Development of an Algorithm for Dosing PAC to Remove NOM and Control DBP Formation

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Transcription:

Development of an Algorithm for Dosing PAC to Remove NOM and Control DBP Formation Adam Eyring, Linda Kramer, Kate Guest Philadelphia Water Department PA-AWWA Annual Conference 2014 Bethlehem, PA

Topics Introduction Study Design Formation Potential PAC Development of Algorithm Summary

Philadelphia Water Department (PWD) Municipal Water & Wastewater Utility Two surface water sources: Schuylkill and Delaware Rivers Three water treatment plants: Queen Lane, Belmont, and Baxter 13 pressure districts Over 3,000 miles of main Supply over 250 MGD to a population of 1.738 million Chloraminated system

PWD WTPs practice conventional treatment. Intake KMnO 4, PAC (seasonal) Rapid Mix ferric, NaOCl, hyd lime, PAC Flocculation Sedimentation NaOCl, hyd lime Filtration NH 3 / F / PO 4 Storage / Distribution

DBP Monitoring 12 locations for THM Rule and Stage 1 16 locations for Stage 2 (monthly) Weekly (non-regulatory) at WTP effluents to gauge levels in the system

Since Stage 1 started Spikes in HAA5 levels at Baxter WTP have been of concern. 160 5 Haloacetic Acids 140 120 100 80 60 40 20 0 1/1/2002 1/1/2003 1/1/2004

Work just a few years earlier showed that Delaware River NOM had a higher reactivity to produce HAAs than Schuylkill.

Studies were performed to address DBP concerns at Baxter WTP: Formation Potential in 2004 NOM Removal with PAC in 2006 Goal: Identify and use a convenient water quality parameter to anticipate and prevent DBP issues.

Study 1: Formation Potential Study Design 1) River water collected weekly 2) Water filtered with 1 and 0.47 μm filters 3) Filtered water dosed with 5 mg/l Cl 2 and incubated at 20ºC for 24 hours Aliquots of water before and after filtering were measured for TOC, DOC, and UV254. DBPs were analyzed after incubation.

Formation Potential Results Good relationship between DBP FP and TOC (chlorine depleted at high TOC)

Formation Potential Results Cont d UV-TOC relationship demonstrated high correlation.

Formation Potential Results Cont d DBP FP also correlated well with UV254.

Formation Potential Results Cont d Increases in UV254 predicted river events well.

Formation Potential Results Cont d WTP Effluent DBPs exhibited good correlation to river UV254. Storm or snowmelt impacted

Formation Potential Results Summary TOC was a good predictor of DBP FP, but it is not a convenient parameter to use. UV was also a good predictor of DBP FP because it correlated well with TOC and DOC. UV254 also had good correlation with WTP effluent DBPs. Increases in UV254 predicted river events well. UV254 was adopted as the convenient parameter to anticipate elevated DBPs. UV254 analysis is a rapid test and can be done at the plant site.

Formation Potential Results Summary cont d Routine UV254 monitoring has shown that coagulant demands increase with UV increases. UV increases can precede turbidity increases during weather events.

Study 2: PAC Testing Study Design 1) River water collected weekly 2) Six 1-liter aliquots jar-tested with different PAC doses (including blank and duplicate) 3) After 1 hour of mixing and 10 min of settling, PAC removed with 1-μm filter Aliquots of water before and after filtering were measured for TOC, DOC, and UV254. PAC was lignite-based and had been in regular use for T&O control.

PAC Testing Results DBP FP reduction versus PAC dose:

PAC Testing Results cont d DBP FP reduction versus UV254 reduction:

Development of Algorithm An effluent HAA result of 45 μg/l (comfort level of 75% of MCL) approximately correlated to UV254 = 0.10 cm -1 a suitable UV254 level to start PAC dosing. Experience with the algorithm through the seasons lead to adjustments to avoid wasting PAC at lower temperatures.

Development of Algorithm cont d Current PAC Algorithm for Different Water Temps (ºF) (May change on short notice in response to spills and T&O events.)

FULL SCALE TREATMENT Dosing Carbon Slurry at Influent Channels to the Tidal Raw Water Basin; 12-18 hour DT BAXTER WATER TREATMENT PLANT

BAXTER WTP CARBON DOSING GUIDE- November 2008 Amended 10/15/13 : no routine dosing water temp < 50F unless UV254 river >0.110/cm or spill or T&O Carbon Dose #/ m g 190 180 170 160 150 140 130 120 110 100 90 80 70 60 50 40 0.05 0.085 0.09 0.099 0.109 0.12 0.129 0.14 River UV254 carbon dose H2O temp >55F and <65F carbon dose H2O temp >66F revised< 55 F and equal to50f Poly. (carbon dose H2O temp >55F and <65F) Poly. (carbon dose H2O temp >66F) Poly. (revised< 55 F and equal to50f)

How have things been since algorithm developed? Daily Routine UV254 analysis of raw water & RWB effluent continues - data used to trigger dosage changes and track carbon product effectiveness Refined the Dosing Curves based on full scale experience -jar test results underpredict full scale UV254 % removal across the large 176 MG Raw Water Basin with 12-18 hour detention time - change from lignite to wood-based carbon in FY09; better removal - change from wood to coconut product (good T&O removal); drop in effectiveness in NOM removal -back to lignite product and refined 2008 Dosing Curves

Post-algorithm (2006) DBP results have been under better control 90 75 60 45 30 15 1999 Q1Q2 2000 Q1 Q2 0 Baxter HAA5 Running Annual & High Service Averages 2001 Q1Q2 2002 Q1Q2 2003 Q1Q2 2004 Q1Q2 2005 Q1Q2 2006 Q1Q2 2007 Q1Q2 2008 Q1Q2 2009 Q1Q2 2010 Q1Q2 2011 Q1Q2 2012 Q1Q2 2013 Q1Q2 2014 Q1 Bx Dist RAA Reg HAA PWD ops goal<75% HAA5 Reg Limit HS Q avg

while UV-254 has been frequently exceeding 0.1 cm -1.

Summary Formation potential study gave us a wealth of information over one year PAC study demonstrated the power of using PAC as a routine method for DBP control Development of algorithm and confirming UV254 as an effective trigger parameter gave us a valuable tool to make treatment process changes and meet DBP compliance

Acknowledgements PWD Operations John Muldowney, Bruce Aptowicz, Bill Wankoff, Rita Kopansky, Norm Jadczak, Joanne Utkus, Jerry Kuziw, Nicole Charlton, Donna Schwartz, Ramesh Shah PWD Laboratory Mike Intenzo, Erwin Lewis, Philip Kurien, Earl Peterkin, Alexa Obolensky, Kan Narangajavana, Lou Ceci, Moses Abdulai, George Oalickal, Joe Spiller

Thank you. Any questions?