(mL)
Date
Initials
NEIC SAMPLE NUMBER
PROJECT NAME
SAMPLE DESCRPT1ON
CLEAN-UP
Sulluric Acid
Alumina-Oxide
Date
Dale
Initials
Initials •
-------
17
aluminum oxide). In the box labeled "Date" the date that the sample was
"cleaned-up" is entered, along with the analyst's initials in the "Initials" box.
If the sample is a soil, the percent moisture may require determination. In
such cases: (1) record the weight of the wet sample in the boxes labeled
"Weight of Wet Sample" in grams (g), (2) record the dry weight of the sample in
the "Weight of Dry Sample" box also in grams, and (3) in the "Date" box record
the date the moisture content was taken. In the box labeled "Analyst" enter the
name of the analyst who performed the moisture content analysis.
If a particular sample is found to contain PCBs, the date the stock
standard was prepared must be entered in the box labeled "Date Stock Std.
Prepared." The information entered for the standard must correspond to the
Aroclor(s) found to be present in the sample. Record the date the intermediate
standard was prepared in the box labeled "Date Intermediate Std. Prepared." In
the "Date Working Std. Prepared" box, enter the date the working standard was
prepared. The concentration of the stock standard, concentration of the
intermediate standard, and concentration of the working standard are recorded
in the "Cone, of Stock Std.", "Cone, of Intermediate Std.", and "Con. of Working
Std." boxes, respectively. All units are recorded in (ig/mL. At the bottom of the
reverse side of each worksheet, the deviations from the standard procedure are
to be recorded along with any other pertinent notes and/or observations.
Gas Chromotograph (GC) Logbook
The gas chromatographic conditions (i.e., oven temperature, attenuation,
etc.), are to be recorded in the dedicated GC logbook [Figure VI-4]. The NEIC
sample number is recorded in the box titled "Sample No." and the run number is
entered in the box titled "Run No." Run numbers are assigned chronologically.
The date is entered in the box titled "MO/DAY/YR." In the "% Sol" box, enter the
dilution factor used in the analysis. Enter the GC column number in the box
titled "COL NO."; this is a unique NEIC number assigned to the gas
chromatographic column. Record the phase (e.g., 3% OV-101), injection
-------
1
1
1
1
1
1
1
1
1
1
•
Figure VI-4
GC LOGBOOK
SAMPLE DATA
• • •:
Rl IN NO Mo D.iv Y. -,<-,ri
Exr
VOL "'
NJ
AM f
GC PARAMETERS
^ ^*GE
INJ
INI r
iNtT rnor,
F NAL '- NAL
j I
|
• DETECTOR PARAMETERS
• '
•
^
•
1
J
•
n
J
I
«
n
«
(
A r IN
SENS
RANGE
TEMP
C
MASS
RANC.E
SI AN
TIME
EM
VOt. TAGE
COMMENTS AND CON HTION CHANGES
*
ANALYST
-------
19
temperature, and oven temperature in the boxes labeled "PHASE," "INJ °C,"
"INIT °C," respectively. In the section titled "detector parameters" enter the
detector type (E.G.), attenuation, and detector temperature in the boxes labeled
"TYPE," "ATTN," and "TEMP °C," respectively. The analyst's initials are entered
in the "ANALYST" box.
It is not necessary to enter the date on every line of the GC logbook,
particularly if the date is the same for all the run numbers. A straight line may be
drawn down the date section. The same is true for the column number, phase,
injection temperature, oven temperature, detector type, attenuation, detector
temperature, and analyst's sections if there are no changes for these entries.
However, the sample number and run number which will be different for each
injection, must be entered each time. If any entry errors are made, draw one
line through the mistake and correct it, also date and initial the correction. Do
not erase, white-out, or obliterate any faulty entries.
Gas Chromatograms and Other Raw Data
All chromatograms and other similar printouts are to be labeled with the
NEIC sample number, dilution factor, run number, date, and analyst name
[Figure VI-5]. If an error is in need of correction, the previously described
procedure is to be used.
DATA REVIEW
Achieved results for each set or project will be reverified by the analyst
once all calculations are completed. All chromatograms will be inspected to
assure initial correct interpretation and identification. All notebook entries and
benchsheets will also be double-checked by the original analyst to affirm proper
entries identification, completeness, and calculations.
The senior analyst or supervisor will periodically perform an in-depth review of
routine projects (at least once per quarter) and review all difficult and/or priority
projects, as identified by the program supervisor. Reanalyses will be
undertaken, if necessary, and any corrections and/or clarifications will be
properly explained and identified in the data file. The Program Supervisor will
-------
Figure VI-5
CHROMATOGRAM
S-
i. t,
-------
21
provide final resolution or explanation for all analytical differences or
irresolvable problems.
Recordkeeping
The senior PCB chemist will maintain the upkeep of the PCB files. Once
analyses have been completed, the entire file is given to the senior PCB
chemist. The senior PCB chemist logs all the required information into the PC
program "Mushroom" and places the file in the PCB filing cabinet.
The analyst will report the analytical results to the senior PCB chemist
and to the Branch Chief. The analytical report will be double-checked by the
original analyst to affirm that proper entries such as Aroclor identification,
concentration or amount, and identification of sample have been made. The
analytical report format is to be followed. The analytical report is to be given to
the senior PCB chemist for review. The senior PCB chemist is to make
revisions and/or corrections, as necessary. The Program Supervisor will
provide final resolution for all irresolvable problems. The analytical results are
to be reported to the Branch Chief in a memorandum [Figure VI-6].
The Program Supervisor will report the analytical results to the
appropriate regional or state office. The memorandum format will be followed
[Figure VI-7]. Any problems with the samples such as an incompletely filled out
seal or tag, difference in sample numbers between the seal and the chain-of-
custody record etc., is to be noted in this report.
The original analyst will sign the analytical report and the Branch Chief
will sign the cover report. The original analyst will ensure that copies of the
chain-of-custody record, the original analytical report, and original cover report
are sent to ttie appropriate regional or state office. Also, the original analyst will
ensure that copies of both reports are kept in the project file and that the
Regional Counsel gets a copy of the cover report.
-------
REPCR1
3uL)JL'_ i'. 'es j .'_3 . '. •'. i 111 n . , . ^ 3 : :"
S-'UWI: Ariuro t-'a :<-• 'i,ir(y.r;, ' /'* '
10: Uean f ill i i
un November ij[,i901 c i yu r-i!np LOG were received under
official cugi.O'ly ~eal3 r "•!• ^^^H^HV ^nU i lie i r
Atialy^i^ was ipqueniocl Tor polvcnior itvated biplienyls
(PCBS) .
Two of (.lie Gajiipier, contained detecuable levels ot PCDs.
The results arc given below:
Sample
ConcentraL ion
66 ug/g
Nl)
Nl)
6 ug/g
NU
Ma]<>r Aroclor(s)
1260
1254
Type of
S am pis
Oil
Oil
Oil
Oi I
Oil
NO- None Ulected
Tli«> deteceiou limit for (-.lie oil samples was 5 uq/g.
Tills high clotecLion limit was due to interferences.
The oil samples were diluted with hexane whicli was
cleaned with sulCuric acid and analyzed by electron-capture
gas chromatography.
AJI EPA QiiallLy Control "sample was analyzed, in
duplicate, along with the sajnples and the results were
wittilu the acceptable limits.
TVn oil container blank was not received along with the
samples. A reagent blank was analyzed along with the samples
and It did not contain any significant interferences.
sample number IHHP was spiked in duplicate with 46
ug/g of Aroclor IPS-t and the recoveries wpre 7 it and 7H.
This low pet cent recovery is due matrix effects.
-------
VI-7
COVER REPORT
DENVER COLORADO 80225
•Jilf November 28,1988
SUnjhCT: Results oC l'o Ivcli lo r i Mated Diphenyl Analyses
FKUM:
TO:
r. Hill, ciue
Pesticides 4 Toxic .Subsi.ances Drancti
Larry Miller, Chief
Toxics f. Pesticides Drnuch, Region III
Attached is the analytical report for the determination of
polychlor inai.ed biphenyls (I'CDs) in samples taken by your
office in connection with an official investigation at the
following site:
Tn summary, two of the samples contained detectable
• levels of PCDs.
Please advise if you have any questions regarding these
analyses and when we may dispose of the remainder of the
samples.
Attachment
cc: Bruce M. Diamond, Regional council, EPA - Region III
David M. Darto .Environmental Scientist,EPA,Region III
(w/attaclunents)
-------
2-1
VII. INSTRUMENTATION
The following describes the type, configuration, maintenance, and
calibration required for the gas chromatographs and balance used in the PCB
analytical program. All maintenance, servicing, and external calibrations are
recorded in the appropriate logbook.
GAS CHROMATOGRAPHS
1. Hewlett-Packard 5840A Gas Chromatograph (used for Screening):
Equipped for packed columns with an on-column injection port, and a
63Ni electron-capture detector (ECD). This GC is also equipped with an
HP 7671A autosampler and a 5840A GC series terminal.
Maintenance and Servicing: Preventive maintenance includes changing
the injection port septa once monthly, more regularly if necessary. The
drying tube is changed after three tanks of carrier gas have been used.
The ECD is cleaned when the background current reaches 1,000 ma and
is not reduced after overnight thermal cleaning. If necessary, the detector
is removed from the GC and returned to Hewlett-Packard for
reconditioning. Other routine maintenance of the GC includes cleaning
the injection port once every 3 months and replacing the glass wool on
the column as it becomes necessary.
Calibration
The instrument is calibrated against specific PCB mixtures of interest that
are prepared fresh daily according to the PCB method [Appendix B].
Response concentration should be within ±20% of the previously
achieved value or corrective action is to be taken.
2. Hewlett-Packard 5880A Gas Chromatooraph (used for quantitation and
screening): Equipped for packed columns (dual) with on-column
injection ports and with two 63Ni electron-capture detectors. This GC is
also equipped with dual 7673A autosamplers and dual 5S80A series GC
terminals.
-------
25
Maintenance and Servicing: Preventive maintenance for this instrument
is the same as that outlined above.
Calibration: Calibration of this gas chromatograph is the same as
described above.
3. Hewlett-Packard 5890A Gas Chromatograph (used for quantitation):
Equipped for packed columns (dual) with on-column injection ports and
with two 63Ni electron-capture detectors. This GC is also equipped with
dual 7673A autosamplers and with two HP 3396A integrators.
Maintenance and Servicing: Preventive maintenance for this instrument
is the same as stated above.
4. Hewlett-Packard 5890A Gas Chromatograph (used for quantitation and
screening): Equipped for packed columns (dual) with on-column
injection ports and with two 63Ni electron-capture detectors. This GC is
also equipped with two 7673A autosamplers and with one 3392A
integrator.
Maintenance and Servicing: Preventive maintenance and servicing for
this instrument is the same as stated above.
BALANCE
1. Mettler AE 160 top loading balance (calibrated once every 3 months
against Class S weights.) The weights that are weighed are: O.IOOOg,
O.SOOOg, LOOOOg, and 2.0000 g. These weighings are performed
three (3) times each and their weights are recorded on the Mettler
logbook. The recorded weights should be within ± 0.0001 g of the true
weight of the Class S weights.
Maintenance and Servicing: The balance is serviced once a year by an
independent contractor.
-------
26
OTHER EQUIPMENT
1. Braun-Sonic 1510 sonicator: Maintenance and servicing is performed
according to the owner's manual.
2. lEC-CS-Centrifuge: Maintenance and servicing is performed according
to owner's manual.
3. Drummond Pipets (100uL and 50 uL capacity): The pipets are
calibrated once every 3 months. The pipets are calibrated by weighing
water on the Mettler balance. The volumes of water that are weighed
with the 100 (iL pipet are: 10 u,L, 25 |u.L 50 JJ.L, and 100 (J.L. These
weighings are performed three (3) times each and the weights and
volumes are recorded in the Drummond pipet (100 \iL) logbook. The
volumes of water that are weighed with the 50 fiL pipet are: 5 (iL,
10 (iL, 25 pi, and 50 jj.L These weighings are performed three (3)
times each and the weights and volumes are recorded in the Drummond
pipet (50 jiL) logbook. The recorded weights, for both pipets, should be
within ± 0.0001 g of each other or corrective action is to be taken.
4. Brinkmann Digital Dispensette (2 to 10 mL capacity): The pipet is
calibrated once every 3 months. The calibration is performed by
weighing known volumes of water on the Mettler balance. The volumes
that are weighed are: 2 mL, 4 mL, 6 mL, 9 mL, and 10 mL. These
weighings are performed three (3) times each and the weights and
volumes are recorded on the Brinkmann Digital Dispensette logbook.
The recorded weights should be within ± 0.0001 g of each other or
corrective action is to be taken.
REAGENTS/SOLVENTS
1. Su If uric acid: ACS grade
2. Hexane, acetone, isooctane, methylene chloride, and diethyl ether:
Pesticide grade
3. Sodium sulfate: ACS grade, dry at 120 °C for 3 hours prior to use.
4. Aluminum oxide: Alumina-Woelm Super I, or equivalent.
-------
27
SOURCES
The primary source of PCB mixtures for use as reference standards shall
be the EPA Repository at Research Triangle Park (RTP). Aroclor standards will
be ordered as needed, using the designated ordering form [Figure VIII-1]. The
Repository address is:
P. Terry Bundy
U.S. Environmental Protection Agency
Pesticides and Industrial Chemicals Repository (MD-8)
Research Triangle Park, North Carolina 27709
Reference standards may also be ordered from the RTP Repository by
telephone (FTS-545-2690) in emergency situations.
Aroclor reference standards from other sources should not be used
unless the standards are unavailable from RTP or specific instructions are
provided by the supervisor to do otherwise.
Reference standards for individual PCB congeners are currently
available only from commercial sources, particularly those for monochloro-,
dichloro-, and decachlorobiphenyl, the three that are most likely to be
encountered. The best available single source is:
Ultra Scientific, Inc.,
1 Main Street
Hope, Rhode Island 02831
(401) 828-9400.
INVENTORY
An inventory will be maintained that documents the receipt of each
Aroclor and PCB congener reference standard. This inventory will be kept
either in a 3 X 5 card file and/or PC data system. The sample custodian will be
responsible for logging in standards under the direction of the senior chemist.
The information to be recorded for each standard includes:
-------
VI11-1
ORDER FORM
REQUEST FOR REFERENCE STANDARDS
MA.f
3 '•»'-/ 3.,,-ev. NSi
„ 5 : -'" '-^ — e^tai 3""9c* cr
3ss-.c cas 4 rdLSf 31 C.~9~" C3
V3-3)
-SA
cai Assistance- 9'9) 5-i:-395:, (~5) 529-395:
i.-rerge-c us: ',"021 798-2590. ',~Si 343-2690
'=rne'gerc:es: ',9'9) 336-0639
T«iex(T,VX): 5IO-927-'300
Oa:e ^eaue _
3ate of Shiorrent
Laoorator/ C3oa Nurrcsr
Request Numo«r
Verified
THIS3LOCX =OR AGHNCY JScGNL-
State
sUGIBIUTY (REQUIRED): H EPA Q FDA CUSDA ~IR-4 Q Other Federal Agency
C Regional/County Government C Municipal Government
C Supplying Manufacturer ^ exempt Laboratory QSuperfuna Laoorator/
The following reference standards are required for our program:
Index
Cod*
Mumoer
Compound
(Index Name)
Index
Code
Number
Compound
(Index Name)
'«««comot«t»OTii form in fuC«UWTtN« 0« TYUfW name ina address. UM Mac* ink if po»aM. Use back of Weei to comoiett list if necessary
Name and address of laboratory:
MPORTANT:
n*ai*> do not request mor* than on* (1) sMieto of any on* compound durinej any «ta namtt BenoeV. Many (iiqn pumy. jnaiyticai-ijria*
comoounds ar* xarce and noensn* to renne. ftatt triat tne luooiy or many r*fer*nc* it*nd*rd comoounca is duit* limited ana mertror* amain
. , ..
of tn«M m«»n«ii will b« «wnmm«t l*n man tn« former too mq u». All n>nn 204 mq tmountt.
"«na ritum ATONCt tit* acxnowiMamtmearddl *nciotM wicti your iriiomcnt. On* card n induded wi» lacr) oarctt. rhn*cards orovid* :rt
MI* evidence of wiiom*m d«iv«ry. A tracer mun B* maiwd arter 30 days, to OIWM n«e us reduce cosdy paoerwom.
Occasionally a acme of liquid material may aooewr emoty. This occurs wrien rnqnoiscosny compounds collect in tn* »*ts« cao. ar wnen volatii*
com sounds disoers*. )«fore concluding you were <*m tn tmoty venei. allow tn* vi* to tn uonqm for I noun: men remove cao and t«amin*.
Suggestion! for ower eomoounds to o* added to m» Seoository inventory are always welcomed. P'«as* UM tn* reven* tide.
-------
29
Identification of Aroclor or PCB congener
Source
Date of receipt
Code or batch number
Purity
Storage location
If more than one standard is received for the same batch or lot, these are further
identified with "-A," "-B," etc.
When a reference standard is depleted or otherwise taken out of use, the
date and initials will also be recorded by the analyst or staff member who last
used the material and a line drawn through the inventory entry or an
appropriate code entered into the data system.
STANDARD PREPARATION
PCB reference standards are prepared for use, as specified in the NEIC
PCB analytical method [Appendix A]. In summary, the stock, intermediate, and
working standards are prepared as follows:
Stock:
Prepare at least annually in isooctane
Store in refrigerator in 40 ml VOA vial
All Aroclors and PCB isomers = 1 mg/mL
Intermediate:
Prepare at least monthly, diluted with isooctane
Store in refrigerator in 40 ml_ VOA vial
Aroclors 1254, 1260, and PCB isomers = 5 ng/mL
Other Aroclors = 2.5 ng/ml_
-------
30
Working:
Prepare daily or as needed, diluted with hexane
Store at room temperature in locked cabinet
Aroclor 1242 and 1248 = 0.25 (ig/mL
Aroclor 1254 and 1260 = 0.50 ng/ml_
Other PCB isomers = 0.25 (ig/mL
Any of the three levels of standards are to be freshly prepared if there is
any indication of solvent evaporation, degradation, contamination, or other
problem.
All prepared standards are to be labeled with PCB identity, solvent, date
prepared, initials of analyst, and appropriate notebook page reference (i.e.,
reference to intermediate preparation for working standards and reference to
stock standard preparation for intermediate standards). All stock and
intermediate standard preparations are to be documented in the laboratory
notebook and cross-referenced as necessary.
-------
31
VIII. QUALITY ASSURANCE
BACKGROUND
The quality assurance (QA) effort for the PCB analytical program at NEIC
will be consistent with the Agency's policies and procedures, and will be
specifically directed toward the generation of reliable, defensible, timely, and
state-of-the-art analytical data.
The overall QA effort will be overseen and managed by the Pesticide and
Toxic Substances Branch Chief, with day-to-day technical responsibility being
provided by the senior PCB chemist. The NEIC QA Officer will coordinate with
the Branch Chief and senior PCB chemist to assure consistency of the Branch's
QA efforts with requirements of the Agency and the Center.
The following components comprise the Branch QA PCB program, which
are further discussed in some detail:
Management Commitment: The Pesticide and Toxic Substances
Branch Chief or supervisor shall be committed to providing and
achieving a meaningful and effective quality assurance effort. The
analytical staff will also make every effort to assure that all results
are scientifically sound, defensible, timely, and produced with a
defined level of quality. Significant quality assurance and/or
analytically related problems are immediately brought to the
supervisor's attention.
Systems Evaluation: The NEIC QA Officer will conduct a systems
audit of the PCB analytical program at least annually. The results
of the evaluation will be provided to the branch Chief in writing
and a written response will be prepared within 30 days of receipt
of the systems audit report. All necessary program corrections or
additions will be instituted as soon as practicable. Systems audits
may also be periodically conducted by other Agency or contract
personnel, or others within the Center.
-------
32
Reference Sample Analyses: The Branch will participate in those
available reference or check sample programs that are consistent
with the types of samples commonly analyzed as part of the
compliance program. Results that are outside the acceptable
range will be thoroughly reviewed by appropriate staff and
reananlyzed, if necessary. Other corrective action, such as further
training or reevaluation of analytical procedures, will be
undertaken, as necessary.
All participating PCB staff in the Branch will analyze each NEIC
check sample, with review and reanalyses being undertaken, if
appropriate, as described above.
Standard Operating Procedures and Methodology: The PCB
program's day-to-day operations will be consistent with the
procedures spelled out in this manual. Any necessary deviations
will be authorized by the senior staff and be documented on the
worksheet, or elsewhere in the raw data. Specific analytical
methodology will be consistent with that given in Chapter V and in
Appendix B. If other methodology is needed for new matrices or
for otherwise uncommon samples, it shall be derived from
standard references, if possible, otherwise the new method will be
fully validated and documented.
Quality Control: Routine quality control measures will be
consistent with the Agency's recommendations as given in
Appendix E. In summary, replicate samples, replicate spiked
samples, container/reagent blanks, and reference samples will be
analyzed with each set of similar matrix to provide measures of
accuracy, precision, and system interferences. Sample set with
spike sample recoveries less than 80% and/or precision
measurements reflecting more than 20% relative percent
difference (or variance) will require reanalyses of the complete set,
unless decided otherwise for valid reasons by the senior staff. An
explanation will be provided in the report in such cases.
-------
33
Blank results that indicate apparently contaminated reagents
and/or containers will be evaluated by senior staff and corrective
steps taken, as necessary. If container contamination is evident,
the appropriate inspectional staff will be contacted immediately by
the supervisor.
An EPA stand reference soil or oil, as appropriate, will be analyzed with
each set of official compliance samples. If results are not within prescribed
limits, and the reason for deviation is not apparent, the entire batch of the matrix
set will be reanalyzed. NEIC results for the standard soil and oil will be tracked
historically and any significant and consistent bias or other noticeable
deviations will be reviewed and corrected by senior staff.
If qualitative identification is not unequivocal through the fingerprint
patterns using the two specified gas chromatographic (GC) columns, additional
appropriate confirmation steps must be taken, such mass spectrometry, infra-
red spectroscopy, or use of a third distinctively different GC column.
-------
34
IX. TRAINING
The training plan presented below is required for all new laboratory
aides, physical science technicians, and chemists who will participate in the
PCS program, either analyzing or assisting with the analysis of official PCB
samples. This plan will be somewhat flexible, depending on the prior
experience, versatility, and overall proficiency of the incumbent analyst. This
plan assumes that the analyst will be new to the field of PCB analyses;
however, he or she will possess the minimum qualifications for his or her
position classification. The training is divided into: (1) on-the-job; (2) self-
study; and (3) participation in seminars, workshops, courses, and so forth.
The following describes a minimal training plan for the new analyst
during his or her technical development. Benchmarks for full skill level are
given at the end of each section.
Laboratory Aide
Read copies of: (1) these standard operating procedures,
(2) the NEIC method for PCB analysis [Appendix C], and
(3) the Agency method for analysis of PCBs in transformer
and waste oils [Appendix D]. Read all appropriate laboratory
safety literature, as identified by the senior staff.
Participate at least three times in official receipt of samples
into the laboratory with an experienced sample custodian,
including log-in to applicable computer systems.
Observe and assist an experienced analyst at least three
times each in the preparation of oil, soil, and surface
samples.
Demonstrate proficiency in sample preparation by
independently preparing sets of oil and soil quality control
samples in triplicate for instrumental analysis by an
experienced analyst.
-------
35
Read selected articles, fact sheets, and other materials, as
identified by the senior staff.
Attend staff meetings and briefings, as appropriate, to
enhance general technical and procedural knowledge, and
Agency policies.
At the full proficiency level, the laboratory aide should be able to
independently log samples into the laboratory and prepare routine oil, soil, and
surface samples for screening and/or quantitative analyses. The laboratory
aide should also be able to perform other routine laboratory support functions,
such as dishwashing, reagent preparation, and ordering of supplies.
• Physical Science Technician
Read copies of: (1) these standard operating procedures,
(2) the NEIC method for PCB analysis [Appendix C], and
(3) the Agency method for analysis of PCBs in transformer
and waste oils [Appendix D]. Read all appropriate
laboratory safety literature, as identified by the senior staff.
Participate at least three times in official receipt of samples
into the laboratory with an experienced sample custodian,
including log-in to applicable computer systems.
Observe and assist an experienced analyst at least one
time in the preparation and gas chromatographic
determination of oil, soil, and surface samples.
Demonstrate proficiency and reliability in sample
preparation and chromatographic determination by
independently preparing sets of oil and soil reference
materials in triplicate. Achieved results should be within the
prescribed limits at the 95% confidence levels.
-------
36
Prepare at least three PCB reports under the immediate
direction of the senior staff, or until proficiency is achieved.
Read selected segments of the PCB regulations, including
those related to the basic PCB control rule (40 CFR
Part 761), particularly the PCB spill clean-up policy rule
(40 CFR Part 761, Subpart G).
Read other selected articles, fact sheets, and other
materials, as identified by the senior staff.
Attend staff meetings, briefings, seminars and conferences,
as appropriate, to enhance technical and procedural
knowledge, and awareness of Agency policies.
At the full proficiency level, the GS-7 physical science technician should
be capable of independently preparing and analyzing routine samples for PCB
content, including report preparation. The technician must be able to readily
detect when interferences or other difficulties are encountered and resolve
minor problems independently and advise senior staff with respect to resolution
of more difficult situations.
• Chemist:
Achieve a working familiarity with: (1) these standard
operating procedures, (2) the NEIC method for PCB
analysis [Appendix C], and (3) the Agency method for
analysis of PCBs in transformer and waste oils
[Appendix D].
Participate at least three times in official receipt of samples
into the laboratory with an experienced sample custodian,
including log-in to applicable computer systems.
-------
37
Observe and assist an experienced analyst at least one
time in the preparation and gas chromatographic
determination of oil, soil, and surface samples.
Demonstrate proficiency and reliability in sample prepara-
tion and chromatographic determination by independently
preparing sets of oil and soil reference materials in
triplicate. Achieved results should be within the prescribed
limits at the 95% confidence levels.
Prepare at least three full PCS reports under the immediate
direction of other senior staff.
Read selected segments of the PCB regulations, including
those related to the basic PCB control rule (40 CFR
Part 761), particularly the PCB spill clean-up policy rule,
(40 CFR Part 761, Subpart G).
Read other selected articles, fact sheets, manuals, and
other materials related to PCBs and their analyses.
Give presentations at staff meetings, briefings, seminars,
and conferences, as appropriate, to advance the state-of-
the-art and to improve procedures and the overall PCB
enforcement program.
At the full proficiency level, the GS-11 chemist should be capable of
independently preparing and analyzing the more complex types of samples for
PCB content, including data evaluation and report preparation. The chemist
must be able to readily detect when interferences or other difficulties are
encountered and resolve most problems independently.
-------
REFERENCES
1. National Enforcement Investigations Center, "NEIC Policies and
Procedures Manual" (Revised May 1986), Denver, Colorado, U.S. EPA,
EPA-330/9-78-001-R
2. Pesticides and Toxic Substances Enforcement Division, March 1981,
"Toxic Substances Control Act Inspection Manual," Volumes I and II,
Washington, D.C., U.S. EPA
3. Federal Code of Regulations, Volume 40 Part 761, Subpart G, "PCB Spill
Cleanup Policy" (also Federal Register, April 2, 1987, p. 10705)
4. National Enforcement Investigations Center, 1987, "Multi-Media
Compliance Audit Procedures," Denver, Colorado, EPA-330/87-001-R
5. Environmental Protection Agency, 1985, "Verification of PCB Spill Cleanup
by Sampling and Analysis," Washington, D.C.; EPA-560/5-85-026
6. Food and Drug Administration, 1968 (updated and revised), "Pesticide
Analytical Manual, Second Edition, Volumes I and II, U.S. Department of
Health, Education, and Welfare
7. Federal Code of Regulations, Volume 40, Part 136, "Guidelines
Establishing Test Procedures for the Analysis of Pollutants Under the
Clean Water Act, Method 608," (also Federal Register, October 26, 1984,
p. 89)
8. Analytical Chemistry 5JL 594 (1982), Lewis, R.G. and Johnson, M.D.,
"Modification and Evaluation of a High-Volume Air Sample for Pesticides
and Semivolatile Industrial Organic Chemicals"
9. National Institute for Occupational Health and Safety, April 1977, NIOSH
Manual of Analytical Methods, Second Ed., Taylor, D.G. Ed. U.S.
Department of Health, Education, and Welfare, Public Health Service,
Cincinnati, Ohio
10. Analytical Chemistry 54. 310 (1982), Lewis, R.G. and MacLeod, K.E.,
"Portable Samplef for Pesticides and Semivolatile Industrial Organic
Chemicals in Air
11. Chemosphere^ 12, 499 (1984), Bankman, E. et al, "Determination of Low
Levels of Chlorinated Biphenyl Impurities in Pigments"
12. Office of Toxic Substances, U.S. EPA, 1985, "Analytical Method: The
Analysis of By-Products Chlorinated Biphenyls in Commercial Products
and product Wastes, Revision 2," EPA 560/5-85-010
-------
REFERENCES (cont.)
13. Office of Solid Waste, 1986, U.S. EPA, "Test Methods for Evaluating Solid
Waste - Physical Chemical Methods," Third Edition
14. "Analytical Chemistry of PCBs," 1986, Erickson, M.D., Butterworth
Publishers, Boston
-------
APPENDICES
A MEMORANDUM OF UNDERSTANDING
B NEIC SAMPLING GUIDANCE
C NEIC ANALYTICAL METHOD
D EPA ANALYTICAL METHOD
E NEIC QUALITY ASSURANCE PROJECT PLAN
F EPA QUALITY CONTROL GUIDELINES
-------
I
I
I
i
I
I
I
I
I
I
I
I
I
I
I
I
I
I
I
APPENDIX A
MEMORANDUM OF UNDERSTANDING
-------
EN'.-IRCNMEN.-L PROTECTION AGENCY
OFFICE OF ENFORCEMENT
NATiON-L ENFORCEMENT INVESTIGATIONS CENTER
BUILDING 53 SOX ..'5:27 DENVER -EDE3AI CENTER
DENVER. COLORADO 80225
November 16, 1987
SUBJECT: Polychlorinated Biphenyl (PCB) Analyses by NEIC
FROM: Or. Theodore 0. Meiggs '/ / /I/ U '- "j^?
Assistant Director, .Laboratory Seryioes
TO: Addressees (See Below)
In FY 1988, the National Fnforcenent Investigations Center (NEIC)
will continue to analyze PCB compliance samples for the regional toxics
compliance programs. These analyses will be conducted under the terms
of an Office of Compliance Monitoring/NEIC Memorandum of Understanding.
Regional sample distribution, guidelines for submission of samples, and
a description of the management of this program •-•";: included in the
attached document, "PCB Compliance Support by NEIC".
Please contact Dean Hill of Tiy staff at FTS 776-8138, if you have
any questions relating to this progran, and/or if you anticipate needing
PCB analytical support during FY '88.
Attachment
Addressees: Gerald Levy, EPA Region I
Ernest Regna, EPA Region II
Larry Miller, EPA Region III
Howell K. Lucius, EPA Region [V
Phyllis Reed, EPA Region V
Norman Dyer, EPA Region VI
Leo Alderman, EPA Region VII
C. Alvin Yorke, SPA Region VIII
Richard Vaille, EPA Region IX
Anita Frankel, EPA Region X
cc: Michael Wood, OCM .
Dean Hill, NEIC
Arturo Palomares, NEIC
-------
PROCEDURES FDR PCS ANALYSIS PY NEIC
I. BACKGROUND
Under a Memorandum of Understanding between the OPTS Office of
Compliance Monitoring (OCM) and the National Enforcement Investigations
Center (NEIC), the NEIC will continue to analyze PCS compliance samples
during FY 1988. The f'JEIC will manage the day-to-day operation of this
technical support which will include the custody of samples, conducting
analyses, reporting results and providing case resolution support to the
regions as necessary. OCM will provide overall program management, which
includes the assignment of regional sample allocations, resolving ques-
tions relating to sample priorities, and ensuring that this effort meets
the needs of the national toxics compliance program.
II. SAMPLE ALLOCATION
750 PCB investigation samples (including those for quality control)
will be scheduled for analyses by the NEIC in FY 1988. The majority of
the samples, approximately 650, will be allocated for routine samples,
while approximately 100 will be targeted for emergency or otherwise
high priority situations. OCM and NEIC have established a regional
sample allocation based on the percentage of resources each region will
receive for PCB compliance activities and past requests for NEIC PCB
analytical services. The table on page 4 shows this allocation based on
the FY 1988 regional PCB inspection distribution.
Analysis of samples collected during emergency situations, or priori-
ty inspections, will take priority over any other routine samples for
that region. The region submitting priority samples should notify the
NEIC by telephone so that if delays in routine analyses are caused by the
priority sample analysis, the region can be advised.
Once a region has used its quarterly allocation, any additional
requests for sample analyses for that region must be arranged with NEIC
or OCM, as appropriate. OCM will make final decisions on over allocation
requests based on discussions with the regional offices and NEIC.
III. SUBMISSION OF SAMPLES
PCB compliance staples should be forwarded directly from the regions
to NEIC in accordance with DOT regulations and Agency chain-of-custody
procedures. Samples without proper chain-of-custody will normally not
be analyzed. Associated sample documentation including chain-of-custody
forms, sample collection forms, any other documentation relating to
the background of the sample, and a regional contact should also be
forwarded to NEIC. Any information regarding the history of the sanple,
Aroclor identification, and suspected PCB levels will be helpful to the
-------
-2-
laboratory. Suspect non-Aroclor PC3 samples should be specifically
identified as such. As mentioned above, the NEIC should be contacted by
telephone prior to sample shipment of priority samples.
Recommended sampling, shipping and custody procedures for soil, oil
and surface samples are attached. These guidelines are based on exper-
ience with a wide variety of compliance samples collected by a number
of inspectors and covering a number of matrices.
Samples and documentation should be shipped to:
Dean F. Hill
EPA-NEIC
P.O. Box 25227, Bldg. 53, DFC
Denver, CO 80225
Contact Dean Hill (FTS 776-8138) or Arturo Palcmares (FTS 776-7970)
if there are any special instructions or circumstances relating to
analyses to be performed.
IV. SAMPLE ANALYSES - QUALITY ASSURANCE
All PCB compliance samples will be analyzed in accordance with the
time frames discussed below. NEIC will analyze PCB samples using standard
analytical methods, as appropriate, for the individual sample matrices.
In order to ensure the precision and accuracy of sample analyses, NEIC
will utilize standard Agency accepted quality control procedures, as
described in the NEIC Quality Assurance Program Plan.
V. RESULTS OF ANALYSIS
It is Agency policy to notify companies of violative situations
and to initiate enforcement actions in a timely manner. In order to
accomplish this, a target has been established for the analysis and re-
porting of results for routine samples within 45 calendar days from
NEIC's receipt of the sanoles. If the 45 day tareef cannot be met, NEIC
will notify the affected regions. Priority samples will be analyzed and
results reported to the region by phone within 15 calendar days from NEIC's
receipt of the samples. The NEIC analytical report will be according to
standard memo format; return of completed custody sheets will be on an
"on request" basis.
NEIC will report results of analysis directly to the regional
Toxics Branch Chief with a copy to the appropriate Regional Counsel.
Analytical reports will include associated quality control data needed
for qualitative and quantitative interpretation.
-------
-3-
VI. SAMPLE RETENTION
PCS compliance samples analyzed under this progran will be maintained
at NEIC until disposal notification is provided by the Regional office.
The Regional offices are to notify NEIC as soon as possible after any PCS
enforcement action is complete, so that the remaining samples may be
discarded.
VII. PROGRAM MANAGEMENT
The NEIC shall maintain a log of samples received, sample analysis
dates, dates reports of analysis were forwarded to the regions, and
samples which were discarded. The NEIC shall provide this information
to OCM in a yearly management report.
The Project Managers for this program are:
NEIC: Dean Hill, Chief
Pesticides and Toxic Substances Branch
Telephone: FTS 776-8138
OCM: Michael Wood, Chief
Compliance Branch
Telephone: FTS 382-7835
-------
-4-
TABLE A
REGIONAL PCS SAMPLE ALLOCATION
REGION
FY 1988
ALLOCATION
QUARTERLY
ALLOCATION
I
44
11
II
64
16
III
48
12
IV
64
16
V
140
35
VI
72
18
VII
160
40
VIII
40
10
IX
92
23
X
26
6
-------
APPENDIX B
NEIC SAMPLING GUIDANCE
-------
SAtPLE HANDLING PROCEDURES FDR
SOIL AWD OIL SAiPLFS FOR PCB ANALYSIS
Recommended Techniques
1. Change gloves between each
sample or more often
2. When sampling soil, use disposable
tongue depressors and, wich oils,
use disposable pastur (capillary)
pipets, if possible, making sure to
exchange between each sample. If
disposable equipment cannot be
used for some reason, then the
sampling materials should be rinsed
and wiped a minimum of 3 times with
acetone and laboratory tissues before
taking the next sample.
3. Representative sampling should be
attempted whenever soil or oil are
taken. At least 30 ml (40 ml vial
filled 3/4 full) should he taken for
an oil sample and 1/2 Ib. (8 oz. jar)
for a soil sample. Non-uniform liquids
(sediment, layering, etc.) should be
sampled in duplicate.
4. Field blanks (controls) should be sent
with the project for each type of matrix
in the project. Field blanks should be
prepared at the sample site after the
matrix has been sampled.
5. Permanent, waterproof ink must be used
if at all possible, on all written
materials associated with the sample,
including chain-of-custody and sample
label.
6. If a written error occurs, on a document
or label, draw a single line through the
error,then initial and date the error.
Reason
- minimizes cross contamination
of samples
- protects investigator from
contact exposure
- minimizes cross contamination
of sanples
provides for more accurate
description of contamination
at the sample site
demonstrates good sampling
technique and freedom from
cross contamination
solvents, water, etc., tend
to obliterate sanple
identification information
corrected errors on official
documents should be legible
and documented
-------
Recommended Techniques
Reason
7. Ideally, EPA custody seals should be
placed around the top of the sample
vial or a jar so as to allow the ends
of the seal to he sealed together on
one side, placing 1/2 on the glass
portion of the vial and 1/2 on the
cap of vial. Alternatively the seal
may be placed on the outside of a plastic
bag containing the vial or jar. In either
case the seal can be further secured and
protected by using a rubber band to
further enfold the seal.
3. When packaging for shipment to NEIC,
each vial or jar should be contained
in its own plastic bag (zip-lock
sandwich/ freezer bag or whirl-pak®
for 40 mL vials) , making .sure that
the top of the bag is knotted, taped,
or otherwise securely sealed. More
than enough vermiculite or Kitty-Litter™
should be added to the primary shipping
container (usually a paint can) so as to
insure that no sample canes into contact
with other samples or the sides of the
primary shipping container. No glass
against glass.
9. All sample numbers should he recorded
on the sample vial or jar and the
official seal and these should be
double-checked for consistency with
chain-of-custody statement.
10. Location and identification of sampling
site should be consistent on all
chain-of-custody and other investigation
records.
11. Mixed matrix samples should be noted
on chain-of-custody to indicate
possibility of multiple results for
the sane sample, (i.e. Oil/Soil;
Soil/ Water; Oil/Water)
12. Recommend not including non-representa-
tive materials in soil samples, or as
samples in thenselves, such -as large
rocks, nails, wire, etc.
this will insure that the
official seal will stay
securely on the sample during
its transport to the laboratory
insures that each sample arrives
at NEIC completely intact
plastic bag allows additional
protection of the packing
(vermiculite or Kitty-Litter")
material becoming contaminated
if container should become
broken
obvious time delays may occur
not to mention potential legal'
ramifications
avoids confusion during processing
of project
avoids confusion regarding sample
data
problems in data interpretation
as concentrations and/or surface
areas are difficult to establish
-------
-3-
Reconmended Techniques
Reason
D. Estimated or suspected Levels of
PCB (if known) should be included
in project information under comments
on chain-of-custodv.
- allows a more rapid analysis
of sample by lab personnel
Reminder: When dealing with unknown soils/oils or other materials, always
assume that the levels of PCB's may be high and that cross-
contamination can easily occur.
-------
PCB WIPE SAMPLES
Recommended Techniques
1 . Change gloves between each sample
or more often. Forceps or tweezers
should also be thoroughly cleaned
(or exchanged) between each sample
if used to manipulate swab.
2. If tweezers or forceps are used
to assist in obtaining surface
samples, these instruments must
be rinsed, and wiped 3 or more times
with acetone (or other solvent) and
laboratory tissues, before the next
sample is taken.
3. If isooctane or other solvent is to
be used to lift PCRs from surface,
apply the isooctane sparingly to
the swab material, (just dampen
the material, do NOT soak it). Do
not use solvent LFTree liquid is
apparent on the surface to lie sampled
and a wt./wt. concentration rather
than a surface area concentration is
desired.
4. Field blanks containing the identical
material and solvent used as the wipe
samples should be submitted to the
laboratory with each project. Field
blanks should be prepared at the
sampling site after other samples
have been taken.
5. Permanent, water proof ink must be used
if at all possible, on all written
materials associated with the sample,
including chain-of-custody and sample
label.
6. If a written error occurs on a docu-
ment or label, a single line should
be drawn through the error, along with
recorder's initials and date.
Reason
- minimizes cross contanination
of samples
- protects investigator from
contact exposure
- minimizes cross contamination
of samples.
- minimizes dilution and potential
losses of PCBs at contact
surface when taking the wipe
demonstrates good sampling
technique and freedom from
cross contanination
solvents, water, etc. tend to
obliterate needed identification
information,
without this identification a
sample may be rendered invalid
for enforcement purposes
corrected errors on official
document should be legible
and documented.
-------
-2-
Recommended Techniques
Reason
7. The surface area if measured, should
be specified (cra^) on Che custody sheet
or other documentation sent with the
sample.
3. Ideally, EPA custody seals should be
placed around the top of the sanple
vial or jar so as to allow the ends of
the seal to be sealed together on one
side, placing 1/2 on the glass portion
of the vial and 1/2 on the cap of the
vial. Alternatively the seal may be
placed on the outside of a plastic bag
containing the vial or jar. In either
case the seal can be frirther secured
and protected by using a rubber band
to further enfold the seal.
9. When packaging for shipment to NfEIC,
each vial should be container] in its
own plastic bag (zip-lock sandwich
freezer bag or whirl-pak® for 40 mL
vials), making sure that the top of
the bag is knotted or taped or other-
wise securly sealed. More than enough
vermiculite or Kitty-Litter" should be
added to the primary shipping container
(usually a paint can) so as to insure
that no sanple comes into contact with
other samples or the sides of the
primary shipping container. No glass
against glass!
10. All sample numbers on the sample vial
and the official seal should be double-
checked for consistency with chain-of-
custody record prior to shipment.
this will allow calculation
of surface concentration and,
inclusion on reports
this will ensure that the
official seal will stay
securely on the sample during
its transport to the labora-
tory-
insures that each sample
arrives at MEIC completely
intact
plastic bag allows additional
protection of the packing
(vermiculite or Kitty-Litter)
material becoming contaminated
if a sample container should
become broken
- mislabeling may occur
Reminder
Most surface areas on which PCRs exist, tend to be in very high concentration.
Extreme care is necessary to insure that cross-contamination of sanples does
not occur.
-------
APPENDIX C
NEIC ANALYTICAL METHOD
-------
THE DETERMINATION OF POLYCHLORINATED BIPHENYL3
IN OIL, SOIL AND SURFACE SAMPLES
SCOPE
1.1 This method describes the procedure used for the determinate :•
polychlorinated biphenyls (PCBs) in oils, soils and SLr'ace
samples at the National Enforcement Investigations Carter
(NEIC). It is intended primarily for use during the analysis of
samples collected to verify compliance with the various Agency
PCB regulations.1 *3 This method has been adapted from the Test
Method 'EPA-600/4-81-045", Tha Determination of Polvchlori-
nated Biohenvls in Transformer Fluids and Waste Oils.1* The NEIC
updated method also addresses soil and surface samples,9'° "
as well as oils and provides conformance with NEIC's technical
capability.
1.2 This gas chromatography (GC) method is applicable to the
determination of PCBs in commercial mixtures (known as
Aroclors), contaminated electrical, hydraulic, and heat exchanger
fluids, waste oils, soils, soil-like materials, surface samples, and
other related matrices. The techniques described in this method
may also be utilized to analyze specific PCB congeners and/or
various other PCB mixtures if the PCB components have been
previously identified by other methods or through knowledge of the
sample history.
1.3 The detection limits of this method are dependent on the
complexity of the sample matrix and the ability of the analyst to
properly maintain the analytical system. Using carefully optimized
instruments, the procedure's calibration range is 0.1 to 0.5 jig/mL
total PCBs. Samples above this level are diluted to fall within the
range of 0.1 to 0.5 ng/mL PCBs. The method detection limit for
Aroclors 1016, 1242,1248, 1254 and 1260 is typically 1.0
-------
' -i Prior to determination of official samples, eacn ana^s; ~^~-
achieve suitable results upon analyses of National Bureau :•
Standards (NBS), standard reference materials (SRMs) or ctrer
equivalent test samples.
1.5 Where trade names or specific products are noted in this metnca.
equivalent apparatus and chemical reagents may be '-sec.
Mention of trade names or specific products is for the assistance of
the user and does not constitute endorsement by the (J.S
Environmental Protection Agency.
2. SUMMARY
2.1 An appropriate portion of the sample is extracted and/or diluted
into hexane and screened by gas chromatography equipped with
an electron-capture detector (ECD) or a Hall electrolytic
conductivity detector (HECO) to determine the approximate
concentration and type of PCB mixture(s) present.
2.2 Based on the screening result, the sample is then diluted or
reprepared such that the concentration of each PCB mixture
present is within the target range of the GC system (0.1 through
0.5
2.3 The diluted or reprepared sample is then introduced into a second
gas chromatographic system for final PCB detection and
measurement, using an electron capture (EC) detector. Several
cleanup techniques are provided for samples that contain
apparent interferences. Interferences may still occur in some
samples even after exhaustive cleanup attempts.
2.4 The concentration of PCBs is calculated using a modified Webb
and McCall procedure,55 using known Aroclor or PCB reference
standards. The analysis time, not including data reduction and
quality control, is approximately 1 hour per sample.
-------
2 5 Quality control measures include at least one set or -ec :a:e
recovery and blank analyses with each batch of samples of s.m ar
matrix. Standard reference materials are also anaiyzec
periodically and PCB isomer or mixture identification is confirmee
using alternate gas chromatographic columns or, if necessary,
standard mass spectrometry techniques.
3. INTERFERENCES
3.1 Qualitative misidentification is a potential problem in GC analysis.
The analyst must be skilled in recognizing chromatograph;c
patterns of the different commercial PCB mixtures. The analyst
should also be alert to the possibility of Aroclor mixtures,
"weathered" PCB patterns and non-Aroclor derived PCBs.
i
3.2 Solvents, reagents, glassware and other sample processing
equipment may yield discrete artifacts and/or elevated baselines,
causing misinterpretation of gas chromatograms. All of these
materials must be demonstrated to be free from interferences
under the conditions of the analysis.
3.3 There is also the potential of encountering interferences in any
matrix type, which may pose some difficulty in obtaining accurate
and precise measurements of PCBs. Additional sample cleanup
procedures may be required. It may be necessary to report
elevated detection limits for some intractable samples.
3.4 Chlorinated solvent and other related interferences in oils and
soils may be high and/or variable. Normal sample cleanup
procedures may not be applicable. Careful solvent evaporation
and/or gas chromatography with temperature programming
capability may be necessary.
-------
APPARATUS
4.1 Gas chromatographs - Gas chromatographs should be equ;ocec
with on-column 1/4-inch injectors. Each oven must be
-------
earner gas. N2 al 45 rnL'mm, --art speed: 05. -ecc-re-
attn.: 7.
4.3.3 HECD Screening - SPB-5 wide bore capillary CC!LJ~-.
60m x 0.75mm ID, 1.0 um film, conditioned overmgrt a:
240 °C, oven temp.: 240 °C, injector temp.: 2^0 :C
detector temp.: 240 3C, reactor temp.: 900 °C, solve-:
flow: 4 mL/min., chart speed: 0.25 cm/min, recorder a::-
2, carrier gas: Heat 10mL/min, Make-up gas at
35 mL/min.
4.3.4 ECO Quantitation - 3% OV-101 on 80/100 Supelcoport, 6'
x 1/4" column, Pyrex with silanized glass wool (or
equivalent). Conditioned overnight at 240 °C. Oven
temp.: 180 °C, injector temp.: 230 °C, detector temq.:
300 °C (340 °C), carrier gas: N2 at 45 mL/min, chart
speed: 0.5, recorder attin: 7.
4.3.5 ECD Capillary Confirmation (optional) - 1^m DB-5
capillary column, 15 meters; Oven temp.: initial temp.:
60 °C hold for 1 min., 7 °C/min. to 270 °C, hold for 15
min.; Injector: 230 °C, 1jil splitless injection; Detector
temp.: 300 °C; Carrier Gas: Heat 10 psi; Make-up Gas:
N2 at 20 mL/min.
4.4 Disposable vials -1,12 and 40 mL vials with the Teflon-lined® or
Teflon-faced silicone caps
4.5 Disposable glass pipets - 1.0, 2.0, 10.0, 25.0 mL, and pasteur
glass pipet
4.6 Micro Pipets - 10, 25, 50 and 100 nL, SMI and Drummond,
Calibrated once monthly by weighing with water at 10, 25, 50 and
Teflon is a registered trademark and will appear hereafter without <9.
-------
•i 7 Sample containers - 40 ml screw cap volatile orgar.c a-a ,s s
(VOA) bottles with Teflon-faced cap liners
•i 3 Chromatographic column - Chromaflex, 400 mm long x 8 r^ i r
(Kontes K-420540-9011 or equivalent)
4.9 Graduated cylinders • 100 and 250 ml
4.10 Balance • Analytical, capable of weighing up to 99 g wit- a
sensitivity of ±0.0001 g
4.11 Concentrator tube - 10 ml and 25 ml graduated (Kontes
K-570050-1025 or equivalent). Calibration must be verified.
Ground glass 19/22 stopper is used to prevent evaporation of
solvent.
4.12 Erlenmeyer flasks - 125 ml and 250 mL ground glass, TS 24/40.
4.13 Separately funnels - 250 ml with Teflon stopcock
4.14 Sieves 2 mm mesh (Number 10)
4.15 100-watt sonic probe, Braun-sonic model 1510 or equivalent
4.16 Centrifuge (1500 R.P.M.)
4.17 Aluminium foil-commercial grade
5. REAGENTS AND MATERIALS
5.1 Reagent Safety Precautions4
5.1.1 The acute and chronic toxicity of each reagent used in this
method has not been precisely defined; however, each
chemical compound should be treated as a potential
health hazard. From this viewpoint, exposure to these
chemicals must be reduced to the lowest possible level.
-------
5.1.2 PCBs have been classified as suspectaa ~ar~a =~
carcinogens. Primary standards of these :c<:
compounds are to be prepared in a well-vent;lated ~:cc
using proper personal protective wear.
5.1.3 Dietnyl ether should be monitored regularly to detern.re
the peroxide content. Under no circumstances shoo.a
diethyl ether be used with a peroxide content in excess of
50 ppm as an explosion could result. Peroxide test sires
manufactured by EM Laboratories (available from
Scientific Products Company, catalogue number P1126-3
and other suppliers) are recommended for testing
peroxides. Procedures for removal of peroxides from
diethyl ether are included in the instructions supplied with
the peroxide test kit.
5.2 Hexane, isooctane, methylene chloride, acetone, propanol-1 and
diethyl ether of pesticide grade
5.3 Sodium sulfate A.C.S., dry at 120° C for 3 hours.
5.4 Alumina (Alumina Woelm-Super I, or equivalent)
5.5 Sulfuric acid A.C.S.
5.6 Glass wool-filtering grade
5.7 NBS reference samples • Certified samples of PCBs in oil
matrices, available from U.S. Department of Commerce, National
Bureau of Standards, Building 222, Room B-311, Gaithersburg,
MO 20899.
5.8 EPA reference samples - Certified Quality Control Samples of
PCBs in oil and soil matrices available from U.S. EPA Office of
Research and Development, Environmental Monitoring and
Support Laboratory, Cincinnati, Ohio 45268
-------
5 3 PCS Reference Stanaarcs
5.9.1 Aroclors 1016, 1221, 1232, 1242, 1248, 1254 and "250
Primary dilutions are prepared from pure stancarcs ;•
various Aroclors obtained from: U.S. Erwironrre-'s
Protection Agency, Quality Assurance Materials 3a~-<
P.O. Box 12313, 2 Triangle Drive, Researcn Tr:a~g e
Park, NC 27709 USA.
5.9.2 Decachlorobiphenyl, 2-Chlorobiphenyl and 3-Chlorcoi-
phenyl. Obtained from UltraScientific, 1 Mam Street,
Hope, Rl 02831
5.10 Calibration Standards
i
5.10.1 Stock: 1.0 mg/mL (1000 u,g/m(_) standard - Dissolve
0.05 g of each Aroclor or individual PCS weighed to
within ±0.0001 g in a 50 ml volumetric flask. Dilute to
volume with isooctane. Store at 4 °C in 60 ml
narrow-mouth, screw-cap bottles with Teflon-lined cap.
Stock standards are stable up to 1 year if a good seal is
maintained.
5.10.2 Intermediate: 5.0 ^ig/mL standard - Pipet 50 (iL of the
1 mg/mL standard with a Micro Pipet into a 10 ml volu-
metric flask. Dilute to volume with hexane. If the seal is
maintained, this intermediate standard can be stored up to
1 month. The validity of in-house-generated intermediate
standards can be verified on a monthly basis by analyzing
NBS PCB reference samples, if necessary.
5.10.3 Working: 0.50 ng/mL standard (for Aroclors 1254 and
1260) - Pipet 1 m!_ of the 5.0 ng/mL standard into a
10 mL volumetric flask and dilute to volume of hexane.
Prepare fresh daily.
-------
5.10.4 Working: 0.25 jig/mL Standards (for Arccicrs .0'5, '22'
1232, 1242 and 1248) Pipet 0.5 ml of the 5 0 ,^g ~_
standard into a 10 ml volumetric flask and dilute :o
volume with hexane. Prepare fresh daily.
5.10.5 Limit of detection: 0.1 jig/mL standard - Pipet 1 ml of re
5.0 )ig/mL standard into a 50 ml volumetric flask. D.iLte
to volume with hexane. Prepare fresh limit of detect, c":
standard on a monthly basis. Store in a 60 ml narrow-
mouth, screw-cap bottle with Teflon-lined cap.
6. SAMPLE COLLECTION AND HANDLING
Currently all sampling is performed by non-laboratory personnel. This
section will be completed at a later date. Specific guidance can be found
in the EPA TSCA Inspection Manual7and the "Program Management"
Section (Chapter II).
7. SAMPLE PREPARATION PROCEDURE
7.1 Screening Procedure - An appropriate portion of the sample is
extracted or diluted and screened by gas chromatography
equipped with either an ECO or HECD to establish the
approximate concentration and type of PCS mixture(s) present.
7.1.1 Oil samples: Place a very small (ca. 0.1 gram, 2 or 3
drops of oil, unweighed) amount in an approximately
10 ml of hexane in a 40 ml disposable vial with
Teflon-lined cap. Treat the hexane portion with sulfuric
acid (Section 8.1). Make a 1 to 1,000 dilution with hexane
of the initial extract. Inject 2 u.1 of the hexane portion onto
aGC.
7.1.2 Soil samples: Extract 1 gram of well-mixed or sieved soil
with approximately 10 ml of hexane in a 40 mL
disposable vial. Shake the sample vigorously for 3
-------
minutes. Treat the hexane portion with suifur.c a: :
(Section 8.1). Make a 1 to 1,000 dilution witn hexare ;•
the initial extract. Inject 2 ul of the hexane portion or:c a
GC.
7.1.3 Surface samples: If large amounts of PCBs are susoectec
in these types of sample (i.e., if the wipe material appears
to be quite oily), a portion of the initial extract (Section 7 4i
should be diluted 1 to 1,000 with hexane and injected into
the GC before the initial hexane extract is analyzed. !f
there is no reason to suspect high concentration of PCBs,
the initial hexane wash is then injected directly into the
GC.
7.2 Oil Sample Quantitation Procedure
7.2.1 For samples estimated by screening to be in 0 to
100 ng/g PCB range, shake the samples vigorously, then
weigh 1.00g of the sample into a 40 ml vial. Pipet
9.0 ml of hexane and shake. Either the oil will dissolve
in the hexane, partially dissolve or not dissolve at all.
Remove the hexane from the sulfuric acid layer with a
pasteur pipet, if necessary, and transfer to another 40 mL
vial. Carefully treat the hexane portion with sulfuric acid
(Section 8.1). Make the necessary dilution, as determined
via screening. Inject 2 nL of the hexane portion into the
GC.
7.2.2 For samples estimated to be over I00ng/g range via
screening, shake the samples vigorously, then weigh
0.10 g of sample into a 40 ml vial. Add 9.9 mL of
hexane and dissolve. Carefully acid-treat this dilution
(Section 8.1). Make the necessary dilution, as deter-
mined via screening. Inject 2 u,L of the hexane portion
into the GC, equipped as described in 4.3.4.
-------
3 Soil Sampie Quantitation Procedure
7.3.1 For samples determined in the 0 to 100 u.g/g range v a
screening, examine the sample to determine if free water,
oil or tar is present. If not, completely empty the sarrc e
bottle onto a clean 2 mm sieve and force the soil thrown.
Rocks, twigs and other extraneous material are separatee
from the soil. If water, oil and/or tar is present, the s.eve
should not be used because of the difficulty in cleaning T
and potential for cross-contamination. In this case,
completely empty the sample bottle onto a sheet of
aluminum foil and manually sort through the sample with
a clean disposable, wooden tongue depressor. Remove
any rocks or extraneous matter to the degree possible.
Break up any lumps of soil and mix thoroughly. Return th,e
mixed or sieved sample to its original container. Sav^e
any rocks, leaves or other debris in a separate aluminum
foil packet.
At the same time the soil aliquot for analysis is taken, the
moisture content of the soil must be measured in order to
correct for the weight of water in the sample. Accurately
weigh about 10 g of mixed sample into a preweighed
weighing boat, let stand overnight at room temperature in
a well-ventilated hood and reweigh the dried sample the
next working day. Do not dry in an oven!
% moisture »(Wj^jy^jlOO
Wi
where: wi = original wet weight of soil
W2 « weight of soil after drying
For quantitative analysis, weigh 1.0g of well-mixed
sample into a 40 ml, disposable vial (a VOA sampling
bottle), pipet 10.0 ml of 50:50 acetone/hexane mixture
and agitate thoroughly with a 100-watt sonic probe for
2 minutes. Centrifuge the sample at 1500 RPM for
-------
2 minutes and decant the solvent into a 250 ~;_
separator/ funnel containing 100mL of water. P'pet a
second 10.0 ml of 50:50 acetone/hexane mixture to :Ke
soil and repeat the sonic extraction and centrifugaticn.
Add the second 10 ml of solvent to the ongira;
separatory funnel and gently agitate for at least
2 minutes. The acetone will be miscible with the water
and the hexane layer should separate to the top. After
removing the acetone/water, carefully drain the hexane
into a 40 mL disposable VOA vial with a Teflon-lined cap.
Acid-clean the sample (Section 8.1). Caution: There
could be traces of acetone/water present that could
violently react with the sulfuric acid. Make the necessary
dilutions, as determined via screening. Inject 2 jiL into a
GC. :
7.3.2 For samples estimated to be over the 100 u,g/g range via
screening, completely empty the sample bottle onto an
alumina foil sheet and thoroughly mix as described
above, removing leaves, rocks and debris to the degree
possible. Return the soil to the original sample bottle.
While mixing the sample, note if it is watery, oily or tarry.
Determine the moisture content aliquot on a log as
described in Section 7.3.1.
If the sample is not oily or tarry, weigh accurately 1.0 g of
the sample into a 40 ml vial, fitted with a Teflon-lined
cap. Add 10.0 ml of 50/50 acetone/hexane to the bottle
cap and place the bottle in a sonic bath for 3 minutes.
Remove 1.0 mL of clean extract and make a 10 to 1
dilution by adding 9.5 mL hexane and carefully treating
with sulfuric acid (Section 8.1). The sulfuric acid will
remove the 0.5 mL of acetone. DO NOT ATTEMPT to
clean the 50/50 acetone/hexane extract with sulfuric acid.
-------
If the sample appears to oe very oiiy or tarry, :re ?C3s /,
usually be contained in the hydrocarbon phase and ',ZZz-<
hexane can be used for the ultrasonic extraction. Acc-
clean the extract, as described in Section 8.1 and gas
chromatograph, as described in 4.3.4.
7.4 Wipe Sample Procedure
7.4.1 Place the swab container in the hood with the cao
removed to remove any sampling solvent for 4 hours and
proceed as in 7.4.2.
7.4.2 If the filter paper or glass wool is not packed too tightly into
the sample bottle, pipet into bottle 10 mL of hexane, into
the bottle and shake on a wrist-action shaker for 30
minutes. Acid-clean ca. 5 ml of the hexane and dilute
1000:1 with hexane (see Section 7.1.3) before injection.
This hexane dilution may either be concentrated, diluted,
or further cleaned up. If the wipe material was washed
with 10 mL or less of hexane, do not concentrate the
wash. If it was necessary to wash with more than 10 ml
(i.e., for a large swab volume), concentrate the extract
sufficiently to give the same detection limit as a 10 ml
wash (i.e., a 50 ml extract should be concentrated 5 to
1).
7.5 Water Sample Procedure
7.5.1 Aqueous samples will normally not contain appreciable
concentrations of PCBs, unless oil or organic solvent
(miscible or immiscible) or sediment is present. Weigh
10.0 g of well-shaken sample into a 40 ml VOA vial, add
5.00 mL of hexane, shake and decant the hexane into a
40 mL VOA vial. Add a second 5 mL portion of hexane to
the water, shake and add to the first hexane portion. Acid-
clean, if necessary (according to Section 8.1), and
-------
analyze by gas chromatography, as descricec -
Section 4.3.4.
EPA "Method 60S"5 should be employed if PCS ccncer-
trations of less than 1 jig/g are sought.
8. CLEANUP
Several tested cleanup techniques are described. Depending on the
complexity of the sample, one or all of the techniques may be required to
resolve PCBs from interferences. Sulfuric acid treatment is the most
commonly used procedure.
3.1 Sulfuric Acid Cleanup
t
8.1.1 All extracts that contain a significant amount of ECD
interfering materials are to be cleaned with concentrated
sulfuric acid before injection onto a gas chromatograph.
The three most common interferences that the acid does
not remove are mineral oil, chlorinated paraffins (which
are often found in waste oils) and technical chlordane (an
insecticide commonly found in soil samples taken in
residential areas). Extended acid treatment may partially
degrade some of the less chlorinated PCBs, such as
those found in Aroclor 1242. This may cause low
recoveries and a possible low bias for some samples,
thus, sulfuric acid should not be allowed to remain in
contact with hexane extracts or dilutions at elevated
temperatures for extended periods of time.
Transfer the 10.0 ml wipe extract, oil dilution or soil
extract to a 40 ml vial and carefully add approximately
30 ml of concentrated sulfuric acid. NEVER add sulfuric
acid to water or water miscible solvents such as acetone.
If unsure as to whether or not non-hydrocarbon solvents
are present, add several preliminary drops of
-------
concentrated sulfunc acid, prior to adding tre *'L,; 2: ~_
Shake the bottle carefully but vigorously. Centr'uga =:
1500 RPMs for 2 minutes in order to separate the ;aye'3,
then transfer the hexane layer to a separate 40 ml VGA
vial with a disposable pipette. If the hexane still corrals
visible hydrocarbons and the acid is a dark brown cc cr.
repeat the sulfunc acid cleanup until no change m cc cr r
either layer is noted.
8.2 Alumina Column Cleanup
8.2.1 Alumina will remove some hydrocarbons and other
materials from hexane extracts; however, this procedure is
somewhat difficult and time consuming. The major utility
of alumina column cleanup is the separation of PCBs frotm
chlorinated paraffins.
1.00 mL of the acid-cleaned extract is eluted through 8 g
of Woelm B Super I basic alumina in a chromaflex
column. The eluting solvent is 10% ethyl ether in hexane.
Discard the first 5 mL through the column and collect the
next 70 mL in a 250 mL Erlenmeyer flask. Concentrate,
under a gentle stream of nitrogen, down to approximately
15 mL. Transfer into a 25 mL concentrator tube. Rinse
the Erlenmeyer flask three times with 3 mL of hexane.
Concentrate down, under a gentle stream of nitrogen, to
10 mL and analyze. It should be noted that this cleanup
includes a 1:10 dilution of the extract.
Whenever a cleanup column is employed, the elution
pattern must be verified with 1.0 mL of the intermediate
analytical reference standard solution to ensure that all of
the PCBs are recovered, and that the majority of the
interfering materials are excluded. The collection pattern
may vary with each use of alumina
-------
3.3 Mercury Cleanup
8.3.1 When elemental or reduced forms of sulfur are present r,
the hexane extract (such as in natural gas condensatss;,
several drops of metallic mercury are added to the acid-
cleaned extract or dilution, and shaken vigorously A
black precipitate will form with sulfur, which is separatee
from the hexane after centrifugation. Sulfur gives a
distinctive GC pattern on the OV-101 column and :s
presence will interfere with the electron-capture signal.
Sulfur compounds may also be found in sediments and
sludge, as indicated by a strong mercaptan-like odor.
9. GAS CHRQMATOGRAPH CALIBRATION
t
^
9.1 Single Point Calibration - Prepare calibration standards for PCS
quantitation from the standard stock solutions (Section 5.9) in
hexane that are close to the unknown in composition and in
concentration, normally 0.5 ng/mL or 0.25 ng/mL for each Aroclor.
The calibration standard response should be within ±20% of the
sample, and must be within the linear ECO response range.
Linearity of response from 0.1 ug/mL to 0.5 ^g/mL (or 0.25 ng/mL)
is verified monthly or whenever the GC is serviced or the
configuration is changed.
10. QUALITY CONTROL
10.1 Sufficient quality control must be performed for each set of
samples, such that all results can be adequately evaluated and
are fully defensible. For sample sets of fewer than 20 samples,
duplicate spike, 1 duplicate sample, and 1 blank are analyzed for
each matrix. For sample sets larger than 20, duplicate spike,
1 duplicate sample, and 1 blank are performed for each set of 20
of any 1 matrix. If none of the samples in a set contain detectable
levels of PCBs, a duplicate spike is prepared and analyzed
instead of a sample replicate. If significant levels of PCBs are
found in a blank, or there is poor recovery or significant
-------
rcnreproducioility «s evident, the entire associated sarp;e set .•-
normally be repeated. Samples within ±20% of a regulator/ ~:
(e.g., 50 (ig/g) are to be analyzed in triplicate. The use of the two
different columns used for screening and quantisation will usually
suffice for positive Aroclor identification.
EPA Quality Control reference samples are to be analyzed aiong
with each set of samples. Oil quality control samples are to be
analyzed in duplicate if oil-based samples are being analyzed arc
the soil quality control sample is to be analyzed with soil or other
solid matrices. An oil quality control sample is to be analyzed if
wipe samples are present. All quality control samples are to be
analyzed in duplicate. The results of these samples must be
within the acceptable limits.
t
It should be recognized that the acceptance criteria for recoveries
and replicates should not be unrealistically strict for samples that
contain PCB concentration significantly below the TSCA
regulatory limits and that it is not realistic spike samples that
contain over about 0.1% (1000 jxg/g) PCBs. Soil spike recoveries
[Table 1] typically should vary from about 80 to 120% and
recoveries from petroleum-based products [Table 2] should range
between 90 to 110%.
Soil replicates [Table 3] should be within about ± 20% and oil
replicates [Table 4] within about ± 10% of each other. Samples
containing greater than 10% oil may vary by as much as ±20%.
11. CALCULATION OF PCB CONCENTRATION
11.1 Identify each PCB (or PCB mixture) in the sample chromatogram
by comparing the retention time of the suspect peak(s) to the
retention data gathered from standards and/or interference-free
quality control samples. The width of the relative retention time
window used for PCB identification should be based on
-------
"aoie :
RECOVERY RESULTS FOR SOIL SAMPLES
A re c. 'or
1260
1260
1242
1254
1248
1260
1242
1260
1260
1260
1260
1242
1260
1254
1260
1016
1016
1260
1260
1260
1260
1242
1260
1254
1254
1254
1254
1260
1242
1260
1260
1242
1242
1260
1260
1242
1260
1260
1260
1260
1260
1260
Spike Level
ng/g
100
10
10
200
25
50
50
50
10
100
100
10
100
10
100
50
25
100
50
100
27
5
50
50
50
50
50
100
25
50
50
100
100
50
50
50
50
100
50
100
50
100
78
89
102
120
114
145
84
119
107
107
97
88
102
109
102
106
96
96
103
99
106
100
105
114
89
100
107
105
125
107
102
110
92
95
119
100
78
125
108
112
118
120
Averace
99
109
95
102
117
99
93
116
108
99
111
93
104
121
100
94
117
104
118
119
-------
"aole 1 cent.)
efer
1260
1260
1242
1242
1242
1260
1242
1260
1242
1260
1242
1242
1260
1242
1242
1260
1242
1260
1260
1260
1260
1260
1260
1254
1260
1260
1254
1260
1260
1242
ipike Level
^g/g
50
50
50
50
50
50
100
50
50
50
50
100
50
50
100
50
50
100
50
50
50
50
50
100
50
50
50
50
50
50
Result #1
120
103
75
117
92
94
88
103
101
98
96
100
100
98
100
118
98
109
119
101
110
98
108
115
107
103
94
94
96
101
122
98
91
107
104
100
127
100
95
103
36
39
105
102
99
i
122'
104
96
103
X« Mean
S.D. * Standard Deviation
X = 104%
S.D. « 11
-------
Taoie 2
RECOVERY RESULTS FOR OIL SAMPLES
Aroclor
1254
1254
1254
1242
1242
1242
1260
1260
1260
1260
1260
1260
1260
1260
1260
1260
1260
1260
1260
1260
1260
1260
1260
1260
44 Values
Spike Le
^g/g
50
50
50
25
25
25
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
50
X » Mean
S.O. - Stan
dard Davis
Result
90
106
93
94
93
95
92
98
93
102
100
93
100
103
92
105
91
98
103
108
92
93
99
101
Result #2 Average %
101
111
99
94
99
92
100
104
97
93
99
101
96
94
101
95
109
99
99
99
X
S.D.:
96
109
99
94
95
92
99
103
99
93
99
102 i
94 '
93
100
99
109
96
99
100
• 98.2%
5.1
-------
3UFLCA7E 3ESLL73 FOR SCil SAMPLE
Result #1
,^g/g
9.4
6.0
120
27
0.17
70
1.4
8.3
18
196
3
58
31
17
56
31
93
9
9.3
4.5
3
3
70
380
260
240
4,500
2,800
2
8
820
100
10
9
26
15
36
2
15
17
13
3
Result #2
Mg/g
7.4
6.5
130
24
0.15
65
1.6
8.3
16
192
3
62
27
16
62
30
98
10
8.2
4.0
4
3
63
340
280
260
5,200
2,400
2
8
890
110
10
10
26
16
31
2
16
6
19
3
Average
8.4
6.2
120
25
0.16
67
1.5
8.3
17
194
3
60
29
16
59
30
95
9
8.7
4.2
3
3
67
360
270
250
4,800
2,600
2
8
850
100
10
9
26
15
33
2
15
6
18
3
>R.D.
23.8
8.1
8.0
11.8
12.5
7.4
13.3
0
11.8
2.1
0
6.7
13.8
6.1
10.2
3.3
5.2
10.5
12.6
11.8
28.6
0
10.4
11.1
7.4
8.0
14.4
15.4
0
0
8.2
9.5
0
10.5
0
6.5
14.9
0
6.5
15.4
5.4
0
-------
Result #1
^g/g
22
6
43
10
19
100
680
1
23
12
52 Values
Result *2
ug/g
21
7
46
1 1
20
110
680
1
30
13
Average
ng/g
21
6
44
10
19
100
680
1
29
12
%RD.
4.7
15.4
6.7
9.5
5.1
9.5
0
0
6.9
8.0
X = 8.0 %
S.D. »6.1
% R.D. * Percent Relative Difference
X*Mean
S.O. - Standard Deviation
-------
Taole 4
DUPLICATE RESULTS FOR OIL SAMPLES
Result #1 Result #2
Aroclor
1242
1242
1242
1242
1242
1242
1248
1248
1248
1254
1254
1260 1
1260
1260
1260
1260
1242, 1254, 1260
1254, 1260
1254, 1260
19 Values
Mg/g
32
158
1.4
1 1
46
16
20
34
37
548
437
,100 1,
306
121
960
69
56
710
43
^g/g
29
156
1.5
1 1
45
17 .
23
83
38
555
415
200
296
122
940
70
56
700
44
Average
w/g
31
160
1.5
1 1
46
17
22
84
38
550
430
1,200
300
120
950
70
56
710
44
X
S.D.
% R.D.
9.7
1.3
6.7
0
2.2
5.9
13.6
1.2
2.6
1.3
5.1
8.3
3.3
0.8 ;
2.1 '
1.4
0
1.4
2.3
» 3.64%
-3.68
% R.D. » Percent Relative Difference
X .Mean
S.O. - Standard
Deviation
-------
measurement of retention time variations of standarcs ever ;-e
course of a day.
11.2 If the response for any PCB peak exceeds the working range of
the system, dilute the sample with hexane to bring within the 0 ' 'o
0.5 u,g/ml_ range or 0.1 to 0.25 jig/mL, as appropriate.
11.3 If accurate measurement of a majority of peaks in the PCB eiut'C"
area of the chromatogram is complicated by the presence of
apparent interferences, either further cleanup is required or the
detection limit raised.
11.4 The method used to calculate the final concentration of PCBs m a
sample will normally be the Webb and McCall procedure5 as
modified by Sawyer.$ The external standard procedure may alsjp
be used for single, minimally modified Aroclor patterns for which
response ratios between sample and standard do not vary by
more than ± 10 of the average over all peaks for the Aroclor.
11.4.1 Webb - McCall: This method will be used under most
circumstances, particularly if a mixture of Aroclors is
apparent, or the pattern appears to be weathered or
degraded. A known amount of each Aroclor standard is
chromatographed and the area of each major GC/EC
peak is measured. A response factor is obtained by using
data developed by Sawyer6 that provided weight percent
information for each GC peak. A sample extract' is
chromatographed under the same GC conditions, and the
area of each peak in the resultant sample chromatogram
is measured and multiplied by the appropriate calculated
response factor. The sum of all measured individual
peaks is equivalent to the total Aroclor amount. This
amount is then related to the original sample weight,
volume, or surface area to obtain a concentration value.
-------
11.4.1.1 Calculations
The program "Aroclor" calculates the amount o-
concentration of PCBs on a ng or jig/g (pen
basis by utilizing a series of data inputs arc
transformations. The program is intended 'or use
on an IBM (or IBM compatible) persc-a:
computer.
The program is accessed by pressing the F8 key
(BASIC). Once BASIC has been successful !y
loaded, the words Load "Arc-dor" are typed in and
Return is pressed. Then type in Run. The Aroclor
menu should appear (Figure 1]. The corre-
sponding ordinal number for the Aroclor program
of choice is then depressed (e.g., "1" for Aroclor
1260). Next type "yes" or "no" to the inquiry as to
whether the sample is a surface (wipe) or not; this
will provide a final answer in units of ng or ng/g,
accordingly. If it assumed that the answer was
"no," the Aroclor program will be loaded and the
screen [Figure 2] will show the calculated con-
centration in \nglg.
-At this point, the data information regarding NEIC
sample number, analyst's name, sample run
number, standard run number, sample dilution
factor, concentration of standard, GC volume
(original extraction volumes) and sample weight
(dry weight for soils) are entered. Press "Enter"
after each entry. After all the data are entered, a
correction prompt will appear and any corrections
can be made after "Y" is depressed. If no
corrections are necessary, "N" is entered.
-------
Fgure 1 • Aroclor Menu
******************
******************
***
******************
******
******
******
******
******
AROCLOR.BAS
Developed By ********************
ARTURO PALOMARES ***
August 1, 1986 *********************
1
f
1
»
National
£2
/1TTT1* _™__«.N^V • a
Enforcement Investigations center
ivlronmental Protection Agency
WWW WWW
A A A A & A
W W W W W V
A A * * * A
W W W V W W
A A A A A +
]« W W V W Iv
* A A A A A
W V W if m W
*
*
PLEASE ENTER YOUR SELECTION AMD PRESS RETURN >»?
-------
F;gur0 2 - Arcclor Program
ENTER NEIC SAMPLE NUMBER? 01-001-89-01-S
ENTER NAME OF THE ANALYST? DEAN F. HILL
ENTER SAMPLE RUN NUMBER? B-lllll
*YOU WILL BE ALLOWED TO
*MAKE CORRECTIONS AFTER
*ENTERING ALL THE DATA
*CORRECTION NUMBERS:
* NEIC NUMBER
ANALYST =2
SAMPLE RUN NUMBER =3
STANDARD RUN NUMBER =4
DILUTION FACTOR =5
CONC., OF STD =6
G.C. VOLUME =7
WEIGHT OF SAMPLE =8
ENTER STANDARD RUN NUMBER? B-11112
ENTER DILUTION FACTOR? 10
ENTER CONCENTRATION OF STD(ug/mL)? .50
ENTER G.C. VOLUME(mL)? 10
ENTER WEIGHT OF SAMPLE(grans)NOTE:for soil
ANY CORRECTIONS (Y OR N)?
enter dry weight? 1.0002
-------
Fgure 3 - Peak Response for Standard
ENTER AREA OF STD PEAK(70)? 9384
*YOU WILL BE ALLOWED
*TO MAKE CORRECTIONS
*AFTER ENTERING ALL OF TH-
*DATA
ENTER
ENTER
ENTER
ENTER
ENTER
ENTER
ENTER
ENTER
ENTER
ENTER
ENTER
ENTER
ENTER
ENTER
AREA
AREA
AREA
AREA
AREA
AREA
AREA
AREA
AREA
AREA
AREA
AREA
AREA
AREA
OF
OF
OF
OF
OF
OF
OF
OF
OF
OF
OF
OF
OF
OF
STD
STD
STD
STD
STD
STD
STD
STD
STD
STD
STD
STD
STD
STD
ANY CORRECTIONS ( Y
PEAK(
PEAK(
PEAK(
PEAK(
PEAK(
PEAK(
PEAK(
PEAK(
PEAK(
PEAK(
PEAK(
PEAK(
PEAK(
PEAK(
OR N)
84)
104
117
125
146
160
174
203
232
280
332
372
448
528
??
?
)1
)«
)<
)«
)i
)<
)<
)<
)<
n
n
)<
)«
N
29389
> 9494
» 94949
' 9494
» 162674
' 8282
» 883
» 23005
' 28989
> 29292
» 9292
» 29020
» 4759
' 92832
-------
F;gur9 4 - Peak Response for Sample
*YOU WILL 3E ALLOWED
*TO MAKE CORRECTIONS
*AFTER ENTERING ALL <:
*DATA
ENTER AREA OF SAMPLE PEAK (84)?
ENTER AREA OF SAMPLE PEAK(104)?
ENTER AREA OF SAMPLE PEAK(117)?
ENTER AREA OF SAMPLE PEAKU25)?
ENTER AREA OF SAMPLE PEAKU46)?
ENTER AREA OF SAMPLE PEAK (160)?
ENTER AREA OF SAMPLE PEAK(174)?
ENTER AREA OF SAMPLE P£AK(203)?
ENTER AREA OF SAMPLE PEAK( 232)7
ENTER AREA OF SAMPLE PEAK (280)7
ENTER AREA OF SAMPLE PEAK( 332)7
ENTER AREA OF SAMPLE PEAK(372)?
ENTER AREA OF SAMPLE PEAK (448)7
ENTER AREA OF SAMPLE PEAK (5 28)7
ANY CORRECTIONS ( Y OR N)?? N
45
4789
334534
0960540
37464
8383
89494
222
9595
8484
0494
0404
74649
939
-------
Next the responses (areas or peak hearts/ c: :-•=
individual standard peaks are entered [Figure 3.'
The values in parentheses refer to the retention
time (X100) relative to p,p'-DDE. A correcr.cn
prompt will appear and corrections can oe rrace
if "Y" is entered, otherwise, "N" is depressed. T~e
sample responses are then entered in sim'ar
fashion [Figure 4]. Once all the areas are
entered, corrections can be made, as described
for the standard.
A "ready to print" query will now appear. A "yes"
answer will yield a hard copy [Figure 5}; a "no"
answer returns the program to the previous
screen. Once the report is printed, a recovery
query will appear. If "Y" is entered, the concen-
tration and volume of the spiking standard in
|ig/mL are then entered, as requested. The per-
cent recovery will then be printed out on the lower
left hand portion of the report. At this point (or if
"N" was entered in response to the recovery
query) the question "do you have another 1260
sample?" will appear. A "yes" answer will return
to the beginning of the calculation program,
whereas, a "no" answer will return the analyst to
the Aroclor menu.
11.5 Report all data in ng/g (for oil or soil samples) and jag/cm2 (for
wipe samples). Soil samples are to be corrected for percent
moisture, if applicable.
11.6 Round off the average of all results greater than 10 ng/g, to two
significant figures and round off results less than 10 ng/g to one
significant figure.
-------
Fgure 5 • PCB Report
CONC;OF SAMPLE IN ug/mL= .4780935
ANALYST: DEAN F. HILL
DILUTION FACTOR: 10
SAMPLE WEIGHT(grams): 1.0002
NEIC SAMPLE NUMBER:01-001-89-01-S
ug/g OF AROCLOR 1260= 47.79979
***************************
AREA OF
AREA OF
AREA OF
AREA OF
AREA OF
AREA OF
AREA OF
AREA OF
AREA OF
AREA OF
AREA OF
AREA OF
AREA OF
AREA OF
AREA OF
STD PEAK*
STD PEAK"
STD PEAK*
STD PEAK'
STD P£AK«
STD PEAK'
STD PEAK»
STD PEAK"
STD PEAK"
STD PEAK'
STD PEAK'
STD PEAK*
STD PEAK*
STD PEAK*
STD PEAK'
RESPONSE
RESPONSE
RESPONSE
RESPONSE
RESPONSE
RESPONSE
RESPONSE
RESPONSE
RESPONSE
RESPONSE
RESPONSE
RESPONSE
RESPONSE
RESPONSE
RESPONSE
FACTOR-
FACTOR-
FACTOR-
FACTOR-
FACTOR-
FACTOR-
FACTOR-
FACTOR-
FACTOR-
FACTOR-
FACTOR*
FACTOR-
FACTOR-
FACTOR-
FACTOR-
• 9384
• 2938
• 9494
> 9494
> 9494
> 1626
• 8282
> 883
• 2300
> 2898
• 2929
• 9292
- 2902
• 4759
' 9283
3.91E+08
8.161111E+07
3.390714E+08
2.157727E+08
8.630909E+07
1.222556E+07
1.505818E+08
8829999
2.U0092E+07
2.5875E+07
2.3432E+07
2.212381E+08
5.374074E-M)7
5.94875E+08
4.6415E+08
RUN NUMBER: 3-11111
CONCENTRATION OF STD
G.C. VOLUME(mL): 10
STANDARD RUN NUMBER: B-11112
AREA OF
AREA OF
AREA OF
AREA OF
AREA OF
AREA OF
AREA OF
AREA OF
AREA OF
AREA OF
AREA OF
AREA OF
AREA OF
AREA OF
AREA OF
SAMPLE
SAMPLE
SAMPLE
SAMPLE
SAMPLE
SAMPLE
SAMPLE
SAMPLE
SAMPLE
SAMPLE
SAMPLE
SAMPLE
SAMPLE
SAMPLE
SAMPLE
PEAK'
PEAK"
PEAK'
PEAK'
PEAK'
PEAK'
PEAK'
PEAK'
PEAK'
PEAK'
PEAK'
PEAK-
PEAK"
PEAK'
PEAK'
9001
2998
9395
9554
9494
1567
8100
887
2287
2678
2567
8298
2654
4290
7654
RESPONSE
RESPONSE
RESPONSE
RESPONSE
RESPONSE
RESPONSE
RESPONSE
RESPONSE
RESPONSE
RESPONSE
RESPONSE
RESPONSE
RESPONSE
RESPONSE
RESPONSE
RATIO-
RATIO-
RATIO-
RATIO-
RATIO-
RATIO-
RATIO-
RATIO-
RATIO-
RATIO-
RATIO-
RATIO-
RATIO-
RATIO-
RATIO-
.9591858
1.020422
3.197754
1.00632
1
.9637147
.9780246
1.00453
.9943478
.9240856
.8764083
.8930262
.9145418
.9014499
.824518
-------
For apparent mixtures of Aroclors, ail Arociors results are :cia
and reported on the basis of the PCB standards used.
Arturo Palomares, NEIC
Dean F. Hill, NEIC
Kenneth C. Wang, NEIC
K. Eric Nottingham, NEIC
December 1, 1988
-------
REFERENCES
40 CFR, Part 61, Subparts A through F (most recent edition).
2. Federal Register 42, #204, p, 46980, October 21, 1982.
3. 40 CFR, Part 761.120, Subpart E (most recent edition).
4. T. A. Bellars and Lichtenberg, J. J., EPA-600/4-81-045, September 1S82.
5. R. G. Webb and McCall, A. C., J. Chromatogr. Set., H 366 (1978).
6. L D. Sawyer, J. Assoc. Off. Anal. Chem., 6J. 272-281 (1978).
7. U.S. Environmental Protection Agency, Inspection Manual, Vol. 1 and
Vol. 2, Toxic Substances Control Act (1985).
8. 40 CFR, Part 136, App. A, Meth. 608, 354-362 (most recent edition).
9. R. F. Schneider, NEIC Sampling Guide (1985). i
10. National Enforcement Investigations Center, Extraction of Solids for
Priority Pollutant Pesticides (1981).
11. Method for Organochlorine Pesticides in Soil and Sediment (NEIC).
-------
APPENDIX D
EPA ANALYTICAL METHOD
-------
Research and
EPA GOO/4-3 I-C45 Sep- :S52
Test Method
The Determination of
Polychlorinated Biphenyls in
Transformer Fluid and
Waste Oils
Thomas A. Bellar and James J. Lichtenberg
1. Scope
1.1 This is the EPA preferred method
for the determination of polychlormated
biphenyls (PCBs) in waste oils according
to PCS regulations.' This gas
chromatographic (GC) procedure is
applicable to the determination of
commercial mixtures of PCBs in
transformer fluids and certain other
hydrocarbon-based waste oils The
method can be used to analyze waste oils
for individual PCS isomers or complex
mixtures of chlorinated biphenyls from
monochlorobiphenyl through
decachlorobiphenyl only if the isomers
have been previously identified by other
methods2 or by knowledge of t^e sample
history
1.2 The detection limits are dependent
upon the complexity of the sample matrix
and the ability of the analyst to properly
maintain the analytical system Using a
carefully optimized instrument, this
method has been shown to be useful for
the determination of commercial PCB
mixtures spiked into transformer fluid
over a range of 5 0 to 500 mg/Kg Based
upon a statistical calculation a: 5 mg/kg
for a simple oil matrix, the metnoo
detection limit for Aroclors 1221, 1 242.
1 254, and 1 260 <:> 1 mg 'kg me method
detection limit (f.'.DL) is define ' as the
minimum concentration of a substance
that can be measured and reported with
99% confidence that the value is above
zero.
1.3 This method is restricted to use by
or under the supervision of analysts
experienced m the use of gas
chromatography and mthe interpretation
of gas chromatograms. Prior to sarroie
analysis, each analyst must demonstrate
the ability to generate acceptable results
with this method by following the proce-
dures described in Section 10 2
2. Summary
2.1 The sample is diluted on a we^ght/
volume basis so that the concentration of
each PCB isomer is within capability of
the GC system (0.01 to 10 ng pL)
2.2 The diluted sample is then injected
into a gas chromatograph for separation
of the PCB isomers Measurement is
accomplibhed with a halogen-specie
detector which maximizes baseline
stability and mimm'.:es interferences
normally encountered wi'h other
detectors The ek- Ton capture detsctor
(ECC) can norm,!!1 , :>e substituted •. • :ne
halogen-specific rd :jctor when
conui'ii d.~hior :
decai. h'orobi,ih •••
10H. 1 2 2 ! I -
'some's (Aroclsrs
I 243. 1 254, 1 25D
-------
1262 and 1 268* or when the sample
matrix does no: interfere w:h tie PCBs
Several cleanup techniques are provided
for samples containing interferences A
mass spectrometer operating in the
selected ion monitoring mode of data
acquisition may also be used as the GC
detector when PCS levels are sufficiently
high and the PCB m/zranges are free
from interference Interferences may
occur in some waste oil samples even
after exhaustive cleanup
2.3 The concentration of the PCBs are
calcula'ed on a mg/kg basis, using
commercial mixtures of PCBs as
standards The analysis time, not
including data reduction, is approximately
35 mm/ sample
3. Interferences
3.1 Qualitative misidentifications are
always a potential problem in GC
analysis The use of a halogen-specific
detector and the analyst's skill in
recognizing chromatographic patterns of
commercial PCS mixtures minimizes this
possibility.
3.2 Whenever analyzed samples do not
provide chromatographic patterns nearly
identical to the standards prepared
from commencal PCBs. the
analyst must confirm the presence of
PCBs by one of three ways by analysis
after column cleanup, by analysis on
dissimilar GC columns, or, by gas
chromatography/mass spectrometry
(GC/MS)
3.3 During the development and testing
of this method, certain analytical
parameters and equipment designs were
found to affect the validity of the
analytical results Proper use of the
method requires that such parameters or
designs are to be used as specified These
items are identified m the text by the
wora must." Anyone wishing to deviate
from the method in areas so identified
must demonstrate that the deviation does
not affect the validity of the data and
alternative test procedure approval must
be obtained through the USEPA,
Environmental Monitoring and Support
Laboratory, Equivalency Program, 26 W.
St Clair Street, Cincinnati, Ohio 45268.3
An experienced analyst may make
modifications to parameters or equipment
identified" by the term "recommended "
Each time such modifications are made to
the method, the analyst must repeat the
procedure in Section 10.2. In this case,
formal approval is not required, but the
documented data from Section 10 2 must
be on file as part of the overall quality
assurance program
3 4 Samples which are diluted at a ratio
of 100 1 and are analyzed by electron
capture GC, consistently produce results
that are 10 to 20% lower than the true
value (See Section 1 2) This is due to
quenching of the detector response by
high boiling hydrocarbons coelutmg with
the PCBs The degree of error is matrix
dependent and is not predictable for
samples of unknown origin As the PCB
concentration approaches 20% of a
control level, for example, 50 mg/kg. the
analyst must routinely reanalyze a
duplicate spiked sample to determine the
actual recovery The duplicate or diluted
sample is spiked at two times the electron
capture observed value and reanalyzed
according to Section 1 0 2 The results are
corrected accordingly
4. Apparatus
4.1 Gas Chromatograph—The gas
chromatograph should be equipped with
on-column Vi-mch injectors The oven
must be large enough to accept a V4" 00
2-meter coiled glass column. If halogen-
specific detectors are used, then the
column oven should have programming
capabilities
4.2 Gas Chromatographic Detector
4.2.1 A halogen-specific detector is
used to eliminate interferences causing
misidentifications or false-positive values
due to non-organohalides which
commonly coeldte with the PCBs
4.2.1. / Electrolytic conductivity detector
— the Hall electrolytic conductivity
detector. Model 700-A (HED), available
from Tracor, Inc , has been found to
provide the sensitivity and stability
needed for the current PCB Regulations.'
421.2 Other halogen-specific
detectors, including older model
electrolytic conductivity detectors and
microcoulometric titration. may be used.
However, the stability, sensitivity, and
response time of these detectors may
raise the MDL and adversely affect peak
resolution. Each system must be shown
to be operating within requirements of
the PCB regulations by collecting single
laboratory accuracy and precision data
and MDL on simple spiked samples, as
described m Section 10 2
4.2.2 Semi-specific detectors, such
ECD, may be substituted when sampK
chromatographic patterns closely match
those of the standards Acid cleanup iSee
Section 8 1} or Flonsil slurry clearup [See
Section 8 7) should be incorporated
routinely when the ECD is used See
Section 3 4 for additional quality control
procedures for ECD
42.3 Quantitative GC/MS techniques
can be used The recommended approach
is selected ion monitoring, but the
GC/MS data system must have a
program that supports this method of
data acquisition The program must be
capable of monitoring a minimum of e'ght
ions, and it is desirable for the system to
have the ability to change the ions
monitored as a function of time For PCB
measurements, several sets of ions may
be used, depending on the objectives of
the study and the data system
capabilities The alternatives are as
follows
4.2 3 1 Single ions for high sensitivity
154, 188. 222, 256, 292, 326, 360. 394
4232 Short mass ranges which may
give enhanced sensitivity, depending on
the data system capabilities 1 54-1 56,
188-192, 222-226, 256-260. 290-295.A
322-328,356-364,390-393. V
4.2.3.3 Single ions giving decreased
sensitivity but are selective for levels of
chlormation.2 190, 224, 260, 294. 330.
362, 394
4 2 3.4 The data system must have the
capability of integrating an abundance of
the selected ions between specified limits
and relating integrated abundances to con-
centrations, using the calibration
procedures described in this method.
4.3 Gas Chromatographic Columns
4.3.1 The GC columns and conditions
listed below are recommended for the
analysis of PCB mixtures m oil If these
columns and conditions are not adequate,
the analyst may very the column
parameters to improve separations. The
columns and conditions selected must be
capable of adequately resolving the PCBs
in the various Arocior mixtures so that
each Arocior is identifiable through
isi,mer pattern recognition (See Figures
1 through 6 to establis1" !HIS ) TQ properly
use the calculation procedure described
in Section 115, the analyst must use the
methyl silicone liquid phase column, /•
-------
I
» scribed m Section 422 Cao'iiary
lumns and tneir associated specialized
inaction techniques are accep!3D!e
f~ "t;rnatives, however, due to problems
sociated with the use of capi !ary
lumns the analyst must demonstrate
that the entire system will produce
fceptable results by pe'formmg the
erations described in Section 10 2.
3 2 Recommended cr.mary analytical
column' Glass. Vi-mch 0 0 (2-mm I D ),
§ft (180 cm) long packed with Gas-
-irom Q 100/1 20 mesh coated with 3%
V-1.
Carrier gas 40 to 60 mL/min (helium.
«!rogen or mixtures of methane in argon,
recommended by the manufacturer of
e detector)
tmperature Program- 120°C isothermal
2 minutes, 6°/min to 220°C and hold
til all compounds elute Figure 7 shows
a chromatogram of the PCB locator
Cxture (See Section 5 8) analyzed under
ese conditions Each PCB peak has
en identified by assigning the same
relative retention times determined in the
»thermal runs (Figures 1 through 6)
thermal Operation. Aroclor 1221,
1 232, or Cli through Cl« isomers —
recommended range 140 to 1 50°C
toclor 1016, 1242, 1248. 1254, 1260,
62, 1 268, or Clj through Clio isomers
— recommended rangs 170 to 200°C
jA.3.3 Recommended confirmatory
B>lumn Glass tubing, Vi-mch O.D. (2-mm
^D.). 6-ft. (180 cm) long, packed with
Gas-Chrom Q 100/120 mesh coated with
»5% OV-1 7 + 1 95%OV-210.
arrier gas 40 to 60 ml/mm (helium.
nitrogen or mixtures of methane in argon,
as recommended bv the manufacturer of
te detector)
•jlumn temperatures: Aroclor 1221,
1 232, or Cli through CU isomers
C commended range — 170 to 1 SO°C.
-oclor 1016, 1242, 1248, 1254, 1260,
268, or CI3 through Clio isomers 200°C.
<.4 Volumetric flasks — 10, 100, 200,
nd 250-mL.
.5 Pipets — 0.10, 1.0. and 5 0 ml
Mohr delivery (for viscous oils cut off tip
If pipet)
.6 Micro syringes — 10.0^L
4.7 Sample containers—20 mL or
Crger screw-cap bottles with Teflon-
ced cap liners (Aluminum foil cap
ier? ~^n he us"=' " T non-corrosive
samples.)
4 8 Chromatographic column —
O.romaflex. 400-mm long x 19-mm I 0
(Kontes K-420540-901 1 or equtva'ent)
4.9 Gel Permeation Chromatograph —
GPC Autoprep 1002 or equivalent,
available from Analytical Bio Chemistry
Laboratories, Inc
4.10 Balance — Analytical, capable of
weighing 99 g with a sensitivity of r
00001 g
4.1 1 Kuderna-Danish (K-D) Evaporative
Concentrator Apparatus
411.1 Concentrator tube — 10 ml,
graduated (Kontes K-570050-1 025 or
equivalent) Calibration must be checked
Ground glass stopper (size 19/22 joint) is
used to prevent evaporation of solvent
4.11.2 Evaporative flask — 500 mL
(Kontes K-57001 -0500 or equivalent).
Attachto concentrator tube with springs
(Kontes K-662750-001 2 or equivalent)
4.11.3 Snyder column—Three-ball
macro (Kontes K503000-01 21 or
equivalent)
5. Reagents and Materials
5.1 Reagent safety precautions
5.1.1 The toxicity or carcinogenicity of
each reagent used in this method has not
been precisely defined; however, each
chemical compound should be treated as
a potential health hazard. From this
viewpoint, exposure to these chemicals
must be reduced to the lowest possible
level by whatever means available The
laboratory is responsible for maintaining
a current awareness file of Occupational
Safety and Health Administration
regulations regarding the safe handling of
the chemical specified m this method A
reference file of material data-handling
sheets should also be made available to
all personnel involved in the chemical
analysis
5.1.2 PCBs have been tentatively
classified as known or suspected, human
or mammalian carcinogens Primary
standards of these toxic compounds
should be prepared in a hood.
5.1.3 Diethyl ether should be monitored
regularly to determine the peroxide
content. Under no circumstances should
diethyl ether be used with a peroxide
content in excess of 50 ppm as an
explosion could result. Peroxide test
strips manufactured by EM Laboratories
(available from Scientific Products Co.,
Cat No P1126-8 and other suppliers) are
recommended for this :•- •'
for remova1 of peroxic'es 'r „ : .-
ether are included m the instruct or s
supplied with the peroxide test kit
5.2 Hexane (mixed hexanes). isooctane,
acetonitnle, methylene chloride,
cyclohexane, and diethyl ether of
pesticide grade
5.3 Recommended Column Packings
53,1 Gas Chrom Q 100/1 20 mesh
coated with 3% OV-1
5.32 Gas Chrom Q 100/1 20 mesh
coated with 1 5% OV-1 7 + 1.95%
OV-210
5.4 Standards
5.4.1 Aroclors 1016. 1221. 1232.
1242, 1248, 1254, 1260, 1262, 1268
Primary dilutions of various Aroclors are
available from USEPA, Environmental
Monitoring and Support Laboratory,
Quality Assurance Branch, 26 W St.
Clair Street, Cincinnati, Ohio 45268
5.4.2 2-Chlorobiphenyl, 3-
chlorobiphenyl, and decachlorobiphenyl.
5.4.3 Pure, individual PCBs, as
identified in the sample by mass
spectrometry or indicated by retention
data
5.4.4 Alumina (Fisher A540 or
equivalent).
5.4.5 Silica gel (Davison Grade 950 or
equivalent)
5.4.5 Flonsil (PR grade or equivalent).
5.4.7 SulfuricacidA.CS.
5.4.8 Quality Control Check Sample —
Certified Samples of PCBs in oil matrices
are available from USEPA, Environmental
Monitoring and Support Laboratory,
Quality Assurance Branch, 26 W. St.
Clair Street, Cincinnati, Ohio 45268.
5.5 Standard Stock Solutions —Prepare
primary dilutions of each of the Aroclors
or individual PCBs by weighing
approximately 0 01 g of material within
± 0 0001 g Dissolve and dilute to 10 0 mL
with isooctane or hexane. Calculate the
concentration in (jg/vL. Store the primary
dilutions at 4°C in 10- to 1 5-mL narrow-
mouth, screw-cap bottles with Teflon cap
liners Primary dilutions are stable
indefinitely if the seals are maintained.
The validity of mhouse-generated or
stored primary and secondary dilutions
must be verified on a quarterly basis by
analyzing Environmental Monitoring and
Support Laboratory-Cincmnati-Quality
I
-------
led PC:
? 6 Working Standards — Prepare
,-.orkmg standards s<~Var m PCB
composition and concentration to the
samples by mixing and diluting the
'.-ijividual standard stock solutions Dilute
i^e mixture !o volume with pesticide
Quality hexane Calculate the
concentration in ng/oL as the individual
Aroclors (Section 11 4) or as the
individual PC3s (Section 1 1 5) Store
rj.lut'ons at 4^C m 10- to 15-mL narrow-
mouth, screw-cap bottles with Teflon cap
hners If the seals are maintained, these
secondary dilutions can be stored
^definitely. (See Section 5 5 )
5 7 Laboratory control standard (LCS) —
Prepare a LCS by spiking a PCB-free oil
typical of the matrix normally analyzed,
such as a transformer oil, at 50 0 mg/kg
with a PCB mixture typical of those
normally found in the samples, such as
Aroclor 1260 at 50 0 mg/kg
5.8 PCB Locator Mixture — Prepare a
PCS locator mixture containing 0 1 ng//;L
of 2-chlorobiphenyl, 0 1 ng/fA. 3-
chlorobiphenyl, 0 5 ng/(jL Aroclor 1242, /
0 5 ng/fjl Aroclor 1 260, and 0.2 ng/fjL
Aroclor 1 268 in hexane (0.1 rig/fjL of
decachlorobiphenyl can be substituted for
Aroclor 1268) Use the chromatogram
generated by the PCB locator mixture to
help identify the retention times of the
various PCB isomers commonly found m
commercial PCB mixtures.
6. Sample Collection and
Handling
6.1 Sample containers should have a
volume of 20 rnL or more and have Teflon
or foil-lined screw caps.
6.2 Sample Bottle Preparation
6 2.1 Wash all sample bottles and seals
in detergent solution Rinse first with tap
water and then with distilled water Allow
the bottles and seals to drain dry in a
contaminant-free area Then rinse seals
with pesticide-grade hexane and allow to
air dry.
6.2.2 Heat sample bottles to 400°C for
1 5 to 20 minutes or rinse with pesticide-
grade acetona or hexane and allow to air
dry
6.2.3 Store the clean bottles inverted or
sealed until use.
6" 2.4 Sample bottles can be reused.
Prior to reuse, rinse the bottles and seals
three times with hexane. allow to air dry,
and then proceed to Section 6 2 1
6.3 Sample Preservation—The
samples should be stored m a cool dry.
dark area until analysis Storage times in
excess of four weeks are not
recommended for unknown or undefined
sample matrices.
6.4 Sample Collection
6.4 1 Fill a large container, such as a
50C ~L beaker, from a representative
area of the sample source If practical,
mix the sample source prior to sampling
6.4.2 Fill a minimum of two 20-mL
sample bottles (Field Sample 1 (FS1) and
Field Sample 2 (FS2» approximately 80%
full from the sampling container
6.4 3 Repeat Sections 6 4 1 and 6 4 2 if
there is a need to monitor sampling
precision, as described m Section 10 6.
/•" ,f\f
7. Procedure f 'V <
7.1 The approximate PCB concentration
of the sample may be determined by X-
ray fluorescence (total halogen
measurement), microcoufometry (total
halogen measurement), density
measurements, or by analyzing a very
dilute mixture of the sample (10,000 1)
according to Section 7.4
7.2 For samples in the 0-to 100-mg/kg
range, dilute at the rate of 100.1 m
hexane
7.2.1 Pipet 1.0 mL of sample into a
100-mL volumetric flask, using a 1.0-mL
Mohr pipet. For viscous samples, cut the
capillary tip off the pipet Dilute to volume
wuh hexane Stopper and mix.
7.2.2 Using the same pipet as in
Section 721, deliver 1.0 mL of sample
into a tared 10-mL beaker weighed to
x 001 g Reweigh the beaker to ± .001 g
to determine the weight of sample used
in 7.2 1.
7.2.3 As an alternative to Sections
7.2.1 and 7 2.2, weigh approximately 1 g
to ± .001 g of sample in a 100-mL
volumetric flask and dilute to volume with
hexane
7.2.4 Analyze the diluted sample
according to Section 7.4 or store the
diluted sample m a narrow-mouth bottle
with a Teflon-lined screw cap.
7.3 For samples above 100 mg/kg in
concentration, dilute at a rate of 1000.1
in hexane.
7.3 1 Pipet 0.10 ml of sample into a
100-mL volumetric flask, using a 0.10
mL-Mohr pipet Dilute to volume with
hexane. stopper and mix
7.3 2 Using -he sa —e c pet .,-3 .n
Section 731, driver 0 10 mL of sa-; £
into a rared IC-mL beaker to ~ OCO' g
Reweigh the beaker to determine :Ke
weight of sample used m Section 7 3 1
7.3.3 As an alternative to Sections
7 3 1 and 732. weigh approximately 0 1
g to ± 0001 g of sample and ma 1 30 mL
volumetric flask Dilute to volume witn
hexane
7.3 4 Analyze the diluted sample
according to Section 7 4 or store in a
narrow-mouth bottle with a Teflon-iined
screw cap
7.3.5 If the concentration of PCBs is
still too high for the chromatographic
system, prepare secondary dilutions from
Sections 7 3.1 or 7 3 3 until acceptable
levels are obtained.
7.4 Analyze the sample by injecting the
hexane mixture into the gas
chromatograph, using auto injectors or
the solvent flush technique *
7.4.1 Recommended injection volumes
Halogen-specific detector — 4 to 5,uL.
ECD 2 to 3 ^L Smaller volumes may be
injected when auto injectors are used if
the resulting MDL are acceptable
Note- When semi-specific detectors are
used, cleanup techniques (See Section
4 2.2) should be routinely incorporated
into the analysis scheme prior to
injection.
7.5 If the resulting chromatogram
shows evidence of column flooding or
nonlinear detector responses, further
dilute the sample according to Section
735
7.6 Determine whether or not PCBs are
present m the sample by comparing the
sample chromatogram to that of the PCB
locator mixture, Section 5 8.
7.6.1 If a series of peaks in the sample
match some of the retention times of
PCBs in the PCB locator mixture, attempt
to identify the source by comparing
chromatograms of each standard
prepared from commercial mixtures of
PCBs (See Section 5.6) Proceed to
Section 11.4 if the source of PCBs is
identified.
7.6.2 If the sampfe contains a complex
mixture of PCBs, proceed to Section 11.5
7.6.3 If a dilution ratio of 1000'1
(Section 7 3) or higher was analyzed and
no measurable PCB peaks were detected,
analyze an aliquot of sample diluted to
100:1.
-------
7 6.4 If several PC3 inter'ere"ce
problems are encountered or if PC3 ratios
do not match standards, proceed :o
[Section 8 Use alternate columns or use
GC/MS' to verify whether or not the
nonrepresentative patterns are due to
PCBs
|8. Cleanup
Several tested cleanup techniques are
(described Depending upon the
complexity of the sample, one or all of the
techniques may be required to resolve the
PCBs from interferences.
18.1 Acid Cleanup
8.1.1 Place 5 0 mL of concentrated
sulfunc acid into a 40-mL narrow-mouth
.screw-cap bottle Add 10.0 mL of the
•diluted sample. Seal the bottle with a
iTeflon-lmed screw-cap and shake for one
minute.
15.1.2 Allow the phases to separate,
transfer the sample (upper phase) to a
clean narrow-mouth screw-cap bottle.
Seal with a Teflon-lined cap.
I
'. 1.3 Analyze according to Section 7.4.
81.4 If the sample is highly
tontammated. a second or third acid
leanup may be employed.
Note' This cleanup technique was tested
Kver a 6-month period, using both
lectron capture and electrolytic
onductivity detectors. Care was taken to
exclude any samples that formed an
Knulsion with the acid. The sample was
ithdrawn well above the sample-acid
terface Undertheseconditions.no
adverse effects associated with column
terformance and detector sensitivity to
CBs were noted This cleanup technique
ould adversely affect the
chromatographic column performance for
tamples containing analytes other than
CBs
.2 Florisil Column Cleanup
«.2.1 Variances between batches of
lonsil may affect the elution volume of
le various PCBs. For this reason, the
volume of solvent required to completely
K'ute all of the PCBs must be verified by
e analyst. The weight of Florisil can
en be adjusted accordingly.
j^.2.2 Place a 20 0-g charge of Florisil,
•ctivated at 1 30°C, into a Chromaflex
™olumn Settle the Florisil by tapping the
column Add about 1 cm of anhydrous
•odium sulfate to the top of the Florisil.
I
Pre-elute the column w.th 70 to 80 ml of
hexane Just before the exposure of the
sodium sulfate layer to air, stop the flow
Discard the eluate
8 2.3 Add 2 0 ml of the undiluted
sample to the column with a 2-ml Mohr
pipet. For viscous samples, cut the
capillary tip off the pipet Add 225 ml of
hexane to the column Carefully wash
down the inner wall of the column with a
small amount of the hexane prior to
adding the total volume Collect and
discard the first 25 0 mL
8.2.4 Collect exactly 200 ml of hexane
eluate in a 200-mL volumetric flask All
the PCBs must be m this fraction
8.2.5 Using the same pipet as in
Section 822. deliver 2 0 ml of sample
into a tared 10-mL beaker weighed to
± 0 001 g. Reweigh the beaker to
determine the weight of the sample
diluted to 200 mL.
8.2.6 Analyze the sample according to
Section 7.4.
8.3 Alumina Column Cleanup
8.3.1 Adjust the activity of the alumina
by heating to 200°C for 2 to 4 hours.
When cool, add 3% water (weight:weight)
and mix until uniform. Store in a tightly
sealed bottle. Allow the alumina to
equilibrate at least 30 minutes before
use. Adjust activity weekly.
8.3.2 Variances between batches of
alumina may affect the elution volume of
the various PCBs For this reason, the
volume of solvent required to completely
elute all of the PCBs must be verified by
the analyst. The weight of alumina can
then be adjusted accordingly.
8.3.3 Place a 50.0-g charge of alumina
into a Chrcmaflex column Settle the
alumina by tapping. Add about 1 cm of
anhydrous sodium sulfate to the top of
the alumina Pre-elute the column with
70 to 80 mL of hexane. Just before
exposing the sodium sulfate layer to air,
stop the flow. Discard the eluate.
8.3.4 Add 2.5 mL of the undiluted
sample to the column with a 5-mL Mohr
pipet. For viscous samples, cut the
capillary end off the pipet. Add 300 mL of
hexane to the column. Carefully wash
down the inner walls of the column with
a small volume of hexane prior to adding
the total volume Collect and discard the
0- to 50-mL fraction.
5.3.5 Collect exactly 250 mL of the
hexane in a 250-mL volumetric flask All
the PCBs must be in this fraction
836 Using the same pipet as m
Section 834, deliver 2 5 ml of sample
into a tared 1 0-mL beaker (^ 0 001 g)
Reweigh the beaker to determine weight
of sample diluted to 250 mL
8.3.7 Analyze the sample according to
Section 7 4
8.4 Silica Gel Column Cleanup
84.1 Activate silica gel at 1 35°C
overnight
8.4.2 Variances between batches of
silica gel may affect the elution volume of
the various PCBs For this reason, the
volume of solvent required to completely
elute all of the PCBs must be verified by
the analyst The weight of silica gel can
then be adjusted accordingly
8.4.3 Place a 25-g charge of activated
silica gel into a Chromaflex column
Settle the silica gel by tapping the
column Add about 1 cm of anhydrous
sodium sulfate to the top of the silica gel
8.4.4 Pre-elute the column with about
70 to 80 mL of hexane. Just before
exposing the sodium sulfate layer to air,
stop the flow. Discard the eluate
5.4.5 Add 2.0 mL of the undiluted
sample to the column with a 2-mL Mohr
pipet. For viscous samples, cut the
capillary tip off the pipet.
8.4.6 Wash down the inner wall of the
column with 5 mL of hexane
5.4.7 Elute the PCBs with 195 mL of
10% diethyl ether m hexane
(volume volume).
5.4.5 Collect exactly 200 mL of the
eluate in a 200-mL volumetric flask All
the PCBs must be in this fraction
8.4.9 Using the same pipet as in
Section 845, deliver 2 0 mL of sample
into a tared 1 0-mL beaker (± 0.001 g).
Reweigh to determine the weight of
sample diluted to 200 mL.
5.4.10 Analyze the sample according to
Section 7.4.
8.5 Gel Permeation Cleanup
8.5.1 Set up and calibrate the gel
permeation chromatograph with an SX-3
column according to the instrument
manufacturer's instruction manual Use
1 5% methylene chloride in cyclohexane
(volume'volume) as the mobile phase
8.5.2 Place 1 0 mL of sample into a
100-mL volumetric flask, using a 1 -mL
Mohr pipet For viscous samples, cut the
capillary tip off the pipet
5
-------
853 Dilute t*e samo'e :o voij^e,
using 15''3 melhylene chlorine ' n
cyclohexane (voiume volume)
854 Using the same pipet as in
Section 852. deliver 1 0 ml of sample
into a tared 10-mL beaker (- 0 001 g)
Reweigh the beaker (± 0 001 g) to
determine the weight of sample used in
Section 852
8.5.5 As an alternative to Sections
852 and 853. weigh approximately 1 g
(r 0 001 g) of sample and dilute to 100 0
ml in 1 5% metnylene chloride in
cyclohexane (volume volume)
856 Inject 5 0 ml of the diluted
sample into tne instrument. Collect the
fraction containing the Cl, through Clio
PCBs (see instruction manual. Section
8 5 1) m a K-D flask equipped with a 10-
mL ampul.
85.7 Concentrate the Section 8 5 4
fraction down to less than 5 mL, using K-
D evaporative concentration techniques
8.5 8 Dilute to 5 0 mL with hexane,
then analyze according to Section 7 4 Be
sure to use 100 mL as the dilution
volume for the final calculation.
8.6 Acetonitnle Partition
8.6.1 Place 10 0 mL of the previously
diluted sample into a 125-mL separatory
funnel. Add 5 0 mL of hexane. Extract the
sample four times by shaking vigorously
for one minute with 30-mL portions of
hexane-saturated acetonitnle.
8.6.2 Transfer and combine the
acetonitnle phases to a 1-L separatory
funnel and add 650 mL of distilled water
and 40 mL of saturated sodium chloride
solution Mix thoroughly for 30 to 35
seconds Extract with two 100-mL
portions of hexane by vigorously shaking
about 1 5 seconds
8.6.3 Combine the hexane extracts in a
I-L separatory funnel and wash with two
100-mL portions of distilled water.
Discard the water layer and pour the
hexane layer through a column (Section
4 8) packed with 3 to 4 inches of
anhydrous sodium sulfate Drain the
column into a 500-mL K-D flask equipped
with a 10-mL ampul Rinse the
separatory funnel and column with three
10-mL portions of hexane.
8.6.4 Concentrate the extracts to 6 to
10 mL in the K-D evaporator m a hot
water bath, then adjust the volume to
10 0 mL Be sure to use the correct
dilution volume (See Section 8 6 1) for
the final calculation.
865 Analyze accorcJing to Section 7 4
8 7 Flonsil Slurry Cleanup
871 Place 10 ml of the diluted sample
into a 20-mL narrow-mouth screw-cap
container Add 0 25 g of Flonsil Seal
with a Teflon-lined screw-cap and shake
for one minute
8.7.2 Allow the Flonsil to settle then
decant the treated solution into a second
container Analyze according to Section
74.
9. Calibration
9.1 Single Point Calibrations — Prepare
calibration standards from standard stock
solutions m hexane that are close to the
unknown in composition and in
concentration If when using an
electrolytic conductivity detector the
sample response is in the low level
nonlinear detection area, the calibration
point must then be within 20% of the
sample The ECD must be operated only
within its linear response range.
9.2 As an alternative to Section 9 1,
prepare a calibration curve for each
Aroclor or PCB detected in the sample.
The standard curve must contain at least
three points, two of which must bracket
the sample concentration. When using an
electrolytic conductivity detector, if the
sample response is m a low level
nonlinear area of the calibration curve,
two of the calibration points must be
within 20% of the unknown The
calibration curve must be checked daily,
using the LCS, Section 5 7. If the
calibration curve is not within 15% of the
LCS, recalibrate the instrument If an ECD
is used then it will be necessary to
correct the LCS value for recovery (See
Section 3 4) Use the recovery value
determined the same day the calibration
curve was generated. The correct value
must be within 1 5% of the spike value,
otherwise the instrument must be
recalibrated.
1 0. Precision and Accuracy
1 0.1 Each laboratory using this method
is required to operate a formal quality
control program. The minimum
requirements of this program consist of
an initial demonstration of laboratory
capability and the analysis of spiked
samples as a continuing check on
performance The laboratory is required
to maintain performance records to
define the quality of data that is
generated Attar January 1. 1933,
ongoing performance checks must be
compared w :h established per'cr-ia^e
criteria to determine ;! the resu'ts cf .^
analyses are wthm accuracy and ^3
precision limits expe::ed of tne method
10.1.1 Before performing any analyses,
the analyst must demonstrate the asili:/
to generate acceptable accuracy and
precision with this method This aoility is
established, as described m Section 10 2
1012 In recognition of the rapid
advances occurring m chromatography,
the analyst is permitted certain options to
improve the separations or lower the cost
of measurements Each time such
modifications are made to the method.
the analyst is required to repeat the
procedure in Section 10 2
10.1.3 The laboratory must spike and
analyze a minimum of 10% of all samples
to monitor continuing laboratory
performance This procedure is described
in Section 10 4.
10.2 To establish the ability to generate
acceptable accuracy and precision m the
use of this method, the analyst must
perform the following operations.
10.2.1 Fo'each commercial PCB
mixture or mi.vidual PCS isomer
normally measured, prepare a PCB
spiking concentrate, in isooctane within f
the range o: 40 ;o 60 mg/mL
JO.2.2 Us ig a microsynnge, add 100
pL of the PCS concentrate to each of a
minimum of four 100 g aliquots of PC8-
free oil A rezresentative waste oil may
be used in piace of the clean oil. but one
or more additional aliquots must be
analyzed to r-rtsrmme the PCB
background -. .el, and the spike level
must exceed twice the background level
for the test to be valid. Analyze the
aliquots accor.lmg to the method
beginning m Section 7.
10.2.3 Ca'c j'ate the average percent
recovery, (Rj. and the relative standard
deviation (si o< :he concentration found.
Waste oil background corrections must be
made before 2 calculations are
performed.
10.2.4 Using the appropriate data from
Tables 1. 2, aid 3, determine the
recovery and single operator precision
expected for the method and compare
these results to the values calculated in
Section 102? If the data are not
comparable, tne analyst must review and
remedy potert'Si problem areas and
repeat the test.
-------
I
§25 A*terj3'iL,3ryi,1?33>-'e
ues for R and s mL3t rree! -re'~:3C3
•'ormance criteria provided bv ;-•?
f~EPA. Environmental Monmr'ng and
oport Labortory, Cincinnati OHIO
268, before any samples may se
•nalyzed
K.3 The analyst must calculate
thod performance of the laboratory for
:h spike concentration and parameter
:emg measured
»3. J Calculate upper and lower
trol limits for method performance.
Upper Control Limit (UCL) = R + 3 s
* Lower Control Limit (LCL) - R - 3 s
ere R and s are calculated as in
. ;tion 10 2 3. The UCL and LCL can be
jsed to construct control charts5 that are
Ieful in observing trends m
rformance After January 1, 1 983, the
control limits above must be replaced by
method performance criteria provided by
tuSEPA.
3.2 The laboratory must develop and
maintain separate accuracy statements of
K oratory performance for waste oil
nples An accuracy statement for the
thod is defined as R ± s. The accuracy
statement should be developed by the
Kilysis of 4 aliquots of waste oil, as
iCnbed in Section 1022, followed by
calculation of R and s Alternately, the
analyst may use four waste oil data
«nts gathered through the requirement
continuing quality control in Section
4. The accuracy statements should be
updated regularly.
».4 The laboratory is required to
lect a portion of their samples in
duplicate to monitor spike recoveries The
tquency of spiked sample analysis must
at least 10°o of ail samples or one
mple per month, whichever is greater.
One aliquot of the sample must be spiked
•>d analyzed, as described in Section
B) 2.2, at two times the background level.
"the recovery for a particular parameter
does not fall within the control limits for
«ethod performance, the results reported
r the parameter in all samptes
ocessed as part of the same set must
be qualified, as described in Section 11.9
•he laboratory should monitor the
•equency of data so qualified to ensure
"at it remains at or below 5%.
•0.5 Before processing any samples.
He analyst should demonstrate through
tne analysis of a PCB-free oil sample, that
all glassware and reagents are tree of
interfe'erices Each tirre a ser of samples
is anal/zed or there is a change in
reagents, a laboratory reagent blank
should be processed as a safeguard
against contamination
10.6 It is recommended that the
laboratory adopt additional quality
assurance practices for use with this
method The most productive, specific
practices depend upon the needs of the
laboratory and the nature of the samples
Field duplicates may be analyzed to
monitor the precision of the sampling
technique When doubt exists regarding
the identification of a peak on the
chromatogram, confirmatory techniques
such as GC with a dissimilar column,
specific element detector, or MS must be
used Whenever possible, the laboratory
should perform analysis of standard
reference materials and participate in
relevant performance evaluation studies.
10.7 Analyze the LCS, Section 5.7,
daily before any samples are analyzed.
Instrument status checks, calibration
curve validation and long-term precision
are obtained from these data In addition,
response data obtained from the LCS can
be used to estimate the concentration of
the unknowns From this information, the
appropriate standard dilutions can be
determined for single-point calibrations
1 0.8 Analyze on a quarterly basis a
Quality Control Sample (Section 5 4 8.) of
PCBs in oil or whenever new standard
dilutions are prepared.
10.8.1 The results of the Quality
Control Sample should agree within 1 5%
of the true value If they do not. the
analyst must check each step in the
standard preparation procedure to resolve
the problem.
11. Calculations
11.1 Locate each PCB in the sample
chromatogram by comparing the
retention time of the suspect peak to the
retention data gathered from analyzing
standards and interference-free Quality
Control Samples The width of the
retention time window used to make
identifications should be based upon
measurement of actual retention time
variations of standards over the course of
a day. Three times the standard deviation
of a retention time for each PCB can be
used to calculate a suggested window
size, however, the experience of the
analyst should weigh heavily in the
interpretation of chromatograms
112 'f the response 'or a'-/ ="^3 pe.M
exceeds the working ra~ge of :~e s/ste'p,
dilute according to Section 735
11.3 if accurate measurement of the
peaks in the PCB elution area of the
chromatogram is prevented by the
presence of interferences, further
cleanup is required
114 If the parent Aroclors or PCBs are
identified in the sample, calibrate
according to Section 9 The concentration
of the PCBs in the sample is calculated by
comparing the sum of the responses for
each PCB m the standard to the sum of
all of the PCBs in the sample This is
particularly important as sample
concentrations approach within 20°o of
50 mg/kg or any other EPA-regulated
concentration If calculations are based
upon a single PCB peak or upon a small
percentage of the total PCB peaks,
serious errors may result Peaks
comprising less than 50% of the total can
be disregarded only if(l) interference
problems persist after cleanup, (2) the
source of PCBs is obvous, or (3) the
concentration of PCBs is not within ±20%
of an EPA-controlled value such as 50
mg/kg
11.4.1 Measure the peak heigh: or
peak area of each peak identified as a
PCB (Section 11.1) m both the sample
and the standard.
11.4.2 Use the following formula to
calculate the concentration of PCBs in the
sample
Concentration mg/kg = -r—-^
where
Sum of standard
Peak Heights (areas)
A = = mm/ng
ng of standard i-jected
Sum of sample.
Peak Heights (areas)
B = = mm//A.
yL mjectea
Vt = dilution volume of sample m mL
W = weight of the sample in grams
11.5 If the parent Aroclors or source of
PCBs is not apparent, calculate the
concentration according to the procedure
of Webb and McCall ' The concentration
of the PCBs in each peak is determined
individually then added together to
determine the total PCB content of the
sampie Eacn PCB identified m the
I
-------
sample must be included in ;h*se
calculations
11.5.1 Small variations between
Aroclor batches make it necessary to
obtain standards prepared f>-om a specific
source of Aroclors Primary dilutions of
these reference Aroclors will be available
in 1981 from the USEPA, Environmental
Monitoring and Support Laboratory,
Quality Assurance Branch, Cincinnati,
Ohio 45268
11.52 Analyze a standard mixture of
Arociors 1 242, 1 254, and 1 260 under the
conditions shown in Figures 3. 5, and 6
Analyze the sample under the same
conditions Compare the resulting
standard chromatograms to those shown
in Figures 3, 5, and 6 Each PCS peak
must be resolved as well or better than
those shown m the figures Determine
the relative retention time (RRT) of each
peak in the standards with respect to
p.p'-DDE or assign the RRT shown in the
figures to the corresponding peak in the
standard Identify the RRT of each PCS in
the sample by comparing the sample
chromatogram to the standard
chromatograms
7 1.5.3 Identify the most likely Aroclors
present in the sample, using the
Identification Flow Chart, Figure 8
/ 1.5.4 Analyze standards according to
Section 9, using the appropriate Aroclors.
11,5.5 Determine the instrument
response factor (A) for each individual
PCB, using the following formula
A =
Peak Height (area)
Ng x mean weight %
Too
where
Ng, = Ng of Aroclor standard injected
(mean weight percent is obtained
from Tables 4 through 9).
1 1 .5.6 Calculate the concentration of
each PCB in the sample, using the
following formula
B x V
Concentration mg/kg = A \»i
where:
A = Response factor from 1 1 .5.5
Peak Height (areas) of sample
8 =
(A. injected
V, = d'lution volume of sample in ml
W = weight of sample in grams
The concentration of each PCB must be
calculated and added together to obtain
the total amount of PCBs present
11.6 Report all data in mg/kg
11.7 Round off all data to two
significant figures
11.8 Add all Aroclors and report what
was used as the standard For example,
57 mg/kg measured as Aroclor 1 260 or
57 mg/kg measured as Aroclors 1 242
and 1260
11.9 Data for the affected parameters
of samples processed as part of a set
where the laboratory spiked sample
recovery falls outside the control limits in
Section 10 4 must be labeled as suspect.
11.10 Determine the actual recovery
for electron capture analyses of each
sample in the uncorrected 40- to 50-
mg/kg concentration range (See Section
3 4) Report the corrected value and the
recovery
12. Precision and Accuracy
12.1 The data shown m Tables 1
through 3 were generated using the
recommended procedures described in
this method to analyze both spiked and
nonspiked oil samples of varying degrees
of complexity Data for both the HED and
ECD were generated by the USEPA,
Environmental Monitoring and Support
Laboratory, Physical and Chemical
Methods Branch, Cincinnati, Ohio 45268.
References
1. Federal Register, 40 CFR, Part 761.
July 1. 1981
2. Eichelberger, J W,L E. Harris, and
W L Budde Anal. Chem.. 46, 227
(1974)
3. Federal Register, 40 CFR, Sections
1364and 136.5, July 1, 1981.
4. White, L. 0.. et al.. AIHA Journal, 31.
22S. (1970).
5 Handbook of Analytical Quality
Control :n Water and Wastewater
Laboratories. EPA-600/4-79-019
UbEPA. Environmental M
and Support Laboratory, C
Ohio 45263, March 1 979
Webb. R G
Chrom Sci
and A C McCall
11, 366(1973)
-------
f
I
I
I
Table 1
Accuracy jnd precision
spiked motor oil'
I
I
I
I
I
I
I
I
I
Dilution Method
Ratio Detector Cleanup
100 ! HED None
700 7 ECO None
TOO 7 HED None
700 7 ECO None
100 7 HED
ECO
HED
ECO
HED
ECD
HED
ECD
HED
ECD
HED
ECD
HED '
ECD
HED
ECD
HED
ECD
HED
ECD
HED
ECD
HED
ECD
Severe interference problems in
Cleanup technique. Sections 8 1
a 7
8 7
5 7
8 1
82
82
82
8.2
83
83
83
8.3
84
8.4
84
8.4
85
85
8.5
85
86
8.6
8.6
8.6
elution area
8.2. 8.3. 8.4
Spike
mg/kg
30 3
303
37 7
37.7
303
303
3; 7
37.7
303
303
37 7
37.7
303
303
31.1
3J.J
30.3
30.3
31.1
31.1
303
30.3
31.1
31.1
30.3
31.1
30.3
31.1
of 1242
Aroc/or
Spiked
1242
1242
1260
1250
7242
1242
1260
1260
1242
1242
1260
1260
1242
1242
1260
1260
1242
1242
1260
1260
1242
1242
1260
1260
1242
1242
1260
1260
Avg
Cone
Found
mg 'kg
28 2
26 7'
272
239
234
254'
28 1
243
30 7
273'
309
31 0
303
2S9'
29 8
308
29.4
26.4'
294
236
31.9
234'
335
30.9
344
23.4'
29./
27.0
Measurement based upon only 3
8.5. and 8 6 did not imi
Drove the Quality o
/Precision}
Re/ S:d (Accuracy! Number
Deviation Percent o!
% Recovered D'/u'ions
42
5 7
20
22
11 5
6.1
80
78
24
102
36
8.6
8.6
50
4 7
65
5.8
53
52
4.5
8.5
3.0
92
55
3.8
4.4
4.2
46
of the 10
93 1
83 1
87.5
76 8
93 7
83 8
90 3
78 1
101
90 1
994
99 7
100.
954
958
99.0
97.0
87 1
945
105.
759
772
108
994
107.
77.2
967
867
5
3
5
3
3
3
3
3
4
4
4
4
3
3
3
3
3
3
3
3
3
2
3
3
4
4
4
4
normally resolved major peaks
f the 1 242 chromatoararr
. If this were an
unknown sample, it would be impossible to qualitatively identify the presence of Aroctor 1242 using ECD. The HED provided an
interference-free chromatogram
-------
Table 2. Accur3cy and prec-
Dilution
Sample ' Ratio
A 100 1
A
A
A
A
A
A
A
A
A • "
A
A
A
A
B 1000:1
B
B
B
C 1000:1
C
C
C
S'On using
Detector
ECD
HED
ECD
HED
ECD
HED
ECD
HED
ECD
HED
ECD
HED
ECD
HED
ECD
HED
ECD
HED
ECD
HED
ECD
HED
waste trans'ormer
Method
Cleanup
None
None
8 1
8 ;
82
82
8.3
8.3
84
84
85
85
None
None
None
"
"
"
None
"
"
fluids
1260
Spike
rng'kg
--
.-
--
••
--
..
..
..
.-
270
27.0
..
--
455
455
..
--
300
300
A vg ID I
Cone
Found
22 6
270
22 8
29 7
22 4
282
227
278
209
30.2
238
286
45.0
55 2
452
471
875
916
284
300
607
686
(Precision)
Rel Std
Deviation
%
36
1 7
2 5
1 4
1 0
22
I 3
28
..
._
03
4 1
33
1.5
08
1.2
05
20
1.2
1.4
36
3.9
(Accuracy)
Percent
Recovered
..
..
..
.-
..
--
--
_.
..
91
102
..
..
96
99
,_
..
104
114
i
I
Number
of
Dilutions
71
7J
7J
7
32
32
32
3'
1
1
7:
72
7
72
72
7
72
72
7
7
72
7
1 A - dark waste oil
B - black waste oil with suspended solids
C - clear waste oil
D - all samples contained Aroclor 1260
2 Duplicate analyses made at each dilution
10
-------
Table 3. Accuracy and precision and limit of detection data results of analyses of
Shell transljrmer fluid spued with PC8s at 5 0 and 27 mg/kg
Electron Capture Detector
(TOO 1 dilution)
Aroclor
1221
1242
1254
1260
Spike
Img/kg)
50
50
50
50
Number of
Analyses
7
14
7
14
Avg
(mg/kg)
75
38
4 1
47
Standard
Deviation
043
0 18
008
0 18
Percent
Recovery
150
76
82
94
MDL^
Img/kg)
1 4
05
02
05
Electrolytic Conductivity Detector
(100:1 dilution)
Spike- Number of Avg. Standard Percent
Aroclor (mg/kg) Analyses (mg/kg) Deviation Recovery
(mg/kg)
1221
1242
1254
1260
50
50
50
50
6
7
6
7
75
59
58
54
Shell Transformer 0/1 + 27
0
0
0
0.
ppm
23
17
16
10
Aroclor
150
118
116
108
1260
0.
0.
0
0
7
5
5
3 '
ft 00 1 dilution)
Detector
ECO
HED
Spike
(mg/kg)
27
27
Number of Avg
Analyses
14
7
(mg/kg)
24.0
283
Rel
Std
Deviation. %
2.
70
1
Percent
Recovery
89
105
MDL - Method Detection Limit at 99% confidence that the value is not zero
Note At these values it would be impossible to identify Aroclor patterns with
any degree of confidence. 1 mg/kg appears to be a reasonable MDL
MDL = ' (n=1..99)(S>
where'
MDL — the method detection limit
(n-1..99) - the students' t value appropriate for a 99%
confidence level and a standard deviation
estimate with n-1 degrees of freedom.
S = standard deviation of the replicate analyses
Table 4 Composition of Aroc!cr 12
Mean
Weight Relative Number of
RRT* Percent Std Dev 3 Chlorines1
n
14
16
19
21
28
32
r37
1-40
Total
31 8
193
10 1
28
208
54
1.4
1.7
933
158
9 1
97
9 7
93
139
30.1
48.8
1
1
2
2
2
2q
3^
2-
3-
3
3
i 85%
1 15%
] 10%
> 90%
' Data obtained from Webb and McCall s
2 Retention time relative to p,p'-DDE=100
Measured from first appearance
of so/vent. Overlapping peaks that are
quantitated as one peak are bracketed
3 Relative standard deviation of 17 analyses
las percentages of the mean of tfte resurts)
* From GC/MS data Peaks containing
m/xtures of isomers of different chlorine
numbers are bracketed
11
-------
I
I
I
I
I
I
I
I
I
I
I
I
T.l'J/g 5. Corrr-JS,tn
RR7-
1 /
14
16
r20
121
28
32
37
40
47
54
58
70
78
Total
or, of ~r?rior 1 232 '
,','ejn
V. sight
152
99
7 1
178
96
39
68
64
42
34
26
46
1.7
942
Relative
Std Dev i
34
25
63 •
24
34
4 7
2.5
2.7
4 7
34
3.7
3 1
7.5
Number of
Chlorines *
7
7
2
2
2
2-i 40%
3 J 60%
3
3
3
4
3-i 3 3%
4^67%
4
4-) 90%
5-1 70%
4
i Data obtained from Webb and McCall s
2 Retention time relative to p.p'-DDE—TOO. Measured from first appearance
of solvent Overlapping peaks that are quantitated as one peak are bracketed
3 Relative standard deviation of four analyses (as percentages of the mean of the results).
4 From CC/MS data Peaks containing mixtures of isomers of different chlorine numbers
are bracketed
Table 6. Composition of Aroclor 1242'
I
I
I
I
I
I
RR-P
11
16
21
28
32
37
40
47
54
58
70
78
84
98
104
125
146
Total
Mean
Weight
Percent
1 1
2.9
11.3
11.0
6 1
11 5
77.7
88
68
56
103
36
27
1 5
23
7.5
1.0
98.5
Relative
Std Dev 3
357
4.2
3.0
5.0
4 7
57
62
43
29
3.3
28
42
97
94
16.4
204
19.9
Number of
Chlorines''
1
2
2
2-j 25%
3-175%
3
3
3
4
3-i 33%
4-1 67%
4
4-i 50%
5J 70%
4
5
5
5
5-1 55%
5-1 15%
5-i 75%
5-1 25%
' Data obtained from Webb and McCalls
2 Retention time relative top.p'-DDE=100 Measured ffom first appearance of solvent.
3 Relative standard deviation of six analyses (as percentages of the mean of the results).
4 From GC/MS data Peaks containing mixtures of isomers of different chlorine
numbers are bracketed -
12 *
-------
r
0
RRP
27
28
32
47
40
47
54
58
70
78
84
98
104
112
125
146
Total
Composition o' ~ rye/or 7243'
'A'eignt
Percent
7 2
52
32
83
83
156
9 7
93
190
66
4.9
32
3.3
1.2
26
1 5
103 1
Relative
Std Dev 3
233
33 '
38
3 6
39
7 7
60
55
7 4
2 7
26
32
36
66
59
100
Number of
Chlorines*
2
3
3
3
3-, 85%
|
4-1 75;i
4
3-1 70%
4J3G%
4
4-i 80%
5J 20%
4
5
5
4-> 10%
5 -I 30%
5
5-i 30%
6-J 70%
' 5-j 55%
6-1 75%
1 Data obtained from Webb and McCalls
2 Retention time relative to p.p'-DDE=100 Measuredfrom first appearance of solvent
3 Relative standard deviation of six analyses (as percentages of the mean of the results/.
* From CC/MS data Peaks containing mixtures of isomers of different numbers
are bracketed.
J able 8. Composition of Aroctor 7254'
Mean
/W7*
47
54
58
70
84
93
104
125
146
160
174
160
174
203
232
Total
Weight
Percent
62
2.9
1.4
132
17.3
7.5
13.6
15.0
10.4
1.3
84
1.3
8.4
1.8
1.0
100.0
Relative
Std. Dev.3
3.7
2.6
28
27
1.9
5.3
3.8
2.4
2.7
84
5.5
8.4
5.5
18.6
26.1
Number of
Chlorines*
4
4
4
4-i
i
5-1
5
5
5
51
6-1
5-j
6-1
6
6
6
5
6
7
25%
75%
70%
30%
30%
70%
1 Data obtained from Webb and McCall.6
2 Retention time relative to p.p'-DDE=l'00. Measuredfrom first appearance of solvent.
3 Relative standard deviation of six analyses fas percentages of the mean of the results).
* From GC/MS data. Peaks containing mixtures of isomers of different chlorine
numbers are bracketed
13
-------
Table 9. Compos*.
RRP
70
84
{98
777
725
746
760
774
203
(-232
1-244
2SO
332
372
448
528
Total
Pi'cert
2 7
4 7
38
33
723
14 1
49
124
93
9.8
77.0
4.2
4.0
.6
1 5
986
Relative
Sid Dev ]
63
1 6 '
35
67
33
36
22
2 7
40
34
2.4
5.0
8.6
25.3
102
Number of
Chlorines*
5
5
5 I 50%
6 •' 40%
6
5- 75%
6-f 85%
6
6-. 50%
7J 50%
6
6-1 70%
7-J 90%
61 70%5
7-190%
7
7
8
8
8
f
1 Data obtained from Webb and McCall.6
2 Retention time relative to p.p'-DD£=100 Measured fromfirst appearance of solvent.
Overlapping peaks that are quantitated as one peak are bracketed
3 Relative standard deviation of six analyses (as percentages of the mean of the results}
•> from CC/MS data Peaks containing mixtures of isomers of different chlorine
numbers are bracketed
^•Composition determined at the center of peak 104.
^Composition determined at the center of peak 232.
27
21
\
'
7
r
f ;
WN^,^ /
7
i
76
Ml
m
Column- 3% OV-1
Detector
Electron Capture
Column Temperature-
150°C.
|
I
I
28
A 3?
\32 l\40
v^x/N^
t 1
048
Time, mm
Figure 1. GaschromatogramofAro-
dor 7227
37
Column: 3% OV-1
Detector. Electron Capture
Column Temperature. 150°C.
O
Figure 2.
Time. min.
Gas chromatogram of Aroclor 1232.
14
€
-------
I
I
I
I
I
I
I
I
I
I
I
I
I
I
I
I
37
Column 3% OV-1
Detector Electron Capture
Column Temperature 770°C.
0 , 4 ! _*?/
~~~ Time, m'in
;' Figure 3. Gas chromatogram of A roclor 1242.
70
Column: 3% OV-1
Detector: Electron Capture.
Column Temperature 1 70°C.
0 4 8 12
Time, min.
Figure 4 Gas chromatogram of Aroctor 1248.
16
16
20
15
I
-------
I
I
I
I
I
I
I
I
I
I
I
I
I
I
I
I
I
I
Column 3%OV-!
Detector. Electron Capture.
Column Temperature 1 70°C.
04 8 12 16
Time. mm.
Figure 5. Gas chromaiogram of Aroclor J254.
20
24
28
Column: 3% OV-1
Detector: Electron Capture.
Column Temperature. 1 70°C.
146
280
8 12 16 20 24 28 32 36 40
528
Picture 6. Gas chromatogram of Aroclor 1260.
16
I
-------
I
I
I
I
I
I
I
I
I
I
I
Column 3% 0V- 1
Detector Hall 700-A
Program 720~C -6Z/Minute to 220°C.
146
c
H)
Si
72
76 20
24
28
Figure 7. Gas chromatogram of PCB locator mixture.
32
17
-------
I/
I
I
I
I
I
I
I
I
I
I
I
I
I
I
I
I
I
I
RRT of first peak <47?
NO'
Is there a distinct
peak with RRT 78>
RRT 47-58?
YES
\ NO
YES
Use 1242 for •
peaks < RRT 84
Use 1242 for
peaks < RRT 70
Use 1254
for peaks
jr, HfFi, f
-------
APPENDIX E
NEIC QUALITY ASSURANCE PROJECT PLAN
-------
QUALITY ASSURANCE PROGRAM PLAN
for the
NATIONAL ENFORCEMENT INVESTIGATIONS CENTER
OFFICE OF ENFORCEMENT
June 1987
-------
CONTENTS
SECTION
1. QUALITY ASSURANCE PROGRAM PLAN IDENTIFICATION AND APPROVAL FORM
2. INTRODUCTION
2.1 Background
2.2 Definitions
2.3 Purpose of the Document
2.4 NEIC Function
2.5 Organizational Chart
3. NEIC QA POLICY STATEMENT
4. QUALITY ASSURANCE MANAGEMENT
4.1 Assignment of Responsibility
4.2 Communication
4.3 QA Program Assessment
5. QUALITY ASSURANCE PERSONNEL
5.1 Quality Assurance Officer
5.2 Quality Assurance Division Representatives
5.3 Other Personnel
6. FACILITIES, EQUIPMENT, SUPPLIES AND SERVICES
6.1 Facilities and Equipment
6.2 Supplies
6.3 Services
7. DATA GENERATION
7.1 Project Requests
7.2 Background Review
7.3 Project Plan
7.4 Standard Operating Procedures
8. DATA PROCESSING
9. DATA QUALITY ASSESSMENT
9.1 Precision
9.2 Accuracy
9.3 Representativeness, Comparability and Completeness
10. CORRECTIVE ACTION
11. IMPLEMENTATION REQUIREMENTS AND SCHEDULE
-------
SECTION 1
QUALITY ASSURANCE PROGRAM PLAN IDENTIFICATION AND APPROVAL FORM
Document Title
Quality Assurance Program Plan
Organization Title National Enforcement Investigations Center
Address U.S. Environmental Protection Agency
Building 53
Denver Federal Center, Denver, CO 80225
Director Thomas P. Gallagher
Title Director, NEIC
Phone Number
236-5100
QA Officer Don Roche
Address
Phone Number
(same)
236-5122
(If different from organization)
Plan Coverage This QA Program Plan includes QA requirements pertinent to
all NEIC-conducted enforcement investigations in which data are generated.
This includes measurement activities in the Operations Division, Laboratory.
Services Division, Data Services Branch and the Technical Evaluation Staff.
Concurrences
(1) Name Don Roche
Title Quality Assurance Officer
Signature
Date
(2) Name Thomas P. Gallagher
Title Director, NEIC
Signature
Date 7 -
-------
Section No. 2
Revision No. 7
Date Q6/01/§7
Page 1 of 5
2. INTRODUCTION
2.1 Background
On May 30, 1979, the Administrator issued an EPA policy statement
requiring all Regional Offices, Program Offices, EPA laboratories
and the States to participate in a centrally managed Agency-wide
Quality Assurance (QA) Program. The responsibility for developing,
coordinating and directing the implementation of this program has
been delegated to the Office of Research and Development (ORD),
which has established the Quality Assurance Management Staff (QAMS)
for this purpose. The goal of the program is to ensure that all
environmentally related measurements which are funded or generated
by EPA mandate are scientifically valid, defensible and of known
precision and accuracy. On June 14, 1979, the Administrator signed
a memorandum extending QA requirements to all EPA extramural pro-
jects. On April 3, 1984, EPA Order 5360.1 established the policy
and program requirements for the conduct of Quality Assurance for
all environmentally related measurements performed by or for the
Agency.
Agency policy requires all EPA and EPA-supported monitoring pro-
grams to develop and implement QA plans covering all data-
generating activities within their organization. This document
is to provide guidance to NEIC personnel on implementation of an
internal QA program. The purpose of this plan is to ensure the
NEIC QA requirements are applied in a manner consistent with
Agency policy.
2.2 Definitions
For this plan, the following terms are defined:
2.2.1 Quality Assurance (QA): The total integrated program for
assuring the reliability of monitoring and measurement
data.
-------
Section No. 2
Revision No.~]T
Date Q6/Q1/37
Page 2 of 5
2.2.2 Quality Control (QC): The routine application of procedures
for obtaining prescribed standards of performance in the
monitoring and measurement process.
2.2.3 Representativeness: The degree to which data accurately and
precisely represent a characteristic of a population, param-
eter variations at the sampling point or an environmental
condition.
2.2.4 Standard Operating Procedure: An operation, analysis, or
action whose mechanics are thoroughly prescribed and
documented and which is commonly accepted as the usual or
normal method for performing certain routine or repetitive
tasks.
2-2-5 Accuracy: The degree of agreement of a measurement with
an accepted reference of true value. Accuracy is expressed
as (1) the difference between the two values, (2) a percent-
age of the reference or true value or (3) a ration of the
two values.
2.2.6 Audit: A systematic check to determine the quality of
operation of some function or activity. Audits may be of
two basic types: (1) performance audits in which
quantitative or qualitative data are independently obtained
for comparison with routinely obtained data in a measurement,
or (2) systems audits of a qualitative nature that consist
of an onsite review of a laboratory's quality assurance
system and physical facilities for sampling, calibration
and measurement.
2.2.7 Comparability: A measure of the confidence with which one
data set can be compared to another.
-------
Section No. 2
Revision No. 7
Date 06/01/57
Page 3 of 5
2.2.8 Completeness: A measure of the amount of valid data
obtained from a measurement system compared to the amount
that was expected to be obtained under normal circumstances.
2.2.9 Precision: The degree of agreement between repeated meas-
urements of one property using the same method or technique.
2.3 Purpose of the Document
This document is the Quality Assurance Program Plan for the
National Enforcement Investigations Center (NEIC). It provides
the Agency QA policy and planning requirements for enforcement
investigations conducted by NEIC. It describes the NEIC QA or-
ganization and function in relation to the Agency and in relation
to NEIC managers and investigators.
2.4 NEIC Function
The National Enforcement Investigations Center, under super-
vision of the Director, serves as the principal source of expertise
involving civil and criminal litigation support for complex inves-
tigations and other support having national and/or significant
Regional impact on EPA and State regulatory programs for air,
water toxic, pesticides, radiation and solid waste pollution con-
trol. In coordination with the Assistant Administrator for
Enforcement and Compliance Monitoring or General Counsel, Regional
Offices, and other EPA Program Directors and their staffs, plans,
develops and provides evidence and information interpretation for
case preparations in all program areas. NEIC maintains an expert
staff of criminal investigators and provides procedural technical
training for criminal investigation activities in all Regional
offices. The Center manages the Agency's criminal investigations
on a national basis and provides expertise and guidance to the
Office of Enforcement and Compliance Monitoring for the development
of multi-medial enforcement strategies and evidence management.
-------
Section No. 2
Revision Mo.7
Date 06/01/87
Page 4 of 5
NEIC provides national expertise to Headquarters and Regional
Offices of EPA and the Department of Justice in evaluating a broad
range of waste disposal and emissions problems, monitoring technol-
ogy and remedial programs not normally available on Regional staffs.
The Center maintains expert staff and sophisticated equipment
capabilities for conducting complex special, continuing and emer-
gency response to civil and criminal investigations in any of the
above areas. The Center's primary responsibilities include assur-
ing the adequacy and validity of scientific and technical evidence,
including data collection and analyses, and review and development
of analytical techniques, methodologies, and computer information
systems; providing quick response services in emergency situations;
applying enforcement strategies in coordination with the Office
of Enforcement and Compliance Monitoring and the Regional Counsels,
providing consultation and assistance in case preparation activi-
ties; providing management, training and specialized assistance
to Regional Offices on criminal investigations; and providing
expert testimony on a wide variety of specialized subjects in
support of enforcement actions. In addition, the Center serves
as a point of coordination with the staffs of other Assistant
Administrators for the preparation, assembly, and analysis of
scientific data and with Regional Administrators in providing
support and training for Federal, State and local personnel and
with other Federal, State or local agencies involved with civil
and criminal case preparations. Prepares reports, manuals, and
other publications necessary to the above.
-------
1/5
C
. c
1
1
<5
o>
OC |
LU Q.
CC en
Of
o
>-
Z LU
2 -
U ii ®
0 35 *
r «5
o
tr
g|
LU §
Q <-"
H 1
J CQ
Q. O
iy
0
_
1
ECTOH
GAIIONS
nge
Ii- 2
< - »
co Z ~>
O
1
OH PLANNING
EMENT
Harp
M i«»
UJ 7
I| |
-r*
U)
DIRECTOR
V SERVICES
0 Meiggs
ASSISTANT
LABOHATOR
Theodore
DIRECTOR
iTlONS
Glllespw
ASSISTANT
OPEH/
William M
^J ,
> s
z =
JJ •-
i °;
i 1 1 i
Ol U
Z J
£ CC S>
> S £
Q y
ul
U.
o
u_
WASHINGTON ST/
C/5
i
5 i
Si l1
v- < ID
!
j
= i ' S
O O» | ± T]
«r c i ^ -i
SI : #5
: ° s 1 3 5 2
§^ gs :i§ 3 i :
^s §1 = l 5 3 |
m ° 2 ^ 5 ^ I
LU * •** V* Ziifl fl
1 J 1
j j j
1 Zi
| a "i *
Z 2 O i5 LU ^
O SQ > U C
P « 2l Z 3
I ° |s|
§ §s
^
U
S«-
(J UJ -f
i=o •*•
00 Z U.
"s s
u. m (5
UJ 3
I«5
uo
X
O
ll r si s
< UJ J —JO. LU
i§i §12 ii
al 1 aisi 1 =2
i
-------
Section No. 3
Revision No. 7
Date 06/01757
Page 1 of 2
3. NEIC QA POLICY STATEMENT
It is the policy of the National Enforcement Investigations Center
(NEIC) that the program of quality assurance will be appropriate to ensure
that data collected are scientifically valid and of known and documented
quality. QA Program requirements cover all activities performed, supported
or required by NEIC which generate environmentally related measurement data.
This includes all field and/or laboratory data, whether for enforcement or
regulation development purposes. It includes activities conducted through
contracts and interagency agreements.
The NEIC Director has the overall responsibility for implementation of
the Agency's mandatory QA Program within the Center. The authority and
responsibility for directing QA activities within NEIC are delegated to the
QA Officer (QAO) and include all areas covered by this QA Program plan.
Measurement activities within NEIC shall be performed in accordance
with project plans. The project plans contain QA requirements for the study.
The QA Program of NEIC shall provide that:
1. The QAO will be the authority for all QA matters within NEIC will
provide liaison with the QAMS to ensure that Agency QA requirements
are met.
2. The QA Program will be carried out by personnel knowledgeable QA
theory and practice.
3. Each Division Director will appoint a QA Representative to assist
the QAO in implementing the NEIC QA policy.
4. Facilities, equipment and services which impact data quality or
integrity shall be routinely inspected and maintained.
-------
Section No. 3
Revision No. 7
Date 06/01787
Page 2 of 2
5. Data generated by, or for, NEIC must meet the following
requirements:
a. Field and analytical methods and procedures used in measure-
ment and monitoring efforts will conform to EPA-approved
methodology when available. All measurement methods will be
fully documented and include quality control procedures.
b. Project Plans and Standard Operating Procedures (SOP),
approved by NEIC will be developed prior to and implemented
for NEIC projects.
c. Data quality objectives will be determined for all data col-
lection efforts.
d. Reported data will include, when appropriate and possible,
statements of precision, accuracy, representativeness, com-
pleteness, and comparability.
6. Data processing procedures will be documented, reviewed, and
revised as required to meet NEIC's data quality requirements.
7. The QAO, working with Division QA Representatives, will initiate
corrective QA actions.
8. The QAO will report to the NEIC and QAMS management on QA progress,
problems, and data quality assessments.
9. This QA Program Plan will be reviewed annually by the QAO and
updated as required.
-------
Section No. 4
Revision No.7
Date 06/01/57
Page 1 of 5
4. QUALITY ASSURANCE MANAGEMENT
4.1 Assignment of Responsibility
4.1.1 NEIC Director
The Director has overall responsibility for all NEIC
activities, including quality assurance. Because the suc-
cess of the QA Program ultimately depends on the Director's
full support of QA management, it is his responsibility to
enlist and encourage the cooperation of all NEIC personnel
in the program.
4.1.2 Quality Assurance Officer
The QAO has primary responsibility for all QA activities.
His responsibilities include the development, evaluation
and documentation of QA policy and procedures at NEIC.
The QAO reports directly to the Deputy Director, NEIC
(organizational chart 2.5).
The QAO assesses the progress and status of the Center QA
Program, identifies specific needs (e.g., methods develop-
ment and problem areas), and recommends specific courses
of action for strengthening the program. The QAO initi-
ates development of NEIC QA guidelines and procedures, is
responsible for the development of audit programs, and is
available to consult with and recommend to the NEIC profes-
sional staff appropriate and necessary QA methods and plans
for ensuring the quality of the data produced.
4.1.3 Quality Assurance Representatives
Each division director designates a QA Representative to
assist the QAO with the NEIC QA Program. The QA
Representatives
-------
Section No. £
Revision No. 7
Date 06/01/87
Page 2 of 5
recommend and review proposals for improvements in QA
policies and procedures and evaluate potential data quality
problem areas. The Representatives consult on matters of
quality assurance specific to their Division, serving as a
source of information on quality assurance matters and
helping to implement the NEIC QA Program within the divis-
ion. The QA Representative is the primary source of infor-
mation on QA policy for the Division.
4.1.4 Technical Management
Each organizational unit is responsible for the technical
quality of the data produced and for developing and docu-
menting QC procedures for the measurement operations it
performs.
4.2 Communication
A system of communication and periodic reporting of QA program
status needs will be initiated to ensure that effective QA programs
are established and maintained within NEIC. In this system, the
QA Officer and Representatives will report to the appropriate
level individual. The QA Officer and Representatives shall keep
responsible management informed of the performance of the data
production system and of related QA problems and needs to ensure
their resolutions.
The overall lines of communication in the QA Program will
generally be organized as described:
a. The QA Management Staff (QAMS) in ORD is the Agency focal
point for all QA program information. QAMS is responsible
for developing guidelines and criteria for the Agency-wide
QA Program and coordinating its implementation. QAMS will
-------
Section No. 4
Revision No.7
Date 06/01/17
Page 3 of 5
provide guidance and assistance to NEIC in specific areas of
QA, as requested, and serve as a source of information on
new methods and equipment for use in QA activities as they
become designated for EPA use. QAMS will provide current
information to NEIC on QA-associated activities in government
agencies, technical societies and the private sector.
QAMS will provide NEIC with results of performance studies
or onsite inspections they conduct. NEIC will also receive
copies of any reports generated by QAMS containing statements
regarding quality assurance and data quality at NEIC.
b. The NEIC QA Officer will coordinate with QAMS in ORD on QA
program matters such as program status, program direction
and guidance, problem and needs identification and need for
technical QA assistance. The NEIC QAO will submit an annual
QA report to QAMS and NEIC management. NEIC QA reports will
contain:
General status of the NEIC QA Program
Changes in the NEIC QA Program Plans and SOPs
Status of QA Project Plans
Data quality assessments, to include:
Accuracy
Precision
Completeness
Representativeness
Comparability
Significant QA progress, plans and recommendations
c. Within NEIC, the Division QA Representatives will exchange
information with the QA Officer on the status, problems,
needs, requests for assistance, etc., of QA activities. This
will include providing the necessary information to the NEIC
QA Officer to assist in the development of the annual NEIC
QA Program Status Reports. Additionally, the QA Representa-
tives within the NEIC will keep managers informed of QA
-------
Section No. 4
Revision No.7
Date 06/01/57
Page 4 of 5
program status, problems, needs, etc. Based on information
received from the Division QA Representatives, the QAMS in
ORD and Regional QA Officers, the NEIC QA Officer shall take
appropriate actions as necessary (actions might be: from the
distribution of routine information, the development and
implementation of QA program changes, etc.).
d. NEIC will participate in appropriate QA performance evaluation
(PE) studies. These include but are not limited to:
Method 5 dry gas meter
Water Pollution performance Studies (WP)
Method 3 ORSAT
4.3 QA Program Assessment
Several activities are necessary to ensure an adequate system of
QA program operation. These include reviews and audits as out-
lined below.
a. Review of Program and Project Plans: Existing programs,
future programs, project plans and extramural procurements
will be reviewed by the QA Officer. These reviews will ensure
that QA/QC activities and requirements are included in the
packages and that proper QA was considered at the project's
inception.
b. External Reviews/Audits of Performance: NEIC Divisions will
participate in an internal monitoring program including
external QA reviews or audits of performance. Systems and
performance audits and comparison studies shall be conducted
as arranged by the Division QA Representative, the Division
Director, the NEIC QA Officer and the QAMS. These audits
will assess the adequacy of, and adherence, to the NEIC QA
Program Plan and Standard Operating Procedures. QAMS will
provide assistance in guiding and conducting these audits.
-------
Section No. 4
Revision No. 7
Date 06/01/57
Page 5 of 5
The QAMS in ORD has the overall responsibility for the
operation of the Agency's external laboratory performance
evaluation program (including performance audits, inter!abo-
ratory comparison studies, methods evaluation studies and
onsite inspections of certain laboratories).
c. Internal Audits of Performance: The NEIC QAO and Division
Representatives will conduct internal systems audits to assess
the adequacy of, and adherence to, the NEIC QA Program Plan
and Standard Operating Procedures.
-------
Section No. 5
Revision No. 7
Date 06/01/57
Page 1 of 1
5. QUALITY ASSURANCE PERSONNEL
5.1 Quality Assurance Officer
The QAO for NEIC meets the following qualifications:
Sufficient professional and administrative stature to deal
effectively with project officers, program managers and
organizational Directors
Active involvement in QA activities, participation in relevant
services and professional meetings
Knowledge of appropriate Federal laws, Agency regulations
and guidelines for QA requirements
Effectiveness in meeting and dealing with the general public,
private industry and officals of Federal, State and local
agencies
5.2 Quality Assurance Division Representatives
Quality Assurance Representatives will implement the QA Program
within their division and assure that problems arising in the
conduct of QA/QC will be promptly and effectively addressed.
5.3 Other Personnel
All personnel involved in monitoring/related activities will
possess an adequate technical knowledge of their duties. This
knowledge may have been acquired through formal education, train-
ing and/or experience. Training programs will be administered as
necessary and may include courses or seminars, workshops, profes-
sional meetings or on-the-job training.
-------
Section No. 6
Revision No. 7
Date 06/01/87
Page 1 of 3
6. FACILITIES, EQUIPMENT, SUPPLIES AND SERVICES
The requirements for all NEIC supported facilities, equipment, sup-
plies and services are determined by the kinds of measurements made in a
particular task or project and the specific objectives (both technical and
QA) of the program. Evaluation of task-specific facilities, equipment,
supplies and services is the responsibility of the Management, senior staff
and Project Coordinators.
The following subsections apply to all NEIC facilities, equipment,
supplies and services.
6.1 Facilities and Equipment
6.1.1 Evaluation
The suitability of a facility for the execution of both
the technical and QA aspects of a task may be assessed
prior to its use through a systems audit. These audits
shall ascertain whether facilities are of adequate size,
with satisfactory lighting, ventilation, temperature, noise
levels, and humidity, and are operationally consistent
with their designed purpose.
General laboratory and field equipment must be present in
sufficient quantity and condition and operationally consis-
tent with their intended use to provide for the generation
and processing of environmental data resulting in known
and documented quality and integrity.
Equipment is evaluated prior to use for its applicability
to the NEIC task. Acceptance testing for new equipment is
performed on an item-by-item basis and is documented for
comparison with future testing. Ongoing evaluation of
equipment and facilities is provided by periodic systems
audits.
-------
Section No. 5
Revision No.7
Date 06/01/57
Page 2 of 3
6.1.2 Inspection and Maintenance
To ensure consistently high data quality in the NEIC QA
Program, a plan for routine inspection and preventive main-
tenance (PM) is followed for all facilities and equipment.
Scheduling of a particular PM program is based on the iden-
tification of critical components that are most likely to
fail without PM and the overall effect of equipment failures,
Maintenance activities shall be performed by qualified
personnel using accepted, documented procedures according
to a PM plan or Standard Operating Procedure.
Documentation of maintenance is essential to monitoring
and documenting data quality. Permanent records of the
maintenance histories of facilities and equipment, includ-
ing detailed descriptions of adjustments made, parts
replaced, etc., shall be kept in bound notebooks, dated
and signed.
6.2 Supplies
An acceptance testing program for expendable supplies shall be
applied. Analysis of blanks, reference standards or other suitable
measurement techniques will be used to determine acceptability.
Thereafter, the expendable supplies will be reordered from the
same manufacturer and retested as necessary. Following successful
completion of the acceptance test, an expiration date is marked
on each container, and it is stored on a first-in first-out basis.
Containers are stored to protect the integrity of the material
and protect personnel from harmful exposures.
A permanent record of acceptance test procedures is maintained.
-------
Section No. 5
Revision No. __7
Date 06/01/87
Page 3 of 3
6.3 Services
The reliability and quality of services provided (e.g., analytical
services, audit services, balance maintenance) shall be documented
and a record maintained. Evaluation of services is accomplished
by appropriate systems or performance audits.
-------
Section No. ^
Revision No. 7
Date 06/01/87
Page 1 of 8
7. DATA GENERATION
Adequate QA must be applied throughout the entire monitoring process
to ensure that the data which are produced are of known and acceptable qual-
ity. It is important that numerous essential QA "elements" be incorporated
into the several major activities/steps of the monitoring process. Those
QA elements which are to be implemented for monitoring activities are out-
lined below. The specific requirements applicable to these QA elements
will be described in Project Plans and/or SOPs which are prepared for NEIC
measurement activities.
The projects undertaken by NEIC span a wide variety of activities,
from one employee performing technical, supportive or administrative tasks,
to numerous employees from divergent disciplines working as a team to ac-
complish a series of complex tasks. Most of the Center's projects consist
of these phases:
Project Request
Background Review
Project Plan
Project Activities
Report
Followup
7.1 Project Requests
All NEIC projects are preceded by requests to the Director for
work to be performed. Many requests received by NEIC for techni-
cal assistance involve projects which require extensive field
work on pollution problems in more than one medium. Others include,
for example, a technical and/or legal review of an abatement pro-
posal or analytical support for a regional enforcement case.
The content of the project request is essential to the success of
the project. To assure that NEIC is as responsive as possible,
it will consider informal requests from sources within the Agency.
To the extent possible, NEIC will press for each request to be
-------
Section No. 7
Revision No. 7
Date _ 06/01/87
Page 2 of 8
confirmed in writing detailing the project objectives, relating
those objectives to a civil enforcement action and identifying
the requester's contact. When this is not practical or possible,
then the Director or Assistant Director, as appropriate, will
write a memo to the requester confirming and outlining the essen-
tial details.
The nature of environmental criminal investigations and the sources
of information concerning criminal activity make it impractical
to require a written request for project initiation. NEIC criminal
project procedures are described in the NEIC Special Agent Manual.
Official requests for technical assistance will be accepted from
the following:
Administrator
Deputy Administrator
Assistant Administrators
Senior Enforcement Counsel
Inspector General ) with the knowledge and concur-
Headquarters Office Directors ) rence of the Assistant Admin-
Headquarters Division Directors ) istrator for Enforcement and
Department of Justice, Headquarters ) Compliance Monitoring
Regional Administrators
Deputy Regional Administrators
Regional Counsel
Regional Division Directors ) with the knowledge and
U.S. Attorney's Offices ) concurrence of the
State and Local Program Directors ) Regional Counsel
Receipt of an official request will be acknowledged by NEIC memo-
randum to the Enforcement Counsel or the appropriate Regional
Counsel and copies sent to individuals identified by the requester.
The acceptance will include a tentative schedule for completing
the work and is usually sent before any work begins. It desig-
nates specific NEIC employees as contacts for technical work and
legal coordination, and seeks access to all files related to the
work. In some cases (e.g..requests for technical support or review
-------
Section No. 7
Revision No.7
Date 06/01/87
Page 3 of 8
of an abatement proposal), the acknowledgement memorandum can
provide a sufficient outline of work activity.
To accomplish the objectives of a request efficiently and effect-
ively, a Project Coordinator is usually named. The selection of
this individual is generally determined by the type of investiga-
tion or assistance requested, such as: a multi-media evaluation
with or without sampling, case preparation, performance audit,
pesticide use investigation or control technology assessment. In
some instances, a technical assistance request may involve only
one individual, for example, a detailed control technology assess-
ment; or it may involve only analytical support, such as pesticide
analyses for regional investigations; or it may require support
from several Branches within NEIC.
The scope of the request determines which NEIC organizational
elements will be required to support the proposed study. Opera-
tions, Laboratory Services, or the Planning and Management staff
may assign individuals to the project. The Project Coordinator
is designated and is then responsible for assuring that all aspects
of the project are completed. This individual will have demon-
strated, through past performance as Project Coordinator or as an
assistant, the ability to perform the extensive administrative
and technical responsibilities of the Project Coordinator.
7.2 Background Review
Review of the available background information applicable to a
specific project is a logical and essential first step in provid-
ing technical assistance. Scope and duration of the background
review are related to the project objectives and vary with the
complexity of the project request. Background information is
available at the Center through the in-house and affiliated librar-
ies and the NEIC computerized data retrieval systems; however,
for many projects it will be necessary to make visits to EPA
-------
Section No. 7
Revision No. 7
Date 06/01/87
Page 4 of 8
headquarters, Regional offices, and/or State and local agencies
to review and obtain copies of pertinent files. Where necessary,
a reconnaissance of the project site provides background verifi-
cation or updating. Examples of information obtained during a
background review include: the applicable laws and regulations,
the status of current and pending litigation related to the proj-
ect, Regional Office legal strategy and how the NEIC study relates
to the strategy, specific description of related process and pol-
lution control systems, copies of relevant source permits and
compliance schedules, past self-monitoring data, prior government
or facility studies, and availability of approved analytical
methods.
The primary purpose of a review is to familiarize NEIC personnel
with the background of the work request and its legal ramifica-
tions so that a comprehensive project plan can be developed.
Moreover, information obtained during the review will often be
used during project performance and report preparation. Therefore,
it is important to conduct as thorough a review as possible early
in the project development. The background review may even con-
tinue throughout the project to obtain needed information.
7.3 Project Plan
A general project outline is included with NEIC acceptance of an
official request. After sufficient background information has
been obtained and evaluated, a more detailed project plan is pre-
pared based on the specific objectives and tasks in the project
request. For projects that are small in scope, the acceptance
memorandum may serve as the project plan. Projects such as com-
plex pollution control evaluation, permit compliance evaluations,
air pollution source surveys, ambient air and/or receiving water
quality surveys, pesticide use investigations, and solid/hazardous
waste disposal evaluations normally require a detailed project
plan. It is NEIC policy that civil enforcement and technical
-------
Section No. 7
Revision No.7
Date 06/01/87
Page 5 of 8
assistance projects will have a project plan. Any exceptions to
this requirement must be approved by the Director or Deputy
Director. Procedures to be used for criminal projects are
described in NEIC's Special Agent Manual. In selected cases, the
Director or Deputy Director may determine that is is desirable to
restrict the internal and/or external distribution of a project
plan.
The Project Coordinator prepares the project plan detailing the
project's scope, logistics and schedules. Items addressed in the
project plan include:
1. Objectives
2. Background information, including a summary of pro-
cess(es), applicable regulations or permit conditions,
etc.
3. Survey methods, including sampling locations, schedules
and procedures, analytical requirements, quality control
program, etc.
4. Process data to be collected
5. Personnel and equipment requirements
6. Safety program and equipment
7. Custody and document control procedures
8. Report target dates
9. Followup plans (when necessary)
The Project Coordinator works closely with the appropriate NEIC
staff to determine items such as equipment and logistical require-
ments, analytical capabilities and personnel availability. The
Project Coordinator also communicates with the requester or desig-
nated representative to ensure that the plan being developed
addresses the tasks requested and focuses on the objectives.
-------
Section No. 7
Revision No. 7
Date 06/01/57
Page 6 of 8~
The plan approximates an agreement between the requesting party
and those individuals performing the work. Manpower, equipment
needs and logistics can be forecast and scheduled. Additional
equipment, contract services or personnel can be secured expedi-
tiously with the advance determination of needs.
The project plan should be provided by NEIC to the requester and
the survey team at least 2 weeks before any specific field, labor-
atory, or consultant activity is undertaken. If no comments on
the plan are received from the requester during this period, it
is assumed that the plan is acceptable. Changes made to the
project plan will be coordinated with the requester and the Deputy
Director or Assistant Director. If necessary, a meeting will be
held between the appropriate NEIC personnel and the requester to
discuss any differences and modifications. Once all concerned
parties agree to the project plan, it serves as a reference docu-
ment for the project; however, during the conduct of the project,
some modifications to the plan may be deemed necessary by NEIC
personnel when unforeseen circumstances arise.* After the com-
mencement of project activities, requests for significant changes
will be directed to the NEIC Director. Requested changes will be
discussed with the appropriate management and supervisory staff
and with the Project Coordinator. The significant changes will
be documented.
The QAO will review all NEIC project plans to assure that appro-
nriat.o flA is i nrnrnnrat.prl
priate QA is incorporated
The plan will contain a. statement that it is subject to change.
-------
Section No. 7
Revision No. 7
Date 06/01/87
Page 7 of 8
7.4 Standard Operating Procedures
Sections on Project Plans describing routine tasks which do not
vary with different environmental studies will be written as
Standard Operating Procedures. They will be sufficiently complete
and detailed to ensure:
Data of known quality and integrity are generated to meet
measurement objectives
The minimum loss of data due to out-of-control conditions
Standard Operating Procedures will be:
Adequate to establish traceability of standards, instrumenta-
tion, samples and environmental data
Consistent with sound scientific/engineering principles
Consistent with current EPA regulations and guidelines,
including the proposed Good Laboratory Practices (Federal
Register, 44(92), Wed., May 9, 1979, pp. 27369-27375)
Consistent with the instrument manufacturer's specific
instruction manuals
Standard Operating Procedures will provide for documentation suffi-
ciently complete to:
Record the performance of all tasks and their results
Explain the cause of missing data
Demonstrate the validation of data each time they are recorded,
calculated, or transcribed
To accomplish these objectives, Standard Operating Procedures
will address the following areas:
1. Sampling and analytical methodology
2. Special precautions, such as holding times and preservation
3. Federal reference, equivalent, and alternate test procedures
4. Instrumentation selection and use
5. Calibration and standardization
-------
Section No. J_
Revision No.7
Date 06/01/87
Page 8 of 8
6. Preventive and remedial maintenance
7. Replicate sampling and analysis
8. Blind and spiked samples
9. Quality control procedures such as inter and intralaboratory
or field activities
10. Documentation
11. Sample custody and handling procedures
12. Sample transportation
13. Data handling/evaluation procedures
14. Service contracts
15. Precision, accuracy, completeness, representativeness and
comparabi1ity
16. Document control/Chain-of-Custody
Measurement activities will adhere to established EPA regulations
and guidelines and NEIC Standard Operating Procedures. Deviations
will be justified and documented. Adherence to approved Standard
Operating Procedures will be determined during systems audits.
Standard Operating Procedures will be updated as needed. In
selected cases, the Director or Deputy Director may determine
that it is desirable to restrict the internal/external distribution
of a Standard Operating Procedures Manual. The Director, Deputy
Director or their designee will be notified of all external requests
for NEIC Standard Operating Procedures Manuals.
-------
Section No. 8
Revision No. 7
Date 06/01/87
Page 1 of 2
8. DATA PROCESSING
Adequate precautions must be taken during the reduction and storage of
data to prevent introducing errors or the loss or misinterpretation of the
data.
a. Checks will be made at data handling points between the analysts
determining the data values and the individual entering the data
into the data storage system.
All data must be recorded clearly and accurately on field
notebooks or laboratory bench data sheets.
All data must be transferred and reduced from field notebooks
and bench sheets completely and accurately.
All field and bench records will be retained in permanent
files.
Whenever possible, data will be organized into standard
formats.
b. A data storage and information system will be used. This system
will be capable of:
Receiving all entered data
Screening and validating data to identify and reject outliers
or errors
Preparing, sorting and entering all data into the data storage
files (which are either computerized or manual)
Providing all stored data points with associated QA/QC
"labels" which can indicate the level of confidence or quality
of the data These labels should possess the capability of:
Indicating what QA/QC activities were included in the
major steps of the monitoring process
Quantitatively describing the precision/accuracy of the
analysis
-------
Section No. 3
Revision No. 7
Date 06/01/57
Page 2 of 2
Making data available to users as required. Specific
requirements and procedures for the above aspects of
data processing will be described in Standard Operating
Procedures.
-------
Section No. 9
Revision No. 7
Date 06/01/87
Page 1 of 2"
9. DATA QUALITY ASSESSMENT
The quality of measurement data generated and processed will be assessed
for precision, accuracy, representativeness, comparability and completeness
based upon Standard Operating Procedures and available external measures of
quality (e.g., audit materials).
EPA-approved and/or best available methodology will be used for data
quality assessment. For many measurements of NEIC, suitable methodology
must be developed and verified.
Aspects of data quality which will be addressed are:
9.1 Precision
Standard Operating Procedures will contain a mechanism for demon-
strating the reproducibility of each measurement process. Examples
of activities to assess precision are: replicate samples, colo-
cated monitors and instrument checks.
9.2 Accuracy
Standard Operating Procedures will contain mechanisms for demon-
strating the relationship of the reported data compared to the
"true" value(s).
9.2.1 Traceability of Instrumentation
Each measurement device will be assigned a unique identifi-
cation number. Documentation shall identify the specific
measurement device and where and when used for calibration.
-------
Section No. 8
Revision No.7
Date 06/01/57
Page 2 of 2
9.2.2 Traceability of Standards
Standard and each measurement device will be calibrated
against a standard of known and higher accuracy when pos-
sible. Calibration standards will be traceable to available
standards of the National Bureau of Standards (NBS). If
NBS standards are not available, other available validated
(primary) standards will be used,
9.2.3 Traceability of Data
Data will be documented to allow complete reconstruction,
from initial field records through data storage system
retrieval.
9.2.4 Methodology
If available, Federal reference, equivalent, or approved
alternate test methods will be used. Other methodology
must be fully documented and justified.
9.2.5 Reference or Spiked Samples
Recoveries shall be within predetermined acceptance limits.
Unacceptable recoveries are identified and documented.
9.2.6 Performance Audits
NEIC will participate in EPA Performance Audit Programs.
9.3 Representativeness, Comparability and Completeness
Where appropriate, statements on Representativeness, Comparability,
and Completeness will be included.
-------
Section No. 10
Revision No. _7
Date 06/01/87
Page 1 of 1
10. CORRECTIVE ACTION
The QAO will be informed by Division QA representatives if data falls
below required, specified limits. Early and effective corrective action
will be taken and results reported to the appropriate management authority.
Corrective action shall be minimized through the development and imple-
mentation of routine internal program controls prior to an adverse program
impact. Examples of controls include:
1. Each measurement system (e.g., instrument) shall have specified
operating limitations.
2. A procedure shall be established for each measurement system to
identify the corrective action which will be taken when the warn-
ing or control limits are exceeded.
3. For each measurement system, the level within the organization
responsible for taking corrective action, and also the level
within the organization responsible for approving corrective
action, shall be clearly stated.
Results of the following QA activities may also initiate corrective
actions:
Performance audits
Systems audits
Interlaboratory comparison studies
-------
Section No. 11
Revision No. 7
Date 06/01/57
Page 1 of 1
11. IMPLEMENTATION REQUIREMENTS AND SCHEDULE
Implementation of the EPA Quality Assurance Program requires that
milestones be identified and schedules set for accomplishment. Milestone
progress in the NEIC QA Program will be reported to QAMS.
Item
Date
Review and update NEIC QA Program Plan 05/01/88
Review and update NEIC Standard Operating Procedures 05/01/88
Evaluate needs for additional Standard Operating 05/01/88
Procedures
Provide QA review of data transmittals and project plans Ongoing
Monitor the operational performance of NEIC through Ongoing
appropriate intra-laboratory and inter-laboratory
quality evaluation programs
Identify routine measurement methods for inclusion in Ongoing
the audit program
-------
APPENDIX F
EPA QUALITY CONTROL GUIDELINES
-------
M£rHQD DETECTION LLMIT FOR CHEMICAL
AND PHYSICAL MEASUREMENTS
Issued by
Duality Assurance Management and Special Studies Staff
Office of Monitoring Systems and Quality Assurance
Office of Researcn and Development
United States Environmental Protection Agency
Washington, D.C.' 2C^cO
March 30, 1
-------
. .-\3i_L u," ..^n i 1,1
ect- on age \c.
5.5 A CASE ST'JCY (14 pages) i
5.5.1 Witnin-Lot Summaries 2 of 14
5.5.2 Between-Lot Summaries 2 of 14
5.5.3 Regression Summaries ana Reporting
Requirements for a Project or Time Period 7 of 14
5.7 SOURCES OF ADDITIONAL INFORMATION (6 pages) 1
5.7.1 Study Planning 1 of 5
5.7.2 Sampling 1 of 6
5.7.3 Assessment of Precision 2 of 6
5.7.4 Assessment of Bias 3 of 5
5.7.5 Use of Control Charts 4 of 6
5.7.6 Method Detection Limit 5 of 6
5.3 A GLOSSARY OF TERMS (3 pages) 1
5.9 RECOMMENDED FORMATS FOR REPORTING DATA
QUALITY (2 pages)
-------
No.
5-4 Summary Regressions for Sulfate
Analysis of Data from Prepared Solutions,
Seoorting Perioa July, 1980 tnrougn
Decemoer, 1930 5.5 9 of 14
5-5 Measurement Data for Sulfate Filter
Samples 5.6 11 of 14
5-6 Summary Regressions for Sulfate Analysis
of Filter Data, Reporting Period August,
1930 to December, 1980 5.6 12 of 14
-------
" a>.e ' z~
= £t'~afn3- cat a Duality, i.e., 01=3, precision, anc V3L. Tne oroce-
c-~es -iscussec in tr.is guideline are oasea on tne assumption tnat
~easjrenent errors for cnemical anc onysical measurement systems are
normally or near normally distributee. It is stressed tnat for partic-
ular situations wnere tms aoes not appear to oe a valia assumption or
wnere proolems occur outside tne scope of tr.is guideline, 6.5., as now
to treat outliers, tne acvice of a qualified statistician should oe
O3tainea.
b.1.3 Application
Application of these procedures involves assessments of precision,
bias and MDL based on special measurements (hereafter referred to as
data quality assessments) of samples of known composition (e.g., refer-
ence materials, spiked samples, blanks) or of unknown composition
(e.g., replicate study samples or repeated analyses of stuay samples)
interspersed throughout the periods of routine operation of the
measurement system. Generally, study samples are received for analysis
in batches or lots (use of the term lots applies to any set or suosets
of data obtained from a study project or monitoring program) and data
quality assessments are made during the course'of analysis of the study
samples in tne lot. Application of the data quality assessments to tne
measurements for the complete sample lot or groups of lots is based on
the assumption that all measurements, including the data quality
measurements, are made with the measurement system "in statistical con-
trol". A measurement system is considered to be in statistical control
wnen its variability is due only to chance causes. Data quality
assessment results used with control charts (Appendix H, ref. 13 of
Section b.7.5) or statistical techniques sucn as the construction of
frequency distributions (Chapter 3, ref. 4 of Section 5.7.5) may be
used to assure that the measurement system is in statistical control.
The statistical measures of data quality prescribed in this chap-
ter should be used in conjunction with archived information on the
operational capability of measurement systems "Compilation of Data
Quality Information for Environmental Measurement Systems", (ref. 1,
Section 5.7.1) in the development of Quality Assurance Project Plans
for EPA environmental measurement programs as required in QAMS-005/80
(ref. 2 of Section 5.7.1).
-------
,"e onicipdl incicatcrs of cata ^uanty are oias anc precis';:".
Bias is systematic er-or. Precision involves tne closeness of
cata values to eacn otner. Accuracy involves closeness of meas^re-
rnents to a reference value ana incorporates both oias and precision.
To formalize these definitions, sone Dasic statistical concepts are
presentee and discusses in tne ensuing paragraphs.
It is reiterated nere tnat tnis cnapter is concerned witn tne
error distributions of the measurement system and not tne distribu-
tions of the chemical and/or physical measurements from a study project
or a monitoring program. The assessments of precision and bias, do,
however, apply to the measurements from a study project or monitoring
program. All statistical concepts and analyses involve the use of data
quality assessments obtained for the specific purposes of estimating
aata quality, i.e., bias, precision, and MDL.
5.2.1 Sample Statistics and Population Parameters
5.2.1.1 Sample Statistics—
If a quantity X (e.g., a concentration) is measured n times, it is
customary to refer to the values Xj, X2, . . . Xn so obtained as
a sample of size n of measurements of X. (It should be clear
throughout the text from the context whether the word "sample" is used
in tnis statistical sense or refers to, e.g., a chemical sample.)
Values obtained in the calculation of quantities which summarize data
of this kind are summary statistics or sample statistics.
More specifically, let X^, X£, . . ., Xn be a set of independent
data quality assessments taken under fixed and prescribed experimental
conditions and regarded as a random sample from some population. For
many.applications the X^ are considered measurements aimed at esti-
mating a reference or true value T. Some basic statistics for a sample
of size n are:
o the sample average X * (X]_ + ... + Xn)/n Eq. 5-1
o the sample bias B - X - T Eq. 5-2
I
o the sample standard deviation s *J^r
"
-------
"23S 'J "2^6"'S
1
_ 1
~" J.
2
•^
Ji
a
-8
51
50
45
-i
-•j
o
1
X
-3
.5
.5
.5
.5
j
6
2
12
.25
.25
.25
.25
Average X = (X]_+X2*X3+X4)/n Variance s2 = y* (X-j-X) /'n-1
= (48+51*50-r45)/4 '*l
• 194/4 = ^.25^6.25+2.25+12.25)/3
X = 48.5 CU s2 = 21/3 * 7.0
s - 2.6 CU
Bias B • X-T
= 48.5-50
8 - -1.5 CU
Based on these results the estimated bias of the measurement sys-
tem, under the above conditions, is -1.5 CU and.the estimated preci-
sion, expressed as the standard deviation, is 2.6 CU. On a practical
basis the bias is not considered to be significant oecause the assumed
value T is contained within the range of the four measured values.
5.2.1.2 Population Parameters—
If a random variable X is measured many times, the calculated sam-
ple statistics will approach constant values referred to as popula-
tion parameters. For example, when n is very large, the sample
average X of n measurements approaches a value called the
population mean, or simply the mean, which is denoted by the
sym&ol M. In the absence of measurement bias, > is the true value of
tne quantity being estimated. Thus, The appropriate estimator for the
population mean M based on n measurements is the sample average X. The
value of X generally will not coincide with M but does give the
best estimate based on the measurements available.
Similarly, if many measurements are made, the sample variance s2
approaches the population variance which is customarily denoted by
?2. Its square root, ?, is the population standard deviation
(s.d.). Again,
-------
;- '-.stances wnere ore;: s: on estimates are cstainec --or, analyse
:- replicate pairs, ~"e range R i'-axi.nun ^al^s - mm muni value/
or relative range SR (13J S/O '3 sometimes jsed as an inaex
of precision. For reolioate pairs tne relationship oetween tne
ana standard deviation is s = R/ /2~7
5.2.2.2 Bias-
Bias, as estimated witn sample statistics, is tne signed
difference Between tne average X of a set of measurements of a
standard and the "true" value of the standard T given by
3 • X - T.
Bias can be negative or positive and is expressed in the units of
measurement or as a percentage of the value of the standard. Percent-
age bias is given by
SB * 100 (X - T)/T.
Bias is also estimated by average percent recovery P (see
Section 5.4.1 for a definition of percent recovery). The relationsnip
Detween percent bias and average percent recovery is:
SB - P - 100.
5.2.3 Components of Variance
For any measurement system there are many sources of variation or
error, some of which are sample collection, handling, shipping, stor-
age, preparation, and analysis. For each individual or groupings of
error sources within a measurement system, there are different classi-
fications of variation or precision. Different classifications are tne
result of the different conditions and manner in which the data quality
assessments are made for estimating precision.
Intralaboratory precision is the variation associated with a
single laboratory or organization. IntralaDoratory precision must be
further subclassified as short-term or long-term precision de-
pending on the conditions and manner in which the precision data are
ootained. Intralaboratory precision is usually referred to as
-------
~-,e T,cst commonly usec estimate of ^racisicn is tre sample stan-
dard deviation, as defined in Section 5.2. Other precision measures
include trie coefficient of variation viGO s/X), range R (maxi-
mum value - minimum value), and relative range RR (100 R/X).
Collocated samples are independent samples collected in sucn a
manner that they are equally representative of the variable(s) of
interest at a yiven point in space and time. Examples of collocated
samples include: samples from two air quality analyzers sampling from
a common sample manifold or two water samples collected at essentially
the same time and from the same point in a lake.
A replicated sample is a sample that has been divided into two
or more portions, at some step in the measurement process. Each por-
tion is then carried through the remaining steps in the measurement
process.
A split sample is a sample divided into two portions, one of
which is sent to a different organization or laboratory and subjected
to the same environmental conditions and steps in tne measurement pro-
cess as the one retained inhouse.
Collocated samples when collected, processed, and analyzed by
the same organization provide intralaboratory precision information
for tne entire measurement system including sample acquisition, han-
dling, shipping, storage, preparation and analysis. Both samples can
be carried through the steps in the measurement process together pro-
viding an estimate of short-term precision for the entire measurement
system. Likewise, the two samples, if separated and processed at dif-
ferent times or by different people, and/or analyzed using different
instruments, provide an estimate of long-term precision of the entire
measurement system.
Collocated samples when collected, processed and analyzed by
different organizations provide interlaboratory precision informa-
tion for the entire measurement system.
-------
:f tne measurement s>stem, anc. tne s>;e o* trie samoie lot,
7:.~ "3---= s = ":!e iots, a *ixe2 frequency -"or ~e:;~*cate measurements
,3uc": as one sanole in ten or twenty) is rsccmnencec. "or small sa~cle
"cts, "ore f-equent repetition may De desiraole to ensjre tnat sr-,**i-
c'ent cata are availaDle to assess precision. Alternatively, multiple
sample lots wit.n a common matrix, analyzes oy tne same measurement sys-
tem, can oe comoineci as aiscussec unaer continual precision assessments
;Section 5.5). If tne environmental measurements normally prccuce a
nign percentage of results oelow tne MDL (see Section D.5), samples for
replicate measurement snould tie selected from tnose containing measura-
ble levels of analyte. wnere tnis is impractical, sucn as witn complex
rnulti-analyte metnoas, sample replicates may oe spiked at appropriate
concentration levels to ensure that sufficient data will be available
to assess precision.
Precision information can be dealt with in a variety of ways
depending on the specific situation of interest and the type of data
available.
Interpretation of precision data must always be based on a clear
knowledge of how the data were created. For example, the precision of
tne entire measurement system, including sample acquisition, can only
be assessed by analyses of collocated samples. Precision data gener-
ated from multiple analyses of a standard only describe tne stability
of the measurement device or instrument and only represent the ultimate
precision which could be achieved for a field sample if. tne sampling
activity, suosequent sample preparation steps, and the sample matrix
had no impact on final results.
Figure 5-1 graphically outlines these samples in a general sense,
but specific sampling and analysis situations may require additional
precision information and more extensive breakdown of precision evalua-
tion samples. If this is the case, a clear indication of what is being
done and why should be provided in data quality assessment documenta-
tion.
5.3.3 Calculation of the Summary Precision Statistics
Summary statistics provide an assessment of the precision of a
measurement system or component thereof for a project or time period
(i.e., for a sample lot or group of sample lots). They may be used to:
-------
: esti-ate precision at cisorete concentration "eveis.
c average estimated precision over acoiicaoie concentration
" a n v, e s.
o oroviae tne oasis for a continual assessment of precision of
fjture measurements.
Tne summary statistics are aevelopea from tne oasic statistics
^atnerea tnrouynout tne project or time period represented. Because
the precision of environmental measurement systems is often a function
of c :entration (e.y., as concentration increases, standard deviation
increases), tnis relationship snould be evaluated before selecting tne
most appropriate form of the summary statistic. An evaluation of the
basic precision statistics as a function of concentration will usually
lead to one of three conclusions:
o Case 1: standard deviation (or range) is Independent of con-'
centration (i.e., constant);
o Case 2: standard deviation (or range) is directly proportional
to concentration, and coefficient of variation (or
relative range) is constant; or
o Case 3: both standard deviation (or range) and coefficient of
variation (or relative range) vary with concentration.
For simplicity of use and interpretation, the relationship most
easily described should be selected for use, i.e., for Case 1 the
standard deviation (or range) is simplest to work with; whereas, for
Case 2, the coefficient of variation (or relative ranye) is simplest.
If tne relationship of precision to concentration falls into Case 3,
reyression analysis can be used to estimate the relationship between
standard deviation (or range) and concentration.
The decision as to wnich case is applicable can be based on plots
of precision versus concentration or by regressions of s (or R) or CV
(orRR) versus concentration by an approach summarized in Table 5-1 and
illustrated in the following examples.
-------
rv
I •-
! 5
te
S
2.8-1
2.-
2.2-
2.1
te
Figure 5-2. Plots of CV (%) versus X (CU) and s (CU) versus X (CU)
for Example 5-2.
-------
-,n ^spection of trie cata raouia:ion of t.ne staicars ceviat'on ana
av5"a3e for eacn pair suggests tnat tne stanaarc deviation increased as
tie average increased. Therefore, trie coefficier': of variation values
were tabulated. An inspection of tne taoulation of CV versas average
•-eveals no clear relationship, i.e., trie CV can De treated as a ccn- -
stant across tne concentration ranye. Tnese findings are confirmee oy
tne plots in Figure 5-3. Tnerefore, tne average CV (7%; is used as tne
precision summary for tnis sample lot. Tne precision, expressed as a
standard deviation, of individual measurements in tnis example, at any
concentration, X, is estimated to De, and is reported as, s - U.Q7X.
Example 5-4 (Case 3. s increases with increasing concentration and
CV decreases with concentration): If a constant relationship does not
appear to exist between standard deviation and concentration or between
coefficient of variation and concentration, tnen it is necessary to use
a more complex approach, sucn as a linear reyression equation, to
describe the relationship. A least-squares linear regression analysis
of the precision (i.e., s or CV) versus measured concentration results
in two coefficients, a slope and an intercept, which are used to repre-
sent the precision of the data set. The ranye and relative range are
sometimes used to estimate precision, particularly for replicate pairs,
because of their ease of computation and use.
For a study involving a lOU-sample lot, 1U collocated sample pairs
were collected for estimating the precision of the entire measurement
system. The results for each set of collocated samples are tabulated
oelow alony with values for the averaye, ranye, standard deviation,
relative range, and coefficient of variation of each pair of samples.
To simplify visual interpretation, the data have been ordered by
increasing values of concentration.
Average Standard Relative Coefficient of
(X^+X2)/2 Range Deviation Range Variation (%!
5.33
10.1
19.5
Id. 6
32.8
108.3
132.
Id6.
301.
3517
6.37
8.65
17.6
20. 5
36.1
102.
124.
197.
527.
3341
5.85
9.38
18.55
19. b5
34.46
105.2
128.0
191.5
514.0
3429
1.04
1.45
1.9
1.9
3.3
6.b
8.0
11.
26.
176
0.735
1.03
1.34
1.34
2.33
4.60
5.66
7.78
18.38
124.43
17.8
Ib.a
10.2
9.8
9.6
6.2
6.2
5.7
5.1
5.1
12
11
7
7
7
4
4
4 -
4
4
-------
-:" or-ar.i; i~' ens t.iat orafer wor<:,n'3 w'tn stanaara deviation arc
cr ce = "i :i ent of /ariatioi, 210,3 of stancarc caviation versus avera:e
ccn.centr2tien arc coefficient of variation versus average concentration
ane si own in Figure 5--. Tnese plots snow tnat s is an increasm = ,
approximately linear function of concentration wnersas CV is a cecreas-
ing, nonlinear function of concentration. In tnis situation it is sin-
pier to use a linear regression equation to represent tne stancarc
aeviation over tne concentration ranye. The calculated regression
equation is s = O.Q36 X * 0.698. The individual measurements in
this example are estimated to have, at any concentration X, a standard
deviation of 0.036 X +0.698 CU.
For organizations tnat prefer working with range and relative
ranye, the tabulation shows a clear increase in ranye, and decrease in
relative range, with increasing concentration. A least-squares linear
regression of range as a function of the average concentration for the
data above yields the following regression equation R = 0.1)51 X
+ U.987. For replicate pairs the standard deviation and ranye are
related by s - R/VTT
5.3.4 Reporting Precision
Because each data user must determine the data reliability
required for his/her application, the data reporter must provide a
standard deviation or alternative measure of precision which applies to
measurement.
The data user should be provided with a narrative statement docu-
menting the conditions and manner in which the precision data were
obtained and the applicable component or components of the measurement
system. Statements for reporting precision estimates for cases 1,2,
and 3 as illustrated in examples 5-2, 5-3 and 5-4, respectively are
given as examples.
o Case 1 (Example 5-2). The estimate of intralaboratory, short-
term precision (i.e., within lot, single analyst) for each con-
centration found in the sample lot is s * 2.4 CU, for concen-
trations in the ranye of 20 to 40 CU, oased on triplicate
analyses of each of three samples. The standard deviation s
can be used to estimate a prooability interval for the random
-------
e~-:r associated witn an mci-'icua. observation <•, as :o'-
'cvvs. 7"e aooroximate *5£ prooaoiiit/ interval for t.ne cif:er-
e^ca in an ooservation X, ana tne limiting average X 'i.e.,
t.-.e value tnat would oe ootainea if tne samcle were anal/zee
many times) is * 2 s. The aooroximate 95i orooaoility interval
for errors ^exoTucing oias) for inciviaual measurements in tris
sample lot is estimated to be ^ 2 s = ^ 2V2.4 CU) = ^_ 4.3 :u.
o Case 2 ^Example 5-3). Tne estimate of intralaooratory, snort-
tern precision for individual measurements in tms sample lot
including steps in tne measurement system from sample collec-
tion tnrougn analysis is s 3 0.07X CU for concentrations in tne
acproximate range of 1.5 to 5.0 CU, cased on the analyses of 3
field replicate pairs. For example, at X s 5.0 CU, the esti-
mated standard deviation is s s 0.35 CU, tne approximate 95i
probability interval for errors (excluding bias), for X = 5.0
CU, is ^ 2 s or +_ 0.7 CU.
o Case 3 (Example 5-4). The estimate of intralaboratory, short-
term precision for individual measurements in this sample lot
including the total measurement system is s a 0.036X •*• 0.698,
for sample concentrations in the approximate range of 5 to 3500
CU, Based on the results from 10 pairs of collocated samples.
The approximate 95% probability interval for the errors (ex-
cluding bias) in an individual measurement X is _+ 2 s s +
2(0.036X + 0.698) CU. For example, at X = 100 CU, s - O CU,
the approximate 95% probability interval for errors (excluding
bias) for X - 100 CU is i 8.6 CU.
5.3.5 Continual Precision Assessments
For organizations in which sample lots are routinely analyzed and
data are reported on a frequent basis, the basic precision statistics
from multiple lots of a given sample matrix may be combined to provide
an estimate of long-term precision and an improved estimate of short-
term precision as illustrated in Section 5.6.3. This assessment can
also be extended to include subsequent lots, unless test results for
these new lots indicate that method precision is significantly differ-
ent. This combining of data quality assessment results permits the
laboratory to provide a precision assessment derived from a substantial
amount of background data rather than from limited precision data pro-
duced in a small study.
This procedure also provides the basis for the use of control
cnarts to monitor the performance of the measurement system. The
-------
Bias - an estimate of trie si as 3 :s tne difference oetween tre
average vai^e X of a set of measurements of a stanaara and t,ne refer-
ence value of tre stanaara 7 given oy:
B = X - T
Alternative estimates of 3i as are percent oias
%8 » 100 (X - T)/T,
and average percent recovery P
n
P « £ P , and
i-1 1
P-i * 100 (AT - Bi)/T,
where A-j * the analytical result from the spiked sample and 8} *
the analytical result from separate analysis of the unspiked sample.
The relationship between percent oias and percent recovery is:
%B • P - 100
Reference material - A material of known or estaolished concen-
tration that is used to calibrate or to assess the bias of a measure-
ment system. Depending on requirements, reference materials may be
used as prepared or may be diluted with inert matrix and used as blind
environmental samples.
Spiking material - A material of known or established concentra-
tion added to environmental samples and analyzed to assess the bias of
environmental measurements.
Target analyte spiking - Spiking with the analyte that is of
basic interest in the environmental sample.
Matrix spike - A sample created by adding known amounts of the
target analyte to a portion of the sample.
Field matrix spike - A sample created by spiking target analytes
into a portion of a sample in the field at the point of sample acquisi-
tion. This data quality assessment sample provides information on the
target analyte stability after collection and during transport, ana
-------
pie
Preparation Analvsis
Field
Matrix
Spike
Provides a oest case estimate
of oias oased on recovery;
includes matrix effects asso-
ciatea witn sample preserva-
tion, snipping, preparation
ana analysis.
Provides an estimate of oias
based on recovery. Incor-
porates matrix effects asso-
ciated with sample preparation
and analysis only.
Analysis j
Matrix
Spike
Provides an indication of
matrix effects associated witn
tne analysis process only.
Figure 5-5. The Use of Target Analyte Spikes for Bias Estimation
-------
"acie jroceaure *or assessment z~ oias. An aacea attraction i; ire
ity to cotain recovery cata an every *iela sample at reiative'y ';«
It is used, for example, to evaluate tne apolicaoi1ity of
jolojy and, indirectly, aata quality assessments to individual
of a sample lot. Sucn practices do not preclude tne neec to
assess oias Dy spiking with the analytes being measured or reported.
5.4.2 Calculation of 3ias Statistics
The most widely used summary of bias is by linear regression of
bias on T; or, equivalently, regression of data quality assessment
results (X-j or X) on T (as illustrated in Section 5.6.3). For
the important special case of spiked samples as described above, tne
following approach may also oe useful.
A portion of the samples in the sample lot is spiked at multiple
concentration levels to determine individual measurements of percent
recovery. These recoveries are used to calculate summary bias statis-
tics for the entire sample lot. The summary statistics are used to
estimate the percent recovery for each individual measurement in the
lot. For each sample spike i, calculate the percent recovery Pi oy,
?i - 100 (A, - Bi)/T1f
where: A^ = the analytical result from the spiked sample,
BJ * the analytical result from a separate analysis of
tne unspiked sample,
TI = tne known true value of tne spike.
Average percent bias is calculated from average percent recovery
for the sample spikes by the relationship
% B • P-100.
If reference materials instead of spiked samples are analyzed to
assess bias, percent recovery is calculated by the equation above with
B-j equal to zero.
Upon completion of the project or time period, the bias assessment
for the data set of environmental measurements is calculated from tne
individual percent recoveries P-j observed through the project period.
Unless a relationship between the percent recovery, or its variability,
and concentration can be established, all percent recovery measurements
-------
-eccve-y associates *itn any incivic^a'
'eas-remeit in cms ICu-samjla i ot "3 estimated tc oe Between ^~, a":
135%, at tne r5« ^rcoaoiiity 'eve".
Ix;~c'e 5--a: In any application of statistics it is important :;
identify jncerlying assumptions ana cnecx t.nem witn tne cata c-y gra:m:
cisplay or statistical cnecKs. Figure 5-6 is a plot of recovery ver3uS
concentration for analyses of sulfate ion aeoositea on Teflon* filters.
Evidently recovery is not constant, out is a sliyntly decreasing func-
tion of concentration. Therefore, a summary in terms of a single aver-
age percent recovery would be of questionable validity. This data is
examined in more detail using a linear regression approach in Section
5.5.2.
5.4.4 Resorting Bias
Each environmental measurement must be reported with an assessment
of bias. Bias should be expressed as a percent error interval of
%B _+ 2 Sp or as a percent recovery interval from P - 2 Sp to P +
2 Sp. (There are several ways to express bias and accuracy. It
should be noted here that expressing bias in this manner is not consis-
tent with the definition given in Subsection 5.4.1. Additional efforts
will be made to acnieve consistency in the definition and use of bias
in future revisions.) Where reference materials are used as a matrix-
free check on laboratory performance as a supplement to sample spiking,
only the results of the sample spikes should be submitted to an envi-
ronmental data base.
The data user should be provided with a narrative statement
explaining the reported bias estimate alony with tabulated percent
recovery intervals. The statement might read:
"Bias is expressed as a 95% probability interval around tne aver-
age percent recovery. A percent recovery interval of 90 to 106%,
for example, means that approximately 95i of the time when a spike
of the measured material is recovered, the observed percent re-
covery can oe expected to lie between 90 ana 106%."
5.4.5 Continual Bias Assessment
As with precision assessments, laboratories in which small sample
lots are routinely analyzed and data are reported on a frequent basis
-------
i ;-/e^ matrix iito a si.ng.e oias assessment *or tne comoiiec samoie
set. "-is assessment can also oe extencec to induce sucsequent small
sa.r;', e lets, unless test results for these new lets incicate t,n,at
metrics oias is significantly different.
Ccmoining Dias data in this manner permits the laooratory to pro-
vice cnas assessments derived from a substantial amount of oackgrcuna
aata rather tnan from limited oias data produced in a small stuay. It
also can provide tne basis for the use of control charts to mc-itor
measurement system bias over time.
Historical data must first be comoined as necessary to develop an
assessment of Dias which includes the determination of averaye percent
recovery (?) and the standard deviation of tne percent recovery
(Sp). These estimates maybe used to develop control chart limits as
P -^ 3 Sp for subsequent measurements. Each recovery measurement,
?i , in a new sample lot must be compared with the control chart
limits. If each value for P-j falls within the control limits, tne
historical percent recovery and analysis assessment can be applied to
all individual measurements of the new sample lot. If P^ falls
outside the control limits, either the historical assessment is not
applicaole to the new data set or the laboratory operation is out of
statistical control.
At least annually, and preferably after no more than 30 to 50 new
recovery measurements have been taken, the control chart limits must be
recalculated to reflect the current percent recovery capabilities of
the measurement system. This may be done by either expansion or
replacement of the historical data base to include the most current
data.
Example 5-9; A laboratory is analyzing and reporting samples on a
continual basis. Historical data for the analysis of spiked samples
established that P = 98.0%, and sp » 4.0%; the control chart limits
are P _+ 3 sp, or 86 and 110%. A sample with a measured background
level (Bi) of 22.0 CU was spiked with the equivalent of 30.0 CU (T)
without appreciably changing the sample volume. The result for the
analysis of the spiked sample (A-j) was 49.2 CU. Therefore:
pi s 13° 49'2 " P'° • 90.7%.
-------
~-ere nave seen T.any -arms used to cesi^nate cetectic" imts ana
•.ley nave seen denned in various ways. Lower Limits of Detection
'.LID), Mini nun Detection Amount (MDA), Metnoc Detection Limit (MDL;,
Detection Sensitivity, ana Limit of Detection (LDD) are some of trie
terns used. Most autnorities in tne field agree tnat tne smallest
detectable quantity, by whatever nane, is related to tne standard
deviation of sample analyses at or near zero analyte concentrations.
Since MDL is a basic performance characteristic of an analytical metnod
only its calculation, with example, is discussed.
5.5.2 MDL
Ideally each laboratory should establish and periodically reevalu-
ate its own MDL for each sample matrix type (for one time only matrix
types and multianalyte samples in difficult matrices, e.g., soils or
fish, this may be impractical) and for each environmental measurement
method. The MDL is determined for measurement systems by the analyses
of seven or more replicates of spiked matrix samples. As with preci-
sion and bias, the assessment of MDL should be based upon the perfor-
mance of the entire measurement system. The standard deviation of the
responses (sm), in concentration units, is used to calculate the MDL
as follows:
MDL = sm (t.gg) Eq. 5-7
wnere:
t,99 = "Student's t value" appropriate for a one-tailed test at
the 99% confidence level and a standard deviation estimate
witrt n-1 degrees of freedom.
For example, if the MDL is determined using measurements from seven
appropriate samples, then use t^g * 3.14 for n-1 » 6 degrees of
freedom. If the determination yielded a standard deviation of 0.15 CU,
the MDL is calculated (Equation 5-7) to be (3.14)(U.15 CU) - 0.47 CU.
-------
~3 illustrate trie application of trie statistics1, concaots jrev1-
ous'iy ciscjssec, caca £"cci an actual laboratory -easurement program are
presented ana calculations of appropriate summary statistics are per-
formea. Tne example includes calculation of with in-lot estimates of
precision and 01 as as well as oetween-lot summary statistics tc illus-
trate a procedure for continual data quality assessment and/or estimat-
ing long-term precision of projects of long duration. The witnin-lot
sample sizes are 3 or smaller in all out one case. Within-lot averages
and standard deviations computed from such small samples tend to be
imprecise estimates of the population mean and standard deviation. The
example shows how improved estimates of these quantities can be ob-
tained Dy averaging over the lots.
The average witnin-lot standard deviation provides a better esti-
mate of short-term, intralaboratory, precision for the total data set.
Likewise, using data quality assessments between- or across-lots can
provide an estimate of between-lot variability, i.e., systematic error
from lot-to-lot as well as an estimate of total variability or long-
term precision over the subject time period.
The estimate of long-term precision is the appropriate measure to
use in describing the precision of the total data set. Estimates of
snort-term (within-lot) precision and between-lot variaoility are use-
ful as part of a data quality assessment program in monitoring the
system's performance and can provide guidance for troubleshooting by
indicating which component(s) of the measurement system is experiencing
larger than normal variability.
The example goes somewhat beyond the treatment presented in Sec-
tion 5.4, oy employing linear regression to summarize relations between
bias and concentration. In this example, a lot is defined as all
measurements made witnin a given day, includiny routine analysis of
study samples and data quality assessment samples at one or more con-
centrations.
The example data are from a program for ion chromatography analy-
sis of sulfate deposits on Teflon1* filters. Data quality assessment
samples in this program consisted of sulfate solutions at three differ-
ent concentrations, known to the analyst. The ion chromatograph was
-------
^a:= q^dii-y assessments :or t.ne exanpie su;-2*e ar.aiysis :
anc cssociatea witmn-lot statistics (i.e., n, X, sw ana 7) are ore-
sentcd in "a3ie 5-2 for tnree values of solution concentration, j, 12^,
and 2-0 Cl;. As seen in tne taoie, tne witmn-lot sample size 'i.e.,
me numoer of aata quality assessment samples) ranges from n = l to n=c .
The witnin-loz average anc standara deviation can vary widely *vitn sj:r.
small sample sizes.
5.5.2 3etween-Lot Summaries
This procedure allows for the calculation of summary statistics
for a project time period that spans several lots. The followiny sta-
tistics are used to report data quality over a uiven time period (e.g.,
quarter, year). They are oDtained from within-lot statistics descnoea
in tne previous section, and are calculated for all data quality
assessments obtained under a particular set of fixed conditions, sucn
as matrix, concentration, and analysis procedure. For the example sul-
fate anaysis program, between-lot statistical summaries are calculated
for each (fixed) data quality assessment sample solution concentration.
Let nj * the number of data quality assessments
at a given concentration in the jth lot.
Xj s the average of the data quality
assessments at a given concentration for
the jth lot.
Sj * the standard deviation of tne data
quality assessments at a yiven
concentration for the jth lot.
k
n = ]T nj = total number of data quality assess-
jal ments for the reporting period, wnere k =
total number of lots.
Then,
The grand weighted average is:
k n- -
X * V iL X Eq. 5-8
L-I n j
-------
V j-i
oetween-iot (or among lots) standard deviation is:
* nj(Xj.X)2 2
2- - ~ sw
Total variation of single observations at tne related concentra-
tion level over time is:
•t • (*l *4 )1/2
Between-lot summary statistics for the sulfate sample data are
given in Ta&le 5-3. Example calculations of between-lot summary sta-
tistics for Condition 1, wnere T a 240 CU, k » 6, and n * 21 are given
Delow:
6
x s E
» |Y (24°-4) + fr (239-2) * IT (24U-4)
|Y (240.5) + |Y (239-6) * |r uss.s)
X * 239.3 CU
s. s , f ("rD sy
S ' 2- 21-6
J-l
("2(1.44)2^5(0.71^ 2*2(1.44)24-2(3.70) 2^2(0.72)2*2(5.03) 2*1
1/2
-------
/ . 0- i
3(24U.4-239.3)2 + 5(239.2-239.3)2 - 3(24C .4-239.3)2-
r3(24(J.5-239.3)2 + 3(239.6-239.3)2 + 3(235.8-239.3)2
- 2.43
• c.
3)/6
1.03 CU
sw
2.66 CU
The summary statistics should be reported for each set of sample
conditions over the appropriate time period using the format of Taole
5-3. (The value sa * 0 at true value 12U resulted from a negative
2
value for s| indicating that there was not significant
variation from lot to lot.)
5.6.3 Regression Summaries and Reporting Requirements for a Project
or Time Period
Any measure of bias (e.g., recovery) or precision can depend on
the concentration T. Even wnen T is unknown, dependence of precision
on T may be seen as dependence on the apparent (measured) concentration
X. Regression summaries of bias and precision over all conditions pro-
vide a useful complement to summary statistics for individual sets of
conditions. Further, in a case where all the reference values, T, of
data quality assessment samples for a given reporting period are dif-
ferent, then between-lot statistical summaries for specific conditions
in the Table 5-3 format would be equivalent to lists of the raw assess-
ment data. A much more useful summary involves a regression and plot
of measurement X on reference value T.
-------
•vc
2
OO U4
MM ^^
t/1 LU
s- a
If
UJ 3£
t— ^
< H-
a
— o
.1 O
a.
C3
I
UJ
-J
<.
5
r
VI
t» Wl
01 • i-
3 """' a.
9
C
U V
•o —
E o
01 « 3
4> ~
•3 «
C »
Ol
•0
u
*«
c
I
s
u
01
— 0)
3. a.
v»
^
9
U
3 "2
"5 ""
&
^^
^ M
=
1-
11
3
»
&l
3
U
I
U
O
ltj*
•
f«
U
V 31
> n
•0 13
9 >
H e-
S
- «
e a
£ V
— U
X 9
I X
VI
a
•a
*
§
~
U
Ol
u.
0.
^^
""•
=
5
en
-
3
J
01
3
J
Ol
3
VI
9
S
01
01
A
*
3
"vi
u
Ol
t_
•^ »
1
VI
VI
VI «•
01 — vi
•s aw 01
VI ^ -*
. ai a.
•3 u =. s
w 3 u ifl
I/I >tM h* VI
W >, U 11
9 — 9 C
e VI
Ol
a
•o
•3
O<
U
—
a
« VI
-------
sw
s -
s -
1
2 -
ea
128
T
188
240
Figure 5-8, Plot of Witnin-lot Standard Deviation s^ (CU) versus T
(CU) for Sulfate Data Quality Assessment Results (Table 5-3,'
Sa
1 .5-
1 .1
8.S-
\2»
T
240
Figure 5-9. Plot of Between-Lot Standard Deviation sa (CU) versus T
(CU) for Sulfate Data Quality Assessment Results (Table 5-3;
-------
— co
f-^
u.
O •
(/I UJ
10 S
>- uJ
i ^j
< UJ
^e
< o
l^» SO
—J 7^
a -^
Q.
5"
i/i
- * *•
a i>
!i-
•3 <5
2 5^
^
01
^^
U
•9
e
•s
c
a
ST
a
I-1
u
0
«rf
w .J
o 3
"5 ""
1=
s
5!
=
— *
3
=>'
S
Ol
3
01
3
i
1
^
3
1 X
£
1.
01 01
> n
•o -o
-1 Ol
3 >
01
— c »• —
a o v —
1 X
in
oa
01
3
01
3
1.
I/I
> 3
Ol I
•o c
•3* 5
tn *
w 01
0 31
T. L. 1 *
e oi u<
.<•• >
— <_ a
X 0 -0
i
•3;
••
01
u
H-
3
Ol
3
u
5s
01
•a
*
0
i
e
u
|
Ol
1
"™
u
01
u
IX
I/I
I/I
"-a
Ol — tn
•3 a-'J^
S 'i
- i- a. 5
w O l; ^
*J »* U Ol
1 U I/I — 1
C -0 11 3
*-,/, 0
§
"•""
u
01
a.
.2 =
11
I/I —
-------
-1 " an n i n c
1. "Compilation cf Data Quality Information for Envi ~onmen-
tai Measurement Systems," C.AMS _ , U.S. EPA, Office of
Sesearcn ana Develooment , wasninaton, DC, 1963 ; Draft).
2. "Inters Guidelines ana Specifications for Preparing
yuaiit. Assurance Project Plans, "QAMS-Q05/30 , U.S. EPA,
Office of Researcn ana Development, Wasninyton, D.C.
20560, Decemoer, 1980.
3. Natrella, M.G., Experimental Statistics. NBS Handbook 91,
U.S. Department of Commerce, National Bureau of Stan-
dards, 1966.
4. Davies, 0. L., The Design and Analysis of Industrial
Experiments . 2nd edition, Hafner Puolisning Co., New
York, 1956.
5. Cox, D.R., Planning of Experiments. Wiley, New York,
1953.
6. Box, G.E.P., W.G. Hunter and J.S. Hunter, Statistics for
Experimenters. Wiley, New York, 1978.
7. Youden, W.J., "Statistical Aspects of Analytical Deter-
minations, "Journal of Quality Technology. 4(1), 1972,
pp. 45-49.
8. Elder, R.S., "Choosing Cost-Effective QA/QC Programs for
Chemical Analysis," EPA Contract No. 68-03-2995, Radian
Corporation, Austin, Texas, 1981 (draft).
5.7.2 Sampling
1. Environmental Monitoring and Support Laboratory, Handbook
for Sampling and Sample Preservation of Water and Waste-
water. EPA-6UO/4/82-029, U.S. EPA, Office of Researcn and
Development, Cincinnati, 1982.
2. BrumDaugn, M.A., "Principles of Sampling in the Chemical
Field," Industrial Quality Control. January 1954, pp.
6-14.
3. Kratochvil, B. and J.K. Taylor, "Sampling for Chemical
Analysis." Analytical Chemistry. 53(8), 1981, pp. 928A-
938A.
4. Currie, L.A. and J.R. DeVoe, "Systematic Error in Chemi-
cal Analysis", In: Validation of the Measurement Process.
ACS Symposium Series 63, American Chemical Society,
Washington, D.C., 1977, pp. 114-139.
-------
12. 7ay"ior, J .R ., An Introa-jcti or to Error Analyses -- 7-e
Stjay of jncercainties in 'nysical Measurements, jmver-
sity Sciences SOOKS, Mills Valley, California, 1532 ,~vs
is a general text) .
.4 -ssessne^r o* 3ias
1. Urlano, G.A. ana C.C. Gravatt, "The Role of Reference
Materials and Reference Metnoas in Chemical Analysis,"
CRC Cr-itlcal Reviews in Analytical Cnemistry, 6^;, 1977,
pp. 36i-<+li.
2. Uriano, G.A. and J.P. Cali, "Role of Reference Materials
ana Reference Methods in the Measurement Process." In:
Validation of the Measurement Process. ACS Symposium
Series No. 63, American Cnemical Society, Washington,
D.C., 1977, pp. 140-161.
3. Skogerboe, R.K. and S.R. Koirtyohann, "Accuracy Assurance
in the Analysis of Environmental Samples." In: Accuracy
in Trace Analysis. Vol. 1, NBS Special Publication 422,
U.S. Department of Commerce, National Bureau of Stan-
dards, 1976, 1976, pp. 199-210.
4. Watts, R.R., "Proficiency Testing and Other Aspects of a
Comprehensive Quality Assurance Program." In: Optimizing
Chemical Laboratory Performance throuyn the Application
oT Quality Assurance Principles. Association of Official
Analytical Chemists, Arlinyton, VA, 1980, pp. B7-115.
5. Horwitz, W.L., R. Kamps and K.W. Boyer, "Quality Assur-
ance in the Analysis of Foods for Trace Constituents,"
Journal of the Association of Official Analytical,
Chemists. 63(6). 1980. pp. 1344-1354.
6. Colby, B.N., "Development of Acceptance Criteria for the
Determination of Organic Pollutants at Medium Concentra-
tions in Soil, Sediments, and Water Samples," EPA Con-
tract No. 68-02-3656, Systems Science and Software,
LaJolla, CA, 1981.
7. Bicking, C., S. Olin and P. Kiny, Procedures for the
Evaluation of Environmental Monitoring Laboratories,
Tracer Jitco, Inc., EPA-600/4-78-017, U.S. EPA, Office of
Research and Development, Environmental Monitoring and
Support Laboratory, Cincinnati, 1978.
8. U.S. Department of the Army, "Quality Assurance Program
for U.S. Army Toxic and Hazardous Materials Ayency,"
Aberdeen Proving Ground, MD., August 1980 (draft).
9. Freeberg, F.E., "Meaningful Quality Assurance Program for
the Chemical Laboratory." In: Optimizing Chemical
Laboratory Performance Throuyn tne Application or Quality
Assurance Principles, Association of Official Analytical
Chemists, Arlinyton, VA, 198U, pp. 13-23.
-------
12. Ig'ewicz, B. ar.c ^.,-i. Myers, "Comoanson of Acorcx*~a-
tions to tne ^ercenta^e Points of tne Samoie Coefficient
of Variation," "ecpr emetic 5 , 12^1), 197J, pp. 155-17].
12. Environmental Monitoring and Suoport .acoratory, Cua' ' :/
Assurance HandDoox for Ai r °o1 1 ution Measurement yst5n5.
Vojune 1 - Jrincio'ies, EPA-ouJ/3-76-jU3 , o.S. EPA, \ffice
of Researcn ana ueveiopment , Researcn Tnanyle ?ar<, NC ,
1976.
14. Gruoos, F.E. "Tne Difference Control Chart witn an Exam-
ple of Its Use," Inoustnal Quality Control. July, 1946,
pp. 22-25.
15. Page, E.S., "Cumulative Sum Cnarts," Tecnnometrlcs. 3(1),
1961, pp. 1-9.
16. Jackson, J.E., "Quality Control Methods for Several
Related Variaoles, "Technometrics . 1(4), 1959, pp.
359-377.
17. Jackson, J.E. and R.H. Morris, "An Application of Multi-
van ate Quality Control to Photoyrapnic Processing,"
Journal of tne American Statistical Association, 52,
1957, pp. 1B6-199.
18. Montgomery, D.C. and H.M. Wadswortn, "Some Techniques for
Multivariate Quality Control Applications," ASQC Tecnni-
cal Conference Transactions. 1972.
19. Frazier, R.P., J.A. Miller, J.F. Murray, M.P. Mauzy,
D.J. Scnaeffer and A.F. Westerhold, "EstaDli shiny a
Quality Control Proyram for a State Environmental Labora-
tory," Water and Sewage Works. 121(5), 1974, pp. 54-57.
20. Hillier, F.S., "X and R-Chart Control Limits Based on a
Small Number of Subgroups, "Journal of Quality Technolo-
, 1(1), 1969, pp. 17-26.
5.7.6 Method Detection Limit
1. Glaser, J.A., O.L. Foerst, G.D. McKee, S.A. Quave, W.L.
Budde, "Trace Analysis for Wastewaters," Environmental
Science and Technology. 15, 1981, pp. 1425-1435.
2. Hubaux, A. and G. Vos, "Decision and Detection Limits for
Linear Calibration Curves," Analytical Chemistry, 42,
1970, pp. «49-a55.
3. "Guidelines for Data Acquisition and Data Quality Evalua-
tion in Environmental Chemistry," Analytical Chemistry,
52, 1980, pp. 2242-2249.
-------
;35^Y JF TERMS
: ons ,
X for samples)
Bias
Coefficient of variation
Correlation Coefficient
error
Lot, batcn
Lot size (N)
Matrix
Method Detection Limit (MOL)
Observed value, observation,
or variate (X)
In a sample of n urn's, Xi,
X? Xn, trie suin of tne
ooservect values in tne samoie
diviaea oy tne numoer of units :r,
tne sample.
Tne difference between me popula-
tion mean and tne true or reference
value, or as estimated from sample
statistics, the difference oetween
the sample average and tne
reference value.
A measure of relative dispersion.
It is equal to the standard devia-
tion divided by the mean and multi-
plied by 10U to give a percentaye
value.
A number between -1 and 1 that
indicates the deyree of linear
relationship between two sets of
numbers.
Tne difference between an observed
value and its true value or the
probability interval that contains
the systematic and and ranaom error
with l-» confidence.
A definite quantity of samples
collected under conditions tnat ara
considered uniform.
The number of units in a particular
lot.
The material in which the ana-
lyte(s) of primary interest is
embeded.
The lowest concentration of an
analyte that a measurement system
can "consistently detect" and/or
measure in replicated field
samples.
The particular value of a charac-
teristic and designated Xj., X£,
X3, and so on.
-------
APPENDIX F
EPA QUALITY CONTROL GUIDELINES
-------
CHAPTER 5
CALCULATION OF PRECISION, iIAS, AN3
•METHOD DETECTION LIMIT FOR CHEMICAL
AND PHYSICAL MEASUREMENTS
Issued by
Quality Assurance Management and Special Studies Staff
Office of Monitoriny Systems and Quality Assurance
Office of Research and Development
United States Environmental Protection Agency
Washington, D.C.' 20^50
March 30, 1984
-------
Section ^age No.
5.5 A CASE STUDY (14 pages) 1
5.5.1 Witnin-Lot Summaries 2 of 1-
5.6.2 Between-Lot Summaries 3 of 14
5.5.3 Regression Summaries and Reporting
Requirements for a Project or Time Period 7 of 14
5.7 SOURCES OF ADDITIONAL INFORMATION (6 pages) 1
5.7.1 Study Planning 1 of 6
5.7.2 Sampling 1 of 6
5.7.3 Assessment of Precision 2 of 6
5.7.4 Assessment of Bias 3 of 5
5.7.5 Use of Control Charts 4 of 6
5.7.6 Method Detection Limit 5 of 5
5.3 A GLOSSARY OF TERMS (3 pages) 1
5.9 RECOMMENDED FORMATS FOR REPORTING DATA
QUALITY (2 payes) 1
11
-------
LIST :~ ILLUSTRATIONS
7aole 3ec~1on Page
No. No. Nc.
5-4 Summary Regressions for Sulfate
Analysis of Data from Preaarea Solutions,
Reporting Period July, 1980 tnrougn
December, 1980 5.6 9 of 14
5-5 Measurement Data for Sulfate Filter
Samples 5.6 11 of 14
5-6 Summary Regressions for Sulfate Analysis
of Filter Data, Reporting Period August,
1980 to December, 1980 5.6 12 of 14
-------
ting cata cuaiity, i.e., oias, precision, anc MDL. Tne proce-
riSC'jssec in tnis guideline are based on tne assumption tnat
nt errors for cnetmcal anc jnysical measurement systems are
normally or near normally distributed. It is stressed tnat for partic-
ular situations where this aoes not appear to be a valid assumption or
wnere problems occur outside the scope of this guideline, e.g., as now
to treat outliers, the advice of a qualified statistician snould oe
ootained.
b.1.3 Application
Application of these procedures involves assessments of precision,
bias and MDL based on special measurements (hereafter referred to as
data quality assessments) of samples of known composition (e.g., refer-
ence materials, spiked samples, blanks) or of unknown composition
(e.g., replicate study samples or repeated analyses of study samples)
interspersed throughout the periods of routine operation of the
measurement system. Generally, study samples are received for analysis
in batches or lots (use of the term lots applies to any set or suosets
of data obtained from a study project or monitoring program) and data
quality assessments are made during the course'of analysis of the study
samples in tne lot. Application of the data quality assessments to tne
measurements for the complete sample lot or groups of lots is based on
the assumption that all measurements, including the data quality
measurements, are made with the measurement system "in statistical con-
trol". A measurement system is considered to be in statistical control
wnen its variability is due only to chance causes. Data quality
assessment results used with control charts (Appendix H, ref. 13 of
Section b.7.5) or statistical techniques such as the construction of
frequency distributions (Chapter 3, ref. 4 of Section 5.7.5) may be
used to assure that the measurement system is in statistical control.
The statistical measures of data quality prescribed in this chap-
ter should be used in conjunction with archived information on the
operational capability of measurement systems "Compilation of Data
Quality Information for Environmental Measurement Systems", (ref. 1,
Section 5.7.1) in the development of Quality Assurance Project Plans
for EPA environmental measurement programs as required in QAMS-005/80
(ref. 2 of Section 5.7.1).
-------
^ate: '•'c.-c.i
: ..: i , ,-, , . i , . _nL wJ.iwC.." i i
Trie principal indicators of data quality are bias and precision.
Bias is systematic error. Precision involves tne closeness cf
cata values to each otner. Accuracy involves closeness of measure-
ments to a reference value and incorporates both Dias and precision.
To formalize these definitions, some basic statistical concepts are
presented and discussed in the ensuing paragraphs.
It is reiterated here tnat tnis chapter is concerned with the
error distributions of the measurement system and not the distribu-
tions of the chemical and/or physical measurements from a study project
or a monitoring program. The assessments of precision and bias, do,
however, apply to the measurements from a study project or monitoring
program. All statistical concepts and analyses involve the use of data
quality assessments obtained for the specific purposes of estimating
data quality, i.e., bias, precision, and MDL.
5.2.1 Sample Statistics and Population Parameters
5.2.1.1 Sample Statistics—
If a quantity X (e.g., a concentration) is measured n times, it is
customary to refer to the values X]_, X2, . . . Xn so obtained as
a sample of size n of measurements of X. (It should be clear
tnroughout the text from the context whether the word "sample" is used
in this statistical sense or refers to, e.g., a chemical sample.)
Values obtained in the calculation of quantities which summarize data
of this kind are summary statistics or sample statistics.
More specifically, let Xj_/X2, . . ., Xn be a set of independent
data quality assessments taken under fixed and prescribed experimental
conditions and regarded as a random sample from some population. For
many applications the X-j are considered measurements aimed at esti-
mating a reference or true value T. Some basic statistics for a sample
of size n are:
o the sample average X - (Xj. + ... + Xn)/n Eq. 5-1
o the sample bias 8 - X - T Eq. 5-2
o the sample standard deviation s sr £ U.-X) Eq. 5-3
"
-------
Messu cements
X
1 = 1
2
3
d
= (XL+X2+X3+X4)
48
51
50
45
/n
-0.5
2.5
1.5
-3.5
Variance $2 =
0.25
6.25
2.25
12.25
T (Xi-X)2/n-l
Bias
= (48+51+50^45)/4
= 194/4
X = 48.5 CD
B = X-T
= 48.5-50
B = -1.5 CU
. 25+6. 25+2. 25+12. 25)/3
/3 =
2.6 CU
s2 = 21/3 = 7.0
Based on these results the estimated bias of the measurement sys-
tem, under the above conditions, is -1.5 CU and.the estimated preci-
sion, expressed as the standard deviation, is 2.6 CU. On a practical
basis the bias is not considered to be significant Because the assumed
value T is contained within the range of the four measured values.
5.2.1.2 Population Parameters—
If a random variable X is measured many times, the calculated sam-
ple statistics will approach constant values referred to as popula-
tion parameters. For example, when n is very large, the sample
averaye X of n measurements approaches a value called the
population mean, or simply the mean, which is denoted by the
symbol ^. In the absence of measurement bias,> is the true value of
the quantity being estimated. Thus, The appropriate estimator for the
population mean M based on n measurements is the sample average X. The
value of X generally will not coincide with /* but does give the
best estimate based on the measurements available.
Similarly, if many measurements are made, the sample variance s^
approaches the population variance which is customarily denoted by
-------
In instances wnere precision estimates are occainea fro~, analyses
;- replicate pairs, tne range R (maximum value - mimmum value;
or relative range RR (10U R/X) is sometimes used as an index
of precision. For reolicate pairs tne relationship oetween tne
ranye and standard deviation is s = R/ /2~T
5.2.2.2 Bias-
Bias, as estimated witn sample statistics, is tne signed
difference between tne average X cf a set of measurements of a
standard and the "true" value of the standard T given by
B » X - T.
Bias can be negative or positive and is expressed in the units of
measurement or as a percentage of tne value of the standard. Percent-
age bias is given by
%B s 100 (X - T)/T.
Bias is also estimated by average percent recovery P (see
Section 5.4.1 for a definition of percent recovery). The relationsnip
Detween percent bias and average percent recovery is:
SB » P - 100.
5.2.3 Components of Variance
For any measurement system there are many sources of variation or
error, some of which are sample collection, handling, shipping, stor-
age, preparation, and analysis. For each individual or groupings of
error sources within a measurement system, there are different classi-
fications of variation or precision. Different classifications are the
result of tne different conditions and manner in which the data quality
assessments are made for estimating precision.
Intralaboratory precision is the variation associated with a
single laboratory or organization. Intralaooratory precision must be
further subclassified as short-term or long-term precision de-
pending on the conditions and manner in whicn the precision data are
obtained. Intralaboratory precision is usually referred to as
-------
5.2.1 Deri n1 ri ons_
"The most commonly used estimate of precision Is tne sample stan-
dard deviation, as defined In Section 5.2. Other precision measures
Include the coefficient of variation (100 s/X), range R (maxi-
mum value - minimum value), and relative range RR (100 R/X).
Collocated samples are independent samples collected in SUCH a
manner that they are equally representative of tne variable(s) of
interest at a yiven point in space and time. Examples of collocated
samples include: samples from two air quality analyzers sampling from
a common sample manifold or two water samples collected at essentially
the same time and from the same point in a lake.
A replicated sample is a sample that has been divided into two
or more portions, at some step in the measurement process. Each por-
tion is then carried through the remaining steps in the measurement
process.
A split sample is a sample divided into two portions, one of
which is sent to a different organization or laboratory and subjected
to the same environmental conditions and steps in the measurement pro-
cess as the one retained inhouse.
Collocated samples when collected, processed, and analyzed by
the same organization provide intralaboratory precision information
for tne entire measurement system including sample acquisition, han-
dling, shipping, storage, preparation and analysis. Both samples can
be carried through the steps in the measurement process together pro-
viding an estimate of short-term precision for the entire measurement
system. Likewise, the two samples, if separated and processed at dif-
ferent times or by different people, and/or analyzed using different
instruments, provide an estimate of long-term precision of the entire
measurement system.
Collocated samples when collected, processed and analyzed by
different organizations provide interlaboratory precision informa-
tion for the entire measurement system.
-------
;n of :ne measurement system, ana trie 3i;e of tne sample lot.
~zr "arge sample lots, a fixea frequency for replicate measurements
[sucn as one sample in ten or twenty) is recornmenaed. For small sample
lots, more frequent repetition may oe desiraale to ensure tnat suffi-
cient cata are available to assess precision. Alternatively, multiple
sample lots witn a common matrix, analyzed by tne same measurement sys-
tem, can oe comoined as aiscussec unaer continual precision assessments
'^Section 5.5). If tne environmental measurements normally produce a
hign percentage of results below tne MDL (see Section 5.5), samples for
replicate measurement should be selected from those containing measura-
ble levels of analyte. Where this is impractical, such as with complex
multi-analyte methods, sample replicates may be spiked at appropriate
concentration levels to ensure that sufficient data will be available
to assess precision.
Precision information can be dealt with in a variety of ways
depending on the specific situation of interest and the type of data
available.
Interpretation of precision data must always be based on a clear
knowledge of how the data were created. For example, the precision of
the entire measurement system, including sample acquisition, can only
be assessed by analyses of collocated samples. Precision data gener-
ated from multiple analyses of a standard only describe the stability
of the measurement device or instrument and only represent the ultimate
precision which could be achieved for a field sample jf_ the sampling
activity, suosequent sample preparation steps, and the sample matrix
had no impact on final results.
Figure 5-1 graphically outlines these samples in a general sense,
but specific sampling and analysis situations may require additional
precision information and more extensive breakdown of precision evalua-
tion samples. If this is the case, a clear indication of what is being
done and why should be provided in data quality assessment documenta-
tion.
5.3.3 Calculation of the Summary Precision Statistics
Summary statistics provide an assessment of the precision of a
measurement system or component thereof for a project or time period
(i.e., for a sample lot or group of sample lots). They may be used to:
-------
o estimate precision at ciscrete concentration levels.
o average estimated precision over appllcaole concentration
ranges.
o provide tne basis for a continual assessment of precision of
future measurements.
The summary statistics are developed from tne basic statistics
tnrouynout tne project or time period represented. Because
tne precision of environmental measurement systems is often a function
of c~"centration (e.y., as concentration increases, standard deviation
increases), this relationship snould be evaluated before selecting the
most appropriate form of the summary statistic. An evaluation of the
basic precision statistics as a function of concentration will usually
lead to one of three conclusions:
o Case 1: standard deviation (or range) is Independent of con-
centration (i.e.. constant);
o Case 2: standard deviation (or range) is directly proportional
to concentration, and coefficient of variation (or
relative range) is constant; or
o Case 3: both standard deviation (or range) and coefficient of
variation (or relative range) vary with concentration.
For simplicity of use and interpretation, the relationship most
easily described should be selected for use, i.e., for Case 1 the
standard deviation (or range) is simplest to work with; whereas, for
Case 2, the coefficient of variation (or relative range) is simplest.
If the relationship of precision to concentration falls into Case 3,
regression analysis can be used to estimate the relationship between
standard deviation (or range) and concentration.
The decision as to which case is applicable can be based on plots
of precision versus concentration or by regressions of s (or R) or CV
(or RR) versus concentration by an approach summarized in Table b-1 and
illustrated in the following examples.
-------
cv
xev1s;;- <:.
Date: Varcn
8-
8~v
te
30
2.1
2."
2.2-
2.1
10
40
Figure 5-2. Plots of CV (%) versus X (CU) and s (CU) versus X (CU)
for Example 5-2.
-------
•o inspection of tne cata taoulation of tne standard aaviation and
average for eac.n pair suggests tnat tne stanaard deviation increases as
tne average increased. Tnerefore, tne coefficient of variation values
were taoulated. An inspection of tne taoulation of CV versus average
reveals no clear relationship, i.e., the CV can be treated as a con-
stant across tne concentration range. These findings are confirmed oy
tne plots in Figure 5-3. Therefore, tne average CV (7%) is used as tne
precision summary for this sample lot. The precision, expressed as a
standard deviation, of individual measurements in this example, at any
concentration, X, is estimated to be, and is reported as, s = U.07X.
Example 5-4 (Case 3, s increases with increasing concentration and
CV decreases with concentration): If a constant relationship does not
appear to exist between standard deviation and concentration or between
coefficient of variation and concentration, then it is necessary to use
a more complex approach, such as a linear regression equation, to
describe the relationship. A least-squares linear regression analysis
of the precision (i.e., s or CV) versus measured concentration results
in two coefficients, a slope and an intercept, which are used to repre-
sent tne precision of the data set. The range and relative range are
sometimes used to estimate precision, particularly for replicate pairs,
because of their ease of computation and use.
For a study involving a IQU-sample lot, ID collocated sample pairs
were collected for estimating the precision of the entire measurement
system. The results for each set of collocated samples are tabulated
below alony with values for the average, range, standard deviation,
relative range, and coefficient of variation of each pair of samples.
To simplify visual interpretation, the data have been ordered by
increasing values of concentration.
Average Standard Relative Coefficient of
Xi X2 Ui+X2)/2 Range Deviation Range Variation (%)
5.33
10.1
19.5
la. 6
32.8
108.5
132.
Id6.
SUl.
3517
6.37
8.65
17.6
2U.5
36.1
1U2.
124.
197.
527.
3341
5.85
9.38
18.55
19. bb
34.45
1U5.2
128.0
191.5
514. 'J
3429
1.04
1.45
1.9
1.9
3.3
6.b
8.0
11.
26.
176
0.735
1.03
1.34
1.34
2.33
4.60
5.66
7.78
18.38
124.43
17.8
15.3
10.2
9.8
9.6
6.2
6.2
5.7
5.1
5.1
12
11
7
7
7
4
4
4 •
4
4
-------
.-3r orgamiations that prefer wor
-------
,5v 1 51 :
a t a ; '
13
error associatec witn an individual coservation X-j as fcl-
iows. Tne apcrcximate *5» prooaDility interval for tne differ-
ence in an observation X-j ana tne limiting average X (i.e.,
tne value mat woula oe ootainea if tne sample were analyzed
many times) Is ^_2 s. The aoproximate 95i prooability interval
for errors (excTuding 21 as) for inalvidual measurements in tm 3
sample lot is estimated to be _* 2 s = _+ 2(2.4 CU) = ^ 4.8 C'J.
o Case 2 (Example 5-3) . The estimate of intralaboratory , short-
term precision for individual measurements in tms sample let
including steps in tne measurement system from sample collec-
tion through analysis is s = 0.07X CU for concentrations in tne
approximate range of 1.5 to 5.0 CU, oased on the analyses of 8
field replicate pairs. For example, at X - 5.0 CU, the esti-
mated standard deviation is s = 0.35 CU, the approximate 95%
probability interval for errors (excluding bias), for X - 5.0
CU, is +. 2 s or +_ 0.7 CU.
o Case 3 (Example 5-4) . The estimate of intralaboratory, short-
term precision for individual measurements in this sample lot
including the total measurement system is s ~ 0.036X •*• 0.698,
for sample concentrations in the approximate range of 5 to 3500
CU, based on the results from 10 pairs of collocated samples.
The approximate 95% probability interval for the errors (ex-
cluding bias) in an individual measurement X is _+ 2 s - _+
2(0.036X + 0.698) CU. For example, at X - 100 CU, s • 4.3 CU ,
the approximate 95% probability interval for errors (excluding
bias) for X = 100 CU is +. 8.6 CU.
5.3.5 Continual Precision Assessments
For organizations in which sample lots are routinely analyzed and
data are reported on a frequent basis, the basic precision statistics
from multiple lots of a given sample matrix may be combined to provide
an estimate of long-term precision and an improved estimate of short-
term precision as illustrated in Section 5.6.3. This assessment can
also be extended to include subsequent lots, unless test results for
these new lots indicate that method precision is significantly differ-
ent. This combining of data quality assessment results permits the
laboratory to provide a precision assessment derived from a substantial
amount of background data rather than from limited precision data pro-
duced in a small study.
This procedure also provides the basis for the use of control
cnarts to monitor the performance of the measurement system. The
-------
3.- ASSESSMENT OF BIAS
5.-.1 2a'~ -i ti ons
Bias - an estimate of tne bias B is the difference between tne
average value X of a set of measurements of a standard and tne refer-
ence value of tne standard T given by:
B = X - T
Alternative estimates of bias are percent oias
SB = 100 (X - T)/T,
and average percent recovery P
n
P = £ P , and
1 = 1 1
Pi = 100 (Ai - Si)/T,
where A-j = the analytical result from the spiked sample a/id Bi »
the analytical result from separate analysis of the unspiked sample.
The relationship between percent bias and percent recovery is:
SB - P - 100
Reference material - A material of known or established concen-
tration that is used to calibrate or to assess the bias of a measure-
ment system. Depending on requirements, reference materials may be
used as prepared or may be diluted with inert matrix and used as blind
environmental samples.
Spiking material - A material of known or established concentra-
tion added to environmental samples and analyzed to assess the bias of
environmental measurements.
Target analyte spiking - Spiking with the analyte that is of
oasic interest in the environmental sample.
Matrix spike - A sample created by adding known amounts of the
target analyte to a portion of the sample.
Field matrix spike - A sample created by spiking target analytes
into a portion of a sample in the field at the point of sample acquisi-
tion. This data quality assessment sample provides information on the
target analyte stability after collection and during transport, ana
-------
Sarnie Soikinq Point
terDpetat'' on
Sample
Acquisition Preparation Analysis
Provides a oest case estimate
of Dias based on recovery;
includes matrix effects asso-
ciated with sample preserva-
tion, snipping, preparation
and analysis.
Provides an estimate of bias
based on recovery. Incor-
porates matrix effects asso-
ciated with sample preparation
and analysis only.
Provides an indication of
matrix effects associated with
the analysis process only.
Figure 5-5. The Use of Target Analyte Spikes for Bias Estimation
-------
dva-is2ie procedure for assessment of 01 as.. An aaaed attraction is tne
soility to obtain recovery aata on every field sample at relatively low
costs. It is used, 'or example, to evaluate tne applicaoility of
metnodoloyy and, indirectly, data quality assessments to individual
memoers of a sample lot. Sucn practices do not preclude the need to
assess bias oy spiking with the analytes being measured or reported.
5.4.2 Calculation of Bias Statistics
The most widely used summary of bias is by linear regression of
-;as on T; or, equivalently, regression of data quality assessment
results (X-j or X) on 7 (as illustrated in Section 5.6.3). For
the important special case of spiked samples as described above, tne
following approach may also be useful.
A portion of the samples in the sample lot is spiked at multiple
concentration levels to determine individual measurements of percent
recovery. These recoveries are used to calculate summary bias statis-
tics for the entire sample lot. The summary statistics are used to
estimate the percent recovery for each individual measurement in the
lot. For each sample spike i, calculate the percent recovery P.J by,
Pi * 100 (AT - BiO/Tj,
where: A-j = the analytical result from the spiked sample,
B-j = the analytical result from a separate analysis of
the unspiked sample,
T-J = the known true value of the spike.
Average percent bias is calculated from average percent recovery
for the sample spikes by the relationship
SB- P-100.
If reference materials instead of spiked samples are analyzed to
assess bias, percent recovery is calculated by the equation above with
B-j equal to zero.
Upon completion of the project or time period, the bias assessment
for the data set of environmental measurements is calculated from the
individual percent recoveries P-j observed through the project period.
Unless a relationship between the percent recovery, or its variability,
and concentration can be established, all percent recovery measurements
-------
beetiz~ ,;. :
R e v i 31 o " ',;.
U Z, w . ',
Tie j-rcent recovery associated witn any Tiai vicjal
measurement in tnis 1 Do-sample lot Is estimated tc be oetween 90% anc
106*, at trie 95» proDaoility level.
Example 5-8: In any application of statistics it is important to
identify underlying assumptions and cnecx tnem witn the aata by grapnic
display or statistical cnecxs. Figure 5-6 is a plot of recovery versus
concentration for analyses of sulfate ion deposited on Teflon* filters.
Evidently recovery is not constant, out is a sliyntly decreasing func-
tion of concentration. Therefore, a summary in terms of a single aver-
age percent recovery would be of questionable validity. This data is
examined in more detail using a linear regression approach in Section
5.5.3.
5.4.4 Reporting Bias
Each environmental measurement must be reported with an assessment
of bias. Bias should be expressed as a percent error interval of
%B +_ 2 Sp or as a percent recovery interval from P - 2 Sp to P +
2 Sp. (There are several ways to express bias and accuracy. It
should be noted here that expressing bias in this manner is not consis-
tent with the definition given in Subsection 5.4.1. Additional efforts
will be made to acnieve consistency in the definition and use of bias
in future revisions.) Where reference materials are used as a matrix-
free check on laboratory performance as a supplement to sample spiking,
only the results of the sample spikes should be submitted to an envi-
ronmental data base.
The data user should be provided with a narrative statement
explaining the reported bias estimate alony with tabulated percent
recovery intervals. The statement might read:
"Bias is expressed as a 95% probability interval around the aver-
age percent recovery. A percent recovery interval of 90 to 106%,
for example, means that approximately 954 of the time when a spike
of the measured material is recovered, the observed percent re-
covery can be expected to lie between 90 and 106%."
5.4.5 Continual Bias Assessment
As with precision assessments, laboratories in which small sample
lots are routinely analyzed and data are reported on a frequent basis
-------
:. e v: s' ;"
Z a t2: '•' •
•nay tomoine ens oasic :ias statistics of multiple snail sample lots of
a ji ven matrix into a single oias assessment for trie comoined sample
set. Tiis assessment can also be extenaea to induce suosequent small
sample lots, unless test results for these new lots indicate tnat
metnod Dias is significantly different.
Comoining bias data in this manner permits the laboratory to pro-
vi ae oias assessments derived from a substantial amount of background
aata rather tnan from limited bias data produced in a small study. It
also can provide the basis for the use of control charts to monitor
measurement system bias over time.
Historical data must first be combined as necessary to develop an
assessment of bias which includes the aetermination of averaye percent
recovery (?) and the standard deviation of the percent recovery
(Sp). These estimates maybe used to develop control chart limits as
P ^ 3 Sp for subsequent measurements. Each recovery measurement,
P-j, in a new sample lot must be compared with the control chart
limits. If each value for Pj falls within the control limits, the
historical percent recovery and analysis assessment can be applied to
all individual measurements of the new sample lot. If P^ falls
outside the control limits, either the historical assessment is not
applicaole to the new data set or the laboratory operation is out of
statistical control.
At least annually, and preferably after no more than 30 to 50 new
recovery measurements have been taken, the control chart limits must be
recalculated to reflect the current percent recovery capabilities of
the measurement system. This may be done by either expansion or
replacement of the historical data base to include the most current
data.
Example 5-9: A laboratory is analyzing and reporting samples on a
continual basis. Historical data for the analysis of spiked samples
established that P = 98.0%, and sp * 4.0%; the control chart limits
are P _+ 3 sp, or 86 and 110%. A sample with a measured background
level (87) of 22.0 CD was spiked with the equivalent of 30.0 CU (T)
without appreciably changing the sample volume. The result for the
analysis of the spiked sample (A-,-) was 49.2 CU. Therefore:
40 ? _ ?? n
P-j = 100 ,n n - 90.7%.
JU. J
-------
?a3e 1
DT scjssT en
7'iere nave been many terms used to designate detection limits ana
tney have seen defined in various ways. Lower Limits of Detection
(LLD), Minimum Detection Amount (MDA) , Method Detection Limit (MDL),
Detection Sensitivity, and Limit of Detection (LOD) are some of tne
terms used. Most authorities in the field agree that the smallest
detectable quantity, by whatever name, is related to the standard
deviation of sample analyses at or near zero analyte concentrations.
Since MDL is a basic performance characteristic of an analytical method
only its calculation, with example, is discussed.
5.5.2 MDL
Ideally each laboratory should establish and periodically reevalu-
ate its own MDL for each sample matrix type (for one time only matrix
types and multianalyte samples in difficult matrices, e.g., soils or
fish, this may be impractical) and for each environmental measurement
method. The MDL is determined for measurement systems by the analyses
of seven or more replicates of spiked matrix samples. As witn preci-
sion and bias, the assessment of MDL should be based upon the perfor-
mance of the entire measurement system. The standard deviation of the
responses (sm), in concentration units, is used to calculate the MDL
as follows:
MDL * sm (t.gg) Eq. 5-7
where:
t.gg = "Student's t value" appropriate for a one-tailed test at
the 99% confidence level and a standard deviation estimate
with n-1 degrees of freedom.
For example, if tne MDL is determined using measurements from seven
appropriate samples, then use t^g » 3.14 for n-1 » 6 degrees of
freedom. If the determination yielded a standard deviation of 0.15 CU,
the MDL is calculated (Equation 5-7) to be (3.14)(U.15 CU) - 0.47 CU.
-------
•; 5 V 5 " 3 " \Z . ./
To illustrate me application of tne statistical concepts previ-
ously aiscussed, aata from an actual laboratory measurement proyram are
presented and calculations of appropriate summary statistics are per-
formed. Tne example includes calculation of witmn-lot estimates of
precision and Dias as well as oetween-lot summary statistics to illus-
trate a procedure for continual data quality assessment and/or estimat-
ing long-term precision of projects of long duration. The within-lot
sample sizes are 3 or smaller in all but one case. Within-lot averages
and standard deviations computed from such small samples tend to be
imprecise estimates of the population mean and standard deviation. The
example shows how improved estimates of these quantities can be ob-
tained by averaging over the lots.
The average within-lot standard deviation provides a better esti-
mate of short-term, intralaboratory, precision for the total data set.
Likewise, using data quality assessments between- or across-!ots can
provide an estimate of between-lot variability, i.e., systematic error
from lot-to-lot as well as an estimate of total variability or long-
term precision over the subject time period.
The estimate of long-term precision is the appropriate measure to
use in describing the precision of the total data set. Estimates of
short-term (within-lot) precision and between-lot variability are use-
ful as part of a data quality assessment proyram in monitoring the
system's performance and can provide guidance for troubleshooting by
indicating which component(s) of the measurement system is experiencing
larger than normal variability.
The example goes somewhat beyond the treatment presented in Sec-
tion 5.4, by employing linear regression to summarize relations between
bias and concentration. In this example, a Tot is defined as all
measurements made within a given day, including routine analysis of
study samples and data quality assessment samples at one or more con-
centrations.
The example data are from a program for ion chromatography analy-
sis of sulfate deposits on Teflon* filters. Data quality assessment
samples in this program consisted of sulfate solutions at three differ-
ent concentrations, known to the analyst. The ion chrotnatograph was
-------
uata q'jal-v assessments far trie example sulfate analysis program
anc associated witnin-lot statistics (i.e., n, X, sw ana T) are pre-
sented in Taole 5-2 for tnree values of solution concentration, 0, 12'J ,
and 240 C'J. As seen in tne table, tne witnin-lot sample size (i.e.,
tne numoer of aata quality assessment samples) ranyes from n=l to n=6 .
The witnin-lot average and standard deviation can vary widely witn sucn
small sample sizes.
5.5.2 3etween-Lot Summaries
This procedure allows for the calculation of summary statistics
for a project time period that spans several lots. The following sta-
tistics are used to report data quality over a yiven time period (e.g.,
quarter, year). They are obtained from within-lot statistics described
in tne previous section, and are calculated for all data quality
assessments obtained under a particular set of fixed conditions, sucn
as matrix, concentration, and analysis procedure. For the example sul-
fate anaysis program, between-lot statistical summaries are calculated
for each (fixed) data quality assessment sample solution concentration.
Let nj = the number of data quality assessments
at a given concentration in the jth lot.
Xj = the average of the data quality
assessments at a given concentration for
the jth lot.
Sj = the standard deviation of the data
quality assessments at a yiven
concentration for the jth lot.
HJ = total number of data quality assess-
ments for the reporting period, where k =
total number of lots.
Then,
The grand weighted average is:
* „
X. £q. 5-8
n
J-l
-------
",n,e average witmn-iot stanaara deviation is:
K
V j-i
Trie oetween-iot (or among lots) standard deviation is:
Eq. 5-10
Total variation of single ooservations at the related concentra-
tion level over time is:
•f('!*4)1/z
Between-lot summary statistics for the sulfate sample data are
given in Table 5-3. Example calculations of between-lot summary sta-
tistics for Condition 1, where T = 240 CU, k s 6, and n * 21 are given
Delow:
J-l
(240.4) + Ij. (239.2) + |j. (240.4)
Ip (240.5) * |p (239.6) + |p (235.8)
X = 239.3 CU
£ ("j-U Sj^
s- » / V^ J J
w / 2- 21 - 6
J-l
. r2(1.44)2to(0.7I?2»2(i.44)2-t-2(3.70)2^2(0.72)2t-2(5.03)2] 1/2
L 15 J
-------
*- o-i
05)76
3(24U.4-239.3)2 + 6(239.2-239.3)2 + 3(240.4-239.3)2-
3(2*0.5-239.3)2 + 3(239.6-239.3)2 + 3(235.8-239.3)2 _ 2 4 = 2 "•;
(3+6+3+3*3+ 3)76I
sa = 1.03 CU
\ + s£ » 2.66 CU
Cl W
The summary statistics should be reported for each set of sample
conditions over the appropriate time period using the format of Table
5-3. (The value sa * 0 at true value 12U resulted from a negative
2
value for s| indicating that there was not significant
variation from lot to lot.)
5.6.3 Regression Summaries and Reporting Reduirements for a Project
or Time Period
Any measure of bias (e.g., recovery) or precision can depend on
the concentration T. Even wnen T is unknown, dependence of precision
on T may be seen as dependence on the apparent (measured) concentration
X. Regression summaries of bias and precision over all conditions pro-
vide a useful complement to summary statistics for individual sets of
conditions. Further, in a case where all the reference values, T, of
data quality assessment samples for a given reporting period are dif-
ferent, then between-lot statistical summaries for specific conditions
in the Table 5-3 format would be equivalent to lists of the raw assess-
ment data. A much more useful summary involves a regression and plot
of measurement X on reference value T.
-------
3
-J
5
LU
/%^
a.
£
O
^<
Lu O
< r>
o =a
on LU
oo LU
LU 3£
< i=
P =3
^-4
3 •
Z -3
—• O
.1 O
.1 —
uj c:
cc. LU
-JJ Q.
UJ
O
CL.
LU
OS
i
Lrt
-w
a?
u
L.
1/1
L» irt
l^
5 a.
z ^
o
c
01 01
S * 3
a.—
Ol u
•3 «
e »
01
2
MV
U
*«
C
Ol
•3
c
Ol
a.
o<
Ol
— 01
a. a.
5"
U
O
-
01
3
!/>
•^ >
*C ' •
-J >
— i. CD
J 0 -3
s
^
W1
u
Ol
a.
30
1
3
«
*-
Ol
3
4)
>
01
3
J?
Ol
•3
3
o
c
Ol
Ol
X
Ol
£3
s
C
S
i/*
*
£
&
^^
IX
I/I
-• > >l
«rt ^M
•0
• «j e
01 — in
^) •!• ^ V
• 01 a.
•3 u a. =
w o u > u a
0 — 0 C
1 t. l/t ^
c a 01 3
— S — O
j= -5 a. i-
-| u 5
— a. 5 <«-
X^- «i O
^
c
0
wt
U
Ol
a.
X
Ol
•O
01
a
13
.
r s-
-= g
Ol
-------
sw
6 -}
5 -
4 -
3 -
2 -
e -i
Rev. 31 ci
3 ate: Me
^aue 11 c
ea
120
T
tee
240
Figure 5-8, Plot of Witnin-Lot Standard Deviation sJJ (CU) versus T
(CU) for Sulfate Data Quality Assessment Results (Table 5-3]
i .1
e.s-
ee
120
T
180
248
Figure 5-9. Plot of Between-Lot Standard Deviation sa (CU) versus T
(CU) for Sulfate Data Quality Assessment Results (Table 5-3)
-------
o •
OO UJ
>- UJ
1 ^J
< UJ
^°
< a
O VI
u. p
UJ
2£ C3
>• —
Q£ »—
< as
UJ
as
i
Lf)
I
1
11
a.
0
~
Ol - b.
"= 3 "a
s Q.
O
S 0)
•o —
c -2
K -0 3
O.—
01 ^
•3 *
~"
Ol
.a
^
u.
*fl
w >
c
Ol
•a
c
o
oT
a
01
— 01
r*
(/>
U
o
iq IB
«-
Q =
O "~
SL2
X—
3
C2
.T
»
3
=
uD
5>
3
t
?VJ
0
Ol
3
^)
^
01
3
*•>
1
^
3
.^
•
Ol
T3>X
U
Of Of
> 31
U
>J 01
3 >
Ol
£ cZ^
"3 o oi —
IK
1/1
"5
a
01
3
t3
>
01
3
U
tJ
• O
01 1
•o _c
•0 w
« 5
-i O>
0 31
T t. 1 1
e 01 i/i
•^ >
w >
— U 01
z o •a
_Q
3
"^
1
Ol
3
a
^
si
s
U
CD
•O
t)
o
1
s
11
w
"°
.3
I
^
U
01
i,
a.
^
IX
Wf
I-il-.
Ol — m
•3 3.-1 Ol
• 01 3.
•o t. — =
w O K V
^ >— t_ U1
w >h ^ Ol
) U (rt *J
= 1±§
f - 3, L-
•*~ & 4^
(^
3 (-
— O
!«• W
"" 01
-------
-.ev: si c^ '-;.
3a*e: '-'drc?
Page 1 :f 5
SOURCES OF ADDITIONAL INFORMATION " •
5.7.1 Study Planning
1. "Conoilation of Data Quality Information for Environmen-
tal Measurement Systems," QAMS , U.S. EPA, Office of
Researcn ana Development, Washington, DC, 1983 (Draft).
2. "Interim Guidelines and Specifications for Preparing
Quality Assurance Project Plans, "QAMS-005/30, U.S. EPA,
Office of Research and Development, Washington, D.C.
20560, Decemoer, 1980.
3. Natrella, M.G., Experimental Statistics, N8S Handbook 91,
U.S. Department of Commerce, National Bureau of Stan-
dards, 1966.
4. Davies, 0. L., The Design and Analysis of Industrial
Experiments, 2nd edition, Hafner Puolisning Co., New
York, 1956.
5. Cox, D.R., Planning of Experiments. Wiley, New York,
1958.
6. Box, G.E.P., W.G. Hunter and J.S. Hunter, Statistics for
Experimenters. Wiley, New York, 1978.
7. Youden, W.J., "Statistical Aspects of Analytical Deter-
minations, "Journal of Quality Technology. 4(1), 1972,
pp. 45-49.
8. Elder, R.S., "Choosing Cost-Effective QA/QC Programs for
Chemical Analysis," EPA Contract No. 68-03-2995, Radian
Corporation, Austin, Texas, 1981 (draft).
5.7.2 Sampling
1. Environmental Monitoring and Support Laboratory, Handbook
for Sampling and Sample Preservation of Water and Waste-
water. EPA-600/4/82-029, U.S. EPA, Office of Research and
Development, Cincinnati, 1982.
2. Brumbaugh, M.A., "Principles of Sampling in the Chemical
Field," Industrial Quality Control. January 1954, pp.
6-14.
3. Kratochvil, B. and J.K. Taylor, "Sampling for Chemical
Analysis," Analytical Chemistry. 53(8), 1981, pp. 928A-
938A.
4. Currie, L.A. and J.R. DeVoe, "Systematic Error in Chemi-
cal Analysis", In: Validation of the Measurement Process,
ACS Symposium Series 63, American Chemical Society,
Wasnington, D.C., 1977, pp. 114-139.
-------
j a 13 • V a r ~ r
raye 2 of 5
12. Taylor, J.R., An Introduction to Error Analysis -- Tne
Study of Uncertainties in Physical Measurements, univer-
sity Sciences BOOKS, Mills Valley, California, 1982 iTms
is a general text) .
.4 ^ssessnent of Bias
1. Uriano, G.A. and C.C. Gravatt, "The Role of Reference
Materials and Reference Metnoas in Chemical Analysis,"
CSC Critical Reviews in Analytical Chemistry, 6t,4), 1977,
pp. 561-411.
2. Uriano, G.A. and J.P. Call, "Role of Reference Materials
and Reference Methods in the Measurement Process." In:
Validation of the Measurement Process. ACS Symposium
Series No. 63, American Chemical Society, Washington,
D.C., 1977, pp. 140-161.
3. Skogerboe, R.K. and S.R. Koirtyohann, "Accuracy Assurance
in the Analysis of Environmental Samples." In: Accuracy
in Trace Analysis. Vol. 1, NBS Special Publication 422,
U.S. Department of Commerce, National Bureau of Stan-
dards, 1976, 1976, pp. 199-210.
4. Watts, R.R., "Proficiency Testing and Other Aspects of a
Comprehensive Quality Assurance Program." In: Optimizing
Chemical Laboratory Performance throuyh the Application
"or Quality Assurance Principles. Association of Official
Analytical Chemists, Arlington, VA, 1980, pp. 87-115.
5. Horwitz, W.L., R. Kamps and K.W. Boyer, "Quality Assur-
ance in the Analysis of Foods for Trace Constituents,"
Journal of the Association of Official Analytical
Chemists, 63(6). 1980. pp. 1344-1354.
6. Colby, B.N., "Development of Acceptance Criteria for the
Determination of Organic Pollutants at Medium Concentra-
tions in Soil, Sediments, and Water Samples," EPA Con-
tract No. 68-02-3656, Systems Science and Software,
LaJolla, CA, 1981.
7. Bicking, C., S. Olin and P. Kiny, Procedures for the
Evaluation of Environmental Monitoring Laboratories.
Tracor Jitco, Inc., EPA-600/4-78-017, U.S. EPA, Office of
Research and Development, Environmental Monitoring and
Support Laboratory, Cincinnati , 1978.
8. U.S. Department of the Army, "Quality Assurance Program
for U.S. Army Toxic and Hazardous Materials Agency,"
Aberdeen Proving Ground, MD., August 1980 (draft).
9. Freeberg, F.E., "Meaningful Quality Assurance Program for
the Chemical Laboratory." In: Optimizing Chemical
Laboratory Performance Throuyh tne Application or Quality
Assurance Principles. Association of Official Analytical
Chemists, Arlinyton, VA, 1980, pp. 13-23.
-------
Z a t2: v a r c:
?a'3e : cf 3
12. Iglewic;, S. and R.H. Myers, "Comparison of Approxima-
tions to tne Percentage Points of tne Sample Coefficient
of Variation," Tecnnometrlcs, 12(1}, 197'j, pp. 155-170.
13. Environmental Monitoring ana Support Laboratory, Qua!ity
Assurance Handbook for Air Pollution Measurement Systems,
Volume I - Principles, EPA-5UJ/3-76-JU5 , U.S. EPA.'jffice
of Researcn ana Development, Research Tnanyle Par<, MC ,
1976.
14. GrvtDs, F.E. "Tne Difference Control Chart with an Exam-
p' - Its Use," Industrial Quality Control, July, 1946,
pp. .2-25.
15. Page, E.S., "Cumulative Sum Charts," Technometn'cs, 3(1),
1961, pp. 1-9.
16. Jackson, J.E., "Quality Control Methods for Several
Related Variables, "Technometrlcs. 1(4), 1959, pp.
359-377.
17. Jackson, J.E. and R.H. Morris, "An Application of Multi-
variate Quality Control to Photographic Processing,"
Journal of the American Statistical Association. 52,
1957, pp. 186-199.
18. Montgomery, D.C. and H.M. Wadsworth, "Some Techniques for
Multivariate Quality Control Applications," ASQC Techni-
cal Conference Transactions, 1972.
19. Frazier, R.P., J.A. Miller, J.F. Murray, M.P. Mauzy,
D.J. Schaeffer and A.F. Westerhold, "Establishing a
Quality Control Program for a State Environmental Labora-
tory," Water and Sewage Works. 121(5), 1974, pp. 54-57.
20. Hillier, F.S., "X and R-Chart Control Limits Based on a
Small Number of Subgroups, "Journal of Quality Technolo-
SL, 1(1), 1969, pp. 17-26.
5.7.6 Method Detection Limit
1. Glaser, J.A., O.L. Foerst, Q.D. McKee, S.A. Quave, W.L.
Budde, "Trace Analysis for Wastewaters," Environmental
Science and Technology. 15, 1981, pp. 1425-1435.
2. Hubaux, A. and G. Vos, "Decision and Detection Limits for
Linear Calibration Curves," Analytical Chemistry, 42,
1970, pp. 849-855,
3. "Guidelines for Data Acquisition and Data Quality Evalua-
tion in Environmental Chemistry," Analytical Chemistrv,
52, 1980, pp. 2242-2249.
-------
in *c . j
'•' 3 r *~ "•
I- I w, . - _, ,
5.3 A G.CSSARY OF TERMS
Antnmetic mean
(if for populations,
X for samples)
Bias
Coefficient of variation
Correlation Coefficient
error
Lot, batcn
Lot size (N)
Matrix
Method Detection Limit (MOL)
Observed value, observation,
or variate (X)
In a sample of n units, XT_,
X2 Xn, tne sum of the
ooserved values in tne sample
divided by the numoer of units in
tne sample.
Tne difference between trie popula-
tion mean and tne true or reference
value, or as estimated from sample
statistics, the difference between
the sample average and tne
reference value.
A measure of relative dispersion.
It is equal to the standard devia-
tion divided by the mean and multi-
plied by 100 to give a percentaye
value.
A number between -1 and 1 that
indicates the deyree of linear
relationship between two sets of
numbers.
The difference between an observed
value and its true value or the
probability interval that contains
the systematic and and random error
with l-tr confidence.
A definite quantity of samples
collected under conditions that
considered uniform.
are
The number of units
lot.
in a particular
The material in which the ana-
lyte(s) of primary interest is
embeded.
The lowest concentration of an
analyte that a measurement system
can "consistently detect" and/or
measure in replicated field
samples.
The particular value of a charac-
teristic and designated X^, X2,
X3, and so on.
-------
Stancarc Deviation X<
Stancarc aeviation(s)
Statistic
Universe or population
A measure of tne dispersion aooat
the mean of tne elements in a
population.
A measure of the dispersion aoout
tne average of tne elements in a
sample. An estimate of tne stan-
dard deviation of a population.
A constant or coefficient tnat
describes some characteristic of a
sample. Statistics are used to
estimate parameters of populations.
The totality, finite or infinite,
of a set of items, units, elements,
measurements, and the like, real or
conceptual, that is under consider-
ation.
-------
- a v i s i 3 n
tj
fc/1
t?
•B
tX
i/l
or*
a tx
t- 1: c
s °
1 X 5 *^
0) 3 ^
9 dfl C
* >» 0
O "
1 I/I *J
u o
•J -^
I/I
'o
o
i) 4-> u
S in 0
— e
^§•5
4^ (fl 4-1
O trt -^
c
0
u
•to* I/I
O w
J»|
'o j= u
w l-
(- — 3
f.K S
z
u
I'S
z
01
3
")5
* ^
0)
3
U
*~
§
1
U
(SI
„
ID
VO
00
en
=
' ' ' P /
.
e
o
+j
• to
s — •
o > e
3-85
« *J
*• ^ •«
> W —
-3 -5
(- w -a
fl in i-
^ «
e — * ^
ia *4 e
*J O «W
i at
« = >.
7 § £
e
5> u
u X "ia
V «^ *j
> OJ O
< CD —
* O
------- |