ASTM D6311-98(2003)

NOTICE: This standard has either been superseded and replaced by a new version or withdrawn.
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Designation:D6311–98 (Reapproved 2003)
Standard Guide for
Generation of Environmental Data Related to Waste
Management Activities: Selection and Optimization of
Sampling Design
This standard is issued under the fixed designation D6311; 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 (´) indicates an editorial change since the last revision or reapproval.
1. Scope
Annex A1. Types of Sampling Designs
1.1 This document provides practical guidance on the se-
A1.1 Commonly Used Sampling Designs
lection and optimization of sample designs in waste manage-
A1.2 Sampling Design Tools
A1.3 Combination Sample Designs
ment sampling activities, within the context of the require-
ments established by the data quality objectives or other
Appendix X1. Additional References
planning process.
Appendix X2. Choosing Analytical Method Based on Variance and Cost
1.2 This document (1) provides guidance for selection of
samplingdesigns;(2)outlinestechniquestooptimizecandidate
Appendix X3. Calculating the Number of Samples: A Statistical Treatment
designs; and (3) describes the variables that need to be
1.4 This standard does not purport to address all of the
balanced in choosing the final optimized design.
safety concerns, if any, associated with its use. It is the
1.3 The contents of this guide are arranged by section as
responsibility of the user of this standard to establish appro-
follows:
priate safety and health practices and determine the applica-
1. Scope
bility of regulatory limitations prior to use.
2. Referenced Documents
2. Referenced Documents
3. Terminology
2.1 ASTM Standards:
4. Significance and Use
D4687 Guide for General Planning of Waste Sampling
D5283 Practice for Generation of Environmental Data Re-
5. Summary of Guide
lated to Waste Management Activities: Quality Assurance
6. Factors Affecting Sampling Design Selection
and Quality Control Planning and Implementation
6.1 Sampling Design Performance Characteristics
D5792 Practice for Generation of Environmental Data Re-
6.2 Regulatory Considerations
lated to Waste Management Activities: Development of
6.3 Project Objectives
6.4 Knowledge of the Site
Data Quality Objectives
6.5 Physical Sample Issues
D5956 Guide for Sampling Strategies for Heterogeneous
6.6 Communication with the Laboratory
Wastes
6.7 Analytical Turn Around Time
6.8 Analytical Method Constraints
D6044 GuideforRepresentativeSamplingforManagement
6.9 Health and Safety
of Waste and Contaminated Media
6.10 Budget/Cost Considerations
D6051 Guide for Composite Sampling and Field Subsam-
6.11 Representativeness
pling for Environmental Waste Management Activities
7. Initial Design Selection
D6232 Guide for Selection of Sampling Equipment for
8. Optimization Criteria
Waste and Contaminated Media Data CollectionActivities
9. Optimization Process
9.2 Practical Evaluation of Design Alternatives
D6233 Guide for Data Assessment for Environmental
9.3 Statistical and Cost Evaluation
Waste Management Activities
D6250 Practice for Derivation of Decision Point and Con-
10. Final Selection
fidenceLimitforStatisticalTestingofMeanConcentration
This guide is under the jurisdiction of ASTM Committee D34 on Waste
Management and is the direct responsibility of Subcommittee D34.01.01 on For referenced ASTM standards, visit the ASTM website, www.astm.org, or
Planning for Sampling. contact ASTM Customer Service at service@astm.org. For Annual Book of ASTM
Current edition approved Sept. 10, 1998. Published November 1998. DOI: Standards volume information, refer to the standard’s Document Summary page on
10.1520/D6311-98R03. the ASTM website.
Copyright © ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959, United States.
D6311–98 (2003)
in Waste Management Decisions 3.8.1 Discussion—The DQO process enables planners to
D6323 Guide for Laboratory Subsampling of Media Re- focus their planning efforts by specifying the use of the data
lated to Waste Management Activities (the decision), the decision criteria (action level) and the
E135 Terminology Relating to Analytical Chemistry for decision maker’s acceptable decision error rates. The products
Metals, Ores, and Related Materials of the DQO Process are the DQOs.
E943 Terminology Relating to Biological Effects and Envi- 3.9 decision rule, n—a set of directions in the form of
ronmental Fate conditional statements that specifies: (1) how the sample data
2.2 USEPA Documents: will be compared to the decision point or action level, (2)
USEPA, Guidance for the Data Quality Objectives Process, whichdecisionwillbemadeasaresultofthatcomparison,and
EPA QA/G-4, Quality Assurance Management Staff, (3) what subsequent action will be taken based on the deci-
Washington, DC, March 1995 sions.
USEPA, Data Quality Objectives Process for Superfund - 3.10 false negative error, n—an error which occurs when
Workbook, EPA 540/R-93/078 (OSWER 9355.9-01A), (environmental) data misleads the decision maker(s) into not
Office of Emergency and Remedial Response, Washing- taking action when action should be taken.
ton, D.C., September, 1993 3.11 false positive error, n—an error which occurs when
USEPA, Environmental Investigations Branch Standard environmental data misleads the decision maker(s) into taking
Operating Procedures and Quality Assurance Manual action when action should not be taken.
(EISOPQAM), Region 4 - Science and Ecosystem Sup- 3.12 heterogeneity, n—the condition of the population un-
port Division, Athens, GA, May 1996 derwhichitemsofthepopulationarenotidenticalwithrespect
2.3 There are numerous useful references available from to the characteristic of interest. (D5956)
ASTM, USEPA, and private sector publishers. Appendix X1 3.13 homogeneity, n—the condition of the population under
contains a list, which is by no means comprehensive, of which all items of the population are identical with respect to
additional commonly used references. the characteristic of interest. (D5956)
3.14 representative sample, n—a sample collected such that
it reflects one or more characteristics of interest (as defined by
3. Terminology
the project objectives) of a population from which it was
collected. (D5956)
3.1 accuracy, n—closeness of a measured value to the true
3.15 risk, n—the probability or likelihood that an adverse
or an accepted reference or standard value. (E135)
effect will occur. (E943)
3.2 attribute, n—a quality of samples or a population.
3.16 sample, n—a portion of material which is collected for
(D5956)
testing or for record purposes. (D5956)
3.3 characteristic, n—a property of items in a sample or
3.16.1 Discussion—Sample is a term with numerous mean-
population that can be measured, counted, or otherwise ob-
ings. The project team member collecting physical samples
served. (D5956)
(for example, from a landfill, drum or waste pipe) or analyzing
3.3.1 Discussion—A characteristic of interest may be the
samples considers a sample to be that unit of the population
cadmium concentration or ignitability of a population.
collected and placed in a container. In statistics, a sample is
3.4 composite sample, n—a combination of two or more
considered to be a subset of the population and this subset may
samples.
consist of one or more physical samples. To minimize confu-
3.5 confidenceinterval,n—anumericalrangeusedtobound
sion, the term “physical sample” is a reference to the sample
the value of a population parameter with a specified degree of
held in a sample container or that portion of the population
confidence (that the interval would include the true parameter
which is subjected to measurement.
value).
3.17 sampling design, n—(1) the sampling schemes speci-
3.5.1 Discussion—When providing a confidence interval,
fying the point(s) for sample collection; (2) the sampling
the number of observations on which the interval is based
schemes and associated components for implementation of a
should be identified.
sampling event.
3.6 confidence level, n—the probability, usually expressed
3.17.1 Discussion—Both of the above definitions are com-
as a percent, that a confidence interval will contain the
monly used within the environmental community. Therefore,
parameter of interest.
both are used within this document.
3.7 data quality objectives (DQO), n—qualitativeandquan-
titative statements derived from the DQO process describing
4. Significance and Use
the decision rules and the uncertainties of the decision(s)
4.1 The intended use of this guide is to provide practical
within the context of the problem(s). (D5956)
assistance in the development of an optimized sampling
3.8 data quality objective process, n—a quality manage-
design. This standard describes or discusses:
ment tool based on the scientific method and developed by the
4.1.1 Sampling design selection criteria,
U.S. Environmental Protection Agency to facilitate the plan-
4.1.2 Factors impacting the choice of a sampling design,
ning of environmental data collection activities. (D5956)
4.1.3 Selection of a sampling design,
4.1.4 Techniques for optimizing candidate designs, and
4.1.5 The criteria for evaluating an optimized sampling
Available from the Superintendent of Documents, U.S. Government Printing
Office, Washington, DC 20402. design.
D6311–98 (2003)
4.2 Within a formal USEPA data generation activity, the the sampling design characteristics, including the characteris-
planning process or Data Quality Objectives (DQO) develop- tics of interest, population boundaries, decision rule, accept-
ment is the first step. The second and third are the implemen- able decision errors and budgets. In considering all aspects of
tation of the sampling and analysis design and the data quality theproject,theselecteddesignshouldaccommodatethespatial
assessment. Within the DQO planning process, the selection and temporal distribution of contaminants at the site, be
and optimization of the sampling design is the last step, and practical, cost effective and generate data that allow the project
therefore, the culmination of the DQO process. The preceding objectives to be met.
steps in the DQO planning process address:
6.1.2 Whenever possible, technical guidelines for measure-
4.2.1 The problem that needs to be addressed,
ment of the sources of variability and levels of uncertainty
4.2.2 The possible decisions,
should be established prior to developing sampling design
4.2.3 The data input and associated activities,
alternatives, to ensure that it is possible to establish that the
4.2.4 The boundaries of the study,
program objectives are met.
4.2.5 The development of decision rules, and
6.1.3 Annex A1 presents an overview of some of the more
4.2.6 The specified the limits on decision error.
commonly used sampling designs and design tools and sum-
4.3 This guide is not intended to address the aspects of the
marizes their advantages and disadvantages. Because numer-
planning process for development of the project objectives.
ous sampling strategies exist, this is limited to the more
However, the project objectives must be outlined and commu-
common. If the more common sampling strategies are not
nicated to the design team, prior to the selection and optimi-
cost-effective or applicable to the population of interest, a
zation of the sample design.
statistician should be consulted to identify other strategies
4.4 This guide references statistical aspects of the planning
which may be more appropriate.
and implementation process and includes an appendix for the
6.2 Regulatory Considerations—The selection of sampling
statistical calculation of the optimum number of samples for a
design,thesamplingtechniquesandanalyticalmethodsmaybe
given sampling design.
dictated by current regulation, permits or consent agreements,
4.5 This guide is intended for those who are responsible for
applicable to the site. These should be reviewed to determine
making decisions about environmental waste management
their impact on the selection process.
activities.
6.3 Project Objectives—Project objectives are usually de-
terminedbythedecisionmakers(forexample,regulatorybody,
5. Summary of Guide
consent agreement group, company management) during the
5.1 The selection and optimization process is an iterative
initial investigation and planning or DQO process. The deci-
process of selecting and then evaluating the selected design
sion makers should have identified the population boundaries,
alternativesanddeterminingthemostresource-effectivedesign
characteristicsofinterest,acceptabilityofanaverageanalytical
which satisfies the project objectives or DQOs. Fig. 1 illus-
value, the need to locate areas of contamination or “hot spots,”
trates this approach.
the statistical needs (for example, acceptable decision errors,
5.2 An appropriate sampling design may be implemented
levels of uncertainty), and the quality control acceptance
without a formal optimization, however, the following steps
criteria, as well as any other pertinent information.
are recommended. Each evaluation step typically results in
6.4 Knowledge of the Site—The site knowledge (for ex-
fewer design alternatives.
ample, geography/topography, utilities, past site use) used to
5.2.1 Evaluation of the designs against the project’s practi-
determine project objectives, will also provide for a more
cal considerations (for example, time, personnel, and material
resource efficient sampling design, for example, divide a site
resources),
intoseparatedesignareasforsamplingorexcludeanareafrom
5.2.2 Calculation of the design cost and statistical uncer-
sampling.
tainty, and
6.5 Physical Sample Issues—The physical material to be
5.2.3 Choice of the sample design decision by the decision
sampled and its location on or within the site will usually
makers.
impact the sampling design and limit the choices of equipment
5.3 The process steps for the evaluation can be followed in
and methods.
any order. And for a small project, the entire selection and
6.5.1 Number of Samples:
optimization process may be conducted at the same time. If
6.5.1.1 The project objectives should specify the confidence
ultimately, a design meeting the project constraints, for ex-
levels for decision making. Using this level of decision error,
ample, schedule and budget, cannot be identified among the
the proximity to a threshold or action limit and the anticipated
candidate sampling designs, it may be necessary to modify the
population variance, the number of samples can be calculated.
closest candidate design or reevaluate and revise the project
The statistical parameter of interest, for example, mean or
...