ASTM D6311-98

NOTICE: This standard has either been superceded and replaced by a new version or discontinued.
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Designation: D 6311 – 98
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 D 6311; 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
A1.3 Combination Sample Designs
1.1 This document provides practical guidance on the se-
Appendix X1. Additional References
lection and optimization of sample designs in waste manage-
Appendix X2. Choosing Analytical Method Based on Variance and Cost
ment sampling activities, within the context of the require-
ments established by the data quality objectives or other
Appendix X3. Calculating the Number of Samples: A Statistical Treatment
planning process.
1.4 This standard does not purport to address all of the
1.2 This document (1) provides guidance for selection of
safety concerns, if any, associated with its use. It is the
sampling designs; (2) outlines techniques to optimize candidate
responsibility of the user of this standard to establish appro-
designs; and (3) describes the variables that need to be
priate safety and health practices and determine the applica-
balanced in choosing the final optimized design.
bility of regulatory limitations prior to use.
1.3 The contents of this guide are arranged by section as
follows:
2. Referenced Documents
1. Scope
2.1 ASTM Standards:
2. Referenced Documents
D 4687 Guide for General Planning of Waste Sampling
D 5283 Practice for Generation of Environmental Data
3. Terminology
Related to Waste Management Activities: Quality Assur-
4. Significance and Use ance and Quality Control Planning and Implementation
D 5792 Practice for Generation of Environmental Data
5. Summary of Guide
Related to Waste Management Activities: Development of
6. Factors Affecting Sampling Design Selection
Data Quality Objectives
6.1 Sampling Design Performance Characteristics
D 5956 Guide for Sampling Strategies for Heterogeneous
6.2 Regulatory Considerations
Wastes
6.3 Project Objectives
6.4 Knowledge of the Site
D 6044 Guide for Representative Sampling for Manage-
6.5 Physical Sample Issues 2
ment of Waste and Contaminated Media
6.6 Communication with the Laboratory
D 6051 Guide for Composite Sampling and Field Subsam-
6.7 Analytical Turn Around Time
6.8 Analytical Method Constraints
pling for Environmental Waste Management Activities
6.9 Health and Safety
D 6232 Guide for Selection of Sampling Equipment for
6.10 Budget/Cost Considerations
Waste and Contaminated Media Data Collection Activi-
6.11 Representativeness
ties
7. Initial Design Selection
D 6233 Guide for Data Assessment for Environmental
8. Optimization Criteria
Waste Management Activities
9. Optimization Process
9.2 Practical Evaluation of Design Alternatives
D 6250 Practice for Derivation of Decision Point and Con-
9.3 Statistical and Cost Evaluation
difence Limit for Statistical Testing of Mean Concentra-
tion in Waste Management Decisions
10. Final Selection
D 6323 Guide for Laboratory Subsampling of Media Re-
Annex A1. Types of Sampling Designs
lated to Waste Management Activities
A1.1 Commonly Used Sampling Designs
E 135 Terminology Relating to Analytical Chemistry for
A1.2 Sampling Design Tools
Metals, Ores and Related Materials
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. Annual Book of ASTM Standards, Vol 11.04.
Current edition approved Sept. 10, 1998. Published November 1998. Annual Book of ASTM Standards, Vol 03.05.
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 6311
E 943 Terminology Relating to Biological Effects and En- 3.9 decision rule, n—a set of directions in the form of
vironmental 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, which decision will be made as a result of that comparison, 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 der which items of the population are not identical with respect
2.3 There are numerous useful references available from to the characteristic of interest. (D 5956)
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. (D 5956)
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
3.1 accuracy, n—closeness of a measured value to the true
collected. (D 5956)
or an accepted reference or standard value. (E 135)
3.15 risk, n—the probability or likelihood that an adverse
3.2 attribute, n—a quality of samples or a population.
effect will occur. (E 943)
(D 5956)
3.16 sample, n—a portion of material which is collected for
3.3 characteristic, n—a property of items in a sample or
testing or for record purposes. (D 5956)
population that can be measured, counted, or otherwise ob-
3.16.1 Discussion—Sample is a term with numerous mean-
served. (D 5956)
ings. The project team member collecting physical samples
3.3.1 Discussion—A characteristic of interest may be the
(for example, from a landfill, drum or waste pipe) or analyzing
cadmium concentration or ignitability of a population.
samples considers a sample to be that unit of the population
3.4 composite sample, n—a combination of two or more
collected and placed in a container. In statistics, a sample is
samples.
considered to be a subset of the population and this subset may
3.5 confidence interval, n—a numerical range used to bound
consist of one or more physical samples. To minimize confu-
the value of a population parameter with a specified degree of
sion, the term “physical sample” is a reference to the sample
confidence (that the interval would include the true parameter
held in a sample container or that portion of the population
value).
which is subjected to measurement.
3.5.1 Discussion—When providing a confidence interval,
3.17 sampling design, n—(1) the sampling schemes speci-
the number of observations on which the interval is based
fying the point(s) for sample collection; (2) the sampling
should be identified.
schemes and associated components for implementation of a
3.6 confidence level, n—the probability, usually expressed
sampling event.
as a percent, that a confidence interval will contain the
3.17.1 Discussion—Both of the above definitions are com-
parameter of interest.
monly used within the environmental community. Therefore,
3.7 data quality objectives (DQO), n—qualitative and quan-
both are used within this document.
titative statements derived from the DQO process describing
4. Significance and Use
the decision rules and the uncertainties of the decision(s)
within the context of the problem(s). (D 5956)
4.1 The intended use of this guide is to provide practical
3.8 data quality objective process, n—a quality manage- assistance in the development of an optimized sampling
ment tool based on the scientific method and developed by the
design. This standard describes or discusses:
U.S. Environmental Protection Agency to facilitate the plan- 4.1.1 Sampling design selection criteria,
ning of environmental data collection activities. (D 5956)
4.1.2 Factors impacting the choice of a sampling design,
3.8.1 Discussion—The DQO process enables planners to 4.1.3 Selection of a sampling design,
focus their planning efforts by specifying the use of the data 4.1.4 Techniques for optimizing candidate designs, and
(the decision), the decision criteria (action level) and the 4.1.5 The criteria for evaluating an optimized sampling
decision maker’s acceptable decision error rates. The products design.
of the DQO Process are the DQOs. 4.2 Within a formal USEPA data generation activity, the
planning process or Data Quality Objectives (DQO) develop-
ment is the first step. The second and third are the implemen-
Annual Book of ASTM Standards, Vol 11.05.
5 tation of the sampling and analysis design and the data quality
Available from the Superintendent of Documents, U.S. Government Printing
Office, Washington, DC 20402. assessment. Within the DQO planning process, the selection
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 6311
and optimization of the sampling design is the last step, and statistical calculation of the optimum number of samples for a
therefore, the culmination of the DQO process. The preceding given sampling design.
steps in the DQO planning process address: 4.5 This guide is intended for those who are responsible for
4.2.1 The problem that needs to be addressed, making decisions about environmental waste management
4.2.2 The possible decisions, activities.
4.2.3 The data input and associated activities,
5. Summary of Guide
4.2.4 The boundaries of the study,
4.2.5 The development of decision rules, and 5.1 The selection and optimization process is an iterative
4.2.6 The specified the limits on decision error. process of selecting and then evaluating the selected design
4.3 This guide is not intended to address the aspects of the alternatives and determining the most resource-effective design
planning process for development of the project objectives. which satisfies the project objectives or DQOs. Fig. 1 illus-
However, the project objectives must be outlined and commu- trates this approach.
nicated to the design team, prior to the selection and optimi- 5.2 An appropriate sampling design may be implemented
zation of the sample design. without a formal optimization, however, the following steps
4.4 This guide references statistical aspects of the planning are recommended. Each evaluation step typically results in
and implementation process and includes an appendix for the fewer design alternatives.
FIG. 1 Implement Sampling Design
NOTICE: This standard has either been superceded and replaced by a new version or discontinued.
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D 6311
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), into separate design areas for sampling or exclude an area from
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 95
objectives.
percentile, and type of frequency of distribution, for example,
normal or log normal, will determine which equation is used to
6. Factors Affecting Sampling Design Selection
calculate the appropriate number of samples. Equation X3.5
6.1 Sampling Design Performance Characteristics:
from Appendix X3, can be used to calculate the number of
6.1.1 The sampling design provides the structure and detail
samples when the objective is to measure the mean for a
for the sampling activity and should be chosen in light of the
population that has a normal distribution for the characteristic
project objectives. Prior to this point, the planning process
of interest.
should have addressed and defined the project needs for each of
6.5.1.2 Appendix X3 contains statistical approaches to cal-
the sampling design characteristics, including the characteris-
culating the number of samples needed for estimating the mean
tics of interest, population boundaries, decision rule, accept-
concentration, for simple random, statistical random, multi-
able decision errors and budgets. In considering all aspects of
stage sampling and search sampling (where the objective is to
the project, the selected design should accommodate the spatial
detect hot spots).
and temporal distribution of contaminants at the site, be
6.5.2 Sample Mass or Volume:
practical, cost effective and generate data that allow the project
6.5.2.1 The sample mass or volume is determined by the
objectives to be met.
size of the items that constitute the population, the heteroge-
6.1.2 Whenever p
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