United States
Environmental Protection
Agency
Environmental Monitoring
Systems Laboratory
Las Vegas NV 89193-3478
Research and Development
EPA/600/S8-89/046 Aug. 1989
Project Summary
Soil Samp
Assurance
Second Edition
Delbert S. Barth, Benjarr
Kenneth W. Brown
Use of the first edition
Sampling Quality Assur
Guide" as a text in a se
inars conducted at various U.S. EPA
Regional Offices elicited many con-
structive comments for improve-
ments from seminar attendees. Many
of these suggested improvements
have been incorporated in this se-
cond edition.
Specifically, the references have
been updated, particula
the incorporation of rece
guidelines documents. M
has been given to ex
design, specifically to pr
developing data quality
The statistical coverag
expanding considerably t
introduction to applicati
nt U.S. EPA
re attention
perimental
cedures for
objectives.
has been
i include an
ns of geo-
statistics and a discussioih of require-
ing Quality
User's Guide-
n J. Mason, Thomas H. Starks, and
of the "Soil
nee User's
ies of sem-
rly through
ments for the definition oi support in
conjunction with guidance for soil
sampling.
This report is intended to be a liv-
ing document providing state-of-the-
art guidance. Accordingly, from time
to time revisions will be prepared to
maintain harmony with improvements
in soil sampling quality assurance
methodology. Future revisions will be
prepared, and authorship identified,
on a chapter-by-chapter basis.
This Project Summary was devel-
oped by EPA's Environmental Monitor-
ing Systems Laboratory, Las Vegas,
NV, to announce key findings of the
research project that is fully docu-
mented in a separate report of the
same title (see Project Report
ordering Information at back).
An adequate quality assurance/quality
control (QA/'QC) program requires the
identification and quantification of all
sources of error associated with each
step of a monitoring program so that the
resulting data will be known quality. The
components of error, or variance, include
those associated with sampling, sample
preparation, extraction, analysis, and
residual error. In the past, maior empha-
sis often has been placed on QA/QC
aspects of sample analysis and closely
associated operations such as sample
preparation and extraction. For monitor-
ing a relatively inhomogeneous medium
such as soil, the sampling component of
variance will usually significantly exceed
the analysis component Thus, in this
case a minimum adequate QA/QC plan
must include a section dealing with soil
sampling. The purpose of this document
is to provide guidance in QA/'QC aspects
related to soil sampling
Generally soil monitoring is undertaken
to carry out the provisions and intent of
applicable environmental laws with high
priority requirements associated with haz-
ardous waste management The objec-
tives of soil monitoring programs are
often to obtain data on the basis of which
to answer one or more of the following
questions:
• Are the concentrations of specified soil
pollutants in a defined study region
significantly different from the concen-
trations in a control region?
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• Do the concentrations of specified soil
pollutants in a defined region exceed
established threshold action levels^
• At the measured concentrations of
specified soil pollutants in a defined
study region, what is the associated
risk of adverse effects to public health,
welfare, or the environment?
For each of these applications, the
QA/QC methods and procedures cannot
be specified without giving careful
consideration to the consequences of
making an error, for example, in a
decision to require or not to require
cleanup of a contaminated region. It
follows in general that to be maximally
cost-effective and defensible the QA/QC
objectives of a soil monitoring program
cannot be separated from the objectives
of the soil monitoring program itself.
In general, the progression of events
leading to the development of an ade-
quate Quality Assurance Program Plan
(QAPP) follows the outline shown below.
1 State study objectives.
2. Evaluate impacts of mistakes.
3. Define data quality objectives
(DQOs).
4. Design study to achieve DQOs.
5. Design QAPP to confirm achievement
of DQOs.
Often it will not be possible to specify
in advance what DQOs are possible to
achieve. In such cases DQO goals should
be set, a QAPP prepared, and a pilot
study conducted to determine the
achievability of the goals.
Present U.S. EPA guidance for
development of DQOs requires that
specifications for the following factors
must be addressed:
precision,
accuracy,
completeness,
representativeness, and
comparability.
A sixth factor of importance to all of
the above is the detection limit of the
measurement method used. Other
important factors which should be
considered in specifying DQOs include:
• acceptable probability of a Type I
error (judging a clean area to be dirty);
• acceptable probability of a Type II
error (judging a dirty area to be clean);
and
• desired minimum detectable relative
difference between two different geo-
graphical areas.
The development of DQOs involves an
iterative interaction between management
and technical staff. Management ident-
ifies the needs and resources available.
The technical staff develops guidance for
assisting management in making the
decisions required to develop the DQOs.
The DQO process usually involves a
three-stage process as outlined below.
1. Identify decision types.
2. Identify data uses/needs.
3. Design data collection program.
The end result is site-specific guidance
for evaluating and interpreting sampling
data.
Control samples are normally as
important to a soil monitoring study as
are samples taken from the study region.
The data from control samples aid in the
interpretation of the results from the
study region and also help to identify
sources and important transport routes
for soil pollutants. Accordingly, the same
level of effort and degree of QA/QC
checks should go into selecting and sam-
pling a control region as goes into sam-
pling the study region.
In sampling of a continuous medium
such as soil, it is necessary to put extra
emphasis on the definition of a sampling
unit. In addition to having a specified lo-
cation, each sampling unit of soil has a
certain three-dimensional volume, shape,
and orientation. These latter three
characteristics, when taken together, are
called the support of the sample.
Changes in support not only change th|
means of distribution, they also chang<
the variances of concentrations and th<
correlations of concentrations betweei
sampling units.
It is essential that any action level fo
soils be defined as a concentration over;
particular support and location relative ti
the ground surface. In this definition of ai
action level, the support is referred to n
this document as the action support. Fo
example, the action support might bi
defined as the top ten cm of soil over
square of 100 m2.
The following table provides recom
mendations, as part of the DQO process
for confidence levels, powers, and min
mum detectable relative increases ove
background for different operation;
situations.
Both Type I (false positive) and Type
(false negative) errors should b
considered in hypothesis testing. Table
and an equation are provided for use i
determining the required number (
samples to achieve defined confidenc
levels and powers. The location of sarr
pling is also important. Stratification <
the sampling region may reduce th
variance in cases where the variance
considered to be unacceptably largi
Compositing of samples is generally m
recommended since it allows no estimai
of the variance among the samples beir
composited. However, some compositir
of samples increases the representativi
ness of samples and may be justified c
that basis.
Suggested types of QA/QC sampk
include various types of blanks, labo
atory control standards calibration cne<
standards, triplicate samples (splits), du|
licate samples, various kinds of au<
samples, etc. How many samples of ea(
type would be needed in a specific stu<
is a question of considerable important
The recommended approach is
determine how each type of QA/C
sample is to be employed and th<
Preliminary Site Investigation
Emergency Cleanup
Planned Removal and Remedial
Response
Confidence Level
(1 -a)
70 - 80%
80 - 90%
90 - 95%
Power
(1 -P)
90 - 95%
90 - 95%
90 - 95%
Relative Increase ovt
Backround lWO(ns
VRVupl to be
Detectable with a Pr<
bability (1 - 0)
10 - 20%
70 - 20%
10 - 20%
where a = probability of a Type I error and
f - probability of a Type II error.
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•Determine the number fro that type based
n the use. For example, field duplicates
are used to estimate the combined
variance contribution of several sources
of variation. Hence, the number of field
duplicates to be obtained in a study
should be dictated by how precise one
wants that estimate of variance to be.
Geostatistics (or kriging) is an ap-
plication of classical statistical theory to
geological measurements that takes into
account the spatial continuities of geo-
logical variables in estimating the distri-
bution of variables. In many ways, geo-
statistics is for measurements taken in 2-,
3-, and 4-dimensional space (the three
spatial dimensions and the time
dimension), what time series is for
measurements taken in one-dimensional
space (time). However, a principal use of
time series is in forecasting; in geosta-
tistics the principal emphasis is on inter-
polation. Nevertheless, both statistical
procedures emphasize modeling the
process to get an insight into the system
being investigated.
The application of classical statistical
procedures to soil measurement data
requires that the samples be collected
randomly (i.e. not on systematic grids),
that the data be independent and
identically distributed (with the distri-
jution being a normal distribution), and
that the measurement error variance
(particularly the between-batch error
variance) be a very small part of the total
variance of the measurements in a
sample survey of a region.
In man soil sampling studies one or all
of the following questions will be of
primary interest.
• Are there any action supports within
the study area that have pollutant
concentrations above action level?
• Where are the above-action-level
action supports located?
• What is the spatial distribution of
pollutant concentration levels among
action supports that have pollutant
concentrations above action level?
The problem with posing soil sampling
methods and objectives in terms of
population means is that the mean will
depend on the size of the area chosen
and the distribution of contamination
throughout that area. For example, the
mean in a small area may exceed the
action level; but if the size of small area
is increased by adding a substantial
amount of less contaminated soil, the
mean in the larger area may not exceed
;e action limit. Decisions on the need
r remedial action should not be based
on how one chooses the size of the area
to be sampled, but rather on whether
action supports exist that are above
designated action limits. A comparison of
means is reasonable in comparing pollu-
tant concentrations at a background site
with pollutant concentrations of a site
down-gradient from a suspected hazard-
ous waste source. Also, cleanup areas
may be defined so that the average
concentration in those units of soil may
be compared with a standard.
It follows from the above discussion
that for most applications, geostatistical
procedures for designing soil sampling
studies and analyzing resultant data are
generally preferred over classical statis-
tical procedures.
Once objectives have been defined for
a soil monitoring study, a total study
protocol, including an appropriate QA/QC
program must be prepared. Usually not
enough is known about the sources and
transport properties of the soil pollutants
to accomplish this in a cost-effective
manner without additional study. The
suggested approach is to conduct an
exploratory study including both a
literature and information search followed
by selected field measurements based
on an assumed dispersion model. The
data resulting from this exploratory study
serve as the basis for the more definitive
total study protocol. If one is dealing with
a situation requiring possible emergency
action to protect public health, it is
necessary to compress the planning and
study design into a short time period and
proceed to the definitive study without
delay. In either case, the objectives of the
monitoring study constitute the driving
force for all elements of the study design,
including the QA/QC aspects.
To develop the exploratory study
protocol with its associated QA/QC plan,
one needs to combine into an assumed
dispersion model, the information
obtained prior to any field measurements.
On the basis of this model, the standard
deviation of the mean for soil samples is
estimated. Value judgments are used to
define required precision and confidence
levels (related to acceptable levels of
Type I or Type II error). A control region
is selected. The numbers of required
samples may then be calculated.
Additional samples should be required to
validate the assumed model. The
locations of the sampling sites should be
selected by an appropriate combination
of judgmental (use of the assumed
model), systematic (to allow for the fact
that the model may be wrong), and
random (to minimize bias) sampling.
Sampling and sample handling must be
accomplished according to standardized
procedures based on principles designed
to achieve data of both adequate quality
and maximal cost-effectiveness. Particu-
lar attention should be given to factors
surrounding the disposition of non-soil
material collected with the soil samples.
The requirements for QA/QC for the
exploratory study need not be a stringent
as for the more definitive study in the
sense that acceptable precisions and
confidence levels may be relaxed some-
what. Allowance should be made,
however, for the collection of a modest
additional number of QA/QC samples
over that specified in the QA/QC plan to
verify that the QA/'QC study design is
adequately achieving its assigned objec-
tives. Also, all normal analytical QA/'QC
checks should be used.
If the exploratory study is conducted
well, it will provide some data for
achieving the overall objectives of the
total monitoring study, it will provide a
check of the feasibility and efficacy of all
aspects of the monitoring design
including the QA/QC plan; it will serve as
a training vehicle for all participants; it will
pinpoint where additional measurements
need to be made; and it will provide a
body of information and data which can
be incorporated into the final report for
the total monitoring study.
For the more definitive study, the se-
lection of numbers of samples and sam-
pling sites, sample collection procedures,
and sample handling methods and proce-
dures follow and build on the principles
discussed and results obtained in the
exploratory study.
Frequency of sampling is an important
aspect of the more definitive study which
usually cannot be addressed in the
exploratory study because of the
relatively short time span over which the
exploratory study is conducted. The
required frequency of sampling depends
on the objectives of the study, the
sources of pollution, the pollutants of
interest, transport rates, and disappear-
ance rates (physical, chemical, or
biological transformations as well as dilu-
tion or dispersion). Sampling frequency
may be related to changes over time,
season, or precipitation. An approach that
has been used successfully has been to
provide intensive sampling early m the
life of the study (e.g., monthly for the first
year) and then to decrease the frequency
as the levels begin to drop. The important
principle is that the sampling should be
conducted often enough that changes in
the concentrations of soil pollutants
important to the achievement of the
monitoring objectives are not missed.
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The important questions to be
answered in the analyses and interpreta-
tion of QA/QC data are: "What is the
quality of the data?" and "Could the
same objective have been achieved
through an improved QA/QC design
which may have required fewer re-
sources?" It is desirable to provide sum-
marized tables of validated QA/QC data
in the final report. This approach allows
users to verify the reported results as
well as begin to build a body of QA/QC
experimental data in the literature which
allow comparisons to be made among
studies. Special emphasis should be
placed on how overall levels of precision
and confidence were derived from the
data. If portions of the study results are
ambiguous and supportable conclusions
cannot be drawn with regard to the reli-
ability of the data, that situation must be
clearly stated.
The adequacy of all aspects of the
QA/QC plan should be examined in detail
with emphasis on defining for future
studies an appropriate minimum ade-
quate plan Some aspects of the QA/QC
plan may have been too restrictive; some
may not have been restrictive enough.
Soil monitoring studies should have
checks and balances built into the QA/QC
plan which will identify early in the study
whether the plan is adequate and,
ifrequired, allow for corrective action to
be taken before the study continues.
This is one of the major advantages of
conducting an exploratory study.
There is insufficient knowledge dealing
with soil monitoring studies to state with
confidence which portions of the QA/QC
plan will be generally applicable to all soil
monitoring studies and which must vary
depending on site-specific factors. As
experience is gained, it may be possible
to provide more adequate guidance on
this subject. In the meantime, it is
recommended that many important
factors of QA/QC plans be considered as
site-specific until proven otherwise.
Another important aspect of QA/QC is
auditing The purpose of an audit is to
insure that all aspects of the QA/QC
system planned for the project are in
place and functioning well. This include
all aspects of field, sample bank, and
laboratory operations. Whenever a prob-
lem is identified, corrective action should
be initiated and pursued until corrected.
Sample chain-of-custody procedures and
raw data are checked as appropriate, and
results of blind QA/QC samples routinely
inserted into the sample load are re-
viewed. Spot checks of sampling
methods and techniques, sampling '3nd
analysis calculations, and data tran-
scription are performed. Checks are
Delbert S. Barth, Benjamin J. Mason, and Thomas H. Starks, are with the University
of Nevada, Las Vegas, NV 89154; the EPA author Kenneth W. Brown ( also the
EPA Protect Officer, see below) is with the Environmental Monitoring Systems
Laboratory,Las Vegas, NV 89193-3478.
The complete report, entitled "Soil Sampling Quality Assurance User's Guide—
Second Edition," (Order No. PB 89-189 8641 AS; Cost: $28.95, subject to change)
will be available only from:
National Technical Information Service
5285 Port Royal Road
Springfield, VA22161
Telephone: 703-487-4650
The EPA Project Officer can be contacted af:
Environmental Monitoring Systems Laboratory
U.S. Environmental Protection Agency
Las Vegas, NV 89193-3478
made to ascertain that required doci
mentation has been maintained and in I
orderly fashion, that each of the recorde
items is properly categorized, and cros:
checking can be easily accomplishei
Checks are made to insure that the da
recording conforms to strict docume
control protocols and the program
QA/QC plan
It is recommended that an audit of tf
overall QA/QC plan for sample docume
tation, collection, preparation, storag
and transfer procedures be perform*
just before sampling starts. This is
review critically the entire samplir
operation to determine the need for ai
corrective action early in the program
The project leader of a soil monitom
project is responsible for ascertaining tr
all members of his project team ha
adequate training and experience to car
out satisfactorily their assigned missio
and functions. This is normally acco
plished through a combination of requir
classroom training, briefings on t
specific monitoring project about to
implemented, and field training exercis<
Special training programs should
completed by all personnel prior to th
involvement in conducting audits
US. OFFICIAL MAIL
United States
Environmental Protection
Agency
Center for Environmental Research
Information
Cincinnati OH 45268
Official Business
Penalty for Private Use $300
EPA/600/S8-89/046
000085833 PS
AGE1CI
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