ASTM D6311-1998(2003) Standard Guide for Generation of Environmental Data Related to Waste Management Activities Selection and Optimization of Sampling Design《与废物管理活动有关的环境数据产生的标准指南.pdf

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1、Designation: D 6311 98 (Reapproved 2003)Standard Guide forGeneration of Environmental Data Related to WasteManagement Activities: Selection and Optimization ofSampling Design1This standard is issued under the fixed designation D 6311; the number immediately following the designation indicates the ye

2、ar oforiginal adoption or, in the case of revision, the year of last revision. A number in parentheses indicates the year of last reapproval. Asuperscript epsilon (e) indicates an editorial change since the last revision or reapproval.1. Scope1.1 This document provides practical guidance on the se-l

3、ection and optimization of sample designs in waste manage-ment sampling activities, within the context of the require-ments established by the data quality objectives or otherplanning process.1.2 This document (1) provides guidance for selection ofsampling designs; (2) outlines techniques to optimiz

4、e candidatedesigns; and (3) describes the variables that need to bebalanced in choosing the final optimized design.1.3 The contents of this guide are arranged by section asfollows:1. Scope2. Referenced Documents3. Terminology4. Significance and Use5. Summary of Guide6. Factors Affecting Sampling Des

5、ign Selection6.1 Sampling Design Performance Characteristics6.2 Regulatory Considerations6.3 Project Objectives6.4 Knowledge of the Site6.5 Physical Sample Issues6.6 Communication with the Laboratory6.7 Analytical Turn Around Time6.8 Analytical Method Constraints6.9 Health and Safety6.10 Budget/Cost

6、 Considerations6.11 Representativeness7. Initial Design Selection8. Optimization Criteria9. Optimization Process9.2 Practical Evaluation of Design Alternatives9.3 Statistical and Cost Evaluation10. Final SelectionAnnex A1. Types of Sampling DesignsA1.1 Commonly Used Sampling DesignsA1.2 Sampling Des

7、ign ToolsA1.3 Combination Sample DesignsAppendix X1. Additional ReferencesAppendix X2. Choosing Analytical Method Based on Variance and CostAppendix X3. Calculating the Number of Samples: A Statistical Treatment1.4 This standard does not purport to address all of thesafety concerns, if any, associat

8、ed with its use. It is theresponsibility of the user of this standard to establish appro-priate safety and health practices and determine the applica-bility of regulatory limitations prior to use.2. Referenced Documents2.1 ASTM Standards:2D 4687 Guide for General Planning of Waste SamplingD 5283 Pra

9、ctice for Generation of Environmental DataRelated to Waste Management Activities: Quality Assur-ance and Quality Control Planning and ImplementationD 5792 Practice for Generation of Environmental DataRelated to Waste Management Activities: Development ofData Quality ObjectivesD 5956 Guide for Sampli

10、ng Strategies for HeterogeneousWastesD 6044 Guide for Representative Sampling for Manage-ment of Waste and Contaminated MediaD 6051 Guide for Composite Sampling and Field Subsam-pling for Environmental Waste Management ActivitiesD 6232 Guide for Selection of Sampling Equipment forWaste and Contamina

11、ted Media Data Collection ActivitiesD 6233 Guide for Data Assessment for EnvironmentalWaste Management ActivitiesD 6250 Practice for Derivation of Decision Point and Con-difence Limit for Statistical Testing of Mean Concentra-tion in Waste Management DecisionsD 6323 Guide for Laboratory Subsampling

12、of Media Re-lated to Waste Management Activities1This guide is under the jurisdiction of ASTM Committee D34 on WasteManagement and is the direct responsibility of Subcommittee D34.01.01 onPlanning for Sampling.Current edition approved Sept. 10, 1998. Published November 1998.2For referenced ASTM stan

13、dards, visit the ASTM website, www.astm.org, orcontact ASTM Customer Service at serviceastm.org. For Annual Book of ASTMStandards volume information, refer to the standards Document Summary page onthe ASTM website.1Copyright ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken,

14、PA 19428-2959, United States.E 135 Terminology Relating to Analytical Chemistry forMetals, Ores and Related MaterialsE 943 Terminology Relating to Biological Effects and En-vironmental Fate2.2 USEPA Documents:USEPA, Guidance for the Data Quality Objectives Process,EPA QA/G-4, Quality Assurance Manag

15、ement Staff,Washington, DC, March 19953USEPA, Data Quality Objectives Process for Superfund -Workbook, EPA 540/R-93/078 (OSWER 9355.9-01A),Office of Emergency and Remedial Response, Washing-ton, D.C., September, 19933USEPA, Environmental Investigations Branch StandardOperating Procedures and Quality

16、 Assurance Manual(EISOPQAM), Region 4 - Science and Ecosystem Sup-port Division, Athens, GA, May 199632.3 There are numerous useful references available fromASTM, USEPA, and private sector publishers. Appendix X1contains a list, which is by no means comprehensive, ofadditional commonly used referenc

17、es.3. Terminology3.1 accuracy, ncloseness of a measured value to the trueor an accepted reference or standard value. (E 135)3.2 attribute, na quality of samples or a population.(D 5956)3.3 characteristic, na property of items in a sample orpopulation that can be measured, counted, or otherwise ob-se

18、rved. (D 5956)3.3.1 DiscussionA characteristic of interest may be thecadmium concentration or ignitability of a population.3.4 composite sample, na combination of two or moresamples.3.5 confidence interval, na numerical range used to boundthe value of a population parameter with a specified degree o

19、fconfidence (that the interval would include the true parametervalue).3.5.1 DiscussionWhen providing a confidence interval,the number of observations on which the interval is basedshould be identified.3.6 confidence level, nthe probability, usually expressedas a percent, that a confidence interval w

20、ill contain theparameter of interest.3.7 data quality objectives (DQO), nqualitative and quan-titative statements derived from the DQO process describingthe decision rules and the uncertainties of the decision(s)within the context of the problem(s). (D 5956)3.8 data quality objective process, na qua

21、lity manage-ment tool based on the scientific method and developed by theU.S. Environmental Protection Agency to facilitate the plan-ning of environmental data collection activities. (D 5956)3.8.1 DiscussionThe DQO process enables planners tofocus their planning efforts by specifying the use of the

22、data(the decision), the decision criteria (action level) and thedecision makers acceptable decision error rates. The productsof the DQO Process are the DQOs.3.9 decision rule, na set of directions in the form ofconditional statements that specifies: (1) how the sample datawill be compared to the dec

23、ision point or action level, (2)which decision will be made as a result of that comparison, and(3) what subsequent action will be taken based on the deci-sions.3.10 false negative error, nan error which occurs when(environmental) data misleads the decision maker(s) into nottaking action when action

24、should be taken.3.11 false positive error, nan error which occurs whenenvironmental data misleads the decision maker(s) into takingaction when action should not be taken.3.12 heterogeneity, nthe condition of the population un-der which items of the population are not identical with respectto the cha

25、racteristic of interest. (D 5956)3.13 homogeneity, nthe condition of the population underwhich all items of the population are identical with respect tothe characteristic of interest. (D 5956)3.14 representative sample, na sample collected such thatit reflects one or more characteristics of interest

26、 (as defined bythe project objectives) of a population from which it wascollected. (D 5956)3.15 risk, nthe probability or likelihood that an adverseeffect will occur. (E 943)3.16 sample, na portion of material which is collected fortesting or for record purposes. (D 5956)3.16.1 DiscussionSample is a

27、 term with numerous mean-ings. The project team member collecting physical samples(for example, from a landfill, drum or waste pipe) or analyzingsamples considers a sample to be that unit of the populationcollected and placed in a container. In statistics, a sample isconsidered to be a subset of the

28、 population and this subset mayconsist of one or more physical samples. To minimize confu-sion, the term “physical sample” is a reference to the sampleheld in a sample container or that portion of the populationwhich is subjected to measurement.3.17 sampling design, n(1) the sampling schemes speci-f

29、ying the point(s) for sample collection; (2) the samplingschemes and associated components for implementation of asampling event.3.17.1 DiscussionBoth of the above definitions are com-monly used within the environmental community. Therefore,both are used within this document.4. Significance and Use4

30、.1 The intended use of this guide is to provide practicalassistance in the development of an optimized samplingdesign. This standard describes or discusses:4.1.1 Sampling design selection criteria,4.1.2 Factors impacting the choice of a sampling design,4.1.3 Selection of a sampling design,4.1.4 Tech

31、niques for optimizing candidate designs, and4.1.5 The criteria for evaluating an optimized samplingdesign.3Available from the Superintendent of Documents, U.S. Government PrintingOffice, Washington, DC 20402.D 6311 98 (2003)24.2 Within a formal USEPA data generation activity, theplanning process or

32、Data Quality Objectives (DQO) develop-ment is the first step. The second and third are the implemen-tation of the sampling and analysis design and the data qualityassessment. Within the DQO planning process, the selectionand optimization of the sampling design is the last step, andtherefore, the cul

33、mination of the DQO process. The precedingsteps in the DQO planning process address:4.2.1 The problem that needs to be addressed,4.2.2 The possible decisions,4.2.3 The data input and associated activities,4.2.4 The boundaries of the study,4.2.5 The development of decision rules, and4.2.6 The specifi

34、ed the limits on decision error.4.3 This guide is not intended to address the aspects of theplanning process for development of the project objectives.However, the project objectives must be outlined and commu-nicated to the design team, prior to the selection and optimi-zation of the sample design.

35、4.4 This guide references statistical aspects of the planningand implementation process and includes an appendix for thestatistical calculation of the optimum number of samples for agiven sampling design.4.5 This guide is intended for those who are responsible formaking decisions about environmental

36、 waste managementactivities.5. Summary of Guide5.1 The selection and optimization process is an iterativeprocess of selecting and then evaluating the selected designalternatives and determining the most resource-effective designwhich satisfies the project objectives or DQOs. Fig. 1 illus-trates this

37、 approach.5.2 An appropriate sampling design may be implementedwithout a formal optimization, however, the following stepsare recommended. Each evaluation step typically results infewer design alternatives.5.2.1 Evaluation of the designs against the projects practi-cal considerations (for example, t

38、ime, personnel, and materialresources),5.2.2 Calculation of the design cost and statistical uncer-tainty, and5.2.3 Choice of the sample design decision by the decisionmakers.5.3 The process steps for the evaluation can be followed inany order. And for a small project, the entire selection andoptimiz

39、ation process may be conducted at the same time. Ifultimately, a design meeting the project constraints, for ex-ample, schedule and budget, cannot be identified among thecandidate sampling designs, it may be necessary to modify theclosest candidate design or reevaluate and revise the projectobjectiv

40、es.6. Factors Affecting Sampling Design Selection6.1 Sampling Design Performance Characteristics:6.1.1 The sampling design provides the structure and detailfor the sampling activity and should be chosen in light of theproject objectives. Prior to this point, the planning processshould have addressed

41、 and defined the project needs for each ofthe sampling design characteristics, including the characteris-tics of interest, population boundaries, decision rule, accept-able decision errors and budgets. In considering all aspects ofthe project, the selected design should accommodate the spatialand te

42、mporal distribution of contaminants at the site, bepractical, cost effective and generate data that allow the projectobjectives to be met.6.1.2 Whenever possible, technical guidelines for measure-ment of the sources of variability and levels of uncertaintyshould be established prior to developing sa

43、mpling designalternatives, to ensure that it is possible to establish that theprogram objectives are met.6.1.3 Annex A1 presents an overview of some of the morecommonly used sampling designs and design tools and sum-marizes their advantages and disadvantages. Because numer-ous sampling strategies ex

44、ist, this is limited to the morecommon. If the more common sampling strategies are notcost-effective or applicable to the population of interest, astatistician should be consulted to identify other strategieswhich may be more appropriate.6.2 Regulatory ConsiderationsThe selection of samplingdesign,

45、the sampling techniques and analytical methods may bedictated by current regulation, permits or consent agreements,applicable to the site. These should be reviewed to determinetheir impact on the selection process.6.3 Project ObjectivesProject objectives are usually de-termined by the decision maker

46、s (for example, regulatory body,consent agreement group, company management) during theinitial investigation and planning or DQO process. The deci-sion makers should have identified the population boundaries,characteristics of interest, acceptability of an average analyticalvalue, the need to locate

47、 areas of contamination or “hot spots,”the statistical needs (for example, acceptable decision errors,levels of uncertainty), and the quality control acceptancecriteria, as well as any other pertinent information.6.4 Knowledge of the SiteThe site knowledge (for ex-ample, geography/topography, utilit

48、ies, past site use) used todetermine project objectives, will also provide for a moreresource efficient sampling design, for example, divide a siteinto separate design areas for sampling or exclude an area fromsampling.6.5 Physical Sample IssuesThe physical material to besampled and its location on

49、or within the site will usuallyimpact the sampling design and limit the choices of equipmentand methods.6.5.1 Number of Samples:6.5.1.1 The project objectives should specify the confidencelevels for decision making. Using this level of decision error,the proximity to a threshold or action limit and the anticipatedpopulation variance, the number of samples can be calculated.The statistical parameter of interest, for example, mean or 95percentile, and type of frequency of distribution, for example,normal or log normal, will determine which equation is used toc