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An Examination of Chlorine Demand of the Catskill and Delaware Supplies of the NYC Water Supply System 2005-2006 PowerPoint Presentation
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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. Water Quality.

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Presentation Transcript
slide1

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

acknowledgements

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.
why examine chlorine demand

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.
presentation overview
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
data were gathered from four sites catlec shaft 18 eastview shaft19

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.

continuous on line data

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.

estimating chlorine dose concentration initial fcr

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.
slide9

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:

selected dose based estimate of initial fcr

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.
any patterns visible in time series plots

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.
slide16

Water Quality

New York City Department of Environmental Protection

Note that Cl Demand increases with flow reduction and residence time increase

slide17

Water Quality

New York City Department of Environmental Protection

Fluctuation of chlorine demand around turbidity spike.

examination of upper 0 2 ile of chlorine demand

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”.
looking for water quality characteristics associated with high chlorine demand

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.
slide22

Water Quality

New York City Department of Environmental Protection

slide25

Water Quality

New York City Department of Environmental Protection

multiple linear regression models
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

slide27

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

conclusions

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.