United States
Environmental Protection
Agency
Office of Acid Deposition,
Environmental Monitoring and
Quality Assurance
Washington DC 20460
EPA/600/4-89/031
April 1989
Research and Development
Direct/Delayed Response
Project: Quality
Assurance Plan for
Preparation and Analysis
of Soils from the
Mid-Appalachian
Region of the
United States

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                                                  EPA/600/4-89/031
                                                  April 1989
      Direct/Delayed  Response  Project:
     Quality Assurance  Plan for Preparation
          and Analysis  of  Soils from  the
Mid-Appalachian  Region of the United States
                              by
      M.L. Papp, R.D.  Van Remortel,  C.J. Palmer, G.E. Byers,
    B.A. Schumacher, R.L. Slagle, J.E. Teberg, and M.J.  Miah
                        A Contribution to the
                 National Acid Precipitation Assessment Program
                       U.S. Environmental Protection Agency
                       Region 5, Library (5PL-16)
                       230 S. Dearborn Street, Eaom 167-0
                       tgaicago, JL  60604
                           U.S. Environmental Protection Agency
                   Ollice of Modeling, Monitoring Systems, and Quality Assurance
                     Office of Ecological Processes and Effects Research
                           Office of Research and Development
                              Washington, D.C. 20460
               Environmental Monitoring Systems Laboratory, Las Vegas, Nevada 89193
                    Environmental Research Laboratory, Corvallis, Oregon 97333

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                                        Notice
     The information in this document has been funded wholly or in part by the U.S. Environmental
Protection Agency under Contract  Number  68-03-3249 to Lockheed Engineering and Sciences
Company and Cooperative Agreement Number 81-2189-03 to the Environmental Research Center of
the University of Nevada at Las Vegas. Additional cooperation has been provided under Contract
Number 68-03-3246 to NSI Technology Services Corporation.  It has been subject to the Agency's
peer and administrative review and  it has been approved for publication as an  EPA document.

     Mention of corporation names, trade names, or commercial products does not constitute
endorsement or recommendation for use.

     This document  is one volume  of a set which fully describes  the Direct/Delayed  Responce
Project, Mid-Appalachian Soil Survey. The complete document set includes the  major data report,
quality assurance plan, laboratory analysis handbook, field and laboratory operations reports, and
quality assurance reports.  Similar  sets are being produced for each Aquatic Effects Research
Program component  project.  Colored  covers, artwork, and the use of the project  name in the
document title serve to identify each companion document set.

     The correct citation of this document is:

Papp1, M. L,  R. D. Van Remortel1,  C. J. Palmer2,  G. E. Byers1,  B. A Schumacher1,  R.  L Slagle1,
     J. E. Teberg1, and M. J. Miah1. 1989.  Direct/Delayed Response Project:  Quality Assurance
     Plan for Preparation and  Analysis of Soils from the Mid-Appalachian Region of the United
     States. EPA/600/4-89/031.  U.S. Environmental Protection Agency, Las Vegas, Nevada.
1 Lockheed Engineering and Sciences Company. Las Vegas, Nevada 89119.
2 Environmental Research Center, University of Nevada, Las Vegas, Nevada 89114.

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                                       Abstract
     The  Direct/Delayed Response Project is designed to address  the  concern over potential
acidification of surface waters by atmospheric sulfur deposition within the United States. The Mid-
Appalachian Soil Survey is  being conducted  as a  synoptic  physical and  chemical  survey to
characterize a statistical sampling of watersheds in a region of the United States believed to be
susceptible to the effects of acidic deposition.  The survey has benefited from information gained
during two previous, similar surveys.  This document addresses the design and implementation of
a quality assurance program and the verification of the analytical data base  for the Mid-Appalachian
Soil Survey.  It is addressed primarily to the users of the data base who will be analyzing the data
and making  various assessments and conclusions relating to the effects  of acidic deposition on
the soils of the Mid-Appalachian region, the third and final region characterized during the project.

     Data quality is assessed by addressing detectability, precision, accuracy, representativeness,
completeness, and comparability of the data.

     This plan is submitted in partial fulfillment of Contract Number 68-03-3249 by Lockheed
Engineering  and  Sciences  Company, Las Vegas,  Nevada,  under  sponsorship of  the  U.S.
Environmental Protection Agency.
                                            in

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                                        Contents
                                                                           Page    Revision
Notice  	   ii           1
Abstract	  iii           1
List of Figures 	  vii           1
List of Tables	viii           1
Acknowledgments	  ix           1
List of Abbreviations	   x           1
Executive Summary	  xii           1

1.   Introduction  	  1 of 2        1
    1.1   Directives  	  1 of 2        1
    1.2   Sources of Information  	  1 of 2        1

2.   Project Description	  1 of 6        1
    2.1   Project Overview  	  1 of 6        1
    2.2   Project Organization  	  2 of 6        1
         2.2.1   Project Management  	  2 of 6        1
         2.2.2   Laboratory Responsibilities  	  5 of 6        1
         2.2.3   Primary Cooperators  	  5 of 6        1

3.   Sampling Strategy  	  1 of 2        1
    3.1   Watershed Selection and Mapping	  1 of 2        1
    3.2   Selection of Sampling Classes	  2 of 2        1

4.   Field and Laboratory Operations	  1 of 8        1
    4.1   Field  Operations  	  1 of 8        1
        4.1.1   Personnel   	  1 of 8        1
        4.1.2   Sampling Activities	  1 of 8        1
    4.2   Preparation Laboratory Operations	  2 of 8        1
        4.2.1   Personnel  	  3 of 8        1
        4.2.2   Preparation Activities	  3 of 8        1
    4.3   Analytical Laboratory Operations	  5 of 8        1
        4.3.1   Personnel  	  5 of 8        1
        4.3.2   Laboratory Activities  	  5 of 8        1
    4.4   Sample Custody	  8 of 8        1

5.   Quality Assurance Objectives  	  1 of 17        1
    5.1   Overview of Quality Objectives	  1 of 17        1
    5.2   Design Characteristics  	  2 of 17        1
        5.2.1   Quality Evaluation Samples  	  3 of 17        1
        5.2.2   Quality Control Samples  	  7 of 17        1
    5.3   Description of Measurement Quality Objectives	10 of 17        1
        5.3.1   Field Sampling and Characterization	 11 of 17        1
        5.3.2   Sample  Preparation	13 of 17        1
        5.3.3   Laboratory Analysis	13 of 17        1

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                               Contents (Continued)
                                                                         Page    Revision
6.   Quality Assurance Implementation  	   1 of 10       1
    6.1  Control of Data Quality	   1 of 10       1
        6.1.1  Field Sampling and Characterization	   1 of 10       1
        6.1.2  Sample Preparation	   2 of 10       1
        6.1.3  Laboratory Analysis	   3 of 10       1
        6.1.4  On-Site Systems Audits	   3 of 10       1
    6.2  Data Verification	   5 of 10       1
        6.2.1  Field Sampling and Characterization Data	   5 of 10       1
        6.2.2  Preparation Laboratory Data  	   5 of 10       1
        6.2.3  Analytical Laboratory Data	   6 of 10       1

7.   Data Quality Assessment and Reporting  	   1 of 3        1
    7.1  Statistical Design  	   1 of 3        1
        7.1.1  Assessment of Detectability	   1 of 3        1
        7.1.2  Assessment of Precision  	   1 of 3        1
        7.1.3  Assessment of Accuracy	   1 of 3        1
        7.1.4  Assessment of Representativeness  	   2 of 3        1
        7.1.5  Assessment of Completeness  	   2 of 3        1
        7.1.6  Assessment of Comparability	   2 of 3        1
    7.2  Overview of Validation Procedures	   2 of 3        1
    7.3  Quality Assurance Reports to Management  	   3 of 3        1
        7.3.1  Status Reporting	   3 of 3        1
        7.3.2  Formal Reporting	   3 of 3        1

8.   Data Management System  	   1 of 3        1
    8.1  Overview of the Data Bases  	   1 of 3        1
        8.1.1  Field Sampling Data	   1 of 3        1
        8.1.2  Preparation Laboratory Data  	   1 of 3        1
        8.1.3  Analytical Laboratory Data	   3 of 3        1
    8.2  Data Base Audits 	   3 of 3        1

References	   1 of 2        1

Appendices

A.   SCS-SOI-232 Field Data Form and Codes  	   1 of 14       1
B.   Preparation Laboratory Data Forms	   1 of 11       1
C.   Analytical Parameters Measured in the Mid-Appalachian Soil Survey ...   1 of 5        1
D.   Analytical Laboratory Verification Criteria	   1 of 17       1
E.   Analytical Laboratory Pre-Award Evaluation Scoring Sheet  	   1 of 7        1
F.   Analytical Laboratory On-Site Evaluation Questionnaire	   1 of 54       1
G.  Field Data Verification Procedures	   1 of 18       1
H.   Preparation Laboratory Verification Procedures   	   1 of 12       1
I.   Preparation Laboratory On-Site Evaluation Questionnaire 	   1 of 9        1
J.   Quality Assurance Reanalysis Templates	   1 of 21       1
K.   Analytical Data Verification  and Validation Flags  	   1 of 5        1
                                            VI

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                                     Figures

Figure                                                      Section   Page    Revision

2-1  DDRP Regional Surveys	  2    1 of 6       1
2-2  DDRP Major Operations  	  2    3 of 6       1
2-3  DDRP Operational Management Structure 	  2    4 of 6       1
2-4  DDRP Quality Assurance Management Structure at EMSL-LV ...  2    5 of 6       1

5-1  Assessment Samples Used in Mineral Sample Batches  	  5    4 of 17      1
5-2  Assessment Samples Used in Organic Sample Batches	  5    5 of 17      1

8-1  DDRP Data Management Operations Flowchart  	  8    2 of 3       1
                                         VII

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                                         Tables

Table                                                           Section   Page    Revision

1-1   Quality Assurance Subjects in Supporting Documents	  1      1 of 2        1

4-1   Preparation Laboratory Parameters   	  4     4 of 8        1
4-2  Analytical Laboratory Parameters  	  4     6 of 8        1
4-3  Laboratory Data Qualifiers  	  4     7 of 8        1
4-4  Decimal-Place Reporting Requirements  	  4     7 of 8        1

5-1   Status/Assessment of Measurement Samples  	  5     6 of 17       1
5-2  Quality Control Requirements for Analytical Batches	  5     8 of 17       1
5-3  Within-batch  Precision Objectives for Field Samples	  5   12 of 17       1
5-4  Within-batch  Precision Objectives for Preparation Samples	  5   14 of 17       1
5-5  Preparation Laboratory Measurement Quality Objectives	5   15 of 17       1
5-6  Within-batch  Precision Objectives for Analytical Samples  	  5   16 of 17       1
                                            VIII

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                                Acknowledgments
     External peer reviews by the following individuals are gratefully acknowledged: D. R. DeWalle,
School of Forest Resources, Pennsylvania State University, University Park,  Pennsylvania; D. W.
Johnson, Oak  Ridge National Laboratory, Oak Ridge, Tennessee;  W. K. Smith, Department of
Statistics, Temple University, Philadelphia, Pennsylvania;  C.  M. Thompson, U.S. Department of
Agriculture (USDA) Soil Conservation Service (retired), Temple, Texas; and W. J. Walker, Department
of Land and Water Resources, University of California, Davis,  California.

     The authors wish  to acknowledge the  following individuals for  their  technical assistance
during the development of this document: J. J. Lee, U.S. Environmental Protection Agency, Corvallis,
Oregon; D. A. Lammers,  USDA Forest Service, Corvallis, Oregon; D. L Cassell, D. S. Coffey, M. G.
Johnson, J. S. Kern,  and  P. W. Shaffer, NSI Technology Services Corporation, Corvallis, Oregon; R.
S. Turner, C. C. Brandt, and M. B. Adams, Oak Ridge National Laboratory, Oak Ridge, Tennessee;
D. D. Schmoyer, Martin Marietta Energy Systems, Oak Ridge, Tennessee; P. A.  Gowland, Automated
Sciences Group, Oak Ridge, Tennessee; T. H. Starks, University of Nevada, Las Vegas, Nevada; and
M. H. Bartling, W. H. Cole. J. V. Burton, J. K. Bartz, R. L. Tidwell, R. W. Gerlach, K. C. Shines, G. A.
Raab, D. V. Peck, R. C. Metcalf, and J. L. Engels, Lockheed Engineering and Sciences Company, Las
Vegas, Nevada.

     The following  individuals provided editorial and logistical support and  are  gratefully
acknowledged:  D. W. Sutton, D. J. Chaloud, L. A. Stanley, K.  M.  Howe, R. B. Corse, S. L Pierett,
J.  R. Baker, L. K. Marks, J. D. Hunter, L. M. Mauldin, P. F. Showers, and  A. Tippett, Lockheed
Engineering and Sciences Company, Las Vegas, Nevada.  B. N.  Cordova, Lockheed Engineering and
Sciences Company,  Las Vegas, Nevada is acknowledged for exceptional word processing and
graphics support.

     Finally, we appreciate the support of the technical director, M. R. Church, and our technical
monitor, L. J. Blume, during the development of this quality assurance plan.
                                           IX

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                              List of Abbreviations
AA             atomic absorption spectrometry
AC_BACL       barium chloride triethanolamine exchangeable acidity
AD~           analytical duplicate
AERP          Aquatic Effects Research Program
AL_AO         acid oxalate extractable aluminum
AL_CD         citrate dithionite extractable aluminum
AL~CL         exchangeable aluminum in unbuffered ammonium chloride
AL_CL2        aluminum in 0.002M calcium chloride
AL~PYP        pyrophosphate extractable aluminum
ALSOW        analytical laboratory statement of work
ANOVA        analysis of variance
BD_CLD        clod bulk density
BD_KV         known volume bulk density
CA_CL         exchangeable calcium in unbuffered ammonium chloride
CA~CL2        calcium in 0.002M calcium chloride
CA  OAC        exchangeable calcium in buffered ammonium acetate
CEC           cation exchange capacity
CEC_CL        unbuffered  ammonium chloride cation exchange capacity
CEC OAC      buffered ammonium acetate cation exchange capacity
CLA7          total clay fraction
CLP           Contract Laboratory Program
CRDL          contract-required detection limit
DDRP          Direct/Delayed Response Project
DL-QCCS       detection limit quality control check sample
DQO           data quality objective
EMSL-LV       Environmental Monitoring Systems Laboratory at Las Vegas, Nevada
EPA           U.S. Environmental Protection Agency
ERL-C         Environmental Research Laboratory at Corvallis, Oregon
FAL           low-range field audit sample
FAO           field audit organic sample triplicate
FAP           field audit sample pair
FD             field duplicate sample
FE_AO         acid oxalate extractable iron
FE_CD         citrate dithionite extractable iron
FE_CL2        iron in 0.002M calcium chloride
FE~PYP        pyrophosphate extractable iron
FIA"           flow injection analysis
FP             flame photometry
1C             ion chromatography
ICC           internal consistency checks
ICP           inductively coupled plasma atomic emission spectrometry
IDL           instrument  detection limit
IFB           invitation for bid
IQR           interquartile range
IR             infrared detection
K CL          exchangeable potassium in unbuffered ammonium chloride
K~CL2         potassium  in 0.002M calcium chloride
K~OAC        exchangeable potassium in buffered ammonium acetate
LAL           low-range laboratory audit sample
LAO           laboratory audit organic sample triplicate

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                              List of Abbreviations (Continued)

LAP            laboratory audit sample pair
LEVIS          Laboratory Entry and Verification Information System
MASS          Mid-Appalachian Soil Survey
MG_CL         exchangeable magnesium in unbuffered ammonium chloride
MG_CL2        magnesium in 0.002M calcium chloride
MG_OAC       exchangeable magnesium in buffered ammonium acetate
MOIST_A       air-dry soil moisture at the analytical laboratory
MOIST_P       air-dry soil moisture at the preparation laboratory
MQO           measurement quality objective
MS            manager's sample
NA_CL         exchangeable sodium in unbuffered ammonium chloride
NA_CL2        sodium in 0.002M calcium chloride
NA OAC        exchangeable sodium in buffered ammonium acetate
NCC           National Computer  Center
NSS            National Stream Survey
NSWS         National Surface Water Survey
OEPER         Office of  Environmental Processes and Effects Research
OM_LOI        organic matter by loss-on-ignition
ORNL          Oak Ridge National Laboratory
PD            preparation duplicate sample
PE            performance evaluation
PH_002M       pH in 0.002M calcium chloride
PH_01M        pH in 0.01M calcium chloride
PHJH2O        pH in deionized water
PH MP         field-moist pH in deionized water
PLSOP         preparation laboratory standard operating procedures
QA            quality assurance
QART          quality assurance reanalysis template
QC            quality control
QCAS          quality control audit sample
QCCS          quality control check sample
QE            quality evaluation
RF_FG         fine gravel rock fragments
RF_MG         medium gravel rock fragments
RSD            relative standard deviation
SAND          total sand fraction
SAS            Statistical Analysis  Systems, Inc.
SBRP          Southern  Blue Ridge Province
SCR            soil chemistry relationship
SCS            Soil Conservation Service
SD            standard  deviation
SDL            system detection limit
SILT           total silt fraction
SI_AO         acid oxalate extractable silicon
SMO           Sample Management Office
SO4_0         zero mg S/L sulfate isotherm parameter
S04_2         two mg S/L sulfate isotherm parameter
SO4_4         four mg S/L sulfate isotherm parameter
SO4_8         eight mg  S/L sulfate isotherm parameter
SO4_16         sixteen mg S/L sulfate isotherm parameter
S04_32        thirty-two mg S/L sulfate isotherm parameter
S04_H2O       water extractable sulfate
SO4_PO4       phosphate extractable sulfate
SOP            standard  operating  procedures
SOR            SCS state office representative
SOW           statements of work
TC            thermal conductivity
USDA          U.S. Department of  Agriculture
                                          XI

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                               Executive Summary


     The quality assurance (QA) policy of the U.S. Environmental Protection Agency (EPA) requires
every monitoring and measurement project to have a written and approved quality assurance project
plan. The purpose of this quality assurance plan is to specify the policies, organization, objectives,
and  the quality evaluation  and quality control activities needed to achieve the data  quality
requirements of the  Direct/Delayed Response Project (DDRP), Mid-Appalachian Soil Survey (MASS).
These  specifications are used  to assess and  control measurement errors  that may enter the
system at various phases of the project, e.g., during soil sampling, preparation, and analysis.

Project Description

     The DORP is conducted as part of the interagency, federally mandated National Acid Precipita-
tion  Assessment Program  which  addresses the concern over potential acidification of surface
waters by atmospheric deposition within the United States. The overall purpose of the project is
to characterize geographic regions of the  United States by predicting the long-term response of
watersheds and surface waters to acidic deposition.

     The EPA is assessing the role that atmospheric deposition of sulfur plays in controlling long-
term acidification of surface waters.  Recent trend analyses have indicated that the rate of sulfur
deposition is either unchanging or slowly declining in the Northeastern United States, but is increa-
sing in the Southeastern United States. If a "direct" response exists between sulfur deposition and
surface water alkalinity, then the extent of current effects on surface water probably  would not
change much  at current levels of deposition,  and conditions would improve as  the levels of
deposition decline. If surface water chemistry changes in a "delayed" manner, e.g., due to chemical
changes in the watershed, then future changes in water chemistry (even with level or declining rates
of deposition)  become difficult to predict.  This range of potential effects has clear and significant
implications to public policy decisions on sulfur  emissions control strategies.

     The DDRP focuses on regions of the United States that have been identified  as  potentially
sensitive to surface water acidification. The MASS is the third of three DDRP regionaj surveys and
includes portions of Pennsylvania, Virginia, and  West Virginia.  Surface water acidification in the
Mid-Appalachian region was studied during the  Eastern Lakes Survey in 1984 and in the National
Stream Survey-Phase I, in 1985.  Information gained during these and other surveys has  been used
to optimize the quality assurance program in the MASS.

     Field  and laboratory data collected in  the  DDRP are  included in the system description
modeling.  These data are then used to assess the key processes that regulate the dynamics of
base cation supply  and sulfur retention within watersheds. Integrated watershed data are used
to calibrate three dynamic  simulation models  that predict future regional responses to acidic
deposition.  Uncertainty and error propagation  estimates are an important  part of all levels of
analysis.

     The DDRP staff at the EPA Environmental Research Laboratory in Corvallis, Oregon, is involved
in all aspects of the MASS. Responsibilities of this laboratory include the development of  an
experimental design,  QA oversight  for  soil mapping and  sampling, and  data  analysis and
interpretation.   The  DDRP staff at the EPA Environmental  Monitoring Systems  Laboratory in Las
Vegas, Nevada, is  involved in  matters relating to  QA implementation,  logistics, and analytical
services.  The responsibilities of this laboratory include the development and implementation of
operational  procedures  and quality  evaluation/control criteria for soil sample preparation and
analysis, and the development of data verification procedures for field and laboratory data.

     The use  of  interagency agreements by EPA has  allowed the DDRP to engage support from
several groups that have expertise in  areas of importance  to the  project.  The DDRP staff at Oak
Ridge National Laboratory is involved in managing, manipulating, and structuring large data bases
to satisfy DDRP data analysis requirements,  me soil survey staff of the United States Department
of Agriculture, Soil Conservation Service is involved in DDRP soil  mapping, characterization, and
sampling.  Laboratory analysis support is solicited through competitive bid on an invitation for bid
by independent contract laboratories.


                                            xii

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 Field and Laboratory Operations

      Field mapping and sampling operations in the MASS are conducted by Soil Conservation
 Service soil scientists under the supervision of EPA representatives.  Approximately five sampling
 crews, each composed of  three  to  four qualified  persons,  are  selected.  These crews  are
 responsible for the description of soil and site characteristics, sample collection, and shipment of
 samples to the preparation laboratory.   Members  of each crew  are  soil scientists that  are
 experienced with the universally  recognized  National Cooperative  Soil  Survey characterization
 procedures. The crew leader is responsible for selecting the sampling site and documenting all field
 data.

      The sampling protocols  specify the procedures for ensuring  the integrity of the samples.
 Specific  instructions on excavating and draining (if  necessary) soil pits are given.  Crews  are
 provided with standard containers for sample  collection.  Samples are kept as cool as possible in
 the field and during transport to the preparation laboratory. In order to maintain their integrity and
 to reduce the  possibility of biological  degradation, samples are stored at a temperature of 4°C
 within 24 hours of sampling. It is anticipated that 150 pedons are to be sampled during the MASS,
 with each pedon yielding an average of six routine samples from its component  horizons.

      To  allow the determination of bulk density, natural soil clods are collected in triplicate, where
 possible  from each soil horizon.  Where clods cannot be collected, known volumes of soil  are
 collected in duplicate.  Using a volume replacement  method, the volume  of soil is estimated by
 replacing a small excavated soil cavity with a  known volume of foam beads. If this method does
 not yield  satisfactory samples, a volume filling method is attempted by filling a container of known
 volume with soil and attempting to pack it to the same density normally encountered in the horizon
 being sampled.

      The preparation laboratory is the  intermediate link between  the sampling crews and  the
 analytical laboratories.  The laboratory is located at  the EPA Environmental Monitoring Systems
 Laboratory in Las Vegas, Nevada, although previous DDRP surveys utilized the services of multiple
 university laboratories for sample preparation. It was thought that  consolidating the preparation
 activities at a single laboratory might result in better  sample handling, improved  sample integrity,
 and higher data quality.  The laboratory serves as a central  location for soil processing  and for
 introducing double-blind measurement quality samples into the sample flow.  The soil samples
 collected by the sampling crews are sent via overnight courier to the  preparation  laboratory, where
 the laboratory staff processes the samples and prepares homogeneous, anonymous subsamples
 that are  shipped to the analytical  laboratories.  To accomplish these  tasks  successfully,  the
 preparation laboratory must uniformly track, process, and store all samples.

      After a bulk soil sample is air dried, the soil is carefully disaggregated and  sieved. The less
 than  2-mm  soil is  retained in a  labeled plastic  bottle and  placed in cold storage  when not
 undergoing processing.  The rock  fragments  are retained for  gravimetric analysis.  In order to
 obtain representative volumes  of soil,  it is necessary to prepare homogeneous subsamples from
 the less  than  2-mm soil fraction using a riffle splitter.  The  subsamples are placed in  labeled
 plastic bottles  and are  organized  in batches that are shipped to separate contract analytical
 laboratories for general and elemental analyses. Each  batch normally contains 40 samples but may
 have as many as 42 samples.   With the exception of a quality control audit sample, all samples
 are randomly placed within a batch and cannot be distinguished by the recipient laboratory.  The
 unused portions of the bulk soil samples are archived in cold storage.

      All raw data obtained are recorded on a series of preparation laboratory raw data forms and
 are immediately entered  into a  personal computer to ensure proper tracking, processing, and eval-
uation of the samples.  The computer  is directly linked to the QA staff and allows real-time data
evaluation and tracking of samples by both parties.  The precision and accuracy  criteria  for
measurement quality samples are checked while the samples are being processed, permitting the
prompt identification of any discrepancies.

      During shipment, the samples received by the analytical laboratories can undergo segregation
both by particle size and by density; therefore, each sample must be rehomogenized by thorough
mixing prior to the removal of aliquots for analysis. The raw data generated during sample analysis
are entered on a personal computer using a specially designed entry and verification system. Data

                                           xiii

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reports are then generated to assist in the evaluation of data quality. Before a batch of analytical
data is accepted all completeness and quality control requirements must be met.  In addition, the
following documents must be updated constantly at the analytical laboratory and must be available,
upon  request, to the  analysts and the  supervisor involved in the  project:   standard operating
procedures, laboratory QA plan,  list of in-house  samples,  instrument performance data, control
charts for all check samples and detection limit check  samples,  and quality control data reports.

      Frequent communications, i.e., two or three contacts each week, are maintained with each
analytical laboratory in order to obtain current sample status and to discuss any problems that may
occur during analyses.  These discussions are to be recorded in a logbook by the QA staff and the
laboratory staff.  Preliminary and final data arc available for access via electronic transfer.  The
preliminary data are reviewed for anomalies and if a problem is identified, the laboratory is notified.
Corrective action or reanalysis may be suggested.

      Legal chain-of-custody procedures are not required for this study; however, sample custody
must  be documented.  The sampling crew leader is  responsible for all samples in the field as well
as the sample shipments. As soil  shipments are received  in the preparation laboratory, they are
immediately logged in and checked against the packing slip and the pedon description forms for
proper labeling and quantity. If any discrepancies are found, the  soil sampling task leader and the
field crew  leader  are  notified.   Following  the receipt of samples, the  appropriate laboratory
managers are responsible for sample integrity until the samples are archived.

Quality Assurance Program

      The data collection criteria provide  a balance between constraints of time and cost and the
quality of data necessary to achieve the DDRP research objectives. The MASS QA Plan  is designed
to accomplish the following  general objectives:

  • establish the QA criteria used to control and assess data collected in the survey,
  • provide standardized sampling, preparation, and analytical methods and procedures,
  • utilize assessment samples and procedures to verify the quality of the data,
  • perform field and  laboratory on-site audits to ensure that  all activities are properly performed
    and that discrepancies are identified and resolved,
  • evaluate  the data and document the results in  QA reports to EPA management.

      The raw soil characterization data for  the DDRP surveys  are collected during  four major
operational phases consisting of mapping, sampling, preparation, and analysis. A certain amount
of data measurement  uncertainty is expected to enter the system at each phase. Grouping of the
data, e.g.,  by sampling class/horizon configurations, also increases  uncertainty.  The sampling
population itself is a source of confounded uncertainty that is extremely difficult to quantify.

      Generally,  the data quality  objectives for the  MASS  encompass the overall allowable
uncertainty from sample measurement and  from the sampling population that the data users are
willing to accept in the analytical  results.  Because of the many possible confounded sources of
uncertainty and the data collection focus of this QA plan, overall data quality objectives for the
survey are not described herein.  Rather, the  plan focuses on the definition, implementation, and
assessment  of measurement quality objectives (MQOs) that  are specified for the entire sample
preparation and analysis phases of data collection  and portions of the field sampling phase. The
MQOs are more or less specific goals defined by  the data users that clearly describe the  data
quality that is sought for each of the measurement phases.  The MQOs are defined according to
the following six attributes:

  • Detectability - the lowest concentration of an analyte that a specific analytical procedure can
    reliably detect.
  • Precision - the level of agreement among multiple measurements of the  same characteristic.
  • Accuracy ~ the difference between an observed value and the true value of the parameter being
    estimated.
  • Representativeness  -  the  degree  to  which  the  data collected accurately represent the
    population of  interest.
  • Completeness -- the quantity of data that is successfully collected with respect to  the amount
    intended in the experimental design.

                                            xiv

-------
  • Comparability - the similarity of data from different sources included within  individual or
    multiple data sets; the similarity of analytical methods and data from related projects across
    regions of concern.

     An attempt has been made to define each quality attribute individually for each measurement
phase  of  the program (sampling, preparation, analysis)  or collectively for  overall measurement
system uncertainty on a parameter-by-parameter basis. The term "uncertainty is used as a generic
term to describe the sum of  all  sources of error associated with  a given portion of the
measurement system.  In order to reduce measurement uncertainty in the final data values, errors
occurring  in each phase must be  identified and  rectified during that phase of the  survey.
Measurement uncertainty for the MASS is controlled through well-defined protocols, system audits,
and the introduction of measurement quality samples at each measurement phase.

     Initial MQOs were established on the basis of the requirements of EPA data users and on
the selection of appropriate methods to obtain the data.  The MQOs were  reviewed by persons
familiar with analytical methods and soil characterization techniques, including soil chemists and
laboratory personnel.  Modifications to the MQOs and to the protocols  were implemented based
on information gained from the DDRP  Northeastern region and Southern  Blue Ridge  Province
surveys, from peer review comments, or according to the limitations of a particular analytical proce-
dure or instrument.

     Measurement quality samples are placed at a rate of about one sample in four in each batch
of analytical samples to determine measurement uncertainty.  The measurement quality samples
are used during various phases of the survey and allow the QA  staff to control and assess the
quality of the data collection process.  Included in each batch of samples are: audit samples that
have known ranges of analyte  concentration (detectability, precision, and accuracy), duplicates of
routine  samples introduced at  each measurement phase  (precision and representativeness), and
an audit sample  for use in laboratory quality control (accuracy). There are separate analytical
within-batch precision and accuracy MQOs for organic and mineral soils because of differences in
methodology and the expected wide variability in analyte concentrations.  For this reason, mineral
and organic samples are organized and  analyzed in separate batches.

Status and Assessment of Measurement Quality Samples
Status of sample'
Sample type
Low-range field audit*
Field audit pair**
Field duplicate
Low-range lab audit*
Lab audit pair**
Preparation duplicate
Quality control audit
Manager's sample
#per
batch
1
2
1
1
2
2
1
—
QA Sampling
staff crew
K
K
-
K
K
-
K
K
B
B
B
-
-
-
-
—
Preparation
laboratory
B
B
B
-
-
B
-
B
Analytical
laboratory
DB
DB
DB
DB
DB
DB
B
—
Assessment purpose'
System
D.A
P,A
P
-
-
-
-
—
Sampling
D,A
P.A
P,R
—
--
..
-
-
Preparation
D.A
P.A
P
-.
-
P.R
—
A
Analysis
A
P.A
P
D
P,A
P
A
-
•  K = known concentration, B = blind, DB = double blind.
*  D = detectability/contamination, P = precision, A = accuracy. R = representativeness.
*  Not placed in organic soil batches.
** Triplicate in organic soil batches.

      The quality evaluation samples are those samples which are known to the QA staff but are
either blind or double blind to the sampling crews, preparation laboratory, or analytical laboratory.
A blind sample has a concentration range that is  unknown to the analyst, whereas a double blind
sample cannot  be distinguished from a routine  sample and has  a concentration range that is
unknown to the analyst.  These samples provide  an independent check on the analytical process
and can be used to evaluate whether the MQOs have been met for any given run or batch, or for
all batches, i.e., overall measurement uncertainty.  Important characteristics of the audit samples


                                            xv

-------
include their similarity to routine samples in matrix type and concentration level,  their homogeneity
and stability, and their defined accuracy windows.  Every quality evaluation sample has a specific
purpose in the data assessment  scheme.

     In order to produce data of consistently high quality, the contract laboratories are required
to analyze certain types of quality control samples that are known to the laboratory staff and that
can be used by the analysts to identify and control analytical measurement uncertainty.  Each of
these samples has certain specifications that must be met before data for the parameter or batch
are accepted.  The control samples are non-blind samples procured under contract to assist the
laboratories in meeting laboratory MQOs and include soil samples, e.g., analytical duplicates, and
non-soil samples, e.g., reagent blanks. The samples allow the laboratory manager and the QA staff
to assess whether the physical and chemical analysis is under control.

Quality Assurance Implementation

     The quality assurance program  is implemented through training,  on-site systems audits,
independent assessments, and other procedures used to control and assure the quality of the data
being collected.  Verification of these data is  accomplished through a  series of computer and
manual checks of data quality.

     Corrective  action for  errors  made   at  the  preparation  and  analytical  laboratories  is
accomplished primarily through the application of a QA reanalysis  template  for each analysis of
interest.  The templates provide  a precision and accuracy checklist of the measurement quality
samples for each batch and are  useful in deciding whether to reanalyze a  particular parameter.

     The analytical data verification is a multi-faceted, computerized approach to provide a concise
and consistent assessment of the data. The overall process is highlighted by the Laboratory Entry
and Verification Information System (LEVIS).  The LEVIS programs are implemented on personal
computers  and facilitate the data entry and quality control sample  evaluation at  the  analytical
laboratories as well as the evaluation  of laboratory performance by the QA staff.  The system is
a menu-driven product that is designed as a two-phase operation, where phase one is an analytical
laboratory system  and phase two is  a quality assessment system. The  LEVIS  initiative was
pursued because previous surveys had shown that manual verification of the data was both labor-
and time-intensive, and allowed only a limited amount of real-time corrective  action on the part of
the laboratories.

     An internal consistency program is used to generate routine data outliers  in each  sample
batch. Analytical data from each parameter are correlated  against corresponding data from all
other analytical parameters measured  in the MASS. For each parameter, the parameter pair with
the strongest linear relationship is identified and evaluated. Soil chemistry relationships are another
tool used to examine the internal consistency of  the routine sample data.   It is expected that
approximately  10 percent of the data will not comply with the relationships; these anomalous data
are examined  by a staff  soil  chemist who either qualifies  them  or assigns appropriate flags
signifying the discrepancy.

Data Quality Assessment  and Reporting

     The assessment of detectability is accomplished  on a parameter basis at four  levels:  (1)
compliance with contract-required detection limits; (2) calculation of actual  instrument detection
limits;  (3) calculation of estimated system detection limits; and (4) identification of routine samples
having concentrations below the system detection limits.  The results can be grouped  in tabular
form to allow comparisons among the values for any parameter of interest.

     A statistical evaluation procedure that has been developed by the QA staff and data users
is applied to the data in order to assess precision as  a function  of confounded data collection
uncertainty.  An additive step-function model  is used, where  an observed  value  of  any  soil
characteristic is considered as the sum of the "true" or accepted value and an error term. Precision
is evaluated for each variance segment of the range of  concentration for a given analyte.

                                            xvi

-------
     The accuracy windows for the laboratory audit samples are based on previous interlaboratory
analyses of the same sample material by the same protocols.  The objective of setting windows
is to  specify a range  of acceptable single  values  based on  a mean and standard deviation
computed from a number of  previously observed values.   The prediction  intervals used for the
accuracy windows are generally determined with confidence intervals constructed around the mean
of these values, using appropriate weighting  factors.

     The sampling aspect of representativeness is assessed by comparing the  individual site and
pedon classifications with the component sampling classes  to which the soils are assigned.
Representativeness of  the  measurement  quality  samples  is  assessed by  comparing  the
concentration ranges of data from the duplicate samples to the  overall concentration range of the
routine sample data. Representativeness  of the  analytical samples is identified by assessing the
homogenization and subsampling procedures at  the preparation and analytical  laboratories using
precision estimates from the duplicate samples.

     Sampling completeness is assessed by comparing the actual number of soil pedons and
associated horizons sampled to that number  specified in the MASS design.  Completeness of the
sample collection, preparation, and analysis is calculated using data from the verified data base,
while  completeness of the data from a data user's perspective, i.e., amount of usable data, is
determined using  the validated data base.

     Following completion of the MASS, a comparison is made across the Northeastern, Southern
Blue Ridge, and Mid-Appalachian regions that focuses on method differences, audit sample results,
laboratory effects, and other QA features of the surveys. Comparison of the DDRP data bases to
other  similar data bases may  also be undertaken. Summary statistics are used to collate individ-
ual values into groups that enable the data users to discern trends of interest among the surveys.

     Task leaders for the various stages of  the MASS provide  a written summary of operations
to the project managers on a quarterly basis. These reports describe the kinds of data collected
as well as summarize the QA activities associated with the data.  The summary of QA activities
includes the  following:

    overview of QA activities,
    list of changes to the QA program,
    results of system and performance audits,
    assessment of data quality based on the verified data bases,
    documentation of unfavorable incidents and  corrective actions,
    distribution of updated control charts, and
    results of special studies.

     Reports relating to data quality assessment are also prepared by QA staff.  These reports
include interpretation of performance audits and replicate sample data, estimates of measurement
error,  and identification of any major discrepancies found during the assessment.   In addition to
this QA Plan, the QA staff produces laboratory operations manuals for use  in the preparation and
analysis of soil samples.  Upon completion of the data verification activities, summary QA reports
of the sample preparation and sample analysis data are produced and distributed to all cooperat-
ing DDRP staff and data users.

Data  Management System

     The purpose of data base management for the MASS is to facilitate the collection,  entry,
review, modification, and distribution of  all data associated with the  survey.   Additional  tasks
include the data  analysis for  report generation, statistical analysis,  verification,  and data file
security.  The MASS final data base contains  three progressive versions of the data gathered: (1)
the raw data base, (2)  the verified data base, and (3) the validated data base.
                                           XVII

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                                                                           Section 1
                                                                           Revision  1
                                                                           Date:  4/89
                                                                           Page 1 of 2
                                      Section  1

                                    Introduction
1.1   Directives

     The  quality assurance  policy  of the
U.S.   Environmental Protection Agency (EPA)
requires every monitoring and measurement
project to have a written and approved quality
assurance (QA) project plan (Costle, 1979a and
1979b). This requirement applies to all environ-
mental monitoring  and measurement efforts
authorized or supported by EPA through regu-
lations,  grants,  contracts,  or other formal
means.  The purpose of this  QA plan is to
specify the  policies, organization, objectives,
and  the quality  evaluation (QE)  and quality
control (QC) activities needed  to achieve the
data quality requirements of the Direct/Delayed
Response Project (DDRP), Mid-Appalachian Soil
Survey (MASS).  These specifications are used
to assess  and control measurement errors
that  may enter the system at various phases
of the project, e.g., during soil sampling, prep-
aration, and analysis.
     All project personnel are expected to be
familiar with the policies and objectives out-
lined in this QA plan to ensure proper interac-
tions between field and laboratory operations
and data management.

1.2   Sources of Information

     The EPA Quality Assurance Management
Staff  guidelines (Stanley and Verner,  1985)
state that the QA project plan should address,
in detail or by reference, each of the 14 items
listed  in  Table  1-1.   Method-specific discus-
sions  presented in the DDRP-MASS Soil Sam-
pling  Manual (Kern  et a!.,  1988),  the DDRP-
MASS Preparation Laboratory Standard Opera-
ting Procedures (Bartling et al., 1988), or the
DDRP-MASS Analytical Laboratory Statements
of Work (USEPA, 1988) might not be repeated
in this project plan.  In these cases, Table 1-1
serves as an index to the appropriate refer-
ences.
Table 1-1.  Sections In This Quality Assurance Project Plan and In Other DDRP Documents Where Quality
         Assurance Subjects are Addressed

                                                    Section Number
Subject
Project Description
Project Organization
QA Objectives for Measurement
Data
Sampling Procedures
Sample Custody and Storage
Calibration Procedures
Analytical Procedures
QA Project
Plan
2
2
5
3,4
4
—
4
Soil Sampling
Manual!
1,2
1,2

7
7,8
—
*—
Preparation
Laboratory
SOP
1
1
2
—
2
2,3
3
Analytical
Laboratory
sow:
1
1
3
—
2
3
4
                                                                            (continued)

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Table 1-1. Continued



Section 1
Revision 1
Date: 4/89
Page 2 of 2
Section Number
Subject
Data Reduction, Validatbn, and
Reporting
QC Standards and Checks
Performance and System Audits
Preventive Maintenance
Data Quality Assessment
Corrective Actions
QA Reports
QA Project
Plan
7.8
5.6
7
6
6,7
6.1
7
Soil Sampling
Manual:
6,7
—
2.6
—
.
2.6
2
Preparation
Laboratory
sor
2.3
2.3
1
3
2,3
2.3
2
Analytical
Laboratory
sow:
4.5
3.4
6
3.4
3.4
3.4
3
• Kern et al., 1988
1 Bartling et al., 1988
1 USEPA, 1988

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                                                                             Section 2
                                                                             Revision  1
                                                                             Date:  4/89
                                                                             Page 1 of  6
                                      Section 2

                                Project Description
2.1   Project Overview

     The  DDRP  is  an integral part of the
Aquatic Effects Research Program (AERP) of
the EPA and is  conducted  as part of the
interagency, federally mandated National Acid
Precipitation  Assessment  Program  (NAPAP)
which  addresses the concern over potential
acidification of surface waters by atmospheric
deposition  within  the United States.   The
overall purpose  of DDRP  is to characterize
geographic regions of the United States by
predicting the long-term response of water-
sheds and surface waters to acidic deposition.

     The DDRP has been designed under the
concept of  regionalized,  integrative surveys
which  initially are approached from a  large
region  of study and lead to the selection and
study  of  regionally characteristic  systems.
These  systems  can be  assessed  through
detailed, process-oriented research which aid
in the understanding of the underlying mecha-
nisms  responsible for observed effects.  The
projected  responses  of  watershed  systems
typical of the regional population can then be
extrapolated to a regional or national scale.

     The  EPA is  assessing the role that
atmospheric  deposition  of  sulfur  plays  in
controlling long-term  acidification of surface
waters (USEPA, 1985). Recent trend analyses
have indicated that the rate of sulfur deposi-
tion is either unchanging or slowly declining in
the Northeastern United States, but is increa-
sing in the Southeastern United States. If a
"direct" response exists between sulfur deposi-
tion  and surface  water alkalinity,  then the
extent  of  current  effects  on surface  water
probably would not change much at current
levels  o*  deposition, and  conditions  would
improve as the levels of deposition decline.  If
surface water chemistry changes in a "delayed"
manner, e.g., due to chemical changes in the
watershed,  then  future changes in  water
chemistry (even with level or declining rates of
deposition) become difficult to predict.  This
range of potential effects has clear and signifi-
cant implications to public policy decisions on
sulfur emissions control strategies.

     The  DDRP  focuses on  regions  of the
United States that have been  identified as
potentially sensitive to surface water acidifica-
tion.  The Northeastern Soil Survey was con-
ducted in 1985 in the  New England states  of
Maine, New Hampshire, Vermont,  Massachu-
setts, Connecticut, Rhode Island, and portions
of New York and Pennsylvania. The Southern
Blue Ridge Province Soil Survey was conducted
in 1986 in portions of  Virginia,  Tennessee,
North Carolina, South  Carolina, and Georgia.
The  Mid-Appalachian  Soil  Survey  (MASS)
includes portions of Pennsylvania, Virginia, and
West Virginia (see Figure 2-1). Surface water
acidification in  these  regions was  studied
during the Eastern Lakes Survey in  1984 and in
the National Stream Survey, Phase-I, in 1985.
                                Northeast
                                 Region
                            Mid-Appalachian
                                Region
                         Southern Blue Ridge
                              Province
Figure 2-1. Regional Surveys of the Direct/Delayed
         Response Project (from Lee et al., 1989)

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                                                                            Section 2
                                                                            Revision  1
                                                                            Date:  4/89
                                                                            Page 2 of  6
     Specific goals of the DORP are to:  (1)
characterize the variability of soil and water-
shed  attributes across  these  regions;  (2)
determine which of the  soil and watershed
characteristics  are most strongly related to
surface-water   chemistry; (3) estimate  the
relative importance of key watershed proces-
ses  in controlling surface  water chemistry
across the regions of concern; and (4) classify
the sample of watersheds with regard to their
response  characteristics  and extrapolate the
results from the sample of watersheds to the
regions of concern (USEPA, 1989).  Figure 2-2
displays a general outline of the DDRP activi-
ties in support of these goals.

     A variety of data sources and methods
of analysis are used to address the objectives
of DDRP.   In  addition to the data  collected
during  DDRP, other data  sources include the
following data bases:

  • National Surface  Water  Survey  (NSWS)
    [water chemistry data],
  • Acid  Deposition Data Network (ADDNET),
    including   GEOECOLOGY  [atmospheric
    precipitation chemistry data],
  • Soil Conservation  Service (SCS) Soils-5
    [soil physical and chemical data],
  • Topographic and Acid Deposition System
    (ADS) [total sulfur deposition data],
  • U.S. Geological Survey [runoff data].

Also,  data  from EPA long-term monitoring
sites, episodic event  monitoring sites,  and
intensively studied watersheds are used in the
data analysis.  The data that are collected are
analyzed at three levels.  Level  I  involves the
system description and  statistical  analysis,
Level II provides single factor response-time
estimates, and Level  III  involves dynamic
systems  modeling.

     Field and  laboratory data collected in the
DDRP and NSWS are included  in the Level I
system description.  These data  are used in
Level II models to assess the key processes
that regulate  the  dynamics  of  base cation
supply and sulfur retention within watersheds.
Integrated watershed data are used in  Level
III to calibrate three dynamic simulation  mod-
els, MAGIC (Cosby et al., 1984). ILWAS (Chen
et al., 1984), and Trickle-Down (Schnoor et al.,
1984), that predict future regional responses to
acidic deposition. Uncertainty and error prop-
agation estimates are an important part of all
three levels of analysis (USEPA, 1989).

2.2  Project  Organization

     Figure  2-3  illustrates the  operational
management structure of the MASS and Figure
2-4 illustrates the local organizational manage-
ment  of  the QA staff.   The director of the
Office of  Environmental Processes and Effects
Research (OEPER) is the EPA official who has
overall responsibility for programs within  EPA
that address the effects of acidic deposition.

2.2.1 Project Management

     The EPA management structure for the
DDRP  surveys  is described in  the following
subsections.

2.2.1.1  Program Director-

     The program  director of  the  Aquatic
Effects Research Program is the EPA Head-
quarters  representative for DDRP and is the
liaison between the headquarters staff, the
laboratory directors, and NAPAP.  Questions
regarding general management and resources
should be forwarded to the program director
through the technical director.

2.2.1.2  Technical Director-

     The DDRP technical director is assigned
tasks at  the discretion of the AERP director.
The primary role of the technical director is to
maintain  the integrity of program objectives, to
integrate components of  the program, and to
ensure that deadlines are met.  The technical
director coordinates and  integrates the DDRP
activities of the EPA Environmental Research
Laboratory at Corvallis, Oregon  (ERL-C)  and
the Environmental Monitoring Systems Labor-
atory at  Las Vegas, Nevada (EMSL-LV).  The
technical director coordinates peer  reviews,
resolves  issues of responsibility, and dissemi-
nates information to the  public.  The techni-
cal director represents the program director as

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                                                                              Section 2
                                                                              Revision 1
                                                                              Date:  4/89
                                                                              Page 3 of 6
                                  WATERSHED SELECTION
                                              (ERL-C)
                                   WATERSHED MAPPING
                                                (SCS)
                                  SAMPLING CLASS/PEDON
                                      SELECTION
                                           (ERL-C/SCS)
                                     SOIL SAMPLING
                                                (SCS)
                                    SOIL PREPARATION
                                             (EMSL-LV)
                                     SOIL ANALYSIS
                                             (EMSL-LV)
                                   DATA VERIFICATION
                                             (EMSL-LV)
                                    DATA VALIDATION
                                              (ERL-C)






rERIFICATIOH
(ERL-C)

INAGEMENT
(ORNL)

                                     DATA ANALYSIS
                                              (ERL-C)
      Figure 2-2.  Major Operations In the Direct/Delayed Response Project Mid-Appalachian Soil Survey
necessary  and  informs the  program director
of EPA laboratory activities, progress,  and
performance.

2.2.1.3  Technical  Monitor

     A technical monitor at each EPA labora-
tory  is responsible for specific DDRP tasks
assigned by the technical director.  Responsi-
bilities include the employment and coordina-
tion of groups of individuals to accomplish the
assigned tasks.  The technical monitor  per-
forms  reviews and  audits, resolves issues of
responsibility, and informs  EPA management
of progress  and performance.   The ERL-C
technical monitor has the primary responsibility
for soil mapping and sampling  activities.  The
EMSL-LV technical  monitor has  the primary
responsibility for soil preparation and physical
/chemical analysis activities.

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                                                                                   Section 2
                                                                                   Revision  1
                                                                                   Date:  4/89
                                                                                   Page 4 of 6
                                      Director of Office  of
                                     Environmental Processes
                                      and Effects Research
                                    Director of Acid Deposition
                                     and Atmospheric Research
                                            Division
                                    Director of Aquatic Effects
                                       Research Program
                       ERL-Corvallis
                     Mapping Supervision
                     Happing/Sampling QA
                     Sampling Supervision
                     Data Validation
                     Data Interpretation
                     Reporting
     EMSL-Las Vegas
    Sampling Logistics
    Soil Preparation
     Analysis Supervision
    Preparation/Analysis QA
    Data Entry
    Data Verification
    Reporting
Figure 2-3. Operational management structure for the Mid-Appalachian Soil Survey of the Direct/Delayed
          Response Project.
2.2.1.4  Quality Assurance Officer

      The QA officer is responsible for ensur-
ing that each project within an EPA laboratory
satisfies  the agency's requirements  for  QA
programs. The QA officer evaluates QA plans,
coordinates  and  supervises system  audits,
disseminates information, and  is responsible
for the  coordination  and oversight  of  the
division QA officers.
2.2.1.5  Division Quality Assurance Officer

      The division QA officer  is  tasked  with
overseeing the QA operations of specific tasks
or projects. Responsibilities include facilitating
the attainment of quality objectives, coordinat-
ing system audits, and resolving  QA  issues
relating to a specific project.  The division QA
officer acts as a liaison with the QA staff and
technical monitor in addressing QA issues.

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                                                                             Section 2
                                                                             Revision  1
                                                                             Date:  4/89
                                                                             Page 5 of 6
                   Division QA Officer
                          EMSL-LV
Figure 2-4.  Organizational management structure of
          the Quality Assurance Staff at the
          Environmental Monitoring Systems
          Laboratory, Las Vegas, Nevada
2.2.2  Laboratory Responsibilities

     A summary of the different DDRP staff
responsibilities at each cooperating laboratory
is provided below.

2.2.2.1 Environmental Research
        Laboratory, Corvallis, Oregon

     The  DDRP staff  at ERL-C is  involved
in  all aspects of the DDRP  soil  surveys.
Responsibilities of ERL-C personnel  for the
overall program include:

 •  developing the  experimental  design  and
    QA oversight for soil mapping and sam-
    pling,
 •  collecting  supplemental  historical  and
    other available data on each sampling site,
 •  coordinating  the  temporary  storage of
    samples in the field and their transfer to
    the preparation laboratory,
 •  analyzing and validating data (jointly with
    EMSL-LV),
 •  interpreting data,
 •  preparing reports (final and progress
reports  with  contributions from the  other
laboratories relative to their responsibilities),
  • assessing   and   resolving   all science-
    related  issues other than  QA or data
    management (jointly with  other laborato-
    ries as necessary), and
  • coordinating survey activities with NAPAP
    management staff.

2.2.2.2  Environmental Monitoring Systems
        Laboratory, Las Vegas, Nevada

     The  DDRP staff at EMSL-LV has exper-
tise in matters  relating to QA implementation,
logistics, and analytical services.  The respon-
sibilities of personnel at EMSL-LV include:

  • developing   QE/QC  procedures  for  all
    sample  preparation and analysis compo-
    nents,
  • developing  and implementing preparation
    laboratory and analytical laboratory oper-
    ating  procedures,
  • developing  and  implementing  analytical
    methods,
  • coordinating logistical support and equip-
    ment  needs for  all field and preparation
    laboratory operations,
  • distributing  processed samples to ana-
    lytical laboratories,
  • developing  and implementing the verifica-
    tion  and   management  procedures  for
    sampling, preparation, and analytical data,
  • developing   and  implementing  the  QA
    project plan and corresponding laboratory
    manuals,
  • analyzing data (jointly with ERL-C),
  • preparing QA data reports for preparation
    laboratory and analytical laboratory opera-
    tions, and
  • resolving  issues  pertaining  to QE/QC,
    logistics, and analytical services.

2.2.3  Primary Cooperators

     The  use of interagency  agreements by
EPA has  allowed  the  DDRP to tap support
from several groups  that  have expertise  in
areas of importance to the project, as outlined
below.

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                                                                           Section 2
                                                                           Revision 1
                                                                           Date:  4/89
                                                                           Page 6 of 6
2.2.3.1  Oak  Ridge  National
         Laboratory, Oak Ridge,
         Tennessee

     The DDRP staff at the Oak Ridge Nation-
al Laboratory (ORNL) has expertise in manag-
ing, manipulating, and restructuring large data
bases to satisfy data analysis  needs.  ERL-C
oversees the activities of ORNL, which  has
responsibilities for:

 •  developing and  maintaining a data base
    management system,
 •  preparing  computer-generated  summary
    tables, statistics, and graphics for reports,
    and
  • assisting with data validation and inter-
    pretation activities.

2.2.3.2  Soil Conservation Service

     The United States Department of Agricul-
ture (USDA), Soil  Conservation Service (SCS)
has expertise in soil mapping and characteriza-
tion on a national scale.  Under the supervi-
sion of  ERL-C, the  SCS has responsibilities
for:

  • soil mapping of the MASS watersheds,
  • site selection  and characterization, and
  • soil sampling  of selected pedons.

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                                      Section 3

                               Sampling Strategy
     Following is a  brief  summary  of  the
considerations involved in designing the MASS
sampling strategy. Additional details are pro-
vided in  documents  prepared by the DDRP
staff at ERL-C, who had the primary responsi-
bility for sampling in the MASS.

3.1   Watershed Selection and
      Mapping

    Since  the objectives of  the DDRP  are
focused on making  regional inferences,  the
watersheds selected for mapping of soils  and
watershed characteristics must  constitute  a
representative sample  of  a region.   After
eliminating watersheds having  known  acid
mine drainage and prohibitively  large water-
sheds  exceeding  3,000  hectares in area, 79
watersheds included  in the Pilot Survey of the
National Stream Survey-Phase I (NSS-I) pro-
vided an excellent starting point from which to
draw the subsample  for MASS.  These water-
sheds satisfied the requirements because: (1)
the NSS-I  pilot survey stream reaches were
selected  according to a rigorous probability
sampling method, i.e., the reaches were strati-
fied  by three subregions and three alkalinity
classes within each subregion; and (2) water
chemistry information was available from NSS-
I for the reaches (Messer et al., 1986).

     The  preliminary  procedure for selecting
the MASS watersheds consisted of eliminating
certain   watersheds  according  to  strictly
defined criteria, as follows:

  • acid-neutralizing capacity (ANC) of greater
    than 200 microequivalents per liter,
  • suspected residual  effects of  acid mine
    drainage,
  • a geomorphic history of Pleistocene glacia-
    tion within the northern portion of the Mid-
    Appalachian region.

     Twenty-three watersheds  having  high
ANC were deleted because they were consi-
dered to be at low risk for future acidification.
Twelve watersheds  identified  as harboring
mine spoils or other disturbances were deleted
because of their anticipated inordinate effect
on chemical characteristics of the soils.  Seven
watersheds with a history of glaciation were
deleted because it was decided that soils in
these  areas  would  exhibit  characteristics
similar to those soils previously  sampled in
the DDRP Northeastern Soil Survey. Hence, 37
watersheds from NSS-I remained for potential
sampling in the MASS.

     The 37 watersheds were  mapped during
the autumn  of 1987 and the  spring of 1988
according to the mapping protocols (Lammers
et al.,  1988).   With the exception of certain
highlighted modifications, the  protocols  are
based on  standard  procedures developed for
the National  Cooperative Soil  Survey (NCSS)
and also describe the preparation of uniform
soil profile descriptions, mapping legends, and
the QA program for  mapping. A second order
soils  map at a 1:24,000  scale is specified.
Mapping  units are mostly consociations and
complexes, and the components of the map-
ping units are phases of soil series,  higher
categories, or miscellaneous areas.  Contras-
ting inclusions are limited to a maximum of 20
percent for soil components and 15 percent for
miscellaneous areas.

     Field review and evaluation of the map-
ping by the  soil mapping task leader,  a Soil
Conservation Service (SCS) state office repre-
sentative (SOR), and an independent regional
correlator/coordinator  (RCC)   ensures  the
consistent application of the mapping  proto-
cols and  the correlation of  mapping units
among the mapping parties. Soil map adequa-
cy is qualitatively evaluated for soil  features
relevant  to the DDRP, such as permeability
or  slope class. Correctness of the mapping
is determined  by point observations  along
selected transects using an approach similar
to that outlined in  Steers and Hajek (1979).

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Both the degree of error and the number of
errors are considered for a designated  size
area.  Key mapping and supervisory personnel
attend a final correlation  workshop to review
and correlate the mapping units and delinea-
tions across the region.

3.2  Selection of Sampling
      Classes

     Sampling each of the soil mapping units
is not necessarily the best way to describe the
chemistry of  the soils in a region.  A  more
straightforward procedure is to combine the
mapping units into groups, or sampling clas-
ses, which are either known  to have or are
expected to have similar characteristics.  Each
of these sampling classes can be sampled
from a number of watersheds, and the mean
characteristics of each sampling class can be
computed. The mean and variance values can
be used to construct area-weighted or volume-
weighted estimates of the characteristics for
each watershed.  For this procedure to work,
at least five  samples must be taken to char-
acterize the variability of each  sampling class.
The objective is to develop a method of group-
ing the large number of soils into a reasonable
number of sampling classes.   The spatial
distribution of mapping units and the relative
proportion of the components  of the mapping
units  are  used to  aggregate  the watershed
attributes.

     Specific information relating to sampling
classes can  be found in the sampling proto-
cols (Kern et al., 1986).

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                                     Section 4

                     Field and Laboratory Operations
     This section outlines the operational and
logistical activities required for the sampling,
preparation, and  analysis of  soils for the
MASS. Specific information on the individual
phases  can be  found in  the  soil sampling
manual  (Kern  et  al.,  1988),  the  preparation
laboratory  standard  operating  procedures
(Bartling    et  al., 1988),  and  the  analytical
laboratory statements of work (USEPA, 1988),
respectively.

4.1   Field Operations

     Field operations are conducted under the
supervision of  ERL-C staff. The primary parti-
cipants are SCS soil scientists tasked through
an interagency agreement.  Complete details
of the MASS field operations can be found in
the mapping protocols (Lammers et al., 1988)
and the sampling manual  (Kern et al., 1988).

4.1.1 Personnel

     Approximately five sampling crews, each
composed of three to four qualified persons,
perform the field sampling operations for the
MASS.  These crews are  responsible for the
description of soil  and site  characteristics,
sample collection, and shipment of samples to
the preparation laboratory. Members of each
crew  are  soil scientists  experienced  in the
National Cooperative Soil Survey characteriza-
tion procedures.  The crew leader is responsi-
ble for selecting  the sampling site and docu-
menting all field data.

4.1.2 Sampling Activities

     Several steps are necessary to complete
soil sampling  activities at a particular  site;
descriptions of these activities follow.
4.1.2.1  Description of Sampling Site
        and Soil Profile

     After the sampling site is located, a pit
large enough for sampling all major horizons is
excavated  to a  depth of 2.0 meters or to
bedrock.  The soil profile is described accord-
ing to the sampling protocols and the data are
recorded on an SCS-SOI-232 field data form
(see Appendix A).  Other descriptive informa-
tion, e.g.,   site characteristics  or herbicide
contamination, also is recorded on the  field
data form.

4.1.2.2 Sampling Procedure

     For each soil horizon greater  than 3
centimeters thick identified  on the field data
form, the sampling crew collects a soil sample
weighing approximately 5.5 kilograms  after
sieving to exclude rock fragments exceeding 20
millimeters in diameter.  A sufficient quantity of
sample should be collected to ensure that a
minimm of 2 kg of less than 2-mm material is
available  after sample preparation.  Sample
bags are  labeled  with DDRP Label A  (see
Appendix A)  which identifies the date the
sample was taken, the crew that collected the
sample, and the appropriate site, sample, and
set identification  (ID)  codes.  The thirteen-
character sample code is  an alpha-numeric
coding  of the sample type, e.g., routine, audit,
or field duplicate; the number  of bags per
sample; the SCS state and  county code; and
the pedon/horizon code. The identification and
sample numbering scheme yields unique alpha-
numeric labels for each pedon and for each
sample collected from the pedon.

     The  sampling  protocols  specify  the
procedures for ensuring  the  integrity of the
samples. Specific instructions on excavating

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and draining (if necessary) soil pits are given.
Crews are provided with standard containers
for sample collection.  Samples  are kept as
cool  as possible in the field and during trans-
port to the preparation laboratory. To maintain
their integrity, samples are to be stored at an
ambient  air temperature  of  4°C  within 24
hours of sampling. This can be accomplished
by temporarily storing the samples in  rented
cold  lockers  or in styrofoam coolers  with
frozen  gel packs.

     It is anticipated  that 150 pedons are to
be sampled during the MASS, with each pedon
yielding an average  of  six routine  samples
from the component horizons.

4.1.2.3  Collection  of  the  Field
         Duplicate Sample--

     Each sampling crew samples one horizon
in duplicate from every third pedon. The type
of  horizon chosen  for this   field duplicate
(FD)  sample is  based on random selection,
although the crew is instructed to avoid contin-
uous sampling of the same type of horizon to
ensure that FOs for each  crew are sampled
across the complete range of possible  hori-
zons.

     The sampling procedure  specifies  that
the FD and  its corresponding routine sam-
ple are collected simultaneously.  Alternate
trowels-full of soil are removed from the  hori-
zon and are placed into separate sample bags
until  two samples of fine earth material equal
to approximately 5.5 kg each are  collected.
The FDs are processed and analyzed  in the
same manner as the routine soil samples. The
analytical results are used  in the assessment
of measurement variability attributed to sam-
pling, preparation, and analysis that contribute
to the overall measurement uncertainty.

4.1.2.4  Handling of the Field Audit
         Samples-

     Field audit samples are supplied  to the
crews  by the  QA  staff.   On each day  that
crews  sample  the FD, they are required to
sieve, rebag, and  label three audit samples
while at the sampling  site.  The samples are
sent with the routine samples to the prepara-
tion laboratory for processing and subsequent-
ly to the analytical  laboratories for analysis.
The results are  used to assess  the  overall
measurement  uncertainty and system-wide
detectability.

4.1.2.5 Collection of the Bulk Density
         Samples-

     To allow the determination of bulk densi-
ty, natural soil clods are collected in triplicate,
where possible, from each soil horizon.  The
clods are placed in  hairnets  and dipped in a
Saran  solution  to  preserve   their  structural
integrity during  transport to the preparation
laboratory.  The clods are carefully packed in
clod boxes with cushioned packing material to
absorb  excess  shock  and  vibration  during
transport.

     Where clods cannot be collected,  known
volumes of soil are collected in duplicate. The
volume of  soil  is estimated  by replacing a
small excavated cavity with a known volume of
foam beads.  If the clod method or volume
replacement method do not yield satisfactory
samples, a volume filling method is initiated by
filling a container of known volume with soil
and attempting to pack it to the same density
normally  encountered in  the  horizon  being
sampled.

4.1.2.6 Sample Shipments-

     Sampling crews are responsible for the
shipment of soil samples  and pedon descrip-
tions to the preparation laboratory.  Shipments
must include a packing slip detailing the num-
ber of  boxes sent and the contents  of  the
shipment, i.e., number of samples and  forms.
An overnight courier service is used for ship-
ment of all bulk samples. Clods are shipped
in clod  boxes packed inside of  styrofoam
coolers.

4.2   Preparation  Laboratory
      Operations

     The preparation laboratory is located at
EMSL-LV and is the intermediate link between

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the sampling crews and the analytical labora-
tories. The bulk soil samples collected by the
sampling crews are sent via overnight courier
to the preparation laboratory, where the labor-
atory staff processes the samples  and pre-
pares homogeneous, anonymous subsamples
that are shipped to the analytical laboratories.
To  accomplish these tasks successfully, the
preparation  laboratory must uniformly track,
process, and store all  samples.   Complete
details of the preparation laboratory activities
are prescribed in the  Preparation Laboratory
Standard   Operating   Procedure   (PLSOP)
(Bartling et al., 1988).

4.2.1  Personnel

      Preparation  laboratory operations  are
performed  by approximately six laboratory
analysts under the supervision of the prepara-
tion laboratory manager. The manager must
be  an experienced soil scientist and has the
responsibility of training and supervising the
analysts.   Each  analyst is responsible for
certain processing activities and is required to
uniformly enter raw data  on specified  data
forms.

4.2.2  Preparation Activities

     Sample preparation involves a number of
activities in order to  produce  homogeneous
and representative subsamples of soil for
analysis, as described below.

4.2.2.1 Sample Receipt-

     The sampling crew member responsible
for shipping samples notifies the laboratory
manager when samples are shipped from the
sampling sites to the preparation laboratory.
Bulk samples and completed packing lists are
shipped via overnight courier directly to the
EMSL-LV cold storage facility.   All incoming
soil  samples  are  received by preparation
laboratory personnel, who record information
for the samples on the  Sample Receipt  Raw
Data Form (see Appendix B). Additional notes
must be kept in a logbook that is submitted to
the QA manager at the end of the survey.
     Each shipment is checked upon arrival
to  ensure that  all samples  sent have been
received.  The condition of the samples is
noted on  the  receipt form and any samples
that are damaged  or missing are reported to
the QA manager. Samples are grouped in sets
that are maintained throughout storage, pro-
cessing, and shipping.

     The original field data forms and photo-
copies of  the appropriate sampling forms are
included in the sample shipment. Information
on  these  forms is  used to  check sample
labeling and to document the receipt of sam-
ples. The  forms are then forwarded to the QA
manager.

4.2.2.2  Sample Storage--

     All soil samples are placed in cold stor-
age immediately upon receipt and remain there
until they undergo further processing. After air
drying, the samples are  returned to cold stor-
age and remain there when not undergoing
processing.  Cold storage is required to main-
tain sample integrity and to minimize microbial
degradation. The laboratory analyst responsi-
ble for sample storage organizes the samples
for easy and efficient access.  The cold stor-
age area  is  maintained  at a  temperature
of 4°C and is  monitored regularly.

4.2.2.3  Sample Processing and
        Analysis-

     Sample integrity is protected during all
steps of sample handling.  The unique identity
of each sample is maintained by labeling with
the sample code, by  documenting the status
of each sample through all processing and
analyses, and by avoiding physical and chemi-
cal contamination during each processing step.
The  analyses  specified  in Table 4-1 and in
Appendix C are accomplished at the prepara-
tion laboratory. These include field-moist pH,
air-dry moisture, organic matter by loss-on-
ignition, rock fragments, and bulk density.

     Bulk samples are  allowed to air dry in
a  contamination-protected  room  until they
achieve a  prescribed moisture content.  Any
observations  of microbial  growth  or  other

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unusual characteristics are noted in a logbook.
If the calculated moisture content of a compo-
site subsample is below 2.5 percent for miner-
al soils or below 6.0 percent for organic soils,
the sample is considered air dry.
Table 4-1. Preparation Laboratory Parameter* and
         Corresponding Analytical Technique*
Parameter
Technique
PH_MP         Combination electrode/millivoltmeter

MOIST_P       Gravimetric

OM_LOI        Loss-on-ignition

RF_FG, RF_MG   Sieve/gravimetric

BD_CLD        Displacement/gravimetric

BD_KV         Replacement/gravimetric
     If samples labeled as organic soil have
less than 20 percent organic matter or sam-
ples labeled as mineral  soil have greater than
20  percent, the  QA manager and  the soil
sampling task leader are notified immediately
for further instructions concerning the affected
samples.

     After a bulk sample is air dry, the soil is
carefully disaggregated and passed through
nested  4.75-mm  and 2-mm  sieves.   After
sieving, the less than 2-mm soil is retained in
a labeled,  plastic bottle and  placed in cold
storage when not undergoing processing. The
rock fragments are retained  for  gravimetric
analysis (NOTE: fragments exceeding 20 mm
in  diameter are removed in the  field).  The
fragments  are  then placed in a pre-labeled,
plastic bag and are archived by set.

     In order to obtain representative volumes
of  soil,  it  is necessary  to  prepare homogen-
eous subsamples from the less than 2-mm
fraction of the bulk samples. Two subsamples
of each bulk sample are obtained through use
of a Jones-type riffle splitter. The  subsamples
are placed in plastic bottles labeled with DORP
Label B (see Appendix B) and are organized by
batch in cold storage to await shipment to
separate contract analytical laboratories for
general and elemental analyses.  The unused
portions of the bulk soil samples are stored in
labeled  plastic bottles and are archived by set
in cold storage.

     Bulk density is defined as weight per unit
volume  expressed in grams per  cubic  centi-
meter (g/cm3).  Generally, three clod samples
or two  known volume samples are extracted
from each horizon.  The mean of the replicate
bulk density values  is accepted  as the bulk
density  of a particular horizon.

     All raw data obtained are recorded on a
series  of preparation  laboratory  raw  data
forms (see Appendix B).  All data obtained are
immediately  entered into  the computer to
ensure proper tracking, processing, and  eval-
uation of the samples.  Calculated data  from
all of the preparation laboratory analyses are
recorded on the summary data form, Form 101,
which  is  compiled  during  the batching of
samples.  The raw data recorded in logbooks
or on data forms must be submitted to the QA
manager upon completion of the MASS prepar-
ation activities.

4.2.2.4  Data Entry-

     Preparation  laboratory personnel  have
access  to a personal computer directly linked
to the  QA  staff  that allows real-time  data
evaluation and tracking  of  samples by  both
parties.  Data entry screens are developed for
entering information  from the raw data forms
used by the analysts.  All  raw data obtained
during sample receipt and sample  analysis are
entered  into a temporary file in the computer
by  laboratory  personnel.    The  verification
programs are run and printouts of the calcula-
ted data and suspect values are generated
(see Section 6.2 and Appendix D). The preci-
sion and accuracy criteria for QE/QC samples
are checked  while  the  samples are  being
processed, permitting the prompt identification
of any discrepancies.

     The  laboratory manager ensures  that
computer  entry is   current at all times and
checks  the  calculated data for outliers and

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other possible discrepancies.   A computer-
generated spreadsheet shows the status of all
samples  received, samples  being processed,
and samples shipped.  The computer program
produces summary  data  forms that contain
the final data values.

4.2.2.5  Batch  Formation and Sample
         Shipment-

     Batches of  processed soil samples are
assembled  as specified  in  the  PLSOP  and
shipped to the designated analytical laborato-
ries.   Each batch normally contains  40  sam-
ples  but may have as many as 42 samples.
With the exception  of the QC audit sample
(QCAS),  all samples  are  randomly placed
within a batch and cannot be distinguished by
the recipient laboratory.

     The site ID, sample code, and set ID for
each sample are  recorded on the DDRP  Form
101.  This form assigns a unique batch/sample
number to  each  soil sample.  The  shipping
form, DDRP Form 102 (see Appendix  B),  is
completed and sent to the laboratories  toge-
ther  with the samples.  Form  102  uses the
batch/sample information from the Form 101 to
identify each sample while keeping the catego-
ry of sample, e.g., audit or routine, unknown to
the recipient.

4.2.2.6  Sample Tracking-

     Sample tracking at   the  preparation
laboratory is initiated with the computer entry
of sample receipt information upon delivery of
samples to the EMSL-LV cold storage facility.
Since the number of pedons to be sampled  in
the MASS is known before sampling begins, a
tally  of the pedons  received at  cold storage
can  be useful in assessing field  sampling
progress.  As the preparation laboratory raw
data are  entered  into the computer, the QA
staff monitors the proportion of samples that
have undergone processing and analysis to the
total number of  samples at the preparation
laboratory.  In addition, the preparation labora-
tory entry/verification system is used to  track
the samples as batches are shipped to analyti-
cal laboratories.    Sample  tracking reports
about the sampling,  preparation, and analysis
phases of the program are prepared for EPA
management every two weeks.

4.3  Analytical  Laboratory
      Operations

     The  sample analysis is  conducted by
contract  analytical  laboratories through  a
series of  activities outlined  in the following
subsections.   Specific  information on the
analytical  operations  can be  found in the
Analytical  Laboratory  Statement  of   Work
(ALSOW) (USEPA, 1988).

4.3.1  Personnel

     Analytical  laboratory  operations  are
performed by a group of experienced labora-
tory analysts under the supervision of a labor-
atory  manager.   The  manager must  have
several  years of  experience  in  laboratory
analysis of soils  and has the responsibility of
training and supervising the  analysts.   Each
analyst is responsible for specific activities
and is required to uniformly enter raw data on
specified  data forms.  The  laboratory  must
employ sufficient personnel to ensure delivery
of acceptable data within the time constraints
established in the contract.

4.3.2 Laboratory Activities

     A  brief  description of the  analytical
laboratory activities is provided in the following
subsections. Specific information is contained
in the ALSOW.

4.3.2.1  Sample  Receipt-

     All samples delivered to a contracted
analytical  laboratory   are  checked in   by  a
receiving clerk who:  (1)  records on the  ship-
ping form  the date the samples are received,
(2)  evaluates the condition  of  the samples
received,  (3) checks the  samples  to identify
discrepancies with the shipping form, and (4)
sends copies of the completed shipping forms
to the EPA Sample Management Office (SMO)
and the QA manager or designee. If there are
any discrepancies or problems such as lea-
kage in shipping  or an insufficient amount of

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sample,  the  QA manager must be  notified
immediately.  The receiving clerk retains a copy
of the completed Form  102 for the  laboratory
records.  The samples are refrigerated at  4°C
as soon as they are logged in  and must be
kept refrigerated when not in use.

4.3.2.2  Sample  Homogenization-

     The samples  received by the analytical
laboratories have been air dried and disaggre-
gated to pass through a 2-mm  sieve at  the
preparation laboratory.  During shipment,  the
sample  material within  each  container segre-
gates both by particle size  and by  density;
therefore, each  sample must be re-homoge-
nized by thorough mixing prior to the  removal
of aliquots for analysis. Previous research by
the QA staff has been useful in specifying the
homogenization procedures (Schumacher et al.,
in preparation).

4.3.2.3  Measurement of Analytical
          Parameters--

     Procedures specified  in the ALSOW  are
to be followed  exactly for each parameter.
Table 4-2 summarizes the parameters to be
measured  and the  corresponding  analytical
techniques, and Appendix C contains a more
detailed description of the parameters.

4.3.2.4  Contractual Compliance-

     Before a batch of sample data is submit-
ted to the QA  staff for  verification,  certain
completeness and QC requirements must be
met. The batch is not considered acceptable
for complete payment until these requirements
are met (see Section 5.0).

4.3.2.5  Data  Entry  and  Reporting-

     The raw data  generated during sample
analysis are entered on a personal computer
using a specially designed entry and  verifica-
tion system (see Section 6.2.3.1).  Data reports
are then generated  to assist  in the  evaluation
of data  quality.
     In  addition, the  following  documents
must be updated constantly at the analytical
laboratory  and must be  available,  upon  re-
quest,  to  the  analysts and the supervisor
involved in  the project:
Table 4-2. Analytical Laboratory Parameter* and
         Correepondlng Analytical Technique*
Parameter
Technique!
MOIST_A

SAND (and all fractions)

SILT (and all fractions)

CLAY

PH_H2O. PH_002M, PH_01M


CA_CL, CA_OAC. CA_CL2

MG_CL,  MGJDAC. MG_CL2

K_OAC.  K_CL. K_CL2

NA_CL. NA_OAC. NA_CL2

CEC_CL, CEC_OAC

ACJBACL

FE CL2. FE PYP, FE_AO.
 Ft CD. AL CL2. AL PYP.
 AL>O, ALjCD, SI_AO,
 AL_CL

SO4JH2O,  SO4 PO4,
 SO4JO-32

CJTOT,  N_TOT


S TOT
Gravimetric

Sieve/gravimetric

Pipet/gravimetric

Pipet/gravimetric

Combination electrode/
millivolt meter

AA or ICP

AA or ICP

AAor FP

AA, ICP, or FP

Autotitration or FIA

Titrimetric

ICP
Ion chromatography
oxidation/combustion
with IR or TC

oxidation/combustion
with IR
 AA = atomic absorption spectroscopy
 ICP= inductively coupled plasma atomic emission
      spectroscopy
 FP = flame emission photometry
 FIA = flow injection analysis
 IR = infrared detection
 TC = thermal conductivity
  • Standard operating procedures - detailed
    instructions  about  the  laboratory  and
    instrument operations.

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Laboratory QA  plan  -  clearly  defined
laboratory protocol, including personnel
responsibilities and use of QC samples.
List of in-house samples ~ includes dates
for completion of analyses, and allowing
the analysts to schedule further analyses.
Instrument performance data - informa-
tion  about  baseline  noise,  calibration
standard response, precision as a function
of  concentration,  and  detection  limits;
used by analysts and supervisor to evalu-
ate daily instrument performance.
QC charts - plots  of warning  and control
limits for all quality control check samples
(QCCS)  and  detection limit  QCCS  (DL-
QCCS)  generated  and updated for each
batch;  the same  QCCS stock solution
should  be used throughout the term  of
sample analysis in order to ensure conti-
nuity of the control chart.   (NOTE: the
purpose of preparing QCCS control charts
is to  ensure that the actual control limits
do not  exceed  the limits defined by the
contract.)
QC data  report -- a  computer printout
generated  by the laboratory manager that
reviews  QC results for  each  parameter;
specifies flags (Table 4-3) that are used to
document  all  results outside  statistically
established QC limits and to identify sam-
ples that  require reanalysis before data
are submitted.
Table 4-3.  Laboratory Data Qualifier*
Data qualifier
Indication
    A       Instrument unstable
    B       Reanalyzed, first reading not acceptable
    F       Result outside criteria with consent of QA
            manager
    G       Result obtained from method of standard
            additions
    J       Result not available;  insufficient sample
            volume shipped to laboratory
    L       Result not available because of interfer-
            ence
    M       Result not available; sample  lost or
            destroyed by laboratory
    N       Result outside QA criteria
    P       Result outside criteria, but insufficient
            volume for reanalysis
    R       Result from reanalysis
    S       Contamination suspected
    T       Container broken
    U       Result unnecessary, or not required by
            procedure
    X       No sample
    Y       [Available for miscellaneous comments]
    Z       Result from approved alternative method

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                                                                            Section 4
                                                                            Revision 1
                                                                            Date: 4/89
                                                                            Page 8 of 9
     Examples of the data reporting forms
used by the analytical laboratory are provided
in the ALSOW, although examples of certain
QE/QC reporting forms are provided in Appen-
dix D.  When  applicable, data are annotated
with  the  appropriate data qualifiers  listed in
Table 4-3.  Results must be  reported to the
number of decimal places listed in Table 4-4.
Table 4-4. Decimal-Place Reporting Requirement*

                           Reporting Decimal
Parameter                     units  Places
MOIST A
SAND (and all fractions)
SILT (and coarse silt)
CLAY (and fine silt)
PHJH20, PH_002M, PH_01M
CA CL. MG CL. K CL, NA CL,
AL_CL
CA OAC. MG OAC. K OAC,
NA_OAC.
CEC_CL. CEC_OAC, AC_BACL
wt. %
wt. %
wt. %
wt. %
pH units
meq/100g
meq/100g
meq/100g
2
2
2
4
2
3
3
3
CA CL2, MG CL2, K_CL2,
 NA_CL2. FE_CL2. AL_CL2       meq/100g
FE PYP. AL PYP, FE AO, AL AO.
SI_AO, FE_CD. ALjCD
SO4_H2O. SO4_PO4
SO4_0-32
C_TOT, N_TOT
S_TOT
wt. %
mg S/kg
mg S/L
wt. %
wt. %
3
3
3
3
4
     All deviations from the analytical proto-
cols must be documented.  All original raw
data such as data system printouts, chroma-
tograms, logbooks, individual data sheets, QC
charts, and standard preparation data should
be retained by the analytical laboratory and be
available upon request.
4.3.2.6  Evaluation of Quality Control
         Data-

     A data entry and verification system (see
Section 6)  that is provided  to  the  analytical
laboratories includes programs that evaluate
the QC data and  report the information for
each parameter in a summary report.   The
objective of these summary reports is to keep
the QA manager informed of the status of the
internal QC checks at the laboratory in order
to identify and resolve any problems that may
arise.  Before laboratories submit a batch of
data to  the QA staff, all  parameters must
satisfy the QC requirements outlined in the
contract.  The  laboratory managers are ex-
pected to keep the QA manager apprised, on
a regular basis, of the evaluation of the QC
data either by phone or by sending preliminary
data electronically to the QA staff for similar
evaluation.

4.3.2.7  Communications-

     Frequent  communications, i.e., two or
three contacts each week, are maintained with
each analytical laboratory in order  to obtain
current  sample status and to discuss  any
problems that  may occur  during  analyses.
These  discussions are to  be  recorded in  a
logbook  by the QA staff and  the  laboratory
staff. Preliminary and final data are available
for access via electronic transfer. The prelimi-
nary data are reviewed for anomalies and if a
problem is identified, the laboratory is notified.
Corrective action  or reanalysis may be sug-
gested. Contractual issues are referred to the
QA manager and to the contract officer. Major
technical issues are referred to the QA manag-
er.

4.4  Sample  Custody

     Legal chain-of-custody procedures are
not required for this study;  however, sample
custody must be documented.  The field crew
leader is responsible for all samples in the

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                                                                             Section 4
                                                                             Revision 1
                                                                             Date:  4/89
                                                                             Page 9 of 9


field as well as the sample shipments. As soil     the soil  sampling task  leader and the field
shipments  are received in the  preparation     crew  leader are notified. Following receipt of
laboratory, they are immediately logged in and     samples, the appropriate laboratory managers
checked  against  the packing  slip  and the     are responsible for sample integrity until the
pedon description forms for proper labeling     samples are archived.
and quantity.  If any discrepancies are found,

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                                                                            Section 5
                                                                            Revision 1
                                                                            Date:  4/89
                                                                            Page 1 of 17
                                     Section 5

                         Quality Assurance Program
     This  section describes the  MASS QA
program which is  designed to  allow  both
control  and assessment  of  measurement
uncertainty during the  sampling, preparation,
and analysis phases of the survey.

5.1  Overview of Quality
      Objectives

     The  data collection criteria  provide  a
balance between constraints of  time and cost
and the quality of data necessary to achieve
the DDRP research objectives. The MASS QA
Plan is designed to accomplish the following
general objectives:

  • establish  the QE/QC  criteria  used  to
    control and assess data collected in the
    survey;
  • provide  standardized sampling, prepar-
    ation, and analytical  methods and proce-
    dures;
  • utilize assessment samples  and proce-
    dures to verify the  quality of the data;
  • perform field and laboratory on-site audits
    to ensure that all  activities are  properly
    performed  and  that  discrepancies  are
    identified and resolved; and
  • evaluate the  data  and document  the
    results in QA reports to EPA management.

     To aid in  this effort, it  is  necessary to
identify both qualitative and quantitative  esti-
mates of the quality of data needed by the
DDRP data users.  Guidelines established by
the EPA Quality Assurance Management Staff
(Stanley and Verner, 1985) encourage the data
users to clearly identify the decisions that will
be  made  and  to specify the  calculations,
statistical and otherwise, that are  applied  to
the data.

     The raw data for  the DDRP surveys are
collected during four major operational phases
consisting of mapping,  sampling, preparation,
and analysis. A certain amount  of data mea-
surement uncertainty is expected to enter the
system at each phase. Grouping of the data,
e.g., by sampling class/horizon configurations,
also increases uncertainty.   The  sampling
population  itself is a source of confounded
uncertainty that is extremely difficult to quanti-
fy.   Generally, the  data quality  objectives
(DQOs)  encompass  the overall  allowable
uncertainty from  sample  measurement and
from the sampling population that the  data
users are willing  to  accept in the  analytical
results (Taylor, 1987).  Because of the many
confounded sources  of  uncertainty,  overall
DQOs for the MASS have not  been  defined.

     This QA  Plan focuses on the definition,
implementation, and assessment of measure-
ment quality objectives (MQOs) that are speci-
fied for  the entire  sample preparation and
analysis phases of data collection, as well as
for the verification of the field sampling phase.
The MQOs are more or  less specific goals
defined by the  data users that clearly describe
the data quality that is sought for each of the
measurement phases. The MQOs are defined
according to the following six attributes:

 •  Detectability ~ the lowest concentration of
    an analyte that a  specific analytical proce-
    dure  can reliably  detect.
 •  Precision — the level of agreement  among
    multiple measurements of the same char-
    acteristic.
 •  Accuracy  - the  difference between an
    observed value and the true value of the
    parameter being estimated.
 •  Representativeness - the degree to which
    the data collected accurately represent the
    population of interest.
 •  Completeness - the quantity of data that
    is successfully collected with  respect to
   the amount intended  in the experimental
   design.
 • Comparability - the similarity of data from
   different sources included within individual
   or  multiple data  sets;  the similarity of
   analytical methods and data from related
   projects across regions of concern.

-------
                                                                           Section 5
                                                                           Revision 1
                                                                           Date:  4/89
                                                                           Page 2 of 17
     An attempt has been made later in this
section to define each quality attribute individu-
ally for each measurement phase of the pro-
gram  (sampling,  preparation,  analysis)  or
collectively  for overall  measurement system
uncertainty  on  a   parameter-by-parameter
basis.  The term  "uncertainty" is used as a
generic term to describe the sum of all sour-
ces of error associated with a given portion of
the measurement system.  In order to reduce
measurement  uncertainty  in  the final data
values, error occurring in each phase must be
identified and rectified during that phase of the
survey.   Measurement uncertainty  for the
MASS is controlled through well-defined proto-
cols, system audits, and the introduction  of
measurement quality samples at each mea-
surement phase.

     Initial MQOs were  established  on the
basis of the requirements of EPA data users
and on the selection of appropriate methods
to obtain the data. The MQOs were reviewed
by persons familiar with analytical methods
and soil characterization techniques, including
soil   chemists and   laboratory personnel.
Modifications to the MQOs and to  the proto-
cols were implemented based on information
gained from the DDRP Northeastern region and
Southern Blue Ridge Province surveys, from
peer review comments, or  according to the
limitations of a particular analytical  procedure
or instrument.

     If the data quality goals cannot  be met
during  the  course of the project, the actual
level of quality is used to reassess the intend-
ed use  of  the data.   A lower than desired
attainment  of data quality could require differ-
ent approaches to be used in data analysis or
may result in  modifications  to the levels  of
confidence  assigned to the data.

5.2  Design Characteristics

     The design  of  the  DDRP QA Program
incorporates  the  concept of  batch  sample
analysis, where the soil samples collected in
the field are  combined  into  groups called
batches.  Within  these batches a  series  of
different  types   of   measurement   quality
samples are included which are used to evalu-
ate and, possibly, control various  types  of
measurement  uncertainty.   There  are  two
distinct groups of measurement quality sam-
ples used in the MASS design:  quality evalua-
tion (QE)  samples and quality control (QC)
samples.  The QE samples allow an indepen-
dent assessment by the QA staff, while  the
QC samples enable  a laboratory to  control
measurement  error and to meet contractual
requirements.  In order to assess the MQOs,
a series of  both types of samples  must  be
analyzed together with the routine samples in
a manner  that is statistically relevant and in
which conclusions concerning  the quality of
data can be made.  There are a number of
assumptions upon which this design  has been
based:

  • Complete  attainment of  the  analytical
    MQOs can be accomplished if each batch
    meets the within-batch MQOs set for the
    data quality  attributes.
  • A two-tiered approach to measuring ana-
    lytical  precision allows the  low concentra-
    tion samples to  be assessed separately
    from the mid-range and high concentration
    samples; a knot  value separates the two
    tiers and  is determined by  dividing  the
    precision objective for the lower tier by the
    precision objective  for the  upper tier and
    multiplying by 100.
  • Approximately 25 percent of the overall soil
    analysis effort is  applied to the analysis of
    QE/QC samples  required for assessment
    purposes; normally there are 40 samples
    in a batch, hence,  about 10 of these are
    measurement quality samples.
  • Measurement uncertainty  at any given
    level, e.g., analytical within-batch precision,
    should be evaluated by the analysis of a
    minimum of  20 QE samples of any given
    type; since 30 to  35 batches are expected
    to be analyzed during MASS, at  least one
    sample  used in  the evaluation of overall
    measurement uncertainty  is included in
    each batch.
  • The primary sources  of measurement
    uncertainty to be  identified, controlled, and
    assessed are from sampling, preparation,
    and analysis.

-------
                                                                           Section 5
                                                                           Revision 1
                                                                           Date:  4/89
                                                                           Page 3 of 17
  • Each of the primary sources of uncertainty
    may be considered to be a combination of
    several smaller  sources of uncertainty,
    e.g., the analytical component can consist
    of  between-laboratory,  between-batch,
    within-laboratory, and within-batch uncer-
    tainties.
  • Accuracy includes characteristics of audit
    sample control windows, bias  in relation
    to other laboratories, and trends relative
    to the accepted "true" value.

     To date, it has  not been feasible to pro-
vide one QE or  QC sample  type whose entire
variability is a  reflection of overall measure-
ment  uncertainty.  However, the  combination
of two or more different types of measurement
quality samples which include the quantifiable
components of system  measurement uncer-
tainty can provide a reasonable and defensible
estimate of overall data  quality.

     Figures 5-1 and 5-2 graphically illustrate
the QE/QC samples  that are placed in each
mineral or organic batch  of analytical samples
to determine measurement uncertainty. There
are separate analytical within-batch precision
MQOs for organic and mineral soils because
of  the  expected  wide  variability in analyte
concentrations.  For  this reason, mineral and
organic samples are organized and analyzed
in separate batches.

5.2.1  Quality Evaluation Samples

     The  QE  samples  are  those  samples
which are known to the QA staff but are either
blind or double  blind to  the sampling crews,
preparation laboratory, or analytical laboratory.
A blind sample has a concentration range that
is unknown to the analysts, whereas a double
blind sample cannot  be  distinguished from a
routine sample and has a concentration range
that is unknown to the analyst (Taylor, 1987).
These samples  provide an independent check
on the QC process and can be used to evalu-
ate whether the MQOs have been met for any
given  run  or batch,  or  for  all batches, i.e.,
overall  measurement  uncertainty.  Impor-
tant characteristics of the QE audit samples
include their  similarity to routine samples in
matrix type  and concentration  level,  their
homogeneity  and stability,  and their defined
accuracy windows.  Every QE sample has a
specific  purpose  in  the  data  assessment
scheme, as described below and in Table 5-1.

5.2.1.1  Field Duplicate  (FD) Sample-

      From every third pedon sampled, a FD
sample is collected from a horizon selected at
random by the  sampling crew leader.   The
crew  places alternate trowels-full of soil  into
separate bags to produce a pair of samples
(one routine, one duplicate) from one specific
horizon  within a specific pedon.  Individual
pairs  are used primarily to assess the overall
within-batch precision. These estimates are
pooled to provide the within-batch component
of overall system measurement uncertainty.

5.2.1.2  Field Audit (FAP or  FAO)
         Sample--

      The  FAP   sample is  a  median-range
mineral audit sample sent in pairs by the QA
staff to the sampling crews.  The FAO sample
is a median range organic audit sample sent
in triplicate by the QA staff to the sampling
crews. The FAP and FAO samples are treated
as  if  they had  just been obtained from the
excavated pit, i.e., the samples are sieved  and
bagged during the collection of a FD sample.
These samples are then handled as  if they
were  routine samples and undergo all of the
associated  soil  preparation  and  analysis
steps. The FAP and FAO samples are used to
identify  within-run and within-batch  system
precision and accuracy for mineral and organic
batches,  respectively.   The  variability,  i.e.,
imprecision, is reported as  the mean square
error by analysis of variance (ANOVA) and the
bias,  i.e., inaccuracy,  is calculated  as  the
difference between an actual measured value
and the reference value established by previ-
ous DDRP analysis. The analytical data from
each pair  are also pooled  from all  batches
to provide an estimate of  other  sources of
measurement uncertainty, such as between-
batch or between-laboratory system uncertain-
ty.

-------
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 accuracy

    11
         7D " field  duplicate; FAL •  low-range field audit; FAP « field audit pair; PD « preparation duplicate; LAL • low-range laboratory audit; LAP *• laboratory
         audit pair; QCAS • quality control  audit •ample; AD " analytical duplicate.
                                                                                                                                                  0) Q) (D

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-------
                                                                           Section 5
                                                                           Revision 1
                                                                           Date:  4/89
                                                                           Page 6 of 17
Table 5-1.  Statua and Assessment of Measurement Quality Samples
Status of sample*
Sample QA
type staff
FAL K
FAP K
FAO K
FD
LAL K
LAP K
LAO K
PD
QCAS K
MS K
Sampling
crew
B
B
B
B
Preparation
laboratory
B
B
B
B
B
B
Analytical
laboratory
DB
DB
DB
DB
DB
DB
DB
DB
B
* K - known concentration, B - blind, DB « double blind
. D - detectability/contamination, P - precision, A - accuracy, R
* For preparation laboratory parameters only.

System
D.A
P.A
P,A
P
Assessm
Sampling
D.A-
P.A-
P.A-
P.R
ant ouroose"
Preparation
D.A-
P.A-
P.A-
P
P.R
A*

Analysis
A
P.A
P.A
P
D
P.A
P,A
P
A
• representativeness
5.2.1.3  Low-Range Field Audit (FAL)
         Sample-

     The  FAL sample  is sent with the FAP
samples to the sampling crews by the  QA
staff and  is handled in the same manner as
the FAP samples. The FAL is used to identify
any system contamination and as an addition-
al check on preparation and system  accuracy
of mineral soil samples. Pooled data from all
FAL samples provide an estimate of the sys-
tem detection limit (SDL), which is calculated
as three times the pooled standard  deviation
of the FAL samples.

5.2.1.4  Preparation Duplicate (PD)
         Sample--

     A pair of PD samples, one split from the
FD sample and one split from  its associated
routine sample, are created at the preparation
laboratory immediately following sample homo-
genization and are placed in each batch. The
PDs are  used to  identify the within-batch
preparation  uncertainty  component of  the
overall measurement uncertainty and as an
independent check on the within-batch  preci-
sion estimates  provided by  the  analytical
laboratories.  The samples characterize mea-
surement  uncertainty  introduced  during or
after   homogenization/subsampling   at  the
preparation laboratory,  but do not identify the
uncertainty related to sample drying or sieving,
or any contamination occurring prior to sample
homogenization.  The uncertainty attributed to
sample  preparation is calculated  by ANOVA
and is  derived after identifying and  isolating
the uncertainty from sample analysis.

5.2.1.5 Laboratory Audit (LAP or LAO)
         Sample--

     The LAP samples are mineral audit sam-
ples, identical to the FAP samples,  that  are
sent in  pairs by the  QA staff directly to  the
preparation  laboratory for inclusion in each
mineral batch sent to an analytical laboratory.
The LAO samples are organic audit samples,
identical to the FAO samples, that are sent in
triplicate by the QA staff directly to the prepa-
ration laboratory for inclusion in each organic
batch sent to an analytical laboratory.  The
LAP  and LAO samples  are used to assess
analytical within-batch precision and accuracy
and are used in combination with the FAP and
FAO samples to identify sources of bias, e.g.,
contamination or method error.   Comparing
the LAP/LAO data across batches allows the
QA staff  to calculate  interlaboratory differ-
ences and to assess between-laboratory and
between-batch components of analytical mea-
surement  uncertainty. The precision compo-
nents of measurement uncertainty are calcu-
lated by ANOVA and the bias is calculated as
the difference between  an actual measured
value and the  reference  value  established

-------
                                                                           Section 5
                                                                           Revision 1
                                                                           Date:  4/89
                                                                           Page 7 of 17
by  previous DORP analysis.  The  LAP/LAO
samples are also used to assess between-
batch and between-laboratory uncertainty.

5.2.1.6  Low-Range Laboratory Audit
         (LAL)  Sample-

     The LAL is a  low-range natural audit
sample, identical to the FAL, that is  sent by
the  QA staff  directly to  the  preparation
laboratory for inclusion in each mineral batch
sent to an analytical laboratory. When used in
conjunction with the FAL sample, the LAL is
helpful  in  calculating  instrument  detection
limits (IDLs) as well  as in identifying the
magnitude and source  of sample contamina-
tion. The calculated IDL for a given parameter
is estimated as  three times  the pooled stan-
dard deviation of the LAL samples. The IDL is
used as an  independent check on laboratory
detection limits.

5.2.1.7  Manager's Sample (MS)»

     The MS is  a natural audit sample used
only at the preparation  laboratory that allows
the  QA staff  to independently  assess the
accuracy of data produced during the prepara-
tion laboratory analyses.  One MS subsample
is placed in each run of analysis and must fall
within  the  control limits established in the
sample  preparation MQOs.

5.2.2  Quality Control Samples

     In order to produce data of consistently
high quality, the  contract  laboratories are
required to analyze certain types  of QC sam-
ples that are known to the laboratory staff
and that can  be used by  the  analysts to
identify  and control  analytical measurement
uncertainty.   Each QC sample  has certain
specifications that must be  met  before data
for  the parameter or batch are accepted, as
listed in Table 5-2. The QC samples are non-
blind samples  procured  under  contract to
assist the laboratories  in meeting laboratory
MQOs  and include both  soil samples, e.g.,
analytical duplicates, and non-soil samples,
e.g., reagent blanks.  The  QC samples are
analyzed by each laboratory and allow the
laboratory manager and the QA  staff to as-
sess whether the physical and chemical analy-
sis is under control. The QC samples used in
the MASS are detailed in the following subsec-
tions.

5.2.2.1  Quality Control Audit Sample
         (QCAS)-

     The QCAS  is a natural audit sample
provided directly to the analytical laboratories
along with the corresponding reference value
obtained by  previous  DDRP analysis.  The
QCAS  is  used to control  bias  and  reduce
between-laboratory and between-batch compo-
nents of measurement uncertainty.  Data for
the QCAS are evaluated by batch on a control
chart  to ensure  that  the  result are within
acceptable accuracy limits as defined by the
QA staff.  If the  QCAS does not  meet the
accuracy window criteria, the batch of sam-
ples is reanalyzed for the parameter in ques-
tion.

5.2.2.2  Analytical Duplicate  (AD)
         Sample-

     A duplicate subsample of a  specified
routine sample, i.e., the 25th sample in each
batch,  is selected as the AD sample at the
analytical laboratory and is used  to  ensure
that within-batch precision  MQOs  are being
satisfied.  Precision is calculated as a stan-
dard deviation or relative standard deviation,
depending on concentration, and is evaluated
to ensure that the result is  within acceptable
limits  set forth in the  laboratory  contract.  If
the precision objectives for the AD are not met,
the batch of samples is reanalyzed for the
parameter in question.

5.2.2.3  Calibration Blank-

     One calibration blank per batch is  ana-
lyzed  immediately after the initial calibration
to check for  baseline  drift.  The calibration
blank is defined as a zero mg/L standard and
contains only the matrix of the calibration
standards with no analyte  present.   During
batch  sample  analysis, a  calibration blank
is  run at the beginning, after every 10 sam-
ples, and at the end of each analyzed batch.

-------
                                                                                  Section 5
                                                                                  Revision 1
                                                                                  Date:  4/89
                                                                                  Page 8 of 17
Tabla 5-2.  Quality Control Requirements for Analytical Batch**
        Sample type
        Parameter
          Requirement
   QC audit sample (QCAS)

   Analytical duplicate (AD)

      Calibration blank
        number run
         measured

    Reagent blank (mean)
   QC check sample (QCCS)
        number run
         measured
    Detection limit QCCS
         (DL-QCCS)

    Matrix spike recovery


       Spike solution




     Ion chromatography (1C)

Instrument detection limit (IDL)

       Sample weight

       Sample volume
           ALL

           ALL


           ALL''"
           ALL'-c'd

 PH H20, PH 002M, PH 01M
         SO4 2-16
         SO4 32
       ALL OTRERSd
           ALL
        SO4 0-32
       ALL OTHERS"

          ALLa
        S04 0-32
       ALL OTHERS"

          S04 0
        SO4_2-16
         S04 32
         CA_CL2

SO4_H2O. SO4_PO4. SO4JO-32

          ALL''0

           ALL

           ALL
     Within accuracy window

Satisfies precision limits in Table 5-5
    ((samples in batch/10) + 1)
            < CRDL

        4.5 <_ mean <_ 7.5
       ± 3% of theoretical
       ± 2% of theoretical
            < CRDL
    ((samples in batch/10) + 1)
       i 5% of theoretical
       ± 10% of theoretical

       ± 20% of theoretical
        95% < x <. 105%
        90% < x <. 110%

            <.CRDL
      i 3% theoretical value
      ± 2% theoretical value
      ± 5% theoretical value

        Resolution >. 60%

            ;< CRDL

     Measured = ± 5% method

       Measured = method
' Except moisture, particle size, and pH parameters.
" Except SO4 2-32.
c Except AC SACL
d Except FSi; CLAY, and AC_BACL.
e Except moisture, particle size, AC_BACL, and SO4_0,4,16 parameters.
These  calibration blanks  are used to check
for  significant baseline drift and should have
values less than the CRDL, except for exchang-
eable acidity.  The within-batch data from the
calibration  blanks are used to calculate long-
term IDLs.

      All calibration standards are prepared as
specified in  the  appropriate  procedure.   A
calibration curve for each analytical method is
established by using  a  minimum  of  three
points within the  dynamic  linear range. The
                 use of at least a three-point calibration curve
                 is  required  in  place  of the manufacturer's
                 recommendations  for  the  instrumentation,
                 unless those recommendations specify more
                 than three points within the linear range. The
                 concentration of  standards must bracket the
                 expected sample concentration without exceed-
                 ing the dynamic linear range of the instrument.
                 The lowest  standard should not be greater
                 than 10 times the CRDL. If the concentration
                 of  a sample falls  outside  the range  during
                 analysis, the sample is diluted and reanalyzed.

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                                                                            Section 5
                                                                            Revision 1
                                                                            Date:  4/89
                                                                            Page 9 of 17
     For the MASS, an IDL is defined as three
times the standard deviation  of  at  least 15
nonconsecutive calibration blank analyses run
on three separate days, based on a similar
formula defined  by Winefordner  and Long
(1983).  In some analyses, such as ion chro-
matography,  a signal may or may not  be
obtained for a blank analysis; in these cases,
the IDL is defined as three times the standard
deviation of 15 nonconsecutive replicate analy-
ses of a standard whose concentration is four
times the lesser of the actual detection limit or
the CRDL

     Acceptable initial IDLs must be estab-
lished prior to any sample analysis.  Ongoing
IDLs are determined and reported monthly or
on a per-batch basis upon batch submission,
whichever is more frequent, for all except the
moisture, particle  size, and pH parameters.
The raw data for the initial IDL  determinations
must be reported to the QA manager.  Initial
IDLs are valid  for one month  following their
establishment;  after this,  new IDLs must be
established prior to any sample analysis for
the first batch of samples.  Ongoing IDLs are
determined only for those parameters being
analyzed during a given reporting period.

     After the  validity  of the initial IDLs  has
been established, the first batch of samples is
analyzed and the IDLs  reported for this batch
are determined as composites of the calibra-
tion blanks from the batch and the calibration
blanks run on the second and third day of the
initial   IDL determination.  If a given IDL is
invalid,  then reanalysis of the  batch for the
parameter of interest is required. Similarly, the
IDLs for other sample  batches will be estab-
lished as composites of the calibration blanks
from the batch being analyzed and the calibra-
tion blanks  from the   two previous  batches
such that the  calibration  blanks have been
determined over three  separate days.  It is
essential that each laboratory analyzes  the
batches sequentially in order to establish the
proper IDL determinations; any exceptions to
this practice must be reported  immediately to
the QA manager.
5.2.2.4  Reagent Blank-

     When an  analytical  method  requires
sample preparation, a reagent blank for each
group of samples processed is prepared and
analyzed.   A reagent blank is defined  as a
sample composed of  all the reagents, in the
same quantities, used in preparing  an actual
sample for analysis. The reagent blank under-
goes the same digestion and extraction proce-
dures as an actual sample.

     For most parameters, the analyte con-
centration of a reagent  blank  must be less
than or equal to the CRDL;  if not, the source
of contamination must be  investigated  and
eliminated. A new reagent blank is then pre-
pared and analyzed, and the same criteria are
applied.   All samples  associated  with the
"high" blank must be reprocessed and reana-
lyzed after the contamination has been elimi-
nated.   Approximately seven samples and a
reagent blank are analyzed prior to the matrix
spike and duplicate analyses so that approxi-
mate endogenous sample concentrations may
be determined.

5.2.2.5 Quality Control Check Sample
         (QCCS)-

     Immediately after calibration of an instru-
ment, a QCCS containing the analyte of  inter-
est at  a  concentration in the mid-calibration
range is analyzed.  The QCCS is analyzed to
verify the calibration curve prior to any sample
analysis, after every 10 samples, and after the
last sample of a batch. The sample must be
selected from a stock solution different than
that used for the instrument calibration.

     The QCCS data are plotted at the labora-
tory on a control chart, which warns when the
concentrations are outside of established QC
limits.  The same QCCS stock  solution must
be used  to establish  all values on a given
control chart to  ensure continuity.   The ob-
served concentration for each QCCS is plotted

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                                                                            Section 5
                                                                            Revision 1
                                                                            Date:  4/89
                                                                            Page 10 of 17
on the chart and the 95 and 99 percent confi-
dence  intervals (warning and control  limits,
respectively) are developed.  The control limits
must not differ from the  theoretical value by
more  than  the limits given in Table 5-2.  A
value outside the control  limits is considered
unacceptable,  hence, the  instrument is  recali-
brated and all  samples up to  the last accept-
able QCCS are reanalyzed.

     After  each day of analysis, the control
charts are  updated.   Cumulative  means  and
new warning and control limits are calculated.
If bias for a given analysis is indicated,  i.e., at
least  seven successive points occur on  one
side of the cumulative mean, sample analysis
must cease until an explanation is found  and
the system is  brought under control.

5.2.2.6  Detection Limit Quality
         Control Check  Sample
         (DL-QCCS)-

     The DL-QCCS is a low-range QC sample
that contains the analyte of interest at concen-
trations specified  in the respective method.
The purpose of the DL-QCCS is to  eliminate
the necessity  of  formally  determining  the
detection limit  on a daily basis. The sample is
run once per  batch and  the  measured value
must  be within 20 percent  of the theoretical
concentration listed in Table 5-2. If this criteri-
on  is not met, the source  of error must be
identified and  corrected,  and an acceptable
result must be obtained before routine sample
analysis is resumed.

5.2.2.7  Matrix Spike Sample-

     For liquid samples, e.g., cation  extrac-
tions, one matrix spike sample is prepared for
each  procedure by  spiking an aliquot of a
solution with a known quantity of analyte prior
to analysis. The spike concentration must be
approximately  equal to the endogenous level or
10  times  the  detection  limit,  whichever is
larger.  Also, the volume of the  added spike
must  be negligible, i.e., less than or equal to
one percent of the sample aliquot volume.

     For solid samples, e.g., aliquots for total
carbon, one matrix spike sample is prepared
for each procedure by adding a known weight
of material containing the analyte of interest to
a sample of known weight.  The spike concen-
tration should be twice the endogenous level
or 10 times the detection limit, whichever is
larger. The concentration of the matrix spike
must not exceed the linear range of the instru-
ment. Although it is not negligible, the weight
of the spike material should be considered
negligible for the purposes of calculation.

     The  spike recovery must  be within the
limits shown in Table 5-2. If these criteria are
not satisfied,  then two additional (different)
samples  are spiked with the analyte in ques-
tion  and  are  analyzed.  If  the recovery from
either sample does not meet requirements, the
entire batch must be analyzed by the method
of standard additions.  The method of stan-
dard additions is performed by analyzing the
sample, analyzing the sample plus a spike at
about the endogenous level, and analyzing the
sample plus a spike at about twice  the endo-
genous level.  The concentration of the matrix
spike sample must not exceed the linear range
of the instrument; if  this is not possible, the
spiked sample is diluted before  analysis.

5.2.2.8  Ion Chromatography  (1C)
         Resolution Sample--

     An 1C resolution test  is performed once
per analytical run by analyzing a standard that
contains  concentrations  of approximately 1
mg/L each for sulfate, phosphate, and nitrate.
The  analysis  is run to provide  evidence of
"clean" peak separation for proper quantifica-
tion of each of the sulfate parameters.  If  the
resolution does not  exceed 60 percent,  the
column should be replaced, and the resolution
test  should be repeated.

5.2.2.9  Internal Duplicate-

      The internal duplicate is  a  duplicate
subsample used  only during the preparation
laboratory analyses.   It is characterized in
essentially the same manner as the AD sample
described above.  The internal  duplicate is
helpful in assessing within-run precision during
sample preparation.

-------
                                                                            Section 5
                                                                            Revision 1
                                                                            Date:  4/89
                                                                            Page 11 of 17
5.3  Description of Measurement
       Quality Objectives

      The  following text describes  the  data
quality attributes and MQOs as they apply to
the sampling, preparation, and  analysis pha-
ses  of  the  MASS.  Implementation  of the
MQOs during the survey is described  in Sec-
tion 6.

      The structure of the three analytical MQO
tables in this  section (tables  5-3,  5-4, and
5-6) is as follows:
  • Parameter   -   data  variable  name  of
    parameter being analyzed (see  Appendix
    C).
  • Reporting units   ~   analytical units in
    which  the laboratory  data  should be
    reported.
  • CRDL - contract-required detection limit
    expressed in reporting units and in parts
    per million.
  • Precision at the lower limit  ~  a guideline
    to define the acceptable absolute standard
    deviation for low concentrations that are
    difficult  to reproduce; a knot, or cutoff
    value, is reported for which data below the
    knot  are assessed separately from  data
    above the knot.
  • Precision at the upper limit -- serves as a
    guideline to define the acceptable percent
    relative standard deviation for concentra-
    tions above the knot.

5.3.1 Field Sampling and
       Characterization

     Soil  sampling includes  the  physical
removal of soil samples from an excavated pit
as well as  the characterization of the soil
pedon and the sampling site.  Because the
MQOs developed for the analytical operations
are not applicable  to the sampling activities,
specific  objectives  for soil  sampling were
developed to ensure that field operations, e.g.,
sampling site location, profile description, and
sampling, are conducted in a consistent man-
ner. 'Tie objectives are intended to reduce the
errors inherent in collecting soils data  and to
provide an estimate of the variability among
sampling crews.
     The goal of the  MASS sampling is to
describe and collect soil samples from repre-
sentative pedons  of  established  sampling
classes.  The classes  are intended to repre-
sent the soil characteristics of the Mid-Appala-
chian region.   The field sampling  produces
both qualitative data from pedon characteriza-
tion, e.g., soil color, and quantitative data from
analysis of the soil samples, e.g., soil pH.

5.3.1.1  Precision and Accuracy-

     Due to the subjective  nature  of pedon
characterization,  values  for  precision and
accuracy cannot be determined.  However, by
the use of multiple descriptions by a number
of individuals at the same pedon, variability of
descriptions can  be assessed.  Control and
assessment of the pedon characterization are
accomplished through  various auditing tech-
niques discussed in later sections.

     Field sampling precision and  accuracy
are assessed using data from the QE field
samples to estimate the system measurement
uncertainty and comparing this uncertainty to
that identified in the  QE  preparation and
analytical samples.  The  field samples  are
expected  to  contain the largest amount  of
confounded error of all QE/QC samples. The
MQOs for precision of the physical and chemi-
cal analyses of the field samples are pres-
ented in Table 5-3.  Accuracy is assessed by
comparing the laboratory data to the audit
window criteria defined for the audit samples.
It should be noted that  the MQOs for field
sampling are not intended to  control field
sampling error but are used to assess this
error and to control within-laboratory error at
the preparation laboratory and within- and
between-laboratory error  occurring  at  the
analytical laboratories.

5.3.1.2  Representativeness-

     Soil types identified in the Mid-Appala-
chian region  are combined  into  sampling
classes that are  known to  have, or are ex-
pected to have, similar  physical and chemical
characteristics. Each of the sampling classes
can be  sampled across a number of water-
sheds in which they occur.  In this approach,

-------
Table 5-3. Analytical Laboratory Wlthln-Batch Precision Objectives for Field Samples
Precision for
mineral samples'*

Parameter
MOIST A
SAND ~
SILT
CLAY
PH H2O
PH 002M
PHJ)1M
CA CL
MG CL
K Cl
NACL
ALjCL
CA OAC
MG~OAC
K OAC
NA_OAC
CEC CL
CEC'OAC
AC_§ACL
CA CL2
MG~CL2
K Cl2
NA CL2
FE~CL2
ALJ3L2
FE PYP
AL PYP
FE~AO
AL AO
SI AO
FE~CD
AL~CD
SO4 H2O
SO4 PO4
SO4J>-32
C TOT
N TOT
S~TOT
Reporting
units
wt. %
H
H
"
pH units
H
"
meq/100g
H
H
H
"
meq/lOOg
M
H
H
meq/100g
N
H
meq/100g
•
M
H
H
M
wt. %
H
H
H
H
II
N
mg S/kg
it
mg S/L
wt. %
M
M
CRDL"
units

—
—
—
_
—
—
0.003
0.005
0.002
0.003
0.007
0.003
0.005
0.002
0.003
0.14
0.14
0.25
0.005
0.0008
0.0003
0.0004
0.0005
0.0011
0.005
0.005
0.005
0.005
0.005
0.002
0.002
0.50
0.50
0.025
0.01
0.005
0.001
ppm

—
—
—
	
—
—
0.05
0.05
0.05
0.05
0.10
0.05
0.05
0.05
0.05
1.050'
1.050-
0.005?
0.50
0.05
0.05
0.05
0.10
0.10
0.50
0.50
0.50
0.50
0.50
0.50
0.50
0.025
0.025
0.025
100.0
50.0
10.0
SD
(lower)
0.3
6.0
6.0
4.0
0.20
0.20
0.20
0.04
0.04
0.04
0.04
0.40
0.04
0.04
0.04
0.04
0.50
0.50
2.0
0.10
0.01
0.01
0.01
0.02
0.10
0.06
0.06
0.06
0.06
0.06
0.06
0.06
3.0
3.0
0.20
0.10
0.03
0.004
RSD
(upper)
2.5%
—
—
—
_
—
—
30%
30%
30%
30%
45%
30%
30%
30%
30%
30%
30%
45%
15%
30%
30%
30%
45%
45%
30%
30%
30%
30%
30%
30%
30%
30%
30%
15%
30%
30%
30%

Knot
12.0
—
—
—
»
—
—
0.13
0.13
0.13
0.13
0.89
0.13
0.13
0.13
0.13
1.7
1.7
4.4
0.67
0.03
0.03
0.03
0.04
0.22
0.20
0.20
0.20
0.20
0.20
0.20
0.20
10.0
10.0
1.3
0.33
0.10
0.01
Section 5
Revision 1
Date: 4/89
Page 12 of 17
Precision for
oraanic samples'"
SD
(lower)
0.3
—
—
—
0.20
0.20
0.20
0.20
0.20
0.20
0.20
1.0
0.20
0.20
0.20
0.20
0.50
0.50
2.0
0.40
0.10
0.05
0.05
0.10
0.40
0.06
0.06
0.06
0.06
0.06
0.06
0.06
3.0
3.0
—
0.10
0.03
0.004
RSD
(upper)
2.5%
—
—
—
__
—
—
30%
30%
30%
30%
45%
30%
30%
30%
30%
30%
30%
45%
15%
30%
30%
30%
45%
45%
30%
30%
30%
30%
30%
30%
30%
30%
30%
—
30%
30%
30%

Knot
12.0
—
—
—
_
—
—
0.67
0.67
0.67
0.67
2.2
0.67
0.67
0.67
0.67
1.7
1.7
4.4
2.7
0.33
0.17
0.17
0.22
0.89
0.20
0.20
0.20
0.20
0.20
0.20
0.20
10.0
10.0
—
0.33
0.10
0.01
* Contract-required detection limit in reporting units and parts per million, respectively.
b Within-batch precision by standard deviation below the knot and by percent relative standard deviation above the knot.
c For FIA only, for titrations, the value is 0.0075.
d Units are meq for this parameter;  for organic soils, value is 0.025 meq (1.25 meq/100g in reporting units).

-------
                                                                          Section 5
                                                                          Revision 1
                                                                          Date:  4/89
                                                                          Page 13 of 17
a given soil sample  does not represent the
specific watershed from which it was collect-
ed; rather, it contributes to a  set of samples
which collectively represent a specific sampling
class for all watersheds within the sampling
region.  The sampling  crew  leader  selects
a sampling site  representing  the designated
sampling class and vegetation class within the
designated watershed according to the sam-
pling  protocols.    Both the  qualitative  and
quantitative data collected are intended to be
representative of soils in the region.

5.3.1.3  Completeness--

     The sampling completeness objective can
be met by ensuring  that 100 percent  of the
designated pedons and their component hori-
zons are sampled, with the exception of cer-
tain undecomposed organic horizons, intermit-
tent  horizons,  or  horizons less than  three
centimeters thick. Only the soil sampling task
leader  at ERL-C  can  authorize pedons to be
excluded from sampling.

5.3.1.4  Comparability-

     Soils are sampled and characterized  in
the same general manner as in previous DDRP
surveys.  Improvements in methods and the
use  of consistent sampling  protocols  and
personnel with equivalent  experience should
provide data of equal or better quality.

5.3.2  Sample Preparation

     The goal of  sample preparation  is to
process bulk soil  samples collected by the
sampling crews and to provide homogeneous
subsamples to the analytical laboratories for
soil analysis.

5.3.2.1  Precision  and  Accuracy-

     A portion  of  the measurement  error
incurred  at  the  preparation  laboratory   is
assessed  by the inclusion  of preparation
duplicate   samples  created  during  the
homogenization/subsampling stage of sample
preparation.  The samples are used in each
batch to assess and, in some cases, control
imprecision during this stage of sample prepa-
ration. The MQOs for the preparation samples
are specified in Table 5-4.

     During sample preparation, the precision
and accuracy  of  analysis are estimated by
comparing  physical and chemical data from
the QE field samples (all  analyses),  the QC
internal duplicates  (PH MP,  MOIST P,  and
OM_LOI only), the clod "replicates (BD_CLD),
and the known volume replicates  (BD_KV).
The specific MQOs for precision and accuracy
of these samples during the preparation labor-
atory analysis  are outlined in Table 5-5.

5.3.2.2  Representativeness-

     Laboratory personnel ensure that the
integrity of the samples  is maintained during
the soil preparation activities.  Adherence to
QC procedures outlined in the PLSOP is moni-
tored by the QA staff. Homogenization of the
bulk soil samples allows representative analyti-
cal subsamples to be prepared.

5.3.2.3  Completeness-

     The preparation laboratory is expected to
complete the specified analyses and process-
ing tasks for  100  percent of the  samples
received.  Each batch of samples sent to a
contracted analytical laboratory must include
the specified configuration of routine, dupli-
cate, and QE/QC samples.

5.3.2.4  Comparability-

     The  preparation laboratory processes
bulk samples  according to  protocols docu-
mented in the PLSOP.  Strict adherence to the
protocols should result in comparability of the
MASS preparation laboratory with  the previous
DDRP preparation laboratories.

5.3.3  Laboratory Analysis

     The  analysis  phase  of  measurement
allows the most quantitative evaluation of data
quality, as outlined below.

-------
Table 5-4. Analytical Laboratory Wlthln-batch Precision Objectives for Preparation Sample*
Precision for
mineral samples

Parameter
MOIST A
SAND"
SILT
CLAY
PH H2O
PH 002M
PHJ01M
CACL
MG CL
KCL
NA CL
AL~CL
CAOAC
MG'OAC
KOAC
NAjOAC
CEC CL
CEC'OAC
AC_§ACL
CACL2
MG CL2
KCl2
NA CL2
FE~CL2
AL_CL2
FE PYP
AL PYP
FE~AO
AL~AO
SI~AO
FE~CD
ALjCD
S04 H20
SO4"PO4
SO4JO-32
C TOT
N~TOT
S TOT
Reporting
units
wt. %
H
H
H
pH units
M
"
meq/100g
M
*
N
N
meq/100g
"
«
"
meq/100g
M
II
meq/lOOg
N
II
H
H
"
Wt. %
M
•
«
H
N
"
mg S/kg
H
mg S/L
wt. %
"
N
CRDL*
units

_
_
—
_
_
—
0.003
0.005
0.002
0.003
0.007
0.003
0.005
0.002
0.003
0.14
0.14
0.25
0.005
0.0008
0.0003
0.0004
0.0005
0.0011
0.005
0.005
0.005
0.005
0.005
0.002
0.002
0.50
0.50
0.025
0.01
0.005
0.001
ppm

_
_
—
__
—
—
0.05
0.05
0.05
0.05
0.10
0.05
0.05
0.05
0.05
1.050C
1.050C
0.005"
0.50
0.05
0.05
0.05
0.10
0.10
0.50
0.50
0.50
0.50
0.50
0.50
0.50
0.025
0.025
0.025
100.0
50.0
10.0
SO
(lower)
0.3
3.0
3.0
2.0
0.10
0.10
0.10
0.02
0.02
0.02
0.02
0.20
0.02
0.02
0.02
0.02
0.25
0.25
1.0
0.05
0.005
0.005
0.005
0.01
0.05
0.03
0.03
0.03
0.03
0.03
0.03
0.03
1.5
1.5
0.10
0.05
0.015
0.002
RSO
(upper)
2.5%
__
__
—
___
_
—
15%
15%
15%
15%
22%
15%
15%
15%
15%
15%
15%
22%
8%
15%
15%
15%
22%
22%
15%
15%
15%
15%
15%
15%
15%
15%
15%
8%
15%
15%
15%

Knot
12.0
_
_
—
_
_
—
0.13
0.13
0.13
0.13
0.91
0.13
0.13
0.13
0.13
1.7
1.7
4.5
0.62
0.03
0.03
0.03
0.05
0.23
0.20
0.20
0.20
0.20
0.20
0.20
0.20
10.0
10.0
1.3
0.33
0.10
0.01
Section 5
Revision 1
Date: 4/89
Page 14 of 17
Precision for
oraanic samples"
SO
(lower)
0.3
_
_
—
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.50
0.10
0.10
0.10
0.10
0.25
0.25
1.0
0.20
0.05
0.025
0.025
0.05
0.20
0.03
0.03
0.03
0.03
0.03
0.03
0.03
1.5
1.5
—
0.05
0.015
0.002
RSO
(upper)
2.5%
_
_
_
__
_
—
15%
15%
15%
15%
22%
15%
15%
15%
15%
15%
15%
22%
8%
15%
15%
15%
22%
22%
15%
15%
15%
15%
15%
15%
15%
15%
15%
—
15%
15%
15%

Knot
12.0
_
_
—
—
_
—
0.67
0.67
0.67
0.67
2.3
0.66
0.66
0.66
0.66
1.7
1.7
4.5
2.5
0.33
0.17
0.17
0.23
0.91
0.20
0.20
0.20
0.20
0.20
0.20
0.20
10.0
10.0
—
0.33
0.10
0.01
* Contract-required detection limit in reporting units and parts per million, respectively.
b Within-batch precision by standard deviation below the knot and by percent relative standard deviation above the knot.
c For FIA only; for titrations, the value is 0.0075.
° Units are meq for this parameter; for organic soils, value is 0.025 meq (1.25 meq/100g in reporting units).

-------
Table 5-5. Preparation Laboratory Wlthln-Run Measurement Quality Objectives
                                                                            Section 5
                                                                            Revision  1
                                                                            Date:  4/89
                                                                            Page 15 of 17

Parameter
PH_MP







MOIST_P






OMJ.OI






RF_FG
RF_MG
BD_CLD
BD_KV
* The internal
Sample
type
Reporting
format
Buffer (QCCS) 0.01
Int dup"
FD
FAL(C)
FAP(B)
FAP (Bw)
FAO (0)
MS
Int dup"
FD
FAL(C)
FAP(B)
FAP (Bw)
FAO (0)
MS
Int dup"
FD
FAL(C)
FAP(B)
FAP (Bw)
FAO (0)
MS
FD
FD
Reps"
Dupsc
duplicate is a
b The replicate bulk density







0.01






0.01






pH units







wt. %






wt. %






0.1 wt. %
0.1 wt. %
0.01 g/cm3
0.01 g/cm3
Expected
range
3.90-4.10
2.50-7.50
2.50-7.50
4.80-6.00
4.40-5.40
4.70-5.70
3.70-4.50
4.10-5.00
0.50-6.00
0.50-6.00
0.00-2.50
1.00-4.00
1.00-4.00
4.00-8.00
0.50-6.00
0.00-90.00
0.00-90.00
0.00-3.00
5.00-15.00
1.00-9.00
65.00-85.00
5.00-15.00
0.0-60.0
0.0-60.0
0.60-2.00
0.40-2.50
Acceptable
accuracy
3.95-4.05
—
_
as specified
as specified
as specified
as specified
as specified
_»
_
control limits
control limits
control limits
control limits
control limits
_
_
control limits
control limits
control limits
control limits
control limits
—
—
—
—
Acceptable
precision
_
0.15 SD
0.20 SD
—
0.15 SD
0.15 SD
0.15 SD
—
15% RSD
20% RSD
—
15% RSD
15% RSD
15% RSD
—
15% RSD
20% RSD
—
15% RSD
15% RSD
15% RSD
—
20% RSD**
20% RSD**
20% RSD **
20% RSD**
replicate subsample that is randomly selected from one soil sample per analytical run.
samples are clod samples
0 The duplicate bulk density samples are known volume
** Since these
anticipated;
duplicates or
in which one to three clods per horizon
samples in which
have been sampled.
one or two samples per horizon are sampled.
replicates are measurements of different samples within the same horizon, variability is
however, when variability is >20% RSD,
these samples are checked for possible
measurement error.
5.3.3.1  Detectability-

     The data users have determined specific
levels of instrument detection for the parame-
ters  being analyzed.   The  contract-required
detection limits (CRDLs) for these parameters
are listed in Table 5-6.  The low concentration
QE samples (PAL and LAL) are used to assess
contamination issues  and  to  calculate  the
instrument and system detection limits for a
specific parameter.
5.3.3.2  Precision and Accuracy-

     The MQOs for precision of the physical
and chemical  analyses of soil samples are
presented in Table 5-6.  Accuracy is assessed
by comparing the analytical data to the audit
window criteria defined  for the laboratory audit
samples (see Section 7.1.3).

-------
Table 5-6. Analytical Laboratory Wlthln-Batch Precision Objectives for Analytical


Parameter
MOIST A
SAND ~
SILT
CLAY
PH H20
PH~002M
PhfOlM
CA CL
MG CL
K CL
NACL
AL'CL
CA OAC
MG~OAC
K OAC
NA_OAC
CEC CL
CEC~OAC
AC_BACL
CA CL2
MG CL2
K CL2
NA CL2
FE~CL2
AL~CL2
FE PYP
AL PYP
FE AO
AL~AO
SI~AO
FE~CD
ALJJD
S04 H2O
S04~PO4
SO4JO-32
C TOT
N~TOT
S~TOT

Reporting
units
wt. %
M
H
H
pH units
M
H
meq/100g
H
H
H
H
meq/100g
M
H
M
meq/100g
«
H
meq/100g
•
N
11
H
N
wt. %
"
"
H
H
H
"
mg S/kg
"
mg S/L
wt. %
H
N


CRDL"
units

_
_
—
--
—
—
0.003
0.005
0.002
0.003
0.007
0.003
0.005
0.002
0.003
0.14
0.14
0.25
0.005
0.0008
0.0003
0.0004
0.0005
0.0011
0.005
0.005
0.005
0.005
0.005
0.002
0.002
0.50
0.50
0.025
0.01
0.005
0.001
ppm

—
_
—
___
—
—
0.05
0.05
0.05
0.05
0.10
0.05
0.05
0.05
0.05
1.050C
1.050C
0.005d
0.5
0.05
0.05
0.05
0.10
0.10
0.50
0.50
0.50
0.50
0.50
0.50
0.50
0.025
0.025
0.025
100.0
50.0
10.0
Precision for
mineral samples'1
SD
(lower)
0.3
3.0
3.0
2.0
0.10
0.10
0.10
0.02
0.02
0.02
0.02
0.20
0.02
0.02
0.02
0.02
0.25
0.25
1.0
0.05
0.005
0.005
0.005
0.01
0.05
0.03
0.03
0.03
0.03
0.03
0.03
0.03
1.5
1.5
0.10
0.05
0.015
0.002
RSD
(upper)
2.5%
__
_
—
fmm
—
—
10%
10%
10%
10%
15%
10%
10%
10%
10%
10%
10%
15%
5%
10%
10%
10%
15%
15%
10%
10%
10%
10%
10%
10%
10%
10%
10%
5%
10%
10%
10%

Knot
12.0
_
_
—
_
_
—
0.20
0.20
0.20
0.20
1.3
0.20
0.20
0.20
0.20
2.5
2.5
6.7
1.0
0.05
0.05
0.05
0.07
0.33
0.30
0.30
0.30
0.30
0.30
0.30
0.30
15.0
15.0
2.0
0.50
0.15
0.02
Sample*
Section 5
Revision 1
Date: 4/89
Page 16 of 17
Precision for
orqanic samples'"
SD
(lower)
0.3
_
_
—
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.50
0.10
0.10
0.10
0.10
0.25
0.25
1.0
0.20
0.05
0.025
0.025
0.05
0.20
0.03
0.03
0.03
0.03
0.03
0.03
0.03
1.5
1.5
—
0.05
0.015
0.002
RSD
(upper)
2.5%
—
_
—
m m —
_
—
10%
10%
10%
10%
15%
10%
10%
10%
10%
10%
10%
15%
5%
10%
10%
10%
15%
15%
10%
10%
10%
10%
10%
10%
10%
10%
10%
—
10%
10%
10%

Knot
12.0
—
—
—
u
__
—
1.0
1.0
1.0
1.0
3.3
1.0
1.0
1.0
1.0
2.5
2.5
6.7
4.0
0.50
0.25
0.25
0.33
1.3
0.30
0.30
0.30
0.30
0.30
0.30
0.30
15.0
15.0
—
0.50
0.15
0.02
a Contract-required detection limit in reporting units and parts per million, respectively.
b Within-batch precision by standard deviation below the knot and by percent relative standard deviation above the knot.
c For FIA only; for titrations, the value is 0.0075.
d Units are meq for this parameter; for organic soils, value is 0.025 meq (1.25 meq/100g in reporting units).

-------
                                                                           Section 5
                                                                           Revision 1
                                                                           Date:  4/89
                                                                           Page 17 of 17
5.3.3.3  Representativeness-

     The integrity of the analytical samples is
to be maintained during soil analysis activities.
Homogenization of the samples at the prepar-
ation laboratory  in conjunction with re-homo-
genization of the  samples at the analytical
laboratory ensures that a uniform stock of
sample  is  available from which  to  select
aliquots for analysis.

5.3.3.4  Completeness--

     The completeness objective for all sam-
ples collected is  90 percent or better for all
analytical parameters. It is possible to attain
100 percent completeness if a sufficient quanti-
ty of each sample is available to complete all
analyses and reanalyses that may be request-
ed.

5.3.3.5  Comparability-

     Analytical data from the MASS are ex-
pected to be comparable to the DDRP North-
eastern region and Southern Blue  Ridge Prov-
ince (SBRP) soil surveys. Improvements in the
analytical protocols  could  result  in data of
higher  quality than  attained in the previous
surveys.

-------

-------
                                                                          Section 6
                                                                          Revision 1
                                                                          Date: 4/89
                                                                          Page 1 of 10
                                     Section  6

                    Quality Assurance Implementation
6.1   Control of Data Quality

      The  following  subsections  describe
the methods used to control the quality of
data produced  during the various  data  col-
lection phases and to ensure that the MQOs
described in Section 5 are met.

6.1.1  Field Sampling and
       Characterization

     Control of data quality in the sampling
phase requires frequent checks on the crews'
compliance with the sampling  protocols, as
described below.

6.1.1.1   Precision and Accuracy-

     All prospective field sampling personnel
are trained by ERL-C personnel at a workshop
held  prior to the initiation of sampling.   The
sampling crew leaders have the responsibility
for training personnel  that are  added to the
project after sampling has begun.  The staff is
encouraged  to  hold an  additional  hands-on
training session for all sampling crew  mem-
bers, although this session is optional.   Fur-
ther ensurance  of precision and  accuracy in
sampling  is accomplished with independent
pedon descriptions.

     A representative of the Soil Conservation
Service (SCS) state soils staff  independently
describes a  minimum of  one pedon per sam-
pling crew. The soil profile is described on the
same face of the soil pit as described by the
sampling crew. The state office representative
(SOR) makes the assessment while the crew
is describing and sampling the pedon.

     The   Regional   Coordinator/Correlator
(RCC) must  be a qualified soil  scientist with
several years experience in soil profile descrip-
tion,  mapping,  and correlation.   The  RCC
performs an  independent profile description at
least once for each sampling crew.  At least
one site in each state is monitored  with the
SOR; the remaining pedons may be monitored
independently. The RCC also ensures that the
SORs perform independent profile descriptions.

     The independent pedon descriptions are
used to assess the variability in site descrip-
tions  among  soil  scientists.  Because the
pedon  can be characterized anywhere along
the pedon  face, this information cannot  be
used to evaluate the accuracy of characteriza-
tion at a specific point, e.g., soil color at a
specific location, but it can be used  to evalu-
ate the  general  variability  of  independent
pedon characterization.

6.1.1.2 Representativeness-

     The soil  sampling information  provided
on the field data forms is used to determine
whether the pedons  sampled are within the
range of morphological characteristics that
identify the respective sampling classes.  Data
are analyzed by ERL-C staff to  determine the
population  characteristics  of the  sampling
classes.

6.1.1.3  Completeness

     Soil  sampling  protocols  specify  the
sampling of 100 percent of the designated
pedons and their corresponding horizons.   If
samples are lost, spilled, or mislabeled, it may
be possible  to return to the same  site and
resample the pedon.  If a  sampling site  is
inaccessible, the reason for excluding the site
must be formally documented by the sampling
crew and immediately reported to the ERL-C
soil sampling task  leader and QA auditor via
the SOR and RCC.

6.1.1.4  Comparability--

     Trie consistent  use of standard  NCSS
methods, specified protocols, and forms for

-------
                                                                           Section 6
                                                                           Revision 1
                                                                           Date:  4/89
                                                                           Page 2 of 10
the  sampling  phase   provides field   and
analytical data  that are comparable to data
generated from other studies which have used
these standardized methods. Specifically, the
MASS data are expected to be comparable to
data collected during the DORP Northeastern
region and SBRP soil surveys.

6.1.2  Sample Preparation

     Control of data quality during  sample
preparation  requires frequent checks of the
laboratory's ability to comply with the proto-
cols.

6.1.2.1  Precision and Accuracy-

     The  preparation  laboratory  combines
sets of routine  and QE/QC soil samples into
batches,  each  containing  approximately 40
samples.  After processing a FD sample and
its associated routine sample, two subsam-
ples are  split out of each sample and are
included in  a batch as the PD/FD and PD/
routine pairs.   Comparison of  physical and
chemical data from each pair allows evaluation
of preparation within-batch precision.   Since
the precision data for some of these samples
are evaluated before soil preparation is com-
pleted, the data may be used to control prepa-
ration laboratory uncertainty.

     As data from the physical and chemical
analyses become  available, the preparation
duplicates are evaluated in terms of the MQOs
listed previously in Table 5-4.  Reanalysis of
soil parameters at the  analytical laboratories
may be justified on the basis of data from the
preparation duplicates.  If reanalysis confirms
the original values, the  sample preparation
phase may be a suspected source of error.

     The  analyses that take   place  at the
preparation laboratory must satisfy the  preci-
sion and accuracy criteria previously outlined
in Table 5-5.  If the QE/QC objectives are not
met, the  data undergo confirmation and the
affected run of samples may be reanalyzed as
specified in the  PLSOP  (Bartling et al., 1988).

     The preparation laboratory manager  is
responsible for providing the QA manager with
bimonthly reports summarizing the progress
of sample preparation. These reports address
issues relating to the tracking of samples and
any QC discrepancies in the resulting data.

6.1.2.2   Representativeness-

     Each bulk soil sample is processed by a
preparation laboratory in order to produce a
thoroughly homogeneous sample.  Homogen-
ization is accomplished by passing the sample
through a Jones-type riffle splitter at least five
times in succession.   The  riffle splitter  is
subsequently used for subsampling homogen-
eous  analytical samples.  All samples not
being processed  are stored  at 4°C  in the
preparation laboratory.  Because the FO sam-
ples are  collected  according  to  a random
selection method, it is assumed that the  PD
samples  split  from  the  FD/routine pair (see
Section 5.2.4) are representative of the ranges
of concentration  for the MASS  routine soil
samples. This  aspect of representativeness is
assessed by  the Kolmogorov-Smirnov test
(Conover, 1980).

6.1.2.3   Completeness-

     All soil samples that satisfy the prepara-
tion  laboratory sample  receipt  criteria are
processed and analyzed as  specified in the
PLSOP.  One pair of FAP  samples and one FAL
sample  (or three  FAO samples), one pair  of
FD/routine  samples, and one  pair of  LAP
samples, one LAL sample (or three LAO sam-
ples), two pairs of  PD/routine samples, one
QCAS, and appropriate  sets of routine sam-
ples are  grouped  into approximately 40 sam-
ples per batch.

6.1.2.4    Comparability-

     By adhering to the  PLSOP, sample prep-
aration should be comparable  to  that of the
DDRP Northeastern  region  and  SBRP soil
surveys.  System audits and periodic routine
audits are  undertaken  by  appropriate  QA
representatives to ensure consistent laboratory
performance.  The MQOs for  analysis within
the preparation laboratory, as  well as MQOs
for  the PD samples,  are used to assess and

-------
                                                                            Section 6
                                                                            Revision 1
                                                                            Date:  4/89
                                                                            Page 3 of 10
control  measurement  uncertainty  affecting
comparability of the data.

6.1.3  Laboratory Analysis

      Before an analytical laboratory is awar-
ded a contract to analyze samples, the labora-
tory must demonstrate  its  ability to meet
certain requirements relating  to on-site facili-
ties, instrumentation, personnel, and the pro-
duction and quality of data. Analytical  labora-
tories respond to an invitation for  bid (IFB)
and are  sent  copies of the ALSOW,  which
contains all contractual requirements including
the methods for soil analysis. A group of pre-
award performance evaluation (PE) soil sam-
ples, consisting of characterized audit samples
used in previous DDRP surveys, is sent to the
participating laboratories for  analysis.  Each
laboratory is rated according to the pre-award
scoring evaluation sheet (see Appendix E).
Laboratories that submit the  lowest bids and
pass the PE criteria are then  observed during
a  pre-award  audit visit (see  Appendix F),
leading to a final selection of  contract  labora-
tories by EPA management.

6.1.3.1   Detectability-

     The analytical laboratories are required to
make repeated  determinations of the IDLs
before analysis begins. The IDLs serve as an
estimate of the lowest concentration of an
analyte that an instrument can reliably detect.
In addition, the laboratories must satisfy the
CRDLs outlined previously in Table 5-2 and are
required to demonstrate with control  charts
that the analytical system is under control at
all times during analysis. The data derived
from the DL-QCCS, FAL, and LAL samples are
used  in assessing  these objectives and  in
calculating IDLs and SDLs.

6.1.3.2  Precision and Accuracy-

     Upon satisfactory  completion of  the
contractual requirements  by  the  analytical
laboratories, a  data package for each batch of
samples  is submitted to the QA operations
staff for evaluation.  The data are verified and
evaluated in accordance with the precision and
accuracy MQOs for the  various QE/QC sam-
ples and with the appropriate soil chemistry
relationships described later in  this section.
Precision for each type of assessment sample
must meet the objectives outlined previously in
the MQO tables of Section 5, insofar as the
objectives relate to the confirmation/reanalysis
considerations  outlined later in  Section 6.2.
Data from the LAP/LAO and LAL samples must
fall within the accuracy windows defined by
the QA staff and data users.  Reanalysis may
be  requested  for  certain   parameters  or
batches  on the basis of imprecise or inaccu-
rate results  from the assessment samples.

6.1.3.3  Representativeness-

     Upon receipt of each analytical sample
from the preparation laboratory,  the analysts
are required to re-homogenize the soil thor-
oughly to ensure  the  representativeness of
aliquots used in the analyses. All samples not
in use are  stored at  4°C in the analytical
laboratory.

6.1.3.4  Completeness--

     The completeness objective for all sam-
ples collected  is 90 percent or better  for all
parameters. A level of 100 percent complete-
ness is possible if  a sufficient amount of all
samples  is  available to complete all routine
analyses and reanalyses.

6.1.3.5  Comparability-

     Comparability is assured by the uniform
use of procedures  documented  in the SOW
and by the use of uniform reporting units  as
specified on the data summary forms. The QA
procedures specified for the analytical labora-
tories allow  for the determination of measure-
ment uncertainty so that the results can  be
compared between  laboratories.  In addition,
the analytical methods used in the survey can
be compared to methods used  in the other
DDRP surveys.

6.1.4  On-Site  Systems Audits

     A major factor in controlling data quality
is the  independent on-site  systems  audit,
which ensures that all of the survey partici-

-------
                                                                            Section 6
                                                                            Revision 1
                                                                            Date: 4/89
                                                                            Page 4 of 10
pants are adhering to the protocols in a con-
sistent manner. The on-site field and laborato-
ry audits are described below.

6.1.4.1  Sampling Crews-

     The sampling crews are audited by three
separate individuals:  the SOR, the RCC, and
the QA field auditor.

     The SOR audits a minimum of one pedon
per sampling crew.  The SOR monitors adher-
ence to  protocol for site selection, sample
collection, and sample labeling.   Written re-
views are submitted to the soil sampling task
leader  at ERL-C within two weeks.   Major
discrepancies are reported verbally within two
working days.  The RCC monitors one site per
sampling crew  for  adherence  to National
Cooperative Soil Survey (NCSS) standards and
the MASS sampling manual (Kern et at., 1988).
During the audit the RCC identifies, discusses,
and resolves  any significant discrepancies.
The RCC and  SOR discuss  the independent
pedon  descriptions and inform  the  sampling
crew  leader during  sampling of any  major
deviations from the protocols that could affect
the quality of samples  that are collected.
Written  reports are  submitted  to the soil
sampling task leader at  ERL-C  within two
weeks and the resolution of major problems is
reported  verbally within two working days.

     The QA  field  auditor   evaluates each
sampling crew at least twice to ensure adher-
ence to the sampling protocols.  These audits
are intended to  evaluate and clarify the site
selection, profile description, and soil sampling
procedures. A detailed sampling questionnaire
is used  in the evaluation  (Kern et al.,  1988).
Written  reports are  submitted  to the soil
sampling task leader at  ERL-C  within two
weeks and major discrepancies are reported
verbally within two working  days.  The field
auditor is  responsible  for  coordinating  the
overall QA sampling program and for resolving
any major issues. The auditor ensures that all
sampling crews receive consistent instructions
and clarification of the protocols.

     The QA  auditor  conducts an  in-depth
review of all field  operations for compliance
with  the sampling protocols.  This  includes
interviewing the sampling crew members while
accompanying the crew on a sampling excur-
sion.  If  there are  any discrepancies, the QA
auditor  must  attempt  to  correct  them  by
reference to or by interpretation of the sam-
pling protocols. The soil sampling task leader
is  responsible for conveying information con-
cerning major issues  to the DDRP technical
director.

6.1.4.2  Preparation Laboratory-

     The preparation laboratory can expect a
minimum of two on-site system audits.  The
first on-site audit  is performed before initial
receipt of  samples in order to assess the
facilities, including the cold storage unit  and
the sample drying and processing areas.  The
questionnaire  in Appendix  I is used in  this
evaluation.  The  QA  auditor discusses  any
discrepancies  with the preparation laboratory
manager. All observations are summarized  in
an  audit  report that is  submitted to  the QA
manager within two weeks following the audit
visit.

     The second on-site audit is conducted
approximately one-third of the way through
sample processing. After reviewing the initial
audit report, any changes made since the first
audit are noted on the questionnaire. Also,
any additional discrepancies identified must be
corrected and brought to the attention of the
QA manager.  A summary report is written for
this and  any additional on-site visits, and  is
submitted  to  the  QA manager  within  two
weeks following the audit.

     The QA staff  also  conducts  periodic
audits to inspect the facilities and to assess
the  data  entry  and  verification activities.
Reports are submitted to the QA manager on
a regular basis.

6.1.4.3  Analytical  Laboratory-

     Each analytical laboratory can expect a
minimum of two on-site audits.  The first on-
site evaluation is performed after the laborato-
ry has successfully analyzed the PE samples.
The QA auditor conducts an in-depth review of

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all laboratory functions that are pertinent to
the analyses. The questionnaire in Appendix F
is  used to document the on-site laboratory
audit. The QA auditor brings any problems to
the attention of the laboratory manager for
corrective action. All observations are summa-
rized in an evaluation report that is submitted
to the QA manager within two weeks following
the audit visit.

     The  second on-site audit is conducted
approximately one-third  of  the way through
sample  analyses.   All  changes  that have
been implemented since  the initial audit  are
reviewed.  Data  from the  QE/QC  samples
received to date are assessed.  An evaluation
report is written for this and any subsequent
on-site audits and  is submitted  to the  QA
manager within two weeks following the audit
visit.

6.2   Data Verification

     The  intent of this subsection is to des-
cribe the various mechanisms that are used in
defining and implementing the data verification
procedures and the corrective actions that are
taken if the MQOs are not satisfied.

6.2.1 Field Sampling and
       Characterization  Data

     Verifying the quality of the soil character-
ization data entered on the  SCS-SOI-232 field
data form (see Appendix A) is a task that
requires a  large reference base of information,
which includes the field data form entry codes
and  a series of NCSS resource handbooks,
e.g., the Soil Survey Manual  (USDA/SCS, 1981).
Some entries are checked against logbooks or
analytical laboratory data and other entries are
compared  with soil taxonomic criteria. Certain
general field characteristics  may not  be possi-
ble to verify.

     The field data  forms are  double-entered
into a personal computer data file upon receipt
of the forms from the sampling crews via the
preparation laboratory manager. A computer
program designed to check  every entry on the
form verifies the field data  (see Appendix G).
The program checks  for appropriate coding
and completeness of entries.  Exception pro-
grams examine the internal consistency of the
field data and compare related field  parame-
ters, e.g., soil texture modifier  versus percent
rock fragments, or compare field and analytical
parameters, e.g., field pH versus laboratory pH.
In addition, certain entry fields on  the first
page  of the field data form  are  manually
checked  for completeness  and correctness
using  the pedon  code and site identification
information provided by ERL-C  personnel.

     The program  appends the discrepant
data with appropriate field  data verification
flags.   A form listing the discrepancies (see
Appendix G) is sent  to the  SCS state office
representative  or  the  appropriate  sampling
crew leader for evaluation. The sampling crew
checks the discrepancy form against the field
data form and logbook, corrects the questiona-
ble entry, signs  the  discrepancy form, and
returns  the form  to  EMSL-LV.   The form is
used by the QA staff to edit  the local working
copy of the raw data base.

     When all of the  field data forms  have
been properly edited, a final run of the verifica-
tion program is performed  on the field data
bases to flag any remaining  anomalies.

6.2.2 Preparation Laboratory Data
     A computer program has been developed
that allows entry and verification of prepara-
tion laboratory data from the raw data forms
shown  in Appendix B.  The  program also
tracks  soil samples through the various sam-
ple processing and analysis  activities, and
assigns verification flags to discrepant data.
A remote modem  assembly allows concurrent
assessment by the QA staff.  A summary of
the preparation laboratory  verification  proce-
dures and flags is presented in Appendix H.

     After the laboratory analysts enter raw
data on the forms, an evaluation procedure is
initiated which identifies coding discrepancies
and those data that do not satisfy the MQO
criteria previously outlined in Table 5-5. The
flags identified in Appendix H are used  to

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qualify the discrepancies. All outliers must be
confirmed or corrected  before  the  data are
assigned to the verified preparation laboratory
data base.

     The summary data form  (DDRP Form
101) is reviewed by QA staff to ensure that the
sample codes correspond to those entered on
the field data and raw data forms.  The inclu-
sion of appropriate QE/QC samples is checked
and recorded for each batch.  Analytical data
are checked for completeness and correctness.
The preparation laboratory manager is instruc-
ted to  acknowledge and correct any errors in
the data while reviewing the raw data forms,
control charts, or logbooks.  The shipping form
(Form  102)  is compared with the Form 101 to
verify the analytical laboratory destination and
the number of  samples shipped.  The data
base manager is notified by QA staff of any
changes made to the data base as a result of
these  checks.    The appropriate analytical
laboratory and the EPA Sample Management
Office  (SMO) are notified of  any changes
affecting sample analysis or data reporting.
All interactions with the laboratories, ORNL,
SMO, and ERL-C staff are recorded in a log-
book.

     Corrective  action  for  the preparation
laboratory  is accomplished primarily through
the application of a QA reanalysis template
(QART) for each analysis of  interest (see
Appendix J).  The QARTs provide an assess-
ment  checklist  of QE/QC samples  for each
analytical run.   The templates are used to
make decisions on whether to request reanaly-
sis of a particular parameter and are designed
to assess data on the basis of precision limits
and accuracy windows.

     The QARTs are  constructed as spread-
sheets, where the row entry fields specify the
evaluation criteria and the column entry fields
represent the magnitude of the measurement
uncertainty that has occurred.  The first col-
umn is used to identify major  measurement
uncertainty and the second column identifies
minor  uncertainty.  When  major uncertainty
occurs, the QA manager informs the prepara-
tion laboratory manager to check for errors in
the data for the suspect run and  parameter
before initiating reanalysis.  If the  laboratory
confirms the values, then  reanalysis may be
requested for  all samples in  the  run.   The
following types of  measurement uncertainty
are  considered major  for all  parameters
measured  at   the  preparation  laboratory
and  constitute  the  basis  for  requesting
confirmation/reanalysis:

 • Precision/accuracy -   The  pair of  FAP
    samples and the FAL sample (or the tripli-
    cate of FAO samples) are grouped to
    allow three evaluations.  The  FAPs  and
    FAOs are  evaluated  for  precision  and
    accuracy, and the FAL is  evaluated  for
    accuracy.  Major uncertainty exists if any
    two  of  these   three  evaluations  fail to
    satisfy the MQOs.
 • QCCS  -   Major uncertainty exists  if a
    QCCS is outside of control limits.
 • Cumulative minor uncertainty -  If three
    or more instances of  minor uncertainty
    occur, this is considered to be comparable
    to major uncertainty.

     The following types of measurement un-
certainty are considered minor  for all para-
meters  measured at the preparation  labora-
tory:

 • Precision/accuracy --   Minor uncertainty
    exists  if  one  of  the  three precision/
    accuracy evaluations do not satisfy the
    MQOs, or if the FDs, internal duplicate, or
    manager's  sample  do not satisfy  the
    MQOs.

6.2.3  Analytical Laboratory Data

     The analytical  data verification is a multi-
faceted, computerized approach to provide a
concise  and  consistent assessment  of the
data.  The overall  program is highlighted by
the Laboratory Entry and Verification Informa-
tion System  (LEVIS); characteristics  of the
system and related programs are described
below.

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6.2.3.1  Laboratory Entry and
         Verification Information
         System (LEVIS)--

     The LEVIS programs  are  implemented
on  personal   computers  and  facilitate the
data entry and QC sample evaluation at the
analytical laboratories as  well as the evalua-
tion of laboratory performance by the QA staff.
The system is a menu-driven product that is
designed  as  a two  phase operation, where
phase  one is an analytical laboratory system
and phase two is  a  quality assessment sys-
tem.

     Phase one  is implemented on computers
supplied by the EPA to each of the analytical
laboratories and linked to  a central EPA com-
puter located at EMSL-LV.  This phase includes
the data entry system and the two laboratory
components of the verification system:   the
QC summary reports and the soil chemistry
relationships.  Phase two is implemented only
on the  central EPA computer and incorporates
two additional  verification programs to as-
sess QE samples for accuracy and precision.
This phase first  converts the phase one  data
base files to  the phase two data base struc-
ture before evaluation programs are run. The
central EPA computer maintains data from all
of the analytical  laboratories.

      Communications  software has  been
selected that allows  the transfer of data files
from the laboratories to the central computer.
The software selected for this operation is PC
Anywhere, produced by Dynamic Microproces-
sor Associates.    The software  allows  the
central  computer  to operate as a  remote
terminal to the laboratory computer when both
are  connected by a modem. Commands typed
on  the central computer are executed on the
laboratory computer, allowing the QA staff to
review  a laboratory's data files, run programs,
and transfer data to  the central computer.

     The entire LEVIS system must be acces-
sible through the menus by selecting options
displayed on the screen.  The three laborato-
ries must  operate independently with  little
support from  the  QA  staff;  therefore,  self-
explanatory  menus  to guide  the user  are
utilized. Color menu screens are implemented
in both phase one  and two to help highlight
options and screen information.

     Several key analytical laboratory person-
nel normally participate in the training, inclu-
ding the laboratory manager, analysts,  and
data entry operators.  To aid in training and
support, a  LEVIS  User's Guide  has  been
prepared (SAIC, 1988) and a  "test" batch of
data is installed on each computer to evaluate
the verification procedures.

     LEVIS phase one facilitates the entry of
the analytical results including all raw data,
e.g., extract volume, collected during sample
analysis.  The  calculation of  the final data,
including the conversion of instrument readings
to reporting units and correction for moisture
content, is  performed by the system.   The
LEVIS  design also facilitates the output to
hard copy printouts of the data files for further
review. Hard copies are made of  the  input
data files and checked against the laboratory
data sheets by the data entry personnel.  The
laboratory manager is required to review the
hard copy outputs.

     The   analytical  laboratories  generally
operate as follows: (1) perform soil analysis;
(2) enter results into  LEVIS;  (3) review data
and correct errors,  if necessary; (4) perform
and evaluate verification checks; (5)  reanalyze
if necessary (repeat previous steps); (6) select
appropriate run for submission if reanalysis is
performed; (7) submit data to QA staff. This
process is  repeated for each parameter until
the entire batch is complete for all parameters
and ready  for  formal  submission.   The QA
staff transfers preliminary data by modem and
phase two verification programs are run by the
QA staff to evaluate the data for possible dis-
crepancies.  Formal submission data are sent
by the  laboratories on floppy disk.

6.2.3.2  Verification of Batch  Data-

     Using the LEVIS system, the preliminary
data undergo a review against the phases one
and two criteria. Instructions  are given to the
laboratory concerning the samples requiring
confirmation of the  reported values  or reruns

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of the existing extract solutions; re-extraction
normally is not performed  at  this time.  If
there is no  extract solution  remaining,  the
laboratory informs the QA manager and awaits
further instructions.  If results  change during
confirmation, the  laboratory is instructed to
re-enter the  correct  data  into  their LEVIS
system  and send EMSL-LV a new floppy and
hard copy  submission of the data. If confir-
mation fails to correct the discrepancies, then
reanalysis  of the batch is requested for the
parameter  of interest.

      Upon concluding the batch sample analy-
sis, some  data  values may still have QE/QC
outliers  or  other discrepancies.  The affected
samples can possibly be grouped into a sep-
arate reanalysis  batch.  The  samples  are
re-extracted and the results from this second
round of analysis are reviewed and, where
appropriate, edited into the data base.

6.2.3.3  Verification by Internal
         Consistency Checks (ICCs)-

     An internal consistency program is used,
apart from LEVIS,  to generate routine data
outliers  in  each batch.  Analytical data from
each parameter are correlated  against corre-
sponding data from  all other analytical para-
meters  measured in the MASS.   For each
parameter,  the parameter pair with the strong-
est linear relationship, based on the coefficient
of determination (r2), is identified.

     Correlations are not  performed on para-
meters  within the same extract or from  the
same measurement.   For example, calcium
values from the ammonium acetate extract are
not correlated with magnesium values from the
ammonium acetate extract, even though  the
resulting r2  value might have the highest corre-
lation.  The reason for this approach is that
certain  errors,  e.g.,  incomplete  extraction,
would not be identified by performing correla-
tions within the same extracting solution.

     The ICCs are performed by  using a
weighted linear regression model (SAS, 1986)
because previous  DDRP data  have exhibited
heteroscedasticity, i.e., the variances  are  not
the same for the entire population.  The weigh-
ting factor (w) used in the regression is calcu-
lated as the reciprocal of the analyte concen-
tration of the independent variable (w = 1 / x).
The weighting is not performed on logarithmi-
cally defined parameters such as soil pH.  A
correlation is  run  by plotting  values for  one
parameter on the X-axis and values for another
parameter on the Y-axis.  The X- and Y-axes of
each  parameter then  are reversed and the
regression is repeated.

     The  results from both regressions are
combined in  order  to  identify  the outliers,
which  are defined as those points  having  a
studentized residual (Belsley et al., 1980) of 3.0
or higher.   The  studentized  residual is an
appropriate  robust technique,  although  one
possible limitation of the approach is that the
outlier itself may strongly influence the regres-
sion estimates of the slope or intercept, there-
by affecting the value of  the residual.  In this
event,  an  application  of  the DFFITS statistic
(Belsley et al., 1980) can  measure the change
in the predicted value resulting from the exclu-
sion of a specific observation in the regression
analysis.  The DFFITS  statistic is used to
examine the significance of large differences in
residuals.   As with the studentized residual,
division by the estimated error normalizes the
statistic to allow comparison among points of
varying precision. As a result, controlling data
points that might unduly affect the predicted
value of the dependent variable tend to have a
high DFFITS value. The critical point used to
define  a high value is the "critical" DFFITS.

     A data  outlier is identified as any  data
point exceeding the critical values defined for
the studentized residual and the DFFITS stati-
stic.   These  points are  temporarily removed
from the set of observations being analyzed.
Using the remaining data, a second regression
is performed on the  same parameters.  Utili-
zing the regression equation,  i.e., slope  and
intercept, from the second regression and the
mean and corrected sum of squares from data
points defined as  outliers  in the  first regres-
sion, a residual test  Is performed that exam-
ines and returns certain outliers  to the set of
"good" or viable  data points.   Any outliers
failing  this test are considered "true" outliers
and undergo additional tests to assess  their

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validity.  Results are checked for accuracy in
transcription  against the values in the  data
package and, where necessary, corrections are
made.

     The purpose of these evaluations  is to
identify routine  values for each  analytical
parameter that are not consistent with the
majority  of  values observed.  These values
are checked  for errors in transcription,  data
entry,  or editing.   If  no discrepancies are
encountered,  these data values are confirmed
by the  analytical laboratory.  In the event that
more than 10 outliers occur in any one batch,
reanalysis may  be requested.   Five to  10
outliers are considered a  minor problem but
may be  used with  other  criteria  to justify
reanalysis.

6.2.3.4  Verification with Soil
         Chemistry Relationships
          (SCRs)-

     The SCRs  are  another  tool used  to
examine the internal consistency of the routine
sample data (see Appendix D). It is expected
that approximately 10 percent of the data will
not  comply  with  these relationships; these
anomalous data are examined by a staff soil
chemist who either qualifies them or assigns
appropriate flags  signifying the discrepancy
(see Appendix K).

     Data flow for the SCRs uses a separate
LEVIS  menu selection, where each program is
selected  to run independently, i.e., the menu
selection does not automatically run all the
SCRs at the same time, although that option
is  available.   The output  reports  are  then
reviewed by the laboratory personnel, and the
raw data for samples  that do  not  meet the
criteria are flagged and then reviewed in order
to  identify errors  with  sample codes,  data
entry, dilutions, parameters, or other factors.
Any discrepancies that can be corrected are
edited  into the data base, and  the QC sum-
mary checks  and  SCRs are run through the
program  again.

     If six or more outlying values from one
batch occur for any given SCR, the  QA staff
reviews all data relating to the batch to deter-
mine whether there is the possibility of sample
contamination or other systematic source of
error. If the outliers cannot be explained with
this approach, reanalysis is requested for the
parameter of interest.  If one to  six outlying
values occur, a minor discrepancy is identified
and may be justification for reanalysis if other
batch-wide discrepancies are noted.

6.2.3.5 Quality Assurance Reanalysis
         Templates  (QARTs)-

     The analytical QARTs provide an assess-
ment checklist of QE/QC samples, ICCs, and
SCRs for each batch of data.  The templates
are used to  make decisions on  whether to
request a batch-wide reanalysis of a particular
parameter from an analytical laboratory. The
QARTs are designed to assess data on the
basis of precision limits, accuracy windows,
ICCs, and SCRs (see Appendix J).

     The QARTs are constructed as spread-
sheets,  where the row entry  fields specify the
evaluation criteria and the column entry fields
represent the magnitude of the measurement
uncertainty that  has occurred.  The first col-
umn is  used to identify major measurement
uncertainty and the second  column identifies
minor uncertainty.  When major uncertainty
occurs, the QA manager informs the analytical
laboratory to check for errors in their  data for
the parameter and batch in  question prior to
initiating reanalysis.  If the laboratory confirms
the values, then reanalysis of the parameter in
question is requested for  all samples  in the
batch.   The  following  types  of measurement
uncertainty are considered major for all param-
eters and constitute the basis for requesting
confirmation/reanalysis:

 • Precision/accuracy  -  the two  pairs of
    PD/routine  samples, one  pair  of LAP
    samples, and one LAL sample are  grouped
    to  allow  four evaluations.  The  PDs are
    evaluated for precision, the  LAPs  are
    evaluated for precision and accuracy, and
    the  LAL  is evaluated for  accuracy.  Major
    uncertainty exists if any two of these four
    evaluations fail to satisfy the MQOs.

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 •  Internal consistency  checks   -   Major
    uncertainty exists if more than ten values
    from  a batch  are outlying  for  a given
    parameter.
 •  Soil  chemistry  relationships   ~   major
    uncertainty exists if six or more SCRs fail
    within a batch.
 •  Cumulative minor uncertainty -  if three
    or more instances of minor uncertainty
    occur, this is considered to be comparable
    to major uncertainty.

     The following types  of  measurement
uncertainty  are  considered  minor  for the
purposes of establishing reanalysis criteria:

  • Precision/accuracy  -   Minor uncertainty
    exists if one of the four precision/ accura-
    cy evaluations do not satisfy the MQOs, or
    if the  FDs or FAPs do not  satisfy the
    MQOs.
  • Internal consistency checks   -  Minor
    uncertainty exists if five to ten values in a
    batch are considered outlying for a given
    parameter.
  • Soil  chemistry relationships   -  Minor
    uncertainty exists if one to six values fail
    within a batch.

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                                     Section  7

               Data Quality Assessment and Reporting
                                                                          Section 7
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                                                                          Page 1 of 3
     This QA plan has defined the MQOs (see
Section 5) and described the implementation of
the QA program for the MASS (see Section 6).
This section describes the  statistical assess-
ment procedures that are applied to the data
and  the  general  assessment of the  data
quality accomplishments.   Reports  to EPA
management are also discussed.

7.1   Statistical Design

7.1.1  Assessment of Detectability

     The assessment of detection limits is
accomplished on a  parameter basis  at four
levels: (1) compliance with CRDLs; (2) calcula-
tion  of actual IDLs; (3) calculation  of esti-
mated SDLs; and (4) identification of routine
samples having concentrations below the SDL.
The results can  be grouped in  tabular form to
allow comparisons among  the values  for any
parameter of interest.

7.1.2  Assessment of Precision

     A statistical evaluation  procedure that
has been developed by the QA staff and data
users is applied  to the data in order to assess
possible uncertainty stemming from confoun-
ded  data collection  imprecision.  An additive
model is used, where an observed value of any
soil characteristic is  considered as the sum of
the "true" or accepted value and an error term.
This model assumes that data uncertainty is
directly related to the error variance (Miah and
Moore, 1988).

     In the  DDRP surveys, the error variance
is dependent upon the "true" value of the soil
characteristics of interest.  Because of the
wide range of analyte  concentrations  for the
soils, it is necessary to separate the concen-
tration range into segments of error variance
that  serve as estimates of data measurement
uncertainty.  The MASS statistical approach,
therefore, requires the entire analytical concen-
tration range to be partitioned into  several
intervals  not necessarily of equal length.  An
assumption  is made that  the error variance
within each  interval is independent of,  and
changes with, the "true" analyte concentration.

     Within  this framework, the error variance
is represented by a step function (Rudin, 1974)
where each step value is the error variance for
a specific, defined interval.  A pooled estimate
of the error  variance is obtained by taking a
weighted average of the individual step values,
using the  corresponding degrees of freedom
as the weighting characteristic.

     A fundamental difficulty is assessing the
effect of the error variances on the  routine
sample data. A measure of this effect, delta,
is estimated by averaging  the step values of
the  error  standard  deviation,  using  the
proportion of routine samples in each  interval
as the weighting characteristic (Van Remortel
et al., 1988). Since data collection is a multi-
phase process and uncertainty accumulates in
the data with each progressing phase, the
cumulative uncertainty is estimated with the
delta values  using the  QE/QC data.

7.1.3 Assessment of Accuracy

     The accuracy windows for the laboratory
audit samples are based on previous interlab-
oratory analyses  of the same sample material
by the same protocols. The  objective of  set-
ting windows is to specify  a range of accept-
able single  values  based on  a mean  and
standard deviation computed from a number of
previously observed values.   The  prediction
intervals used for the  accuracy windows are
generally  determined  by  robust estimation
using a biweight  procedure (Kadafar, 1982). If
the standard  biweight  approach  produces
windows that are too wide to accommodate
the data requirements of the DDRP data users,

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a MQO-based confidence interval around the
biweight-generated mean is used.

     The known accuracy windows for these
samples are used in deciding when a particu-
lar sample is outside of control  limits.  The
mean of a LAP/LAO pair or triplicate is used in
lieu of an individual sample.

7.1.4  Assessment of
       Representativeness

     The sampling aspect of representative-
ness is assessed by comparing the individual
site and pedon classifications with the compo-
nent sampling classes to which the soils are
assigned.  Soils that fall outside the range of
characteristics of  their  respective sampling
class would be considered non-representative.

     Representativeness of the measurement
quality samples is assessed by comparing the
concentration ranges of data from the FD and
PD samples to the overall concentration range
of the routine sample data.  This is accom-
plished  through  the  application  of  critical
values determined by the Kolmogorov-Smirnov
test (Conover, 1980) which assesses the ability
of the duplicate samples to track  the distribu-
tion of routine sample concentrations.

     Representativeness of the homogeniza-
tion and subsampling procedures at the prepa-
ration and analytical laboratories  is assessed
using precision  estimates for the PO and AD
samples, respectively.
 7.1.5
 ness
Assessment  of  Complete-
     Sampling completeness is assessed by
comparing the actual number of pedons and
associated horizons sampled to that number
specified in the MASS design.  Completeness
of the sample preparation and analysis  is
easily calculated using data from the verified
data base, while completeness of the data
from a data user's perspective is determined
using confidence level 0,  1, and 2 data as a
percentage of the entire validated data base
(see Section 7.2).
7.1.6 Assessment of
         Comparability

     Comparability is perhaps the most diffi-
cult of the data quality attributes to assess,
primarily  because of the  many different as-
pects of comparison that are involved.  Follow-
ing completion of the MASS, a comparison is
made across the Northeastern, SBRP, and Mid-
Appalachian regions that focuses on method
differences, audit sample results, laboratory
effects, and other QA features of the surveys.
Comparison of the DDRP data bases to other
similar data bases may also be undertaken.
Summary statistics are used to collate individ-
ual values into pooled groups that enable the
data users to discern trends of interest among
the surveys.

7.2   Overview  of Validation
       Procedures

     While the verification procedures evaluate
data  at  the sample/batch level,  validation
procedures examine the plausibility of data in
the context of a  subregional set of samples.
The MASS sampling strategy generally groups
those soils having similar physical and chemi-
cal characteristics  together.  The  validation
process identifies unusual data that warrant
special  attention when used  in  statistical
analysis,  particularly in  regional  estimates
concerning   a  target  population  of soils.
Observations identified  as anomalous during
the review  of routine data at the sampling
class/horizon level or subregional level are
considered outliers in relation to the remainder
of the data.  Outliers are identified using the
Box  and  Whisker outlier  test (Velleman and
Hoaglin,  1981).  The outliers may result from
the natural variability of  soils in  the  set  of
watersheds or from anthropogenic disturban-
ces in the natural environment.  Other sources
may be derived from sampling, preparation, or
analytical measurement uncertainty.

     Although outliers may represent unusual
data  in comparison with  other data, these
values are not necessarily inaccurate in their
representation of a watershed.  The validation
process is not designed as a stringent pass or

-------
                                                                           Section 7
                                                                           Revision 1
                                                                           Date:  4/89
                                                                           Page 3 of 3
fail test, but rather as a way to identify points
having suspicious origins. All routine sample
data are subjected to a set of rigorous valida-
tion checks by ERL-C and ORNL personnel that
results in  a series of flags being appended
on  all data  not meeting   the  criteria (see
Appendix  K).   Each reviewed datum  is as-
signed a level of confidence based upon the
number and weight of the laboratory qualifiers
and the verification/validation flags assigned to
that datum.  The levels of confidence  range
from  0 to 4, where levels 3 and 4 data are
suspected to be invalid for most uses. The
data users generally consider levels 0, 1, and
2 data to be suitable for most modeling appli-
cations.

      The  verified data are  subjected  to an
investigation of parameter relationships  within
a sampling class/horizon group.

7.3  Quality Assurance  Reports
       to Management

      The QA staff  is required to produce a
series of reports, both verbal and written, to
document  the  MASS  QA activities, as  des-
cribed below.

7.3.1  Status Reporting

      Communication among the various parti-
cipants in the  MASS  is  maintained through
scheduled conference calls, electronic mail, site
visits, and meetings. These  activities provide
all  participants  with  the current  status  of
operations and allow prompt discussion and
resolution  of issues related to the research
plan, methodologies, or QA implementation.
     Task leaders for the various stages of
the MASS provide a written summary of opera-
tions to  ERL-C on a quarterly basis.  These
reports describe the kinds of data collected as
well as summarize the QA activities associated
with the  data.  The summary of QA activities
includes the following:

  • overview of QA activities
  • list of changes to the QA program
  • results of system and performance audits
  • assessment of data quality based on the
    verified data bases
  • documentation  of  unfavorable  incidents
    and corrective actions
  • distribution of updated control charts
  • results of special studies

     Reports relating to data quality assess-
ment are  also prepared by QA staff.  These
reports include interpretation  of performance
audits and replicate sample data, estimates of
measurement error, and identification  of any
major discrepancies found during the assess-
ment.    The  reports are submitted  to the
technical monitor at EMSL-LV.

7.3.2  Formal Reporting

     In addition to this QA Plan,  the DDRP
staff at EMSL-LV produces laboratory opera-
tions manuals for use in the preparation and
analysis of soil samples.  Upon completion of
the data verification activities, summary QA
reports of the sample preparation and sample
analysis data are produced and distributed to
all cooperating DDRP staff and data users.

-------

-------
                                                                           Section 8
                                                                           Revision 1
                                                                           Date:  4/89
                                                                           Page 1 of 3
                                      Section  8

                          Data Management  System
 8.1  Overview of the Data Bases     8.1.1  Field Sampling Data
      The purpose of data base management
 for the MASS  is to facilitate the collection,
 entry, review, modification, and distribution of
 all data associated with the survey (see Figure
 8-1).  Additional tasks include the data analy-
 sis for report generation, statistical analysis,
 verification, and data file security.  The MASS
 final  data base  contains  three  progressive
 versions of the data gathered: (1) the raw data
 base, (2)  the verified data  base,  and (3) the
 validated data base. A user's guide has  been
 developed to assist the data users in under-
 standing the structure, codes, and flags of the
 DDRP data bases (Turner et al., 1989).

      The raw data base is the version of data
 that is produced from the data entry operation.
 This data base  is assembled by EMSL-LV and
 sent to ORNL for storage and control of the
 official raw data base. It is comprised of data
 from  three sources: field  sampling, sample
 preparation, and  sample analysis.   Each of
 these data sources contributes to the com-
 pleted raw data base.

     The  verified data  base has the same
 structure as the raw data base but is modified
 to reflect changes resulting from data verifica-
 tion activities.  All modifications are tracked
 with an  electronic  audit trail system.  The
 verified data base is generated by EMSL-LV
 and sent to ERL-C and ORNL for processing
 and validation.

     The validated  data base consists  of a
 file  listing all verification and validation flags
 plus a single level of confidence assigned for
 each datum, as well as transposed files in
tabular format  containing  the higher quality
data and  imputed data replacing  the lower
quality data in an enhanced data set.
      The data collected during the field sam-
 pling operation are recorded on SCS-SOI-232
 field data forms by the sampling crews.   An
 initial review of each form is performed by the
 crew leader  before copies are  sent to  the
 preparation laboratory manager and to  the
 EMSL-LV QA staff, where the data are double
 entered into the NCC  IBM with SAS  screens.
 Entries are compared and reviewed for entry
 errors and the corrected data are added to the
 raw data base file. This file is archived and
 made  available to  the data  base manager.
 The verification program  is run on a  working
 copy of the raw data base in order to perform
 extensive data checks and  reviews.  As data
 anomalies are resolved with each sampling
 crew and field liaison, corrections are entered
 into the working copy in order to create the
 verified data  base.  The program is run once
 more in order to assign verification flags and
 is then submitted to the data base manager.

     The data structure for the field data
 bases consists of two files: the pedon base
 data and the pedon horizon data. The  transfer
 of field data forms  occurs simultaneously for
 both types of data, but the computer opera-
 tions are performed separately.

 8.1.2 Preparation Laboratory Data

     The data generated at the preparation
 laboratory  are entered directly into SAS files
 on  a personal computer  in  the  laboratory.
 Upon receipt of soil samples and field data
 forms, the sample  receipt  data are  entered
 and checked.  As analyses are performed in
 the  laboratory, the data  are also   entered
 into the computer  and verification  programs
 are run to check the data.  All raw and verified
data files are  transferred to the NCC  IBM for

-------
                MASS
          DDRP SOIL SURVEY

              FLOWCHART
                                                                                gc/qc
Section 8
Revision 1
Date:  4/89
Page 2 of 3
Figure 8-1. Flowchart of data management activities for the Direct/Delayed Response Prefect.

-------
                                                                            Section 8
                                                                            Revision 1
                                                                            Date: 4/89
                                                                            Page 3 of 3
storage and eventual  integration with other
MASS  data and undergo  further verification,
e.g., comparison of field-moist pH values with
air-dry pH values from the analytical laborator-
ies.  Finally, the preparation  laboratory data
are merged with the analytical laboratory data
to form the  laboratory data base.

     The  raw  data  file  for the  preparation
laboratory data on the NCC IBM consists of
.only one file containing all of the required data.
Five intermediate files  on the personal com-
puter are used to capture the laboratory opera-
tions data and sample  tracking information.

8.1.3  Analytical Laboratory Data

     Data generated at the analytical laborat-
ory are entered by laboratory personnel into
the Laboratory Entry and Verification Informa-
tion System (LEVIS) on  personal computers at
each laboratory.  The LEVIS scheme facilitates
the  entry,  edit,  and review of  intermediate
data, as well as the calculation of final data
values.  The LEVIS  program also  performs
QE/QC checks and produces summary reports.

     Phone modem access to each laboratory
personal computer is available to facilitate the
transfer of preliminary data. Preliminary data
are used only by the QA staff to evaluate the
current  status of laboratory  operations and
data entry. The laboratories deliver the official
analytical data to EMSL-LV on floppy disks in
the LEVIS data  base structure. The  QA staff
performs  additional  QE/QC and verification
checks on the personal computer and the data
are reviewed for confirmation/reanalysis  re-
quirements. The entry of data from reanalysis
follows the same procedures identified above.

      The  LEVIS  data  entry screens  are
designed to  prompt an entry field for  each
parameter  separately  and to combine the
parameters  into groups for  storage.   The
intermediate  personal  computer  data  file
structure consists of  42 files and can  be
grouped into three main data types of 14 files
each:  routine data, matrix spike  data,  and
QCCS data.  The raw data files submitted by
the laboratories  and the personal computer
verified data  files are uploaded to the  NCC
IBM to create the EMSL-LV raw data base and
verified  data base.   Additional verification
programs on the  NCC IBM are run to complete
the verification process.

8.2  Data Base Audits

     All of the DDRP data bases are subject
to independent audits by a group of reviewers
under the direction of EPA through the techni-
cal director.  The purpose of the audits  is to
ensure that all aspects of  the data  tracking
and management system are being  conducted
properly.  The audits  are performed in a man-
ner similar to those in  the National Surface
Water Survey conducted by an  independent
auditor contracted by the EPA (IS&T,  1986).

-------

-------
                                                                            References
                                                                            Revision  1
                                                                            Date: 4/89
                                                                            Page 1 of  2
                                     References
Barth, D. S., B. J. Mason, T. H. Starks, and K.
     W. Brown.  1989. Soil Sampling Quality
     Assurance  Guide.    Second  Edition.
     EPA/600/8-89/046.   U.S. Environmental
     Protection Agency, Las Vegas, Nevada.

Bartling, M. H., M.  L  Papp,  and  R. D. Van
     Remortel. 1988. Direct/Delayed Response
     Project: Preparation Laboratory Standard
     Operating  Procedures   for   the Mid-
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Belsley, D. A., E. Kuh, and R. E. Welsch. 1980.
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Chen, C. W., S. A. Gherini, J. D. Dean, R. J. M.
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     Development and Calibration of the Inte-
     grated  Lake-Watershed   Acidification
     Study Model.  In: Modeling of Total Acid
     Precipitation Impacts, J.  L. Schnoor (Ed.),
     pp.  175-203.    Butterworth   Publishers,
     Boston, Massachusetts.

Conover, W. J. 1980.  Practical Nonparametric
     Statistics, Second Edition. J. Wiley and
     Sons, New York.  493 pp.

Cosby, B. J., R.  F. Wright, G. M. Hornberger,
     and J. N. Galloway.  1984.   Model of
     Acidification of  Groundwater  in Catch-
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     Carolina State University, Raleigh, North
     Carolina.

Costle, D. M. 1979a.  EPA Quality Assurance
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Costle, D. M. 1979b. Quality Assurance Requi-
     rements for all EPA Extramural Projects
     Involving Environmental Measurements.
     Administrator's  Policy Statement, 5-30-
     79.   U.S.   Environmental   Protection
     Agency, Washington, D.C.
International Science & Technology, Inc. 1986.
     Data Base Audit: National Lake Survey,
     Phase  I - Western Lake Survey.  IS&T
     Report No. 10067.  International Science
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Kadafar, K 1982.  A Biweight Approach to the
     One Sample Problem.  Jour. Amer. Stat.
     Assoc. 77(378) :416-424.

Kern, J. S., M. L. Papp,  J. J. Lee, D. A. Lam-
     mers, and L J. Blume.  1988. Soil Sam-
     pling   Manual   for the  Direct/Delayed
     Response Project  Mid-Appalachian Soil
     Survey.   U.S.  Environmental Protection
     Agency, Corvallis, Oregon.

Lammers, D. A., J. J. Lee, and J. A. Ferwerda.
     1988.   Mapping Protocols  for  Direct/
     Delayed Response Project Soil Mapping
     Activities in the Mid-Appalachian Region.
     U.S.  Environmental  Protection Agency,
     Corvallis, Oregon.

Lee, J., R. Church, D. Lammers, L. Liegel,  M.
     Johnson,  D.   Coffey,   R. Holdren,  D.
     Stevens, R. Turner, and L. Blume. 1989.
     Watershed   Surveys  to  Support   an
     Assessment of the Regional Effects of
     Acidic  Deposition  on  Surface  Water
     Chemistry. Environmental Management
     13(1)95-108.

Messer,  J. J.,  K.  N. Eshleman, S.  M.  Stam-
     baugh,  and   P. R.  Kaufmann.  1986.
     National Surface Water Survey: National
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     EPA/600/4-86/026.   U.S. Environmental
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Miah, M. J., and J. M. Moore.  1988. Parameter
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Rudin, W.  1974. Real and Complex Analysis.
     McGraw-Hill Publishers, New York.   22
     pp.

-------
                                                                            References
                                                                            Revision 1
                                                                            Date: 4/89
                                                                            Page 2 of 2
                            References (continued)
Science Applications International Corporation.
     1988. User's Guide: Laboratory Entry and
     Verification  Information  System.   Oak
     Ridge  National Laboratory,  Oak Ridge,
     Tennessee.

SAS Institute.  1986.  SAS System for Linear
     Models.  SAS Institute, Inc., Gary, North
     Carolina.  210 pp.

Schnoor, J.  L, W. D. Palmer, Jr., and G. E.
     Glass.  1984. Modeling Impacts of Acid
     Precipitation for Northeastern Minnesota.
     In:   Modeling of Total Acid Precipitation
     Impacts, J. L Schnoor (Ed.), pp. 155-173.
     Butterworth Publishers,  Boston, Massa-
     chusetts.

Stanley, T. W., and S. S.  Verner.   1985.  The
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     Quality Assurance Program.  In:  Quality
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     ments, pp. 12-19.  ASTM STP 867. Ameri-
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     Philadelphia, Pennsylvania.

Steers, C. A.,  and B.  F. Hajek. 1979.  Deter-
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     Random Selection of Transects. Soil Sci.
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Taylor, J. K. 1987. Quality Assurance of Che-
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     Chelsea, Michigan.  328 pp.

Turner, R. S., C. C. Brandt, D. D. Schmoyer, J.
     C. Goyert, K. D. Van Hoesen, L J. Allison.
     G.  R. Holdren,  P.  W.  Shaffer,  M. G.
     Johnson, D. A. Lammers, J. J. Lee, M. R.
     Church,  L  J.  Blume, and M. L. Papp.
     1989.  Direct/Delayed Response Project
     Data Base User's Guide.  Environmental
     Sciences Division  Publication Number
     2871.  Oak Ridge National Laboratory,
     Oak Ridge, Tennessee.

U.S. Agency for International  Development.
     1987.  Keys to Soil Taxonomy. Technical
     Monograph No. 6. Soil Management
     Support   Services.    Third   Printing.
     Cornell University, Ithaca, New York.

U.S. Department of  Agriculture/Soil Conserva-
     tion Service.  1981.  Soil Survey Manual.
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     Staff.  U.S. Government Printing Office,
     Washington, D.C.

U.S. Environmental Protection Agency. 1985.
     Direct/Delayed  Response  Project  Soil
     Survey Data Quality  Objectives (Review
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     Agency, Washington, D.C.

U.S. Environmental Protection Agency. 1988.
     Statements of Work for Soil Analysis in
     the Direct/Delayed Response Project Mid-
     Appalachian Soil Survey. Attachment A
     in  Invitation  for  Bid   Solicitations
     W802498D1 and W802621D1.  U.S. Envi-
     ronmental Protection Agency, Las Vegas,
     Nevada.

U.S. Environmental Protection Agency. 1989.
     An  Overview  of  the  Direct/Delayed
     Response Project.  In: AERP Status, April
     1989.  EPA/600/M-89/005.   U.S. Environ-
     mental Protection  Agency,  Washington,
     D.C.

Van Remortel, R D., G. E.  Byers, J. E. Teberg,
     M. J. Miah, C. J. Palmer, M. L. Papp, M.
     H. Bartling, A. D. Tansey, D.  L Cassell,
     and P. W. Shaffer. 1988. Direct/Delayed
     Response  Project:  Quality  Assurance
     Report for Physical and Chemical Analy-
     ses  of Soils  from  the  Southern  Blue
     Ridge Province  of the United  States.
     EPA/600/8-88/100.    U.S. Environmental
     Protection Agency, Las Vegas, Nevada.

Velleman,   P. F., and D.  C.  Hoaglin.    1981.
     Applications, Basics, and Computing of
     Exploratory  Data Analysis.    Duxbury
     Press, North Scituate, Massachusetts.

Winefordner, J. D., and G.  L  Long.  1983. Limit
     of Detection: A Closer Look at the IUPAC
     Definition. Anal. Chem. 55(7)712-724.

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                                                             Appendix A
                                                             Revision 1
                                                             Date: 4/89
                                                             Page 1 of 14
                              Appendix  A

             SCS-SOI-232 Field Data Form and Codes


      Field data describing each sampled pedon are recorded on the SCS-SOI-232 form. This
appendix also includes a list of the specific codes to be used on the form.

-------
                                                              Appendix A
                                                              Revision 1
                                                              Date: 4/89
                                                              Page 2 of 14
US DEPARTMENT OF AGRICULTURE SOIL DESCRIPTION SCS SOID
SOIL CONSERVATION SERVICE 1 17
SOIL SERIES REPRESENTED
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
DATE
MO OAV YR
I 1 , 1 ,
SITE ID s
St COUNTY UNIT U
, 1 , , 1 , , l$
MLRA
t t 1
LATITUDE 0
DEC WIN SEC l
,1,1,1
LONGITUDE 0
DEC MIN SEC '
,,1,1,1
                                           PEOON CLASSIFICATION

                                          SG     PSC    MIN  RX  IMP O1H

                                         1  1  I  1  L  i   _  I  I  1
PRECIP



' 1
WATERTABUE

DEPTH DAYS

1 1 111

K
n


i



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c


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1 1
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                  I  I
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1 1 1 1 , 1 1 1 1 1 I
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1 1 1 1 1
                otscmetRS NAMES
              LOCATION DESCRIPTION

NOTES
WATERSHED

CLASS
1 I
ST

Olfl D1ST
1



CHEW

1 1 1
WA1ERSHEDNAME
1 1 1 I i L 1 1 1 i | 1 1 1 1 1 1 I 1 1 1 1 1 1 1 1 1 •

-------
                                    Appendix A
                                    Revision 1
                                    Date: 4/89
                                    Page 3 of 14

1
2
3
4
b
6
/
8
9
10
DEPTH
| |
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-------
Appendix A
Revision 1
Date: 4/89
Page 4 of 14
MOTTLES
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-------
                                                 Appendix A
                                                 Revision 1
                                                 Date: 4/89
                                                 Page 5 of 14
EFFER-
VES-
CENCE
C A E
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FREE FORM NOTES
LOG
WEATHER
SET 1 0
UNDERSTORY VEG.

SLIDES H PED FACE
UNDERSTORY
OVERSTORY
LANDSCAPE





-------
                                                                                       Appendix A
                                                                                       Revision 1
                                                                                       Date: 4/89
                                                                                       Page 6 of 14
SITE CODES
Slope Shape (U/A)
1
2
3
4
5
convex
plane
concave
undulating
complex
Geomorphic Component (GM)
1     interfluve
2     head slope
3     side slope
4     nose slope
Hillslope Component (HS)
1
2
3
4
5
Slope
45
90
135
180
225
270
315
0
Major
BA
BI
BO
CA
CF
CP
DF
DP
FH
GF
GU
HH
HI
KP
LP
LU
LV
MO
MV
PI
PL
PT
RV
SB
SH
TA
VM
summit
shoulder
back slope
foot slope
toe slope
Aspect (ASP)
northeast
east
southeast
south
southwest
west
northwest
north
Landform (MAJ)
Badlands
Barrier Island
Bolson
Canyon
Coalescent Fan Piedmont
Coastal Plain
Drumlin Field
Deeply Dissected Plateau
Foothills
Glaciofluvial Landform
Glaciated Upland
High Hills
Hills
Karst Plain
Lake Plain
Level or Undulating Upland
Lava Plain
Mountains
Mountain Valley
Piedmonts
Plains
Plateau
River Valley
Semibolson
Sandhills
Tableland
Volcanic Mountains
Local Landform (LOC)
AF   Alluvial Fan
AP   Alluvial Flat (plain)
BE   Beach
BF   Barrier Flat
BO   Bog
BS   Backswamp
BT   Beach Terrace
BU   Butte
CB   Carolina Bay
CO   Cove
CR   Crater
CU   Cuesta
DE   Delta
DO   Dome
DR   Drumlin
DU   Dune
EK   Esker
EM   End Moraine
ES   Escarpment
FE   Felsenmeer
FP   Flood Plain
FT   Fluvial Terrace
FJ   Fjord
GM  Ground Moraine
HO  Hogback
HS   Hillside
KA   Kama
KE   Kettle
LS   Low Sand  Ridge
LT   Lake Terrace
MA  Marsh
ME  Mesa
MO  Mountainside
MT  Marine Terrace
OP   Outwash Plain
OT   Outwash Terrace
OX   Oxbow
PE   Pediment
PL   Playa
RI   Ridge
SB   Structural Bench
SI   Sink
SL   Slough
SM  Salt Marsh
SW  Swamp
VC   Volcanic Cone
VS   Valleyside

Kind of Watertable (KD)
0     none
2     perched
3     apparent
4    ground
Land Use (LU)
A    abandonded cropland
C    cropland
E    forest land grazed
F    forest land not grazed
G    pasture land and native
     pasture
H    horticultural land
I    cropland irrigated
J    hayland
L    waste disposal land
N    barren land
O    other
P    rangeland grazed
Q    wetlands drained
R    wetlands
S    rangeland not grazed
T    tundra
U    urban and built-up land

Stoniness Class  (ST)
0    class 0
1    class 1
2    class 2
3    class 3
4    class 4
5    class 5

Hydraulic Conductivity Class
(HC)
1    very slow
2    slow
3    moderately slow
4    moderate
5    moderately rapid
6    rapid
7    very rapid

Drainage Class (DR)
1    very poorly drained
2    poorly drained
3    somewhat poorly drained
4    moderately well drained
5    well drained
6    somewhat excessively
     drained
7    excessively drained

Parent Material Weathering (W)
1    slight
2    moderate
3    strong

Bedrock Inclination (B)
1     < 5 degree inclination
2    5-30 degree inclination
3     > 30 degree inclination

-------
                                                                                          Appendix A
                                                                                          Revision 1
                                                                                          Date: 4/89
                                                                                          Page 7 of  14
Parent Material Mode of Deposition
(M)
A     alluvium
D     glacial drift
E     eolian
F     mine spoil and earth fill
G     glacial outwash
H     volcanic ash
I     lacustrine sands
J     lacustrine silts
K     lacustrine clays
L     lacustrine
M     marine
N     marine sands
0     organic
P     marine silts
Q     marine clays
R     solid rock
S     eolian-sand
T     glacial till
U     unconsolidated sediments
V     local colluvium
W    loess
X     residuum
Y     solifluctate
Z     estuarine

Parent Material Origin (ORIG)
AO    sandstone unspecified
A1    sandstone-noncalcareous
A2    arkosic-sandstone
A4    sandstone-calcareous
BO    interbedded sedimentary
      unspecified
B1    limestone-sandstone-shale
B2    limestone-sandstone
B3    limestone-shale
B4    limestone-siltstone
B5    sandstone-shale
B6    sandstone-siltstone
B7    shale-siltstone
CO    conglomerate  unspecified
C1    conglomerate-noncalcareous
C2    conglomerate-calcareous
EO    ejecta-ash unspecified
E1    acidic-ash
E2    basic-ash
E3    basaltic-ash
E4    andesitic-ash
E5    cinders
E6    pumice
E7    scoria
E8    volcanic bombs
HO    shale unspecified
H1    shale-noncalcareous
H2    shale-calcareous
H3    shale-clay
10    igneous unspecified
11     igneous-coarse (or intrusive)
12    igneous-basic  (eg., gabbro)
13    igneous-intermediate (eg.,
      diorite)
14    igneous-granite
15    igneous-fine (or extrusive)
16    igneous-basalt
17    igneous-andesite
Parent Material Origin (cont.)
18    igneous-acid (eg., rhyolite)
19    igneous-ultrabasic
KO    organic unspecified
K1    mossy material
K2    herbaceous material
K3    woody material unspecified
K4    wood fragments
K5    logs and stumps
K6    charcoal
K7    coal
LO    limestone unspecified
L1    chalk
L2    marble
L3    dolomite
L4    limestone-phosphatic
L5    limestone-arenaceous
L6    limestone-argillaceous
L7    limestone-cherty
MO    metamorphic unspecified
M1    gneiss unspecified
M2    gneiss-acidic
M3    gneiss-basic
M4    serpentine
MS    schist unspecified
M6    schist-acidic
M7    schist-basic
M8    slate
M9    quartzite
PO    pyroclastic  unspecified
P1    tuff unspecified
P2    tuff-acidic
P3    tuff-basic
P4    volcanic breccia unspecified
P5    breccia-acidic
P6    breccia-basic
P7    tuff-breccia
P8    aa
P9    pahoehoe
SO    sedimentary unspecified
S1    marl
S2    glauconite
TO    siltstone unspecified
T1    siltstone-noncalcarebus
T2    siltstone-calcareous
YO    mixed unspecifed
Y1    mixed-noncalcareous
Y2    mixed-calcareous
Y4    mixed-igneous-metamorphic &
      sedimentary
Y5    mixed-igneous & metamorphic
Y6    mixed-igneous & sedimentary
Y7    mixed-metamorphic &
      sedimentary
MS    meta-sedimentary

Bedrock fracture (BDRK)
1     < 10 cm between fractures
2     10 to 45 cm between fractures
3     45 cm to 1.0 m between
      fractures
4     1.0 to 2.0 m between fractures
5     > 2.0 m between fractures
Moisture Regime (MST RGE)
AQ   aquic
AR   aridic
PA   peraquic
PU   perudic
TO   torric
UD   udic
US   ustic
XE   xeric

Erosion Class (ER WA)
0     none
1     slight
2     moderate
3     severe

Runoff Class (RN OF)
1     none
2     ponded
3     very slow
4     slow
5     rapid
6     moderate
7     very rapid

Diagnostic Features (KND)
A     anthropic
B     cambic
C     calcic
D     durinodes
E     petrocalcic
F     fragipan
G     gypsic
H     histic
I     sombric
J     petrogypsic
K     placic
L     lithic contact
M     mollic
N     natric
O     ochric
P     plaggen
Q     albic
R     argic
S     spodic
T     argillic
U     umbric
V     sulfuric
W    paralithic contact
X     oxic
Y     salic
Z     duripan
1     kandic

Flooding and Ponding, frequency
NO   none
RA   rare
OC   occasional
FR   frequent
CO   common

-------
                                                                                      Appendix A
                                                                                      Revision 1
                                                                                      Date: 4/89
                                                                                      Page 8 of 14
HORIZON CODES
Color location (LOC)
0    not given
1    interior
2    exterior
3    crushed
4    dithionite-citrate pretreated
5    after exposure to air
6    after ignition
7    pyrophosphate extract

Texture class (CLASS)
C    clay
CE   coprogenous earth
CIND cinders
CL   clay loam
COS coarse sand
COSL coarse sandy loam
CSCL coarse sandy clay loam
DE   diatomaceous earth
FB   fibric material
FM   fragmental material
FS   fine sand
FSL  fine sandy loam
G    gravel
GYP gypsiferous earth
ICE  ice or  frozen soil
L    loam
LCOS loamy  coarse sand
LFS  loamy  fine sand
LS   loamy  sand
LVFS loamy  very fine sand
MARL marl
MPT mucky peat
MUCK muck
OPWD oxide protected weathered
      bedrock
PDOMpartially decomposed organics
PEAT peat
S    sand
SC   sandy clay
SCL sandy clay loam
SG   sand and gravel
SI   silt
SIC  silty clay
SICL silty clay loam
SIL  silt loam
SL   sandy loam
SP   sapric material
U    unkown texture
UDOMundecomposed organics
UWB unweathered bedrock
VAR variable
VFS very fine sand
VFSL very fine sandy loam
WB   weathered bedrock
Texture modifier (MOD)
BY   bouldery
BYV very bouldery
BYX extremely bouldery
CB   cobbly
CBA angular cobbly
CBV very cobbly
CBX extremely cobbly
CN   channery
CNV very channery
CNX extremely channery
FL   flaggy
FLV very flaggy
FLX extremely flaggy
GR   gravelly
GRC coarse gravelly
GRF fine gravelly
GRV very gravelly
GRX extremely gravelly
ST   stony
STV very stony
STX extremely stony

Structure grade (GRD)
0    structureless
1    weak
2    moderate
3    strong
4    very strong
5    weak and moderate
6    moderate and strong

Structure size (SZ)
CO   coarse
CV   coarse and very coarse
F    fine
FF   very fine and fine
FM   fine and medium
M    medium
MC  medium and coarse
TK   thick
TN   thin
VC   very coarse
VF   very fine
VK   very thick
VN   very thin

Structure shape (SHP)
ABK angular blocky
BK   blocky
CDY cloddy
COL columnar
CR   crumb
GR   granular
LP   lenticular
MA  massive
PL   platy
PR   prismatic
SBK subangular blocky
SGR single grain
WEG wedge
Dry consistence (DRY)
EH   extremely hard
H    hard
L    loose
S    soft
SH   slightly hard
VH   very hard

Moist consistence (MOIST)
EFI  extremely firm
FI   firm
FR   friable
L    loose
VFI  very firm
VFR very friable

Other consistence (OTHER)
B    brittle
CO   uncememented
D    deformable
I    indurated
MS   moderately smeary
R    rigid
SC   strongly cemented
SD   semi deformable
SM   smeary
VR   very rigid
VWC very weakly cemented
WC  weakly cemented
WSM weakly smeary

Stickiness (ST)
S    sticky
SO   non sticky
SS   slightly sticky
VS   very sticky

Plasticity (PL)
P    plastic
PO   non plastic
SP   slightly plastic
VP   very plastic

Cementing agent (CEM)
H    humus
I    iron
L    lime
S    silica
X    lime and silica

Mottle abundance (AB)
F    few
C    common
M   many

Mottle size (SZ)
1    fine
12   fine and medium
13   medium and coarse
2    medium
3    coarse

-------
                                                                                        Appendix A
                                                                                        Revision 1
                                                                                        Date: 4/89
                                                                                        Page 9 of 14
Mottle distinctness
D    distinct
F    faint
P    prominent

Surface features kind of coat (KND)
A    skeletans over cutans
B    black stains
C    chalcedony on opal
D    clay bridging
G    gibbsite coats
I     iron stains
K    intersecting slickensides
L    lime or carbonate coats
M    manganese or iron-
      manganese stains
0    organic coats
P    pressure  faces
Q    nonintersecting slickensides
S    skeletans (sand or silt)
T    clay films (cutans)
U    coats
X    oxide coats

Abundance of coats (AB)
F    few
C    common
M    many

Continuity of coat (CN)
C    continuous
D    discontinuous
P    patchy

Distinctness of  coat (DST)
D    distinct
F    faint
P    prominent

Location of coat (LOG)
B    between  sand grains
C    on tops of columns
F    on faces  of peds and in pores
H    on horizontal faces of peds
I     in root channels and/or pores
L    on lower  surfaces of peds or
      stones
M    on bottoms of plates
N    on nodules
P    on faces  of peds
R    on rock fragments
S    on sand and gravel
T    throughout
U    on upper  surfaces of peds or
      stones
V    on vertical faces of peds
Z    on vertical and horizontal
      faces of peds

Boundary distinctness
A    abrupt
C    clear
D    diffuse
G    gradual
Boundary topography
B    broken
I     irregular
S    smooth
W    wavy

Effervescence class (CL)
0    very slightly effervescent
1     slightly effervescent
2    strongly effervescent
3    violently effervescent

Effervescence agent (AG)
H    HCI, unspecified
I     HCI. 1 normal
O    Hydrogen peroxide, 3 to 4
      percent
P    Hydrogen peroxide,
      unspecified

Effercescence extension (EX)
C    continuous
D    discontinuous

Kind of field measurement (KND)
CL   clay
PB   Bromthymol blue
PC   Cresol red
PG   Bromcresol green
PH   hellige-truog
PL   LaMotte-Morgan
PP   Phenol red
PR   Chlorophenol red
PS   soiltest
FT   Thymol-blue
PY   pH Ydrion
SA   sand
SC   coarse and very coarse sand
SF   fine sand
SI    silt
SM   medium sand
SV   very fine sand
OB   fiber unrubbed
OR   rubbed fiber

Wetness class (WETNESS)
D    dry
M    moist
W    wet

Hydraulic conductivity class
1     very slow
2     slow
3     moderately slow
4     moderate
5     moderately rapid
6     rapid
7     very rapid
Root quantity (QT)
VF   very few
FF   very few to few
F     few
FC   few to common
C     common
CM   common to many
M     many

Root size (SZ)
1     fine 1-2mm
11     very fine and fine
12    fine and medium
13    fine to coarse
2     medium 2-5mm
23    medium and coarse
3     coarse  > 5mm
V1    very fine < 1mm

Root location (LOC)
C     in cracks
M     in mat at top of horizon
P     between peds
S     matted around stones
T     throughout

Shape of pore (SHP)
IE    filled with coarse material
IF    void between rock
      fragments
IR    interstitial
IT    interstitial and tubular
TC   continuous tubular
TD   discontinuous tubular
TE    dendritic tubular
TS    constricted tubular
TU   tubular
VS   vesicular
VT    vesicular and tubular

Quantity of pores (QT)
VF    very few
FF    very few to few
F     few
FC   few to common
C     common
CM   common to many
M     many

Size of pore (SZ)
1     fine .05-2mm
11     very fine and fine
12     fine and medium
13     fine to coarse
2     medium 2-5mm
23    medium and coarse
3     coarse >  5mm
V1     very fine < .05mm

Pore Continuity (CN)
L     low
M     moderate
H     high

-------
                                                                                       Appendix A
                                                                                       Revision 1
                                                                                       Date: 4/89
                                                                                       Page 10 of 14
Kind of concentration (KND)
A2    clay bodies
B1    barite crystals
B2    soft masses of barite
C1    calcite crystals
C2    soft masses of lime
C3    lime concretions
C4    lime nodules
01    mica flakes
D2    soft dark masses
D3    dark concretions
D4    dark nodules
E3    gibbsite concretions
E4    gibbsite nodules
F1    plinthite segregations
F2    soft masses of iron
F3    iron concretions
F4    ironstone nodules
G1    gypsum crystals
G2    masses of gypsum
G3    nests of gypsum
G4    gypsum threads
H1    halite crystals
H2    salt masses
K2    soft masses of carbonate
K3    carbonate concretions
K4    carbonate nodules
K5    carbonate threads
M1    nonmagnetic shot
M2    soft masses of iron-
      manganese
M3    iron-manganese concretions
M4    magnetic shot
S1    opal crystals
S2    soft masses of silica
S3    silica concretions
S4    durinodes
T2    worm casts
T3    insects casts
T4    worm nodules

Quantity of concentrations (QT)
VF    very few
FF    very few to few
F     few
FC    few to  common
C    common
CM   common to many
M    many

Shape of concentration (SHP)
C    cylindrical
D    dendritic
0    rounded
P    plate like
T    threads
Z    irregular
Size of concentration (SZ)
1    fine <2mm
12   fine and medium
2    medium 2-5mm
23   medium and coarse
3    coarse  > 5-20mm
34   coarse and very coarse
4    very coarse 20-76mm
45   very coarse and extremely
     coarse
5    extremely coarse > 76mm

Roundness of rock fragment (RND)
1
2
3
4
5
angular
subangular
subrounded
rounded
well rounded
Size of rock fragment (SZ)
1     pebbles
2     cobbles
3     stones
4     boulders
5     charmers
6     flagstones

Kind of rock fragment (KND)
A     sandstone
B     mixed sedimentary
E     ejecta
F     ironstone
H     shale
I     igneous rocks
K     organic fragments
L     limestone
M     metamorphic rocks
O     oxide-protected rock
P     pyroclastic rocks
R     saprolite
S     sedimentary rocks
Y     mixed lithology

-------
                                                                                  Appendix A
                                                                                  Revision 1
                                                                                  Date: 4/89
                                                                                  Page 11 of  14
CLASSIFICATION



Classification, Great Group

Alfisols
AAQAL
AAQDU
AAQFR
AAQGL
MQKA
AAQNA
AAQOC
AAQPN
AAQUM
ABOCR
ABOEU
ABOFR
ABOGL
ABONA
ABOPA
AUDAG
AUDFE
AUDFR
AUDFS
AUDGL
AUDHA
AUDKA
AUDKH
AUDNA
AUDPA
AUDRH
AUSDU
AUSHA
AUSKA
AUSKH
AUSNA
AUSPA
AUSPN
AUSRH
AXEDU
AXEFR
AXEHA
AXENA
AXEPA
AXEPN
AXERH

Aridisols

DARDU
DARHA
DARNO
OARNT
DARPA
DORCL
DORCM
DORDU
DORGY
DORPA
DORSA
Albaqualf
Duraqualf
Fragiaqualf
Glossaqualf
Kandiaqualf
Natraqualf
Ochraqualf
Plinthaqualf
Umbraqualf
Cryoboralf
Eutroboralf
Fragiboralf
Glossoboralf
Natriboralf
Paleboralf
Agrudalf
Ferrudalf
Fragiudalf
Fraglossudalf
Glossudalf
Hapludalf
Kandiudalf
Kandhapludalf
Natrudalf
Paleudalf
Rhodudalf
Ourustalf
Haplustalf
Kandiustalf
Kandhaplustalf
Natrustalf
Paleustalf
Plinthustalf
Rhodustalf
Durixeralf
Fragixeralf
Haploxeralf
Natrixeralf
Palexeralf
Plinthoxeralf
Rhodoxeralf
Durargid
Haplargid
Nadurargid
Natrargid
Paleargid
Calciorthid
Camborthid
Durorthid
Gypsiorthid
Paleorthid
Salorthid
Entisols

EAQCR
EAQFL
EAQHA
EAQHY
EAQPS
EAQSU
EAQTR
EARAR
EFLCR
EFLTO
EFLTR
EFLUD
EFLUS
EFLXE
EORCR
EORTO
EORTR
EORUD
EORUS
EORXE
EPSCR
EPSQU
EPSTO
EPSTR
EPSUD
EPSUS
EPSXE
                                                                Inceptisols
Cryaquent
Fluvaquent
Haplaquent
Hydraquent
Psammaquent
Sulfaquent
Tropaquent
Arent
Cryofluvent
Torrifluvent
Tropofluvent
Udifluvent
Ustifluvent
Xerofluvent
Cryorthent
Torriorthent
Troporthent
Udorthent
Ustorthent
Xerorthent
Cryopsamment
Quartzipsamment
Torripsamment
Tropopsamment
Udipsamment
Ustipsamment
Xeropsamment
Histosols
HFIBO
HFICR
HFILU
HFIME
HFISP
HFITR
HFOBO
HFOCR
HFOTR
HHEBO
HHECR
HHELU
HHEME
HHESI
HHESO
HHETR
HSABO
HSACR
HSAME
HSATR
Borofibrist
Cryofibrist
Luvifibrist
Medifibrist
Sphagnofibrist
Tropofibrist
Borofolist
Cryofolist
Tropofolist
Borohemist
Cryohemist
Luvihemist
Medihemist
Sulfihemist
Sulfohemist
Tropohemist
Borosaprist
Cryosaprist
Medisaprist
Troposaprist
IANCR
IANDU
IANDY
IANEU
IANHY
IANPK
IANVI
IAQAN
IAQCR
IAQFR
IAQHL
IAQHP
IAQHU
IAQPK
IAQPN
IAQSU
IAQTR
IOCCR
IOCDU
IOCDY
IOCEU
IOCFR
IOCUS
IOCXE
IPLPL
ITRDY
ITREU
ITRHU
ITRSO
ITRUS
IUMCR
IUMFR
IUMHA
IUMXE

Mollisols

MALAR
MALNA
MAQAR
MAQCA
MAQCR
MAQDU
MAQHA
MAQNA
MBOAR
MBOCA
MBOCR
MBOHA
MBONA
MBOPA
MBOVE
MRERE
MUDAR
MUDHA
MUDPA
MUDVE
MUSAR
MUSCA
MUSDU
MUSHA
MUSNA
MUSPA
Cryandept
Durandept
Dystrandept
Eutrandept
Hydrandept
Placandept
Vitrandept
Andaquept
Cryaquept
Fragiaquept
Halaquept
Haplaquept
Humaquept
Placaquept
Plinthaquept
Sulfaquept
Tropaquept
Cryochrept
Durochrept
Dystrochrept
Eutrochrept
Fragiochrept
Ustochrept
Xerochrept
Plaggept
Dystropept
Eutropept
Humitropept
Sombritropept
Ustropept
Cryumbrept
Fragiumbrept
Haplumbrept
Xerumbrept
Argialboll
Natralboll
Argiaquoll
Calciaquoll
Cryaquoll
Duraquoll
Hapfaquoll
Natraquoll
Argiboroll
Calciboroll
Cryoboroll
Haploboroll
Natriboroll
Paleboroll
Vermiboroll
Rendoll
Argiudoll
Hapludoll
Paleudoll
Vermudoll
Argiustoll
Calciustoll
Durustoll
Haplustoll
Natrustoll
Paleustoll

-------
                                                                                     Appendix A
                                                                                     Revision 1
                                                                                     Date: 4/89
                                                                                     Page 12 of 14
Mollisols (cont)
MUSVE
MXEAR
MXECA
MXEDU
MXEHA
MXENA
MXEPA

Oxisols

OAQAC
OAQEU
OAQHA
OAQPN
OPRAC
OPREU
OPRHA
OPRKA
OPRSO
OTOAC
OTOEU
OTOHA
OUDAC
OUDEU
OUDHA
OUDKA
OUDSO
OUSAC
OUSEU
OUSHA
OUDKA
OUSSO
Vermustoli
Argixeroll
Calcixeroll
Durixeroll
Haploxeroll
Natrixeroll
Palexeroll
Acraquox
Eutraquox
Haplaquox
Plinthaquox
Acroperox
Eutroperox
Haploperox
Kandiperox
Sombriperox
Acritorrox
Eutrotorrox
Haplotorrox
Acrudox
Eutrudox
Hapludox
Kandiudox
Sombriudox
Acrustox
Eutrustox
Haplustox
Kandiustox
Sombriustox
Spodosols
SAQCR
SAQDU
SAQFR
SAQHA
SAQPK
SAQSI
SAQTR
SFEFE
SHUCR
SHUFR
SHUHA
SHUPK
SHUTR
SORCR
SORFR
SORHA
SORPK
SORTR
Cryaquod
Duraquod
Fragiaquod
Haplaquod
Placaquod
Sideraquod
Tropaquod
Ferrod
Cryohumod
Fragihumod
Haplohumod
Placohumod
Tropohumod
Cryorthod
Fragiorthod
Haplorthod
Placorthod
Troporthod
Ultisols

UAQAL
UAQFR
UAQKA
UAQKH
UAQOC
UAQPA
UAQPN
UAQUM
UHUHA
UHUKA
UHUKH
UHUPN
UHUSO
UUDFR
UUDHA
UUDKA
UUDKH
UUDPA
UUDPN
UUDRH
UUSHA
UUSKA
UUSKH
UUSPA
UUSPN
UUSRH
UXEHA
UXEPA

Vertisols

VTOTO
VUDCH
VUDPE
VUSCH
VUSPE
VXECH
VXEPE
Albaquult
Fragiaquult
Kandiaquult
Kandhaplaquult
Ochraquult
Paleaquult
Plinthaquult
Umbraquult
Haplohumult
Kandihumult
Kandhaplohumult
Plinthohumult
Sombrihumult
Fragiudult
Hapludult
Kandiudult
Kandhapludult
Paleudult
Plinthudult
Rhodudult
Haplustult
Kandiustult
Kandhaplustult
Paleustult
Plinthustult
Rhodustult
Haploxerult
Palexerult
Torrert
Chrotnudert
Pelludert
Chromustert
Pellustert
Chromxerert
Pelloxerert
Classification, Subgroup

AA    Typic

AB    Abruptic
AB04  Abruptic aridic
AB08  Abruptic cryic
AB10  Abruptic haplic
AB14  Abruptic udic
AB16  Abruptic xerollic

AC    Acric
AC05  Acric Plinthic

AE    Aerie
AE03  Aerie arenic
AE05  Aerie grossarenic
AE06  Aerie humic
AE08  Aerie mollic
AE09  Aerie tropic
AE10  Aerie umbric
AL    Albaquic
AL02  Albaquultic
AL04  Albic
AL08  Albic glossic
AL10  Alfic
AL12  Alfic arenic
AL13  Alfic andeptic
AL16  Alfic lithic

AN    Andic
AN01  Andeptic
AN03  Andaquic
AN06  Andic dystric
AN08  Andic epiaquic
AN 11  Andeptic glossoboric
AN20  Andic udic
AN22  Andic ustic
AN24  Andaqueptic
AN25  Anionic
AN30  Anthropic

AQ    Aqualfic
AQ02  Aquentic
AQ04  Aquaptic
AQ06  Aquic
AQ07  Aquic anionic
AQ08  Aquic arenic
AQ14  Aquic duric
AQ16  Aquic duriorthidic
AQ18  Aquic dystric
AQ24  Aquic haplic
AQ26  Aquic lithic
AQ28  Aquic petroferric
AQ34  Aquollic
AQ36  Aquultic

AR    Arenic
AR02  Arenic aridic
AR04  Arenic plinthaquic
AR06  Arenic plinthic
AR08  Arenic rhodic
AR10  Arenic ultic
AR14  Arenic umbric
AR16  Arenic ustalfic
AR18  Arenic ustollic
AR22  Argiaquic
AR24  Argiaquic xeric
AR26  Argic
AR28  Argic lithic
AR30  Argic pachic
AR32  Argic vertic
AR34  Aridic
AR36  Aridic calcic
AR42  Aridic duric
AR52  Aridic petrocalcic

BO   Boralfic
BO02 Boralfic lithic
BO04 Boralfic udic
B006 Borollic
BOOS Borollic glossic
BO10  Borollic lithic
B012  Borollic vertic

-------
                                                                                            Appendix A
                                                                                            Revision 1
                                                                                            Date:  4/89
                                                                                            Page  13 of 14
Classification, Subgroup (cont)
CA
CA04
CA06
CA10
CA20
Calcic
Calcic pachic
Calciorthidic
Calcixerollic
Cambic
HA    Haplaquodic
HA02  Haplic
HA07  Haploxerollic
HA09  Hapludic
HA12  Hapludollic
HA16  Haplustollic
CH    Chromic
                                 HE
                                 HE02
CR
CR10
CR14
CU
CU02
CU04
DU
DU02
DUOS
DU10
DU12
DU14
DY02
DY03
DY04
DY06
EN
EN02
EN06
Cryic
Cryic lithic
Cyric pachic
Cumulic
Cumulic udic
Cumulic ultic
Durargidic
Duric
Durixerollic
Durixerollic lithic
Durorthidic
Durorthidic xeric
Dystric
Dystric entic
Dystric fluventic
Dystric lithic
Entic
Entic lithic
Entic ultic
EP     Epiaquic
EU
EU02
EU04
Eutric
Eutrochreptic
Eutropeptic
FE     Ferrudalfic

FI     Fibric
FI02   Fibric terric

FL02   Fluvaquentic
FL06   Fluventic
FL12   Fluventic umbric

FR10   Fragiaquic
FR18   Fragic

GL02  Glossaquic
GL04  Glossic
GL10   Glossic udic
GL12   Glossic ustollic
GL16   Glossoboric

GR    Grossarenic
GR01  Grossarenic entic
GR04  Grossarenic plinthic

GY    Gypsic
                                               Hemic
                                               Hemic terric
                                        HI     Histic
                                        HI02  Histic lithic
                                        HI06  Histic pergelic
                                        HU
                                        HU02
                                        HU05
                                        HU10
                                        HU15
                                        HU20
                                        Humic
                                        Humic lithic
                                        Humic pergelic
                                        Humaqueptic
                                        Humic rhodic
                                        Humic xanthic
HY    Hydric
HY02  Hydric lithic

IN     Incept ic

KA    Kandic
KA02  Kandiudalfic
KA04  Kandiustalfic

KH    Kandhaplic

LE     Leptic

LI     Limnic
LI02   Lithic
LI04   Lithic mollic
LI05   Lithic pergelic
LI03   Lithic petrocalci
LI06   Lithic ruptic-alfic
LI07   Lithic ruptic-argic
LIOS   Lithic ruptic-entic-xerollic
LI09   Lithic ruptic-entic
LI11   Lithic ruptic-xerorthentic
LI12   Lithic ultic
LI13   Lithic ruptic-ultic
LI14   Lithic umbric
LI15   Lithic ruptic-xerochreptic
LI16   Lithic ustic
LI18   Lithic ustollic
LI22   Lithic xeric
LI24   Lithic xerollic

MO    Mollic

NA06  Natric

OC    Ochreptic

OR    Orthidic
OR01  Orthic
OR02  Orthoxic

OX    Oxic
PA
PA02
PA04
PA08
PA10
PE
PE01
PE02
PE04
PE06
PE08
PE14
PE16
PE20
PK
PK10
PK12
PL
PL04
PL06
PS
PS02
QU
RE
RH
RU02
RU09
RU11
RU15
RU17
RU19
SA
SA02
SA04
SI
SO
SP
SP02
SP04
SU
TE
TH04
TH06
TO
TO02
TO04
T006
TO10
Pachic
Pachic udic
Pachic ultic
Paleustollic
Palexerollic
Pergelic
Pergelic ruptic-histic
Pergelic sideric
Petrocalcic
Petrocalcic ustalfic
Petrocalcic ustollic
Petrocalcic xerollic
Petroferric
Petrogypsic
Placic
Plaggeptic
Plaggic
Plinthaquic
Plinthic
Plinthudic
Psammaquentic
Psammentic
Quartzipsammentic
Rendollic
Rhodic
Ruptic-alfic
Ruptic-lithic
Ruptic-lithic-entic
Ruptic-lithic-xerochreptic
Ruptic-ultic
Ruptic-vertic
Salorthidic
Sapric
Sapric terric
Sideric
Sombric
Sphagnic
Sphagnic terric
Spodic
Suflic
Terric
Thapto-histic
Thapto-histic tropic
Torre rt ic
Torrifluventic
Torriorthentic
Torripsammentic
Torroxic

-------
            Appendix A
            Revision 1
            Date: 4/89
            Page 14 of 14
Classification, Subgroup (cont)

TR Tropaquodic
TR04 Tropic

UD Udertic
UD01 Udalfic
UD02 Udic
UD03 Udollic
UD05 Udorthentic

UL Ultic

UM Umbreptic
UM02 Umbric

US Ustalfic
US02 Ustertic
US04 Ustic
US06 Ustochreptic
USOS Ustollic
US12 Ustoxic

VE Vermic
VE02 Vertic

XA Xanthic

XE Xeralfic
XE02 Xerertic
XE04 Xeric
XE08 Xerollic


Classification, Particle Size Class

003 cindery
004 cindery over sandy or sandy-
skeletal
005 ashy
006 cindery over loamy
007 ashy over cindery
008 ashy over loamy
009 ashy-skeletal
010 medial
011 medial-skeletal
012 medial over cindery
013 ashy over loamy-skeletal
014 medial over clayey
015 cindery over medial-skeletal
016 medial over fragmental
017 cindery over medial
018 medial over loamy
019 ashy over medial
020 medial over loamy-skeletal
022 medial over sandy or sandy-
skeletal
024 medial over thixotropic
026 thixotropic
027 thixotropic-skeletal
028 thixotropic over fragmental
030 thixotropic over sandy or
sandy-skeletal
032 thixotropic over loamy-skeletal
034 thixotropic over loamy
036
044
046
050
051

052
054
055

056
058
062
063
064
066
068
072

080
082
084

086
088
092

094
096
097
098
100

102
106
108
110

112
114
116
118

120
122
124
126
134

fragmental
sandy-skeletal
sandy-skeletal over loamy
loamy- skeletal
loamy-skeletal over
fragmental
loamy-skeletal over sandy
loamy-skeletal over clayey
loamy-skeletal or clayey-
skeletal
clayey-skeletal
clayey-skeletal over sandy
sandy
sandy or sandy-skeletal
sandy over loamy
sandy over clayey
loamy
loamy over sandy or sandy-
skeletal
coarse-loamy
coarse-loamy over fragmental
coarse-loamy over sandy or
sandy-skeletal
coarse-loamy over clayey
coarse-silty
coarse-silty over sandy or
sandy-skeletal
coarse-silty over clayey
fine-loamy
fine-loamy over cindery
fine-loamy over fragmental
fine-loamy over sandy or
sandy-skeletal
fine-loamy over clayey
fine-silty
fine-silty over fragmental
fine-silty over sandy or sandy-
skeletal
fine-silty over clayey
clayey
clayey over fragmental
clayey over sandy or sandy-
skeletal
clayey over loamy-skeletal
clayey over fine-silty
clayey over loamy
fine
very fine

Classification, Mineralogy Class

03
05
08
09
10
» 12
14
16
18
20
22
24



Allitic
carbonatic
coprogenous
chloritic
diatomaceous
ferrihumic
ferritic
ferruginous
gibbsitic
glauconitic
gypsic
halloysitic


26    illitic
27    illitic (calcareous)
28    kaolinitic
30    marly
32    micaceous
34    mixed
35    mixed (calcareous)
37    montmorillonitic
38    montmorillonitic
      (calcareous)
40    oxidic
44    serpentinitic
46    siliceous
47    siliceous (calcareous)
48    sesquic
50    vermiculitic

Classification, Reaction Class
04
06
08
10
12
14
acid
allic
dysic
euic
nonacid
noncalcareous
Classification, Temperature
Regime

04    frigid
06    hyperthermic
08    isofrigid
10    isohyperthermic
12    isomesic
14    isothermic
16    mesic
18    thermic

Classification, Other Class

04    coated
05    cracked
06    level
08    micro
12    ortstein
14    shallow
15    shallow & uncoated
16    sloping
17    shallow & coated
20    uncoated

-------
                                                                    Appendix B
                                                                    Revision 1
                                                                    Date: 4/89
                                                                    Page 1 of 11
                                Appendix B

                 Preparation Laboratory Data Forms


      Raw and calculated data from samples undergoing analysis at the  MASS preparation
laboratory are recorded on the data forms presented in this appendix.  Examples of the sample
labels are also  provided.  The information on the raw data  forms is  entered  into a  personal
computer and undergoes data verification.

-------
                                                                       Appendix B
                                                                       Revision 1
                                                                       Date:  4/89
                                                                       Page 2 of 11
               DIRECT/DELAYED RESPONSE PROJECT (DDRP) SOIL SURVEY
                                     FORM 101

             Batch ID            	
             Crew ID            	
             Lab Set Sent to      	
             Date Shipped        	
Set ID
Date Sampled
Date Received
Date Prep Completed
No. of Samples

                                       Air-dry   Field    OM-        Rock         Bulk
Samp Set                             Moisture Moist   LO1     Fragments %    Dens
 No   ID     Sample Code   Site ID       %      pH      %     2-4.7    4.7-20   g/cm3

  1
  2
  3
  4
  5
  6
  7
  8
  9
 10
 11
 12
 13
 14
 15
 16
 17
 18
 19
 20
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42

-------
                                                                                Appendix B
                                                                                Revision 1
                                                                                Date:  4/89
                                                                                Page 3 of 11
                        DIRECT/DELAYED RESPONSE PROJECT  (DDRP)
                                     SHIPPING  FORM 102
                                                 DATE RECEIVED

                                                  BY DATA MGT.
Prep Lab ID
Batch ID
D D M M M Y Y
Date Received
Date Shipped 	
| Analytical
SAMPLE BO.
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
	
BULK SAMPLES
SHIPPED
1 	 1





































39
40 1
RECEIVED








































Signature of Preparation Laboratory 1
Comments :
PH < 6.5








































RETURNED TO LEMSCO
(CHECK T IF TBS)


























'













lanaqer:

FIGURE FORM

     40
           102
                 WHITE - SMO
CANARY - ANALYTICAL

 WITH COPY TO SMO
 PINK - ANALYTICAL

WITH COPY TO EMSL-LV
                                                                     GOLD - ANALYTICAL LAB

-------
                                                           Appendix B
                                                           Revision 1
                                                           Date:  4/89
                                                           Page 4 of  11
            NAOSS Ubel A
Date Sampled:


Crew ID: _

Site ID:
DD MMMY Y
Sample Code:

Horizon: „„,,...

Set ID;	
  Depth:.
cm
NADSS
Batch ID
Sample
Ub«l B
No:._

-------
SOIL SAMPLE RECEIPT FOR*
SAX CODE





















CUM
ID





















SITE
ID





















SET
ID





















DATE
SAMPLED





















DATE
SUPPED





















DATS
RECEIVED





















RECEIVED
BI





















SAMPLE CONDITION
WET/DRY (N/D) BAG SPLIT (B/S)
SIEVED/UMSIEVED (E/U)
ODDER VOLUME (DV)





















CLOD
NUMBER





















KNONN
VOLUME
CAVITT
SAMPLE
NUMBER





















COMMENTS























-------
SAMPLE ID:
  SITE ID:
   SET ID:
 BATCH ID:
 BULK SAMPLE RAW DATA
 	    PATE SAMPLED:
	             DATE REC'D:
	          PROCESS START:
	       PROCESS COMPLETE:
                                                               Appendix B
                                                               Revision 1
                                                               Date:  4/89
                                                               Page 6 of 11
SOIL TYPE:  M/0
 Initials:
                    FIELD pH:
                    Initials:
                       AIR SAMPLE  DRYING:
                   Date      % Moisture    Initials
 Date:
 2 to 4.75 ma:
       Data:
 ROCK FRAGMENT WT:
_.	g     4.75 to 20 mm:
'	           Initials:
ENTERED IN COMPUTER:   Date:
                         Initials:
COMMENTS:

-------
                                    Appendix B
                                    Revision 1
                                    Date: 4/89
                                    Page 7 of 11
pB RAW DATA
DATE    /     /
SAMPLE CODE
Init OCCS










D
QCCS










D
SAMP.
*
























PH
























SAMPLE CODE
occs










D
QCCS










Final QCCS
SAMP.
*
























pH

























-------
                                                                                        Appendix B
                                                                                        Revision 1
                                                                                        Date:  4/89
                                                                                        Page 8 of  11
                                 SOIL SAfflLX UK BRI DETERJOKATIOJ
ALL WEIGHTS REPORTED TO 0.01 GRAMS
  SAX CODE
                           TIB
                           DO.
TII
w.
                                        AIR DRI
 OVE1 DRT
(ira+son,)
                           DATE
                   ID
COKXZMTS

-------
                                                                                     Appendix B
                                                                                     Revision 1
                                                                                     Date:  4/89
                                                                                     Page 9 of  11
                                     SAXFU LOSS-OR-IGXmOl DATA
ALL WIGHTS KBPORIED  H 0.01 CXAX8
  SAX CODI
                         CROC.
                          90.
AIR
Wt.
0.  D.
 HI.
ASIKD
 W.
                                                      OATI
                                                            ID
                                                                 couant

-------
                                                          CLOD BULK DENSITY RAW DATA
                                                                                                                                                         P«9« 	/	
ALL WEIGHTS RECORDED TO 0.01 GRAMS
 SAN CODE
                    REP
                         FLD DP
•oi«t7dry
                                               LAB DP
                                                        LAB KT
                                                                 CLOD B20
                                                                            TEKP
                                                                                              CRUC
                                                                                               NO.
                                                                                                     R FRAG
                                                                                                                     FLOAT
PRO!
T/N
                                                                                                                                    ID
                                                                                                                                              COMMENTS
                                                                                                                                                                               **

-------
                                                                                        Appendix B
                                                                                        Revision 1
                                                                                        Date:  4/89
                                                                                        Page 11 of 11
                                     KMWH VOLOtt IDLX DMIITT DMA
ALL WIGHTS RBCORDCO TO 0.0  GRAMS
  SAX CODI
                   AIR m
                           00 NT
                                    R FRM
 VOL
(cc.)
                                                   DAII
                                                            ID
                                                                  conxnr*
                                                                                     PACI

-------
                                                                  Appendix C
                                                                  Revision 1
                                                                  Date:  4/89
                                                                  Page 1 of 5
                                Appendix C

   Analytical Parameters  in the Mid-Appalachian Soil Survey
      Following is a list and description of the analyses that are performed at the preparation
laboratory and the analytical laboratories during the MASS. The parameters are described by their
data variable name, which is consistent with their  presentation in the main text.

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                                                                                             Appendix C
                                                                                             Revision 1
                                                                                             Date:  4/89
                                                                                             Page 2 of 5
Appendix C.  Analytical Parameters Measured In the Mid-Appalachian Soil Survey
Parameter
                                              Description of Parameter
PH_MP*

MOIST_P*

OMJ.OI*

RF_FG*

RF_MG*

BD_CLD*

BD_KV*

MOIST_A

SAND

VCOS

COS

MS

FS

VFS

SILT

COSI

FSI

CLAY

PHJH20

PH 002M
Field-moist pH determined in a deionized water extract using a 1:1 mineral soil to solution ratio and 1:4
organic soil to solution ratio, measured with a pH meter and combination electrode.
Air-dry soil moisture measured at the preparation laboratory and expressed as a percentage on an oven-
dry weight basis; mineral soils are dried at 105°C, organic soils at 60°C.
The percent organic matter content is measured by loss on ignition of an oven-dry sample; a cutoff value
of 20 percent organic matter is used to separate mineral soils from organic soils.
The 2.00- to 4.75-mm fine gravel rock fragments are sieved from the bulk samples and the weight percent
is determined gravimetrically.
The 4.75- to 20.00-mm medium gravel rock fragments are sieved from the bulk samples and the weight
percent is determined gravimetrically.
The oven-dry soil bulk density, minus rock fragments, of replicate soil clods is determined by a gravimetric
displacement method.
The oven-dry soil bulk density, minus rock fragments, of duplicate known volume samples is determined
by a gravimetric replacement method or a gravimetric filling method.
Air-dry soil moisture measured at the analytical laboratory and expressed as a percentage on an oven-
dry weight basis; mineral soils are dried at 105°C, organic soils at 60°C.
Total sand is the portion of the sample with particle diameter  between 0.05 mm and 2.0 mm, and is
calculated as the summation of percentages for individual sand fractions: VCOS + COS + MS + FS + VFS.
Very coarse sand is the sand fraction between 1.0 mm and 2.0 mm, and is determined by sieving the sand
which has been separated from the silt and clay.
Coarse sand is the sand fraction between 0.5 mm and 1.0 mm, and is determined by  sieving the sand
which has been separated from the silt and clay.
Medium sand is the sand fraction between 0.25 mm and 0.50 mm, and is determined by sieving the sand
which has been separated from the silt and clay.
Fine sand is the sand fraction between 0.10 mm and 0.25 mm,  and is determined by  sieving the sand
which has been separated from the silt and clay.
Very fine sand is the sand fraction between 0.05 mm  and 0.10 mm, and is determined by sieving the sand
which has been separated from the silt and clay.
Total silt is the portion  of the sample  with particle diameter between 0.002 mm and  0.05 mm, and is
calculated by subtracting from 100 percent the sum of the total sand and clay.
Coarse silt is the silt fraction between  0.02 mm and 0.05 mm, and is calculated by subtracting the  fine
silt fraction from the total silt.
Fine silt is the silt fraction between 0.002 mm and 0.02 mm; it is determined by pipetting  and is calculated
by subtracting the clay fraction from the less than 0.02-mm fraction.
Total clay is the portion  of the sample with particle diameter of less than 0.002 mm;  it  is determined by
pipetting.
pH determined in a deionized water extract using a 1:1 mineral soil to solution ratio or 1:5 organic soil to
solution ratio, measured with a pH meter and combination electrode.
pH determined in a 0.002M calcium chloride extract using a 1:2 mineral soil to solution ratio or 1:10 organic
soil to solution ratio, measured with a pH meter and combination electrode.
                                                                                                  (continued)

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                                                                                             Appendix C
                                                                                             Revision 1
                                                                                             Date:  4/89
                                                                                             Page 3 of 5
Appendix C.  Continued
Parameter
Description of Parameter
PH_01M      pH determined in a 0.01M calcium chloride extract using a 1:1 mineral soil to solution ratio or 1:5 organic
             soil to solution ratio, measured with a pH meter and combination electrode.

CA_CL       Exchangeable calcium determined with an unbuffered 1M ammonium chloride solution; approximately 1:26
             mineral soil to solution ratio or 1:52 organic soil to solution ratio are used; atomic absorption spectrometry
             or inductively coupled plasma atomic emission spectrometry is specified.

MG_CL       Exchangeable magnesium determined with an unbuffered 1M ammonium chloride solution; approximately
             1:26  mineral soil to  solution ratio or 1:52 organic soil to  solution ratio are used; atomic absorption
             spectrometry or inductively coupled plasma atomic emission spectrometry is specified.

K_CL        Exchangeable potassium determined with an unbuffered 1M ammonium chloride solution; approximately
             1:26  mineral soil to  solution ratio or 1:52 organic soil to  solution ratio are used; atomic absorption
             spectrometry or flame emission photometry is specified.

NA_CL       Exchangeable sodium determined with an unbuffered 1M ammonium chloride solution; approximately 1:26
             mineral soil to solution ratio or 1:52 organic soil to solution ratio are used; atomic absorption spectrometry,
             inductively coupled plasma atomic emission spectrometry, or flame emission photometry is specified.

AL_CL       Exchangeable aluminum determined with an unbuffered 1M ammonium chloride solution; approximately 1:26
             mineral soil to solution ratio or 1:52 organic soil  to solution ratio  are used; inductively coupled plasma
             atomic emission spectrometry is  specified.

CA_OAC     Exchangeable calcium determined with 1M ammonium acetate solution buffered at pH 7.0; approximately
             1:26  mineral soil to  solution ratio or 1:52 organic soil to  solution ratio are used; atomic absorption
             spectrometry or inductively coupled plasma atomic emission spectrometry is specified.

MG_OAC     Exchangeable  magnesium  determined  with 1M ammonium  acetate solution  buffered at  pH  7.0;
             approximately 1:26 mineral soil to solution ratio or 1:52 organic soil to solution ratio are used; atomic
             absorption spectrometry or inductively coupled plasma atomic emission spectrometry is specified.

K_OAC       Exchangeable potassium determined with 1M ammonium acetate solution buffered at pH 7.0; approximately
             1:26  mineral soil to  solution ratio or 1:52 organic soil to  solution ratio are used; atomic absorption
             spectrometry or flame emission photometry is specified.

NAJDAC     Exchangeable sodium determined with 1M ammonium acetate solution buffered at pH 7.0; approximately
             1:26  mineral soil to  solution ratio or 1:52 organic soil to  solution ratio are used; atomic absorption
             spectrometry, inductively coupled plasma atomic emission spectrometry, or flame emission photometry is
             specified.

CEC_CL      Cation exchange capacity determined with an unbuffered 1M ammonium chloride solution is the effective
             CEC which occurs at approximately the field pH when combined with the  acidity component; approximately
             1:26 mineral soil to solution ratio  or 1:52 organic soil to solution ratio are used; samples are analyzed for
             ammonium content by one of three methods: automated distillation/titration; manual distillation/automated
             titration; or ammonium displacement/flow injection analysis.

CEC_OAC    Cation exchange capacity determined with 1M ammonium  acetate  solution  buffered at  pH 7.0 is the
             theoretical estimate of the maximum potential CEC for a specific soil when combined with the acidity
             component; approximately 1:26 mineral soil to solution ratio or 1:52 organic soil to solution ratio are used;
             samples are analyzed for ammonium content by one of three methods: automated distillationAitration;
             manual distillation/automated titration; or ammonium displacement/flow injection analysis.

AC_BACL     Total exchangeable acidity determined by titration in a buffered (pH 8.2) barium chloride triethanolamine
             extraction using an approximately 1:30 soil to solution ratio.

CA_CL2      Extractable calcium determined by a 0.002M calcium chloride  extraction;  a 1:2 mineral soil to solution ratio
             or 1:10 organic soil to solution ratio are used; the calcium  is used to calculate lime potential; atomic
             absorption spectrometry or inductively coupled plasma atomic emission spectrometry is specified.
                                                                                                   (continued)

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                                                                                              Appendix C
                                                                                              Revision 1
                                                                                              Date:  4/89
                                                                                              Page 4 of 5
Appendix C.  Continued
Parameter
Description of Parameter
MG_CL2     Extractable magnesium determined by a 0.002M calcium chloride extraction; a 1:2 mineral soil to solution
             ratio or 1:10 organic soil to solution ratio are used; atomic absorption spectrometry or Inductively coupled
             plasma atomic emission spectrometry is specified.

K_CL2       Extractable potassium determined by a  0.002M calcium chloride extraction; a 1:2 mineral soil to solution
             ratio or 1:10 organic soil to solution ratio are used;  atomic absorption spectrometry or flame emission
             photometry is specified.

NA CL2      Extractable sodium determined by a 0.002M calcium chloride extraction; a 1:2 mineral soil to solution ratio
             or 1:10 organic soil to solution ratio are used; atomic absorption spectrometry, inductively coupled plasma
             atomic emission spectrometry, or flame  emission photometry is specified.

FE  CL2      Extractable iron  determined by a 0.002M calcium chloride  extraction; a 1:2 mineral soil to solution ratio
             or 1:10 organic soil to solution ratio are  used; inductively coupled plasma atomic emission spectrometry
             is specified.

AL_CL2      Extractable aluminum determined by a 0.002M calcium chloride extraction;  a 1:2 mineral  soil to solution
             ratio or 1:10 organic soil to solution ratio are used;  the aluminum concentration obtained from this procedure
             is used to calculate aluminum potential;  inductively coupled  plasma atomic emission  spectrometry is
             specified.

FE_PYP      Extractable iron determined by a 0.1M sodium pyrophosphate extraction using a 1:100 soil to solution ratio;
             the  pyrophosphate extract estimates organically-bound iron; inductively coupled plasma atomic emission
             spectrometry is specified.

AL_PYP      Extractable aluminum determined by a 0.1M sodium pyrophosphate extraction using a 1:100 soil to solution
             ratio; the pyrophosphate extract estimates organically-bound aluminum; inductively coupled plasma atomic
             emission spectrometry is specified.

FE_AO       Extractable iron  determined by an ammonium oxalate-oxalic acid extraction using  a 1:100 soil to solution
             ratio; the acid oxalate extract estimates organic and amorphous iron oxides; inductively coupled plasma
             atomic emission spectrometry is specified.

AL_AO       Extractable aluminum determined by an ammonium oxalate-oxalic acid extraction using a 1:100 soil to
             solution ratio; the acid oxalate extract  estimates  organic and amorphous aluminum oxides; inductively
             coupled plasma  atomic emission spectrometry is specified.

SI_AO       Extractable silicon determined by an ammonium oxalate-oxalic acid extraction using a 1:100 soil to solution
             ratio; inductively coupled plasma atomic emission  spectrometry is specified.

FE CD       Extractable iron  determined by a  sodium citrate-sodium dithionite extraction using a 1:30 soil to solution
             ratio; the citrate dithionite extract estimates non-silicate iron; inductively coupled plasma atomic emission
             spectrometry is  specified.

AL CD       Extractable aluminum determined by a  sodium  citrate-sodium dithionite extraction using a 1:30 soil to
             solution ratio; the citrate dithionite  extract estimates non-silicate aluminum;  inductively coupled plasma
             atomic emission spectrometry is specified.

SO4 H20    Extractable sulfate determined with a double deionized water extract; this extraction approximates the
             sulfate which will readily enter the soil solution and uses a 1:40 soil to solution ratio; ion chromatography
             is specified.

SO4 PO4    Extractable sulfate determined with a  0.016M sodium phosphate (500 mg P/L) extract; this extraction
             approximates the  total amount of  adsorbed  sulfate and  uses a  1:40 soil  to  solution  ratio;  ion
             chromatography is specified.

SO4_0       Sulfate remaining in a 0 mg S/L solution following equilibration with a 1:5 mineral  soil to solution ratio or
             1:20 organic soil to solution ratio; the data are used to develop sulfate isotherms; ion chromatography is
             specified.
                                                                                                     (continued)

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                                                                                              Appendix C
                                                                                              Revision  1
                                                                                              Date:  4/89
                                                                                              Page 5 of 5
Appendix C.  Continued
Parameter                                    Description of Parameter
804 2       Sulfate remaining in a 2 mg S/L solution following equilibration with a 1:5 mineral soil to solution ratio or
             1:20 organic soil to solution ratio; the data are used to develop sulfate isotherms; ion chromatography is
             specified.

SO4 4       Sulfate remaining in a 4 mg S/L solution following equilibration with a 1:5 mineral soil to solution ratio or
             1:20 organic soil to solution ratio; the data are used to develop sulfate isotherms; ion chromatography is
             specified.

S04_8       Sulfate remaining in a 8 mg S/L solution following equilibration with a 1:5 mineral soil to solution ratio or
             1:20 organic soil to solution ratio; the data are used to develop sulfate isotherms; ion chromatography is
             specified.

S04J6      Sulfate remaining in a 16 mg S/L solution following equilibration with a  1:5 mineral soil to solution ratio
             or 1:20 organic soil to solution ratio; the data are used to develop sulfate isotherms; ion chromatography
             is specified.

S04_32      Sulfate remaining in a 32 mg S/L solution following equilibration with a  1:5 mineral soil to solution ratio
             or 1:20 organic soil to solution ratio; the data are used to develop sulfate isotherms; ion chromatography
             is specified.

C_TOT       Total carbon determined by rapid oxidation followed by infrared detection  or thermal conductivity detection
             using  an automated CHN analyzer; total carbon can be used  to characterize the soil organic matter.

N_TOT       Total nitrogen determined by rapid oxidation followed by infrared detection or thermal conductivity detection
             using  an automated CHN analyzer; total nitrogen can  be  used to characterize the soil organic matter.

S_TOT       Total sulfur determined by automated sample combustion followed by infrared detection of evolved sulfur
             dioxide.

* This parameter is measured at the preparation laboratory.

-------

-------
                                                                       Appendix D
                                                                       Revision 1
                                                                       Date: 4/89
                                                                       Page 1 of 17
                                  Appendix D

              Analytical Laboratory Verification Criteria
      The following QC criteria and data reporting forms are used by the LEVIS programs to
evaluate the results of laboratory analysis. The results are obtained using the analytical procedures
detailed in the Analytical Laboratory Statements of Work.  The raw data are entered into LEVIS,
calculations are performed, and summary reports are generated for review by the analytical
laboratories.

-------
                  CRITERIA FOR QUALITY CONTROL SUMMARY CHECKS
                     (FLAG IF THESE CRITERIA ARE NOT MET)
                                                                  Appendix D
                                                                  Revision 1
                                                                  Date: 4/89
                                                                  Page 2 of 17
Summary Page 1 - NA


Summary Page 2 - NA


summary Page 3

  Replicate Evaluation
summary Page 4

  Spike Recovery
summary Page 5

  Reagent Blank Mean
  All pH Parameters and all Particle Size
  parameters, calculated SD <= SD from the
  RED form,

  All other parameters, calculated SD
  <= SD from the RED  form  if  the mean
  of the reps, is < the KNOT from the RED
  form and calculated %RSD <= RSD from
  the RED form if the mean is >= the KNOT
  from the RED form.
  All Sulfate Isotherms,  95% <= x <= 105%

  All other parameters,  90% <= x <= 110%
   FINE  SILT  +  CLAY  parameter  - no check,
   All pH parameters,  4.5  <= Mean <= 7.5,
   AC_BACL, 1.300  <= Mean  <= 1.800 meg,
   CA_CL2, 76 <= Mean <= 84,      (+/- 5%)
   SO4_0 <= CRDL,
   SO4_2,  1.94 <= Mean <= 2
   SO4_4,  3.88 <= Mean <= 4
                                       SO4 8,  7.76 <= Mean <= 8
,06,
.12,
• 24,
(+/- 3%)
(+/- 3%)
(+/- 3%)
Summary Page 6

  QCCS - True

  QCCS - NO. Run
                                       SO4_16,15.52 <= Mean <= 16.48,  (+/-  3%)
                                       S04_32,31.36 <= Mean <= 32.64,  (+/-  2%)
                                       All other parameters, <= CRDL from
                                         the CRD Form.
   Report  True  value  from Q.C Form

Particle Size (SAND,  SILT and CLAY only),
     1  or  more,
  All other  parameters,
     (Ceiling of (# Samples in Batch/10) )+l.
                               (continued)

-------
                                                                    Appendix D
                                                                    Revision 1
                                                                    Date: 4/89
                                                                    Page 3 of 17
  QCCS -No. of Out of Range
    (Report number of QCCS
     not meeting the criteria)
  DLQCCS - True

  DLQCCS - Meas.


  Calib. Blank - No. Run

  Calib. Blank - No. of Out of Range
    (Report number  of  Calib.
     Blanks not meeting criteria)

 QA Check Sample
 All Sulfate  Isotherms,
   QCCS within +/-  5%  of  the True QCCS
   form the QC Form,
 All other parameters,
   QCCS within +/-  10% of the True QCCS
   from the QC Form.

 Report DLQCCS value from the QC Form.

 Within +/- 20% of  the True DLQCCS from
   the QC Form.

 (Ceiling of  (# samples in Batch/10))+l.

AC_BACL, 26.0 <= Calib. Blank <= 36.0 mL
 All other parameters,
   <= CRDL from the CRD Form.

 Sample Result between High/Low range.
   (range supplied  on the summary page)
summary Page 7 - NA


Summary Page 8

  All samples in a batch must meet  these Criteria or a flag is set.

  Sample Wt. Check                      Particle Size - Measured Sample Wt.
                                          10 +/- 5% or 20 +/- 5%,
                                        All other parameters  - Measured Sample
                                          Wt.  between Method Wt. +/- 5%

  Sample Vol. check                     Measured Sample Vol. = Method Vol.
s===sss===ss==:sas==ss=ss::3s^s:^^s^=s^=:^^^^^^^^^^^s:==^==^ssr:=;s^^^^™=™ss^s^a:^^^^^^:^^^ss^^^5=^:s^:s;^^~^~^=
Summary Page 9

  spike solution Check                  Each Inst.  Reading between:
                                        CA_CL2,  76  <= X <= 84,        (80 + /- 5%)
                                        SO4_0  <= CRDL,
                                        S04_2,   1.94 <= Mean <= 2.06,   (+/- 3%)
                                        S04_4,   3.88 <= Mean <= 4.12,   (+/- 3%)
                                        S04_8,   7.76 <= Mean <= 8.24,   (+/- 3%)
                                        SO4_16,15.52 <= Mean <= 16.48,  (+/- 3%)
                                        S04_32,31.36 <= Mean <= 32.64,  (+/- 2%)

Summary Page 10

  Instrument Detection Limit            <= the CRDL from the CRD Form.

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                                                                   Appendix D
                                                                   Revision 1
                                                                   Date: 4/89
                                                                   Page 4 of 17
                         SOIL CHEMISTRY RELATIONSHIPS
      Simple mathematical relationships are used to examine the soil chemistry
of data for  each  sample.   For each SCR,  it  is  expected that approximately  10
percent of the data may not  comply with these relationships.  These anomalous
data are examined by  a soil  chemist who qualifies them or assigns appropriate
flags.  The following SCRs are examined in qualifying the data:

(1)   The analytical laboratory pH values should relate as follows:

      PH_01M  <  PH___002M  <  PH_H20
            if pH dTfferences are > 0.05 units

      Gael,  solution  masks  the  effect of  soluble salts  in soils;  Ca*4  ions
      displace H4  ions from exchange sites; the H4  ion concentration in solution
      increases, resulting in the measurement of lower pH.

(2)   The cation exchange capacity parameters should relate as follows:

      CEC_CL  <  CEC_OAC
            if CEC_CL > Imeq/lOOg and PH_H20 < 7.0

      A higher  CEC  is measured  by using a  buffered  (pH 7) NH4OAc saturating
      solution to determine CEC  in an  acid soil.  With an increase  in pH,
      hydrogen  ions  are  displaced.   This  creates more  exchange  sites for
      retention of NH44.  The NH4cl saturating solution is unbuffered; therefore,
      cation  exchange takes place nearer  the  soil  pH,   resulting  in the
      measurement of lower CEC.

(3)   The exchangeable cations and CEC should relate as follows:

      CA_OAC + MG_OAC + K_OAC + NA_OAC  <  CEC_OAC
            if CEC_CL > Imeq/lOOg

      CA_CL + MG_CL + K_CL + NA_CL  <  CEC_CL
            if CEC_CL > Imeq/lOOg

      The total CEC is made up of all cations  adsorbed on the surface of the clay
      minerals and organic matter, including Ca,  Mg, K, Na, Al, and H.  Therefore
      the addition of the base cations excluding  the acid Al and H should  be less
      than the total capacity of the soil to hold cations.

(4)   The relationship between CEC and the percent clay is as follows:

      CEC_OAC/CLAY  <  50
            if CLAY > 1.0 and CEC_CL > Imeq/lOOg

      CEC_CL/CLAY  <  50
            if CLAY > 1.0 and CEC_CL > Imeq/lOOg

      Clay mineralogy is a  major  factor in predicting CEC  in soils.   The
      theoretical maximum CEC value for vermiculite clay  (which has the  highest
      CEC values) is 180 meq/lOOg and the highest clay content in soil  samples
      from previous DDRP  surveys  is 36 percent.   Because the percent clay and
      vermiculite content of the  MASS  soils  are expected to be lower than the
      highest values from previous surveys, this relationship should hold.

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                                                                  Appendix D
                                                                  Revision 1
                                                                  Date: 4/89
                                                                  Page 5 of 17


(5)   The extractable sulfates should relate as follows:

      SO4_H2O  <  SO4_SO4
            if so4_po4 > Imgs/kg soil

      The phosphate extractable solution estimates the total adsorbed  sulfate;
      water extractable solution estimates the sulfate which readily enters soil
      solution.

(6)    The relationships between the sulfate isotherms is as follows:

      SO4_ON  <  SO4_2N  <  SO4_4N  <  SO4_8N  <  SO4_16N  <  SO4_32N
            if SO4_32N >= 7.5 mg s/kg soil

      The adsorption isotherms for sulfate should be greater as more sulfate is
      added to the  soils  for potential  adsorption  onto  the anion  exchange
      complexes.

(7)   The relationships between the sulfate  isotherms is as follows:

      SO4_0  <  SO4_2  <  SO4_4  <  SO4_8 <  SO4  16  <  SO4_32
            if so4_32N <= 7.5 mg s/kg soil      ~

      The adsorption isotherms for sulfate should be greater as more sulfate is
      added to the  soils  for potential  adsorption  onto  the anion  exchange
      complexes.

(8)   The ratio of water-extractable sulfate and the  zero  sulfate isotherm is
      as follows:

      4  <  SO4 H2O/SO4_0  <  20
            if s"o4_H2o >= 2mgs/kg  and SO4_0 >= 0.1 mgS/kg

      This is based on the theoretical  relationship  between the  two different
      extraction methods and provides a check on the extraction procedures.

(9)   The relationship between the calcium chloride  extracted cations and the
      ammonium chloride exchangeable cations is as follows:

      NA_CL2  <  NA_CL * 1.10
            if NA_CL2 > 0.03meq/100g

      K_CL2  <  K_CL * 1.10
            if K_CL2 > 0.003meq/100g

      MG_CL2  <  MG_CL * 1.10
            if MG_CL2 > 0.008meq/100g

      The extraction of these three cations by NH,Cl is an exhaustive extraction
      while the extraction of the cations by  CaCl,  is  done with a much more
      dilute extraction agent and will result  in a  nearly  complete  extraction
      of the cation.   Therefore by  increasing  the  NH,Cl extracted cation by  a
      factor  of  1.10  (chosen to include  10% error during the  extraction
      procedure)  should be greater than the  CaCl, extracted  cations.

-------
                                                                   Appendix D
                                                                   Revision 1
                                                                   Date: 4/89
                                                                   Page 6 of 17


(10)   The relationships of total carbon, nitrogen, and sulfur should relate  as
      follows:

      7  <  C TOT/N_TOT  <  50
            i7 C_TOT >- 0.1% and NJTOT >- 0.03%

      40  <  C_TOT/S_TOT  <  400
            if C_TOT >» 0.1% and SJTOT >» 0.005%

      The ratios are based on common C:N and C:S relationships found in previous
      surveys and should hold for all except the lowest concentration samples.

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                                                                                        Appendix D
                                                                                        Revision 1
                                                                                        Date: 4/89
                                                                                        Page 7 of 17
QC Summary Report
 Page 1 of 10
 number of Observation*
and Submission Selection
   Batch t 	
Date Run 	/	/_
Number of Sample* in Batch _
Submission 1
Run 1
Form f
01
03
03
03
03
03
03
03
03
03
03
04
OS
06A/B
07A/B
08
09
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
Parameter
MOIST
SAND
SILT
CLAY
VCOS
COS
MS
FS
VFS
COSI
FSI
PH_H2O
PH~01M
CEC_OAC
CBC_CL
CA_OAC
1
1
-
-
-
~ \
-
1
: i :
Number of Observation* and Submission Selection
XX *
















MG OAC
K_OAC
NAJ5AC
CAjCL
MG CL
K CL
HA_CL
ALjCL
AC BACL
PH_002M
CA_CL2
MG~CL2
K_CL2
NA_CL2
FB_CL2
AL CL2



PE_PYP
ALJ?yP
FE_AO
AL_AO
SI_AO
FE CD
AL_CD
SO4 H2O
S04 P04
S04_0
SO4~2
S04~4
S04~8
S04~1C
S04~32
C TOT
H_TOT
S_TOT

XX *





XX *





1














































































XX * XX *














f











































































XX *

XX *





























































































XX *


















































 "*"  Denotes the Run I selected for submission.

-------
                                                                                     Appendix D
                                                                                     Revision 1
                                                                                     Date: 4/89
                                                                                     Page 8 of 17
QC Summary Report
 Page 2 of 10


Number of Samples in Batch __
Range Checks
   Batch * _
Date Run   /
Form *
01
03
03
03
03
03
03
03
03
03
03
04
05
06A/B
07A/B
08
09
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42

Parameter
HOIST
SAND
SILT
CLAY
vcos
COS
MS
FS
VPS
COS I
FSI
PH_H2O
PH_01M
CEC OAC
CECjCL
CA_OAC
MG_OAC
K_OAC
NA_OAC
CA_CL
MG_CL
K_CL
NA_CL
AL_CL
AC_BACL
PHJD02M
CA_CL2
MG_CL2
K_CL2
NA CL2
FE_CL2
AL_CL2
FB_PYP
AL PYP
FE_AO
AL_AO
SI_AO
FE_CD
AL_CD
SO4_H2O
S04 P04
S04~0
S04_2
SO4_4
SO4_8
SO4_16
SO4 32
C_TOT
H TOT
S_TOT

Units
wt.
wt.
wt.
wt.
wt.
wt.
wt.
wt.
wt.
wt.
wt.
pH units
pH units
meq/lOOg
meq/lOOg
meq/lOOg
meq/lOOg
meq/lOOg
meq/lOOg
meq/lOOg
meq/lOOg
meq/lOOg
meq/lOOg
meq/lOOg
meq/lOOg
pH units
meq/lOOg
meq/lOOg
meq/lOOg
meq/lOOg
meq/lOOg
meq/lOOg
wt.
wt.
wt.
wt.
wt.
wt.
wt.
mg S/kg
mg S/kg
mg S/L
mg S/L
mg S/L
mg S/L
mg S/L
mg S/L
wt. %
wt. I
wt. t

Number
of Obs.
XX



















































Minimum
Value
xxx.xxxx



















































Maximum
Value
xxx.xxxx



















































Mean
Value
xxx.xxxx


















































1

-------
                                                                                         Appendix D
                                                                                         Revision 1
                                                                                         Date: 4/89
                                                                                         Page 9 of 17
QC Summary Report
 Page 3 of 10
Replicate Evaluation
    Batch t
Date Run   /

Form I
01
03
03
03
04
05
06A/B
07A/B
08
09
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42

Parameter
MOIST
SAND
SILT
CLAY
PH_H2O
PH_01M
CEC_OAC
CEC_CL
CA_OAC
KG OAC
K_OAC
NA_OAC
CA_CL
MG_CL
K_CL
NA_CL
AL_CL
AC BACL
PH_002M
CA_CL2
MG_CL2
K_CL2
NA_CL2
FE_CL2
AL CL2
FE_PYP
AL_PYP
FE_AO
AL_AO
SI_AO
FE CD
AL_CD
SO4_H2O
SO4_P04
S04_0
S04_2
S04_4
S04_8
SO4 16
S04_32
C_TOT
N_TOT
S_TOT

1st
xxx. xxx * (S/R)











































5D or % RSD and Fl
2nd
xxx. xxx * (S/R)











































ag
3rd
xxx . xxx * (S/R)











































"*"  In column indicates a problem with  that parameter.
"S"  In column indicates the reported value is the standard deviation.
•R"  In column indicates the reported value is the % RSD.

-------
                                                                                       Appendix D
                                                                                       Revision 1
                                                                                       Date: 4/89
                                                                                       Page 10 of 17
QC Summary Report
 Page 4  of 10
Percent Spike Recovery
                               Batch * 	
                               Date Run   /
Form
t
01
02
03
04
05
06A/B
07A/B
08
09
10
11
12
13
14
15
16
17
18
19
20
21
22
\ 23
24
25
26
27
28
29
30
31
32
33
, 34
•35

36
37

38
39
Parameter
% Spike Recovery and Flag
1st | 2nd | 3rd
XXX. XX * j XXX. XX * XXX. XX *
HOIST | XXXXXXXXXXX | XXXXXXXXXX | XXXXXXXXXX
Particle Sice j XXXXXXXXXXX j XXXXXXXXXX | XXXXXXXXXX
Particle Site j XXXXXXXXXXX j XXXXXXXXXX j XXXXXXXXXX
PHJC20 1 XXXXXXXXXXX j XXXXXXXXXX j XXXXXXXXXX
PH_0 1M j XXXXXXXXXXX | XXXXXXXXXX 1 XXXXXXXXXX
CBC OAC
CBC_CL
CA_OAC
MG_OAC
K_OAC
HA_OAC
CA_CL
MG_CL
K_CL
HA_CL
AL CL
AC BACL
PHJ>02M
CA CL2
MG CL2
K_CL2
NA CL2
PB_CL2 *
AL_CL2
FE_PYP
AL_PYP
FB_AO
AL_AO
SI_AO
FB_CD
AL_CD
S04_H2O
S04 PO4
S04 0
S04 2 (1)
(2)
S04 4
S04 8 (1)
(2)
S04 16
S04_32 (1)
/ o %
40 C_TOT
41 H_TOT
42 S_TOT











XXXXXXXXXXX
XXXXXXXXXXX















XXXXXXXXXXX


xxxxxxxxxxx


xxxxxxxxxxx















xxxxxxxxxx
xxxxxxxxxx


























xxxxxxxxxx
xxxxxxxxxx















xxxxxxxxxx | xxxxxxxxxx


xxxxxxxxxx


xxxxxxxxxx


xxxxxxxxxx xxxxxxxxxx




    In column indicates a problem with that parameter.

-------
                                                                                       Appendix D
                                                                                       Revision 1
                                                                                       Date: 4/89
                                                                                       Page 11 of  17
QC Summary Report
 Page 5  of 10
Reagent Blanks
   Batch  t _
Date Run   /
Form
f
01
02
04
05
06A/B
07A/B
08
09
10
11
12
13
14
IS
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
Parameter
MOIST
FSI + CLAY
PH_H2O
PH_01M
CEC_OAC
CEC_CL
CA_OAC
MG_OAC
K_OAC
HA_OAC
CA_CL
MG_CL
K_CL
NA_CL
AL_CL
AC_BACL
PH_002M
CA_CL2
MG_CL2
K_CL2
NA_CL2
FE_CL2
AL_CL2
FE_PYP
AL_PYP
FE_AO
AL_AO
SI_AO
FE_CD
AL_CD
SO4_H2O
S04 PO4
S04 0
S04_2
SO4 4
SO4_8
S04_16
S04_32
C_TOT
H_TOT
S_TOT
Reagent Blank and Flag
Units
XXXXXXXXXXXXXX
9
pH units
pH units
mg N/L or meq
mg N/L or meq
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
meq
pH units
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg/L
mg S/L
mg S/L
mg S/L
mg S/L
mg S/L
mg S/L
mg S/L
mg S/L
wt. %
wt. %
wt. %
1st | 2nd 3rd
XXX. XXX | XXX. XXX XXX. XXX
xxxxxxxxx 1 xxxxxxxxx 1 xxxxxxxxx
1 xxxxxxxxx 1 xxxxxxxxx
j xxxxxxxxx j xxxxxxxxx
j xxxxxxxxx j xxxxxxxxx

















































xxxxxxxxx




































xxxxxxxxx
























Mean
XXX . XXX *
xxxxxxxxxxx








































   In column indicates a problem with that parameter.

-------
                                                                                        Appendix D
                                                                                        Revision 1
                                                                                        Date: 4/89
                                                                                        Page 12 of 17
QC Summary Report
 Page 6  of 10
                    QCCS,  DLQCCS, and Calibration Blank
   Batch f 	
Date Run  /
Number of  Samples in Batch 	



Form t

01
03
03
03
03
03
03
03
03
03
03
04
05
06A/B
07A/B
08
09
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42



Parameter

MOIST
SAND
SILT
CLAY
VCOS
COS
MS
FS
VFS
COS I
FSI
PH_H2O
PH 01M
CEC OAC
CEC_CL
CA_OAC
MG_OAC
K_OAC
NA_OAC
CA CL
MG_CL
K_CL
NA_CL
AL_CL
AC_BACL
PH_002M
CA_CL2
MG_CL2
K CL2
NA_CL2
FE CL2
AL_CL2
FE~PYP
AL_PYP
FE_AO
AL_AO
SI AO
FE_CD
AL_CD
SO4 H2O
SO4 PO4
SO4_0
SO4_2
S04 4
S04_8
SO4_16
SO4 32
C_TOT
N TOT
S_TOT
QCCS
True
Value
XXX . XXX

XXXXXXXXX

















































No. | No. Out
Run
x *

XXXXX

















































Range
X

XXXXXX

















































DLQCCS Calib. Blank |
	 1
True | No. |No.Out|
Value | Meas. Run Range]
XXX. XXX 1 * X * | X

| XXXXXXXXX | XXXXXXX | | XXXXX | XXXXXX |
j xxxxxxxxx 1 xxxxxxx j j xxxxx j xxxxxx
j xxxxxxxxx j xxxxxxx j 1 xxxxx 1 xxxxxx
| xxxxxxxxx j xxxxxxx 1 xxxxx xxxxxx
1 xxxxxxxxx 1 xxxxxxx 1 1 xxxxx | xxxxxx j
j xxxxxxxxx 1 xxxxxxx j | xxxxx | xxxxxx j
1 xxxxxxxxx 1 xxxxxxx 1 xxxxx j xxxxxx 1
1 xxxxxxxxx j xxxxxxx j xxxxx | xxxxxx 1
1 xxxxxxxxx 1 xxxxxxx | xxxxx | xxxxxx j
1 xxxxxxxxx | xxxxxxx j j xxxxx 1 xxxxxx |
xxxxxxxxx 1 xxxxxxx 1 j xxxxx j xxxxxx |
xxxxxxxxx 1 xxxxxxx j
xxxxxxxxx 1 xxxxxxx 1












xxxxxxxxx




































xxxxxxx
























xxxxx
xxxxx












xxxxx
















xxxxxx
xxxxxx












xxxxxx
















1 xxxxx | xxxxxx
xxxxx xxxxxx
| xxxxx 1 xxxxxx
1 xxxxx 1 xxxxxx
1 xxxxx j xxxxxx



    In column indicates a problem with that parameter.

-------
                                                                                       Appendix D
                                                                                       Revision 1
                                                                                       Date: 4/89
                                                                                       Page 13 of 17
QC Summary Report
 Page 7  of 10
O.A Check  Sample Results
   Batch  t _
Date Run   /
Form t
01
03
03
03
03
03
03
03
03
03
03
04
05
06A/B
07A/B
08
09
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
Parameter
MOIST
SAND
SILT
CLAY
VCOS
COS
MS
FS
VFS
COSI
FSI
PH_H20
PH_01M
CEC OAC
CEC CL
CA OAC
MG OAC
K_OAC
NA_OAC
CA_CL
MG_CL
K_CL
NA_CL
AL_CL
AC_BACL
PH_002M
CA CL2
MG_CL2
K CL2
NA_CL2
FE_CL2
AL_CL2
FE_PYP
AL_PYP
FE_AO
AL_AO
SI_AO
FE_CD
AL_CD
S04_H20
SO4_P04
SO4_0
S04_2
S04_4
S04_8
SO4 16
S04_32
C TOT
N TOT
SJTOT
LOW
Range Value
XXX . XXX
XXXXXXXXXXXXXXX
51.159
19.059
16.567
0.426
2.602
7.650
19.831
17.460
8.232
11.349
4.440
3.890
15.107
6.645
0.222
0.187
0.224
0.014
0.239
0.181
0.208
0.0002
XXXXXXXXXXXXXXX
15.119
4.140
0.336
0.087
0.038
0.022
0.011
0.027
0.543
0.518
0.350
0.341
XXXXXXXXXXXXXXX
1.456
0.423
25.143
64.396
3.884
5.183
6.505
9.310
15.221
27.567
4.261
0.122
0.0164
Sample
Result Value
XXX . XXX *
xxxxxxxxxxxxxxxxxx






















xxxxxxxxxxxxxxxxxx












xxxxxxxxxxxxxxxxxx













High
Range Value
XXX • XXX
XXXXXXXXXXXXXXX
62.397
31.068
19.999
1.346
3.631
8.904
27.371
24.373
13.639
17.250
4.606
4.133
20.440
8.991
0.306
0.277
0.280
0.058
0.323
0.247
0.289
0.074
XXXXXXXXXXXXXXX
22.676
4.310
0.486
0.171
0.089
0.039
0.028
0.141
0.735
0.701
0.474
0.511
XXXXXXXXXXXXXXX
2.184
0.572
35.548
87.778
4.514
6.024
7.560
10.820
17.689
32.038
5.041
0.191
0.0194
   In column indicates a problem with that parameter.

-------
l\.
    ). UOJSIA8U
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JO'SZ'OS
[O'SZ'OS
JO'SZ'OS
JO'SZ'OS
JO'SZ'OS
JO'SZ'OS
JO'OS'OOI
\0'Ot'OB














0'6ZI
0'6ZT
O'fOZ
0'»OZ
O'JOZ
O'tOZ
O'tOZ
O'O*
O'Ot
O'Ofr
O'Ot
0'0»
O'Ot
O'Ofr






















j xxxxxxxxxx | xxxxxxxx |
j xxxxxxxxxx 1 xxxxxxxx j
j xxxxxxxxxx j xxxxxxxx 1
j xxxxxxxxxx j xxxxxxxx j
j xxxxxxxxxx 1 xxxxxxxx j
xxxxxxxxxx j xxxxxxxx j
xxxxxxxxxx j xxxxxxxx j
j xxxxxxxxxx 1 xxxxxxxx |
j xxxxxxxxxx j xxxxxxxx 1
1 xxxxxxxxxx 1 xxxxxxxx
j xxxxxxxxxx 1 xxxxxxxx
1 xxxxxxxxxx 1 xxxxxxxx 1
O'OZ I
O'OZ I
j xxxxxxxxxx j xxxxxxxx 1 xxxxxxxxxx
1 xxxxxxxxxx 1 xxxxxxxx 1
1 xxxxxxxxxx 1 xxxxxxxx |

" TOA
' T°A ' }M
ZO'O'l'Ol XOX D
O'S'OI
O'S'OI
O'S'OI
O'S'OI
O'S'Ot
O'S'OI
S'Z'S
O'Z't
O't
O't
O'Z
O'Z
O'Z
O'Z
O'Z
O'OZ
O'OZ
O'OZ
O'OZ
O'OZ
O'OZ
O'OZ
O'Z
O'S
O'S
O'S
O'S
O'S
O'S
O'S
O'S
O'S
O'S
O'S
O'OZ
O'OZ
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O'OI
(6)
po^aH
ZE tOS
91 tOS
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t tos
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tOd tOS
OZH fOS
QD TV
aD~aj
OY~IS
OV TY
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did TY
did 3d
Z1D~*IY
zio~ad
Z1D YN
Z1D 51
Z1D OH
Z1O~YD
HZOO~Hd
1DYH OV
1O TV
ID YN
ID X
13 SM
1D~YD
DYO YN
DYO S
DYO OK
3VO YD
13 D3D
DYO D33
HtO Hd
OZH Hd
azfs ataf^fed
azts aiDT^tBd
XSIOH
^annijvd

zt
It
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6E
8E
/.E
9E
SE
»E
£E
ZE
IE
OE
6Z
8Z
LZ
9Z
sz
>z
EZ
zz
IZ
oz
61
81
it
91
SI
n
El
ZI
II
01
60
80
S/ViO
S/V90
so
to
EO
zo
to
t uuoj

                                                           "[OA
                                                                                    Ot jo 8

-------
QC Summary Report
 Page 9 of 10
Spike Solution Check
                                                             Batch t
                               Date Run   /  /
0 mg S/l
Theor.
Value
(mg S/L)
0.00
0.00
0.00
j Isotherm
Inst.
Reading
(mg S/L) *



2 mg S/l
Theor .
Value
(mg S/L)
2.00
2.00
2.00
j Isotherm
Inst.
Reading
(mg S/L) *




8 mg S/I
Theor.
Value
(mg S/L)
8.00
8.00
8.00

^ Isotherm
Inst.
Reading
(mg S/L) *










16 mg S/l
Theor.
Value
(mg S/L)
16.00
16.00
16.00

i Isotherm
Inst.
Reading
(mg S/L) *



4 mg S/l
Theor.
Value
(mg S/L)
4.00
4.00
4.00
J Isotherm
Inst.
Reading
(mg S/L) *



32 mg S/l
Theor.
Value
(mg S/L)
32.00
32.00
32.00
J Isotherm
Inst.
Reading
(mg S/L) *



CA_
Theor.
Value
(mg/L)
80.00
80.00
80.00
_CL2
Inst.
Reading
(mg/L) *



•*• In column indicates a problem with the parameter.
                                                                                       Appendix D
                                                                                       Revision 1
                                                                                       Date: 4/89
                                                                                       Page 15 of 17

-------
                                                                                         Appendix D
                                                                                         Revision 1
                                                                                         Date: 4/89
                                                                                         Page 16 of 17
QC Summary Report
 Page 10  of 10
                            Detection Limits
   Batch t _
Date Run   /
Form
*
01
02
03
04
05
06A
06B
07A
07B
08
09
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
| Calculated | Instrument Date
Reporting Contract Required | Detection Determined
Parameter Units Detection Limit j Limit * (MM/DD/YY)
HOIST | XXXXXXXXXXXX | XXXXXXXXXXXXXXXXXX | XXXXXXXXXXX | XXXXXXXXXXX
Particle Size | XXXXXXXXXXXX | XXXXXXXXXXXXXXXXXX j XXXXXXXXXXX | XXXXXXXXXXX
Particle Size j XXXXXXXXXXXX | XXXXXXXXXXXXXXXXXX | XXXXXXXXXXX 1 XXXXXXXXXXX
PH_H20 | XXXXXXXXXXXX j XXXXXXXXXXXXXXXXXX 1 XXXXXXXXXXX 1 XXXXXXXXXXX
PH_0 1M j XXXXXXXXXXXX j XXXXXXXXXXXXXXXXXX 1 XXXXXXXXXXX I XXXXXXXXXXX
CEC_OAC (FIA)
CEC_OAC (Tit.)
CEC_CL (FIA)
CEC_CL (Tit.)
CA_OAC
MG_OAC
K_OAC
NA_OAC
CA_CL
MG_CL
K_CL
NA_CL
AL_CL
AC_BACL
PH_002M
CA_CL2
MG_CL2
K_CL2
NA_CL2
FE CL2
AL_CL2
FE_PYP
AL_PYP
FE AO
AL_AO
SI AO
FE_CD
AL_CD
S04_H2O
S04_P04
S04_0
SO4 2
SO4 4
S04_8
SO4_16
S04_32
C_TOT
N_TOT
S TOT
meq/lOOg
meq/lOOg
meq/lOOg
meq/lOOg
meq/lOOg
meq/lOOg
meq/lOOg
meq/lOOg
meq/lOOg
meq/lOOg
meq/lOOg
meq/lOOg
meq/lOOg
meq/lOOg
XXXXXXXXXXXX
meq/lOOg
meq/lOOg
meq/lOOg
meq/lOOg
meq/lOOg
meq/lOOg
wt.
wt.
wt.
wt.
wt.
wt. %
wt. %
mg S/kg
mg S/kg
mg S/L
mg S/L
mg S/L
mg S/L
mg S/L
mg S/L
wt. t
wt. %
wt. t
1.050 mg N/L
0.0075 meq **
1.050 mg N/L
0.0075 meq **
0.050 mg/L
0.050 mg/L
0.050 mg/L
0.050 mg/L
0.050 mg/L
0.050 mg/L
0.050 mg/L
0.050 mg/L
0.100 mg/L
0.005 meq
XXXXXXXXXXXXXXXXXX
0.500 mg/L
0.050 mg/L
0.050 mg/L
0.050 mg/L
0.100 mg/L
0.100 mg/L
0.500 mg/L
0.500 mg/L
0.500 mg/L
0.500 mg/L
0.500 mg/L
0.500 mg/L
0.500 rog/L
0.025 mg S/L
0.025 mg S/L
0.025 mg S/L
0.025 mg S/L
0.025 mg S/L
0.025 mg S/L
0.025 mg S/L
0.025 mg S/L
0.010 wt. t
0.005 wt. t
0.001 wt. %














XXXXXXXXXXX






































xxxxxxxxxxx
























•*" In column  indicates a problem with that parameter.
**  For titrations, the instrumental detection limit is a calculated
    value  based upon a minimum titration.

-------
                                                                                  Appendix D
                                                                                  Revision 1
                                                                                  Date: 4/89
                                                                                  Page 17 of 17
Foxn Descriptions Sorted by Form t
Form
t
01
02
03
04
05
06A
06B
07A
07B
08
09
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
Form
Type
0
10
11
8
8
2
6
2
6
2
2
2
2
2
2
2
2
2
7
8
1
1
1
1
1
1
3
3
3
3
3
3
3
4
4
5
5
5
5
5
5
9
9
9
Parameter
HOIST
Particle Size Raw
Particle Size Calc.
PH_H2O
PHJJ1M
CEC_OAC (FIA)
CEC_OAC (Titr.)
CEC_CL (FIA)
CEC CL (Titr.)
CA_OAC
MG OAC
K OAC
NA OAC
CA_CL
MG_CL
K_CL
HA_CL
AL_CL
AC_BACL
PH_002M
CA_CL2
MG_CL2
K_CL2
NA_CL2
FE CL2
AL_CL2
FE_PYP
AL_PYP
FE_AO
AL_AO
SI_AO
FE_CD
A1,_CD
SO4 H2O
SO4 PO4
S04_0
SO4 2
SO4_4
SO4 8
S04_16
SO4_32
CJTOT
H_TOT
S TOT
Description
Air Dry Moisture Percent
Particle Size (Raw Data)
Particle Size (Calculated Data)
pH in Hater
pH in 0.0 1M Calcium Chloride
Cation Exchange Capacity - Ammonium Acetate
Cation Exchange Capacity - Ammonium Acetate
Cation Exchange Capacity - Ammonium Chloride
Cation Exchange Capacity - Ammonium Chloride
Calcium in Ammonium Acetate
Magnesium in Ammonium Acetate
Potassium in Ammonium Acetate
Sodium in Ammonium Acetate
Calcium in Ammonium Chloride
Magnesium in Ammonium Chloride
Potassium in Ammonium Chloride
Sodium in Ammonium Chloride
Aluminum in Ammonium Chloride
Barium Chloride - TEA Acidity
pH in 0.002M Calcium Chloride
Calcium in Calcium Chloride
Magnesium in Calcium Chloride
Potassium in Calcium Chloride
Sodium in Calcium Chloride
Iron in Calcium Chloride
Aluminum in Calcium Chloride
Pyrophosphate Extractable Iron
Pyrophosphate Extractable Aluminum
Acid Oxalate Extractable Iron
Acid Oxalate Extractable Aluminum
Acid Oxalate Extractable Silicon
Citrate Dithionite Extractable Iron
Citrate Dithionite Extractable Aluminum
Water Extractable Sulfate
Phosphate Extractable Sulfate
Zero mg S/L Isotherm Parameter
Two mg S/L Isotherm Parameter
Four mg S/L Isotherm Parameter
Eight mg S/L Isotherm Parameter
Sixteen mg S/L Isotherm Parameter
Thirty-two mg S/L Isotherm Parameter
Total Carbon
Total Nitrogen
Total Sulfur

-------
                                                                 Appendix E
                                                                 Revision 1
                                                                 Date: 4/89
                                                                 Page 1 of 7
                               Appendix E
  Analytical Laboratory Pre-Award Evaluation Scoring Sheet


   The following format is used to grade each contract laboratory that analyzes ore-award audit
samples provided by the QA staff.  The scores from this evaluation are used in considering the
award of contracts for DDRP analysis.

-------
                                                                    Appendix E
                                                                    Revision 1
                                                                    Date: 4/89
                                                                    Page 2 of 7
                                  APPENDIX E
                PRE-AWARD PERFORMANCE  EVALUATION SCORING SHEET
LABORATORY:
                                          DATE:
Quantitation: 	
Relationships:
Quality Control:
Deliverables: 	
TOTAL SCORE: 	
PERCENTAGE: 	
Sample 1:
Sample 2:
Sample 3:
Sample 4:
Sample 5:
                   (Maximum score per sample
        250  points)
r^*u\.j. x* v**"*1* A J- A**!, a. vw
Parameter Possible Point a
PH_H2O 3
PH_002M 3
PH_0 1M 3
S04_0 3
S04_2 3
S04_4 3
S04_8 3
S04_16 3
S04_32 3
SO4_H2O 3
SO4_PO4 3
CA_CL 3
MG_CL 3
K_CL 3
NA_CL 3
AL_CL 3
CEC_CL 3
Points Awarded
( Samoles )
1

















2

















3

















4

















5

















Total
Score


















-------
Appendix E
Revision 1
Date: 4/89
Page 3 of 7


Parameter Possible Points
CA_OAC 3
MG_OAC 3
K_OAC 3
NA_OAC 3
CEC_OAC 3
CA_CL2 3
MG_CL2 3
K_CL2 3
NA_CL2 3
FE_CL2 3
AL_CL2 3
AC_BACL 3
FE_PYP 3
FE_AO 3
FE_CD 3
ALJ?YP 3
AL_AO 3
AL_CD 3
SI_AO 3
SAND 3
M_SAND 3
SILT 3
CLAY 3
Subtotals
Points Awarded
(
1
























2
























Samol
3
























33)
4
























5

























Total
Score
























- Points are awarded per sample for being within accuracy windows
or for meeting %RSD precision limits.

-------
                                                                     Appendix E
                                                                     Revision 1
                                                                     Date:  4/89
                                                                     Page 4 of 7
PART II.  STANDARD RELATIONSFIPS
Possible
Parameter Grouo Points
Soil pH 5
Sulfate isotherms 10
Extractable Sulfate 5
CEC 5
article Size 5
Subtotals
Points Awarded
( Samples }
1






2






3






4






5






Total
Score






- Points are  awarded per sample.
PART III.  QUALITY CONTROL
Sample Type Possible Points'
Reagent Blanks
All < IDL 6
One or more > IDL 0
QC check Samples
All QCCS within 6
One or more QCCS out 0
Matrix Spikes
All within 100 + 10%
recovery 8
One or more out of
criteria 0
Detection Limit QCCS
All within 20% 30
One or two outside 20% 15
Three or more outside 0
20%
Instrument Detection Limits
All IDLs < CRDL 30
One IDL > CRDL 15
Two or more IDLs > CRDL 0
subtotals
Points Awarded
(Samples)
1






2






3






4






5






Total
Score






- Points are  awarded per sample.

-------
                                                                      Appendix E
                                                                      Revision 1
                                                                      Date: 4/89
                                                                      Page 5 of 7
PART IV.  REPORTING AND DELIVERABLES
Possible
Criteria Points
Analytical data submitted in
specified format 5
QC data submitted in
specified format 5
Tabulated IDLs and
associated blank data 5
supplied
Confirmation of summary
results by signature of
lab manager 5
Subtotals
Points
(Si
1


2


i Awai
uncles
3


•ded
i)
4


5


Total
Score


- Points are  awarded per sample.

-------
                              ELEMENTAL ANALYSIS

                PRE-AWARD PERFORMANCE EVALUATION  SCORING SHEET
                                                                   Appendix E
                                                                   Revision 1
                                                                   Date: 4/89
                                                                   Page 6 of 7
LABORATORY:
                                                  DATE:
Quantitation:

Relationships:
Quality Control:

Deliverables:
TOTAL SCORE:
Sample 1:

Sample 2:

Sample 3:

Sample 4:

Sample 5:

PERCENTAGE:
                        (200 points possible  per  sample)
r-Anx -L . uuATiXJ.xnxj.un
Parameter* Possible Points"
C_TOT 20
N_TOT 2 0
S_TOT 20
Subtotals
Points Awarded
(Samples)
1




2




3




4




5




Total
Score




* Refer to glossary for descriptions of parameters.
b Points are awarded per sample: two for being within accuracy windows  and
  one  for meeting  %RSD  precision  limits;  for  certain summary parameters the
  values are three and  two,  respectively.
PART II.  STANDARD RELATIONSHIPS
Parameter* Possible Points"
C_TOT/N_TOT 10
C TOT/S TOT 10
Subtotals
Points Awarded
(Samples)
1



2



3



4



5



Total
Score



  Points are awarded per sample

-------
                                                                    Appendix E
                                                                    Revision 1
                                                                    Date: 4/89
                                                                    Page 7 of 7
PART III.  QUALITY  CONTROL
Parameter*  Possible Points"

Reagent Blanks
  All < IDL                  10
  One or more >  IDL          0
QC check samples
  All QCCS within            10
  One or more QCCS  out       0
Points Awarded
(SamDles)
1


2


3


4


5


Total
Score


Parameter* Possible Points"
Matrix Spikes
All within 100 + 10%
recovery 2 0
One or more out of
criteria 0
Detection Limit QCCS
All within + 20% 30
Two or less outside + 20% 15
Three or more outside +20% 0
Instrument Detection Limits
All IDLs within 30
One IDL out 15
Two or more IDLs out 0
Subtotals
Points Awarded
< Samples )
1




2




3




4




5




Total
Score




  Points are awarded per sample.
PART IV.  REPORTING AND DELIVERABLES
Criteria Possible Points*
Analytical data submitted in
specified format 5
QC data submitted in specified
format 5
Tabulated IDLs and associated
blank data supplied 5
confirmation of summary results
by signature of lab manager 5
Subtotals
Points Awarded
f Samples)
1



2



3



4



5



Total
Score



*  Points  are awarded per sample.

-------

-------
                                                                   Appendix F
                                                                   Revision 1
                                                                   Date: 4/89
                                                                   Page 1 of 54
                                  Appendix F

    Analytical Laboratory On-Site Evaluation Questionnaire
      The following questionnaire is  used  by QA staff to provide documentation of on-site
laboratory audits.  An analytical laboratory is evaluated prior to the award of a contract to assess
the ability of the laboratory, in terms of personnel, facilities, and equipment, to analyze soil samples
successfully.  A second evaluation is made after sample analysis is underway. At the time of the
second evaluation, adherence to the Analytical Laboratory Statements of Work is evaluated and
specific discrepancies are addressed.

-------
                                                                 Appendix F
                                                                 Revision 1
                                                                 Date: 4/89
                                                                 Page 2 of 54
            ANALYTICAL LABORATORY ON-SITE  EVALUATION QUESTIONNAIRE
                               DDRP SOIL SURVEY

                             GENERAL (Page 1 of 2)
                                                 Date:
Laboratory:
Street Address:
Mailing Address  (if different  from above)
City:
State:	   Zip:



Laboratory Telephone Number:  (         )  	



Laboratory Director: 	.
Laboratory Quality Assurance  Officer:

  (Quality Control chemist)
Type of Evaluation:
Contract Number:
Contract Title:

-------
                                                                  Appendix F
                                                                  Revision 1
                                                                  Date: 4/89
                                                                  Page 3 of 54
                             GENERAL (Page 2 of 2)


Personnel Contacted:


                    Name                                    Title
Laboratory Evaluation Team:


                    Name                                    Title

-------
                    ORGANIZATION AND  PERSONNEL  (Page 1 of 3)


LABORATORY ORGANIZATIONAL CHART
                                                                    Appendix F
                                                                    Revision 1
                                                                    Date: 4/89
                                                                    Page 4 of 54

-------
                                                                 Appendix F
                                                                 Revision 1
                                                                 Date: 4/89
                                                                 Page 5 of 54



                   ORGANIZATION AND PERSONNEL  (Page  2 of 3)

Laboratory Personnel

                            Academic         Special              Years
Position        Name        Training*        Training            Experience**
* List highest degree obtained and  specialty.   Also list years toward a
  degree.
**List only experience directly relevant  to task to be performed.

-------
                                                                Appendix F
                                                                Revision 1
                                                                Date: 4/89
                                                                Page 6 of 54
                   ORGANIZATION AND PERSONNEL (Page 3 of 3)
Item

Do personnel assigned to this project have the
appropriate educational background to success-
fully accomplish the objectives of the program?

Do personnel assigned to this project have the
appropriate level and type of experience to
successfully accomplish the objectives of this
program?

Is the organization adequately staffed to meet
project commitments in a timely manner?

Does the laboratory Quality Assurance
Supervisor report to senior management levels?

Was the Project Manager available during the
evaluation?

Were chemists and technicians available during
the evaluation?

Was the Quality Assurance Supervisor available
during the evaluation?
                           Yes
No
Comment
                    Item
LABORATORY MANAGER (Page 1 of 1)

                           NO
                       Yes
    Comment
Does the laboratory manager have his/her own
copy of the standard operating procedures?

Does the laboratory manager have his/her own
copy of the instrument performance data?

Does the laboratory manager have his/her own
copy of the latest monthly QC plots?

Is the laboratory manager aware of the most
recent control limits?

Does the laboratory manager review the
following before reporting data:

     a.  The data itself?

     b.  The quality control data sheet
         with analyst notes?

     c.  The general instrument performance
         and routine maintenance reports?

-------
                                                                Appendix F
                                                                Revision 1
                                                                Date: 4/89
                                                                Page 7 of 54
               STANDARD OPERATING PROCEDURES (SOP) (Page 1 of 1)
               Item
Yes
No
Comment
Does the laboratory have a standard
operating procedure (SOP) manual?

Is the SOP manual followed in detail?

Does the SOP manual contain quality control
practices?

Does each analyst/technician have a copy
of the SOP manual?

Does the SOP manual deviate from the
procedures required by the project?

If the SOP manual does deviate, are the
deviations documented in written form?

Does each analyst/technician have a copy of
all methods and procedures required by this
project?

Are plots of instrumental accuracy and
precision available for every analysis?

Are detection limit data tabulated for
each analysis?

-------
                                                                Appendix F
                                                                Revision 1
                                                                Date: 4/89
                                                                Page 8 of 54
                      LABORATORY FACILITIES (Page 1 of 3)
When touring the facilities, give special attention to:
     (1) the overall appearance of organization and neatness,
     (2) the proper maintenance of facilities and instrumentation,
     (3) the general adequacy of the facilities to accomplish
         the required work.
               Item
Yes No
Comment
Does the laboratory appear to have adequate
workspace (6 linear meters of unencumbered
bench space per analyst)?

Does the laboratory have a source of
distilled/demineralized water?

Is the specific conductance of distilled/
demineralized water routinely checked and
recorded?

Are the analytical balances located away
from draft and areas subject to rapid
temperature changes?

Has the balance been calibrated within one
year by a certified technician?

Is the balance checked with a class S
standard before each use and recorded in a
logbook?  Have technician demonstrate
how this is done.

Are exhaust hoods provided to allow effi-
cient work with volatile materials?

Have the hoods been checked for operating
efficiency? How often is this done?

Is the laboratory maintained in a clean and
organized manner?

Are contamination-free work areas provided
for the handling of toxic materials?

Are adequate facilities provided for
separate storage of samples, extracts, and
standards, including cold storage?

Is the temperature of the cold storage units
recorded daily in logbooks?

Are chemical waste disposal policies/
procedures adequate?

Are contamination-free areas provided for
trace level analytical work?

Can the laboratory supervisor document that
trace-free water is available for prepara-
tion of standards and blanks?

-------
                                                                 Appendix F
                                                                 Revision 1
                                                                 Date: 4/89
                                                                 Page 9 of 54
                      LABORATORY FACILITIES (Page 2 of 3)
               item
Yes
No
Comment
Do adequate procedures exist for disposal
of waste liquids from the ICP and AA
spectrometers ?

Do adequate procedures exist for disposing
of liquid and solid wastes?

Is the laboratory secure?

Are all chemicals dated on receipt and
thrown away when shelf life is exceeded?

Are all samples stored in the refrigerator
between analyses?

Are acids and bases stored in separate
areas?

Are hazardous, combustible, and toxic
materials stored safely?
                             LABORATORY FACILITIES
Item
Gas
Lighting
Compressed air
Vacuum system
Electrical services
Hot and cold water
Distilled water
Laboratory sink
Ventilation system
Hood space
Cabinet space
Storage space (m*)
Refrigerated storage (4°C)
Avai;
Yes













[able
No













Comments
(where applicable, cite system,
QC check, adequacy of space)














-------
                       LABORATORY FACILITIES  (page 3 of  3)

COMMENTS  ON LABORATORY  FACILITIES
                                                                    Appendix F
                                                                    Revision 1
                                                                    Date: 4/89
                                                                    Page 10 of 54

-------
                                           Appendix F
                                           Revision 1
                                           Date: 4/89
                                           Page 11 of 54
EQUIPMENT  GENERAL (Page  1  of 2)
item
Balance, analytical
(1)
(2)
(3)
Balance, top
loader
class "S"
weights
Balance table
NBS-calibrated
thermometer
Desiccator
Distilled water
Double deionized,
distilled/deion-
ized, or double
distilled water
Glassware
(1) Beakers
(2) Erlenmeyer
flasks
( 3 ) Sedimentation
cylinders
( 4 ) Graduated
cylinders
(5) Fleakers
(6) Other
Drying ovens
Hot plates
Water bath
Centrifuge
Vortex mixer
Equipment
# of
Units























Make























Model























Condition/aae
Good























Fair























Poor























Comments
























-------
                                                                     Appendix F
                                                                     Revision 1
                                                                     Date: 4/89
                                                                     Page 12 of 54
                         EQUIPMENT GENERAL (Page  2  of 2)
item
Eppendorf pipets
(or equivalent)
Reciprocating
shaker
Eauioment
f of
Units

Make

Model

Cond:
Good

ition/aae
Fair

Poor

Comments

Comments:

-------
                                                                 Appendix F
                                                                 Revision 1
                                                                 Date: 4/89
                                                                 Page 13 of 54
                               MOISTURE  CONTENT
Item
Manufacturer
                                   Model
              Installation
                Date
                                               Comments
Balance, +0.01 g

Convection ovens
Item
 Available
Quantity    |  Type
                                                                    Comments
Thermometers
0 to 200°C

Weighing
containers

Desiccator

Desiccant
Comments:

-------
                                                                Appendix F
                                                                Revision 1
                                                                Date: 4/89
                                                                Page 14 of 54
Question
MOISTURE CONTENT (Page 2 of 2)

                     Yes
No
NA
Comments
Is the balance calibrated weekly?

Do thermometers have a range of -20 to
200°C?

Are thermometers calibrated (with barometric
correction) at the boiling and freezing
points at least once every 3 months?

Is the oven temperature checked and
recorded daily?

Is the oven temperature calibrated at
least monthly?

Are organic soil samples dried at the
specified temperature?

Are replicates of each sample prepared
and run?

Are mineral soil samples dried at the
specified temperature?

Are two separately calibrated ovens used,
one for organic and one for mineral soils?

If only one oven is used, is at least 24
hours allowed for the oven to stabilize
at the new temperature?

Is sample-drying time extended as
specified in the procedure?

Are calculations correctly performed, and
are at least 5% (or 2 per batch) checked
by hand?

-------
                                                                Appendix F
                                                                Revision 1
                                                                Date: 4/89
                                                                Page 15 of 54
                            PARTICLE SIZE ANALYSIS
Item
Manufacturer
Model
Installation Date
Comments
Hot plate or
block digester

Analytical
balance,
0. Img

Shaker hori-
zontal recip-
rocating (120
oscillations/
min)

Sieve shaker
(1.25 cm
vertical and
lateral
movement)

Complete
sieve set with
receiving pan

Automatic
pipets

Shaw pipet
rack

Motor-driven
stirrer
                            PARTICLE SIZE ANALYSIS
Item
   Available
  Quantity
                                                Type
                    Comments
Thermometer
10 to 50°c

Erlenmeyer flask
or Fleaker 300
mL

Pasteur-
chamberlain
filter candles
(fineness"F")

1-L Sedimenta-
tion cylinders

Insulation
covering

Hand-driven
stirrer

-------
                                                                Appendix F
                                                                Revision 1
                                                                Date: 4/89
                                                                Page 16 of 54
                     PARTICLE SIZE ANALYSIS  (Page 2 of 4)
Item
 Available
 Quantity
                                                Type
                   Comments
Shaw pipet rack
equivalent

Ring stand

Clamp

Volumetric
pipet, 25 mL

Evaporating
dishes

Waterproof
markers
or paint pens

Weighing bottles
90-mL wide-mouth

Desiccator
Set of sieves, square-mesh, woven phosphor-bronze or stainless steel wire
cloth; U.S. Series and Tyler Screen Scale equivalent designations as follows;
Nominal
ODeninq(mm)
1.0
0.5
0.25
0.105
0.046
U.S.
No.
18
35
60
140
300
Tyler
Mesh Size
16
32
60
150
300
Chemical
                            PARTICLE SIZE ANALYSIS
Quantity
Grade
Expiration Date
Comments
Hydrogen
peroxide (HO)
30 to 35%  2 2

Dessicant:
Phosphorus
pentoxide
(P O )
1 2 5'
Sodium carbon-
ate (Na CO )
       2  3
Sodium Hexameta
phosphate
(NaPO )6

-------
                                                                Appendix F
                                                                Revision 1
                                                                Date: 4/89
                                                                Page 17 of 54
                     PARTICLE SIZE ANALYSIS (Page 3 of 4)
comments:
                            PARTICLE SIZE ANALYSIS
Question
Yes
    No
        NA
              Comments
Is analysis performed on mineral horizons
only?

Is the organic matter removed as specified
before proceeding?

Are chemicals reagent grade or better?

Is heat applied after organic matter is
visibly destroyed to remove excess HO?

Is reciprocating shaker calibrated once
every 6 months if no gauge is included
(every year with gauge)?

Is the 500 stroke per minute (1.25 cm
vertical and lateral oscillator) shaker
calibrated once every 6 months?

Are pipets calibrated monthly, gravimetri-
cally on a calibrated balance?

-------
                                                                Appendix F
                                                                Revision 1
                                                                Date: 4/89
                                                                Page 18 of 54
Question
PARTICLE SIZE ANALYSIS (Page 4 of

                      Yes No  NA
                                                       4)
Comments
Are the specified methods used for
separating sand, silt, and clay?

Is a standard sand, silt, clay "soil"
used as a control?

Is the water temperature checked during
sedimentation to determine when to take
a sample?

Are the specified procedures followed
during sedimentation?

Is note made of which sedimentation table
is used to determine sampling depth and
time?

Are weights for each mineral fraction
correctly recorded and calculated?

Are calculations correctly performed, and
are at least 5% (or 2 per batch) checked
by hand?

-------
                                                                Appendix F
                                                                Revision 1
                                                                Date: 4/89
                                                                Page 19 of 54
Item
Manufacturer
pH DETERMINATION

 Model        Installation Date
                                                                 Comments
Digital
pH meter

Combination
electrodes,
non-gel type
Item
 Available
 Quantity
Type
                                                                comments
Thermometer

Beakers, 50 mL

stirrers

QCCS standard
Chemical
 Quantity
 Grade
Expiration Date
Comments
Calcium
Chloride
Calcium
hydroxide
(Ca(OH)2)

Chloroform
(CHClo) or
Thymol
(C10H1 O)
      4
Hydrochloric
acid (HCl)

National
Bureau of
Standards
(NBS) buffers

Potassium
Biphthalate
(KHC H O )
V    844'
Potassium
chloride (KCl)

-------
                                                                Appendix F
                                                                Revision 1
                                                                Date: 4/89
                                                                Page 20 of 54
Question
pH DETERMINATION (Page

                   Yes
                                               2 of 3)
                       No
NA
Comments
Are chemicals reagent grade or better?

Is the air-dried soil stored in sealed
containers?

Is the pH meter digital to +0.01
(and +1 mv)?

Does the pH meter have internal
temperature compensation to +0.5°c?

Is the combination electrode a non-gel
type?

Is the combination electrode of the
recommended style with retractable
sleeve junction?

Are the buffers calibrated daily to +.01
pH units?

Is the pH meter:
      - calibrated before samples are
         analyzed
      -checked every batch as stated
         in methods

Is temperature compensation manual or
internal?

Are equilibrium times required for
standards checked, to see if electrode
response is slowing?

Is a spare combination electrode available
and properly stored?

Is manufacturer recommended warm-up time
allowed before samples are run?

Are pH meters placed away from drafts and
areas of rapid temperature change?

Are the specified between-sample
procedures followed?

Are pH units equipped with programmable
sampling times?

If yes above, are they used in this
analysis?

Are electrodes properly stored and
maintained?

Are the QC results plotted in real time?

-------
                                                                 Appendix F
                                                                 Revision 1
                                                                 Date: 4/89
                                                                 Page 21 of 54
Question
pH DETERMINATION (Page 3 of 3)

                   Yes No  NA
Comments
what is the QCCS sample?

Is the QCCS solution analyzed  first  and
thereafter as called for in the methods?

Are a QCCS and duplicate sample included
in each run?

Is the quality control data reviewed by
the analyst before deciding whether  to
release the data for reporting?

-------
                                                                Appendix F
                                                                Revision 1
                                                                Date: 4/89
                                                                Page 22 of 54
Item
                           CATION EXCHANGE CAPACITY
Manufacturer
Model
                                             Installation  Date
                                                 Comments
Mechanical
extractor

Flow injection
analyzer

Titration
apparatus

Reciprocating
shaker
Item
 Available
Quantity
                                              Type
                                                 Comments
Steam
distillation
unit

Digestion
tubes 250 mL

Kjeldahl
flasks, 800 mL

Analytical
filter pulp

Disposable
syringes 60 mL

Rubber tubing
connectors

Linear
polyethylene
bottles, 25 mL
Chemical
                           CATION EXCHANGE CAPACITY
 Quantity
Grade
Expiration Date
Comments
Glacial acid
(HC2H302)

Ammonium
hydroxide
(NH4OH)

Ammonium
acetate
(NH40AC)

Ammonium
chloride

-------
                                                                 Appendix F
                                                                 Revision 1
                                                                 Date: 4/89
                                                                 Page 23 of 54
                     CATION EXCHANGE CAPACITY (Page 2 of 5)
 Chemical
Quantity
Grade
Expiration Date
                                                                  Comments
 (NH4C1)

 Ethanol
 (CH3CH20),  95%

 Nessler's
 reagent

 Potassium
 iodide  (KI)

 Mercuric
 iodide  (Hgl2)

 Sodium
 hydroxide
 (NaOH)

 Sodium
 chloride
 (Nad)

 Antifoam

 Hydrochloric
 acid  (HCl)

 Sodium
 carbonate
 (Na2CO3)

 Methyl orange
 indicator

 Boric Acid

 Zinc, granular

 Phenol
 (C6H6O)

 Potassium
 sodium
 tartrate

 (KNaC4H406).
 4H20

 Sodium
 citrate
 (Na3C6H5o7).
 2H2O)

 Sodium nitro-
 ferricyanide
 (Na3Fe(CN)5
N03.2H2O)

-------
                                                                 Appendix F
                                                                 Revision 1
                                                                 Date: 4/89
                                                                 Page 24 of 54
chemical
   CATION EXCHANGE CAPACITY  (Page 3 of 5)

Quantity       Grade         Expiration Date
Comments
Sodium hypo-
chlorite
(NaOCl)
Comments:

-------
                                                                Appendix F
                                                                Revision 1
                                                                Date: 4/89
                                                                Page 25 of 54
Question
CATION EXCHANGE CAPACITY (Page 4 of 5)

                       Yes No
NA
Comments
Are the chemicals reagent grade or better?

Are dilute standards prepared and cali-
brated daily?

Are working standards prepared and
calibrated at least weekly?

Are reagents stored properly to prevent
premature decomposition?

Are hazardous chemicals used strictly
under the hood?

Is an antifoam agent available for use?

Is all glassware cleaned and stored as
specified?

Does the flow injection analyzer (FIA)
have the correct interference filter?

Are the pump lines inspected for wear
before each run?

Is the heat bath of the FIA calibrated
monthly and checked before each run?

Are the pump tubes all of the correct
type for the agents and method in use?

Are all peripherals such as printer,
plotter, and disk drives functional and,
in the case of recorders and plotters,
calibrated before each run?

Is the shaker used for organic samples
calibrated every six months or less along
with general maintenance?

Is the auto analyzer (distillation/
titration) calibrated for titration before
each run?

Are the condensation facilities of the
distillation apparatus inspected before
each run?

Are all calculations performed correctly,
and are at least 5% being checked by hand?

Is the mechanical extractor calibrated
for extraction time?

Is the calibration of the mechanical
extractor checked at least monthly?

-------
                                                                Appendix F
                                                                Revision 1
                                                                Date: 4/89
                                                                Page 26 of 54
Question
CATION EXCHANGE CAPACITY (Page

                       Yes No
                                                    5 of  5)
NA
Comments
Are the specified size, type, and grade of
disposable syringes used with the
extractor?

Is the tubing checked frequently and
replaced when needed?

Is the filter pulp washed before the
extraction is performed?

Are all procedures involving the
extraction followed precisely according to
the statement of work?

Are three blanks carried through to record
mean and standard deviation?

-------
                                                                Appendix F
                                                                Revision 1
                                                                Date: 4/89
                                                                Page 27 of 54
Item
                             EXCHANGEABLE CATIONS
Manufacturer
Model/Grade
                                             Installation  Date
                                                  Comments
Flame atomic
absorption
spectrometer

Inductively
coupled plasma
emission
spectrometer

Atomic flame
emission
spectrometer
chemical
 Quantity
 Grade
Expiration Date  |  Comments
Argon
Acetylene gas
(C H )
v 2 4;
Natural gas
Hydrochloric
acid (HCl)

Nitric acid
Calcium
carbonate
Magnesium
oxide (MgO)

Potassium
chloride (KCl)

Sodium
chloride (Nad)

Lanthanum
oxide (La O )
      v  2 3;
Cesium
chloride (CsCl)

-------
                                                                 Appendix F
                                                                 Revision 1
                                                                 Date: 4/89
                                                                 Page 28 of 54
Chemical
                      EXCHANGEABLE  CATIONS (Page 2 of 3)
Quantity
Grade
Expiration Date
Comments
Lithium
chloride
(LiCl)

Lithium
nitrate
QCCS

Calcium (Ca)

Magnesium  (Mg)

Potassium  (K)

Sodium ( Na )

Aluminum ( Al )
Comments:

-------
                                                                Appendix F
                                                                Revision 1
                                                                Date: 4/89
                                                                Page 29 of 54
                      EXCHANGEABLE CATIONS  (Page 3 of  3)
Question
Yes
No
NA
Comments
Is the analytical instrument cleaned and
adjusted before and after each run?

Is the power source secure, that is,
protected against line fluctuation?

Are standards made in a matrix as close as
possible to that of the extract?

If the lanthanum oxide method is used, is
the La2O3 added to the samples and
standards?

Are the pHs of the samples and standards
approximately identical?

Are all chemicals of analytical reagent
grade or better?

Are chemicals used for standards traceable
to NBS standards?

Does the laboratory have copies of Methods
for Chemical Analysis of Water and Wastes,
and Standard Methods 14th edition or
access to them?

Are all calculations performed correctly,
and are at least 5% (2 per batch) checked
manually?

-------
                                                                Appendix F
                                                                Revision 1
                                                                Date: 4/89
                                                                Page 30 of 54
                          LIME AND ALUMINUM POTENTIAL
Item
Manufacturer
Model/Grade
Installation Date
                                                               Comments
Flame atomic
absorption
spectrometer

Inductively
coupled plasma
spectrometer

Flame atomic
emission
spectrometer
Item
  Available
 Quantity
                                                 Type
                        Comments
Reciprocating
shaker

Linear poly-
ethylene
bottles
(25 and 50mL)

250 mL
polypropylene
centrifuge
bottles
Chemical
  Quantity
   Grade
 Expiration Date
Comments
Calcium
chloride
Hydrochloric
acid(HCl)

NBS traceable
standards :

Calcium (Ca)

Magnesium (Mg)

Potassium (K)

Sodium (Na)

Iron ( Fe )

Aluminum ( Al )

-------
                                                                    Appendix F
                                                                    Revision 1
                                                                    Date: 4/89
                                                                    Page 31 of 54
                    LIME AND ALUMINUM POTENTIAL  (Page 2 of 2)
Comments:
                             LIME AND  ALUMINUM POTENTIAL
Question
Is the reciprocating shaker calibrated
every six months or less in addition to
general maintenance?
What is the QC sample?
Is the QC solution analyzed initially
as called for in the methods?
Are the QC results plotted on QC charts
in real time?
Is the quality control data reviewed by
the analyst before deciding whether to
release the data for reporting?
Are the results for Ca reported after
adjusting for the CaCl extraction
solution? ^
Are results reported based on oven-dry
soil weight?
Are all calculations correctly performed,
and are 5% (2 per batch) checked manually?
Yes

No

NA

Comments


-------
                                                                Appendix F
                                                                Revision 1
                                                                Date: 4/89
                                                                Page 32 of 54
                         EXTRACTABLE IRON AND ALUMINUM

Sodium Pvrophosphate. citrate Dithionite and Acid Qxalate Methods
Item
Manufacturer
 Model
Installation Date
                                                                   Comments
Centrifuge

Inductively
coupled plasma
spectrometer
Item
 Available
Quantity
                                                Type
                  Comments
Reciprocating
shaker

Repipet

Automatic
    pipet

Buret

250 mL
polypropylene
centrifuge
bottles

Fleakers

Volumetric
pipets

Volumetric
flasks
Chemicals
  EXTRACTABLE IRON AND ALUMINUM

   Quantity       Grade       Expiration Date
                                  Comments
Sodium pyro-
phosphate

Sodium hyrox-
ide (Na OH)

pH buffers,
pH=7 and 10

Phosphoric
acid(H3PO4)

Superfloc 16

Sodium
dithionite
(Na2S204)

-------
                                                                 Appendix F
                                                                 Revision 1
                                                                 Date: 4/89
                                                                 Page 33 of 54
                  EXTRACTABLE IRON AND ALUMINUM (Page 2 of 3)
Chemicals
Quantity
Grade
Expiration Date
                                                                   Comments
Sodium citrate
(Na3C6H5O7 H O)

Ammonium
oxalate
((NH4)2C2O4.

H20)
Oxalic acid
(H2C2O4.H O)

pH buffers,
pH = 4 and 2

Nitric acid
(HNO3)
Comments:

-------
                                                                Appendix F
                                                                Revision 1
                                                                Date: 4/89
                                                                Page 34 of 54
Question
EXTRACTABLE IRON AND ALUMINUM (Page 3 of 3)

                          Yes
No
NA
Comments
Are the proper type of polypropylene 250
mL centrifuge tubes used?

Is the reciprocating shaker calibrated
yearly if it possesses a speed gauge,
every 6 months if not?

Is the centrifuge calibrated yearly if
it possesses a speed gauge, every 6 months
if not?

Are standards made up in the same expected
matrix as are the extracts?

Are the chemicals reagent grade or better?

Is the extract promptly stored at 4°C?

Is analysis performed for Fe and Al within
24 hours of extraction?

Are the calculations carried out correctly
and are at least 5% (2/batch) checked
by hand?

-------
                                                                Appendix F
                                                                Revision 1
                                                                Date: 4/89
                                                                Page 35 of 54
                              EXTRACTABLE SULFATE
item
 Manufacturer
 Model
Installation Date
                                                                    Comments
Balance,
+0.01 g

ion chromato-
graph

Automated
injection
system

Filtration
apparatus

Centrifuge
Vortex mixture
Rec iproc at ing
shaker
Item
Available
Quantity
 Type
                                                                Comments
100-raL centri-
fuge tubes
with screw
caps

Volumetric
flasks

0.20m pore
size membrane
filters

volumetric
pipets
Chemical
  Quantity
Grade
 Expiration Date
Comments
Monobasic
sodium
phosphate
(N3H2P04.H20)

Sodium
carbonate
(Na2CO3)

Sodium
hydroxide
(NaOH)

-------
                                                                Appendix F
                                                                Revision 1
                                                                Date: 4/89
                                                                Page 36 of 54
                       EXTRACTABLE  SULFATE (Page 2  of 3)
Chemical
Quantity
Grade
Expiration Date
Comments
Sulfuric acid
(H2SO4)

Magnesium
sulfate
(Mg2so4)

Sodium nitrate
(NaNO3)
Question
                          Yes
               No
           Comments
Is the ion chromatograph maintained
according to manufacturer's specifi-
cations?

Are manufacturer recommendations for
optimum 1C sensitivity used?

Are chemicals reagent grade or better?

Are the phosphate and sulfate concentra-
tions low enough so they elute separately?
Are dilutions made if not?

Are all the proper accessories maintained
on the 1C?
      -anion separation column?
      -micro-membrane suppressor (anion
        separation) column?

Is the optional automatic injection
system used?

Are all solutions made fresh when needed?
      -0.40 M NaCO3
      -0.0020 M Na2C03 / 0.0020 M NaOH
      -other
      -stock resolution standard
      -working resolution standard
      -sulfate and nitrate calibration

Are conversion operations performed
correctly for:
      -meq/L to mg/L SO4?
        (1 meq = 48.0288 mg)
      -mg/L to meq/L SO4?
        (1 meq = 0.02082 meq)
      -SO4 to S?
        (1 mg SO4 = 0.3338 mg S)
      -S to S04?
        (1 mg S = 2.9962 mg SO4)

Are recording instruments calibrated
before each use?

-------
                                                                Appendix F
                                                                Revision 1
                                                                Date: 4/89
                                                                Page 37 of 54
                       EXTRACTABLE SULFATE (Page 3 of 3)
Question
Yes
    No
NA
Comments
Is a pump stroke noise suppressor or
pressure gauge used to stabilize pressure?

Is resolution high enough so no startover
is required?

Are peak heights/areas recorded in a
logbook?

If peaks are not sharp and symmetric, is
an approved method for peak area
determination used?

Is peak area determined by microprocessor?
If yes, which methods and formulas does
it use?

Are calibration curves constructed accord-
ing to manufacturer's recommendations?

Is the flow rate checked gravimetrically
with time for consistency of flow?

Is the rate of flow calibrated before each
batch is run?

-------
                                                                Appendix F
                                                                Revision 1
                                                                Date: 4/89
                                                                Page 38 of 54
Item
        SULFATE ADSORPTION ISOTHERMS

Manufacturer   Model        Installation Date
                                                                  Comments
Balance,
+0.01g

Ion chromato-
graph

Centrifuge

Filtration
apparatus

Reciprocating
shaker
Item
Available
Quantity
                                              Type
Comments
Centrifuge
tubes with
screw caps,
100 or 50mL

0.45 pm pore
size membrane
filters

volumetric
pipet, 50 mL
chemical
                 Quantity
               Grade
              Expiration Date
Comments
Magnesium
sulfate
Comments

-------
                                                                Appendix F
                                                                Revision 1
                                                                Date: 4/89
                                                                Page 39 of 54
Question
SULFATE ADSORPTION ISOTHERMS (Page 2 of 2)

                         Yes No  NA    Comments
Are MgSO4 adsorption solutions correctly
prepared?

Are the adsorption solutions calibrated
for accuracy before being used in the run?

Are the working standards made fresh
daily?

Is the deionized water sent through the
0.20 pm membrane filter?

Is the supernatant sent through the
0.45 pro membrane filter?

Is the correct amount of soil (oven-dried
weight) used?

Are methods of analysis by ion chroma-
tography the same as used in the extract-
able sulfate procedure?

Are the correct conversion factors used as
in the extractable sulfate procedure?

Are all calculations performed correctly,
and are at least 5% (2 per batch) checked?

-------
                                                                 Appendix F
                                                                 Revision 1
                                                                 Date: 4/89
                                                                 Page 40 of 54
Item
            EXCHANGEABLE ACIDITY

Manufacturer   Model        Installation  Date    comments
Mechanical
extractor

Rec iproc ating
shaker

Automatic
titrator

pH meter

pH electrode
Item
Available
Quantity
                                              Type
                                                 Comments
Syringes 60mL

Filter pulp

Pipettors,
adjustable to
25 mL

Stirring rods

Titration
(Erlenmeyer)
250 and 125 mL

Tubes, 25 roL
glass

Eppendorf
pipets, 5 mL
and 5L

Diluter

Volumetric
flasks

Linear poly-
ethylene
bottles 25 mL

Drying tube

-------
                                                                 Appendix F
                                                                 Revision 1
                                                                 Date: 4/89
                                                                 Page 41 of 54
Chemical
                      EXCHANGEABLE  ACIDITY (Page 2 of 4)
Quantity
Grade
Expiration Date
Comments
Ascarite

Barium
chloride
(BaCl2.2H2O)

Triethanola-
mine
(N(CH2CH2OH)3)

Hydrochloric
acid (HCl)

Sodium hydrox-
ide (NaOH)

Methyl orange
indicator

NBS-traceable
buffers, pH=4,
7, and 10
Comments:

-------
                                                                Appendix F
                                                                Revision 1
                                                                Date: 4/89
                                                                Page 42 of 54
                      EXCHANGEABLE ACIDITY (Page 3 of 4)
Question
Yes
No
NA
Comments
Is the buffer solution protected from CO ?

Are the syringes prepared according to
protocol?

Is the pH calibration the same as for the
pH procedure (comment on any exceptions)?

Is the automatic titrator calibrated
gravimetrically before each batch?

Is the pH endpoint of the automatic
titrator calibrated to 4.60?

Are at least 5% of the calculations
checked manually?

Are calculations performed correctly?

Is the reciprocating shaker calibrated
every six months or less in addition to
general maintenance?

Is the auto analyzer (distillation/
titration) calibrated for titration before
each run?

Are titration results calculated, and
are 5% hand checked?

Is the 25-mL pipetter calibrated gravi-
metrically daily (if the adjustable type)
and at least weekly if a fixed volume?

Is the diluter calibrated and checked
gravimetrically before each run?

Is the same amount of filter pulp used
with each sample?

Is the filter pulp washed before use?

Is the specified number of blanks run for
each batch?

Are chemicals of reagent grade or better?

Is the mechanical extractor calibrated
for extraction time?

Is the calibration of the mechanical
extractor checked at least monthly?

Are the specified size, type, and grade of
disposable syringes used with the
extractor?

-------
                                                                 Appendix F
                                                                 Revision 1
                                                                 Date: 4/89
                                                                 Page 43 of 54
Question
EXCHANGEABLE ACIDITY (Page 4 of  4)

                     Yes No  NA  I  Comments
Is the tubing checked frequently  and
replaced when needed?

Are all procedures involving the  extr-
action followed precisely according to  the
statement of work?

Are three blanks carried through  to record
mean and standard deviation?

-------
                                                                Appendix F
                                                                Revision 1
                                                                Date: 4/89
                                                                Page 44 of 54
Question
FLAME ATOMIC ABSORPTION SPECTROSCOPY
                      Yes No  NA    Comments
For which methods is this instrument used?
Is the burner head cleaned and adjusted
for each run?
Is the burner head cleaned frequently when
solutions of high ionic strength are
analyzed?
Is DI water or cleaning solution aspirated
both before and after a run?
Is the nebulizer cleaned at least weekly?
Is the correct flame type used for deter-
mination of each element?
Is the acetylene of specified purity?
Is gas pressure monitored during a run?
Are filters used to remove water and oil
from the compressed air?
Is constant air pressure maintained? How?
Is the wavelength optimized before a run?
Is the slit width correctly set for the
desired element?
Is the optical system aligned at least
every 6 months?  With a major realignment
every 12 months?
Are the lamp and instrument allowed
adequate time to warm up before use
     -Lamp time (30-60+ minutes)?
     -Instrument time
       (constant if possible)?
     -Flame time (5+ minutes)?
Is the unit adequately vented?
Is tubing inspected before each run?

-------
                                                                Appendix F
                                                                Revision 1
                                                                Date: 4/89
                                                                Page 45 of 54
Question
INDUCTIVELY COUPLED PLASMA EMISSION
                            Yes No
                                                   SPECTROSCOPY
NA
Comments
For which methods is this instrument used?
Is the tubing inspected before each run?
Are the electrodes replaced as instructed
by the manufacturer or more frequently?
Is the instrument adequately vented?
Is the instrument in a temperature
controlled room?
Is ample time allowed for the instrument
to warm up?
Are standards calibrated both alone and
as part of a multi-element matrix?
Is the UV-IR shielding in place?
Is an adequate supply of the carrier gas
present?
Are manufacturer operating procedures
followed?
On multi-element units, are alternate
wavelengths used when necessary to
avoid interference?

-------
                                                                Appendix F
                                                                Revision 1
                                                                Date: 4/89
                                                                Page 46 of 54
                   FLAME PHOTOMETRY (FLAME ATOMIC EMISSION)
Question
Yes
No
NA
Comments
For which methods is this instrument used?

Are the correct filters used for each
element?

Is the pressure of the gases monitored
during a run?

Is the oxygen supply of 99.95% purity or
higher?

Is the fuel supply of sufficient purity
and of constant pressure?

Is the aspirator cleaned before and after
each run?

is a rinse solution of Dl water (or
wash solution) used between samples to
prevent salting-up of the aspirator?

Is the unit given adequate time to warm up
before use?

Is the unit calibrated before use?

Is the aspirator/nebulizer unit inspected
daily for proper seating and function?

Is the unit placed away from areas of
drafts and sudden temperature changes?

-------
                                                                Appendix F
                                                                Revision 1
                                                                Date: 4/89
                                                                Page 47 of 54
                            DOCUMENTATION/TRACKING
               Item
                Yes
                    No
Comment
Is a sample custodian designated?
of sample custodian 	
If yes, name
Are the sample custodian's procedures and
responsibilities documented?  If yes, where
are these documented?

Is sample tracking performed via paper or
computer?

Are written standard operating procedures  (SOPs)
developed for receipt of samples?  if yes,
where are they documented?

Are written standard operating procedures  (SOPs)
developed for compiling and maintaining sample
document files?  If yes, where are they document-
ed?
Are samples stored under refrigeration?
temperature?
      At what
After completion of the analysis are the
samples properly stored for six months or
until laboratory personnel are told otherwise?

-------
                                                                Appendix F
                                                                Revision 1
                                                                Date: 4/89
                                                                Page 48 of 54
                            ANALYTICAL METHODOLOGY
               Item
Yes
No
Comment
Are the required methods used?

is there any unauthorized deviation from contract
methodology?

Are written analytical procedures provided to
the analyst?

Are reagent grade or higher purity chemicals
used to prepare standards?

Are fresh analytical standards prepared at a
frequency consistent with good Q.A?

Are reference materials properly labeled with
concentrations, date of preparations, and the
identity of the person preparing the sample?

Is a standard preparation and tracking logbook
maintained?

Do the analysts record bench data in a neat and
accurate manner?

Is the appropriate instrumentation used in
accordance with the required protocol(s)?

-------
                      ANALYTICAL METHODOLOGY (Page 2 of  2)

COMMENTS ON ANALYTICAL METHODS AND PRACTICES
                                                                    Appendix F
                                                                    Revision 1
                                                                    Date: 4/89
                                                                    Page 49 of 54

-------
                                                                Appendix F
                                                                Revision 1
                                                                Date: 4/89
                                                                Page 50 of 54
               Item
QUALITY CONTROL
              Yes
No
         Comment
Does the laboratory maintain a quality
control manual?
Does the manual address the important
elements of a QC program, including the
following:
a.  Personnel?
b.  Facilities and equipment?
c.  Operation of instruments?
d.  Documentation of procedures?
e.  Procurement and inventory practices?
f.  Preventive maintenance?
g.  Reliability of data?
h.  Data validation?
i.  Feedback and corrective action?
j.  Instrument calibration?
k.  Record keeping?
1.  Internal audits?
Are QC responsibilities and reporting
relationships clearly defined?
Have standard curves been adequately
documented?
Are laboratory standards traceable?
Are quality control charts maintained  for
each routine analysis?
Do QC records show corrective action
when analytical results fail to meet
QC criteria?
Do supervisory personnel review the data and
QC results?
Does the  QC chemist have a copy of the
standard  operating procedures?
Does the  QC chemist have a copy of the
instrument performance data?
Does the  QC chemist have a copy of the
latest QC plots?

-------
                                                                Appendix F
                                                                Revision 1
                                                                Date: 4/89
                                                                Page 51 of 54
               Item
QUALITY CONTROL (Page 2 of 2)

                     Yes  No
Comment
Is the QC chemist aware of the most recent
control limits?

Does the QC chemist prepare a blind audit
sample once per week?

Does the QC chemist routinely review and
report blank audit data to the laboratory
manager?

Does the QC chemist update control limits
and obtain new control charts once
per batch?

Are all QC data (e.g., control charts,
regression charts, QC data bases) up to
date and accessible?

Are minimum detection limits calculated
as specified?

Is QC data sheet information reported to
the analyst?

-------
                                                                Appendix F
                                                                Revision 1
                                                                Date: 4/89
                                                                Page 52 of 54
                          DATA HANDLING (Page 1  of 2)
               Item
                                             Yes
                                                 No
Comment
Does data clerk check all input to the
computer for accuracy?

Are calculations checked by another person?

Are calculations documented?

Does strip chart reduction by on-line
electronic digitization receive at least
5% manual spot checking?

Are data from manually interpreted strip
charts spot-checked after initial entry?

Do laboratory records include the following:

      -Sample identification number

      -Sample type

      -Date sample received in laboratory

      -Date of analysis

      -Analyst

      -Result of analysis (including raw
        analytical data)

      -Recipient of the analytical data

Does laboratory follow required sample
tracking procedures from sample receipt
to discard?

Does the data clerk routinely report
quality control data sheet information
to the analyst?

Does the data clerk submit quality
control data sheet information to the
laboratory manager, along with the
analytical data to be reported?

Do records indicate corrective action
taken?

Are provisions made for data storage for
all raw data, calculations, quality
control data, and reports?

Are all data and records retained the
required amount of time?

Are computer printouts and reports
routinely spot-checked against laboratory
records before data are released?

-------
                                                                Appendix F
                                                                Revision 1
                                                                Date: 4/89
                                                                Page 53 of 54
                             SUMMARY (Page 1 of 2)
               item
Yes
No
Comment
Do responses to the evaluation indicate that
project and supervisory personnel are aware c
QA and its application to the project?
Do project and supervisory personnel place
positive emphasis on QA/QC?

Have responses with respect to QA/QC aspects of
the project been open and direct?

Has a cooperative attitude been displayed by all
project and supervisory personnel?

Does the organization place the proper emphasis
on quality assurance?

Have any QA/QC deficiencies been discussed before
leaving?

is the overall quality assurance adequate to
accomplish the objectives of the project?

Have corrective actions recommended during
previous evaluations been implemented?

Are any corrective actions required?  If so,
list the necessary actions below.

-------
                                                                  Appendix F
                                                                  Revision 1
                                                                  Date: 4/89
                                                                  Page 54 of 54
                              SUMMARY (Page 2 of 2)
Summary Comments  and Corrective Actions

-------
                                                                         Appendix G
                                                                         Revision 1
                                                                         Date: 4/89
                                                                         Page 1 of 18
                                   Appendix G

                   Field Data  Verification Procedures
       The following verification scheme represents the checks and flags that are applied to the
pedon characterization data. After a pedon description undergoes verification, flagged data are
identified on forms and are sent to the appropriate sampling crews for confirmation or
correction. The corrections are edited into the data base and the verification program is applied
to the data base to assign the final verification flags.

-------
                                                                   Appendix G
                                                                   Revision 1
                                                                   Date: 4/89
                                                                   Page 2 of 18


          SCS-SOI-232 FIELD DATA VERIFICATION PROCEDURES  (10/19/88)

                          MID-APPALACHIAN SOIL SURVEY

These procedures are strictly related to computer verification programs.
other verification procedures are discussed in the QA Plan.  Parameters that
may be left blank will be denoted by a '*' symbol.  All other parameters
should be filled in; if not, they are flagged.

The first test of each parameter is usually to determine whether the value in
that parameter is missing.  In SAS, a non-numeric character can not be placed
in a parameter that has been identified for numeric values and will therefore
be considered a missing .  If a value for a parameter is considered missing
and flagged AO, the other tests on the particular parameter will not be run.

The field data flag codes are as follows:

      FLAG  FLAG DESCRIPTION

      AO    value missing
      BO    invalid code
      CO    non-numeric character in numeric field
      DO    non-alphabetic character in alpha field
      EO    correlation outlier
      FO    value inappropriate
              NAME  -  can be left alone
              SITE ID

ERL-C will provide a list of the valid STATE/COUNTY/UNIT combinations for each
pedon. This combination will be called SITE_ID.  If the combination on the 232
does not match an ERL-C combination or the combination has already been used
flag, flag SITE_ID BO

STATE (SA_ST) alpha
If SA_ST code is missing, flag AO
If SA_ST not equal to PA, VA, WV, flag BO
If SA_ST code contains a numeral, flag DO

COUNTY (SA_CO) - numeric
If SA_CO code missing, flag AO
If SA_CO code contains alpha character, flag CO

UNIT (SA_UN) - numeric
If SA_UN code missing, flag AO
if SA_UN code contains alpha character, flag CO

* sub (SUB__UNS) - Leave alone

-------
                                                                   Appendix G
                                                                   Revision 1
                                                                   Date: 4/89
                                                                   Page 3 of 18
              MLRA

MLRA and SUBMLRA must be  linked. MLRA may  or may  not contain SUBMLRA.   MLRA
and SUBMLRA must also be  correlated with the STATE  codes

MLRA - numeric

If MLRA code missing, flag AO
* SUB (MLRA_S) - alpha               (see  MLRA)
If MLRA_S contains numeric characters,  flag DO

The following are MLRA &  MLRA_S codes that apply  to each  STATE:

      PA       VA          WV
      127      128         127
      140      130         128
      147      147
               148

If MLRA is not a valid code for the STATE, flag BO


              LATITUDE

LAT - numeric
If LAT code is missing, flag AO

LAT_DR - alpha
if LAT_DR is missing, flag AO
If LAT_DR does not equal  to "N", flag BO
If LAT_DR contains numeric characters,  flag DO


              LONGITUDE

LNG - numeric - Same flags as LAT
LNG_DR - alpha
if LNG_DR code missing, flag AO
If LNG_DR code does not equal to "W", flag BO
If LNG_DR  contains numeric characters, flag DO


              SLOPE

SL_PCT - numeric
If SL_PCT code is missing, flag AO
If SL_PCT contains alpha characters, flag CO

SL_SHPU/SL_SHPA - numeric
If SL_SHP code is missing, flag AO
If SL_SHP does not equal to a number from  1-5,  flag BO

-------
                                                                   Appendix G
                                                                   Revision 1
                                                                   Date: 4/89
                                                                   Page 4 of 18
SL_GMP - numeric (see gm codes for values)
If SL_GMP code is missing, flag AO
If SL_GMP does not equal to 1,2,3,4, flag BO

SL_HILL - numeric
If SL_HILL code is missing, flag AO
If SL-HILL does not equal 1,2,3,4,5 flag BO

SL_ASP - numeric
If SL_ASP code is missing and PED_O does not equal H, flag AO
If PED_0 does not equal H, then SL_ASP must equal 0, 45, 90, 135, 180, 225,
270, 315 if not flag BO
If PED_O equals H, then SL_ASP can be blank
SL_LEA - numeric
If SL_LEA code missing, flag AO
If SL_LEA contains alpha characters, flag CO

SL_LET - numeric
If SL_LET code missing, flag AO
If SL_LET < SL_LEA, flag EO
IF SL_LET contains alpha characters, flag CO

SL_KND - alpha
If SL_KND code is missing, flag AO
If SL_KND does not equal B,C,F,G,L,M,T,Z, flag BO
If SL_KND contains numeric characters, flag DO

SL_VAR - numeric
If SL_VAR code is missing, flag AO
If SL_VAR does not equal a number from 0,1,2,4, flag BO

SL_PAT - numeric
If SL_PAT code is missing, flag AO
If SL_PAT does not equal a number from 0-3, flag BO

SL_POS - numeric
If SL_POS code is missing, flag AO
If SL_POS does not equal a number from 2,3,4,5,7,8,9, flag BO
if SL_POS contains an alpha character, flag CO

PG_REG - alpha (major landform for codes)
If PG_REG code is missing, flag AO
If PG_REG does not equal a specified code, flag BO

PG_LOC - alpha     (see local landform for codes)
If PG_LOC code is missing, flag AO
If PG_LOC does not equal a specified code, flag BO
If PG LOG contains a numeric character, flag DO

-------
                                                                    Appendix G
                                                                    Revision 1
                                                                    Date: 4/89
                                                                    Page 5 of 18


               PEDON  CLASSIFICATION

 This  values  will  be hand checked against soil series name

 *  Precip  (PREC) - leave  alone


        WATER TABLE

 *WT_DPT -  numeric.
 If WT_KND  is zero,  WT_DPT should be blank;  if not,  flag BO
 If WT_KND  is not  zero and WT_DPT is missing,  flag AO

 WT_KND - numeric
 If WT_KND  does not  equal a number 0,2,3,4,  flag BO
 If WT_KND  is missing,  flag AO
 If WT_KND  contains  alpha characters,  flag CO

 WT_DAY - numeric
 IF WT_KND  filled  in,  WT_DAY should have  code;  if not,  flag AO
 IF WT_KND  not equal to a number  between  1-365,  flag FO

 LU_CLS - alpha
 If LU_CLS  code is missing,  flag  AO
 If LU_CLS  does not  equal A,C,E,F,G,H,I,J,L,N,O,P,R,S,T,U,Q,
 flag  BO
 If LU_CLS  contains  a numeric character,  flag  DO

 SN_CLS - numeric
 If SN_CLS  code is missing,  flag  AO
 If SN_CLS  does not  equal a number from 0-5, flag BO

 If SN_CLS  contains  an alpha character, flag CO

 BA_PRM - numeric
 If BA_PRM  code is missing,  flag  AO
 If BA_PRM  does not  equal a number from 1-7, flag BO
 If BA_PRM  contains  an  alpha character, flag CO

 Texture classes from coarse to fine  are  listed  below.  Scan TT_CLS1  and
 TT_CLS2,  find  which  code on the  232  is che lowest on the  listT The  numbers to
 the right  should  be  the  corresponding PERM code,  if not,  flag PERM  with EO

 TT_CLS       PERM

 COS
 S
FS
VFS          6-7
LCOS
LS

-------
                                                                   Appendix G
                                                                   Revision 1
                                                                   Date: 4/89
                                                                   Page 6 of 18
LFS
LVFS
COSL
SL
FSL
VFSL
L
SIL          3-5
SI
CSCL
SCL
CL
SICL
SC

SIC
C           1-2
DR_CLS (numeric)
If DR_CLS code is missing, flag AO
If DR_CLS does not equal a number from 1-7, flag BO
If DR_CLS contains an alpha character, flag CO
If SL_PCT > 15 and PERM = 1-4; DR_CLS should = 1-5; else flag EO
If SL_PCT > 15 and PERM = 5-7; DR_CLS should - 4-7; else flag EO

Elevation (ELEV) - numeric information should be right justified
                   with leading zeros on the left.
If ELEV code is missing, flag AO


              PARENT  MATERIAL

For this category only 1 entry for the parameters PM_WTHl, PM_DEPl, PM_Bl,
PM_ORGl is needed.

PM_B1 (2,3,4) - numeric
If PM_Bl code is missing, flag AO
If PM_B1 does not equal 1,2,3, flag BO

PM_DEP1 (2,3,4) - alpha
If PM_DEPl (2,3,4) code is missing, flag AO
If PM_DEP1 does not equal A,S,L,V,R,E,D,M,U,H,G,O,X,W,T,Y,F,
flag BO
If PM_DEPl contains a numeric character, flag DO

PM_ORG1 (2,3,4) alpha in first column, numeric in second
If PM_ORGl code is missing, flag AO
PM_ORG1 If 1st column is not alpha, flag DO
        If 2nd column is not numeric, flag CO

* PM BRK - numeric

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                                                                   Appendix G
                                                                   Revision 1
                                                                   Date: 4/89
                                                                   Page 7 of 18


If PM_BRK does not equal a number from 1-5, flag BO
if PM_BRK contains an alpha character, flag CO

                                               •
              TEMPERATURES

All parameters can be left alone


              MOISTURE REGIME

MREG - alpha
If MREG code ia missing, flag AO
If MREG does not equal UD or AQ, flag BO
If MREG contains numeric values, flag DO


              WEATHER STATION NUMBER

Can be left alone


              CONTROL SECTION

CS_DPU - numeric
If CS_DPU value is missing, flag AO
If CS_DPU not less than CS_DPL, flag EO

CS_DPL - numeric
If CS_DPL value is missing, flag AO

If control section data is missing the following correlation will not  be
executed

CS_DPU & CS_DPL are checked together for the following conditions:

Control section rules for MASS when TT_ORD other than H, or
when HZ_MST not « B and H2_SFX not = l7 2£ when HZJSFX, HZ_MST not = R

1) if depth (HZ_DPL from page 2) of last horizon above any horizon where
   HZ_MST="R" is greater than 100; CS_DPU = 025 and CS_DPL = 100

2) if HZ_DPL of last above any horizon where HZ_MST-"R" is greater than 36 and
   less than 100; CS_DPU « 025 and CS_DPL » HZ_DPL of last horizon above
   horizon where HZ_MST = -R"

3) If HZ_DPL of last horizon above any horizon where HZ_MST="R" is less than
   36; CS_DPU = 000 and CS_DPL « HZ_DPL of last horizon~"horizon where  HZ_MST =
   "R-

If rule is not followed, flag EO where problem occurs

-------
                                                                   Appendix G
                                                                   Revision 1
                                                                   Date: 4/89
                                                                   Page 8 of 18
If HZ MST or TX ORD is H then:
1) If HZ_DPL of last horizon with a HZ_MST of O is greater than 130 CS_DPU  -
   000 and CS_DPL = 130

2) If HZ_DPL of last horizon with a HZ_MST of O is less than 130 CS_DPU - 000
   and CS_DPL = HZ_DPL of last horizon with HZ_MST of O

If rule is not followed, flag EO where problem occurs

If HZ_MST = B and HZ_SFX = T then:

CS_DPU = HZ_DPU of 1st Bt horizon and CS_DPL = CS_DPU + 50 if, when the 50  is
added it is still in a Bt horizon; if not then CS_DPL = HZ_DPL of last Bt
horizon
If rule is not followed, flag EO where problem occurs

If HZ_MST or HZ_SFX = R then:

1) If HZ_DPL above any horizon where HZ_SFX of "R" occurs is greater than 100,
   CS_DPU =025 and CS_DPL = 100; or CS_DPU =025 and CS_DPL = HZ_DPL of
   horizon above where HZ_SFX = "R"

2) If HZ_DPL above any horizon where HZ_SFX="R- occurs is greater than 36 and
   less than 100, CS_DPU = 025 and CS_DPL = HZ_DPL of horizon where HZ_SFX  =
   "R"; or CS_DPU =025 and CS_DPL = HZ_DPL of horizon above where HZ_SFX = "R

3) If HZ_DPL above any horizon where HZ_SFX of "R" occurs is less than 36,
   CS_DPU = 000 and  CS_DPL = HZ_DPL of horizon where HZ_SFX = "RM; or CS_DPU
   = 000 and CS_DPL = HZ_DPL of horizon above HZ_SFX of -R-

If rule is not followed, flag EO where problem occurs

* ER_CLS -  leave alone

RNOFC - numeric 1-7
If RNOFC code is missing, flag AO
If RNOFC does not equal a number from 1-7, flag BO
If RNOFC contains alpha characters, flag CO


              DIAGNOSTIC  FEATURES

If TX_ORD is equal to "E" code, a diagnostic feature is not needed

If TX_ORD is not equal to "E", one set of diagnostic features (DF_DPU1,
DF_DPL1, DF_KND1) should be entered, if not flag DF_DPUl, DF_DPLl, DF_KNDl  AO


DF_DPU1 (2,3,4,5) - numeric
If DF_DPU1 etc.is not less than DF_DPLl etc., flag BO

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                                                                   Appendix G
                                                                   Revision 1
                                                                   Date: 4/89
                                                                   Page 9 of 18


DF_DPL1 (2,3,4,5) - numeric
If DF_DPL1 etc. > DF_DPU2, flag EO

DF_KND1 (2-5) - alpa (see KND codes)
If DF_KNDl etc. does not contain appropriate codes, flag BO
If DF_KND1 etc. contains a numeric character, flag DO


              FLOODING

FL_FRQ - alpha
If FL_FRQ is missing, flag AO
If FL_FRQ does not contain codes NO,RA,OC,FR,CO, flag BO
if FL_FRQ contains numeric characters, flag DO


              PONDING

PO_FRQ - alpha
IF PO_FRQ is missing, flag AO
IF PO_FRQ does not contain codes NO,RA,OC,FR,CO, flag BO
IF PO_FRQ contains numeric characters, flag DO


              VEGETATION

Leave alone - manually checked


              DEPTH

HZ_DPU - numeric
If HZ_DPU is missing, flag AO

HZ	DPL — numeric
IF HZ_DPL is missing from any horizon but the last, flag AO
If HZ_MST = "R", HZ_DPL should be blank; if not, flag BO

AS you proceed from one horizon to the next, HZ_DPL must be equal to  HZ_DPU  of
the horizon below.


                   example

          horz      depth
                    000 HZ_DPU
           01
                    005 HZ DPL
                    005 HZ_DPU
           02
                    025 HZ DPL

-------
                                                                   Appendix G
                                                                   Revision 1
                                                                   Date: 4/89
                                                                   Page 10 of 18
If this rule is not followed, flag HZ_DPU EO
              HORIZON  DESIGNATION

* HZ_DSC - numeric
If HZ_DSC is blank, it is assumed to be "1". Numbering starts at "2- with the
second layer of contrasting material.

If HZ_DSC equals "1", flag BO
The first non-blank HZ_DSC must be a "2", if not, flag BO
Each proceeding HZ_DSC must be >= the previous HZ_DSC, if not flag the first
HZ_DSC where anomoly occurs EO

HZ_MST - alpha
If HZ_MST code is missing, flag AO
If HZ_MST does not contain a letter O,A,E,B C,R, or a combination of these
letters, flag BO
If HZ_MST contains numeric values, flag DO

* HZ_SFX - alpha-numeric
If alpha characters not = to A,B,C,E,F,G,I,K,M,N,O,P,R,S,T,V,W,H,X,Y,Z, Flag
BO
              THICKNESS

HZ_AVG - numeric
If HZ_AVG value is missing, flag AO
IF HZ_AVG is not > HZ_MIN and <= HZ_MAX, flag EO

HZ_MAX - numeric
If HZ_MAX value is missing, flag AO
If HZ_MAX is not > HZ_MIN & HZ_AVG, flag EO

HZ_MIN - numeric
If HZ_MIN value is missing, flag AO
If HZ_MIN not < HZ_MAX & HZ_AVG, flag EO
If HZ MIN > difference of HZ DPU and HZ DPL of same horizon, flag EO
              DRY  COLOR

If one parameter is filled in, all others on that line of the horizon under
this heading, with the possible exception of DC_PCT should be filled in for
that horizon; if not flag AO for that parameter

* DC_LOC1 (2,3) - numeric 0-3
If DC_LOCl etc. not = to numbers from 0-3, flag BO
If DC_LOC1 etc. contains an alpha character, flag CO

* DC PCTl (2,3) - numeric

-------
                                                                   Appendix G
                                                                   Revision 1
                                                                   Date: 4/89
                                                                   Page 11 of 18


There are three lines for each horizon. If the same  DC_LOC  code  is used  on
more than one line for a horizon then a percent must be placed in DC_PCT, if
not flag DC_PCT where problem occurs AO

The DC_PCT for a horizon containing the same DC_LOC  must  add
to 90% - 100% if not, flag DC_PCT EO

                         example

         DC_LOC    DC_PCT
           1         25
           1         75
           2         *

*  this parameter can be left blank because the DC_LOC value  is  used only once
   for this horizon.

*  DC_HUE1 (2,3) - alpha-numeric
If numeric part of hue > 10, flag AO
If numeric part not equal to 0, 2.5, 5, 7, 7.5, 10,  flag  BO

*  DC_VAL1 (2,3) - numeric

*  DC_CHR1 (2,3) - numeric


              MOIST  COLOR

If H2_MST = "O" or "R" or HZ_SFX = "R" ; MC_LOC, MC_HUE, MC_VAL,
MC_CHR does not need to be filled in. All other horizons  must have at least
one  MC_LOC, MC_HUE, MC_VAL,MC_CHR else flag AO.

* MC_LOC1 (2,3)
* MC_PCT1 (2,3)
* WC_HUE1 (2,3)
* MC_VAL1 (2,3)
* MC_CHR1 (2,3)

There are three lines for each horizon. If the same  MC_LOC  code  is used  on
more than one line for a horizon then a percent must be placed in MC_PCT, if
not flag MC_PCT where problem occurs AO

The MC_PCT for a horizon containing the same MC_LOC  must  add
to 90% - 100% if not, flag MC_PCT EO


              TEXTURE

class (TT_CLS1 & TT_CLS2) - alpha (see texture codes)
If HZ_MST does not equal "O" or "R" or HZ_SFX does not equal  "R"  TT_CLS1  or
TT_CLS2 must be filled in;  if not, flag AO

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                                                                   Appendix G
                                                                   Revision 1
                                                                   Date: 4/89
                                                                   Page 12 of 18


If TT_CLSl or TT_CLS2 does not contain the proper code, flag BO
If TT_CLSl or TT_CLS2 contains numeric characters, flag DO

If HZ_MST equals "O" or "R" or HZ_SFX equals "R"; TT_CLS1 and TT_CLS2 does not
need to be entered.

     This next program will have to wait until analytical
               data is available

There will be a correlation between the texture class codes and the particle
size measurements from the analytical laboratories. The following texture
classes are defined by this information which should correspond to the
analytical particle size information.


              Texture Codes

Sands - 85 percent or more sand and a percentage of silt plus 1.5 times the
percentage of clay is 15 or less. The following codes are classified under
this category:

         1) COS   2) S   3) FS   4) VFS

Loamy sands - At the upper limit 85 to 90 percent sand and the percentage of
silt plus twice the percentage of clay exceeds 30; or less than 7 percent
clay, less than 50 percent silt, and between 43 and 52 percent sand.  The
following codes are classified under this category:

         1) LCOS   2) LS   3) LFS   4) LVFS

Sandy Loams - 20 percent or less clay and 52 percent or more sand and the
percentage of silt plus twice the percentage of clay exceeds 30; or less than
7 percent clay, less than 50 percent silt, and between 43 and 52 percent sand.
The following codes are classified under this category:

         1) COSL   2) SL   3) FSL   4) VFSL

Loam (L)- 7 to 27 % clay, 28 to 50 % silt, and less than 52 % sand.

silt Loam (SIL) - 50 % or more silt and 12 to 27 % clay; or 50 to 80 %  silt
and less than 12 % clay.

Sandy Clay Loam (SCL) - 20 to 35% clay, less than 28% silt, and 45% or  more
sand.

Silt (SI) - 80 % or more silt and less than 12 % clay.

clay Loam (CL) - 27 to 40 % clay and 20 to 45 % sand.

silty clay Loam (SICL) - 27 to 40 % clay and less than 20 % sand.

Sandy Clay (SC) - 35 % or more clay an 45 % or more sand.

-------
                                                                   Appendix G
                                                                   Revision 1
                                                                   Date: 4/89
                                                                   Page 13 of 18
Silty Clay (SIC) - 40 % or more clay and 40 % or more silt.

Clay (C) - 40 % or more clay, less than 45 % sand, and less than 40 %  silt.

* MOD (TT_MOD1 & TT_MOD2) - alpha (see modifier codes)
If TT_MODl or TT_MOD2 does not contain a correct code, flag BO
If TT_MODl or TT_MOD2 contain numeric characters, flag DO

The modifiers are based on % and size of rock fragments  (page 4)
     RF_PCT
      15-35
RF_PCT
 36-60
RF_PCT
  >60
modifier
BY
ST
CB
CN
CR
FL
GR
SH
SY
GY
CBA
CRC
GRF
GRC
misc.
SR CY
AY MK
RB PT
size
4
3
2
5
1-3
2-3
1
1-3
1-3
1
2
1-3
1
1




modifier
BYV
STV
CBV
CNV
CRV
FLV
GRV
SHV
SYV
GYV








size
4
3
2
5
1-3
2-3
1
1-3
1-3
1








                                        modifier
                                             BYX
                                             STX
                                             CBX
                                             CNX
                                             CRX
                                             FLX
                                             GRX
                                             SHX
                                             SYX
                                             GYX
                           size
                              4
                              3
                              2
                              5
                             1-3
                             2-3
                              1
                             1-3
                             1-3
                              1
For example, if a texture modifier of "BYV" is used in the third horizon,
there must be rock fragments of size class three and a percentage  (RF_PCT)
between 35-60 in the same horizon; if not,    flag TT MODI or TT MOD2 with EO,
              STRUCTURE

SR_GRD1 (2,3), SR_SHP1 (2,3), SR_SIZl (2,3) - only one matrix needs to be
entered; the others may be left blank.

SR_GRD1 (2,3), SR_SHP1 (2,3), SR_SIZl (2,3) CS_DRY, CS_MST, CS_OTH, CS_STK,
CS_PLC - IF the horizon sequence number equals "1" and the HZ_MST equals "O"
or HZ_MST equals "R", none of the parameters indicated need values entered in
any of these fields.

SR_GRD1 (2,3) - numeric
if SR_GRDI etc. code is missing, flag AO
If SR_GRD1 etc. not equal to numbers from 0-6, flag BO
If SR_GRD1 etc. contains alpha characters, flag CO

-------
                                                                   Appendix G
                                                                   Revision 1
                                                                   Date: 4/89
                                                                   Page 14 of 18


* SR_SIZ1 (2,3) - alpha
If SR_GRD1 etc. equals "0", SR_SIZ must be blank; if not, flag BO
If SR_GRD1 etc. does not equal "0", SR_SIZ must not be blank; else flag AO
If SR_SIZ1 etc. not equal to  EF,VF,FF,F,FM,M,MC,CO,VC,CV,TK,TN, VK,VN, flag
BO
If SR_SIZ1 etc. contains numeric characters, flag DO

SR_SHP1 (2,3) - alpha
If SR_SHP1 etc. is code missing, flag AO
If SR_GRD1 etc. equals "0", then SR_SHP must equal "MA" or "SGR"; if not,  flag
BO
If SR_SHP1 etc. does not equal PL,COL,SBK,CR,WEG,LP,BK,
GR,MA,PR,ABK,CDY,SGR, flag BO
If SR_SHPl etc. contains numeric characters, flag DO


              CONSISTENCE

One of these parameters must be filled in for each horizon. The others  may be
blank; if not, flag all parameters with AO

* CS_DRY - alpha
If CS_DRY does not equal L,S,SH,H,VH,EH, flag BO
If CS_DRY contains numeric character, flag DO

* CS_MST - alpha
If CS_MST does not equal L,VFR,FR,FI,VFI,EFI, flag BO
If CS_MST contains numeric characters, flag DO

* CS_OTH - alpha
If CS_OTH does not equal WSM,SM,MS,B,R,VR,CO,VWC,WC,SC,I,SF,VF,SD flag  BO
If CS_OTH  contains numeric characters, flag DO

* CS_STK - alpha
If CS_STK does not equal SO,SS,S,VS, flag BO
If cs_STK contains numeric characters flag DO

* CS_PLC - alpha
If CS_PLC does not equal PO,SP,P,VP, flag BO
If CS_PLC contains numeric characters, flag DO


              MOTTLES
If one parameter  is filled in, all others in that line of the horizon  under
this heading should be filled in;  if not, flag AO for the missing parameter


* MO_AMT1 (2,3) - alpha
If MO_AMT1 etc. does not equal F,C,M, flag BO
If MO AMTl etc. contains numeric characters flag DO

-------
                                                                   Appendix G
                                                                   Revision 1
                                                                   Date: 4/89
                                                                   Page 15 of 18


* MO_SIZ1 (2,3) - numeric
If MO_SIZ1 etc. does not equal 1,2,3,12,13, flag BO
If MO_SIZl etc. contains alpha characters, flag CO

* MO_CON1 (2,3) - alpha
If MO_CON1 etc. does not equal F,D,P, flag BO
If MO_CONl etc. contains a numeric character, flag DO

* MO_HUE1 (2,3) - alpha-numeric
if numeric portion of MO_HUE > 10, flag BO

* MO_VAL1 (2,3) - numeric
If MO_VALl contains alpha characters, flag CO

* MO_CHR1 (2,3) - numeric
If MO_CHRl contains alpha characters, flag CO


         SURFACE  FEATURES

If one parameter is filled in, all others on that line of the horizon,  with
the exception of SF_HUE, SF_VAL and SF_CHR, should be filled in; if not, flag
AO for the missing parameter.

* SF_KND1 (2,3) - alpha
If SF_KND1 etc. does not = U,B,D,I,Q,L,M,S,X,A,C,G,K,P,O,T,
flag BO
If SF_KNDl etc. contains a numeric character, flag DO

* SF_AMTl (2,3) - alpha
If SF_AMT1 etc. does not equal V,F,C,M, flag BO
If SF_AMTl etc. contains a numeric character, flag DO

* SF_DCN1 (2,3) - alpha
If SF_DCN1 etc. does not equal P,D,C, flag BO
If SF_DCNl etc. contains a numeric character flag DO

* SF_DST1 (2,3) - alpha
If SF_DST1 etc. does not equal F,D,P, flag BO
If SF_DSTl etc. contains a numeric character, flag DO

* SF_LOC1 (2,3) - alpha
If SF_LOC1 etc. does not equal P,H,V,Z,U,L,C,M,S,B,R,I,F,T,N, flag BO
If SF_LOCl etc. contains a numeric character, flag DO

* SF_HUE1 (2,3) - alpha-numeric
If numeric portion of SF_HUE >10, flag BO

* SF_VAL1 (2,3) - numeric
If SF_VALl contains alpha characters, flag CO

-------
                                                                   Appendix G
                                                                   Revision 1
                                                                   Date: 4/89
                                                                   Page 16 of 18


* SF_CHR1 (2,3) - numeric
If SF_CHRl contains alpha characters, flag CO


              BOUNDARY

if BD_DST and BD_TPG filled in for last horizon, flag FO

BD_DST - alpha
if BD_DST not  filled; except for last horizon, flag AO
if BD_DST does not contain A,C,G,D, flag BO
If BO_DST contains a numeric character, flag DO

BD_TPG - alpha
If BDJTPG not filled; except for last horizon, flag AO
If BD_TPG does not equal S,W,I,B, flag BO
If BD_TPG contains a numeric character, flag DO


              EFFERVESCENCE

Leave alone


              FIELD  MEASURED  PROPERTIES

FP_KND1 (2-6) - alpha-numeric
If HZ_MST not equal to -O" or "R" or HZ_SFX not equal to "R" and FP_KNDl (2-3)
code missing, flag AO
If FP_KNDl does not equal CL,PB,PC,PG,PH,PL,PP,PR,PS,PT,PY,SA,SC,
SF,SI,SM,SV,OB,OR, flag BO
if FP_KNDl etc. contains  numeric characters flag DO

FP_AMTl (2-6) - numeric -(no decimals).
If HZ_MST not equal to "O" or "R- or HZ_SFX not equal to -R" and FP_AMTl (2,3)
code missing, flag AO
if FP_AMT contains decimals, flag BO
If FP_AHT contains alpha characters, flag CO

A correlation can be run between field pH for a horizon and the corresponding
analytical laboratory pH.


                 WETNESS

SM_AMT1 - alpha
If HZ_MST not equal to "O" or -R"and SM_AMTl missing, flag AO
If SM_AMT1 etc. does not equal D,M,W, flag BO
If SM_AMTl etc. contains numeric values, flag DO

-------
                                                                   Appendix G
                                                                   Revision 1
                                                                   Date: 4/89
                                                                   Page 17 of 18
                  HYDRAULIC CONDUCTIVITY

SM_AMT2 - numeric
if SM_AMT2 code is missing, flag AO
If SM_AMT2 does not equal 1-7, flag BO
If SM_AMT2 contians alpha values, flag


              ROOTS

If one parameter is filled in, all others on that line should also be filled
in; if not, flag the unfilled areas AO

* RO_AMT1 (2,3) - alpha
If RO_AMT1 (2,3) does not equal VF,FF,F,FC,CM,C,M, flag BO
If RO_AMT1 (2,3) contains numeric values, flag DO

* RO_SIZ1 (2,3) - alpha-numeric
If RO_SIZ1 (2,3) does not = VI,11,1,12,2,23,3,13, flag BO

* RO_LOC1 (2,3) - alpha
If RO_LOC1 (2,3) does not equal C,P,T,M,S, flag BO
If RO_LOC1 (2,3) contains a numeric character, flag DO

Roots should not skip horizons i.e. if there are roots in horizon 2 and  4,
there must be roots in horizon 3; if not, flag the three root categories of
the suspect horizon EO.


              PORES

If one parameter is filled in, all others on that line should also be filled
in; if not, flag the unfilled areas AO

* PO_SHP1 (2,3) - alpha
If PO_SHP1 (2,3) does not = IR,IT,TU,TD,TS,VT,IE,IF,TC,TE,
VS,TP, flag BO
If PO_SHP1 (2,3) contains numeric characters, flag DO

* PO_AMT1 (2,3) - alpha
If PO_AMT1 (2,3) does not equal VF,FF,F,FC,CM,C,M, flag BO
If PO_AMT1 (2,3) contains numeric characters, flag DO

* PO_SIZ1 (2,3) - alpha-numeric
If PO_SIZ1 (2,3) does not equal VI,11,1,12,2,23,3,13, flag BO

* PO_CN1 (2,3) - alpha
If PO_CN does not equal L,M,H, flag BO
If PO CN contains numeric characters, flag DO

-------
                                                                   Appendix G
                                                                   Revision 1
                                                                   Date: 4/89
                                                                   Page 18 of 18
              CONCENTRATIONS
If one parameter is filled in, all others on that line should also be filled
in; if not, flag the unfilled areas AO

* cc_KNDl (2,3) - alpha-numeric (see table kinds of concentrations for values)
If 1st column is not alpha, flag DO
If 2nd column is not numeric, flag CO
if CC_KND1 (2,3) is not a correct value, flag BO

* CC_AMT1 (2,3) - alpha
If CC_AMT1 (2,3) does not equal VF,FF,F,FC,CM,C,M, flag BO
If cc_AMTl (2,3) contains numeric values, flag DO

* CC_SHPl (2,3) - alpha
If CC_SHP1 (2,3) does not equal C,D,0,P,T,Z, flag BO
if CC_SHP1 (2,3) contains a numeric character, flag DO

* CC_SIZl (2,3) - numeric
If CC_SIZ1 (2,3) does not equal 1,12,2,23,3,4,5,34,45, flag BO
if CC_SIZ1 (2,3) contains alpha characters, flag CO


              ROCK  FRAGMENTS

if one parameter is filled in, all others on that line of the horizon should
be filled in, if not, flag the missing parameters AO.

* RF_KNDl (2-6) - alpha
If RF_KND does not equal Y,S,A,H,K,O,I,B,T,P,F,M,L,E,R, flag BO
if RF_KND contains numeric characters, flag DO

* RF_PCT1 (2-6) - numeric

* RF_SIZl (2-6) - numeric
if RF_SIZ1 does not equal a number from 1-6, flag BO
if RF_SIZ1 contains alpha characters, flag CO

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                                                                       Appendix H
                                                                       Revision 1
                                                                       Date: 4/89
                                                                       Page: 1 of 12
                                  Appendix H

          Preparation Laboratory Verification Procedures
     The following verification procedures are applied to the soil samples received, processed, and
analyzed at the preparation laboratory.  The computer program is used to track the progress of
sample preparation, calculate final values from the raw data, and identify erroneous data.  The
flags are applied only to the preparation laboratory data and are unrelated to similarly-defined flags
in the analytical laboratory data.

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                                                                   Appendix H
                                                                   Revision 1
                                                                   Date: 4/89
                                                                   Page: 2 of 12
    PREPARATION LABORATORY COMPUTER ENTRY/TRACKING/VERIFICATION PROCEDURES


     The  following  text provides  an overview  of the  computer  tracking and
verification program designed for use at the preparation laboratory during the
DDRP Mid-Appalachian soil Survey.   The system is designed to track the progress
of samples,  calculate final data values,  perform verification checks, and assign
flags to any detected aberrant values.

     The program creates the Form 101 that summarizes  final data reported by the
preparation  laboratory.   Hard  copies   of  this  form are  sent  to  all  DDRP
cooperating agencies and groups. In addition,  the Form 101 is available  on floppy
disk. .
SAMPLE TRACKING

     The  preparation  laboratory manager must track samples as they are received
from the sampling crews, during cold storage,  through processing and analysis,
and during  batch  formation and shipment to the  analytical  laboratories.   The
computer data are used to track the location and progress of each sample while
it is physically at the laboratory.

     in order to  track the sampling  activities  and shipment/receipt  of bulk
samples,  the following information is to be reported to the QA manager weekly:

         number of samples received
         number of pedons sampled and percentage of total expected
         number of sets received

     In order to track the progress of the preparation activities, the following
information is to be reported to the QA manager weekly:

         number and percent of samples that have completed specific analyses
         number of bulk samples which are completely processed (excluding bulk
         density) and are ready to be batched
     —  number of sets that have been completed
         number of batches sent to analytical laboratories


DATA VERIFICATION

     The  system allows the entry and editing of data by preparation laboratory
personnel and the review of progress and data analysis by the QA staff.  After
a run  of data is entered  into  a  "temporary"  data file,  the  final values are
calculated  and  verified.   A  printout of this  information is checked by the
preparation laboratory manager and by a representative from the QA staff.  The
data that have satisfied the verification criteria are then moved into a  "master"
data file which is used to track progress and percentages of the analyses that
have been completed.   The master file cannot be edited by preparation laboratory
personnel.

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                                                                   Appendix H
                                                                   Revision 1
                                                                   Date: 4/89
                                                                   Page: 3 of 12
     The five raw data  forms  that  are  entered into the computer are:  (1) sample
receipt raw data form,  (2) clod bulk density raw data form, (3) known volume bulk
density raw data form, (4) loss on ignition raw data form, and (5) bulk sample
processing raw data form.   In the descriptions of the forms below,  a list of the
data calculations,  verification checks, and pertinent  verification flags are
included.  At the beginning of  each description  is a  list of  the data from each
particular form which must be  transferred  to the  Form 101.  The flags consist
of two  characters,  an alpha character  and a  numeric character.   The numeric
character designates which data form the flag pertains to, e.g.,  a  flag with the
numeric character "3" pertains to the known volume raw data  form.


SUMMARY OF VERIFICATION FLAGS

Sample Receipt Raw Data Form

Al   Missing data on form
Bl   Sample code mislabeled
Cl   site ID mislabeled
Dl   More than 2 known  volume samples
El   More than 3 clods

Clod Bulk Density Raw Data Form

A2   Missing data on form
B2   Submerged clod weight >  Lab clod  weight, and  clod did not float
C2   clod floated
D2   Problem clod (deletes value from  average)
E2   Oven-dry clod weight  > Lab clod weight
F2   Oven-dry clod weight  > Field-moist  clod weight
G2   Coefficient of variation > 20 among replicates
H2   Bulk density > 2.0
12   Bulk density < 1.0
J2   Sample code not recorded same as  on sample  receipt  form
K2   Number of replicates  not recorded same as on  sample receipt  form
L2   Replicates > 3

Known Volume Bulk Density Raw Data Form

A3   Missing data on form
B3   Oven-dry weight >  Air-dry  weight
C3   Weight of fines +  Rock fragments  >  Air-dry  weight
D3   Sample code not recorded same as  on sample  receipt  form
E3   Number of replicates  not recorded same as on  sample receipt  form
F3   Bulk density > 2.0
G3   Bulk density < 1.0
H3   Coefficient of variation > 20 among replicates
13   Impossible value because of error in raw data

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                                                                   Appendix H
                                                                   Revision 1
                                                                   Date: 4/89
                                                                   Page: 4 of 12
Loss on ignition Raw Data Form

A4   Missing data on form
B4   Organic matter > 100%
C4   Oven-dry weight > Air-dry weight
D4   Ashed weight > Oven-dry weight
E4   Sample code not recorded same as on sample receipt form
F4   Sample analysis duplicated
G4   Organic soil type not correlating
H4   Mineral soil type not correlating
14   Internal duplicate/routine pair > 15% RSD
J4   FAP samples > 15% RSD
K4   Field duplicate/routine sample > 20% RSD
L4   FAL sample outside accuracy window
M4   FAP sample outside accuracy window
N4   Manager's sample outside accuracy window

        nple Processing Raw Data Form

A5   Missing data on form
B5   Mineral soil air-dry moisture > 2.5%
C5   Organic soil air-dry moisture > 6.0%
D5   Field-moist pH > 6.0
E5   Sample code not recorded same as on sample receipt form
F5   Internal duplicate/routine sample > 15% RSD
G5   Field duplicate/routine sample > 20% RSD
H5   FAP samples > 15% RSD
15   pH QCCS buffer < 3.95 or > 4.05
J5   Manager's sample outside accuracy window
K5   FAP sample outside accuracy window


SAMPLE RECEIPT RAW DATA FORM

Form 101 Information;

SAM_CODE
SITE_ID
SET_ID

General;

     ERL-C provides EMSL-LV with the pedon number (state,  county,  unit)  and site
ID for each pedon to be  sampled.   This information is placed in the data base
before preparation activities begin.

     All samples received from the field and their condition are recorded on the
sample receipt raw data form and immediately entered into the data base. A file
comparison procedure is initiated, comparing the pedon number and site  ID with
the raw data  from the sample receipt form.   if  any  discrepancies  are found,
processing of the affected samples ceases until the discrepancies  are rectified.

-------
                                                                   Appendix H
                                                                   Revision 1
                                                                   Date: 4/89
                                                                   Page:5 of 12


All flags for the receipt data are unique and identified by the numeric character
H 1 H
 X •
     After all  verification  checks  for  the  sample  receipt  data  have been
satisfied, the data are sorted by set ID.  All samples  with the  same set ID will
undergo processing simultaneously.

calculations;

     No calculations are to be performed on the sample receipt  form.

Verification Flags

If any data are missing on the form; then flag Al
If sample code is mislabeled; then flag Bl
If site ID is mislabeled; then flag Cl
If more than 2 known volume samples are recorded; then flag Dl
If more than 3 clods are recorded; then flag El

     When flags other than Dl and El are generated, processing of  the  affected
samples must cease until the problem is rectified.

Reporting!

     The computer produces a printout, sorted by SET_ID and SAM_CODE, that lists
all flags assigned.


CLOD BULK DENSITY RAW DATA FORM

Form 101 Information;

BD_CLD

General;

     The clod  data  are  entered into a temporary working file.  The  verification
program should be run on a regular basis and the discrepancy printout generated.
All flags for the clod data are unique and identified by the numeric character
"2".

     After all verification checks for the  clod  data  have been satisfied,  the
data are sorted by  set ID and sample code.  All samples with the  same set ID will
undergo processing simultaneously.

Calculations;

SARAN_WT (g) =  (FIELD_DP + LAB_DP) * (LAB_WT - FLD_WT) / LAB_DP

OD_SAR (g) = SARAN_WT * 0.85

SARAN VOL (cm3)  - SARAN_WT / 1.30

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                                                                   Appendix H
                                                                   Revision 1
                                                                   Date: 4/89
                                                                   Page:6 of 12


R_FRAG VOL  (cm1) - R_FRAG / 2.47

WATER VOL (cm')  - CLOD_H2O / WT_DEN

SOIL/PORES VOL  (cm3) - WATER VOL - (R_FRAG VOL + SARAN VOL)

BD_CLD (g/cm1) - [LAB_WT - (R_FRAG + OD SARANJHT + 1.88)] / SOIL/PORES VOL - 0.20

Verification Flags;

If any parameter field is blank, except for  'COMMENTS'; then  flag A2
If CLOD_H20 > LAB_WT and FLOAT not marked  'Y'; then  flag B2
If FLOAT is marked  "Y"; then flag C2
If PROB is marked "Y"; then flag D2 (deletes value from average)
If FIELD_WT > LAB_WT; then flag E2
If CLOD_OD > FIELD_WT; then flag F2
If CV > 20; then flag G2
If BD_CLD > 2.0; then flag H2
If BD_CLD < 1.0; then flag 12
If a SAM_CODE does  not match the receipt file; then  flag J2
if REP does not match the receipt file; then flag K2
If REP > 3; then flag L2

Reporting;

     For  each SAM_CODE  there are usually  3 replicates,  although  this number
varies.  Therefore,  a check for replicate consistency is necessary,   if the PROB
column is marked "Y" for any replicate in a SAM_CODE,  this  replicate should not
be included in the  following calculation.

     The computer produces a printout, sorted by SET_ID, SAM_CODE, and  REP,  that
lists all flags assigned.   For  each  SAM_CODE, the mean, standard deviation, and
coefficient of variation of all replicates are listed.

     The  number of horizons and the percentage of  the total number of samples
having clods are reported.


KNOWN VOLUME BULK DENSITY RAW DATA FORM

Form 101 Information;

BD_KV

General;

     Known volume samples are taken from those horizons  where clods  cannot be
extracted.

-------
                                                                   Appendix H
                                                                   Revision 1
                                                                   Date: 4/89
                                                                   Page: 7 of 12
Calculations;

FINES_WT (g)  =  (OD_WT - R_FRAG - BAG_WT)

BD_KV (g/cm3)   = FINES_WT / (VOL - (R_FRAG / particle density)

Verification Flags;

If any parameter field is blank, with the exception of 'COMMENTS';  then flag A3
If OD_WT > AIR_WT;  then flag B3
If FINES_WT + R_FRAG > AIR_WT; then flag C3
If a SAM_CODE does not match the receipt form; then flag D3
If REP does not match the receipt form; then flag E3
If BD_KV > 2.0; then flag F3
If BD_KV < 1.0; then flag G3
If CV > 20; then flag H3

Reporting;

     The computer produces a printout, sorted by SET_ID, SAM_CODE,  and REP,  that
lists all flags assigned.  For each SAM_CODE,  the mean,  standard deviation,  and
coefficient of variation of all replicates are listed.

     The  number of  horizons and the percentage  of  the total number  of  samples
having known volume samples are reported.


LOSS ON IGNITION RAW DATA FORM

Form 101 Information;

OM_LOI

Calculations;

     Each  CRUC_NO will  be associated with a pre-determined CRUC_WT.

OM_LOI  =  [(OD_WT - ASHED_WT) / (OD_WT - CRUC_WT)] *  100


Verification Flags;

If any parameter field is blank,  with  the exception of 'COMMENTS';  then flag A4
If OM_LOI > 100; then flag B4
If OD_WT > AIR_WT;  then flag C4
If ASHED_WT > OD_WT; then flag D4
If a SAM_CODE does not match the receipt file; then flag E4
If the SAM_CODE is duplicated on the LOI form; then flag F4
If OM_LOI > 20 and SOILTYP on the bulk sample form is not  "O"; then  flag G4
If OM_LOI < 20 and SOILTYP on the bulk sample form is not  "M"; then  flag H4
If the internal duplicate/routine pair is > 15% RSD; then  flag 14

-------
                                                                   Appendix H
                                                                   Revision 1
                                                                   Date: 4/89
                                                                   Page: 8 of 12


If the FAP samples > 15% RSD; then flag J4
If the field duplicate/routine pair > 20% RSD; then flag K4
If a FAL sample is outside accuracy window; then flag L4
If a FAP sample is outside accuracy window; then flag M4
If a MS is outside accuracy window; then flag N4

Reporting;

     The computer produces a printout, sorted by SET_ID and  SAM_CODE,  that lists
all flags assigned.

     The number of horizons and the percentage  of  the total number  of samples
that have been analyzed are reported.


BULK SAMPLE PROCESSING RAW DATA FORM

Form 101 Information;

PH_MP
MOIST_P (1,2,3)
RF_FG
RF_MG

General;

     General information concerning the bulk  sample  is recorded on  this form.
when the  form is  complete, the  sample  is considered  ready  to be batched and
shipped to an analytical laboratory.

Calculations;

PH_MP   (no calculation required)

MOIST_P (1, 2, 3)  =  [(INIT_WT1 - OD_WT / (OD_WT - TIN_WT)]   *  100

     Each MOIST_P  calculation will  be conducted  only  if the previous  MOISTJP  is
> 2.5 percent for mineral samples or > 6.0 percent for  organic samples.

RF_FG  =  (RF_FGRAW / A_BULK)  * 100

RF_MG  =  (RF_MGRAW / A_BULK)  * 100

Verification Flags;

If any parameter field is blank,  with the  exception of 'COMMENTS';  then flag  A5
If SOILTYP =  'M' and MOIST_P  (1,2,3) > 2.5; then flag  B5
If SOILTYP =  'O' and MOIST_P  (1,2,3) > 6.0; then flag  C5
If PH_MP > 6.0; then flag D5
if a SAM_CODE does not match  the receipt file;  then  flag E5
If the internal duplicate/routine pair > 15% RSD; then  flag  F5

-------
                                                                   Appendix H
                                                                   Revision 1
                                                                   Date: 4/89
                                                                   Page:9 of 12


If the field duplicate/routine pair for MOIST_P, RF_FG, or RF_MG > 20% RSD; then
   flag G5   (or >0.20 SD for PH_MP)
If the FAP samples for MOIST_P, RF_FG, or RF_MG >  15% RSD;  then  flag H5   (or
   0.15 SD for PH_MP)
If pH QCCS out of window; then flag 15
If MOIST_P is outside accuracy window; then flag J5
If PH_MP is outside accuracy window; then flag K5

Reporting;

     The computer produces a printout, sorted by SET_ID and SAM_CODE,  that lists
all flags assigned.

     The number of horizons and the percentage  of  the total number  of samples
that have been analyzed are reported.

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                                                                          Appendix H
                                                                          Revision 1
                                                                          Date: 4/89
                                                                          Page: 10 of 12
                                    PH

                          MASS PREP LAB DATA REVIEW
Sample
 Date
  FAP
acc/prec
FAL
ace
Buffer
 Int  Dup
(0.15 SD)
Field Dup
(0.20 SD)
Manager
•ample
 ace.
                                                                 PASS

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                                                                        Appendix H
                                                                        Revision 1
                                                                        Date: 4/89
                                                                        Page: 11 of 12
                           AIR-DRI MOISTURE

                       MASS PREP LAB DATA REVIEW
Sample
 Date
   FAP
acc/prec
   (15»RSD)
FAL
acc
 Int Dup
(15% RSD)
Field Dup
(20% RSD)
 Manager
 sample
(control)
PASS

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                                                                        Appendix H
                                                                        Revision 1
                                                                        Date: 4/89
                                                                        Page: 12 of 12
                       WSS-ON-IGNITION

                    MASS PREP LAB DATA REVIEW
Sample
 Date
   PAP
acc/prec
   (IStRSD)
FAL
ace
 Int Dup
(15» RSD)
Field Dup
(20» RSD)
 Manager
 •anpl*
(control)
PASS

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                                                                       Appendix I
                                                                       Revision 1
                                                                       Date: 4/89
                                                                       Page: 1 of 9
                                  Appendix I


    Preparation Laboratory On-Site Evaluation Questionnaire


      The following questionnaire is used to provide documentation of on-site audits of the
preparation laboratory by QA staff. Generally, the preparation laboratory is evaluated at least
twice. The first audit is conducted before samples are received in order to assess the ability of
the laboratory, in terms of personnel, facilities, and equipment, to process soil samples
successfully.  At the time of the second evaluation, adherence to the Preparation Laboratory
Standard Operating Procedures is evaluated and specific discrepancies are addressed.

-------
                  Lockheed-ESC PREPARATION  LABORATORY ON-SITE
                       BIWEEKLY EVALUATION  QUESTIONNAIRE
Date:
                                                                    Appendix I
                                                                    Revision 1
                                                                    Date: 4/89
                                                                    Page: 2 of 9
Laboratory Telephone  Number:

Laboratory Manager: 	
Laboratory Quality Assurance Officer:

Technicians Present  During Evaluation:

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                                                                   Appendix I
                                                                   Revision 1
                                                                   Date: 4/89
                                                                   Page: 3 of 9
Questions
 General

	Yes
                                                      No
Comments
 Is the overall  appearance
 of the laboratory clean?
 Is there proper  storage/
 disposal of chemicals  and
 hazardous materials?
Are safety stickers properly
displayed?
Are the fire extinguishers
in place?
Date of last service call  for
fire extinguishers?
Is there a disposal system
for paper, etc.?
Is the air compressor
accessible to all areas
of the laboratory?
Is there an adequate supply
of gloves, goggles, DDI HO,
paper towels, etc.?      ^
Is there a copy of the SOP
available to technicians?
is there an updated record
of instrument calibrations?
Are the computer records kept
up-to-date?
Is the eye wash station easily
accessible in case of emergency?
Is the power box easily accessible
in case of emergency shutoff?
Comments;

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                                                                   Appendix I
                                                                   Revision 1
                                                                   Date: 4/89
                                                                   Page:4 of  9
Questions
                               cold Storage Room

                                          Yes
                                                                Comments
Is there adequate space  for
sample storage?
Is there easy access to
samples?
Is the temperature of the
cold storage kept at
4°C
      - 2°C?
Is a systematic way
of shelving and locating
samples being maintained?
Is there clear and precise
labeling of samples?
Are samples being kept in an
area free from moisture
and contamination?
Are samples tightly sealed?
Is there clear separation
of organic and mineral
samples?
Is the cold storage room clean?
Is the floor area clean
of samples?
Comments;

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                                                                   Appendix I
                                                                   Revision 1
                                                                   Date: 4/89
                                                                   Page: 5 of 9
                                 Sample Drying

Questions                                 Yes        No         comments

Are all samples covered and
free from contamination while
drying?

Are samples that are spread
to dry properly labeled?

Are gloves being used
to mix the samples?

Is the bulk sample form
filled out for each sample
drying?

Is the paper being changed
as needed during drying?

Is the air flow being
maintained?

Are the doors closed?

Is the drying area clean?

Are cleaning protocols being
followed?


Comments;

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                                                                   Appendix I
                                                                   Revision 1
                                                                   Date: 4/89
                                                                   Page: 6 of 9
                              Sample Preparation

Questions                                 Yes        No        Comments

Are proper sample grinding
procedures being followed?

Are proper cleaning procedures
between samples being followed?

Is the preparation room clean?

Are the fans being used during
sample preparation?



Comments;
                                      EH

Questions                                 Yes        No         Comments

Is there an up-to-date calibration
curve for pH determinations?
Is there an up-to-date QCCS log
for pH determinations?
Are pH electrodes stored
properly?
Is there enough filling  solution
in the electrode?
Is the procedure for pH
determination being followed
according to the SOP?
Comments;

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                                                                    Appendix I
                                                                    Revision 1
                                                                    Date: 4/89
                                                                    Page: 7 of 9
                         Moisture and Loss On Ignition

Questions                                  Yes         No        Comments

Is the sample used to
determine field moisture
properly secured from
contamination prior to the  loss-
on-ignition determination?

Are the oven and crucibles
cleaned between each set of
samples?

Are crucibles clearly
numbered?

Are the muffle furnace and
desiccators clean?

Are oven and furnace hazards
clearly posted?

Are oven gloves in good
condition?

Are the platinum-tipped
tongs being used consistently
when moving the crucibles?


comments;

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                                                                   Appendix I
                                                                   Revision 1
                                                                   Date: 4/89
                                                                   Page: 8 of 9
Questions
Procedures Purina Sample Riffle Splitting

                        Yes         No
Comments
Is there proper cleaning of
riffle-splitter and sieves?
Is the door closed?
Is the fan operating?
Is the trailer used only by
personnel performing the riffle-
splitting?
                                    General
  IP at ion a
                        Yes
                                                     No
                                                                Comments
Is the trailer clean?
Is the balance clean?
Are record books updated?
Are rock  fragments  labeled
and stored properly?
Are the three riffle-split
subsamples clearly  labeled?
Do the technicians  understand
and practice  the  procedures
properly?
Comments;

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                                                                   Appendix I
                                                                   Revision 1
                                                                   Date: 4/89
                                                                   Page: 9 of 9
Questions
 Bulk Density

	Yes
No
Comments
Is there proper mixing of the
saran and acetone?
Is there proper sealing of the
saran/acetone to prevent
evaporation?
Are the clods labeled
properly?
Are the procedures for both
bulk densities being followed?
Are all weights recorded to the
nearest .Olg?
Do technicians know the proper
procedure for a clod that floats?
Are evaporating dishes clearly
labeled?
Comments;

-------

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                                                                     Appendix J
                                                                     Revision 1
                                                                     Date: 4/89
                                                                     Page: 1 of 21
                                 Appendix J

              Quality Assurance Reanalysis Templates
      The following QARTs are used in the evaluation of QE/QC and routine sample data.  As a
batch of soils data is received, it is reviewed according  to the criteria  set forth in the template.
If major uncertainty or a large occurrence  of  minor uncertainty is identified, confirmation or
reanalysis is requested for the affected parameter and batch.

-------
PARAMETER: PH HP

Field Audit
Low & Pair
QCCS
Internal
duplicate
Field
duplicate
Manager
sample
MAJOR
If any 2 of 3 relationships occur ana 2 minor
flag occurs:
1) FAL beyond control limits
2) Mean of FAP or FAO beyond control limits
3) FAP or FAO SD > 0.15
Out of expected range
none
none
none
MINOR
If 1 of 3 of the relationships
listed in the major column occurs
none
Routine/duplicate SD > 0.15
Routine/duplicate SD > 0.20
Sample beyond control limits
NON
If 0 of 3 of the relationships
listed in the major column occur
within expected range
Routine/duplicate SD < 0.15
Routine/duplicate SD < 0.20
Sample within control limits
Reanalyeie is requested with occurrence  of  1 major or 3 minor & uncertainty


Quality Assurance Reanalysis Template for the Determination of Field-Moist pH.
                                                                                                                                     0) Q) 0> TJ
                                                                                                                                    (Q •* < -Q
                                                                                                                                     CD ® ft 
-------
PARAMETER: OH LOT

Field Audit
Low d Pair
Internal
duplicate
Field
duplicate
Manager
sample
MAJOR
If any 2 of 3 relationships occur and 1 minor
flag occurs:
1) FAL beyond control limits
2) Mean of FAP or FAO beyond control limits
3) FAP or FAO RSD > 15%
none
none
none
MINOR
If 1 of 3 of the relationships
listed in the major column occurs
Routine/duplicate RSD > 151
Routine/duplicate RSD > 20%
Sample beyond control limits
NON
If 0 of 3 of the relationships
listed in the major column occur
Routine/duplicate RSD < 15%
Routine/duplicate RSD < 20%
Sample within control limits
Reanalysis is requested with occurrence of 1 major or 3 minor 4 uncertainty



Quality Assurance Reanalysle Template for the Determination of Organic Matter by Loss on Ignition.
                                                                                                                           -OO3J

                                                                                                                           
-------
PARAMETER: HOIST P

Field Audit
Low & Pair
Internal
duplicate
Field
duplicate
Manager
sample
MAJOR
If any 2 of three of relationships occur and
one minor flag occurs:
1) FAL beyond control limits
2 ) Mean of FAP or FAO beyond control limits
3) FAP or FAO RSD > 20%
none
none
none
MINOR
If 1 of 3 of the relationships occur
listed in major column occurs
Routine/duplicate RSD > 15%
Routine/duplicate RSD > 20%
Sample beyond control limits
NON
If 0 of 3 of the relationships
listed in the major column occur
Routine/duplicate RSD < 15%
Routine/duplicate RSD < 20%
Sample within control limits
Reanalysis is requested with occurrence of  1 major or 3 minor t uncertainty


Quality Assurance Reanalysis Template for  the Determination of Air-Dry Moisture.
                                                                                                                               0> j? §-"8
                                                                                                                               as-
                                                                                                                               N>
X
c_

-------
PARAMETER:  SAND,  SILT

Lab Audits
t
Prep Dupa
Field Dupa
4
Field Audits
Soil
Chemistry
Relationships
Internal
Relationships

MAJOR
If any 2 of 4 relationships occur:
1) prep dup/routine pair:
SD > 3.0 if value at lower limit
2) prep dup/field dup pair:
SD > 3.0 if value at lower limit
3) mean value lab audits out of accuracy window, or
SD > 3.0 if value at lower limit
4) low level lab audit out of accuracy window
NOME
NOME
> 10 outliers

MINOR
If 1 out of 4 of the relationships
listed in the major column occurs
Within batch precision:
SD > 6.0 if value at lower limit
NONE
5-10 outliers

NON
If 0 of 4 of the relationships
listed in the major column occur
Within batch precision:
SD < 6.0 if valur at lower limit
NONE
< 5 outliers

Reanalysis is requested with occurrence of 1 major or  3 minor 4 uncertainty




Quality Assurance Reanalysis Template for the Determination of Sand and Silt.

-------
PARAMETER:  CLAY

Lab Audits
&
Prep Dups
Field Dups
t
Field Audits
Soil
Chemistry
Relationships
Internal
Relationships

MAJOR
If any 2 of the 4 relationships occur:
1) prep dup/routine pair:
SD > 2.0 if value at lower limit
2) prep dup/field dup pair:
SD > 2.0 if value at lower limit
3) mean value lab audits out of accuracy window, or
SD > 2.0 if value at lower limit
4) low level lab audit out of accuracy window
NONE
If any relationship occurs > 6 times:
CEC OAC/CLAY > 50
if clay > 1.0 and CEC_CL > 1 meq/100 g
CEC-CL/CLAY > 50
if clay > 1.0 and CEC-CL > 1 meq/100 g
> 10 outliers

MINOR
If 1 of 4 of the relationships
listed in the major column occurs
Within batch precision:
SD > 4.0 if value at lower limit
If relationships occur < 6 times
5-10 outliers

NON
If 0 of 4 of the relationships
listed in the major column occur
Within batch precision:
SD < 4.0 if value at lower limit
If relationships do not occur
< 5 outliers

Reanalysis is requested with occurrence of 1 major or 3 minor t uncertainty

Quality Assurance Reanalysis Template for the Determination of Clay.
                                                                                                                                     Q> Q)  (D "O
                                                                                                                                     0) ®  M »

-------
PARAMETER:  PH H20,  PH OO2M, PH 01M

Lab Audits
I
Prep Dups
Field Dups
t
Field Audits
Soil
Chemistry
Relationships
Internal
Relationships

MAJOR
If any 2 of 4 relationships occur:
1) prep dup/ routine pair:
SD > 0.1 if value at lower limit
2) prep dup/field dup pair:
SD > 0.1 if value at lower limit
3) mean value lab audits out of accuracy window, or
SD > 0.1 if value at lower limit
4) low level lab audit out of accuracy window
NONE
If relationship occurs > 6 times
PH H20 < PH 002M < PH DIM if difference > .05
> 10 outliers

MINOR
If 1 of 4 of the relationships
listed in the major column occurs
Within batch precision:
SD > 0.2 if value at lower limit
If relationship occurs < 6 times
5-10 outliers

NON
If 0 of 4 of the relationships
listed in the major column occur
Within batch precision:
SD < 0.2 if value at lower limit
If relationship does not occur
< 5 outliers

Reanalysis is requested with occurrence of 1 major or  3 minor t uncertainty




Quality Assurance Reanalysis Template for the Determination of Soil pH.

-------
 PARAMETER: CA,  MG,  NA, K_CL
           CA,  MG,  NA, K OAC

Lab Audits
I
Prep Dups
Field Dups
 .02 if value at lower limit
%RSD > 15* if value at upper limit
2) prep dup/field dup pair:
SD > .02 if value at lower limit
IRSD > 151 if value at upper limit
3) mean value lab audits out of accuracy window, or
SD > .02 if value at lower limit
IRSD > lot if value at upper limit
4) low level lab audit out of accuracy window
none
If relationships occur > 6 times:
CA OAC + MG OAC + NA OAC + K OAC > CEC OAC
if" CEC_CL > 1 meq/100 g
CA CL -4- MG CL + NA CL + K CL > CEC CL
il CEC_CL > 1 meq/lOO g
> 10 outliers

MINOR
If 1 of 4 of the relationships
listed in the major column occurs
Within batch precision:
SD > .04 if value at lower limit
IRSD > 301 if value at upper limit
If relationship occurs < 6 times
5 - 10 outliers

NON
If 0 of 4 of the relationships
listed in the major column occur
Within batch precision:
SD < .04 if value at lower limit
IRSD < 301 if value at upper limit
If relationship does not occur
< 5 outliers

Reanalysis  is requested with occurrence of 1 major or 3 minor &  uncertainty

Quality Assurance Reanalysis Template for the Determination of the Exchangeable Cation* In Ammonium Chloride and Ammonium Acetate.

-------
PARAMETER:  AL CL

Lab Audits
t
Prep Dups
Field Dups
t
Field Audits
Soil
Chemistry
Relationships
Internal
Relationships

MAJOR
If any 2 of 4 relationships occur!
1) prep dup/ routine pair:
SD > .20 if value at lower limit
%RSD > 22% if value at upper limit
2) prep dup/field dup pair:
SD > .20 if value at lower limit
tRSD > 22% if value at upper limit
3) mean value lab audits out of accuracy window, or
SD > .20 if value at lower limit
%RSD > 15% if value at upper limit
4) low level lab audit out of accuracy window
HONE
If relationship occurs > 6 times:
AL_CL > 0.1 meq/100 g if pH_H2O > £.0
> 10 outliers

MINOR
If 1 of 4 of the relationships
listed in the major column occurs
Within batch precision:
SD > 5.0 if value at lower limit
%RSD > 30% if value at upper limit
If relationship occurs < £ times
5-10 outliers

NON
If 0 of 4 of the relationships
listed in the major column occur
Within batch precision:
SD < 5.0 if value at lower limit
%RSD < 30% if value at upper limit
If relationship does not occur
< 5 outliers

Reanalysis is  requested with occurrence of 1 major or 3  minor 4 uncertainty




Quality Aeeurance Reanalysis Template for the Determination of Aluminum In Ammonium Chloride.

-------
 PARAMETER: CEC OAC, CEC CL

Lab Audits
t
Prep Dups
Field Dups
t
Field Audits
Soil
Chenistry
Relationships
Internal
Relationships

MAJOR
If any 2 of 4 relationships occur:
1) prep dup/routine pair:
SD > .25 if value at lower limit
tRSD > 15t if value at upper limit
2) prep dup/field dup pair:
SD > .25 if value at lower limit
tRSD > 151 if value at upper limit
3) mean value lab audits out of accuracy window, or
SD > .25 if value at lower limit
tRSD > 101 if value at upper limit
4) low level lab audit out of accuracy window
NONE
If relationship occurs > 6 times
CEC_OAC < CEC_CL
if CEC_CL > 1 meq/100 g and PH_H2O < 7.0
> 10 outliers

MINOR
If 1 of 4 of the relationships
listed in the major column occurs
Within batch precision:
SD > .50 if value at lower limit
tRSD > 30% if value at upper limit
If relationship occurs < 6 times
5-10 outliers

NON
If 0 of 4 of the relationships
listed in the major column occur
Within batch precision:
SD < .50 if value at lower limit
tRSD < 30t if value at upper limit
If relationship does not occur
< 5 outliers

Reanalysis is  requested with occurrence of 1 major or 3 minor t uncertainty




Quality Aaaurance Reanalysis Template lor the Determination ol Cation Exchange Capacity In Ammonium Chloride and Ammonium Acetate.
                                                                                                                                (D

                                                                                                                                to

-------
PARAMETER:   AC  BACL

Lab Audits
(,
Prep Dupa
Field Dups
t
Field Audits
Soil
Chemistry
Relationships
Internal
Relationships

MAJOR
If any 2 of 4 relationships occur:
1) prep dup/ routine pair:
SD > 1.0 if value at lower limit
%RSD > 22% if value at upper limit
2) prep dup/field dup pair:
SD > 1.0 if value at lower limit
%RSD > 22% if value at upper limit
3) mean value lab audits out of accuracy window, or
SD > 1.0 if value at lower limit
%RSD > 15% if value at upper limit
4) low level lab audit out of accuracy window
NONE
NONE
> 10 outliers

MINOR
If 1 of 4 of the relationships
listed in the major column occurs
Within batch precision:
SD > 2.0 if value at lower limit
%RSD > 45% when using upper limit
NONE
5-10 outliers

NON
If 0 of 4 of the relationships
listed in the major column occur
Within batch precision:
SD < 2.0 when using lower limit
%SDR < 45% when using upper limit
NONE
< 5 outliers

Reanalysis is requested with occurrence of  1 major or 3 minor t uncertainty




Quality Aaaurance Reanalyze Template for  the Determination of Barium Chloride Exchangeable Acidity.

-------
PARAMETER:  CA CL2

Lab Audits
i.
Prep Dupa

Field Dups
I
Field Audits
Soil
Chemistry
Relationships
Internal
Relationships

MAJOR
If any 2 of 4 relationships occur:
1) prep dup/ routine pair:
SD > .05 if value at lower limit
%RSD > 8% if value at upper limit
2) prep dup/field dup pair:
SD > .05 if value at lower limit
%RSD > 84 if value at upper limit
3 ) mean value lab audits out of accuracy window, or
SD > .05 if value at lower limit
%RSD > 5% if value at upper limit

NONE
NONE
> 10 outliers

MINOR
If 1 of 4 or the relationships
listed in the major column occurs

Within batch precision:
SD > .10 if value at lower limit
IRSD > 15% if value at upper limit
NONE
5-10 outliers

NON
If 0 of 4 of the relationships
listed in the major column occur

Within batch precision:
SD < .10 if value at lower limit
%RSD < 15% if value at upper limit
NONE
< 5 outliers

Reanalysis is requested with  occurrence of 1 major or  3 minor * uncertainty




Quality Assurance Reanalysis Template for the Determination of Extraetable Calcium In Calcium Chloride.

-------
PARAMETER:   MG CL2, NA CL2,  K CL2

Lab Audits
S.
Prep Dups
Field Dups
t
Field Audits
Soil
Chemistry
Relationships
Internal
Relationships

MAJOR
If any 2 of 4 relationships occur:
1) prep dup/ routine pair:
SD >.005 if value at lower limit
%RSD > 15% if value at upper limit
2) prep dup/field dup pair:
SD >.005 if value at lower limit
%RSD > 15% if value at upper limit
3) mean value lab audits out of accuracy window, or
SD >.005 if value at lower limit
IRSD > 10% if value at upper limit
4) low level lab audit out of accuracy window
HONE
If relationship occurs > 6 times
MG CL2 > MG CL * 1.10 if MG CL2 > 10 * CRDL
HA CL2 > NA CL * 1.10 if NA CL2 > 10 « CRDL
K_CL2 > K_CL * 1.10 if K_CL2 > 10 * CRDL
> 10 outliers

MINOR
If 1 of 4 of the relationships
listed in the major column occurs
Within batch precision:
SD > .010 if value at lower limit
%RSD > 30% if value at upper limit
If relationships occur < 6 times
5 - 10 outliers

NON
If 0 of 4 of the relationships
listed in the major column occur
Within batch precision:
SD < .010 if value at lower limit
%RSD < 30% if value at upper limit
If relationships do not occur
< 5 outliers

Reanalysis  is  requested with occurrence of 1 major or  3 minor * uncertainty




Quality Assurance Reanlyals Template for the Determination of Extractable Magnesium, Potassium, and Sodium In Calcium Chloride.

-------
PARAMETER:  FE CL2

Lab Audits
&
Peep Dups
Field Dups
I
Field Audits
Soil
Chemistry
Relationships
Internal
Relationships

MAJOR
If any 2 of 4 relationships occur:
1) prep dup/routine pair:
SD > .01 if value at lower limit
%RSD > 22% if value at upper limit
2) prep dup/field dup pair:
SD > .01 if value at lower limit
%RSD > 22% if value at upper limit
3) mean value lab audits out of accuracy window, or
SD > .01 if value at lower limit
%RSD > 15% if value at upper limit
4) low level lab audit out of accuracy window
NONE
NONE
> 10 outliers

MINOR
If 1 of 4 of the relationships
listed in the major column occurs
Within batch precision:
SD > .02 if value at lower limit
%RSD > 45% if value at upper limit
NONE
5-10 outliers

NON
If 0 of 4 of the relationships
listed in the major column occur
Within batch precision:
SD < .02 if value at lower limit
%RSD < 45% if value at upper limit
NONE
< 5 outliers

Reanalysis is requested with occurrence of 1 major or 3  minor t  uncertainty




Quality Assurance Reanlysis Template for the Determination of Extractable Iron In Calcium Chloride.

-------
PARAMETER:   AL CL2

Lab Audit*
t
Prep Dupe
Field Dups
I
Field Audits
Soil
Chemistry
Relationships
Internal
Relationships

MAJOR
If any 2 of 4 relationships occur:
1) prep dup/routine pair:
SD > .05 if value at lower limit
%RSD > 22% if value at upper limit
2) prep dup/field dup pair:
SD > .05 if value at lower limit
%RSD > 22% if value at upper limit
3) mean value lab audits out of accuracy window, or
SD > .05 if value at lower limit
%RSD > 15% if value at upper limit
4) low level lab audit out of accuracy window
HONE
NONE
> 10 outliers

MINOR
If 1 of 4 of the relationships
listed in the major column occurs
Within batch precision:
SD > .10 if value at lower limit
%RSD > 45% if value at upper limit
NONE
5-10 outliers

NOU
If 0 of 4 of the relationships
listed in the major column occur
Within batch precision:
SD < .10 if value at lower limit
%RSD < 45% if value at upper limit
NONE
> 5 outliers

Reanalysis is requested with occurrence of 1 major or 3 minor i uncertainty


Quality Assurance Reanlysls Template for the Determination of Extractable Aluminum In Calcium Chloride.
                                                                                                                                   0) CB   _

                                                                                                                                   ?> ?. W ®

                                                                                                                                   11*. 2 a
                                                                                                                                   01    3  '

-------
PARAMETER:  FE_PYP, AL_PYP, FE_AO, AL_AO, SI_AO,  FE_CD,  AL_CD

Lab Audits
I
Prep Dups
Field Dups
d
Field Audits
Soil
Chemistry
Relationships
Internal
Relationships

MAJOR
If any 2 of 4 relationships occur:
1) prep dup/ routine pairt
SD > .03 if value at lower limit
%RSD > 15% if value at upper limit
2) prep dup/field dup pair:
SD > .03 if value at lower limit
tRSD > 15% if value at upper limit
3) mean value lab audits out of accuracy window, or
SD > .03 if value at lower limit
tRSD > 10% if value at upper limit
4) low level lab audit out of accuracy window
NONE
NONE
> 10 outliers

MINOR
If 1 of 4 of the relationships
listed in the major column occurs
Within batch precision:
SD > .06 if value at lower limit
%RSD > 30% if value at upper limit
NONE
5-10 outliers

NON
If 0 of 4 of the relationships
listed in the major column occur
Within batch precision:
SD < .06 if value at lower limit
%RSD < 30% if value at upper limit
NONE
< 5 outliers

Reanalysis is requested with occurrence  of  1 major or 3 minor I uncertainty


Quality Assurance Reanlysis Template for the Determination of Extractable Iron, Aluminum, and Silicon In Pyrophosphate, Acid Oxalate, and
Citrate DIthlonlte.
                                                                                                                                     o> o>

                                                                                                                                     ®
                                                                                                                                            X
                                                                                                                                     o
-------
PARAMETER:   SO4 PO4, SO4 K2O

Lab Audits
c,
Prep Dups
Field Dups
&
Field Audits
Soil
Chemistry
Relationships
Internal
Relationships

MAJOR
If any 2 of 4 relationships occur:
1) prep dup/routine pair:
SD > 1.5 if value at lower limit
%RSD > 15t if value at upper limit
2) prep dup/field dup pair:
SD > 1.5 if value at lower limit
IRSD > 15% if value at upper limit
3) mean value lab audits out of accuracy window, or
SD > 1.5 if value at lower limit
IRSD > 5% if value at upper limit
4) low level lab audit out of accuracy window
NONE
If relationship occurs > 6 times
SO4 PO4 < SO4 H2O
if SO4_H2O > 1 mg S/kg soil
S04 H2O/SO4 0 > 4 or SO4 H2O/SO4 0 > 20
if SO4_H2O > 2 mg S/kg and SO4_0 > . 1 mg S/kg
> 10 outliers

MINOR
If 1 of 4 of the relationships
listed in the major column occurs
Within batch precision:
SD > 3.0 if value at lower limit
IRSD > 30% if value at upper limit
If relationship occurs < 6 times
5-10 outliers

NON
If 0 of 4 of the relationships
listed in the major column occur
Within batch precision:
SD < 3.0 if value at lower limit
%RSD < 30% if value at upper limit
If relationship does not occur
< 5 outliers

Reanalysis is  requested with occurrence of 1 major or 3 minor 4 uncertainty




Quality Assurance Reanlyals Template for the Determination of Extractable Sulfate In Water and Phosphate.
•oo:
0) fi> I _ _


® S W <&

'-1 * ° a
                                                                                                                                 to

-------
PARAMETER:  SO4 0-32

Lab Audits
&
Prep Dupe
Field Dupe
&
Field Audits
Soil
Chemistry
Relationships
Internal
Relationships

MAJOR
If any 2 of 4 relationships occur:
1) prep dup/routine pair:
SD > .10 if value at lower limit
%RSD > 8% if value at upper limit
2) prep dup/field dup pair:
SD > .10 if value at lower limit
%RSD > 8% if value at lower limit
3) mean value lab audits out of accuracy window, or
SD > .10 if value at lower limit
%RSD > 5% if value at upper limit
4) low level lab audit out of accuracy window
NONE
If relationship occurs > 6 times
SO4 32 < S04 16 < S04 8 < SO4 4 < SO4 2 < SO4 0
If S04_32N >= 7.5 mg S/Kg soil
> 10 outliers

MINOR
If 1 of 4 of the relationships
listed in the major column occur
Within batch precision:
SD > .20 if value at lower limit
%RSD > 15% if value at upper limit
If relationship occurs < 6 times
5-10 outliers

NON
If 0 of 4 of the relationships
listed in the major column occur
Within batch precision:
SD < .20 if value at lower limit
%RSD < 15% if value at upper limit
If relationship does not occur
< 5 outliers

Reanalysis is  requested with occurrence of 1 major  or  3 minor & uncertainty
Quality Assurance Reanlysis Template for the Determination of Sulfate Adsorption Isotherms.

-------
PARAMETER:   C TOT

Lab Audits
«
Prep Dupa

Field Dupa
I
Field Audita
Soil
Chemistry
Relationships
Internal
Re 1 at ions h ips

MAJOR
If any 2 of 4 relationships occur:
1) prep dup/ routine pair:
SD > .05 if value at lower limit
%RSD > 15% if value at upper limit
2) prep dup/field dup pair:
SD > .05 if value at lower limit
%RSD > 15% if value at upper limit
SD > .05 if value at lower limit
IRSD > 10% if value at upper limit
4) low level lab audit out of accuracy window
NONE
If any relationship occurs > 6 times
C TOT/N TOT < 7 or C TOT/N TOT > 50
if" N_TOT > .03 wt% and C_TOT > .1 wt%
C TOT/S TOT < 40 or C TOT/S TOT > 400
if SJTOT > .005 wt% and C TOT > .1 wt%
> 10 outliers

MINOR
If 1 of 4 of the relationships
liated in the major column occurs

Within batch precision:
SD > .10 if value at lower limit
%RSD > 30% if value at upper limit
If relationship occurs < 6 times
5-10 outliers

NON
If 0 of 4 of the relationships
liated in the major column occur

Within batch precision:
SD < .10 if value at lower limit
IRSD < 30% if value at upper limit
If relationship does not occur
< 5 outliers

Reanalysia is requested with occurrence of 1 major or  3 minor I uncertainty




Quality Assurance Reanlysls Template for the Determination of Total Carbon.

-------
PARAMETER:  N TOT

Lab Audits
&
Prep Dups
Field Dups
I
Field Audits
Soil
Chemistry
Relationships
Internal
Relationships

MAJOR
If any 2 of 4 relationships occur:
1) prep dup/routine pair:
SD >.015 if value at lower limit
%RSD > 15% if value at upper limit
2) prep dup/ field dup pair:
SD >.015 if value at lower limit
%RSD > 15% if value at upper limit
3) mean value lab audits out of accuracy window, or
SD >.015 if value at lower limit
%RSD > 101 if value at upper limit
4) low level lab audit out of accuracy window
NOKE
If relationship occurs > 6 times
C TOT/N TOT < 7 or C TOT/N TOT > 50
if N TOT > .03 wt« and C TOT > .1 wt«
> 10 outliers

MINOR
If 1 of 4 of the relationships
listed in the major column occurs
Within batch precision:
SD > .03 if value at lower limit
%RSD > 30% if value at upper limit
If relationship occurs < 6 times
5-10 outliers

NON
If 0 of 4 of the relationships
listed in the major column occur
Within batch precision:
SD < .03 if value at lower limit
%RSD < 30% if value at upper limit
If relationship does not occur
< 5 outliers

Reanalysis is requested with  occurrence of 1 major or 3  minor & uncertainty




Quality Assurance Reanlysls Template for the Determination of Total Nitrogen.

-------
PARAMETER:  S TOT

Lab Audits
t
Prep Dupe
Field Dups
t
Field Audits
Soil
Chemistry
Relationships
Internal
Relationships

MAJOR
If any 2 of 4 relationships occur!
1) prep dup/routine pair:
SD >.002 if value at lower limit
IRSD > 15% if value at upper limit
2) prep dup/field dup pair:
SD >.002 if value at lower limit
%RSD > 15% if value at upper limit
3) mean value lab audits out of accuracy window, or
SD >.002 if value at lower limit
%RSD > 10% if value at upper limit
4) low level lab audit out of accuracy window
NONE
If relationship occur > 6 times
C_TOT/S_TOT < 40 or C_TOT/S_TOT > 400
if SJTOT > .005 wtl and CJEOT > .1 wt%
> 10 outliers

MINOR
If 1 of 4 of the relationships
listed in the major column occurs
Within batch precision:
SD > .004 if value at lower limit
%RSD > 30% if value at upper limit
If relationship occurs < 6 times
5-10 outliers

NON
If 0 of 4 of the relationships
listed in the major column occur
Within batch precision:
SD <.004 if value at lower limit
%RSD < 30% if value at upper limit
If relationship does not occur
< 5 outliers

Reanalysis is requested with occurrence of  1 major or 3 minor 4 uncertainty



Quality Assurance Reanlyele Template for the Determination of Total Sulfur.
                                                                                                                                     0)

                                                                                                                                     
-------
                                                                          Appendix K
                                                                          Revision 1
                                                                          Date: 4/89
                                                                          Page 1 of 5
                                    Appendix K

            Analytical Data Verification and Validation Flags
       This appendix lists the data qualifiers, or flags, that are  assigned to the verified and
validated data bases.  The verification flags specify the nature of discrepancies on a batch and
sample  basis,  while the  validation flags are used to characterize more general types of
discrepancies that may affect the level of confidence applied to each datum in the validated data
base. The verification flags are applied only to the analytical laboratory data and are unrelated to
similarly-defined flags in the preparation laboratory data.

-------
                                                                   Appendix K
                                                                   Revision 1
                                                                   Date: 4/89
                                                                   Page 2 of 5
                      ANALYTICAL DATA VERIFICATION FLAGS
Blank Exception Program

B4"   Potential negative sample bias based on laboratory blank data.

B5"   Reagent blank mean is > CRDL.

B6*   Laboratory calibration blanks or reagent blanks are > CRDL.

B9**   Insufficient number of calibration blanks were run.

Duplicate Precision Exception Program

Dl"   Analytical duplicate (AD/routine) precision exceeds the maximum expected
      SD or %RSD.

D5"   Preparation duplicate (PDF/routine) precision exceeds the maximum expected
      so or %RSD.

D6"   Preparation duplicate (PDR/routine) precision exceeds the maximum expected
      SD or %RSD.

D7"   Field  audit pair/triplicate  (FAP/FAO)  precision  exceeds  the  maximum
      expected SD or %RSD.

D8"   Laboratory audit pair/triplicate (LAP/LAO) precision exceeds the maximum
      expected SD or %RSD.

D9"   Field duplicate (FD/routine) precision exceeds  the maximum  expected SD or
      %RSD.

Detection Limit Exception Program

Ll"   Instrument detection limit (IDL) exceeds contract-required detection limit
      (CRDL).

Audit Accuracy Program

NO"   Low-range laboratory audit (LAL)  sample value exceeds upper accuracy limit.

Nl"   LAL sample is below lower accuracy limit.

N2**  Mean of LAP or LAO exceeds upper accuracy limit.

N3**  Mean of LAP or LAO is below lower accuracy limit.

N4"   Quality control audit sample (QCAS) exceeds upper accuracy limit.

N5"   QCAS is below lower accuracy limit.

                                                                   (Continued)

-------
                                                                   Appendix K
                                                                   Revision 1
                                                                   Date: 4/89
                                                                   Page 3 of 5
QCCS Exception Program

Ql"   Quality control check sample (QCCS) exceeds upper control limit.

Q2"   QCCS is below lower control limit.

Q3"   insufficient quantity of QCCS were measured.

Q4"   Detection limit QCCS is not within 20% of the theoretical concentration.

Matrix Spike Program

Sl"   Percent recovery of matrix spike is above contractual criteria  (>105% for
      sulfur parameters, >110% for all others).

S2"   Percent recovery of matrix spike is below contractual criteria  (<95% for
      sulfur parameters, <90% for all others).

S3"   Spike  solution  readings  are  outside  of  contractual  criteria  (sulfate
      isotherm parameters only).

Miscellaneous

AO*    Value missing

MO*    Value was obtained by using a method that is unacceptable according to the
      contract.

WO*    Air-dry sample weight is not within contractual requirement.

W2*    Sample extract volume is not within contractual requirement.

xo*    Invalid but confirmed data based on review of QE/QC data.

Xl*    Invalid but confirmed data - potential gross  contamination of sample or
      parameter.

X2*    Invalid but confirmed data - potential gross contamination of pedon.

X3*   Possible contamination  due to  either sampling technique,  e.g., bucket
      augering, or soil amendments,  e.g. herbicides, liming, manure, etc.

X4*   Outliers from statistical internal consistency  check; raw data and reported
      data checked only for transcription errors.

X5*   Outliers from manual pedon/horizon internal consistency check; raw data
      and reported data checked only for transcription errors.


                                                                   (Continued)

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                                                                   Appendix K
                                                                   Revision 1
                                                                   Date: 4/89
                                                                   Page 4 of 5
Soil chemistry Relationships


NC*   Hot checked because basic initial criteria were not met.

Cl*   PH_H20 < PH_002M if pH differences > 0.05 units.


C2*   PH_002M < PH_01M if pH differences > 0.05 units.


C3*   PH_H20 < PH_01M if pH differences > 0.05 units.


C4*   CEC_OAC < CEC_CL if CEC_CL > 1 meq/lOOg and PH_H2O < 7.0


C5*   CA_OAC + MG_OAC + K_OAC + NA_OAC > CEC_OAC if CEC_CL > 1 meq/100g


C6*   CA_CL + MG_CL + K_CL + NA_CL > CEC_CL if CEC_CL > 1 meq/lOOg

C7*   CEC_OAC/CLAY > 50 if CLAY > 1.0% and CEC_CL > 1 meq/100g


C8*   CEC_CL/CLAY > 50 if CLAY > 1.0% and CEC_CL > 1 meq/lOOg

C9*   AL_CL > 0.01 meq/lOOg if PH_H2O > 6.0


Tl*   C_TOT/S_TOT < 7  or > 50 if CJTOT i  0.1% and N_TOT  £ 0.03%.

T2*   C_TOT/N_TOT < 40 or > 400 if C_TOT £ 0.1% and N_TOT & 0.03%.


II*   SO4_32 < SO4_16 if SO4_32N £  7.5 mg  S/kg soil.

12*   S04_16 < S04_8 if SO4_32N S 7.5 mg S/kg soil.

13*   SO4_8 < SO4_4 if SO4_32N  SO4_PO4 if SO4_PO4 > 1 mg S/kg soil (mineral samples); SO4_H2O
      > SO4_PO4 * 1.10 (organic samples).

                                                                   (Continued)

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                                                                    Appendix K
                                                                    Revision 1
                                                                    Date: 4/89
                                                                    Page 5 of 5
R2*   SO4_H2O/SO4_0 < 4 or > 20 if SO4_H2O £ 2 rag S/kg and SO4_0 i 0.1 mg S/kg.

HI*   NA_CL2 > NA_CL *  1.10 if  NA_CL2  > 0.03  meg/100g.

H2*   K_CL2 > K_CL * 1.10  if K_CL2  >  0.003 meq/lOOg.

H3*   MG_CL2 > MG_CL *  1.10 if  MG_CL2  > 0.008 meq/100g.


*  Sample Flag: flags the  affected  parameter  for specified samples only.
** Batch-wide Flag: flags  the  affected parameter for all  samples in the batch
   (assumes that measurement quality samples are representative for the batch).
                       ANALYTICAL DATA VALIDATION FLAGS
VI    Datum  >  ±3x interquartile  range limits or  > ±1.5x  interquartile range
      limits; has verification  flag  type  K,  w, M,  or X

V2    QE/QC data outside expected ranges

V3*   Horizon aggregation problem

V4    Misclassification in  sampling  class

V5*   Field data notes indicate a problem

V6    Sample contaminated but internally consistent pedon chemistry; verification
      flag for individual outlier

V7**  Double check for use  in aggregating

V8**  Internally inconsistent chemistry

V9**  Indeterminate problem or  negative value                 '


 * Informational flag only
** Data sent to EMSL-LV for confirmation
     U.S. GOVEBMOIT rainiXG OFFICE 1990/748-159/00448

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