ASTM D5956-96
(Guide)Standard Guide for Sampling Strategies for Heterogeneous Wastes
Standard Guide for Sampling Strategies for Heterogeneous Wastes
SCOPE
1.1 This guide is a practical, nonmathematical discussion for heterogeneous waste sampling strategies. This guide is consistent with the particulate material sampling theory, as well as inferential statistics, and may serve as an introduction to the statistical treatment of sampling issues.
1.2 This guide does not provide comprehensive sampling procedures, nor does it serve as a guide to any specification. It is the responsibility of the user to ensure appropriate procedures are used.
1.3 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 determine the applicability of regulatory limitations prior to use.
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Designation: D 5956 – 96
Standard Guide for
Sampling Strategies for Heterogeneous Wastes
This standard is issued under the fixed designation D 5956; 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 helpful when sampling is expensive, hazardous, or difficult.
2.1.5 correlation, n—the mutual relation of two or more
1.1 This guide is a practical, nonmathematical discussion
things.
for heterogeneous waste sampling strategies. This guide is
2.1.6 database, n—a comprehensive collection of related
consistent with the particulate material sampling theory, as
data organized for quick access.
well as inferential statistics, and may serve as an introduction
2.1.6.1 Discussion—Database as used in this guide refers to
to the statistical treatment of sampling issues.
a collection of data generated by the collection and analysis of
1.2 This guide does not provide comprehensive sampling
more than one physical sample.
procedures, nor does it serve as a guide to any specification. It
2.1.7 data quality objectives (DQO), n—DQOs are qualita-
is the responsibility of the user to ensure appropriate proce-
tive and quantitative statements derived from the DQO process
dures are used.
describing the decision rules and the uncertainties of the
1.3 This standard does not purport to address all of the
decision(s) within the context of the problem(s).
safety concerns, if any, associated with its use. It is the
2.1.8 data quality objective process, n—a quality manage-
responsibility of the user of this standard to establish appro-
ment tool based on the scientific method and developed by the
priate safety and health practices and determine the applica-
U.S. Environmental Protection Agency to facilitate the plan-
bility of regulatory limitations prior to use.
ning of environmental data collection activities.
2. Terminology
2.1.8.1 Discussion—The DQO process enables planners to
focus their planning efforts by specifying the use of the data
2.1 Definitions of Terms Specific to This Standard:
(the decision), the decision criteria (action level) and the
2.1.1 attribute, n—a quality of samples or a population.
decision maker’s acceptable decision error rates. The products
2.1.1.1 Discussion—Homogeneity, heterogeneity, and prac-
of the DQO process are the DQOs.
tical homogeneity are population attributes. Representativeness
2.1.9 heterogeneity, n—the condition of the population
and intersample variance are sample attributes.
under which items of the population are not identical with
2.1.2 characteristic, n—a property of items, a sample or
respect to the characteristic of interest.
population that can be measured, counted, or otherwise ob-
2.1.10 homogeneity, n—the condition of the population
served.
under which all items of the population are identical with
2.1.2.1 Discussion—A characteristic of interest may be the
respect to the characteristic of interest.
cadmium concentration or ignitability of a population.
2.1.10.1 Discussion—Homogeneity is a word that has more
2.1.3 component, n—an easily identified item such as a
than one meaning. In statistics, a population may be considered
large crystal, an agglomerate, rod, container, block, glove,
homogeneous when it has one distribution (for example, if the
piece of wood, or concrete.
concentration of lead varies between the different items that
2.1.4 composite sample, n—a combination of two or more
constitute a population and the varying concentrations can be
samples.
described by a single distribution and mean value, then the
2.1.4.1 Discussion—When compositing samples to detect
population would be considered homogeneous). A population
hot spots or whenever there may be a reason to determine
containing different strata would not have a single distribution
which of the component samples that constitute the composite
throughout, and in statistics, may be considered to be hetero-
are the source of the detected contaminant, it can be helpful to
geneous. The terms homogeneity and heterogeneity as used in
composite only portions of the component samples. The
this guide, however, reflect the understanding more common to
remainders of the component samples then can be archived for
chemists, geologists, and engineers. The terms are used as
future reference and analysis. This approach is particularly
described in the previous definitions and refer to the similarity
or dissimilarity of items that constitute the population. Accord-
This guide is under the jurisdiction of ASTM Committee D-34 on Waste
ing to this guide, a population that has dissimilar items would
Management and is the direct responsibility of Subcommittee D34.01 on Sampling
be considered heterogeneous regardless of the type of distri-
and Monitoring.
bution.
Current edition approved Oct. 10, 1996. Published December 1996.
Copyright © ASTM, 100 Barr Harbor Drive, West Conshohocken, PA 19428-2959, United States.
D 5956
2.1.11 item, n—a distinct part of a population (for example, 2.1.18 sampling, n—obtaining a portion of the material
microscopic particles, macroscopic particles, and 20-ft long concerned.
steel beams).
2.1.19 stratum, n—a subgroup of a population separated in
2.1.11.1 Discussion—The term component defines a subset space or time, or both, from the remainder of the population,
of items. Components are those items that are easily identified being internally consistent with respect to a target constituent
as being different from the remainder of items that constitute or property of interest, and different from adjacent portions of
the population. The identification of components may facilitate the population.
the stratification and sampling of a highly stratified population 2.1.19.1 Discussion—A landfill may display spatially sepa-
when the presence of the characteristic of interest is correlated
rated strata since old cells may contain different wastes than
with a specific component. new cells. A waste pipe may discharge temporally separated
2.1.12 population, n—the totality of items or units under strata if night-shift production varies from the day shift. Also,
consideration. a waste may have a contaminant of interest associated with a
particular component in the population, such as lead exclu-
2.1.13 practical homogeneity, n—the condition of the popu-
sively associated with a certain particle size.
lation under which all items of the population are not identical.
2.1.19.2 Discussion—Highly stratified populations consist
For the characteristic of interest, however, the differences
between individual physical samples are not measurable or of such a large number of strata that it is not practical or
significant relative to project objectives. effective to employ conventional sampling approaches, nor
would the mean concentration of a highly stratified population
2.1.13.1 Discussion—For practical purposes, the population
be a useful predictor (that is, the level of uncertainty is too
is homogeneous.
great) for an individual subset that may be subjected to
2.1.14 random, n—lack of order or patterns in a population
evaluation, handling, storage, treatment, or disposal. Highly
whose items have an equal probability of occurring.
stratified is a relative term used to identify certain types of
2.1.14.1 Discussion—The word random is used in two
nonrandom heterogeneous populations. Classifying a popula-
different contexts in this guide. In relation to sampling, random
tion according to its level of stratification is relative to the
means that all items of a population have an equal probability
persons planning and performing the sampling, their experi-
of being sampled. In relation to the distribution of a population
ence, available equipment, budgets, and sampling objectives.
characteristic, random means that the characteristic has an
Under one set of circumstances a population could be consid-
equal probability of occurring in any and all items of the
ered highly stratified, while under a different context the same
population.
population may be considered stratified.
2.1.15 representative sample, n—a sample collected in such
2.1.19.3 Discussion—The terms stratum and strata are used
a manner that it reflects one or more characteristics of interest
in two different contexts in this guide. In relation to the
(as defined by the project objectives) of a population from
population of interest, stratum refers to the actual subgroup of
which it was collected.
the population (for example, a single truck load of lead-acid
2.1.15.1 Discussion—A representative sample can be (1)a
batteries dumped in the northeast corner of a landfill cell). In
single sample, (2) a set of samples, or (3) one or more
relation to sampling, stratum or strata refers to the subgroups
composite samples.
or divisions of the population as assigned by the sampling
2.1.16 sample, n—a portion of material that is taken for
team. When assigning sampling strata, the sampling team
testing or for record purposes.
should maximize the correlation between the boundaries of the
2.1.16.1 Discussion—Sample is a term with numerous
assigned sampling strata and the actual strata that exist within
meanings. The scientist collecting physical samples (for ex-
the population. To minimize confusion in this guide, those
ample, from a landfill, drum, or waste pipe) or analyzing
strata assigned by the sampling team will be referred to as
samples, considers a sample to be that unit of the population
sampling strata.
collected and placed in a container. In statistics, a sample is
considered to be a subset of the population, and this subset may
3. Significance and Use
consist of one or more physical samples. To minimize confu-
3.1 This guide is suitable for sampling heterogeneous
sion the term physical sample is a reference to the sample held
wastes.
in a sample container or that portion of the population that is
subjected to in situ measurements. One or more physical 3.2 The focus of this guidance is on wastes; however, the
approach described in this guide may be applicable to non-
samples, discrete samples, or aliquots are combined to form a
waste populations, as well.
composite sample. The term sample size has more than one
meaning and may mean different things to the scientist and the 3.3 Sections 4-9 describe a guide for the sampling of
statistician. To avoid confusion, terms such as sample mass or heterogeneous waste according to project objectives. Appendix
sample volume and number of samples are used instead of X1 describes an application of the guide to heterogeneous
sample size. wastes. The user is strongly advised to read Annex A1 prior to
reading and employing Sections 4-9 of this guide.
2.1.17 sample variance, n—a measure of the dispersion of a
set of results. Variance is the sum of the squares of the 3.4 Annex A1 contains an introductory discussion of het-
erogeneity, stratification, and the relationship of samples and
individual deviations from the sample mean divided by one
less than the number of results involved. It may be expressed populations.
2 2
as s 5 ( ~x 2 x¯! /~n 2 1!. 3.5 This guide is intended for those who manage, design, or
i
D 5956
implement sampling and analytical plans for the characteriza- characteristics become less useful in predicting composition or
tion of heterogeneous wastes. properties of individual portions of the population. In this latter
case, when possible, it is advantageous to sample the individual
4. Sampling Difficulties
strata separately, and if an overall average of a population
4.1 There are numerous difficulties that can complicate
characteristic is needed, it can be calculated mathematically
efforts to sample a population. These difficulties can be
using the weighted averages of the sampling stratum means
classified into four general categories:
(7).
4.1.1 Population access problems making it difficult to
5. Stratification
sample all or portions of the population;
4.1.2 Sample collection difficulties due to physical proper-
5.1 Strata can be thought of as different portions of a
ties of the population (for example, unwieldy large items or
population, which may be separated in time or space with each
high viscosity);
portion having internally similar concentrations or properties,
4.1.3 Planning difficulties caused by insufficient knowledge
which are different from adjacent portions of the population
regarding population size, heterogeneity of the contaminant of
(that is, concentrations/properties are correlated with space,
interest, or item size, or a combination thereof; and,
time, component, or source). Fig. 1 is a graphical depiction of
4.1.4 Budget problems that prevent implementation of a
different types of strata.
workable, but too costly, sampling design.
5.1.1 A landfill may display spatially separated strata since
4.2 The difficulties included in the first three categories are
old cells may contain different wastes than new cells (stratifi-
a function of the physical properties of the population being
cation over space);
sampled. The last sampling difficulty category is a function of
5.1.2 A waste pipe may discharge temporally separated
budget restraints that dictate a less-costly sampling approach
strata if night-shift production varies from the day shift
that often results in a reduced number of samples and a reduced
(stratification over time);
certainty in the estimates of population characteristics. Budget
5.1.3 Lead-acid batteries will constitute a strata separate
restraints can make it difficult to balance costs with the levels
from commingled soil if lead is the characteristic of interest
of confidence needed in decision making. These difficulties
(stratification by component); and,
may be resolved by changing the objectives or sampling/
5.1.4 Drums from an inorganic process may constitute a
analytical plans since population attributes or physical proper-
different strata from those co-disposed drums generated by an
ties of the population can seldom be altered. Documents on
organic process (a subtype of stratification by component
DQOs discuss a process for balancing budgets with needed
referred to as stratification by source).
levels of confidence.
5.2 Different strata often are generated by different pro-
4.3 Population access and sample collection difficulties
cesses or a significant variant of the same process. The different
often are obvious, and therefore, more likely either to be
origins of the strata usually result in a different concentration
addressed or the resulting limitations well-documented. A field
distribution and mean c
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