1、Designation: D6956 11Standard Guide forDemonstrating and Assessing Whether a ChemicalAnalytical Measurement System Provides Analytical ResultsConsistent with Their Intended Use1This standard is issued under the fixed designation D6956; the number immediately following the designation indicates the y
2、ear 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 () indicates an editorial change since the last revision or reapproval.1. Scope1.1 This guide describes an approach for demonstrating th
3、equality 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 limit,
4、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 result
5、s 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, the
6、 user isreferred to International Standards Organization (ISO) Stan-dard 17025 or the National Environmental LaboratoryAccredi-tation Conference (NELAC) laboratory accreditation stan-dards.1.4 The values stated in SI units are to be regarded asstandard. No other units of measurement are included in
7、thisstandard.1.5 This standard does not purport to address all of thesafety concerns, if any, associated 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 requirements prior to use.2
8、. Referenced Documents2.1 ASTM Standards:2D4687 Guide for General Planning of Waste SamplingD5283 Practice for Generation of Environmental Data Re-lated to Waste Management Activities: Quality Assuranceand Quality Control Planning and ImplementationD5681 Terminology for Waste and Waste ManagementD57
9、92 Practice for Generation of Environmental Data Re-lated to Waste Management Activities: Development ofData Quality ObjectivesD5956 Guide for Sampling Strategies for HeterogeneousWastesD6044 Guide for Representative Sampling for Managementof Waste and Contaminated MediaD6233 Guide for Data Assessme
10、nt for EnvironmentalWaste Management ActivitiesD6250 Practice for Derivation of Decision Point and Con-fidence Limit for Statistical Testing of Mean Concentrationin Waste Management DecisionsD6311 Guide for Generation of Environmental Data Re-lated to Waste Management Activities: Selection andOptimi
11、zation of Sampling DesignD6582 Guide for Ranked Set Sampling: Efficient Estima-tion of a Mean Concentration in Environmental SamplingD6597 Practice forAssessment ofAttaining Clean Up Levelfor Site Closure2.2 Other Documents:Guidelines for Evaluating and Expressing the Uncertainty ofNIST Measurement
12、Results, National Institute of StandardTechnology Technical Note 1297, 199431This 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 July 1, 2011. Published August 2011.
13、Originallyapproved in 2003. Last previous edition approved in 2003 as D6956 03. DOI:10.1520/D6956-11.2For 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 D
14、ocument Summary page onthe ASTM website.3Available from National Institute of Standards and Technology (NIST), 100Bureau Dr., Stop 1070, Gaithersburg, MD 20899-1070, http:/www.nist.gov.1Copyright ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959, United States.
15、ISO/IEC 17025:1999 General Requirements for the Com-petence of Testing and Calibration Laboratories4Quantifying Uncertainty in Analytical Measurement,EURACHEM/ CITAC Guide, second edition, 200053. Terminology3.1 For definitions of terms used in this guide, refer toTerminology D5681.3.2 Definitions:3
16、.2.1 action level (AL)the level above or below whichwill lead to the adoption of one of two alternative actions.3.2.2 measurement quality objectives (MQOs)quantitative statements of the acceptable level of selectivity,sensitivity, bias, and precision for measurements of the analyteof interest in the
17、 matrix of concern.3.2.3 measurement systemall elements of the analyticalprocess including laboratory subsampling, sample preparationand cleanup, and analyte detection and quantitation, includingthe analysts.3.2.4 method of standard additionsthe addition of a seriesof known amounts of the analytes o
18、f interest to more than onealiquot of the sample as a means of correcting for interferences.3.2.5 selectivitythe ability to accurately measure the ana-lyte in the presence of other sample matrix components oranalytical process contaminants.3.2.6 surrogate a substance with properties that mimicthe pe
19、rformance 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 guide is intended for use by both generators andusers of analytical results. It is intended to promote cons
20、istentdemonstration 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 documentation that a laboratoryshould supply with the analytical results to establish that theresulting measure
21、ments: (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 results provider needs to give the user/decision maker, inorder for measurement providers to supply data users
22、 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 of the analyte that is to be determined, for example, totallead, dissolved lead, organic lead, inorganic le
23、ad), 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,4.3.3 Projected sampling date and delivery date to thelaboratory,4.3.4 Method of chemical preservation (for exam
24、ple, 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 and action limits,4.3.8 Allowable interferences as described in 10.4,4.3.9 Documentation requirement, and4.
25、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 sample collection process and projectschedule to accommodate the laboratory activities necessary todetermine
26、 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 time thelaboratory receives the samples until the time the analyticalresults are provided to the user includin
27、g 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 are a subsetof the data quality objectives (DQOs). The DQOs describe theoverall measurement quality and tolera
28、ble 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 environmentallaboratory measurement operations. Additional information onthe DQO process and establishing th
29、e 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).5.4 This guide assumes that the laboratory is operating withall administrative and analytical systems func
30、tioning within thequality assurance and quality control protocols and proceduresdescribed in their quality system documents (quality assuranceplan and standard operating procedures).5.5 This guide does not address multi-laboratory approachesto demonstrating acceptable laboratory performance such asc
31、ollaborative 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 measurement system. The approachset forth in this guide employs two fundamental properties ofmeasurement systems: bi
32、as 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 measurement system is sensitiveenough to measure the analytes of interest at the level ofinterest, it is not
33、 capable of being used for the purpose at hand.Both areas are frequently highlighted for demonstration inacceptable environmental measurement collection efforts.4Available from American National Standards Institute (ANSI), 25 W. 43rd St.,4th Floor, New York, NY 10036, http:/www.ansi.org.5Available f
34、rom http:/www.citac.cc/QUAM20001.pdf.D6956 1126.2 This guide provides 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 demon
35、stration.6.3 This guide describes, in general terms, the rigor of thedemonstration 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
36、 to collectadditional experimental measurements.6.4 When analytical performance 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
37、information may be used to determine oneor more of the measurement properties (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
38、users a technicallydefensible strategy to determine the applicability 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 p
39、rofessional judgment inselecting the best available option to meet the 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
40、 are general principles that can assistthe user in selecting an appropriate 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 le
41、vel of quality shouldbe available from the project data quality requirements, 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 applie
42、d but rather the pooled effect(overall analytical uncertainty) of all 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
43、of the overall project goals. This guide doesnot purpose a specific set 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 fr
44、ee of unacceptable bias is obtainedwhen the measurement system is shown 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
45、 same types of chemical andphysical interferences. If two such analytical 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 o
46、f the subject system to yield validmeasurements. If the two techniques 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
47、measurement system using refer-ence materials provided by NIST, or some 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
48、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
49、use of reference standards isextremely sensitive to the degree that the reference materialshave the same matrix/analyte physical properties and chemistryas the project samples. If the match of the properties betweenthe project samples and the reference materials is poor, thestudy results can be misleading.6.6.3 Option 3The lack of availability of more than oneanalytical method (no alternative technology or resources) orof appropriate reference materials will prevent use of thetechniques mentioned above. When this is the case, the use ofmatrix spikes and surrogates bec
