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Optimizing Plant Operations by Using Particle Counters to Detect Cryptosporidium-sized Particles

1^st Tarrik Quneibi¹, 2^nd Rebecca Lahr²

¹Civil and Environmental Engineering, University of Michigan ²Ann Arbor Drinking Water Treatment Plant

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Introduction

The addition of particle counters after filtration in the treatment train at the Ann Arbor Drinking Water Treatment Plant was to determine how the use of particle count data could be implemented into plant optimization and maintenance while assisting with process control.

Cryptosporidium is an ongoing concern for utilities and its inactivation is a top priority in keeping the public safe. In literature, combined particle counts have been associated with high turbidity, changes in filtration rate, temperature variations, and type of media. By analyzing particle count data of cryptosporidium sized particles, utilities can optimize plant operations by adjusting coagulant dosage and filter runtime during spikes in particle counts to reduce potential high concentrations of contaminants.

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Figure 1: Relationship between combined turbidity and combined particle counts from literature. (Bridgeman 2002)

Objectives

1. To monitor concentrations of Cryptosporidium size particles in filter effluent and identify action levels for process control.

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• To determine any relationships between high cryptosporidium sized particle counts and high turbidity, or filtration rate.

Materials and Methods

The particle count data was recorded using ChemTrac PC3400 particle counters, which were installed after filtration. The particle counters were calibrated using ChemTrac 2K-02 (2 micron) and 2K-10 (10 micron) calibration beads. Calibration was performed using a 1500 counts/ml solution of 2K-02, and a 1000 counts/ml solution of 2K-10. A QA/QC check was performed using different concentrations of the calibration bead solutions. Cryptosporidium sized particle (2-6 microns) data were used during the analysis.

Results/Modeling

Finding 3: For quantifying Cryptosporidium sized particles, particle counters maintained <40% difference from expected concentrations (accuracy) and <10% relative standard deviation (precision) after continuous online operation for 4 months

Table 1. Left, as the 2-micron concentration increased the accuracy decreased, while precision increased. Right, As the concentration of the 10-micron solution increased, the accuracy and precision increased.

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Figure 2. 2-6 micron particle counts were plotted over runtime for Wheeler filters with 3” of sand, no sand, and Leopold filters.

Discussion and Conclusions

• The data was precise and was within 40% accuracy as long as proper maintenance was being met on the particle counter instruments.
• There was no visible correlation between 2–6-micron particle counts and high turbidity, high flow rate, or change in flow rate, which was to be expected as particle counts are more sensitive than turbidity.
• Although clear trends were observed, there was no clear trend for particle concentration over filter runtime for all filter runs. Sand level and filter type do not impact cryptosporidium sized particles during filter runs. More statistical analysis is needed to determine any trends between runs to determine relevant action levels for process control.

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Acknowledgements

We gratefully acknowledge the Ann Arbor Drinking Water Treatment Plant staff for assisting with data collection.

References

[ ERS ### ]

Finding 2: Cryptosporidium sized particles were not correlated to turbidity, flow rate, or change in flow rate.

Figure 3. Cryptosporidium sized particles vary in concentration regardless of turbidity or filtration rate.

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Finding 1: Each filter run had a clear profile, not just noise, but profiles between filters were not always similar.

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[1] Bridgeman (2002)

[2] AWWA Research Foundation (2000)

[3] Janice Skadsen (Ann Arbor), Tony Myers (Ch2m hill), and Jason Sharpley (HDR)