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 problems, 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.