ASTM D5283-92(2009)
(Practice)Standard Practice for Generation of Environmental Data Related to Waste Management Activities: Quality Assurance and Quality Control Planning and Implementation
Standard Practice for Generation of Environmental Data Related to Waste Management Activities: Quality Assurance and Quality Control Planning and Implementation
SIGNIFICANCE AND USE
Environmental data are often required for making regulatory and programmatic decisions. These data must be of known quality commensurate with their intended use.
Data generation efforts involve the following: establishment of the DQOs; design of the project plan to meet the DQOs; implementation of the project plan; and assessment of the data to determine whether the DQOs have been met.
Certain minimal criteria must be met by the field and laboratory organizations generating environmental data. Additional activities may be required based on the DQOs of the data collection effort.
This practice defines the criteria for field and laboratory organizations generating environmental data and identifies some other activities that may be required based on the DQOs.
This practice emphasizes the importance of communication among those involved in establishing DQOs, planning and implementing the sampling and analysis aspects of environmental data generation activities, and assessing data quality.
Environmental field operations are discussed in Section 7, and environmental laboratory operations are discussed in Section 8.
SCOPE
1.1 Environmental data generation efforts are composed of four parts: (1) establishment of data quality objectives (DQOs); (2) design of field measurement and sampling strategies and specification of laboratory analyses and data acceptance criteria; (3) implementation of sampling and analysis strategies; and (4) data quality assessment. This practice addresses the planning and implementation of the sampling and analysis aspects of environmental data generation activities (Parts (1) and (2) above).
1.2 This practice defines the criteria that must be considered to assure the quality of the field and analytical aspects of environmental data generation activities. Environmental data include, but are not limited to, the results from analyses of samples of air, soil, water, biota, waste, or any combinations thereof.
1.3 DQOs should be adopted prior to application of this practice. Data generated in accordance with this practice are subject to a final assessment to determine whether the DQOs were met. For example, many screening activities do not require all of the mandatory quality assurance (QA) and quality control (QC) steps found in this practice to generate data adequate to meet the project DQOs. The extent to which all of the requirements must be met remains a matter of technical judgement as it relates to the established DQOs.
1.4 This practice presents extensive management requirements designed to ensure high-quality environmental data. The words “must,”“ shall,” “may,” and “should” have been selected carefully to reflect the importance placed on many of the statements made in this practice.
1.5 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.
Note 1—A complete table of contents of this practice is given in Appendix X1.
General Information
Relations
Standards Content (Sample)
NOTICE: This standard has either been superseded and replaced by a new version or withdrawn.
Contact ASTM International (www.astm.org) for the latest information
Designation: D5283 − 92 (Reapproved 2009)
Standard Practice for
Generation of Environmental Data Related to Waste
Management Activities: Quality Assurance and Quality
Control Planning and Implementation
This standard is issued under the fixed designation D5283; 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 priate safety and health practices and determine the applica-
bility of regulatory limitations prior to use.
1.1 Environmental data generation efforts are composed of
fourparts:(1)establishmentofdataqualityobjectives(DQOs);
NOTE 1—A complete table of contents of this practice is given in
Appendix X1.
(2) design of field measurement and sampling strategies and
specification of laboratory analyses and data acceptance crite-
2. Referenced Documents
ria;(3)implementationofsamplingandanalysisstrategies;and
2.1 ASTM Standards:
(4) data quality assessment. This practice addresses the plan-
D1129 Terminology Relating to Water
ning and implementation of the sampling and analysis aspects
E1187 Terminology Relating to Conformity Assessment
of environmental data generation activities (Parts (1) and (2)
(Withdrawn 2006)
above).
2.2 U.S. Environmental Protection Agency Documents:
1.2 This practice defines the criteria that must be considered
SW-846, Test Methods for Evaluating Solid Waste, Vol 1,
to assure the quality of the field and analytical aspects of
Third Edition (NTIS No. PB88239223/LL), November
environmental data generation activities. Environmental data
include, but are not limited to, the results from analyses of
QAMS-005/80 (NTIS No. PB83170514/LL), Interim
samples of air, soil, water, biota, waste, or any combinations
Guidelines and Specifications for Preparing Quality As-
thereof.
surance Project Plans, Office of Monitoring Systems and
1.3 DQOs should be adopted prior to application of this
Quality Assurance, December 29, 1980
practice. Data generated in accordance with this practice are
EPA/QAMS, Development of Data Quality Objectives, De-
subject to a final assessment to determine whether the DQOs
scription of Stages I and II, July 16, 1986
were met. For example, many screening activities do not
QAMS004/80 (NTISNo.PB83219667/LL), Guidelines and
requireallofthemandatoryqualityassurance(QA)andquality
Specifications for Preparing Quality Assurance Program
control (QC) steps found in this practice to generate data
Plans, Office of Monitoring Systems and Quality
adequate to meet the project DQOs. The extent to which all of
Assurance, September 20, 1980
the requirements must be met remains a matter of technical
2.3 Other documents related to the subject matter of this
judgement as it relates to the established DQOs.
practicearecitedinAppendixX2.Thislistisnotintendedtobe
comprehensive.
1.4 This practice presents extensive management require-
ments designed to ensure high-quality environmental data.The
words“must,”“shall,”“may,”and“should”havebeenselected
3. Terminology
carefully to reflect the importance placed on many of the
3.1 Definitions—The terms most applicable to this practice
statements made in this practice.
have been defined in Terminologies D1129 and E1187.
1.5 This standard does not purport to address all of the
safety concerns, if any, associated with its use. It is the 3.2 Definitions of Terms Specific to This Standard:
responsibility of the user of this standard to establish appro-
For referenced ASTM standards, visit the ASTM website, www.astm.org, or
contact ASTM Customer Service at service@astm.org. For Annual Book of ASTM
This practice is under the jurisdiction of ASTM Committee D34 on Waste Standards volume information, refer to the standard’s Document Summary page on
Management and is the direct responsibility of Subcommittee D34.01.01 on the ASTM website.
Planning for Sampling. The last approved version of this historical standard is referenced on
Current edition approved Feb. 1, 2009. Published March 2009. Originally www.astm.org.
approved in 1992. Last previous edition approved in 2003 as D5286 – 92 (2003). Available from Superintendent of Documents, Government Printing Office,
DOI: 10.1520/D5283-92R09. Washington, DC 20402.
Copyright © ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959. United States
D5283 − 92 (2009)
3.2.1 background sample—a sample taken from a location 3.2.14 project—single or multiple data collection activities
on or proximate to the site of interest and used to document that are related through the same planning sequence.
baseline or historical information.
3.2.15 project planning documents—all documents related
3.2.2 collocatedsamples—independentsamplescollectedas to the definition of the environmental data collection activities
close as possible to the same point in space and time and associated with a project.
intended to be identical.
3.2.16 quality assurance program plan (QAPP)—an orderly
3.2.3 data quality objectives (DQOs)—statements on the assemblageofmanagementpolicies,objectives,principles,and
general procedures by which an organization involved in
level of uncertainty that a decision maker is willing to accept
in the results derived from environmental data (see EPA/ environmentaldatagenerationactivitiesoutlineshowitintends
to produce data of known quality.
QAMS, July 16, 1986).
3.2.17 quality assurance project plan (QAPjP)—an orderly
3.2.4 environmental data generation activity— tasks asso-
assemblage of detailed procedures designed to produce data of
ciated with the production of environmental data, including
sufficient quality to meet the DQOs for a specific data
planning, sampling, and analysis.
collection activity.
3.2.5 equipment rinsate (equipment blank)—a sample of
3.2.18 reference material—a material containing known
analyte-free media that has been used to rinse the sampling
quantities of target analytes in either solution or a homoge-
equipment. This blank is collected after the completion of
neous matrix and used to document the bias of the analytical
decontamination and prior to sampling and is useful for
process.
documenting the adequate decontamination of sampling equip-
ment.
3.2.19 split samples—aliquots of sample taken from the
same container and analyzed independently. These are usually
3.2.6 field blank—a sample of analyte-free media similar to
taken after mixing or compositing and are used to document
the sample matrix that is transferred from one vessel to another
intra- or interlaboratory precision.
or exposed to the sampling environment at the sampling site.
This blank is preserved and processed in the same manner as
3.2.20 standard addition—the practice of adding a known
the associated samples and is used to document contamination
amountofananalytetoasampleimmediatelypriortoanalysis,
in the sampling and analysis process.
typically used to evaluate matrix effects.
3.2.7 field duplicates—collocated samples that are analyzed
3.2.21 standard operating procedures (SOPs)—the estab-
independently and are useful in documenting the precision of
lished written procedures of a given organization. Special
the sampling and analytical process.
project plans may require procedures different from the estab-
lished SOPs.
3.2.8 laboratory control sample—a known matrix spiked
with compound(s) representative of the target analytes and
3.2.22 surrogate—an organic compound that is similar to
used to document laboratory performance.
the target analyte(s) in chemical composition and behavior in
the analytical process, but is not normally found in environ-
3.2.9 material blank—a sample composed of construction
mental samples.
materials such as those used in well installation, well
development, pump and flow testing, and slurry wall construc-
3.2.23 trip blank—a sample of analyte-free media taken
tion. Examples of these materials are bentonite, sand, drilling from the laboratory (or appropriate point of origin) to the
fluids, and source and purge water. This blank documents the
sampling site and returned to the laboratory unopened. A trip
contamination resulting from use of the construction materials. blank is used to document the contamination attributable to
shipping and field handling procedures and is also useful in
3.2.10 matrix duplicate—an intralaboratory split sample
documenting the contamination of volatile organics samples.
used to document the precision of a procedure in a given
sample matrix.
4. Summary of Practice
3.2.11 matrix spike—an aliquot of sample spiked with a
4.1 Thispracticedescribesthecriteriaandactivitiesforfield
known concentration of target analyte(s) and used to document
and laboratory organizations involved in generating environ-
the bias of an analytical process in a given sample matrix. The
mental data in terms of human and physical resources, QAand
spiking occurs prior to sample preparation and analysis.
QCprocedures,anddocumentationrequirementsdependingon
3.2.12 matrix spike duplicates—intralaboratory split
the DQOs.
samples spiked with identical concentrations of target ana-
lyte(s) and used to document the precision and bias of a
5. Significance and Use
procedureinagivensamplematrix.Thespikingoccurspriorto
sample preparation and analysis. 5.1 Environmental data are often required for making regu-
latory and programmatic decisions. These data must be of
3.2.13 method blank—an analyte-free media, to which all
known quality commensurate with their intended use.
reagents are added in the same volumes or proportions used in
sample processing. The method blank must be carried through 5.2 Data generation efforts involve the following: establish-
the complete sample preparation and analytical procedure and ment of the DQOs; design of the project plan to meet the
is used to document contamination resulting from the analyti- DQOs; implementation of the project plan; and assessment of
cal process. the data to determine whether the DQOs have been met.
D5283 − 92 (2009)
5.3 Certain minimal criteria must be met by the field and blanks, equipment rinsates, field duplicates, background
laboratory organizations generating environmental data. Addi- samples, reference materials, material blanks, and split
tionalactivitiesmayberequiredbasedontheDQOsofthedata samples, shall be specified. Control parameters for field activi-
collection effort. ties shall also be described (see 7.6.4).
6.3.5.2 Laboratory Quality Control—The types and fre-
5.4 This practice defines the criteria for field and laboratory
quency of use of laboratory QC samples, such as laboratory
organizations generating environmental data and identifies
control samples, laboratory blanks, matrix spikes, matrix
some other activities that may be required based on the DQOs.
duplicates, and matrix spike duplicates, shall be specified.Any
5.5 This practice emphasizes the importance of communi-
specific performance criteria shall be specified. Data validation
cation among those involved in establishing DQOs, planning
criteria shall be defined.
and implementing the sampling and analysis aspects of envi-
6.4 Project Documentation—All documents required for
ronmentaldatagenerationactivities,andassessingdataquality.
planning, implementing, and evaluating the data collection
5.6 Environmental field operations are discussed in Section
effort shall be specified. These may include, although not
7, and environmental laboratory operations are discussed in
limited to, a statement of work, technical and cost proposals,
Section 8.
work plan, sampling and analysis plan, quality assurance
project plan (QAPjP), health and safety plan, community
6. Project Specification
relations plan, documents required by regulatory agencies,
requirements for raw field and analytical records, technical
6.1 Project activities should be defined prior to the start of
reports assessing the environmental data, and records retention
any field or laboratory activities. At a minimum, project
policy. Planning documents shall specify the required level of
specifications should address the following topics:
document control and identify the personnel having access.
6.2 Data Quality Objectives—DQOs for the data generation
Document formats that may be required to ensure that all data
activity should be defined prior to the initiation of field and
needs are satisfied shall be specified. In addition, a project
laboratory work. It is desirable that the field and laboratory
schedule that identifies critical milestones and completion
organizations be aware of the DQOs so that the personnel
dates should be available.
conducting the work are able to make informed decisions
during the course of the project.
7. Standard Practices for Environmental Field
6.3 Project Plan— The project should be designed to meet Operations
the DQOs, and the project plan should define the following:
7.1 Purpose—The field organization must conduct its op-
6.3.1 Project Objectives—Project objectives provide back-
erations in such a manner as to provide reliable information
ground information, state reasons for the data collection effort,
that meets the DQOs. To achieve this goal, certain minimum
identify any regulatory programs governing data collection,
policies and procedures must be implemented in order to meet
define specific objectives for each sampling location, and
the DQOs.
describe the intended uses for the data.
7.2 Organization—Thefieldorganizationshallbestructured
6.3.2 Project Management—Aperson(s) shall be designated
such that each member of the organization has a clear under-
as having responsibility and authority for the following: (1)
standing of his or her duties and responsibilities and the
developing project documents that implement the DQOs; (2)
relationship of those responsibilities to the total effort. The
selecting field and laboratory organizations to conduct the
organizational structure, functional responsibilities, levels of
work; (3) coordinating communication among the field and
authority, job descriptions, and lines of communication for
laboratoryorganizationsandgovernmentagencies,asrequired;
activities shall be established and documented. One person
and (4) reviewing and assessing the final data.
may cover more than one organizational function.
6.3.3 Sampling Requirements—Sampling locations,
7.2.1 Management—The management of the field organiza-
equipment, and procedures and sample preservation and han-
tion is responsible for establishing organizational, operational,
dling requirements shall be specified.
health and safety, and QA policies. Management shall ensure
6.3.4 Analytical Requiremen
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