1. Advanced Techniques for Monitoring NOM and Controlling DBPs Ben Wright, PE Bill Becker, PE, PhD Dave Reckhow, PhD Steve Schindler 2013 NYC Watershed/Tifft Science & Technical Symposium

3. Frumhoff et al, 2007 Peduzzi, 2004

4. Water Quality Impacts of Extremes Heavy precipitation Contaminants, nutrients, and sediment flushed into rivers and lakes Overloading of storm and wastewater systems (increasing risk of contamination) Severe drought  Concentrates point source contaminants in raw drinking water supplies  Water quality can degrade as reservoirs drop  NOM levels can peak following reservoir refill

5. Droughts and Nutrients NOAA Earth Observatory

6. Algal Blooms Blooms are caused by ideal combination of (typically higher) temperatures and nutrients 2011 bloom on Lake Erie

7. Research to Characterize NOM Water Research Foundation - On-Line NOM Characterization: Advanced Techniques for Controlling DBPs and for Monitoring Changes in NOM under Future Climate – NYC DEP NYSERDA - Climate change and water quality - Impacts and adaptation strategies for NYS utilities – MCWA, MVWA, OCWA, SCWA, Waterloo, Watertown, Latham Water, and NYC DEP

8. Climate Comparison Downscaled GCM data from both DEP and NYSERDA – Will compare projected weather patterns with historical Sampling in spring and summer for reservoirs in VA and NC – Will compare NY and southern reservoir lab results Carvins Cove, Roanoke, VANorth Fork Reservoir, Asheville, NC

9. NOM Characterization Methods

10. Direct Hydrophobicity Test 10 Hydrophobic NOM – Retained on XAD-8 TOC#1-TOC#2 Mesophilic NOM – Retained on XAD-4, but not on XAD-8 TOC#2-TOC#3 Hydrophilic NOM – Not retained TOC#3 XAD-8 Test Water XAD-4 To Waste TOC#1 TOC#2 TOC#3

11. Elution-Based Hydrophobicity Test Actual recovered NOM from each resin – Hydrophobic = TOC #4 – Mesophilic = TOC #5

12. Figure 1 Experimental setup for PRAM. SPE cartridges contained 100 mg of sorbent with a total volume of 1.5 mL and average pore size of 60 Å. The retention coefficient (RC) is calculated based on the maximum breakthrough concentration and the initial concentration. C-18, C- 8, and C-2 are nonpolar sorbents; Silica, Diol, and Cyanide (CN) are polar sorbents; Amino (NH-2) is a weak anion exchange and SAX is the strong anion exchanger. Published in: Fernando L. Rosario-Ortiz; Shane Snyder; I. H. (Mel) Suffet; Environ. Sci. Technol. 2007, 41, 4895-4900. DOI: 10.1021/es062151t Copyright © 2007 American Chemical Society SCX Ph UV/Vis + TOC Differences between UMass method and the Rosario-Ortiz method are in red Polarity Rapid Assement Method (PRAM)

13. Florescence Spectroscopy

14. What is Fluorescence Spectroscopy Light interacts with organic matter (OM) in water Specific wavelengths excite molecules (fluorophores) within the OM causing them to fluoresce – Chemical composition, source, cause different fluorescence signatures Excitation-emission matrixes are becoming more popular for determining the amount of dissolved OM in the water

15. Typical Excitation Emission Matrix Region ID Description Region I Microbial Byproducts, Proteins, Biopolymers Region II Fulvic-Like Compounds Region III Humic -Like Compounds

16. DOM and Fluorescence Colored dissolved organic matter (CDOM) is optically active fraction of DOM Land use, urban growth/development, climate change, severe weather impact all impact source and quantity of raw water DOM Treatment processes can remove DOM Example: decrease in fluorescence with increase in coagulant dose Raw 20 mg/L PACl 40 mg/L PACl

17. How Can Fluorescence Help Utilities Identify potential correlations between certain types of DOM and DBPs Optimize coagulation and other processes Identify source water changes Identify impact of extreme weather (both flooding and drought) on water quality Identify sources of DOM Identify areas of potential fouling for membrane applications

18. Spectral Analysis S::CAN spectro::lyser – Measures complete absorbance spectra of waters (200-750 nm) – Calibrated with identical unit in UMASS lab – Installed at DEP April 2013 Research Goal: evaluate ability of spectro::lyser to measure relationships between spectral features, NOM fractions, and DBP precursors

20. Utilizing Improved Methods Source water quality – Watershed improvement/protection – Source rotation Treatment process optimization Distribution system modifications

21. Stage 2 Compliance Tool Kit The Manual and web tool provide guidance for complying with Stage 2. The goal of the materials is to help utilities: – Evaluate potential compliance relative to a goal – Understand DBP reduction strategies – Compare DBP reduction strategies using system specific information to estimate: Percent DBP reductions Cost

22. Available Data Determine Data Available: DBPs: – Stage 1 Quarterly since at least 2002 (for larger systems) – IDSE (between 2006 and 2009) What type of IDSE performed? Standard Monitoring Hydraulic Model System Specific Study Data used to satisfy IDSE 1 – 6 measurements per sample site for 1 year – Additional / Non-Compliance Continued monitoring of IDSE sites or early monitoring of selected compliance sites

23. Other Useful Data Population Served TOC Raw water alkalinity Raw Water Bromide Finished water pH Advanced TOC characterization – UV 254 and/or SUVA Chlorine usage data – Total chlorine usage in plant – Residual chlorine levels Distribution System – Locational Water Age (if known) – Seasonal Demand – System Storage Capacity

24. Web Tool Generated Report 24

25. Strategies Considered 25 SourceTreatmentDistribution Source Change or Blending Source Management Purchase Water Point of Chlorination Optimize Chlorine Dose Optimize / Add PAC Optimize Coagulation for TOC Change Coagulation Change Primary Disinfection Advanced TOC removal – GAC Advanced TOC removal - MIEX Membranes Optimize DS Chlorination / Booster Chlorination Change Secondary disinfection Optimize Storage Operation In-Tank Treatment System Flushing

26. Determining Impact of Strategies Each Strategy linked to an “optimum” DBP reduction Users will answer a series of questions about their systems to hone in on “actual” DBP reduction potential Cost curves for each strategy are also linked to questionnaire responses 26

27. Thank You! Ben Wright – bwright@hazenandsawyer.com Bill Becker – wbecker@hazenandsawyer.com 27