Charles R. Cutietta-Olson, Deputy Chief Watershed Water Quality Operations, BWS, DEP 9/10/09

1. Water Quality New York City Department of Environmental Protection An Examination of Chlorine Demand of the Catskill and Delaware Supplies of the NYC Water Supply System 2005-2006 Charles R. Cutietta-Olson, Deputy Chief Watershed Water Quality Operations, BWS, DEP 9/10/09

2. Water Quality New York City Department of Environmental Protection Acknowledgements • Thanks to Lori Emery, Salomé Freud and Lin Lu for looking at early graphics and output and providing correction, direction and encouragement. • Thanks to the Early Warning Remote Monitoring Group for providing the continuous monitoring data files. • Thanks to Ralph Marchitelli, Dan Massi and the supervisors at Shaft 18 for providing documentation and patiently responding to questions.

3. Water Quality New York City Department of Environmental Protection Why examine chlorine demand? • Quantifying chlorine demand and understanding patterns could lead to better system operations. • The investigator speculated that different turbidity sources may be associated with different levels of chlorine demand, and 2005-2006 includes periods higher turbidities associated with storms in the Catskills and storm events local to Kensico Reservoir, the Source Water for both systems. • Most of the data were available as an electronic file of continuous on-line measurements. • Chlorine demand of the water supply should be a natural function of water quality and thus empirically quantifiable rather than something that must be examined through probability and statistics.

4. Presentation Overview • Site locations and source data • Cl demand = initial FCR – FCR at first treated site • Estimating initial Free Chlorine Residual (initialFCR) • Data frequency plots, Cat vs. Del • Chlorine demand during two weather events proximal to the Source Water • Discussion of upper 0.2%ile of Chlorine Demand “events” • Data frequency plots of upper 25th%ile of Chlorine Demand • Multiple linear regression models

5. Cl demand = initialFCR – FCRfirst treated site Data were gathered from four sites: CATLEC Shaft 18Eastview Shaft19 The equation for calculating disinfection compliance requires four parameters: free chlorine residual (FCR), contact time, temperature and pH. DEP uses the values recorded at CATEV, Uptake 1, DEL19 and Uptake 2 for compliance purposes.

6. Water Quality New York City Department of Environmental Protection Continuous On-line Data Data had gaps which had to be filled. Data fill sources included compliance Source Water turbidity data and Kensico Laboratory Data.

7. Water Quality New York City Department of Environmental Protection Estimating Chlorine Dose Concentration (initialFCR) • Cl Demand = initialFCR – FCRfirsttreated site • initialFCR is not measured, but must be estimated. • Dose-based initialFCR is derived from System Operations’ records of dose changes in lbs/MGD. • Use-based initialFCR is derived from records of pounds of chlorine gas used by each system and the amount of flow it was applied to on an hourly basis. • To compare Use-based and Dose-based estimates of initialFCR, the noon time moment for each day for the 2005-2006 period was plotted for each system.

9. Kendall’s tau correlation coefficients and number of observations (n) for dose-based initialFCR(dFCRinitial) and use-based initialFCR (uFCRinitial) and for first treated site. (p-value for all coefficients <0.0001) Catskill System: Delaware System:

10. Water Quality New York City Department of Environmental Protection Selected Dose-based Estimate of initialFCR • Use estimates should be a better predictor than dose estimates. • Both tables list a stronger tau coefficient between FCRfirst treated site and the dose-based (dFCRinitial) rather than use-based (uFCRinitial) initial FCR estimate. • The tau coefficients suggest that dFCRinitial is at least not a worse predictor of FCRfirst treated site than uFCRinitial.

11. Water Quality New York City Department of Environmental Protection Any Patterns Visible in Time Series Plots? • Complete data sets of ~200,000 observations were pared down based on frequency of treated pH monitoring (30 min). • Data sets of ~32,000 observations were plotted as time series, but patterns were not obvious. • The following frequency distribution plots display Catskill System data on the left and Delaware System data on the right.

15. The next two slides display time series data from two local weather-driven turbidity events.

16. Water Quality New York City Department of Environmental Protection Note that Cl Demand increases with flow reduction and residence time increase

17. Water Quality New York City Department of Environmental Protection Fluctuation of chlorine demand around turbidity spike.

18. Water Quality New York City Department of Environmental Protection Examination of Upper 0.2%ile of Chlorine Demand • Catskill System, Cl Demand ≥ 1 mg/L: • 38% of the 74 observations were associated with aqueduct shutdowns (28 obs). • Other instances appeared to be “blips” which could result from power spikes or equipment maintenance. • September 2006 event comprises 26% of this data set (19 obs). • Delaware System, Cl Demand ≥ 0.9 mg/L: • 85% of the 82 observations occur in the 12/19-20/05 period. • Some instances appear to be “blips”.

19. Water Quality New York City Department of Environmental Protection Looking for Water Quality Characteristics Associated with High Chlorine Demand • Working only with treated and raw pH, treated and raw temperature, and raw water turbidity. • The following plots display ~32,000 observation data set on left vs. data subsetted for approximately upper 25% percentile of Cl Demand data on right.

22. Water Quality New York City Department of Environmental Protection

25. Water Quality New York City Department of Environmental Protection

26. Multiple Linear Regression Models Catskill System All data n=24,765 total model R2 = 0.390 25th%ile Cl Demand of above data n=6,856 total model R2 = 0.176

27. Multiple Linear Regression Models Delaware System All data set n=27,793 total model R2 = 0.296 25th%ile Cl Demand of above data n=7,256 total model R2 = 0.234

28. Water Quality New York City Department of Environmental Protection Conclusions • Chlorine demand of both systems was normally distributed around 0.5 ppm over the period of investigation • Fluctuations in chlorine demand appeared most closely related to changes in temperature as measured at the treated sites. • Unfiltered continuous–monitoring data require considerable work before analysis. • The Catskill System may be more influenced by ambient environmental factors than the Delaware System.