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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.
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.
Note 1—A complete table of contents of this practice is given in Appendix X1.
2. Referenced Documents (purchase separately) The documents listed below are referenced within the subject standard but are not provided as part of the standard.
D1129 Terminology Relating to Water
E1187 Terminology Relating to Conformity Assessment
U.S. Environmental Protection Agency DocumentsQAMS 004/80 (NTIS No. PB83219667/LL), Guidelines and Specifications for Preparing Quality Assurance Program Plans, Office of Monitoring Systems and Quality Assurance, September 20, 1980
ICS Number Code 03.120.10 (Quality management and quality assurance); 13.030.01 (Wastes in general)
UNSPSC Code 81141500(Quality control); 77101505(Environmental monitoring)
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ASTM D5283-92(2009), Standard Practice for Generation of Environmental Data Related to Waste Management Activities: Quality Assurance and Quality Control Planning and Implementation, ASTM International, West Conshohocken, PA, 2009, www.astm.orgBack to Top