Consensus Standards, Method
Uncertainty and Quality Assurance in
Analytical Chemistry Curricula
Kevin Ashley, Ph.D.
U.S. Department of Health and Human Services
Centers for Disease Control and Prevention
National Institute for Occupational Safety and Health
Cincinnati, Ohio
Disclaimer
Mention of company or product names does not constitute
endorsement by the Centers for Disease Control and
Prevention. The findings and conclusions in this
presentation are those of the speaker and do not
necessarily represent the views of the National Institute for
Occupational Safety and Health.
Introduction

Overview of voluntary consensus standards


QA/QC in analytical laboratory


Need defensible results; verify with QA/QC data
Treatment of analytical method uncertainty


What are they & why are they important?
Vitally important in commercial / gov’t lab
Include ideas in analytical curricula

Give students background in aspects that they’ll
have to address in ‘real world’ lab.
What are voluntary consensus
standards?
Technical documents developed by consensus:
■ Test methods, specifications, guides, practices,
terminology
■ Based on best science for tech transfer:
“Research to Practice”
→ Establish standard of care in field (i.e., analysis)
Voluntary consensus standards in
analytical chemistry
Non-profit, non-governmental organizations
Global forums for developing voluntary consensus
standards (e.g., ASTM International, ISO)
Methods/procedures for sampling, sample
preparation, analysis, estimation of uncertainty,
QA/QC requirements
Importance of Standardization
Conformity in methods for sampling and
analysis
Normalized protocols describing laboratory
quality assurance / quality control
Aim to ensure / maximize data quality,
minimize overall analytical uncertainty
Provide evidence of acceptable performance
Analytical Method Evaluation &
Validation




Sample Generation
 Sampler Capacity
 Dynamic range
 Precision & Bias /
Uncertainty
 Interferences
 Reference materials

Literature Search
Analysis Development
Sampler Development
Method Evaluation
 Analyte Recovery
 Sample Stability
 Limit of Detection

■ Interlaboratory testing
Field Testing
► Standardization
Sampling & Sample Preparation
(workplace air)
Analytical Method Development





Chromatography
Spectroscopy
Electrochemistry
Bioanalytical chemistry
Other exs.
Relative Contributions to Analytical Error
Significant error
Intermediate error
Small error
Sampling
Sample
preparation
Analysis
Overall (expanded) error = ∑ (individual errors)
Quality Assurance/ Quality Control

Quality of Sampling and Analytical Method Results
 Quality of results limited by method, analytical laboratory
and analyst
 Method evaluation helps define method performance
 Analyst and analytical laboratory contribution to quality
measured by:
 Quality Control Program
→ Internal - spiked samples, field blanks, control charts
→ External - participation in proficiency test programs
► Consensus standards describe these elements,
processes & procedures
Ex. of an ASTM International standard
D7035: Standard Test Method for Determination of
Metals and Metalloids in Airborne Particulate Matter
by Inductively Coupled Plasma Atomic Emission
Spectrometry (ICP-AES)
Scope
Referenced Standards
Terminology
Summary of Method
Significance & Use
Apparatus & Materials
Sampling
Sample Preparation
Analysis
Expression of Results
Method Performance
Records
Reporting
Appendices
Annexes
References
Analytical Method Uncertainty
Precision & Bias
ASTM International: ASTM E691 – Standard Practice
for Conducting an Interlaboratory Study to
Determine the Precision of a Test Method
Uncertainty
International Organization for Standardization:
Guide to the Expression of Uncertainty in
Measurement (ISO/GUM)
Analytical Precision
For n analyses, determine μ, s & RSD (CV)
Propagation of random errors:
stot = [∑ si2 ]½ = [s2(weighing) + s2(pipetting) +
s2(dilutions) + s2(analysis) + si’2]½
Then estimate (95%) CL’s
Perform outlier tests (etc.)
→ For estimation of overall method precision, also include
estimate of contribution to error from sampling
Limits of Detection and
Quantitation
95% Confidence
Limits
Response
Calibration
Line
LOD LOQ
Analyte conc.
Analytical Bias

Bi = (μi – Ri) Ri-1




Estimate by comparison of measured results against
reference analytical method
Estimate by analysis of reference materials
Is bias negligible?; ideally <<10% (+ or –)
Is bias correctable or not?


Is cause of systematic error identifiable and, if so,
does corrective action ameliorate the problem
Consider contributions to bias from steps preceding
analysis (e.g., sampling errors, stability & transport)
Uncertainty
“Type A” evaluation: u = s/√n
Applicable when n repeat measurements are possible.
► Exs: Compute std. dev. from repeated absorbance or
temperature measurements
“Type B” evaluation: u = s/√3
Applicable when upper & lower limits are known (or
estimated) but repeat measurements cannot be made.
► Exs: Volumetric glassware tolerances; analytical balance
+/– specs
Uncertainty Budget &
Expanded Uncertainty
Include contributions of all aspects u1, u2, u3, etc.
to measurement uncertainty
Compute combined uncertainty:
Uc = [u12 + u22 + u32 +... + (etc.)]½
Then obtain expanded uncertainty with coverage
factor k:
U = kUc
Comparison of Uncertainty Estimate
to Acceptance Criteria
Uncertainty (%)
35
Accepted
Acceptance
Criterion → 25
Rejected
Inconclusive
95% Confidence Limit
15
5% Confidence Limit
5
A
B
Method
C
Example: Method for Organonitrogen
Pesticides in Air
Carbendazim
Thiobencarb
Propoxur
Diuron
Propham
Methomyl
Oxamyl
Formetanate
Chlorpropham
Captan
Methiocarb
Aldicarb
Carbaryl
Carbofuran
Methomyl
Carbendazim
5% Lower Confidence Limit
95% Upper Confidence Limit
← 25% acceptance criterion
0
10
20
30
40
Uncertainty (Accuracy)
50
Summary

Overview of use of analytical uncertainty, QA/QC &
consensus standards

Criteria for acceptable analytical performance

Myriad applications & requirements in commercial &
government laboratories

Coverage of statistics in analytical chemistry curricula
could be augmented by discussion of these areas
Questions / Comments?
Contact Info:
Dr. Kevin Ashley
U.S. Department of Health and Human Services
Centers for Disease Control and Prevention
National Institute for Occupational Safety and Health
4676 Columbia Parkway, Mail Stop R-7
Cincinnati, Ohio 45226-1998 (USA)
Tel. +1(513)841-4402; e-mail: KAshley@cdc.gov
www.cdc.gov/niosh