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Modeling Processes from Pipes to PlantTransformation of Wastewater in Collection Systems
Muriel Steele, Tom Johnson, Matthew Ward – CH2M
Jes Vollertsen – University of Aalborg & HV-Consult ApS
2
Modeling Processes from Pipes to Plant
• Background and motivation
• Sewer system modeling
• Impacts to WWTP modeling
• Potential applications of combined modeling
• Case study
• Conclusions
3
Background and motivation
4
Process Modeling in WWTPs
• Common practice for design and operation
• Used to:
– predict plant performance
– determine treatment capacity
– identify improvements to treatment processes
5
Influent Wastewater Characterization
• Important step in building a useful model
• Crucial to accurately predict
– biological nutrient removal
– biosolids production COD
Soluble COD
Truly Soluble Colloidal Non-biodegradable
Particulate COD
Biodegradable Inert
6
Changes in characterization
• Characteristics of the collection system assumed constant
– No change with system growth? Unlikely…
• Examples of characteristic changes
– Residential growth far from the treatment plant
– New industrial users
Soluble COD
Truly Soluble Colloidal Non-biodegradable
? ?
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Collection system impacts
• Many utilities operate separate departments for collections and treatment of wastewater
• Operations can unknowingly affect the other
• For example: chemical addition for odor control
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Sewer System Modeling and Impacts to WWTP Modeling
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WATS (Wastewater Aerobic/anaerobic Transformations in Sewers)
• Model development began in the 1990’s and focused on aerobic microbial transformations in gravity sewers
• Since then, the model has increased in complexity through the addition of
– More wastewater compounds
– New types of sewer networks
– Additional transformation processes
HV-Consult ApS
10
WATS
• Models several types of processes
– Biological
– Chemical
– Mass transport
HV-Consult ApS
Aerobic Transformations
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WATS
Anoxic Transformations
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WATS
Anaerobic Transformations
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Wastewater characterization for WWTP modeling –COD distribution
• WATS
– Fermentable substrates
– Fermentation products
– Hydrolysable substrate
• Fast, medium, slow hydrolysable
– Biomass
• Heterotrophic biomass in water
• Heterotrophic biomass in biofilm
• Sulfide forming biomass in water
• Sulfide forming biomass in biofilm
• Activated Sludge Model (ASM)
– Soluble Fermentable Substrates
– Soluble Fermentation Products
– Slowly Biodegradable Substrate
– Biomass
• Heterotrophic Organisms
• Autotrophic Organisms
• Phosphate Accumulating Organisms
– Inerts
• Soluble inerts
• Inert Particulates
14
Wastewater characterization for WWTP modeling –Other pertinent compounds
• WATS
– Sulfide
• Total and dissolved
– Iron
• Free iron and iron sulfide
– Phosphate
– Dissolved oxygen
– Nitrate
– Nitrite
– Ammonia+ammonium
• ASM
– Metal hydroxides
– Metal phosphates
– Inorganic phosphorus
– Polyphosphate
– Soluble Ammonia N
– Soluble Nitrate/Nitrite N
– Particulate nutrient fractions
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Wastewater characterization for WWTP modeling –Connecting WATS and Pro2D2
• Focus on characterization, not concentrations
– WATS and ASM characterization too different to be a one-to-one conversion
– Truly soluble COD fraction = Fermentable + fermentation products
– Colloidal COD fraction = Fast hydrolysable substrates
– Particulate COD = Medium + slow hydrolysable substrates
• Ongoing improvements in WATS will be incorporated into WATS/Pro2D2 link
– Example: Currently improving the iron mass balance within the WATS model
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Potential Applications of Combined Modeling
• Collection system changes
– Added residential or industrial users
• Odor management
– Oxygen or nitrate addition
– Iron salt addition
• Pump station operation
Individual User
Collection System
Pump Stations
Force/Gravity Mains
Treatment Plant
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Case study – New Force Main and Treatment Plant Modifications
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Case Study – Background and Methods
• Large municipality in the Western U.S.
• Adding a new pump station and force main
• Upgrading the receiving treatment plant
– Higher capacity
– Improved treatment performance
• Used existing force main and sampling data to calibrate WATS model
• Used calibrated model to make predictions about new force main
Individual User
Collection System
Pump Stations
Force/Gravity Mains
Treatment Plant
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WATS Model Calibration – Influent WW Characterization
Wastewater COD Fractionation Based on Sampling Results
Analysis WATS Parameter Calculation Value (mg COD/L)
Total COD (CODTOT)
Total COD 647.0
Dissolved COD (CODDIS)
214.0
Flocked/filtered COD (CODFF)
184.1
Volatile Fatty Acids (VFAs)
Fermentation Products (SA) Theoretical COD/VFA 137.8
Fermentable Substrate (SF) CODFF - SA 46.3Heterotrophic biomass in bulk water (XHw) CODTOT * 0.0365 23.6Sulfide-forming biomass in bulk water (XHsulf) 0Fast Hydrolysable Substrate (XSf) CODDIS - CODFF 29.9Medium Hydrolysable Substrate (XSf) (CODTOT – CODDIS – XHw) * 0.3 122.8Slowly Hydrolysable Substrate (XSf) (CODTOT – CODDIS – XHw) * 0.7 286.6
Other constituents measured: nitrogen (ammonia and nitrate), phosphorus (ortho-P), and hardness
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6
6.2
6.4
6.6
6.8
7
7.2
7.4
0
200
400
600
800
1000
1200
1400
6/5/2017 6/6/2017 6/7/2017 6/8/2017 6/9/2017 6/10/2017 6/11/2017 6/12/2017
pH
H2S
(ppm
)
H2S Run-Ave pH Run-Ave Flow (Diurnal Curve)
WATS Model Calibration – H2S gas and pH
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WATS Model Calibration – Diurnal Variations
0
10
20
30
40
12 AM 4 AM 8 AM 12 PM 4 PM 8 PM 12 AM
Flow
(mgd
)
Time of Day
5.50
6.00
6.50
7.00
7.50
12 AM 4 AM 8 AM 12 PM 4 PM 8 PM 12 AM
pH
Time of Day
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WATS Model Calibration
0
200
400
600
800
1000
1200
1400
0 6 12 18 24 30 36 42 48
H2S
(ppm
)
Time (hours)
Modeled Odalog Data
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Applying Calibrated Model to New Force Main
• Flow curve
– Based on pump station capacity
• Proposed Alignment
– 60% design
StationDistance
downstream of Pump Stn (ft)
Dissolved Sulfide (mg/L) H2Sg,eq (ppm)
15 + 61.85 172 0.01 0.431 + 00.00 1,715 0.13 16.148 + 08.00 3,380 0.39 51.550 + 76.29 3,800 0.42 56.093 + 00.00 7,713 1.23 181.4
115 + 73.77 9,903 1.63 245.0127 + 74.03 11,052 1.87 282.8174 + 33.26 15,858 2.81 431.3192 + 49.94 17,685 3.17 488.0221 + 70.20 19,858 3.74 580.0237 + 90.00 21,458 4.06 629.3255 + 71.05 23,858 4.39 681.3283 + 77.09 26,258 4.92 765.9317 + 00.00 29,458 5.53 863.6341 + 00.00 31,858 5.96 932.8429 + 81.19 41,258 7.51 1180.5430 + 80.00 41,503 7.53 1182.8484 + 40.79 46,258 8.45 1330.0490 + 90.00 47,338 8.55 1346.0528 + 00.00 51,058 9.16 1444.3558 + 60.00 54,158 9.66 1524.0559 + 50.85 54,958 9.88 1734.8
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Applying Calibrated Model to New Force Main
• Issues with high H2S gas at average conditions
• Even worse when diurnal variation considered
0
500
1000
1500
2000
2500
3000
0 6 12 18 24 30 36 42 48
H 2S
(ppm
)
Time (hours)
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Proposed H2S Mitigation Solution
• Oxygen injection
0
100
200
300
400
500
600
700
0
100
200
300
400
500
600
0 15000 30000 45000
DO
(mg/
L)
Elev
atio
n (ft
)
Distance Downstream of Pump Stn (ft)
Crown Elevation (ft) HGL, peak flow (ft)DO solubility, peak flow (mg/L) Average DO (mg/L) @ 127 mg/L doseDO (mg/L), 7AM @ 127 mg/L
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Alternative H2S Mitigation Solution
• Iron salts will be added to treatment plant for CEPT
• If added to collection system, may reduce oxygen demand
• Benefits to CEPT need to be verified before implementation
Flow, mgd 8 37.7
Ferric Addition at WWTP
O2 dose, mg/L 201.5 63
O2 dose, lb/d 13,452 19,820
Ferric Addition at Pump Station
O2 dose, mg/L 185 51
O2 dose, lb/d 12,350 16,045
O2 dose saved 8% 19%
27
Other Treatment Plant Implications
• Transformation of wastewater with oxygen injection is significant
– Oxygen contributes to heterotrophic growth in collection system
– Consumption of soluble COD significant
• Approximately 3,000 additional gallons per day of supplemental carbon needed to denitrification with oxygen injection
– ~$6,000 - $6,750 per day increase in treatment plant operation!
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Conclusions
• Combined collection system/treatment plant modeling is beneficial
• Allows identification of potential treatment issues or benefits from changes to the collection system
• Systems should be considered collectively to understand true life cycle costs
Individual User
Collection System
Pump Stations
Force/Gravity Mains
Treatment Plant
