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DESIGN AND DELIVERY OF SAMPLING PROGRAMMES

DESIGN AND DELIVERY OF SAMPLING PROGRAMMES. Meteau 2008 Lisbon Malcolm Morgan Drinking Water Inspectorate. Key Issues.

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DESIGN AND DELIVERY OF SAMPLING PROGRAMMES

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  1. DESIGN AND DELIVERY OF SAMPLING PROGRAMMES Meteau 2008 Lisbon Malcolm Morgan Drinking Water Inspectorate

  2. Key Issues • The success of any survey, monitoring programme or investigation involving sampling and analysis is totally dependent on the quality of design and delivery of the sampling programme • What samples to take • When to take them • How to take them • Who will take them • How to measure success of delivery

  3. Overall Design • Where and when should samples be taken • Points in system • Geographical and temporal distribution • Number of samples • Programme period

  4. Factors Affecting Overall Design • Accessibility of sampling points • Sampling methodology • Who will take the samples • Sample transport logistics • Sample preservation and storage • Analytical capability • Laboratory constraints • Uncertainty of analysis • Uncertainty of sampling • QA/QC for sampling

  5. Sampling points • Plumbing metals do not only arise from plumbing • Source water • Distribution • (Contamination during sampling and storage) • (Contamination during analysis) • Factors affecting metals pick up from plumbing • Water quality • Type of plumbing • Contact time (stagnation time)

  6. Sampling points • At the tap • Normal drinking water tap • Stagnation sample • How long? • Flushed sample • Metals from other sources

  7. Typical metal uptake profile

  8. How to Sample • Fixed stagnation time • 30 minutes • 4 hours • 8 hours • 12 hours • 16 hours • Short stagnation • Exact time critical • Must use trained samplers • High precision needed at low concentrations • Relatively high distortion from sampling errors • Long stagnation • Exact time less critical • Disruption for householder • Possible to use householder to sample

  9. How to sample • Randomstagnationtime • Easy to programme • Minimum disruption for householder • Can use trained samplers • Good for checking compliance with a standard • Difficult to assess changes in uptake due to treatment changes etc

  10. When to Sample • Time of year • Seasonal variations • Time of day • Diurnal variations • Practical considerations

  11. Who Takes the Sample • Dedicated sampler • Trained • Experienced • Reliable • Work easily audited • Occasional sampler • Not main job, may not give high priority • May be trained • May not be experienced • May not be reliable • Work less easily audited

  12. Who Takes the Sample • Ad hoc sampler (eg householder) • Poorly trained • May not be reliable • Will not be experienced • Not easily audited • Extra H & S implications • Could influence choice of sampling points

  13. How do we measure success? • What is success • Why measure success • What to measure • How do we measure • Qualitative • Quantitiative • What do we do with the results

  14. What is success • All samples: • Taken from the right place • At the right time • In the right way • Delivered to the laboratory • On time • In perfect condition

  15. Or more realistically • Pre-defined percentage of samples • Taken according to schedule • By appropriately trained samplers • Acceptably small deviation from procedure • Delivered safely to laboratory • Quality control programme • Delivered in full • Satisfactory results

  16. Qualitative measures • Internal Audit: • Sampling procedures • Sampler training • Sampling practice • Sample preservation, handling and transport • Exception reports • actions

  17. Quantitative measures • Quality control samples • Trip blanks • Spiked samples/standards • Duplicate samples • Reagent blanks/Bottle blanks/Procedural blanks • Control charts • Statistical control • Action records

  18. What do we do with the results • Qualitative • Review to learn lessons for future work • Calculate confidence in quality of sampling • X% of sampling events subject to error • Can sub-divide into types of error

  19. What do we do with the results? • Quantitative • Estimate of uncertainty of sampling • Identify unsuspected sources of error • Training issues • Process issues • Contamination/deterioration • Initiate immediate corrective action

  20. Standards for sampling • ISO 5667 Series: • Design • Procedures for taking different types of sample • Sample preservation • QA & QC for sampling

  21. BS8550 A new draft Standard for auditing water sampling • Concentrates on qualitative aspects • Should have wider applicability • Wide consultation on initial draft • Regulators • Accrediting body • Sampling organisations • Road tested

  22. BS 8550 Next Steps • Public consultation • Includes workshop in March 2009 • Revision and publication • Bring to ISO for consideration as basis of an International Standard

  23. Summary • The design and size of a sampling programme determines what use can be made of the data generated • The quality of delivery of the sampling programme is critical to the quality of the data generated

  24. Final thoughts • The uncertainty of analysis is typically up to 20% • In a well controlled sampling programme the uncertainty of sampling is typically 20-50% • Can be several hundred percent in some programmes • All bets are off if sampling quality is not controlled

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