1、Designation: D 6956 03Standard Guide forDemonstrating and Assessing Whether a ChemicalAnalytical Measurement System Provides Analytical ResultsConsistent with Their Intended Use1This standard is issued under the fixed designation D 6956; the number immediately following the designation indicates the
2、 year 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 guide describes an approach for demonstrating
3、 thequality of analytical chemical measurement results from theapplication of a measurement system (that is, method orsequence of methods) to the analysis of environmental samplesof soil, water, air, or waste. The purpose of such measurementscan include demonstrating compliance with a regulatory lim
4、it,determining whether a site is contaminated above some speci-fied level, or determining treatment process efficacy.1.2 This guide describes a procedure that can be used toassess a measurement system used to generate analyticalresults for a specific purpose. Users and reviewers of theanalytical res
5、ults can determine, with a known level of confi-dence, if they meet the quality requirements and are suitablefor the intended use.1.3 This protocol does not address the general componentsof laboratory quality systems necessary to ensure the overallquality of laboratory operations. For such systems,
6、the user isreferred to International Standards Organization (ISO) Stan-dard 17025 or the National Environmental LaboratoryAccredi-tation Conference (NELAC) laboratory accreditation stan-dards.1.4 This standard does not purport to address all of thesafety concerns, if any, associated with its use. It
7、 is theresponsibility of the user of this standard to establish appro-priate safety and health practices and determine the applica-bility of regulatory requirements prior to use.2. Referenced Documents2.1 ASTM Standards:2D 4687 Guide for General Planning of Waste SamplingD 5283 Practice for Generati
8、on 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 Sampling Strategies for
9、HeterogeneousWastesD 6044 Guide for Representative Sampling for Manage-ment of Waste and Contaminated MediaD 6233 Guide for Data Assessment for EnvironmentalWaste Management ActivitiesD 6250 Practice for Derivation of Decision Point and Con-fidence Limit for Statistical Testing of Mean Concentration
10、in Waste Management DecisionsD 6311 Guide for Generation of Environmental Data Re-lated to Waste Management Activities: Selection andOptimization of Sampling DesignD 6582 Guide for Ranked Set Sampling: Efficient Estima-tion of a Mean Concentration in Environmental SamplingD 6597 Practice for Assessm
11、ent of Attaining Clean UpLevel for Site Closure2.2 Other Documents:Guidelines for Evaluating and Expressing Uncertainty ofNIST Measurement Results, National Institute of StandardTechnology Technical Note 1297, 19943ISO/IEC 17025:1999 General Requirements for the Com-petence of Testing and Calibratio
12、n Laboratories4Quantifying Uncertainty in Analytical Measurement,EURACHEM/ CITAC Guide, second edition, 20003. Terminology3.1 Definitions:3.1.1 action level (AL)the level above or below whichwill lead to the adoption of one of two alternative actions.3.1.2 analytethe constituent to be measured.3.1.3
13、 biasthe difference between the value determinedusing the measurement protocol in question and the true value;operationally the difference between the expected mean of the1This guide is under the jurisdiction of ASTM Committee D34 on WasteManagement and is the direct responsibility of Subcommittee D
14、34.01.01 onPlanning for Sampling.Current edition approved Nov. 18, 2003. Published December 2003.2For referenced ASTM standards, 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 Docum
15、ent Summary page onthe ASTM website.3Available from National Institute of Standards and Technology (NIST), 100Bureau Dr., Stop 3460, Gaithersburg, MD 208993460.4Available from the American National Standards Institute (ANSI), 25 W. 43rdSt., 4th Floor, New York, NY 10036.1Copyright ASTM International
16、, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959, United States.sample test results and an accepted true value. D 57923.1.4 data quality objective (DQO)qualitative and quan-titative statements of the overall level of uncertainty that adecision-maker is willing to accept in resu
17、lts or decisionsderived from environmental measurements, includes uncertain-ties in sampling location, sample handling, and sample analy-sis.3.1.5 laboratory control samplean aliquot of the samplematrix, free from the analytes of interest, spiked with verifiedknown amounts of analytes, or a material
18、 containing knownand verified amounts of analytes.3.1.6 matrix spikean aliquot of the sample spiked withknown levels of the target analytes.3.1.7 measurement quality objectives (MQOs)quantitative statements of the acceptable level of selectivity,sensitivity, bias, and precision for measurements of t
19、he analyteof interest in the matrix of concern.3.1.8 measurement systemall elements of the analyticalprocess including laboratory subsampling, sample preparationand cleanup, and analyte detection and quantitation, includingthe analysts.3.1.9 method of standard additionsthe addition of a seriesof kno
20、wn amounts of the analytes of interest to more than onealiquot of the sample as a means of correcting for interferences.3.1.10 reference material (RM)the generic term referringto a certified material.3.1.11 selectivitythe ability to accurately measure theanalyte in the presence of other sample matri
21、x components oranalytical process contaminants.3.1.12 surrogate a substance with properties that mimicthe performance of the analyte of interest in the measurementsystem, but which is not normally found in the sample ofconcern and is added for quality control purposes.4. Significance and Use4.1 This
22、 guide is intended for use by both generators andusers of analytical results. It is intended to promote consistentdemonstration and documentation of the quality of the mea-surement results and facilitate determination of the validity ofmeasurements for their intended use.4.2 This guide specifies doc
23、umentation that a laboratoryshould supply with the analytical results to establish that theresulting measurements: (1) meet measurement quality require-ments; (2) are suitable for their intended use; and (3) aretechnically defensible.4.3 While the guide describes information that the measure-ment re
24、sults provider needs to give the user/decision maker, inorder for measurement providers to supply data users withappropriate data, information is needed from the data user.Examples of information that the user should provide to thelaboratory, in addition to the analytes of concern (including theform
25、 of the analyte that is to be determined, for example, totallead, dissolved lead, organic lead, inorganic lead), include butare not limited to:4.3.1 Type of material (that is, matrixfresh or salt water,coal fly ash, sandy loam soil, wastewater treatment sludge),4.3.2 Maximum sample holding time,4.3.
26、3 Projected sampling date and delivery date to thelaboratory,4.3.4 Method of chemical preservation (for example, notpreserved, chemical used),4.3.5 Chain-of-custody requirements, if any,4.3.6 Analytical methods that must be used, if any,4.3.7 Measurement quality requirements expressed asDQOs or MQOs
27、 and action limits,4.3.8 Allowable interferences as described in 10.4,4.3.9 Documentation requirement, and4.3.10 Subcontracting restrictions/requirements.4.4 Users/decision makers should consult with the labora-tory about these issues during the analytical design stage. Thiswill allow the design of
28、sample collection process and projectschedule to accommodate the laboratory activities necessary todetermine the desired level of measurement quality. Thenumber of samples, budgets, and schedules should also bediscussed.5. Limitations and Assumptions5.1 This guide deals only with samples from the ti
29、me thelaboratory receives the samples until the time the analyticalresults are provided to the user including necessary documen-tation.5.2 Aspects of environmental measurements that are withinthe control of the laboratory are normally specified by theproject stakeholders in the form of MQOs. MQOs ar
30、e a subsetof the data quality objectives (DQOs). The DQOs describe theoverall measurement quality and tolerable error of the decisionfor the project while the MQOs describe the uncertainty of theanalytical process only. The DQO overall level of uncertaintyincludes uncertainty from both sampling and
31、environmentallaboratory measurement operations. Additional information onthe DQO process and establishing the level of analyticaluncertainty can be found in the references provided in Section2.5.3 This guide applies whether the measurements are per-formed in a fixed location or in the field (on-site
32、).5.4 This guide assumes that the laboratory is operating withall administrative and analytical systems functioning within thequality assurance and quality control protocols and proceduresdescribed in their quality system documents (quality assuranceplan and standard operating procedures).5.5 This g
33、uide does not address multi-laboratory approachesto demonstrating acceptable laboratory performance such ascollaborative testing, inter-laboratory studies, or round-robintypes of studies.6. Outline of Approach6.1 This guide uses the concepts of bias and precision todescribe uncertainty in a measurem
34、ent system. The approachset forth in this guide employs two fundamental properties ofmeasurement systems: bias and precision to determine thequality of the analytical results. The guide singles out selec-tivity, a component of bias, for special emphasis. Sensitivity isalso discussed since, unless a
35、measurement system is sensitiveenough to measure the analytes of interest at the level ofinterest, it is not capable of being used for the purpose at hand.Both areas are frequently highlighted for demonstration inacceptable environmental measurement collection efforts.D69560326.2 This guide provides
36、 examples of approaches that deter-mine bias, precision, selectivity, and sensitivity of a measure-ment system used to analyze a set of samples. It also providesexamples of factors laboratories should consider in designingthe demonstration.6.3 This guide describes, in general terms, the rigor of the
37、demonstration of bias, precision, selectivity, and sensitivitythat should be conducted for a set of samples. It describes theappropriate use of public literature and historical laboratoryperformance information to minimize the need to collectadditional experimental measurements.6.4 When analytical p
38、erformance results are already avail-able on the measurement systems response to the type ofsample to be analyzed (for example, historical results from thelaboratory conducting the demonstration, method developerinformation), such information may be used to determine oneor more of the measurement pr
39、operties (that is, bias, precision,selectivity, sensitivity). Only very limited amounts of newmeasurements would then be necessary to support the conclu-sions drawn from the existing information.6.5 This guide is intended to offer users a technicallydefensible strategy to determine the applicability
40、 of an analyti-cal technique to a set of environmental samples. The complex-ity of the problem, the available resources (trained staff,equipment, and time), and the intended use of the analyticalresults require the application of professional judgment inselecting the best available option to meet th
41、e project-specificneeds. The following sections present the user with a variety ofoptions to determine bias, precision, selectivity, and sensitivity.The discussion of these options does not recommend one overanother. However, there are general principles that can assistthe user in selecting an appro
42、priate option.6.6 The laboratory should select the available option thatwill provide the information needed to determine if themeasurements meet the required level of quality (as defined bythe user/decision maker). The necessary level of quality shouldbe available from the project data quality requi
43、rements, DQOsor MQOs. This guide assumes that the laboratory and usershave sufficient familiarity (or access to qualified individuals)that can balance the trade-offs associated with the MQOs, suchthat rigid standards are not applied but rather the pooled effect(overall analytical uncertainty) of all
44、 items affecting measure-ment usability (bias, precision, selectivity, sensitivity) areconsidered. The following options are ranked from the mostreliable (Option 1) to the least reliable (Option 4) and should beconsidered in light of the overall project goals. This guide doesnot purpose a specific s
45、et of procedural steps because each caseis different and must be addressed by a consensus processinvolving appropriate representatives from the stakeholders.6.6.1 Option 1The most certainty in showing that ameasurement system is free of unacceptable bias is obtainedwhen the measurement system is sho
46、wn to yield the sameresults as another system that employs a fundamentally differ-ent measurement principle. The likelihood is small that twoanalytical techniques will experience the same systematicerrors and will be subject to the same types of chemical andphysical interferences. If two such analyt
47、ical techniques agree,the possibility of unknown systematic errors is substantiallydecreased. Therefore, showing that a different measurementtechnique yields the same results as the subject techniqueserves to validate the ability of the subject system to yield validmeasurements. If the two technique
48、s disagree, there is apossibility of systematic or random error in one or bothtechniques.6.6.2 Option 2The next lower level of certainty is ob-tained by determining the bias, precision, sensitivity, andselectivity of the candidate measurement system using refer-ence materials provided by NIST, or so
49、me other appropriatenational certifying authority (for example, Standards Canada,DIN). Such reference materials would have been confirmed bythe use of multiple methods, each using a different analyticalprinciple. Comparison of the test results from new methodswith published reference values on such materials can be usedto determine measurement system bias. Commercially pro-duced reference materials may also be used, but the true valuesare usually developed using only one (sometimes two) analyti-cal technique(s). The reliable use of reference standards isextremely sensit
