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The Bottom Line on the ICR Microbial Data

The Bottom Line on the ICR Microbial Data. Jeffrey S. Rosen and Brian Ellis TPMC. Objective of this Presentation. Summarize the microbial data collected during the Information Collection Rule Discuss the limitations of the microbial data Present limited results based on ICR data

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The Bottom Line on the ICR Microbial Data

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  1. The Bottom Line on the ICR Microbial Data Jeffrey S. Rosen and Brian Ellis TPMC

  2. Objective of this Presentation • Summarize the microbial data collected during the Information Collection Rule • Discuss the limitations of the microbial data • Present limited results based on ICR data • Review conclusions • Discuss where we go from here

  3. Acknowledgement • The information presented here is the product of numerous Organizations and People • Difficult to list them all here • The ICR Technical Working Group • EPA, AWWA, Large Drinking Water Utilities • Many consultants, academicians, vendors

  4. Background • Data collected from June 1997 - December 1998 • 229 Utilities, 350 drinking water plants • 5838 Sampling events reported for plant influent samples. • Samples for Giardia, Cryptosporidium, Total Coliforms, Fecal Coliform, E. coli and Viruses • 6.9% detects for Total Cryptosporidium • 18.9% detects for Total Giardia

  5. Limitations • Low recovery rates with High variability for Giardia and Cryptosporidium • Potential for high false positive results • Highly variable volumes analyzed • Reporting of results in (oo)cysts per 100 L results in large multipliers Count per 100 Liters = (oo)cysts counted * 100 volumes analyzed Volume analyzed ranged from 20 mLs - 769 liters average ~ 10 Liters, median 3 liters

  6. Multiplication Factor Facts for Crypto • Factor ranged from .13 to 5000 • 86 records over 100 oocysts/100liters • Multiplication factor ranges from 4.9 to 769 • 43 of these 86 records are based on 1 oocyst counted • 15 of these 86 records are based on 2 counts • Highest concentration (2000 oocysts/100 liters) based on 6 counts, 300 mLs analyzed, factor =333.3 • Second Highest concentration (1923 oocysts/100liters based on 5 counts, 260 mLs analyzed, factor=384.6

  7. Recovery Rates

  8. Results - Overall

  9. Results By Surface Water Category

  10. RL (n= 3468, nonzero n=140) FS + RL (n= 5680, nonzer o n=377) FS (n= 2112, nonzero n=237) 1 0 0 9 0 t n e c 8 0 r e P 7 0 e RL (n=215, nonzero n=66) FS + RL (n= 346, nonzero n=150) FS (n=131, nonzero n=84) v i t a 6 0 l u m RL (n=215, nonzero n=112) 5 0 u C FS + RL (n= 346, nonzero n=225) 4 0 FS (n=131, nonzero n=113) 3 0 0 1 0 0 2 0 0 3 0 0 4 0 0 5 0 0 RL (n= 3468, nonzero n=378) FS + RL (n= 5680, nonzero n=1056) FS (n= 2112, nonzero n=678) Distributional Summaries Individual Measurements Count per 100 Liters Count per 100 Liters Cryptosporidium Giardia Count per 100 Liters Count per 100 Liters Plant Means

  11. Temporal Internal StructuresGiardia

  12. Temporal Internal StructuresCryptosporidium

  13. Temporal Distributions Coliforms

  14. Multiple Detects Could be an artifact of different detection rates.

  15. E. Coli Appears to be an Indicator of Pathogen Risk • The ICR and Supplemental Survey suggest that based on a 12 month maximum Running Annual Average: • an average concentration of 5 to 10 E. coli per 100 mL is indicative of a lake or reservoir vulnerable to high levels of Cryptosporidium, • an average concentration of 50 E. coli per 100 mL is indicative of a flowing stream vulnerable to high levels of Cryptosporidium. E. coli Microbial Index Approach for Screening Source Waters for Susceptibility to High Levels of Cryptosporidium Misty L. Pope, Brian Ellis, Jeffrey S. Rosen, Jessica Pulz, Kevin Connell, and Mark LeChevallier

  16. Valid Conclusions from ICR data • More Pathogens in Flowing Streams than in Lakes and Reservoirs • Recovery rates for Cryptosporidium and Giardia are low on average and highly variable • Modeling efforts have probably correctly classified central tendencies but failed at defining the upper and lower tails of the distribution

  17. Uncertain Conclusions from the Data • Low occurrence of Giardia and Cryptosporidium in source waters • National distribution of Giardia and Cryptosporidium • Extremely high occurrences in both lakes and reservoirs and flowing streams. • ICR sampling period is representative of most time intervals. • Difference % detection between Giardia and Cryptosporidium • No understanding of viability and infectivity

  18. Users Beware • The pathogens data are still not finalized • There are multiple data bases • Final Auxiliary 1(version 5) is not the best data set • Best data set for protozoa data is DS6 available from EPA (Mike Messner, 202-260-8107, messner.michael@epa.gov)

  19. The Bottom Line • ICR confirmed our uncertainties about Pathogens occurrence, distribution and sampling • Pathogens do occur in levels of concern but we do not know where and when • In order to understand the occurrence and distribution of pathogens, more sampling is needed • Longer time period, • more frequent sampling • better methods.

  20. For an update of the presentation • Download from www.drinkingh2o.com • Give me a business card and I will e-mail it to you Thank you for your attention!!

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