Plant 2: 100.000 PE, online control of length of the aerated phase in place. Influent. Sand trap. Anaerobic tanks. Aeration tank. Aeration tank. Clarifiers. Effluent.
LCA and nutrient removal
Joris Roels, Tom Wambecq, Kris De Gussem, Alessio Fenu, Aquafin, Belgium Xavier Flores-Alsina, Peter Vanrolleghem ModelEAU, Canada
Introduction
• Online control for nutrient removal is standard practice at Aquafin (AQF) (Flanders) • Goal of online control at Aquafin = meeting the effluent consent at the lowest cost • Currently AQF has no stimulus to produce a cleaner effluent than strictly necessary since AQF doesn’t pay a levy for the residual pollution • A new methodology was assessed which sets as goal a reduction of the the footprint of wastewater treatment following a life cycle approach • For this purpose, calibrated, asm2d models were made of 3 full scale WWTP’s on which the two methodologies (costs respecting effluent consent versus lowest footprint) were compared
Neptune project, contract no 036845, FP6-2005-Global-4, SUSTDEV-2005-3.II.3.2
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Outline of the 3 plants
• Plant 1: 27.000 PE, limited online control already in place
O2
Influent
Sand trap
Intermittent Aeration
Aeration tank
O2
NO3
Clarifiers
Dsand enitrifying filters
NO3
Sludge dewatering
Effluent
Neptune project, contract no 036845, FP6-2005-Global-4, SUSTDEV-2005-3.II.3.2
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Outline of the 3 plants • Plant 2: 100.000 PE, online control of length of the aerated phase in place
NO3
Influent
Sand trap
Aeration tank
O2
Clarifiers
Anaerobic tanks Aeration tank O2
Effluent
Sludge dewatering Stormwater tanks
Neptune project, contract no 036845, FP6-2005-Global-4, SUSTDEV-2005-3.II.3.2
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Outline of the 3 plants • Plant 3: 270.000 PE, state of the art of online control at AQF
NO3 NH4
Aeration tank
O2
O2 Aeration tank Influent
Sand trap
Anaerobic tanks
O2 Aeration tank
PO4
O2 Aeration tank
Clarifiers
Effluent
Sludge dewatering Stormwater tanks
Neptune project, contract no 036845, FP6-2005-Global-4, SUSTDEV-2005-3.II.3.2
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Calibration Concentration of ammonium (mg/L)
Ammonium effluent 5 4 3 2 1 0
0
50
100
150
200
250
300
day
350
Nitrate effluent
Concentration of nitrate (mg/L)
10
8
6
4
2
0
0
50
100
150
200
250
300
350
day
Neptune project, contract no 036845, FP6-2005-Global-4, SUSTDEV-2005-3.II.3.2
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Calibration Power usage (Reality: 1680118 KwH) (model total: 1659549 KwH) other: 3.9% not modelled: 1.2% nitrate retour: 1.8% mixers: 2.7% heating: 5.4%
recirculation: 6.9% aeration: 39.1%
influent: 6.9%
dynasand: 10.4%
sludge line: 21.7%
Neptune project, contract no 036845, FP6-2005-Global-4, SUSTDEV-2005-3.II.3.2
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Comparison of optimisation strategies Meeting effluent consent at lowest cost = straigthforward Reducing footprint of WWTP’s • Impact is expressed as mPET: milli people equivalents targeted. 1 PE represents the environmental impact of 1 hypothetical person in a defined country and year. • Impact is composed of a number of impact categories such as global warming, eutrophication, acidification, ozone depletion, ecotoxicity, human toxicity, …. E.g. the EDIP97 methodology normalises the global warming impact of 1 PE to 8700 kg CO2-equivalents per year. • Data from Henrik Fred Larsen: Parameter Nitrogen Phosphorus Electricity consumption Sludge production Infrastructure FeCl3 40% dosing Sodium acetate dosing
Impact 37,23 mPET / kg N 269,2 mPET / kg P 0,12324 mPET / kWh 0,1 mPET / kg 37% DM sludge 0,127 mPET / m³ influent treated 2,611 mPET / kg 0,7781 mPET / kg NaOAc
Neptune project, contract no 036845, FP6-2005-Global-4, SUSTDEV-2005-3.II.3.2
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Impact reduction of wastewater treatment • Waste water treatment plants are lowering the ecological footprint (as expected..) LCA 8000 Kjeldahl Nitrogen Nitrate Phosphate Energy Sludge Infrastructure Chemical dosing
7000
LCA (in PET)
6000 5000 4000 3000 2000 1000 0
NoBefore WWTP
After WWTP
Neptune project, contract no 036845, FP6-2005-Global-4, SUSTDEV-2005-3.II.3.2
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Optimisation scenario’s • • • • •
Migration from manual to online control by installing extra online sensors Changing setpoints of existing controllers (NH4, SRT, O2, …) Alternative (rule based) control algorithms Changing position of existing sensors Increasing internal recycle pumping capacity
• For each plant roughly 2000 simulations were run
Neptune project, contract no 036845, FP6-2005-Global-4, SUSTDEV-2005-3.II.3.2
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Results / Conclusions Plant 1 Plant 2 Plant 3
Cost optimisation
Footprint optimisation
Costs*
-15 %
-10 %
Footprint
-3%
-7%
Costs*
-2%
0%
Footprint
- 13 %
- 22 %
Costs*
-7%
-2%
Footprint
-7%
- 11 %
* Sum of operational cost for electricity consumption, sludge disposal and chemical dosing
• • •
Cost optimisation leads to a cost reduction of 2 – 15 % and an impact reduction of 3 – 13 % Footprint optimisation leads to a cost reduction of 0 – 10 % and an impact reduction of 7 – 22 % Footprint optimisation leads to a cleaner effluent than the legally imposed quality, favours bio-P over chemical P removal and results into less NH4 in the effluent
Neptune project, contract no 036845, FP6-2005-Global-4, SUSTDEV-2005-3.II.3.2
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Conclusions
• • • • •
•
A reduction of footprint with 1 % leads to an increase of operational costs with 1 % Standardisation of footprint calculation is necessary (!) Optimisation towards footprint is very compatible with the way operators tend to manually control the plants Online control reduces operational costs and increases treatment efficiency A plant that is already (partly) controlled online can perform even better if the correct controller settings are applied. These correct settings vary from plant to plant even when layouts are similar since every plant has its own characteristic influent composition. Custom made controllers are necessary to achieve the best performance
Neptune project, contract no 036845, FP6-2005-Global-4, SUSTDEV-2005-3.II.3.2
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Acknowledgment
• This study was part of the EU Neptune project (Contract No 036845, SUSTDEV-2005-3.II.3.2), which was financially supported by grants obtained from the EU Commission within the Energy, Global Change and Ecosystems Program of the Sixth Framework (FP6-2005-Global-4)
Neptune project, contract no 036845, FP6-2005-Global-4, SUSTDEV-2005-3.II.3.2
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Work package 4 LCA and ICA Lluís Corominas, Xavier Flores-Alsina, Peter Vanrolleghem
Neptune project, contract no 036845, FP6-2005-Global-4, SUSTDEV-2005-3.II.3.2
Case study Neptune Simulation Benchmark • A2O plant sized using the Metcalf & Eddy design guidelines • The influent profile have been generated using phenomenological models including daily, weekly and seasonal variation (low C/N ratio) • The EAWAG ASM3 bio P and the double exponential velocity function of Takács are the main process models
Neptune project, contract no 036845, FP6-2005-Global-4, SUSTDEV-2005-3.II.3.2
Case study Evaluation of control strategies • Different combinations of controllers tested using the Neptune Benchmark • Comparison of strategies with and without chemical addition • Is the implementation of control reducing environmental impact? • Are the controllers based on the addition of chemicals the right solution to reduce environmental impact? (evaluation using LCA) DO controller
NO3- controller (Qintr_recycle)
NO3- controller (Qcarbon)
Chemical addition
PO43- controller (Qmetal)
OUR controller
NH4+ controller
OUR controller
NH4+ controller
OUR controller
NH4+ controller
TSS controller
TSS Vstorage controller controller
TSS controller
TSS controller
TSS controller
TSS controller
Neptune project, contract no 036845, FP6-2005-Global-4, SUSTDEV-2005-3.II.3.2
Results: dynamic profiles 7
5
Nitrate control (carbon addition)
A1 A3
12 10
NO3- (gN·m-3)
DO (g (-COD)·m-3)
6
14
DO control
A1 A2
4 3
8 6
2
4
1
2
0 240
0 240
242
244
246
248
250
252
254
256
258
260
242
244
246
A1 A9
14
Ammonia control (cascade)
A1 A7
250
252
254
256
258
260
258
260
time (days)
time (days)
8
248
12
Phosphate control (metal addition)
PO43- (g·m-3)
NH4+ (gN·m-3)
6
4
10 8 6 4
2
2
0 240
242
244
246
248
250
252
time (days)
254
256
258
260
0 240
242
244
246
248
250
252
254
time (days)
Neptune project, contract no 036845, FP6-2005-Global-4, SUSTDEV-2005-3.II.3.2 A1: NO CONTROL
256
Results: LCA evaluation DO, NH4+, NO3- (internal recycle) and TSS control
No Control A1 (No controller) 4.00 3.50 3.00
mPET*year/m3
2.50 2.00 1.50 1.00 0.50 0.00 Induced impacts Energy
Infrastructure
Avoided impacts Sludge
Chemicals
Total nutrients
DO + NH4+ + TSS + NO3- and PO43- controlled by adding external carbon source
DO + NH4+ + TSS + PO43- controlled by metal addition
Avoided impact: Influent – effluent nutrient impact Induced impact: Effluent nutrient + Electricity + Sludge + Infr + chemicals
Neptune project, contract no 036845, FP6-2005-Global-4, SUSTDEV-2005-3.II.3.2
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Conclusions • The implementation of control leads to an increase of the avoided impact and a decrease in the induced impact • The most environmentally friendly strategies are the ones that include metal and carbon addition as they induce a significant reduction of nitrate and phosphorus in the effluent • LCA gives better results for strategies that improve nutrient removal vs those that reduce energy consumption
Neptune project, contract no 036845, FP6-2005-Global-4, SUSTDEV-2005-3.II.3.2
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Acknowledgements This research is supported by the Canada Research Chair in Water Quality Modeling and a NSERC Special Research Opportunities grant as part of the Canadian contribution to the European Union 6th framework project NEPTUNE. This study was part of the EU Neptune project (Contract No 036845, SUSTDEV-2005-3.II.3.2), which is financially supported by grants obtained from the EU Commission within the Energy, Global Change and Ecosystems Program (FP6-2005-Global-4).
Canada Research Chair in Water Quality Modeling
Neptune project, contract no 036845, FP6-2005-Global-4, SUSTDEV-2005-3.II.3.2
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