International Module W501 Measurement of Hazardous Substances (including Risk Assessment) Day 2

1. International Module W501 Measurement of Hazardous Substances (including Risk Assessment) Day 2

2. Air Sampling Theory & Practice Confined Spaces Biological Monitoring Sample Analysis

3. Today’s Learning Outcomes • Receive guidance in understanding the reasons for any incorrect answers to the overnight questions from Day 1 • Understand the principles of sampling for airborne contaminants and be able to use those principles to devise a suitable sampling strategy

4. Today’s Learning Outcomes (cont) • Be familiar with the requirements for monitoring in confined spaces and understand some of the issues that need to be considered during this process • Understand the principles of biological monitoring and their appropriate application

5. Today’s Learning Outcomes (cont) • Be familiar with the various methods that are used to analyse the various contaminants found in the workplace • Understand the requirements to ensure the quality of laboratory analysis

6. Topics To Be Discussed • Review of overnight questions • Air sampling theory & practice • Sampling strategies • Survey design • Personal sampling • Area sampling • Surface & other measurements

7. Topics To Be Covered (cont) • Confined spaces • Biological Monitoring • Sample analysis

8. Air Sampling Theory & Practice

9. Air Sampling Theory & Practice • Workplace sampling strategies • Strategies • Surveys • Routine monitoring • Interpretation of result • Basic statistical analysis • Quality assurance

10. Sampling Strategies • Primary Objective: • Provide analytical information about the workplace • Other objectives: • Investigate complaints • Compliance to exposure limits • Evaluate effectiveness of controls

11. Sampling Strategies (cont) • Cannot formulate a sampling strategy until the objectives of the exercise are clear & understood • Need to ask the question: “How will the data generated from this exercise be used?”

12. Sampling Strategies (cont) • BOHS suggests consideration of the following before developing any monitoring programme • Qualitative risk assessment • Measurements other than airborne samples (bulk samples, airflow patterns) • Biological monitoring • Other health hazards • Any environmental or worker characteristics

13. Factors to Consider in a Monitoring Strategy • Type of samples (area v personal) • Location of sampling device (area) • How many samples • Length of sampling interval • What period of the day should monitoring occur so as to be consistent with work patterns

14. Factors to Consider in a Monitoring Strategy (cont) • How should the samples be taken • Contaminants likely to be present • What are the expected concentrations • Potential interferences with sampling or analytical method • Analytical method and possible constraints

15. Surveys • Initial appraisal • Basic survey • Detailed survey • Routine survey

16. Initial Appraisal • Commonly called a “walkthrough survey” • Can provide answers to these questions: • What are the potential exposures • Where & when do they occur • Can exposures be prioritised in terms of risk • Is further evaluation necessary • If so, what is the preferred approach

17. Initial Appraisal (cont) • While the “walkthrough survey “ gives basic information you may still need further information on: • Physical properties of substances • Physical form in the workplace • Potential routes of intake • Any skin effects • Any available exposure limits

18. Basic Survey • Generally required when: • Initial appraisal indicates unacceptable exposures possible • New process being commenced • Substantial changes to a process, operations or control measures • Unusual events (e.g. maintenance) • New exposure limit declared

19. Basic Survey (cont) • Possible objectives: • Confirmation (or otherwise) of possible unacceptable exposures from initial appraisal • Information on engineering or other controls • To establish if a more detailed survey is necessary

20. Basic Survey (cont) • Questions to be addressed before proceeding: • Who should be monitored ? • When should they be monitored ? • Where should the monitoring occur ? • How should the sampling occur ?

21. Basic Survey (cont) • Other factors • Legislative requirements • Accuracy & precision required • Intrinsic safety requirements • Laboratory analysis • Transport of samples • Portability of equipment

22. Detailed Survey • Usually has a clear objective • to obtain reliable measurements, reach conclusions regarding exposure & decide control measures • Results need to be representative of personal exposures & appropriate method used to compare results to exposure standard

23. Detailed Survey (cont) • All aspects of survey need to be reviewed to minimise errors • statistical based monitoring & analysis sometimes used

24. Routine Surveys • Generally involve periodic sampling to meet defined goals, such as: • Checking control measures • Compliance • Corporate requirements • Epidemiological studies

25. Routine Monitoring • Issues that need to be considered: • Frequency • Sampling methodology • Number of samples required • Type of data analysis

26. Frequency of Routine Surveys • No set rules but the following should be considered when making judgments: • How close are exposures to exposure standard • How effective are the controls • What is the process cycle • Seasonal & shift variation • High variability in data

27. Statistical Based Monitoring • Approach developed in 1970’s by NIOSH • Collect a statistical sub-set of worker exposure to represent all persons’ exposure in a Similar Exposure Group (SEG) • Sampling must be random • Number of samples collected determined by required confidence level

28. Process of Statistical Monitoring • Establish similar exposure groups (SEGs) • Develop statistically based sampling schedule • Collect data • Statistically analyse data

29. Process of Statistical Monitoring (cont) • Modify exposure groups (if required) • Final report • Ongoing data collection (maintenance sampling)

30. Establish Similar Exposure Groups • Can be defined : • By process and environmental agent • By process, job and environmental agent • By process, job, task and environmental agent • By process, task and environmental agent • By work teams • By non-repetitive work

31. Establish Similar Exposure Groups • Observational • Simplest form but least accurate • Sampling • Preliminary sampling to establish groups • Combination of observation and sampling • Most accurate approach

32. Interpretation of Results • Compliance analysis • Legislative requirements • Non compliance analysis • Solely end use dependent • Project outcomes drive how the data is evaluated

33. Basic Statistical Analysis • Distribution of data • Basic statistical formulae • Other statistical measures • Log probability plots

34. Normal v Lognormal Distributions Source: AIHA 1998 – reproduced with permission

35. Occupational Hygiene Data • The lognormal distribution generally best fits occupational hygiene data (but not always) • One reason is you cannot have exposures with a concentration less than zero & potentially there is no upper limit to exposure levels

36. Basic Statistical Formulae • Arithmetic mean – AM • Standard deviation – SD or s • Geometric mean – GM • Geometric standard deviation - GSD

37. Basic Statistical Formulae (cont)

38. Basic Statistical Formulae (cont)

39. How GSD Can Be Useful? GSDInference 1.0 No variability. All readings have same value <1.44 Data approximates a normal distribution 1.5-2.0 Very little variability in data 2.0-3.5 Moderate variability in data >3.5 High variability in data

40. Other Statistical Measures • Upper & lower confidence limits • 95th percentile • Minimum Variance Unbiased Estimate (MVUE)

41. Confidence Limits - (Lands) • Provides an estimate of the error of the AM (or MVUE) for a lognormal dataset Sy CL = exp {In (û) + C  n-1} Where Sy = SD of log transformed data C = Land’s C factor n = number of data samples û = exp ( y + ½ Sy2 ) y = mean of the dataset

42. Why is 95% Confidence Generally Used? • Convention • Arbitrary decision - Ronald A Fisher in 1926 • First used in a paper by Fisher describing how to assess whether adding manure to a field would increase crop yields • Not a rigid criterion for “truth”

43. 95th Percentile • Useful when evaluating the health hazards of agents with acute effects • Used by some corporations as a measure of compliance

44. MVUE • Minimum Variance Unbiased Estimate (MVUE) : The estimate of the true mean of a lognormal dataset MVUE =

45. GM v MVUE (AM) Source: AIHA 1998 – Reproduced with permission

46. Log Probability Plots • Gives visual assessment of distribution • Can highlight mixed SEGs • Can obtain other statistical data from graph – eg GM (50%ile) and GSD (84%ile/50%ile) • Need to plot concentration against r/(n+1) where r = rank and n = number of results on log-probability paper (lognormal distribution)

47. Computer Generated Log Probability Plot Source; University of Wollongong

48. Quality Assurance • Confidence in workplace exposure data requires: • An appropriately validated method • Numerous quality assurance schemes throughout the world to check methods & laboratories • Appropriate sampling methodology & practice • No current schemes • Need to self audit

49. Air Sampling Theory & Practice • Survey design • Non sampling approaches • Sampling numbers • Sampling patterns • Sampling to assess acute or chronic effects • Practicalities of sampling programmes

50. Non Sampling Approaches • Control banding • Developed in the late 1980’s by the pharmaceutical industry • Compounds classified into bands by their toxicity • Each band aligned with a control scheme