&EPA
                  • -* *—*" "-T —*— "^—*" V ^^^/ V^^ ^ur-^
Guidance on the Documentation
and Evaluation of Trace Metals Data
Collected for Clean Water Act
Compliance Monitoring
                                 > Printed on Recycled Paper

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Acknowledgements

IMS guidance was prepared under the direction of William A Telliard
Division (BAD) within the U.S. Environmental Protection Agency's
Engineering and Analysis Division (BAD).  This guidance was prepared under EPA
by the DynCorp Environmental Programs Division with assistance from Interface, Inc
                                                                            and Ar dyo,
Disclaimer

Tliis document has been reviewed and approved for publication by the Analytical Methods; S taffwUhin
L Engineering and Analysis Division of the EPA  Office of Water.  Mention of trade names or
commercial products does not constitute endorsement or recommendation for use.
Further Information

For further information, contact

       William A. Telliard, Chief
       Analytical Methods Staff
       Engineering and Analysis Division
       U.S. Environmental Protection Agency
       401 M Street
       Washington, DC 20460
       Phone: 202-260-7134
       Fax:   202-260-7185
 Requests for additional copies should be directed to:

        US EPA NCEPI
        11029 Kenwood Road
        Cincinnati, OH 45242
        513-489-8190

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                                                                                Chapter  1
                                                                                 Introduction

         Numerous organizations, such as state pollution control agencies, health departments  local
  government agencies, industrial dischargers, research facilities, and federal agencies (e.g  EPA
  ooO** data on effluent and ambient metal concentrations for use in a variety o
  determining attainment status for water quality standards, discerning trends m w
  effluent concentrations and variability, estimating background kJ* for total mab
  (TMDLs, assessing permit compliance,  and conducting research1.   The quality of data used is an

  SET rU5    ' m T00?' ^ qUality °f *aCe l6Vel metals data mav be compromised due to
  SSZS£ rg rP^g' mtT?°?' St°rage' "ld ^i8- * fact' one of *«» ««*»* obstacles faced
  by laboratories attempting ttace metals determinations is the potential for contamination of samples during
  rtcSTSL   "? ^   ^°rSeS-  TiaCe metalS *• Ubiquit°US fa *» ^ironment, and sLple^
  reaMy become contaminated by numerous  sources, including:   metallic or metal-containing labware
  rne^-containmg reagents, or metallic sampling equipment; improperly cleaned and stored equipment
  atmospheric inputs such as dirt, dust, or other participates from exhaust or corroded structoes.

          ? mf asurement of ttace metals at EPA **« q«aUty criteria (WQC) levels has been spurred by
  WOP  ±^f T °D " Wf r quaktybased aPProach to *» Control of toxic pollutants.  Current ambient
  WQC  eves for trace metals requu-e measurement capabilities at levels as much as 280 times lower than
  those levels reqmred  to support technology-based  controls or achievable by  routine  analyses
  environmental laboratories. Also, recent USGS and EPA studies strongly indicate mat rigorous steps
  be taken m order to preclude contamination during the collection and aldysis of «S
 crit™                             C°UeCted for ttace metals terminations at ambient water quality
 cntena levels are vahd and not a result of contamination, rigorous quality control (QC) must be SS
  oaU sample collection, preparation, and analysis activities. EPA has pubUshed analytical methods $983
 1991) for monitoring metals  in waters  and wastewaters, but these methods are inadequate for the
 2STSS-?   ,Tf CT,ent^°nS of metals fa ^bient waters due to the lack of soml or all of the
 jsenti^ quality control and handling criteria.  Tins  prompted the Engineering  and Analysis Division
 C5AD) to develop new sampling and analytical methods that include the rigorous sample handling and
 quality control procedures necessary to deliver verifiable data at WQC levels  The new samolins method
 is entitled, M**ad 1669:  Sampling Ancient Water for Detection of Tr^e M^a^l^er
                                                   icalmethods include Methods 1631 ,1632*636,
                                              ^ Methods")-  M^y of these analysis methods were
 rean                                       Wlth additi°nal quality contto1 "d sample handlSJ
 requirements; others are new methods that are based on newly developed analytical procedures
                                                           to
                                                                           Division Directo, and

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Data Evaluation Guidance
       Appropriate quality assurance (QA) and quality control (QC) procedures are the key to producing,
precise and accurate data unbiased by contamination. Examination of trace metals data without data from
blanks and other QC analyses yields little or no information on whether sample data are reliable. Data
gadfly must be documented through the use of blanks (both field and laboratory blanks), standards matoc
spikeLtrix spike duplicates, and field duplicates, as well as other QC analyses   The resulte of aU QC
procedures must be included in the data reporting package along with die sample results if data quality
is to be known.

        The remainder of this document contains guidance that is intended to aid in the review of trace
metals data submitted for compliance monitoring purposes under  the National Pollutant Discharge
SLL System (NPDES) when these data are collected in accordance with Method  669 and analyzed
byT 1600 Series Analysis Methods.  Chapter 2 of this document outlines the data elements that must
be reported by laboratories  and permittees so  that EPA reviewers can validate the data   Chapter 3
provides guidance concerning the review of data collected and reported in accordance with Chapter 2
Chapter 4 provides a Data Inspection Checklist that can be used to standardize procedures for documenting
the findings of each data inspection.

        The guidance provided in these chapters is similar in principle to the data reporting and review
 guidance provided in EPA's Guidance on Evaluation, Resolution, and Documentation  of Analyucal
Problems Associated™* Compliance Monitoring (EPA 821-B-93-001), but has been specifically adapted
 to reflect particular concerns related to the evaluation of data for trace metals.

        This guidance is  applicable to the examination of recently gathered trace metals date and to
 historical data in existing EPA databases. It should be noted, however that some qualification of historical
 dSa may be required before these data can be included in current databases.  A draft User sGuule to the
 SSS£^<^
 EMSL-LV), provides guidance that may be used to qualify data for inclusion into current databases  Thi
 EMstLV guidance stipulates that at least some form of QA/QC must be associated wrth the histoncal
 data for evaluation.  This QA/QC may be in the form of various types of b anks (method ^d,eteO.
 replicates field, analytical, etc.), spikes (matrix, surrogate internal standard, etcO, andPE samples Certified
 reference materials, QC check samples etc.). A scoring mechanism is applied to these QA/QC data, and
 the usability of the sample data is based on the resulting score.
                                                                                   January 1996

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                                                                        Chapter 2

                                               Checklist of Laboratory Data Required
                                  to Support Compliance Monitoring for Trace Metals
                                        Determined in Accordance with Method 1669
                                               and the 1600 Series Analysis Methods


        d^singtife^MMfor S^n * m^Z^ dementS neC6SSaiy tO ^^ "** ^^ data
               Levels (Method 1669) and the 1600 Series Analysis Methods^ should °L
                                    —* data  output, th<     '~  "
        Method Number



       In recognition of advances that are occurring in analytical technology, the 1600 Series Analysis
 Memods  are performance-based.  That is, an alternate procedure or tecSuque may be
 modrfications is to improve method performance on the sample being analyzed At no tin*
                                    E- •— *- - - -
2.
       Detailed Narrative

January 1996

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Data Evaluation Guidance


so that the data user can understand the reason(s) for acceptance/rejection of the data or any changes to
the reference method.
3.      Data Reporting Forms

        The complete data reporting package must include data reporting forms
analyzed, the Jab and metal species determined, and the concentrations found.  Analytes
          les at concentrations below the minimum level (ML) must be reported as non-detect&
           concentrations detected in blank samples must be reported, regardless of tiie level  Results
              fo?Lh sample analyzed, including any dilutions and reanalyse, Metals should be luted
by name and CAS Registry number.

        Tto ML is the quantitation level as  defined by the EPA 1600 series method used for sample
          ^laboratory is required to determine the MDL for each analyte m accordance with the
           delcribS in^O CRR Part 136, Appendix B- Definition and Procedure for DetermtnaUonof
           ^L Limit - Revision 1.11. Ttet MDL multiplied by 3.18 must be less than or equal to the
 ML given in the EPA  1600 Series Analysis Method.

         •Die use of data qualifiers or flags by the laboratory is discouraged.  Rather, laboratories should





 used.

 4.      Summary of Quality Control Results

         Results for all quality control analyses required by the reference EPA method must be presented
  in the complete datTreportmg package,  ff more than one method was used Or if more ton one se  of
  Tan^Vs wS andy^,l muftbe ckarly evident which QC corresponds to a given method and set of
  samples.

         Results for QC procedures that must be provided include, but are not limited to, the following
  (where applicable):

          Instrument tuning
          Calibration                                           ,  . .      ,  ,
          Calibration verification (initial and following every 10 analytical samples)
          Initial precision and recovery
          Ongoing precision and recovery
          Blanks
                 Laboratory (method) blanks
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                                                                         Data Evaluation Guidance
                 Field blanks
                 Calibration blanks
                 Equipment blanks
          Matrix spike/matrix spike duplicates
          Field duplicates
          Method of standard additions (MSA) results
          Spectral interference checks
          Serial dilutions
          Internal standard recoveries
          Method detection limits
          Quality  control charts and limits
  Table 2 lists the required frequency and purpose of the QC procedures.
  5.
Raw Data
  •mhmitt 57            an?yS6S mUSt te kept °n me at ** ^oratory (Chapter 2, Section 7) and
  neaH   ^ "*   ? tothe ^ ""*"« UpOn "*"*• ^ ^trument output (en^ssion Lens^
  peak height area, or other signal intensity) must be traceable from the raw data to L final result SpoS
  The raw data must be provided for not only the analysis of each field sample but also for all caSS"
                         instrument specific md mav include' ^t are not limited to, the
 following^ ***
        Sample numbers and other identifiers
        Digestion/preparation or extraction dates
        Analysis dates and times
        Analysis sequence/run chronology
        Sample weight or volume
        Volume prior to each extraction/concentration step
        Volume after each extraction/concentration step
        Final volume prior to analysis
        Injection volume
        Matrix modifiers
        Dilution data, differentiating between dilution of a sample or an extract
        Instrument (make, model, revision, modifications)

        c!Z^fr0dUfT SyS!em (^asonic nebulizer' hydride generator, flow injection system, etc.)
        Column (manufacturer, length, diameter, chelating or ion exchange resin etc )
                                                               P-^-dentrfpower,flow
       Detector (type, wavelength, slit, analytical mass monitored, etc.)
       Background correction scheme
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Data Evaluation Guidance
       Quantitation reports, data system outputs, and other data to link the raw data to the results

       DkeSistrument readouts (e.g., strip charts, mass spectra, printer tapes, and other recordings of
       raw data) and other data to support the final results                                  J
       Lab bench sheets and copies of all pertinent logbook  pages  for all  field and QC  sample
       preparation and cleanup steps, and for all other parts of the determinations
 6.      Example Calculations

        Example calculations that will allow an independent reviewer to determine how toe laboratory used
 the raw data to arrive at a final result must be provided in the data reporting package if any adjustments
 Se Ltd 7* the equations included in the method,  Useful examples ^^fe bo* detfed ^ ^g
 compounds.  Htto laboratory or the method employs a standardized reporting level for undetected
 compounds, this should be made clear in the example calculation. Adjustments made for sample volume,
 dilution, internal standardization, etc. should be evident.
 7.     Archiving Data on Magnetic Media

        It is not necessary for the laboratory or responsible organization to submit digitized binary
 hexadecimal, or other raw signal recordings with the data package. However, the laboratory tot performs
 dte Ldysis hould archive these data so that the raw reduced data can to reconstructed, and the. Utonto*
 orOrganization responsible for reporting the data should be prepared to submit raw data on magnetic
 medif To* request by EPA. Magnetic media may be required for automated data review, for diagnosis
 of data reduction problems, or for establishment of an analytical database.


 8.      Names, Titles, Addresses, and Telephone Numbers of Analysts and QC Officer

         The names  titles,  addresses,  and telephone numbers of the analysts  who  performed the
 determinations and'the quality control  officer who verified the results must be  included in die data
 matte package.  If the data package is being submitted by a person or organization other ton to
 SX kSory it is that person or organization's responsibility to ensure that the laboratory provides
 all the data listed above and that all method requirements are met. For example,  with regards to effluent
 or ambient monitoring data submitted by an NPDES permittee on a Discharge Momtonng Report (DMR),
 die task of collecting and reporting quality control data falls to die permittee.

         In addition, the personnel, tides, addresses, telephone numbers, and name (if different from the
  laboratory that analyzed the field samples) of the facility that cleaned and shipped the sampling equipment
  id Derated the equipment blanks, the laboratory (if different) that analyzed the equipment b anks and
  ti?e facility responsible for the collection, filtration, and transport of the field samples to the laboratory
  must be obtained and included in die data reporting package.
                                                                                     January 1996

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                                      Table 1
   Method Numbers, Analytical Techniques, Method Detection Limits, and Minimum Levels
  Method
    1631
              Technique
           Oxidation/Purge &
             Trap/CVAFS
   1632
   1636
   1637
   1638
   1639
 Metal
                                          MDL (pgfl,)1
Mercury
  1640
                            ML
0.000054
                           0.0002
  Lowest EPA
 Water Quality
Criterion (ug/L)3

       0.012
lydride AA
Ion
romatography
C/STGFAA

ICP/MS








iTGFAA





yiCPMS


•MMMMBL
1 Arsenic
1 Hexavalent
Chromium
Cadmium
Lead
Antimony
Cadmium
Copper
Lead
Nickel
Selenium
Silver
Thallium
Zinc
Antimony
Cadmium
Trivalent
Chromium
Nickel
Selenium
Zinc
Cadmium
Copper
Lead
Nickel f
•MMMMM!
0.002
. 0.23
0.0075
0.036
1 0.0097
0.013
0.087
0.015
0.33
0.45
0.029
0.0079
0.14
1.9
0.023
0.10
0.65
0.83
0.14
0.0024
0.024
0.0081
0.029
•OMMBMnL
0.005
0.5
0.02
0.1
0.02
0.1
0.2
0.05
1
1
0.1
0.02
0.5
5
0.05
0.2
2
2
0.5
0.01
0.1
0.02
0.1
•^^••MMI
"~ — i
0.018 1
10 1
0.37 |
0.54 1
14 1
0.37 1
2.4 1
0.54 1
8.2 1
5 1
0.32 1
1.7 1
1 32 1
14 1
0.37 1
57 1
8.2 1
5 I
32 §
0.37 1
2.4 §
0.54 1
8.2 1
M^^_H^^^_J
Method Detection Limit as determined by 40 CFR Part 136, Appendix B



ss;:^
                                                             i3'

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                                                                               Chapter 3
                                                              Guidance for Reviewing Data
                                                  from the Analysis of Trace Metals Using
                                      Method 1669 and the 1600 Series Analysis Methods


         Use of the guidelines provided below, or of similarly developed standardized protocols  is
  recommended as a tool with which Regional and State permitting authorities cT^^
  inspection and acceptance procedures and minimize differences that might otherwise result between date
               " Pe™?f ^P°nSible f°r SUbmitting data'  A Data InsP*cti™ C^ckliSt has^ bin
                ***?  *? ,f°UOWing Chapter-   ™S Checklist Provides a standardized format for
                         ^^
1.
         Purity and Traceabiliiy of Reference Standards
mM«     nt
measurement. In
                     °f ™y n0n;?bSOlUte 6mpirical mea^ement is dependent on the reference for that
                    ermining pollutants in water or other sample matrices, the analytical instrument and

                  -St * ^^ Wlth a known refereace ™teliai of documented^ S
             This information need not be provided with every sample analysis.  Rather, it sho^d be
 maintamed on file at the laboratory and provided upon request. When ialyses are conducted mlconLct

 ±S TV      T^? U°n Sh°Uld * pr°Vided t0  *" permittee ** ** *« that the laborSoS is
 employed for specific analyses and updated as needed.                                  ««««ry 15,


 2.     Number of Calibration Points


        The 1600 Series Analysis Methods specify that a minimum of three concentrations are to be used
 when calibrating the instrument. One of these points must be the Minimum Level (ML, seTJem 5)  Sd
 note must be near the upper end of the calibration range. Calibration must be peJL^SS^

          ie   7 S3mPleS ^f^ m analyZed-  ^ USe of *e ML as a point on the calibration curie
               means by which to assure that measurements made at this quantitation level are reliable.
 ™v,       d^f^iewef.ushould revie^ me points used by the laboratory to calibrate the instrument and
 make certain that the calibration range encompasses the Minimum Level and that all sample and QC
 measurements are  within the calibration range.   Samples that produced results  J£H£eSS £

 n±T6OoT ^ SA°1 T, ^ f Uted and reanalyZed " aCCOrdance with «» specificationTde^
 Lt  o th     ^ ^     °d ^ ^ US6d by ^ Iab°rat0iy- ""» ^^ sa™Ple ««to need only
 apply to those analytes that exceeded the calibration range of the instrument  fc other words  it is
 acceptable to use data for different analytes from different levels within the same sample.  SomI flexlbmty

                                      1 « onl
dat, flj ^ t°m "I311315;? °f ** dantod S3mple *" D0t provided' ^^ "* can be made of the
data that are above the  calibration range (>10%).  The response  of the analytical instrument to
concentrations of analytes will eventually level off at concentrations above the calibration
January 1996

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Data Evaluation Guidance


it is not possible to specify the concentration at which this will occur, it is generally safe to assume that
to%££ concenLS above the calibrated range is a lower limit of the  actual «J£^£
Therefore, if the concentration above the calibration range is also above a regulatory limit, it is a virtual
certainty that the actual concentration would also be above that limit.

3.      Linearity  of Calibration

        The relationship between the response of an analytical instrument to the concentration or amount
of an anSIntroduced into the instrument is referred  to as the "calibration curve". An  analytical
instrument can be  said to be calibrated in any instance in which an instrumental response can  be:
to the concentration of an analyte.  The response factor (RF, calculated for external standard cahb
or Sati^ response factor (RRF, calculated for internal standard calibration) is the ratio of the response
of the instrument to  the concentration  of the analyte introduced into the instrument. Equations  tor
calculating RFs and RRFs are provided in the 1600 Series Analysis Methods.

        While the shape of calibration curves can be modeled by quadratic equations or higher order
           al functions, most analytical  methods focus on a calibration range in which.to  meat
           is essentially a function of the concentration of the analyte.  The advantage of the  linear
      ration is that the RF or RRF represents the slope of  calibration curve, simplifying calculations  and
      interpretation.   The 1600 Series Analysis Methods contain specific criteria for determmmg to
      ™ of calibration curves determined by either an internal or external standard technique.  When the
           criterion is met, the calibration curve is sufficiently linear to permit the laboratory to use an
          IP or RRF,  and it is assumed that the calibration curve is a straight line that passes ^ough toe
  zero/zero calibration  point.  Linearity is determined by calculating the relative standard deviation (RSD)
  Se RF oTS for each analyte and comparing this RSD to the specified limit. The^specific  acceptance
  criteriaarelisted  m the  Data Inspection Checklist (Chapter 4, Item 12) and in the 1600 Series Analysis
  Methods. TJiese methods also include alternative procedures to be used in the event the linearity criteria
  fail specifications.

         The laboratory  must provide the RSD results by which an independent reviewer can judge
  linearity even in  instances hi which the laboratory is using a calibration curve. In these instances, the ctata
  reviewer should review each calibration point to assure that the response increases as me concentration
  SSSses  If it does not, the instrument is not operating properly, and the data should not be considered
  valid.

  4.     Calibration Verification

         Calibration verification involves the analysis of  a single standard, typically  in the middle of the
  calibration range, at the beginning (and,  in  some  cases,  at the end) of  each analytical  shift  The
  ctnceZtion of each analyte in a reference standard is determined using the initial calibration data and
  compared to specifications  in the method.  If results are within the specifications   the ^oratory may
  pZed with analysis without recalibrating. The initial calibration data are then used to quantify^sample
  results  Specific criteria for acceptance  of calibration verifications are provided m the Data Inspection
  Checklist (Chapter 4, Item  17) and the 1600 Series Analysis Methods.
   10
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                                                                          Data Evaluation Guidance



   nr* f  ^f °n Verification' which is used m *e 1600 Series Analysis Methods, differs in concept and




   uutial calibration, all subsequent sample analyses are conducted using the new respons  fXorc  The

         °         S       ""    ""*** "  <" *«** ^—e Lween thfold
                                         ** * am°UDtS t0 a ^ sin^-P^ calibration.
  r I-K       16«° SeiieS ^^y818  Methods require calibration verification after every ten samnles
  Calibration verification is performed by analyzing an aliquot of the mid-point ctftaS s^cS? and
  obtaining results that meet the specifications contained in L methods. These speSficate a^Sen for








  5.      Method Detection Limit and Minimum Level
 limit (Mutadv,                         Iab°rat0ry t0 Perform a method Section
 urnit (MDL) study for each analyte  in accordance with the procedures given in 40
 Appendix B. The MDL studies are conducted to demonstrate tL the
                                                                  ^
 methods. The MDL studies were conducted by at least one laboratory for each method and

January 1996
                                                                                           11

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Data Evaluation Guidance
              low the ML, the data reviewer should require the responsible party to correct and resubmit
               TcxTO of action is not possible, the reviewer should determine the sample-specific ML
and consider results below that level to be non-detects for regulatory purposes.

        If sample results are reported above the ML, but are below the faculty's regulatory compliance




S^muSu^ 51 ttofc «4*> resdK in OKier «o detennin. if the level of poHu«, daecfcdmay
be attributable to contamination.

        Although sample results are to be reported only if they exceed the ML, all blank results are to be
 reported  r^ardless of the level.  This reporting requirement allows data reviewers the opportunity to
           Spact of any blank contamination on sample results that are reported above the ML.
complian
         the
    '   It is important to remember that if a change that will affect the MDL is made to a method foe




 and were capable of producing the desired MDLs.

         The procedures given in this document are for evaluation of results for determination °f regulatory
       ianS'and not for assessment of trends, for triggering or for J^^i^L^^
                  rtine of all results, whether negative, zero, below the MDL, above the MDL but below
                 S ML. may be of value and may be required by the permitting authority as necessary
  to enforce ^ a particular ckcuWance. Dealing with the multiplicity of consequences presented by such
  results, either singly or in combination, is beyond the present scope of this document.

  6.      Initial Precision and Recovery

         The laboratory is required to demonstrate its ability to generate acceptable precision and accuracy



  SSStatoen that laboratories that have  difficulty passing the start-up test have such marginal
  performance that they will have difficulty in the routine practice of the method.

          The test consists of spiking four aliquots of reagent water with the metals of interest at 2 - 3 times
  the MLS«rrUstedPin the method and analyzing these four aliquots. The mean concenttaUon
  S) and the standard deviation (s) are then calculated for each analyte and compared to the specifications
  in tS memoS! If the mean and the standard deviation are within the limits, the laboratory can use the
  method to analyze field samples.
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                                                                          Data Evaluation Guidance
  hv th  i ^   t      P u       /   t0 ^ ^ sPecifications ^ the method, none of the data produced
  by the laboratory can be considered to be valid. If the laboratory did not perform the start-up tests the
  data cannot be vahd, unless all other QC criteria have been met and the laboratory has submitted ffR^d
  associated  mstrument QC  data that were generated after-the-fact by the  same analyst on foe * ame
  instrument. If these conditions are met, then the data reviewer may consider thb data to be acceptable for
  most purposes  NOTE: The^ inclusion of this alternative should not in any way Sl±S to^c
  die practice of performing IPR analyses  after the analysis  of field samples.  Rather, EPA believls
  demonstration of aboratory capability  prior to sample analysis is an" essential QC

  Si1 * 1S Pr°V1^ }£* " f t001 t0 Peimitting aUth°ritieS When  data have *«** ben collected
  ±Sedt i™Z   f   STleS'  °nCe *" Pr°blem haS *« identified> * re
  expected to implement corrective action necessary to ensure that it is not repeated.

         It is important to remember that if a change is made to a method, the IPR procedure must be
  repeated using the modified procedure. If the start-up test is not repeated when these steps are rTdffiS
  or added, any data produced by the modified methods cannot be considered to be valid.      moamea

  7.      Analysis of Blanks

         Because trace metals are ubiquitous in the environment, the precautions necessary to preclude
                  h111016 eX?S1Ve *IHI?Me reqUked t0 Preclude cont^ation when sy^etic^rganic
  fcon™        t Q0n~f iqmr T?^68 m determined- EPA h<* f°™
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Data Evaluation Guidance
from its cleaning facility, maintain these results on file, and provide them to the permitting authority upon
r^uest  The data reviewer should evaluate equipment blank results only if it is necessary to identify
potential sources of contamination present in field blanks.

        Controlling laboratory contamination is an important aspect of the quality assurance plan for the
equipment-cleanm! facility, laboratory, and field team.   Each party should maintain records regardmg
Urik contamination. Typically, these records take the form of a paper trad for each piece of equipment
anTcontrol charts, and Sey should be used to prompt corrective action by the party •"°^"*£>.
contamination.  For example, if records at a single site suggest that equipment blanks  laboratory blanks,
and calibration blanks are consistently clean but that field blanks show consistent levels ofoootanmation,
then the field sampling team should re-evaluate their sample handling procedures, identify the problem,
^TuStirute corrective actions before collecting  additional samples.   Siimlarly  equipment  cleamng
facilities and laboratories should utilize the results of blank analyses to identify and correct problems in
their processes.

        Unfortunately, it is often too late for corrective action if data are received that suggest the presence
 of uncontrolled contamination that adversely affects the associated data.  The exception to this rule is the
 casTui which the field and equipment blanks show no discernable levels of contamination, 'ontammation
 is deleted in the laboratory or calibration blanks, sample holding times have not expired and sufficient
 sample volume remains to allow the laboratory to identify and eliminate the source of contamination and
 rSyze the associated sample(s). In all  other cases, the reviewer must exercise one of several options
 listed below when making use of the data.

        If a contaminant is present in a blank but is not  present in a sample, then there is little need for
         concern about the sample result. (It may be useful, however, to occasionally review *e raw data
         for samples without the contaminant to ensure that the laboratory did not edit the results for this
         compound.)

         If the sample contains the contaminant at levels of at least 10 times that in the blank, then the
         likely contribution to the sample from the contaminant in the sample is at most 10%. Since most
         of the methods in question are no more accurate than that level, the possible contamination  is
         negligible, and the data can be considered to be of acceptable quality.

         If the sample contains the contaminant at levels of at least 5 times but less than 10 times the blank
         result  the numerical result in the sample  should  be considered an upper limit of the  true
         concentration, and data users should be cautioned when using such data for enforcement purposes.

         If the sample contains the contaminant at levels below 5 times the level in the blank, the sample
         data are suspect unless there are sufficient data from analyses of multiple blanks  to  perform a
         statistical analysis proving the significance of the analytical result.  Such statistical analyses are
         beyond the scope of this guidance.

         If Mask contamination is found in some types of QC samples but not others (e.g., only in the
         laboratory blank but not in the field blank), the data user should apply the guidelines listed above,
   14
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                                                                           Data Evaluation Guidance
         but may also use this information to identify the source of contamination and take corrective
         actions to prevent future recurrences.

         There are two difficulties in evaluating sample results relative to blank contamination.  First the
  reviewer must be able to associate the samples with the correct blanks.  Field blanks are associated with
  each group of field samples collected from the same site. Calibration blanks are associated with samples
  by the date and time of analysis on a specific instrument.  Laboratory (method) blanks are associated with
  each batch of 10 samples prepared and digested in accordance with a particular method during a single
  shift. If Hie reviewer cannot associate a batch of samples with a given blank, the reviewer should request
  this  association from the laboratory so that the results for the samples can be validated.

         The second difficulty involves samples that have been diluted.  The dilution of the sample with
  reagent water represents an additional potential source of contamination that will not be reflected in the
  results for the blank unless the blank was similarly diluted. Therefore, in applying the 10-times rule stated
  above, the concentration of the sample is compared to the blank results multiplied by the dilution factor
  of the sample. For instance,  if 1.2 ppb of a contaminant is found in the blank, and the associated sample
  was  diluted by a factor of six relative to the extract  from the blank prior to analysis, then the diluted
  sample result would have to be greater than 1.2 x 6 x 10 or 72 ppb to be acceptable.  Diluted sample
 results between 36 and 72 ppb would be considered an upper limit of the actual concentration, and diluted
  sample results that were less than 36 ppb would be considered unacceptable in the absence of sufficient
 blank data to statistically prove the significance of the result.

        In  most cases,  the practice of subtracting the concentration reported in the blank from the
 concentration in the sample is not recommended as a tool to evaluate sample results associated with blank
 data.  One of the most common problems with this approach is that blank concentrations are sometimes
 higher than one or more associated sample results, yielding negative results.

        Nearly all of the 1600 Series Analysis Methods are capable of producing MDLs that are at least
 10 times lower than the lowest water quality criteria (WQC) published in the National Toxics Rule Since
 most discharge permits require monitoring at levels that are comparable to or higher than the WQC
 published in the National Toxics Rule, EPA believes that, in nearly all cases, laboratories should be
 capable of producing blank data that are at least 10 times less than the regulatory compliance level  It
 should also be noted that laboratories cannot be held accountable for contamination that is present in field
 blanks but  not present in laboratory blanks; in such  cases the sampling crew should take corrective
 measures to eliminate the source of contamination during then: sample collection and handling steps.


 8.      Ongoing Precision and Recovery

        The 1600 Series Analysis Methods require laboratories to prepare  and analyze an "ongoing
 precision and recovery" (OPR) sample with each batch  of up to 10 samples started through the extraction
 process on the same twelve hour shift.  This OPR sample is identical to the aliquots  used in the IPR
 analyses (see Item 6), and the results of the OPR are  used to ensure that laboratory performance is in
 control during the analysis of the associated batch of field samples.
January 1996
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Data Evaluation Guidance
       The data reviewer must verify that the OPR sample has been run with each sample batch and that
the applicable recovery criteria in the analytical method have been met. If the recovery criteria have not
been met, the reviewer may use the following guidelines when making use of the data:

       If the concentration of the OPR is above method specifications but that analyte is not detected in
       an associated sample, then it unlikely that the sample result is affected by the failure in the OPR.

       If the concentration of the OPR is above method specifications and that analyte is detected in the
       sample, then the numerical sample result may represent an upper limit of the true concentration,
       and data users should be cautioned when using the data for enforcement purposes.

       If the concentration of the OPR is below method specification but that analyte is detected in an
       associated sample, then the sample result may represent the lower limit of the true concentration
       for that analyte.

       If the concentration of the OPR is below method specification and that analyte is not detected in
    '    an associated sample, then the sample data  are suspect and cannot be considered valid  for
       regulatory compliance purposes.

        If the OPR standard has not been run, there is no way to verify that the laboratory processes were
 in control. In such cases, a data reviewer may be able to utilize the field sample data by examining the
 matrix spike recovery results (see item 9), the BPR results, OPR results from previous and subsequent
 batches  and any available historical data from both the laboratory and the sample site. If the matrix spike
 results associated with the sample batch do not meet  the performance criteria in the methods, then the
 results for that set of samples cannot be considered valid.  If the laboratory's IPR results and the matrix
 spike results associated with  the sample batch in question meet the all applicable performance criteria in
 the methods, then the data reviewer may be reasonably confident that laboratory performance was in
 control during field sample analysis. This level of confidence may be further increased if there is a strong
 history of both laboratory performance with the method and method performance with the sample matrix
 in question, as  indicated by additional OPR and matrix spike data collected from the laboratory and
 samples from the same site.

 9.      Precision and Recovery of Matrix Spike and Matrix Spike Duplicate Compounds

         The 1600 Series Analysis Methods require that laboratories spike  the  analytes of interest into
 duplicate aliquots of at least one sample from each group of ten samples collected from a single site. The
 first of these spiked  sample aliquots is known as the matrix spike sample; the second is known as the
 matrix spike duplicate.  These spiked  sample aliquots are used to determine if the method is applicable
 to the sample matrix in question. The 1600 Series Analysis Methods are applicable to the determination
 of metals at concentrations typically found in ambient water samples and certain treated effluents (e.g.,
 the part-per-trillion to low  part-per-billion range).  These  methods may not be applicable to marine
 samples and many effluent and in-process samples collected from industrial dischargers. Therefore, it is
 important to evaluate method performance hi the sample matrix of interest.
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                                                                           Data Evaluation Guidance
         In evaluating matrix spike sample results, it is important to examine both the precision and
  accuracy of the duplicate analyses. Precision is assessed by examining the relative percent difference
  (RPD) of the concentrations found in the matrix spike and matrix spike duplicate samples, and comparing
  the RPD to the acceptance criteria specified hi the analytical method.  If the RPD of a matrix spike/matrix
  spike duplicate pair exceeds the applicable criterion, then the method cannot be bonsidered to be applicable
  to the sample matrix, and none of the associated sample data can be accepted for regulatory compliance
  purposes.

         If RPD criteria are met, the method is considered to be capable of producing precise data hi these
  samples, and the data reviewer must then verify that the method is capable of producing accurate data
  Accuracy is assessed by examining the recovery of compounds in  the matrix spike and matrix spike
  duplicate samples.  If the recovery of the matrix spike and duplicate are within the method-specified limits
  then the method is judged to be applicable to that sample matrix. If, however, the recovery of the spike
  is not within the recovery range specified, either the method does not work on the sample, or the sample
  preparation process is out of control.

        If the method is not appropriate for the sample matrix, then changes to the method are required
  Matrix spike results are necessary in evaluating the modified method. If the analytical process is out of
  control, the laboratory must take immediate corrective action before any more samples are analyzed.

        To separate  indications  of method  performance  from those of laboratory performance,  the
 laboratory should prepare and analyze calibration verification standards and OPR samples. If the results
 for either of these analyses are not within the specified range, then the analytical system or process must
 be corrected. After the performance of the analytical system and processes have been verified (through
 the successful analysis of CCV and OPR samples), the spike sample analysis should be repeated. If the
 recovery of the matrix spike and duplicate are within the method-specified range, then the method and
 laboratory performance can be considered acceptable.  If, however, the recovery of the matrix spike does
 not meet the specified range, the laboratory should attempt to further isolate the metal and repeat the test.
 If recovery of the metal remains outside the acceptance criteria, the data reviewer may apply the following
 guidelines when attempting to make use of the data:

        If the recovery of the matrix spike and duplicate are above method specifications  but that metal
        is not detected hi an associated sample or is detected below the regulatory compliance limit, then
        it unlikely that the sample result is affected by the failure in the matrix spike.

        If the recovery of the matrix spike and duplicate are above method specifications and that metal
        is detected hi an associated sample above the regulatory compliance level, then the sample result
        may represent the upper limit of the true concentration,  and the data should not be considered
        valid for regulatory compliance purposes.

        If the concentration  of the matrix spike and duplicate are below method specifications but that
        metal is detected hi an associated sample, then the sample result may represent the lower limit of
        the true concentration for that metal. If the metal was detected in the sample at a concentration
        higher than  the regulatory compliance limit, then it is unlikely that the sample result is adversely
January 1996
                                                                                             17

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Data Evaluation Guidance
        affected by the matrix. If, however, the metal was detected below the regulatory compliance limit,
        the data should not be considered valid for regulatory compliance purposes.


10.     Statements of Data Quality for Spiked Sample Results

        The 1600 Series Analysis Methods specify that after the analysis of five spiked samples of a given
matrix type, a statement of data quality is constructed for each analyte.  The statement of data quality for
each analyte is computed as the mean percent recovery plus and minus two times the standard deviation
of the percent recovery for the analyte. The statements of data quality should then be updated by the
laboratory after each five to ten subsequent spiked sample analysis.

        The statement of data quality can be used to estimate the true value of a reported result and to
construct confidence bounds around the result. For example, if the result reported for analysis of selenium
is 10 ppb, and the statement of data quality for selenium is  84% ± 25% (i.e., the mean recovery  is 84%
and the standard deviation of the recovery is 25%), then the true value for selenium will be in the range
of 9.4 - 14.4 ppb, with 95% confidence. This range is derived as follows:

        Lower Limit =  [(10 -r .84) - (10 x .25)] = [11.9 - 2.5] = 9.4 ppb
        Upper Limit = [(10 -=- .84) + (10 x .25)] = [11.9 + 2.5] = 14.4 ppb

        Many laboratories do not provide the data quality statements with the sample results, in which case
the data reviewer must determine if the data quality statements are being maintained for each analyte and
may need to obtain the data. If necessary, the reviewer can construct the data quality statement from the
individual data points.  The lack of a data quality statement does not invalidate  results but makes  some
compliance decisions more difficult.  If statements of data quality are not being maintained by the
laboratory, there may be increased concern about both specific sample results and the laboratory's overall
 quality assurance program.

 11.    Statements of Data Quality for Spiked Reagent Water Results

        In addition to statements of data quality for results of analyses of the compounds spiked into field
 samples, the 1600 Series Analysis Methods require that statements of data quality be constructed from the
 initial  and ongoing precision and recovery data.  The purpose of these statements is to assess laboratory
 performance  in the practice of the method, as compared to  the assessment of method performance made
 from the results of spiked field samples.  Ideally, the two statements of data quality would be the  same.
 Any difference could be attributable to either random error or sample matrix effects.

 12.    Field Duplicates

        Method 1669 requires the collection of at least one field duplicate for each batch of field  samples
 collected from the same site. The field duplicate provides an indication of the overall precision associated
 with entire data gathering effort, including sample collection, preservation, transportation, storage, and
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                                                                            Data Evaluation Guidance
  analysis procedures.  The data reviewer should examine field duplicate results and use the following
  equation to calculate the relative percent difference between the duplicate and its associated samples.
                                                    (D1+D2)
         where:
         Dl = concentration of the analyte in the field sample
         D2 = concentration of the analyte in the duplicate field sample


     .    If the analyte of interest was not detected in either replicate of the field sample, then the RPD will
 be zero. If the analyte was detected in each field sample replicate, but the results are highly disparate
 (indicated by a large RSD), the reviewer should apply the following guidelines when making use of the
 data:

         If the analyte was detected in each replicate and at similarly variable concentrations in the blank
         samples, then the field sample variability may be attributable to variable contamination, and the
         data may not be valid for regulatory compliance purposes.

         If the analyte was  detected in each replicate  at a concentration  well above the regulatory
         compliance level, but was not detected in the associated blank samples, then it is likely that the
         sample results are not adversely affected.

        Ideally, the RPD between field duplicates and MS/MSD samples will be identical.  Any difference
 between the two is attributable to variability associated with the field sampling process.
January 1996
                                                                                              19

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                                                                              Chapter 4

                                                                 Data Inspection Checklist
        The following pages contain a data inspection checklist that may be used by data reviewers
 laboratory personnel, and other parties to document the results of each data inspection in a standardized
 format.
January 1996
                                                                                        21

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                                    Data Inspection Checklist
 1.  Name of Reviewer
                                       Summary Information
                                                      ^•M
                                                       Tide:
                   Required Samples
                         Sample Results Provided
    Sample Location or Sample ID
Analyte(s)
Sample Location or Sample
           ID
                                                                                      Analyte(s)
 2. Method Used:

 3*. Total No. of analytical shifts per instrument (determined from analysis run log):
         Instrument
                                                       No. of Shifts
 4. Total No. of CCVs Required:             	
 (one for each 10 samples after the
 first 10 samples on each instrument)

 5. Total No. of CCBs Required:             	
 (one for each CCV)

 6. Total No. of Field Blanks Required:       	
 (one per site or per 10 samples, whichever is more
 frequent)
  7.  Total no. of Lab Blanks Required:
  (one per batch" per method/instrument)
               Total No. of CCVs Reported:
               Total No. of CCBs Reported:
  8. Total no. of OPR analyses Required:
  (one per batch per method/instrument)

  9. Total no. of MS/MSD samples Required:
  (one per 10% per matrix per site)

  10. Total no. Field Duplicates Required:
  (one per 10 samples per site)

  11. Total no. of MDL results required:
  (one per method and per analyte)
               Total No. of Field Blanks Reported:
                Total No. of Lab Blanks Reported:
                Total No. of OPR Analyses Reported!.
                Total No. of MS/MSD samples Reported:
                Total No. of Field Duplicates Reported:.
                Total No. of MDL Results Reported:.
22
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                                         Data Inspection Checklist
     12.



     a.


     b.
                                  Initial Calibration



 Was a multiple point initial calibration performed*?                         Eyes    dno


 Were all sample concentrations reported within the calibration range?         dyes    dno


 If no, list method and analytes for which initial calibration was not performed or which exceeded
 the calibration range.
    c.
 Analv
                           No ICAL CY/N) Exceeded ICAL Range
    d.-     Did the initial calibration meet linearity criteria?                           dyes   dno


    e.      K no, was a calculation curve used to calculate sample concentrations?       dyes   dno


    lA^f *?? (m™?? ^ «*»«*»> should be performed for each analyte; if the RSD of the mean RRF is less than 15% or if
    the RSD of the mean RF is less than 25%, then the averaged RRF or RF, respectively, may be used for tot analyte.
    13.



    a.


   b.


   c.


   d.
                 Method Detection Limit (MDL)/Minimum Level (ML)



Did the laboratory demonstrate their ability to achieve the required MDL?     dyes   Dno


Did the initial calibration range encompass the ML?                        dyes   dno


Were all field samples detected below the ML reported as non-detects?       dyes   dno


If the answer to item a, b, or c above was "no", describe problem:
January 1996
                                                                                                    23

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                                   Data Inspection Checklist
 14.



 a.



 b.



 c.



 d.



 e.
         Initial Calibration Verification (ICV)/Initial Calibration Blanks (ICB):




Was an ICV run prior to field samples?                                 nves   nno



Were ICV results within the specified windows?                          Eyes   Dno




Was the ICV followed by an ICB?                                  .   nves   Dno



Was the ICB free from contamination?                                  Dyes   Dno



If any item  in a - d above was answered "no", list problems below:



               Failed ICV Recovery     Concentration Detected in ICB   Affected Samples
 15.



 a.




 b.



 c.



 d.
                        Initial Precision and Recovery (DPR)




 Were IPR data reported for each analyte?                                nves   nno




 Did all IPR aliquots meet required recovery criteria (x)?                   Eyes   Dno




 Did the standard deviation (s) of each IPR series meet the required criterion? Dyes   Dno




 If any item in a - c above was answered "no", document problem below.




 Analvte Ave. Result Reported (X)       RSD Reported   Affected Samples
  16                           Ongoing Precision and Recovery (OPR)




  a.      Were OPR data reported for each analyte, instrument, and batch?           Dyes   Dno



  b.      Did all OPR samples meet required recovery criteria (x)?                  dyes   Dno




  c.      If item a or b above was answered "no", document problem below.



         Analvte OPR Recovery OO Reported     Shifts Missing OPR     Affected Samples
24
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                                       Data Inspection Checklist
    17.



    a.



    b.



    c.




    d.




    e.
      Continuing Calibration Verification (CCV)/Continuing Calibration Blank (CCB)



 Were CCVs run prior to each batch of 10 samples on each instrument?      Dyes   Dno



 Were all CCV results within the specified windows?



 Was each CCV followed by a CCB?




 Was each CCB free from contamination?




 If any item in a - d above was answered "no", list problems below:




 Analyte Affected Samples        Shift Missing CCV/CCB      Failed CCV/CCB ID
    Dyes   Dno



    Dyes   Dno




    Dyes   Dno
   18.



   a.



   b.



   c.
                           Laboratory (Method) Blanks



Was a method blank analyzed for each instrument & sample batch?




Was each method blank demonstrated to be free from contamination?



If the answer to item a or b was "no", document problems below.



Analyte     Affected Samples       Blank Concentration Reported
    Dyes   Dno



    Dyes   Dno








Shift Missing MB
   19.



   a.



   b.



   c.
                                  Field Blanks




Was a field blank analyzed for each 10 samples per site?




Was each field blank demonstrated to be free from contamination?




If the answer to item a or b was "no", document problems below.




Analyte    Affected Samples       Blank Concentration Reported
   Dyes   Dno




   Dyes   dno








Shift Missing FB
January 1996
                                                                                              25

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                                   Data Inspection Checklist
 20.


 a.

 b.

 c.

 d.


 e.
                               MS/MSD Results


Were appropriate number of MS/MSD pairs analyzed?                     Eyes   Dno

Were all MS/MSD recoveries within specified windows?                  Eyes   Dno

Were all RPDs within the specified window?                            dyes   Dno

Was appropriate corrective action (e.g., MSA for GFAA, serial dilution
for ICP) employed on affected samples?                                Dyes   Dno

If the answer was "no" to items a - d above, document affected samples:
         Analyte MS % R
                      MSD%R
MS/MSD RPD   Affected Samples
  21.


  a.

  b.

  c.

  d.
                             Additional Information


Were Instrument Tune Data Provided?                                 Eyes   dno

Were equipment blanks demonstrated to be free from contamination? Dyes   Dno

Were statements of data quality provided?                              Eyes   Dno

Did field duplicate demonstrate acceptable precision?                     Dyes   Dno
26
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                                                                                     Glossary
  Accuracy:  The degree of agreement between a measured value and the true or expected value of the
  quantity of concern.

  Calibration Blank: A sample of reagent water analyzed after the calibration verification standard to
  check for contamination attributable to the analytical system.

  Calibration Range (Calibration Curve):  A graphical relationship between the known values for a series
  of calibration standards and instrument responses, specifically the linear  portion of this relationship
  between calibration standards.

  Dissolved Metals:  The concentration of metal(s) that will pass through a 0.45 micron filter assembly,
 prior to acidification of the sample.

 Equipment Blank:  An aliquot of reagent water that is subjected in the laboratory to all aspects of sample
 collection and analysis, including contact with all sampling devices and apparatus. The purpose of the
 equipment blank is to determine if the sampling  devices and apparatus for sample collection have been
 adequately cleaned prior to shipment to the field  site. An acceptable equipment blank must be achieved
 before the sampling devices and apparatus are used for sample collection.

 Field Blank:  An aliquot of reagent  water that is  placed in a sample container hi the laboratory, shipped
 to the sampling site, and treated as a sample in all respects, including contact with the sampling devices
 and exposure to sampling site conditions, storage, preservation, and all analytical procedures, which may
 include  filtration.  The field blank is used to determine if field sample handling processes, sample
 transport, and sampling site environment have caused sample contamination.

 Field Duplicates: Two identical aliquots of a sample collected hi separate sample containers at the same
 time and place under identical circumstances and sample collection techniques, and handled in exactly the
 same manner as other samples.  Field duplicates  are used as a measure of the precision associated with
 sample handling, preservation, and storage as well as laboratory handling, preparation,  and analytical
 procedures.

 Initial Precision and Recovery (IPR): A series of four consecutively analyzed aliquots of reagent water
 containing the analyte(s) of interest at 2 - 3 times the ML. IPRs are performed prior  to the first time a
 method is used and any time the method or instrumentation is modified.  The IPR is used to demonstrate
 the analyst/laboratory ability to generate acceptable  precision and accuracy through the calculated mean
 (x) and standard deviation (s)  for each analyte.

 Laboratory Blank:  An aliquot of reagent water  that is treated exactly as a sample including exposure
 to all glassware, equipment, solvents, reagents,  internal standards, and surrogates that  are used with
 samples, the laboratory  blank is used to determine  if analytes or interferences are present in the laboratory
 environment, reagents, or the apparatus.
January 1996
                                                                                              27

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Magnetic Media: A storage medium on which all instrumentally acquired raw data may be retained.

Matrix Spike (MS) and Matrix Spike Duplicate (MSD): Aliquots of an environmental sample to which
known quantities of analytes are added in the laboratory.  The MS and MSD are analyzed under the same
conditions as other samples and are used to quantify the bias and precision associated with the sample
matrix. The background concentration of the analytes in the sample are determined and subtracted from
the MS and MSD results.

Method Blank:  See 'laboratory blank".

Method Detection Limit (MDL):  The minimum concentration of an analyte that, in a given matrix and
with a specified method, has a 99% probability of being identified, qualitatively  or quantitatively
measured, and reported to be greater than zero.

Minimum Level (ML): The lowest level at which the entire analytical system gives a recognizable signal
and acceptable calibration point.

Ongoing Precision and  Recovery (OPR):  An aliquot of reagent water containing the analyte(s) of
interest  The OPR is used  to demonstrate continuing ability of the analyst/laboratory  to generate
acceptable results based on target and standard recoveries.

Qualify Assurance (QA): An integrated system of activities involving planning, quality control, quality
assessment, reporting, and quality improvement to ensure that a product or service meets defined standards
of quality with a stated level of confidence.

Quality Control (QC):  The overall system of technical activities designed measure and control the
quality of a product or service so that it meets the needs of users. The  aim is to provide quality that is
satisfactory, adequate, dependable, and economical.

Precision: The  degree of mutual agreement characteristic of independent measurements as  the result of
repeated applications of the process under specified conditions.

Reagent Water: Water demonstrated to be free from the metal(s) of interest at the method detection limit
 (MDL) of the analytical method to be used for determination of the metal(s)  of interest.

 Reference Standards:  A material or substance, one or more properties  of which are sufficiently well
 established to be used for the calibration of analytical apparatus, the assessment of a measurement method,
 or assigning of values to materials.

 Trace Metals:  Concentrations of metals found at or near their established water quality criteria levels.
 28
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                                                                           Appendix A

                                                           EPA Water Quality Criteria for
                                             Priority Pollutant Metals and Metals Species


  The table provided on the following page provides the freshwater, marine, and human health water quality
  criteria published by EPA for priority pollutant metals and metals species.  Human health criteria reflect
  values published by EPA in the National Toxics Rule at 57 FR 60848. Aquatic criteria reflect values
  published by EPA in the National Toxics Rule and in the Stay of Federal Water Quality Criteria for
  Metals (60 FR 22228). This table includes criteria for both total recoverable metals and dissolved metals
  In addition, the table includes freshwater criteria that are based on a hardness of 100 mg/L  In order to
  provide a worst-case scenario, the table also includes criteria that are based on a hardness of 25 mg/L
  <"»™  Calculations for deriving these values were published by EPA at 60 FR 22228.
January 1996
                                                                                        29

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