Optimization Stories From the Field
Marvin Gnagy, P.E., President
PMG Consulting, Inc.
NE District AWWA Canton HOF
August 17, 2017
Optimization Stories From The Field
▪ Optimization practices used in the field▪ Short synopsis
▪ Optimization stories▪ Evaluations made
▪ Technical solutions developed
▪ Implementation and verification
▪ Results achieved
▪ Questions
Agenda
2
Optimization Stories From The Field
3
▪ Define objectives/goals▪ Why should this project be initiated
▪ Develop baseline characteristics▪ Current operations and metrics
▪ Benchmark industry standards or best practices▪ Compare where things are to where you believe they should be
▪ Conduct gap analysis▪ How do I get to the goals?
▪ Tools, capital, training, operating adjustments that might be needed to achieve the goals
Optimization Practices Used in Field
3
Optimization Stories From The Field
4
▪ Establish Implementation strategy▪ Capital needs
▪ Tools, modeling, etc.
▪ Operational changes
▪ Adjustment protocols
▪ Verification procedures
▪ Track progress against objectives/goals▪ Did you meet the objectives and goals?
▪ Did you exceed the objectives and goals?
▪ Did you improve water quality?
▪ Did you improve performance?
Optimization Practices Used in Field
4
Optimization Stories From The Field
Atlanta-Fulton County, Georgia
5
Optimization Stories From The Field
▪ 90 mgd surface water plant▪ Average daily production 44.5 mgd
▪ Reservoir storage from Chattahoochee River
▪ Coagulation/filtration plant▪ Chemical treatment
▪ Solids handling
▪ Disinfection and storage
▪ Finished water pumping to two wholesale distribution systems▪ 400,00 people
Atlanta-Fulton County
6
Optimization Stories From The Field
Atlanta-Fulton County
7
Floc Speed Adjustments Initiative
Optimization Stories From The Field
Atlanta-Fulton County
8
Sedimentation basins with plate settlers
Optimization Stories From The Field
▪ Floc Speed Adjustments Initiative▪ Jagged, feathery floc observed entering the sedimentation process
▪ Measured drive output speeds at different VFD settings
▪ Established rotational output at any VFD setting
▪ Defined current G values for each of four stages
▪ 4 sec-1, 4 sec-1, 3 sec-1, 2 sec-1
▪ Operators afraid of floc shear
▪ Conducted jar testing to establish optimum G values for floc development and settleability
▪ Graphed floc settleability versus G value to find optimum mixing characteristics
Atlanta-Fulton County
9
Optimization Stories From The Field
Atlanta-Fulton County
10
Low density
floc particles
observed in
full-scale
operations
Optimization Stories From The Field
Atlanta-Fulton County
11
y = 0.38399x - 0.03307R² = 0.99695
0.01.02.03.04.05.06.07.08.09.0
10.011.012.013.014.015.016.017.018.019.020.021.022.023.0
0 5 10 15 20 25 30 35 40 45 50 55 60
Sh
aft
Ro
tati
on
al
Sp
eed
, R
PM
Floc Drive Speed, Hz
VFD rotational
speed calibration
Optimization Stories From The Field
Atlanta-Fulton County
12
y = 0.38399x - 0.03307R² = 0.99695
0.01.02.03.04.05.06.07.08.09.0
10.011.012.013.014.015.016.017.018.019.020.021.022.023.0
0 5 10 15 20 25 30 35 40 45 50 55 60
Sh
aft
Ro
tati
on
al
Sp
eed
, R
PM
Floc Drive Speed, Hz
At any drive
setting
Optimization Stories From The Field
Atlanta-Fulton County
13
y = 0.38399x - 0.03307R² = 0.99695
0.01.02.03.04.05.06.07.08.09.0
10.011.012.013.014.015.016.017.018.019.020.021.022.023.0
0 5 10 15 20 25 30 35 40 45 50 55 60
Sh
aft
Ro
tati
on
al
Sp
eed
, R
PM
Floc Drive Speed, Hz
At any drive
setting
We know the
rotational
output
Optimization Stories From The Field
Atlanta-Fulton County
14
R² = 0.9996
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
0 10 20 30 40 50 60
Flo
c S
ett
leab
ilit
y, g
pm
/ft
2
First Stage G Value, sec-1
Floc settleability curve from jars
Optimization Stories From The Field
Atlanta-Fulton County
15
R² = 0.9996
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
0 10 20 30 40 50 60
Flo
c S
ett
leab
ilit
y, g
pm
/ft
2
First Stage G Value, sec-1
Current G
value, 4 sec-1
Floc settleability curve from jars
Optimization Stories From The Field
Atlanta-Fulton County
16
R² = 0.9996
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
0 10 20 30 40 50 60
Flo
c S
ett
leab
ilit
y, g
pm
/ft
2
First Stage G Value, sec-1
Current G
value 4 sec-1
Suggested G value
40 sec-1
Floc settleability curve from jars
Optimization Stories From The Field
Atlanta-Fulton County
17
R² = 0.9996
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
0 10 20 30 40 50 60
Flo
c S
ett
leab
ilit
y, g
pm
/ft
2
First Stage G Value, sec-1
Current G
value 4 sec-1
Operating SOR =
1.14 gpm/ft2
Suggested G value
40 sec-1
Optimization Stories From The Field
• Adjusted floc drive speeds to produce suggested G values
• Tracked settled water turbidity online monitoring
• Reduced from 0.5 NTU average to 0.1 NTU average within 4 days
• Possible to reduce coagulant dosage to obtain similar settled turbidity
• Implemented without capital costs
Atlanta-Fulton County
18
Optimization Stories From The Field
• Dewatering accomplished in gravity thickeners, lime amendment to pH 12, sludge conditioning and pumping, plate and frame filter press
• Cake disposal in local landfill
• Cake typically 23% solids (another story)
Atlanta-Fulton County
19
Optimization Stories From The Field
▪ Coagulant reduction could impact other processes and costs▪ Reduced solids production
▪ Reduced lime for dewatering
▪ Reduced post-lime for pH adjustment/corrosion control
▪ Cake disposal
▪ Phase 2 optimization▪ Define current operating costs
▪ Develop potential costs under optimized coagulant dosing
▪ Establish new settled water target values
▪ Verify operating costs from annual operations
Atlanta-Fulton County
20
Optimization Stories From The Field
Initial Operating Metrics
Alum, mg/L 15.6
Post-lime, mg/L 3.92
Dewatering lime, lbs/mo. 76,798
Filter cake, dry tons per year 941
Alum, lbs/MG 132.2
Post-lime, lbs/MG 33.3
Dewatering lime, tons per dry
ton cake 1.832
Atlanta-Fulton County
21
$180,969
$35,400
$66,998
$87,219
2015 Operating Cost Breakdown
Coagulant
Post-lime
Dewatering lime
Cake disposal
Cost savings
Annual operating cost $370,586
Optimization Stories From The Field
Initial Operating Metrics Projected Operating Metrics
Alum, mg/L 15.6 Alum, mg/L 12.5
Post-lime, mg/L 3.92 Post-lime, mg/L 3.2
Dewatering lime, lbs/mo. 76,798 Dewatering lime, lbs/mo. 57,599
Filter cake, dry tons per
year941
Filter cake, dry tons per
year752
Alum, lbs/MG 132.2 Alum, lbs/MG 105.9
Post-lime, lbs/MG 33.3 Post-lime, lbs/MG 27.2
Dewatering lime, tons per
dry ton cake 1.832Dewatering lime, tons per
dry ton cake 1.832
Atlanta-Fulton County
22
Expected 20% overall reduction in operating costs
Optimization Stories From The Field
▪ Implementation and verification of annual operations▪ Month-to-month tracking and comparisons first year
▪ Calculation of operating costs and actual savings
▪ Adjustment of operating metrics
▪ Summation of first-year operations
Atlanta-Fulton County
23
Dewatering lime feed
Optimization Stories From The Field
Initial Operating Metrics Actual Operating Metrics
Alum, mg/L 15.6 Alum, mg/L 9.6
Post-lime, mg/L 3.92 Post-lime, mg/L 2.9
Dewatering lime, lbs/mo. 76,798 Dewatering lime, lbs/mo. 51,123
Filter cake, dry tons per
year941
Filter cake, dry tons per
year650
Alum, lbs/MG 132.2 Alum, lbs/MG 79.8
Post-lime, lbs/MG 33.3 Post-lime, lbs/MG 23.7
Dewatering lime, tons per
dry ton cake 1.832Dewatering lime, tons per
dry ton cake 1.832
Atlanta-Fulton County
24
Optimization Stories From The Field
Atlanta-Fulton County
25
$100,280
$24,392
$44,599$58,704
$142,611
2016 Operating Cost Breakdown
Coagulant
Post-lime
Dewatering lime
Cake disposal
Cost savings
Annual operating cost $227,975
Actual 38% reduction in annual costs obtained
Excellent coordination between operations and
engineering toward a common goal
$180,969
$35,400
$66,998
$87,219
2015 Operating Cost Breakdown
Coagulant
Post-lime
Dewatering lime
Cake disposal
Annual operating cost $370,586
Optimization Stories From The Field
Buffalo Water, New York
26
Optimization Stories From The Field
▪ 120 mgd surface water plant, originally 1922▪ Average daily production 71 mgd
▪ Direct draw from eastern basin Lake Erie▪ Just upstream of Niagara River
▪ Coagulation/filtration plant▪ Chemical treatment
▪ Solids handling
▪ Disinfection and storage
▪ Finished water pumping to distribution system▪ 257,00 people
Buffalo Water
27
Lake Intake Structure
Optimization Stories From The Field
Buffalo Water
28
Coagulant Mixing Initiative
Optimization Stories From The Field
▪ SternPac coagulant used since 1990’s▪ Raw water turbidity averages 2 NTU
▪ Settled water turbidity averaged 0.85 NTU
▪ Filter run times 72 hours
▪ Low head loss, possible optimization initiaitive
▪ One coagulant feed point▪ Low service discharge header
▪ Relatively poor mixing
▪ Coagulant not contacting within pump flow depending on pump in operation
Buffalo Water
29
Optimization Stories From The Field
Buffalo Water
30
Coagulant Feed Line
Discharge header
Optimization Stories From The Field
Buffalo Water
31
Coagulant Feed Line
Discharge header
Optimization Stories From The Field
Buffalo Water
32
Coagulant Feed Line
Discharge header
Optimization Stories From The Field
Buffalo Water
33
Coagulant Feed Line
Changed
feed point to
each pump
discharge to
improve
mixing
Discharge header
Optimization Stories From The Field
▪ Mixing improvement immediately led to 17% reduction in coagulant dosage▪ 9.7 mg/L to 8 mg/L
▪ Coagulant reduction also impacted▪ Sludge dewatering
▪ Polymer conditioning
▪ Cake disposal
▪ Operating costs
Buffalo Water
34
Optimization Stories From The Field
Buffalo Water
35
Floc and sed basins cleaned annually, no sludge
removal equipment
Optimization Stories From The Field
Buffalo Water
36
Sludge pumped to backwash lagoon for further processing
Optimization Stories From The Field
Buffalo Water
37
Lagoon contents pumped to
conditioning tank for polymer
addition
Optimization Stories From The Field
Initial Operating Metrics
SternPac, mg/L 9.67
Dewatering polymer,
lbs/ton12.95
Cake production, dry
tons/yr931
Cake solids, % 22.6
Buffalo Water
38
$244,236$177,669
$48,037
Coagulant
Disposal
Polymer
2014 Operating Cost Breakdown
Annual Operating Cost $469,941
Optimization Stories From The Field
Buffalo Water
39
Initial Operating Metrics Actual Operating Metrics
SternPac, mg/L 9.67 SternPac, mg/L 8.0
Dewatering
polymer, lbs/ton12.95
Dewatering polymer,
lbs/ton10.13
Cake production,
dry tons/yr931
Cake production, dry
tons/yr725
Cake solids, % 22.6 Cake solids, % 32.1
Optimization Stories From The Field
Buffalo Water
40
Actual 33.5% reduction realized in annual costs
$196,621
$95,023
$20,640
$157,658
Coagulant
Disposal
Polymer
Savings
2015 Operating Cost Breakdown
Annual Operating Cost $312,284
$244,236$177,669
$48,037
Coagulant
Disposal
Polymer
2014 Operating Cost Breakdown
Annual Operating Cost $469,941
Optimization Stories From The Field
Buffalo Water
41
Actual 33.5% reduction realized in annual costs
Annual cost savings $157,657
$196,621
$95,023
$20,640
$157,658
Coagulant
Disposal
Polymer
Savings
2015 Operating Cost Breakdown
Annual Operating Cost $312,284
$244,236$177,669
$48,037
Coagulant
Disposal
Polymer
2014 Operating Cost Breakdown
Annual Operating Cost $469,941
Optimization Stories From The Field
▪ Future optimization plans▪ Floc speed adjustments (underway with another 12% coagulant
reduction)
▪ Incorporate activated carbon reactors for T&O/cyanotoxin treatment
▪ Install conventional rapid mix to further reduce coagulant feed
▪ Add streaming current monitors to automate coagulant feed
▪ Optimize filter performance
Buffalo Water
42
Optimization Stories From The Field
NEMRWSD – Tupelo, MS
43
Optimization Stories From The Field
NEMRWSD – Tupelo, MS
44
Optimization Stories From The Field
▪ 18 mgd surface water plant drawing from Tombigbee River▪ Average daily production 12 mgd
▪ Coagulation/filtration plant▪ Chemical treatment
▪ Solids handling
▪ Disinfection and storage
▪ Final chloramination
▪ Finished water pumping to four wholesale distribution systems▪ ≈70,000 people
NEMRWSD – Tupelo, MS
45
Optimization Stories From The Field
NEMRWSD – Tupelo, MS
46
Disinfection Optimization Initiative
Optimization Stories From The Field
▪ Filtered water disinfected using free chlorine▪ Water flows through three clearwells for CT compliance
▪ Final pass ammonia added for chloramine conversion
▪ High TOC in filter effluent is common
▪ HAA5 formation issues existed previously
– 2 periods greater than 60 µg/L LRAA
▪ Residual monitored continuously
▪ Clearwells supply high service pumps▪ Six pumps and three large diameter distribution force mains to the
supply district
NEMRWSD – Tupelo, MS
47
Optimization Stories From The Field
NEMRWSD – Tupelo, MS
48
AMMONIA
RESIDUAL
CHLORINE
Average total
chlorine 3.3
mg/L
RESIDUAL
RESIDUAL
RESIDUAL
Optimization Stories From The Field
NEMRWSD – Tupelo, MS
49
AMMONIA
RESIDUAL
CHLORINE
Average total
chlorine 3.3
mg/L
RESIDUAL
RESIDUAL
RESIDUAL
Were not taking
advantage of 48” piping
contact time
Optimization Stories From The Field
▪ Developed CT model to predict potential chemical feed and monitoring locations▪ Meet CT requirements according to water temperature variations
▪ Water temp variations 7oC to 30oC
▪ Minimize HAA5 formation in summer months
▪ Produce chloramines to slow HAA5 formation
▪ Install new ammonia feed and residual monitoring points as predicted
▪ Obtain Mississippi DOH approvals▪ Changes in feed points
▪ CT monitoring and compliance
NEMRWSD – Tupelo, MS
50
Optimization Stories From The Field
NEMRWSD – Tupelo, MS
51
8,200 7.00 7.0 8.0 0.80 2.80 0.05 0.05 0.05 21.9
CUMMULATIVE
MINUTES
FRONT WEIR
CHAMBER PRETREATMENT 26.4 26.4
END OF WEIR
CHAMBER 1 WEIR CHAMBER 0.6 27.0
END OF
CLEARWELL A CLEARWELL A 5.5 32.5
END OF
CLEARWELL B CLEARWELL B 22.4 54.9END OF
CLEARWELL C CLEARWELL C 5.5 60.4 1.02
NORTHEAST MISSISSIPPI REGIONAL WATER SUPPLY DISTRICT - TUPELO, MS
CT CALCULATIONS MODEL
LOWEST
CLEARWELL
OPERATING
LEVEL, ft.
WEIR CHAMBER
FREE CHLORINE
CONC. mg/L
PRETREATMENT
BASINS FREE
CHLORINE
CONC. mg/L
CLEARWELL B
FREE CHLORINE
CONC. mg/L
1 = SELECT CURRENT
AMMONIA FEED POINT CUMMULATIVE CT (mg/L-minutes)
PEAK HOURLY
TREATMENT
FLOW, gpm
HIGHEST
WATER pH
LOWEST
WATER TEMP. oC
DISINFECTION CONTACT
TIMES - MINUTES
CLEARWELL A
FREE CHLORINE
CONC. mg/L
CLEARWELL C
FREE
CHLORINE
CONC. mg/L
22.8
22.8
22.8
CT RATIO22.8
21.1
REQUIRED
CT FROM
TABLES
mg/L-min.
1.02
7.0
Optimization Stories From The Field
▪ Model suggested CT compliance through weir chamber using free chlorine▪ Ammonia feed after weir chamber to slow HAA5 formation
▪ Residual monitoring downstream of feed point
▪ Added multiple feed point and residual monitors to clearwell arrangements
NEMRWSD – Tupelo, MS
52
Optimization Stories From The Field
NEMRWSD – Tupelo, MS
53
AMMONIA 4
RESIDUAL 4
CHLORINE
Multiple NH3
feed points
based on water
temp changes
RESIDUAL 3
RESIDUAL 1
RESIDUAL 2
AMMONIA 1
AMMONIA 2AMMONIA 3
Optimization Stories From The Field
▪ Solved HAA5 issues with ammonia feed changes to slow formation▪ LRAA 38 µg/L
▪ Some residual maintenance issues in parts of distribution system
▪ Investigation into residuals suggested northern edge impacted significantly▪ Low total chlorine residuals
▪ Elevated HAA5 levels
▪ Some odors observed
▪ Chlorine decay evaluations conducted
NEMRWSD – Tupelo, MS
54
Optimization Stories From The Field
▪ Large distribution system and multiple storage tanks
▪ Northern most tank area where most of low residuals occur▪ Total chlorine depleted less than
1.0 mg/L
▪ Chlorine decay analysis (bulk water in lab)▪ Define decay coefficient and
develop computer model
▪ Adjust model for piping decay along with bulk water decay
▪ Predict water age in distribution system
Tupelo, MS
55
Water
Plant
Optimization Stories From The Field
56
NEMRWSD – Tupelo, MSWater System A
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0
Decay Period, days
Fre
e C
hlo
rin
e R
em
ain
ing
, m
g/
L
Temp = 21oC
Raw data in
graphical
form
Optimization Stories From The Field
57
NEMRWSD – Tupelo, MSWater System A
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0
Decay Period, days
Fre
e C
hlo
rin
e R
em
ain
ing
, m
g/
L
Temp = 21oC
Exponential
trend line
selection and
overlay
Optimization Stories From The Field
58
NEMRWSD – Tupelo, MSWater System A
y = 1.800e-0.284x
R2 = 0.999
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0
Decay Period, days
Fre
e C
hlo
rin
e R
em
ain
ing
, m
g/
L
Temp = 21oC
Trend line
equation and R2
correlation
Optimization Stories From The Field
59
NEMRWSD – Tupelo, MSWater System A
y = 1.800e-0.284x
R2 = 0.999
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0
Decay Period, days
Fre
e C
hlo
rin
e R
em
ain
ing
, m
g/
L
Temp = 21oC
Identified
decay
coefficient
(kb) is 0.284
Optimization Stories From The Field
NEMRWSD – Tupelo, MS
60
• Conducted decay
analysis for Tupelo
water in laboratory• Initial residual 3.05
mg/L
• Observed total chlorine
residual for 21 days• Residual declined
below 1.9 mg/L
Optimization Stories From The Field
▪ Determine decay coefficient (k) from equation
Ct=Coe(-kt)
NEMRWSD – Tupelo, MS
61
Water System B
y = 2.7835e-0.0196x
R2 = 0.9442
1.7
1.8
1.9
2.0
2.1
2.2
2.3
2.4
2.5
2.6
2.7
2.8
2.9
3.0
3.1
0 2 4 6 8 10 12 14 16 18 20 22
Decay Period, days
To
tal
Ch
lori
ne R
em
ain
ing
, m
g/
L
Temp = 20oC
Optimization Stories From The Field
▪ Determine decay coefficient (k) from equation
Ct=Coe(-kt)
NEMRWSD – Tupelo, MS
62
Water System B
y = 2.7835e-0.0196x
R2 = 0.9442
1.7
1.8
1.9
2.0
2.1
2.2
2.3
2.4
2.5
2.6
2.7
2.8
2.9
3.0
3.1
0 2 4 6 8 10 12 14 16 18 20 22
Decay Period, days
To
tal
Ch
lori
ne R
em
ain
ing
, m
g/
L
Temp = 20oC
Identified
water decay
coefficient (kb)
is 0.0196
Optimization Stories From The Field
NEMRWSD – Tupelo, MS
63
NE Mississippi Regional Water Supply District
Tupelo, MS
Total Chlorine Decay Model
Temp 30oC (temp varies 7
oC to32
oC)
k 0.0392
Days 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21
3.20 3.08 2.96 2.85 2.74 2.63 2.53 2.43 2.34 2.25 2.16 2.08 2.00 1.92 1.85 1.78 1.71 1.64 1.58 1.52 1.46 1.41
3.10 2.98 2.87 2.76 2.65 2.55 2.45 2.36 2.27 2.18 2.10 2.02 1.94 1.86 1.79 1.72 1.66 1.59 1.53 1.47 1.42 1.36
3.00 2.88 2.77 2.67 2.57 2.47 2.37 2.28 2.19 2.11 2.03 1.95 1.88 1.80 1.73 1.67 1.60 1.54 1.48 1.43 1.37 1.32
2.90 2.79 2.68 2.58 2.48 2.38 2.29 2.20 2.12 2.04 1.96 1.89 1.81 1.74 1.68 1.61 1.55 1.49 1.43 1.38 1.33 1.27
2.80 2.69 2.59 2.49 2.39 2.30 2.21 2.13 2.05 1.97 1.89 1.82 1.75 1.68 1.62 1.56 1.50 1.44 1.38 1.33 1.28 1.23
2.70 2.60 2.50 2.40 2.31 2.22 2.13 2.05 1.97 1.90 1.83 1.76 1.69 1.62 1.56 1.50 1.44 1.39 1.33 1.28 1.23 1.19
2.60 2.50 2.40 2.31 2.22 2.14 2.06 1.98 1.90 1.83 1.76 1.69 1.63 1.56 1.50 1.45 1.39 1.34 1.28 1.24 1.19 1.14
2.50 2.40 2.31 2.22 2.14 2.06 1.98 1.90 1.83 1.76 1.69 1.63 1.56 1.50 1.44 1.39 1.34 1.28 1.24 1.19 1.14 1.10
2.40 2.31 2.22 2.13 2.05 1.97 1.90 1.82 1.75 1.69 1.62 1.56 1.50 1.44 1.39 1.33 1.28 1.23 1.19 1.14 1.10 1.05
2.90 2.79 2.68 2.58 2.48 2.38 2.29 2.20 2.12 2.04 1.96 1.89 1.81 1.74 1.68 1.61 1.55 1.49 1.43 1.38 1.33 1.27
2.80 2.69 2.59 2.49 2.39 2.30 2.21 2.13 2.05 1.97 1.89 1.82 1.75 1.68 1.62 1.56 1.50 1.44 1.38 1.33 1.28 1.23
2.70 2.60 2.50 2.40 2.31 2.22 2.13 2.05 1.97 1.90 1.83 1.76 1.69 1.62 1.56 1.50 1.44 1.39 1.33 1.28 1.23 1.19
2.60 2.50 2.40 2.31 2.22 2.14 2.06 1.98 1.90 1.83 1.76 1.69 1.63 1.56 1.50 1.45 1.39 1.34 1.28 1.24 1.19 1.14
2.50 2.40 2.31 2.22 2.14 2.06 1.98 1.90 1.83 1.76 1.69 1.63 1.56 1.50 1.44 1.39 1.34 1.28 1.24 1.19 1.14 1.10
2.40 2.31 2.22 2.13 2.05 1.97 1.90 1.82 1.75 1.69 1.62 1.56 1.50 1.44 1.39 1.33 1.28 1.23 1.19 1.14 1.10 1.05
2.30 2.21 2.13 2.05 1.97 1.89 1.82 1.75 1.68 1.62 1.55 1.50 1.44 1.38 1.33 1.28 1.23 1.18 1.14 1.09 1.05 1.01
2.20 2.12 2.03 1.96 1.88 1.81 1.74 1.67 1.61 1.55 1.49 1.43 1.38 1.32 1.27 1.22 1.18 1.13 1.09 1.05 1.01 0.97
2.10 2.02 1.94 1.87 1.80 1.73 1.66 1.60 1.54 1.48 1.42 1.37 1.31 1.26 1.21 1.17 1.12 1.08 1.04 1.00 0.96 0.92
2.00 1.92 1.85 1.78 1.71 1.64 1.58 1.52 1.46 1.41 1.35 1.30 1.25 1.20 1.16 1.11 1.07 1.03 0.99 0.95 0.91 0.88
1.90 1.83 1.76 1.69 1.62 1.56 1.50 1.44 1.39 1.34 1.28 1.24 1.19 1.14 1.10 1.06 1.02 0.98 0.94 0.90 0.87 0.83
1.80 1.73 1.66 1.60 1.54 1.48 1.42 1.37 1.32 1.27 1.22 1.17 1.13 1.08 1.04 1.00 0.96 0.93 0.89 0.86 0.82 0.79
1.70 1.63 1.57 1.51 1.45 1.40 1.34 1.29 1.24 1.20 1.15 1.11 1.06 1.02 0.98 0.94 0.91 0.87 0.84 0.81 0.78 0.75
1.60 1.54 1.48 1.42 1.37 1.32 1.26 1.22 1.17 1.12 1.08 1.04 1.00 0.96 0.92 0.89 0.86 0.82 0.79 0.76 0.73 0.70
1.50 1.44 1.39 1.33 1.28 1.23 1.19 1.14 1.10 1.05 1.01 0.98 0.94 0.90 0.87 0.83 0.80 0.77 0.74 0.71 0.69 0.66
1.40 1.35 1.29 1.24 1.20 1.15 1.11 1.06 1.02 0.98 0.95 0.91 0.88 0.84 0.81 0.78 0.75 0.72 0.69 0.67 0.64 0.62
1.30 1.25 1.20 1.16 1.11 1.07 1.03 0.99 0.95 0.91 0.88 0.85 0.81 0.78 0.75 0.72 0.69 0.67 0.64 0.62 0.59 0.57
1.20 1.15 1.11 1.07 1.03 0.99 0.95 0.91 0.88 0.84 0.81 0.78 0.75 0.72 0.69 0.67 0.64 0.62 0.59 0.57 0.55 0.53
1.10 1.06 1.02 0.98 0.94 0.90 0.87 0.84 0.80 0.77 0.74 0.72 0.69 0.66 0.64 0.61 0.59 0.57 0.54 0.52 0.50 0.48
1.00 0.96 0.92 0.89 0.86 0.82 0.79 0.76 0.73 0.70 0.68 0.65 0.63 0.60 0.58 0.56 0.53 0.51 0.49 0.48 0.46 0.44
Init
ial T
ota
l C
l 2, m
g/L
Optimization Stories From The Field
▪ Average water age less than 3 days▪ Southern areas less than 2 days
water age
Tupelo, MS
64
Water
Plant0.5 days
1.2 days
1.2 days
1.2 days
1.2 days
1.2 days
1.2 days
2.3 days
Optimization Stories From The Field
▪ Average water age less than 3 days▪ Southern areas less than 2 days
water age
▪ Northern areas increasing water age to 4.5 days
Tupelo, MS
65
Water
Plant0.5 days
1.2 days
1.2 days
1.2 days
1.2 days
1.2 days
1.2 days
2.3 days
4.3 days
4.5 days
4.5 days
Optimization Stories From The Field
▪ Average water age less than 3 days▪ Southern areas less than 2 days
water age
▪ Northern areas increasing water age to 4.5 days
▪ Baldwyn Tank (north) water age 22 days
▪ Installed PAX tank mixer to reduce water stagnation
▪ Within 1 day total chlorine residuals increased to 2.5 mg/L
▪ Reduced HAA5s 30% in Baldwyn Tank area from stagnant water
Tupelo, MS
66
Water
Plant0.5 days
1.2 days
1.2 days
1.2 days
1.2 days
1.2 days
1.2 days
2.3 days
4.3 days
4.5 days
4.5 days
22 days
Optimization Stories From The Field
6767