ASTM D6044-96

NOTICE: This standard has either been superceded and replaced by a new version or discontinued.
Contact ASTM International (www.astm.org) for the latest information.
Designation: D 6044 – 96
Standard Guide for
Representative Sampling for Management of Waste and
Contaminated Media
This standard is issued under the fixed designation D 6044; the number immediately following the designation indicates the year of
original adoption or, in the case of revision, the year of last revision. A number in parentheses indicates the year of last reapproval. A
superscript epsilon (e) indicates an editorial change since the last revision or reapproval.
1. Scope responsibility of the user of this standard to establish appro-
priate safety and health practices and determine the applica-
1.1 This guide covers the definition of representativeness in
bility of regulatory limitations prior to use.
environmental sampling, identifies sources that can affect
representativeness (especially bias), and describes the at-
2. Referenced Documents
tributes that a representative sample or a representative set of
2.1 ASTM Standards:
samples should possess. For convenience, the term“ represen-
D 3370 Practices for Sampling Water from Closed Con-
tative sample” is used in this guide to denote both a represen-
duits
tative sample and a representative set of samples, unless
D 4448 Guide for Sampling Groundwater Monitoring
otherwise qualified in the text.
Wells
1.2 This guide outlines a process by which a representative
D 4547 Practice for Sampling Waste and Soils for Volatile
sample may be obtained from a population. The purpose of the
Organics
representative sample is to provide information about a statis-
D 4700 Guide for Soil Sampling from the Vadose Zone
tical parameter(s) (such as mean) of the population regarding
D 4823 Guide for Core-Sampling Submerged, Unconsoli-
some characteristic(s) (such as concentration) of its constitu-
dated Sediments
ent(s) (such as lead). This process includes the following
D 5088 Practice for Decontamination of Field Equipment
stages: (1) minimization of sampling bias and optimization of
Used at Nonradioactive Waste Sites
precision while taking the physical samples, (2) minimization
D 5792 Practice for Generation of Environmental Data
of measurement bias and optimization of precision when
Related to Waste Management Activities: Development of
analyzing the physical samples to obtain data, and (3) minimi-
Data Quality Objectives
zation of statistical bias when making inference from the
D 5956 Guide for Sampling Strategies for Heterogeneous
sample data to the population. While both bias and precision
Wastes
are covered in this guide, major emphasis is given to bias
D 6051 Guide for Composite Sampling and Field Subsam-
reduction.
pling for Environmental Waste Management Activities
1.3 This guide describes the attributes of a representative
sample and presents a general methodology for obtaining
3. Terminology
representative samples. It does not, however, provide specific
3.1 analytical unit, n—the actual amount of the sample
or comprehensive sampling procedures. It is the user’s respon-
material analyzed in the laboratory.
sibility to ensure that proper and adequate procedures are used.
3.2 bias, n—a systematic positive or negative deviation of
1.4 The assessment of the representativeness of a sample is
the sample or estimated value from the true population value.
not covered in this guide since it is not possible to ever know
3.2.1 Discussion—This guide discusses three sources of
the true value of the population.
bias—sampling bias, measurement bias, and statistical bias.
1.5 Since the purpose of each sampling event is unique, this
There is a sampling bias when the value inherent in the
guide does not attempt to give a step by step account of how to
physical samples is systematically different from what is
develop a sampling design that results in the collection of
inherent in the population.
representative samples.
There is a measurement bias when the measurement process
1.6 Appendix X1 contains two case studies, which discuss
produces a sample value systematically different from that
the factors for obtaining representative samples.
inherent in the sample itself, although the physical sample is
1.7 This standard does not purport to address all of the
safety concerns, if any, associated with its use. It is the
Annual Book of ASTM Standards, Vol 11.01.
1 3
This guide is under the jurisdiction of ASTM Committee D34 on Waste Annual Book of ASTM Standards, Vol 11.04.
Management and is the direct responsibility of Subcommittee D34.01.01 on Annual Book of ASTM Standards, Vol 04.08.
Planning for Sampling. Annual Book of ASTM Standards, Vol 11.02.
Current edition approved Nov. 10, 1996. Published January 1997. Annual Book of ASTM Standards, Vol 04.09.
Copyright © ASTM, 100 Barr Harbor Drive, West Conshohocken, PA 19428-2959, United States.
NOTICE: This standard has either been superceded and replaced by a new version or discontinued.
Contact ASTM International (www.astm.org) for the latest information.
D 6044
itself unbiased. Measurement bias can also include any sys- presence of fundamental heterogeneity (or fundamental error)
tematic difference between the original sample and the sample in the population that sampling variance arises. Degree of
analyzed, when the analyzed sample may have been altered sampling variance defines the degree of precision in estimating
due to improper procedures such as improper sample preser- the population parameter using the sample data. The smaller
vation or preparation, or both. the sampling variance is, the more precise the estimate is. See
also sampling error.
There is a statistical bias when, in the absence of sampling
3.11 homogeneity, n— the condition of the population under
bias and measurement bias, the statistical procedure produces a
which all items of the population are identical with respect to
biased estimate of the population value.
the characteristic(s) of interest.
Sampling bias is considered the most important factor
3.12 judgment sampling, n—taking of a sample(s) based on
affecting inference from the samples to the population.
judgment that it will more or less represent the average
3.3 biased sampling, n—the taking of a sample(s) with prior
condition of the population.
knowledge that the sampling result will be biased relative to
3.12.1 Discussion—The sampling location(s) is selected
the true value of the population.
because it is judged to be representative of the average
3.3.1 Discussion—This is the taking of a sample(s) based condition of the population. It can be effective when the
population is relatively homogeneous or when the professional
on available information or knowledge, especially in terms of
visible signs or knowledge of contamination. This kind of judgment is good. It may or may not introduce bias. It is a
useful sampling approach when precision is not a concern. This
sampling is used to detect the presence of localized contami-
is one form of authoritative sampling (see biased sampling.)
nation or to identify the source of a contamination. The
3.13 population, n— the totality of items or units of
sampling results are not intended for generalization to the
materials under consideration.
entire population. This is one form of authoritative sampling
3.14 representative sample, n—a sample collected in such a
(see judgment sampling.)
manner that it reflects one or more characteristics of interest (as
3.4 characteristic, n—a property of items in a sample or
defined by the project objectives) of a population from which
population that can be measured, counted, or otherwise ob-
it is collected.
served, such as viscosity, flash point, or concentration.
3.14.1 Discussion—A representative sample can be a single
3.5 composite sample, n—a combination of two or more
sample, a collection of samples, or one or more composite
samples.
samples. A single sample can be representative only when the
3.6 constituent, n— an element, component, or ingredient of population is highly homogeneous.
the population. 3.15 representative sampling, n—the process of obtaining a
representative sample or a representative set of samples.
3.6.1 Discussion—If a population contains several contami-
3.16 representative set of samples, n—a set of samples that
nants (such as acetone, lead, and chromium), these contami-
collectively reflect one or more characteristics of interest of a
nants are called the constituents of the population.
population from which they were collected. See representative
3.7 Data Quality Objectives, DQOs, n—qualitative and
sample.
quantitative statements derived from a DQO process describing
3.17 sample, n—a portion of material that is taken for
the decision rules and the uncertainties of the decision(s)
testing or for record purposes.
within the context of the problem(s) (see Practice D 5792).
3.17.1 Discussion—Sample is a term with numerous mean-
3.8 Data Quality Objective Process—a quality management
ings. The scientist collecting physical samples (for example,
tool based on the Scientific Method and developed by the U.S.
from a landfill, drum, or monitoring well) or analyzing samples
Environmental Protection Agency to facilitate the planning of
considers a sample to be that unit of the population that was
environmental data collection activities. The DQO process
collected and placed in a container. A statistician considers a
enables planners to focus their planning efforts by specifying
sample to be a subset of the population, and this subset may
the use of data (the decision), the decision criteria (action consist of one or more physical samples. To minimize confu-
level), and the decision maker’s acceptable decision error rates. sion, the term sample, as used in this guide, is a reference to
either a physical sample held in a sample container, or that
The products of the DQO process are the DQOs (see Practice
D 5792). portion of the population that is subjected to in situ measure-
ments, or a set of physical samples. See representative sample.
3.9 error, n—the random or systematic deviation of the
3.17.1.1 The term sample size also means different things to
observed sample value from its true value (see bias and
the scientist and the statistician. To avoid confusion, terms such
sampling error).
as sample mass/sample volume and number of samples are
3.10 heterogeneity, n— the condition or degree of the
used instead of sample size.
population under which all items of the population are not
3.18 sampling error— the systematic and random devia-
identical with respect to the characteristic(s) of interest.
tions of the sample value from that of the population. The
3.10.1 Discussion—Although the ultimate interest is in the
statistical parameter such as the mean concentration of a
constituent of the population, heterogeneity relates to the
Pitard, F. F., “Pierre Gy’s Sampling Theory and Sampling Practice: Heteroge-
presence of differences in the characteristics (for example,
neity, Sampling Correctness and Statistical Process Control,” 2nd ed., CRC Press
concentration) of the units in the population. It is due to the Publishers, 1993.
NOTICE: This standard has either been superceded and replaced by a new version or discontinued.
Contact ASTM International (www.astm.org) for the latest information.
D 6044
systematic error is the sampling bias. The random error is the agement and contaminated media.
sampling variance.
5. Representative Samples
3.18.1 Discussion—Before the physical samples are taken,
5.1 Samples are taken to infer about some statistical param-
potential sampling variance comes from the inherent popula-
eter(s) of the population regarding some characteristic(s) of its
tion heterogeneity (sometimes called the “fundamental error,”
constituent(s) of interest. This is discussed in the following
see heterogeneity). In the physical sampling stage, additional
sections.
contributors to sampling variance include random errors in
5.2 Samples—When a representative sample consists of a
collecting the samples. After the samples are collected, another
single physical sample, it is a sample that by itself reflects the
contributor is the random error in the measurement process. In
characteristics of interest of the population. On the other hand,
each of these stages, systematic errors can occur as well, but
when a representative sample consists of a set of physical
they are the sources of bias, not sampling variance.
samples, the samples collectively reflect some characteristics
3.18.1.1 Sampling variance is often used to refer to the total
of the population, though the samples individually may not be
variance from the various sources.
representative. In most cases, more than one physical sample is
3.19 stratum, n—a subgroup of the population separated in
necessary to characterize the population, because the popula-
space or time, or both, from the remainder of the population,
tion in environmental sampling is usually heterogeneous.
being internally similar with respect to a target characteristic of
5.3 Constituents and Characteristics—A population can
interest, and different from adjacent strata of the population.
possess many constituents, each with many characteristics.
3.19.1 Discussion—A landfill may display spatially sepa-
Usually it is only a subset of these constituents and character-
rated strata, such as old cells containing different wastes than
istics that are of interest in the context of the stated problem.
new cells. A waste pipe may discharge into temporally sepa-
Therefore, samples need to be representative of the population
rated strata of different constituents or concentrations, or both,
only in terms of these constituent(s) and characteristic(s) of
if night-shift production varies from the day shift. In this guide,
interest. A sampling plan needs to be designed accordingly.
strata refer mostly to the stratification in the concentrations of
5.4 Parameters—Similarly, samples need to be representa-
the same constituent(s).
tive of the population only in the parameter(s) of interest. If the
3.20 subsample, n— a portion of the original sample that is
interest is only in estimating a parameter such as the population
taken for testing or for record purposes.
mean, then composite samples, when taken correctly, will not
4. Significance and Use
be biased and therefore constitute a representative sample
4.1 Representative samples are defined in the context of the (regarding bias) for that parameter. On the other hand, if the
study objectives. interest happens to be the estimation of the population variance
4.2 This guide defines the meaning of a representative (of individual sampling units), another parameter, then the
sample, as well as the attributes the sample(s) needs to have in variance of the composite samples is a biased e
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