1、Designation: D6956 11D6956 17Standard 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 indicat
2、es the 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 () indicates an editorial change since the last revision or reapproval.1. Scope1.1 This guide describes an approach for demonstr
3、ating the quality of analytical chemical measurement results from theapplication of a measurement system (that is, method or sequence of methods) to the analysis of environmental samples of soil,water, air, or waste. The purpose of such measurements can include demonstrating compliance with a regula
4、tory limit, determiningwhether a site is contaminated above some specified level, or determining treatment process efficacy.1.2 This guide describes a procedure that can be used to assess a measurement system used to generate analytical results fora specific purpose. Users and reviewers of the analy
5、tical results can determine, with a known level of confidence, if they meet thequality requirements and are suitable for the intended use.1.3 This protocol does not address the general components of laboratory quality systems necessary to ensure the overall qualityof laboratory operations. For such
6、systems, the user is referred to International Standards Organization (ISO) Standard 17025 orthe National Environmental Laboratory Accreditation Conference (NELAC) laboratory accreditation standards.1.4 The values stated in SI units are to be regarded as standard. No other units of measurement are i
7、ncluded in this standard.1.5 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibilityof the user of this standard to establish appropriate safety safety, health, and healthenvironmental practices and determine theapplicability of
8、 regulatory requirementslimitations prior to use.1.6 This international standard was developed in accordance with internationally recognized principles on standardizationestablished in the Decision on Principles for the Development of International Standards, Guides and Recommendations issuedby the
9、World Trade Organization Technical Barriers to Trade (TBT) Committee.2. Referenced Documents2.1 ASTM Standards:2D4687 Guide for General Planning of Waste SamplingD5283 Practice for Generation of Environmental Data Related to Waste Management Activities: Quality Assurance and QualityControl Planning
10、and ImplementationD5681 Terminology for Waste and Waste ManagementD5792 Practice for Generation of Environmental Data Related to Waste Management Activities: Development of Data QualityObjectivesD5956 Guide for Sampling Strategies for Heterogeneous WastesD6044 Guide for Representative Sampling for M
11、anagement of Waste and Contaminated MediaD6233 Guide for Data Assessment for Environmental Waste Management Activities (Withdrawn 2016)3D6250 Practice for Derivation of Decision Point and Confidence Limit for Statistical Testing of Mean Concentration in WasteManagement Decisions1 This guide is under
12、 the jurisdiction of ASTM Committee D34 on Waste Management and is the direct responsibility of Subcommittee D34.01.01 on Planning forSampling.Current edition approved July 1, 2011Sept. 1, 2017. Published August 2011October 2017. Originally approved in 2003. Last previous edition approved in 2003201
13、1 asD6956 03.D6956 11. DOI: 10.1520/D6956-11.10.1520/D6956-17.2 For referencedASTM standards, visit theASTM website, www.astm.org, or contactASTM Customer Service at serviceastm.org. For Annual Book of ASTM Standardsvolume information, refer to the standards Document Summary page on the ASTM website
14、.3 The last approved version of this historical standard is referenced on www.astm.org.This document is not an ASTM standard and is intended only to provide the user of an ASTM standard an indication of what changes have been made to the previous version. Becauseit may not be technically possible to
15、 adequately depict all changes accurately, ASTM recommends that users consult prior editions as appropriate. In all cases only the current versionof the standard as published by ASTM is to be considered the official document.Copyright ASTM International, 100 Barr Harbor Drive, PO Box C700, West Cons
16、hohocken, PA 19428-2959. United States1D6311 Guide for Generation of Environmental Data Related to Waste Management Activities: Selection and Optimization ofSampling DesignD6582 Guide for Ranked Set Sampling: Efficient Estimation of a Mean Concentration in Environmental Sampling (Withdrawn2012)3D659
17、7 Practice for Assessment of Attaining Clean Up Level for Site Closure (Withdrawn 2016)32.2 Other Documents:Guidelines for Evaluating and Expressing the Uncertainty of NIST Measurement Results, National Institute of StandardTechnology Technical Note 1297, 1994 4ISO/IEC 17025:1999 General Requirement
18、s for the Competence of Testing and Calibration Laboratories5Quantifying Uncertainty in Analytical Measurement, EURACHEM/ CITAC Guide, second edition,Second Edition, 200063. Terminology3.1 For definitions of terms used in this guide, refer to Terminology D5681.3.2 Definitions:3.2.1 action level (AL)
19、the level above or below which will 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 analyte of interest in the matrix of concern.3
20、.2.3 measurement systemall elements of the analytical process including laboratory subsampling, sample preparation andcleanup, and analyte detection and quantitation, including the analysts.3.2.4 method of standard additionsthe addition of a series of known amounts of the analytes of interest to mor
21、e than onealiquot of the sample as a means of correcting for interferences.3.2.5 selectivitythe ability to accurately measure the analyte in the presence of other sample matrix components or analyticalprocess contaminants.3.2.6 surrogatea substance with properties that mimic the performance of the a
22、nalyte of interest in the measurement system,but which is not normally found in the sample of concern and is added for quality control purposes.4. Significance and Use4.1 This guide is intended for use by both generators and users of analytical results. It is intended to promote consistentdemonstrat
23、ion and documentation of the quality of the measurement results and facilitate determination of the validity ofmeasurements for their intended use.4.2 This guide specifies documentation that a laboratory should supply with the analytical results to establish that the resultingmeasurements: (1) meet
24、measurement quality requirements; (2) are suitable for their intended use; and (3) are technicallydefensible.4.3 While the guide describes information that the measurement results provider needs to give the user/decision maker, in orderfor measurement providers to supply data users with appropriate
25、data, information is needed from the data user. Examples ofinformation that the user should provide to the laboratory, in addition to the analytes of concern (including the form of the analytethat is to be determined, for example, total lead, dissolved lead, organic lead, inorganic lead), include bu
26、t are 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 the laboratory,4.3.4 Method of chemical preservation (for example, not pre
27、served, 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 as DQOs or MQOs and action limits,4.3.8 Allowable interferences as described in 10.4,4.3.9 Documentation requirement, and4.3.10 Subco
28、ntracting restrictions/requirements.4.4 Users/decision makers should consult with the laboratory about these issues during the analytical design stage. This willallow the design of sample collection process and project schedule to accommodate the laboratory activities necessary to determinethe desir
29、ed level of measurement quality. The number of samples, budgets, and schedules should also be discussed.4 Available from National Institute of Standards and Technology (NIST), 100 Bureau Dr., Stop 1070, Gaithersburg, MD 20899-1070, http:/www.nist.gov.5 Available from American National Standards Inst
30、itute (ANSI), 25 W. 43rd St., 4th Floor, New York, NY 10036, http:/www.ansi.org.6 Available from http:/www.citac.cc/QUAM20001.pdf.D6956 1725. Limitations and Assumptions5.1 This guide deals only with samples from the time the laboratory receives the samples until the time the analytical resultsare p
31、rovided to the user including necessary documentation.5.2 Aspects of environmental measurements that are within the control of the laboratory are normally specified by the projectstakeholders in the form of MQOs. MQOs are a subset of the data quality objectives (DQOs). The DQOs describe the overallm
32、easurement quality and tolerable error of the decision for the project while the MQOs describe the uncertainty of the analyticalprocess only. The DQO overall level of uncertainty includes uncertainty from both sampling and environmental laboratorymeasurement operations. Additional information on the
33、 DQO process and establishing the level of analytical uncertainty can befound in the references provided in Section 2.5.3 This guide applies whether the measurements are performed in a fixed location or in the field (on-site).5.4 This guide assumes that the laboratory is operating with all administr
34、ative and analytical systems functioning within thequality assurance and quality control protocols and procedures described in their quality system documents (quality assurance planand standard operating procedures).5.5 This guide does not address multi-laboratory approaches to demonstrating accepta
35、ble laboratory performance such ascollaborative testing, inter-laboratory studies, or round-robin types of studies.6. Outline of Approach6.1 This guide uses the concepts of bias and precision to describe uncertainty in a measurement system. The approach set forthin this guide employs two fundamental
36、 properties of measurement systems: bias and precision to determine the quality of theanalytical results. The guide singles out selectivity, a component of bias, for special emphasis. Sensitivity is also discussed since,unless a measurement system is sensitive enough to measure the analytes of inter
37、est at the level of interest, it is not capable of beingused for the purpose at hand. Both areas are frequently highlighted for demonstration in acceptable environmental measurementcollection efforts.6.2 This guide provides examples of approaches that determine bias, precision, selectivity, and sens
38、itivity of a measurementsystem used to analyze a set of samples. It also provides examples of factors laboratories should consider in designing thedemonstration.6.3 This guide describes, in general terms, the rigor of the demonstration of bias, precision, selectivity, and sensitivity thatshould be c
39、onducted for a set of samples. It describes the appropriate use of public literature and historical laboratory performanceinformation to minimize the need to collect additional experimental measurements.6.4 When analytical performance results are already available on the measurement systems response
40、 to the type of sample tobe analyzed (for example, historical results from the laboratory conducting the demonstration, method developer information),such information may be used to determine one or more of the measurement properties (that is, bias, precision, selectivity,sensitivity). Only very lim
41、ited amounts of new measurements would then be necessary to support the conclusions drawn from theexisting information.6.5 This guide is intended to offer users a technically defensible strategy to determine the applicability of an analytical techniqueto a set of environmental samples. The complexit
42、y of the problem, the available resources (trained staff, equipment, and time), andthe intended use of the analytical results require the application of professional judgment in selecting the best available option tomeet the project-specific needs. The following sections present the user with a vari
43、ety of options to determine bias, precision,selectivity, and sensitivity. The discussion of these options does not recommend one over another. However, there are generalprinciples that can assist the user in selecting an appropriate option.6.6 The laboratory should select the available option that w
44、ill provide the information needed to determine if the measurementsmeet the required level of quality (as defined by the user/decision maker). The necessary level of quality should be available fromthe project data quality requirements, DQOs or MQOs. This guide assumes that the laboratory and users
45、have sufficient familiarity(or access to qualified individuals) that can balance the trade-offs associated with the MQOs, such that rigid standards are notapplied but rather the pooled effect (overall analytical uncertainty) of all items affecting measurement usability (bias, precision,selectivity,
46、sensitivity) are considered. The following options are ranked from the most reliable (Option 1) to the least reliable(Option 4) and should be considered in light of the overall project goals. This guide does not purposepropose a specific set ofprocedural steps because each case is different and must
47、 be addressed by a consensus process involving appropriate representativesfrom the stakeholders.6.6.1 Option 1The most certainty in showing that a measurement system is free of unacceptable bias is obtained when themeasurement system is shown to yield the same results as another system that employs
48、a fundamentally different measurementprinciple. The likelihood is small that two analytical techniques will experience the same systematic errors and will be subject tothe same types of chemical and physical interferences. If two such analytical techniques agree, the possibility of unknownsystematic
49、 errors is substantially decreased. Therefore, showing that a different measurement technique yields the same results asD6956 173the subject technique serves to validate the ability of the subject system to yield valid measurements. If the two techniquesdisagree, there is a possibility of systematic or random error in one or both techniques.6.6.2 Option 2The next lower level of certainty is obtained by determining the bias, precision, sensitivity, and selectivity ofthe candidate measurement system using reference materials provided by NIST, or some other appropri
