ASTM D6044-96(2009)
(Guide)Standard Guide for Representative Sampling for Management of Waste and Contaminated Media
Standard Guide for Representative Sampling for Management of Waste and Contaminated Media
SIGNIFICANCE AND USE
Representative samples are defined in the context of the study objectives.
This guide defines the meaning of a representative sample, as well as the attributes the sample(s) needs to have in order to provide a valid inference from the sample data to the population.
This guide also provides a process to identify the sources of error (both systematic and random) so that an effort can be made to control or minimize these errors. These sources include sampling error, measurement error, and statistical bias.
When the objective is limited to the taking of a representative (physical) sample or a representative set of (physical) samples, only potential sampling errors need to be considered. When the objective is to make an inference from the sample data to the population, additional measurement error and statistical bias need to be considered.
This guide does not apply to the cases where the taking of a nonrepresentative sample(s) is prescribed by the study objective. In that case, sampling approaches such as judgment sampling or biased sampling can be taken. These approaches are not within the scope of this guide.
Following this guide does not guarantee that representative samples will be obtained. But failure to follow this guide will likely result in obtaining sample data that are either biased or imprecise, or both. Following this guide should increase the level of confidence in making the inference from the sample data to the population.
This guide can be used in conjunction with the DQO process (see Practice D 5792).
This guide is intended for those who manage, design, and implement sampling and analytical plans for waste management and contaminated media.
SCOPE
1.1 This guide covers the definition of representativeness in environmental sampling, identifies sources that can affect representativeness (especially bias), and describes the attributes that a representative sample or a representative set of samples should possess. For convenience, the term“ representative sample” is used in this guide to denote both a representative sample and a representative set of samples, unless otherwise qualified in the text.
1.2 This guide outlines a process by which a representative sample may be obtained from a population. The purpose of the representative sample is to provide information about a statistical parameter(s) (such as mean) of the population regarding some characteristic(s) (such as concentration) of its constituent(s) (such as lead). This process includes the following stages: (1) minimization of sampling bias and optimization of precision while taking the physical samples, (2) minimization of measurement bias and optimization of precision when analyzing the physical samples to obtain data, and (3) minimization of statistical bias when making inference from the sample data to the population. While both bias and precision are covered in this guide, major emphasis is given to bias reduction.
1.3 This guide describes the attributes of a representative sample and presents a general methodology for obtaining representative samples. It does not, however, provide specific or comprehensive sampling procedures. It is the user's responsibility to ensure that proper and adequate procedures are used.
1.4 The assessment of the representativeness of a sample is not covered in this guide since it is not possible to ever know the true value of the population.
1.5 Since the purpose of each sampling event is unique, this guide does not attempt to give a step by step account of how to develop a sampling design that results in the collection of representative samples.
1.6 Appendix X1 contains two case studies, which discuss the factors for obtaining representative samples.
1.7 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and ...
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Designation: D6044 − 96(Reapproved 2009)
Standard Guide for
Representative Sampling for Management of Waste and
Contaminated Media
This standard is issued under the fixed designation D6044; the number immediately following the designation indicates the year of
original adoption or, in the case of revision, the year of last revision.Anumber in parentheses indicates the year of last reapproval.A
superscript epsilon (´) indicates an editorial change since the last revision or reapproval.
1. Scope 1.6 Appendix X1 contains two case studies, which discuss
the factors for obtaining representative samples.
1.1 This guide covers the definition of representativeness in
1.7 This standard does not purport to address all of the
environmental sampling, identifies sources that can affect
safety concerns, if any, associated with its use. It is the
representativeness (especially bias), and describes the attri-
responsibility of the user of this standard to establish appro-
butes that a representative sample or a representative set of
priate safety and health practices and determine the applica-
samples should possess. For convenience, the term“ represen-
bility of regulatory limitations prior to use.
tative sample” is used in this guide to denote both a represen-
tative sample and a representative set of samples, unless
2. Referenced Documents
otherwise qualified in the text.
2.1 ASTM Standards:
1.2 This guide outlines a process by which a representative
D3370Practices for Sampling Water from Closed Conduits
samplemaybeobtainedfromapopulation.Thepurposeofthe
D4448GuideforSamplingGround-WaterMonitoringWells
representative sample is to provide information about a statis-
D4547Guide for Sampling Waste and Soils for Volatile
tical parameter(s) (such as mean) of the population regarding
Organic Compounds
some characteristic(s) (such as concentration) of its constitu-
D4700Guide for Soil Sampling from the Vadose Zone
ent(s) (such as lead). This process includes the following
D4823Guide for Core Sampling Submerged, Unconsoli-
stages: (1) minimization of sampling bias and optimization of
dated Sediments
precision while taking the physical samples, (2) minimization
D5088Practice for Decontamination of Field Equipment
of measurement bias and optimization of precision when
Used at Waste Sites
analyzing the physical samples to obtain data, and (3) minimi-
D5792Practice for Generation of Environmental Data Re-
zation of statistical bias when making inference from the
lated to Waste Management Activities: Development of
sample data to the population. While both bias and precision
Data Quality Objectives
are covered in this guide, major emphasis is given to bias
D5956Guide for Sampling Strategies for Heterogeneous
reduction.
Wastes
1.3 This guide describes the attributes of a representative
D6051Guide for Composite Sampling and Field Subsam-
sample and presents a general methodology for obtaining
pling for Environmental Waste Management Activities
representative samples. It does not, however, provide specific
or comprehensive sampling procedures. It is the user’s respon-
3. Terminology
sibilitytoensurethatproperandadequateproceduresareused.
3.1 analytical unit, n—the actual amount of the sample
1.4 The assessment of the representativeness of a sample is
material analyzed in the laboratory.
not covered in this guide since it is not possible to ever know
3.2 bias, n—a systematic positive or negative deviation of
the true value of the population.
the sample or estimated value from the true population value.
1.5 Sincethepurposeofeachsamplingeventisunique,this
3.2.1 Discussion—This guide discusses three sources of
guidedoesnotattempttogiveastepbystepaccountofhowto
bias—sampling bias, measurement bias, and statistical bias.
develop a sampling design that results in the collection of
There is a sampling bias when the value inherent in the
representative samples.
physical samples is systematically different from what is
inherent in the population.
This guide is under the jurisdiction of ASTM Committee D34 on Waste
Management and is the direct responsibility of Subcommittee D34.01.01 on
Planning for Sampling. For referenced ASTM standards, visit the ASTM website, www.astm.org, or
Current edition approved Feb. 1, 2009. Published March 2009. Originally contact ASTM Customer Service at service@astm.org. For Annual Book of ASTM
approved in 1996. Last previous edition approved in 2003 as D6044–96(2003). Standards volume information, refer to the standard’s Document Summary page on
DOI: 10.1520/D6044-96R09. the ASTM website.
Copyright © ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959. United States
D6044 − 96 (2009)
There is a measurement bias when the measurement process presence of differences in the characteristics (for example,
produces a sample value systematically different from that concentration) of the units in the population. It is due to the
inherent in the sample itself, although the physical sample is presence of fundamental heterogeneity (or fundamental error)
itself unbiased. Measurement bias can also include any sys- in the population that sampling variance arises. Degree of
tematic difference between the original sample and the sample samplingvariancedefinesthedegreeofprecisioninestimating
analyzed, when the analyzed sample may have been altered the population parameter using the sample data. The smaller
due to improper procedures such as improper sample preser- the sampling variance is, the more precise the estimate is. See
vation or preparation, or both. also sampling error.
There is a statistical bias when, in the absence of sampling
3.11 homogeneity, n—theconditionofthepopulationunder
biasandmeasurementbias,thestatisticalprocedureproducesa
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—thetakingofasample(s)withprior
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—Thisisthetakingofasample(s)basedon
condition of the population. It can be effective when the
available information or knowledge, especially in terms of
populationisrelativelyhomogeneousorwhentheprofessional
visible signs or knowledge of contamination. This kind of
judgment is good. It may or may not introduce bias. It is a
sampling is used to detect the presence of localized contami-
usefulsamplingapproachwhenprecisionisnotaconcern.This
nation or to identify the source of a contamination. The
is one form of authoritative sampling (see biased sampling.)
sampling results are not intended for generalization to the
3.13 population, n—the totality of items or units of materi-
entire population. This is one form of authoritative sampling
als under consideration.
(see judgment sampling.)
3.14 representative sample, n—a sample collected in such a
3.4 characteristic, n—a property of items in a sample or
mannerthatitreflectsoneormorecharacteristicsofinterest(as
population that can be measured, counted, or otherwise
defined by the project objectives) of a population from which
observed, such as viscosity, flash point, or concentration.
it is collected.
3.5 composite sample, n—a combination of two or more
3.14.1 Discussion—Arepresentative sample can be a single
samples.
sample, a collection of samples, or one or more composite
3.6 constituent, n—anelement,component,oringredientof
samples.Asingle sample can be representative only when the
the population.
population is highly homogeneous.
3.6.1 Discussion—If a population contains several contami-
3.15 representative sampling, n—the process of obtaining a
nants (such as acetone, lead, and chromium), these contami-
representative sample or a representative set of samples.
nants are called the constituents of the population.
3.16 representative set of samples, n—a set of samples that
3.7 Data Quality Objectives, DQOs, n—qualitative and
collectively reflect one or more characteristics of interest of a
quantitativestatementsderivedfromaDQOprocessdescribing
population from which they were collected. See representative
the decision rules and the uncertainties of the decision(s)
sample.
within the context of the problem(s) (see Practice D5792).
3.17 sample, n—a portion of material that is taken for
3.8 Data Quality Objective Process—a quality management
testing or for record purposes.
tool based on the Scientific Method and developed by the U.S.
3.17.1 Discussion—Sample is a term with numerous mean-
Environmental Protection Agency to facilitate the planning of
ings. The scientist collecting physical samples (for example,
environmental data collection activities. The DQO process
fromalandfill,drum,ormonitoringwell)oranalyzingsamples
enables planners to focus their planning efforts by specifying
considers a sample to be that unit of the population that was
the use of data (the decision), the decision criteria (action
collected and placed in a container. A statistician considers a
level),andthedecisionmaker’sacceptabledecisionerrorrates.
sample to be a subset of the population, and this subset may
The products of the DQO process are the DQOs (see Practice
consist of one or more physical samples. To minimize
D5792).
confusion,theterm sample,asusedinthisguide,isareference
3.9 error, n—the random or systematic deviation of the
to either a physical sample held in a sample container, or that
observed sample value from its true value (see bias and
portion of the population that is subjected to in situ
sampling error ).
measurements, or a set of physical samples. See representative
3.10 heterogeneity, n—the condition or degree of the popu- sample.
lation under which all items of the population are not identical
with respect to the characteristic(s) of interest.
3.10.1 Discussion—Although the ultimate interest is in the
Pitard, F. F., “Pierre Gy’s Sampling Theory and Sampling Practice:
statistical parameter such as the mean concentration of a
Heterogeneity, Sampling Correctness and Statistical Process Control,” 2nd ed.,
constituent of the population, heterogeneity relates to the CRC Press Publishers, 1993.
D6044 − 96 (2009)
3.17.1.1 Theterm sample sizealsomeansdifferentthingsto 4.6 Following this guide does not guarantee that represen-
thescientistandthestatistician.Toavoidconfusion,termssuch tativesampleswillbeobtained.Butfailuretofollowthisguide
as sample mass/sample volume and number of samples are willlikelyresultinobtainingsampledatathatareeitherbiased
used instead of sample size. or imprecise, or both. Following this guide should increase the
level of confidence in making the inference from the sample
3.18 sampling error—the systematic and random deviations
data to the population.
ofthesamplevaluefromthatofthepopulation.Thesystematic
4.7 This guide can be used in conjunction with the DQO
error is the sampling bias. The random error is the sampling
process (see Practice D5792).
variance.
3.18.1 Discussion—Before the physical samples are taken,
4.8 This guide is intended for those who manage, design,
potential sampling variance comes from the inherent popula-
and implement sampling and analytical plans for waste man-
tion heterogeneity (sometimes called the “fundamental error,”
agement and contaminated media.
see heterogeneity). In the physical sampling stage, additional
contributors to sampling variance include random errors in
5. Representative Samples
collectingthesamples.Afterthesamplesarecollected,another
5.1 Samples are taken to infer about some statistical param-
contributor is the random error in the measurement process. In
eter(s) of the population regarding some characteristic(s) of its
each of these stages, systematic errors can occur as well, but
constituent(s) of interest. This is discussed in the following
they are the sources of bias, not sampling variance.
sections.
3.18.1.1 Samplingvarianceisoftenusedtorefertothetotal
5.2 Samples—When a representative sample consists of a
variance from the various sources.
single physical sample, it is a sample that by itself reflects the
3.19 stratum, n—a subgroup of the population separated in
characteristics of interest of the population. On the other hand,
space or time, or both, from the remainder of the population,
when a representative sample consists of a set of physical
beinginternallysimilarwithrespecttoatargetcharacteristicof
samples, the samples collectively reflect some characteristics
interest, and different from adjacent strata of the population.
of the population, though the samples individually may not be
3.19.1 Discussion—A landfill may display spatially sepa-
representative.Inmostcases,morethanonephysicalsampleis
rated strata, such as old cells containing different wastes than
necessary to characterize the population, because the popula-
new cells. A waste pipe may discharge into temporally sepa-
tion in environmental sampling is usually heterogeneous.
rated strata of different constituents or concentrations, or both,
5.3 Constituents and Characteristics—A population can
ifnight-shiftproductionvariesfromthedayshift.Inthisguide,
possess many constituents, each with many characteristics.
strata refer mostly to the stratification in the concentrations of
Usually it is only a subset of these constituents and character-
the same constituent(s).
istics that are of interest in the context of the stated problem.
3.20 subsample, n—a portion of the original sample that is
Therefore, samples need to be representative of the population
taken for testing or for record purposes.
only in terms of these constituent(s) and characteristic(s) of
interest. A sampling plan needs to be designed accordingly.
4. Significance and Use
5.4 Parameters—Similarly, samples need to be representa-
4.1 Representative samples are defined in the context of the
tiveofthepopulationonlyintheparameter(s)ofinterest.Ifthe
study objectives. interestisonlyinestimatingaparametersuchasthepopulation
mean, then composite samples, when taken correctly, will not
4.2 This guide defines the meaning of a representative
be biased and therefore constitute a representative sample
sample, as well as the attributes the sample(s) needs to have in
(regarding bias) for that parameter. On the other hand, if the
order to provide a valid inference from the sample data to the
interesthappenstobetheestimati
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