urban water management and environmental engineering ... · m. sc. pascal kosse energy balance and...

Energy balance and greenhouse gas emissions of municipal wastewater treatment systemsM. Sc. Pascal Kosse | Dr.-Ing. Manfred Lübken | Prof. Dr.-Ing. habil. Marc Wichern

wwtp „Bochum Ölbachtal“ © Ruhrverband

26th August 2015

Urban Water Management and Environmental Engineering

2M. Sc. Pascal Kosse Energy balance and greenhouse gas emissions of municipal wastewater treatment systems26.08.15

RUHR-UNIVERSITÄT BOCHUM | Urban Water Management and Environmental Engineering

Adaption of existing infrastructures to the already inevitable consequences of climate change. Shift of rainfalls from summer to winter and higher temperatures lead to

enhanced vaporization → Less water for dilution of wwtp effluents

Flood events

Obligatory reduction of greenhouse gases for the framework of a sustainable wastewater management (Mitigation).

Mitigation measures contribute to a lower carbon footprint of a wastewater treatment plant → lower carbon taxes.

Understanding the production pathways for greenhouse gases will help to develop early warning systems and operational strategies to avoid greenhouse gas emissions

Motivation



The primary anthropogenic greenhouse gases of concern are carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O).

Global Warming Potential (GWP) expresses the individual effect of each gas as an equivalent mass of carbon dioxide over a timeframe of 100 years.

GWP compiles the length of time that a gas remains in the atmosphere & the gas’s unique ability to absorb energy

GWP (CH4) = 25, GWP (N2O) = 298

Greenhouse gases of concern

© World Nature Organization (WNO)



Influent

Denitrification (anoxic)

Nitrification (aerobe)

Secondary sedimentation

tank

Sludge thickening

Aerated grit and grease chamber

Screen

Grit

Excess sludge (secondary sludge)

Primary sedimentation

tank

Prim

ary

sludge

Sludge digester

DewateringSewage to incineration

Gre

ase

Return sludge

Scre

enin

gs

CH4 CO2CH4 CO2

CH4N2OCH4N2O CO2

CH4

CH4

CH4

N2O CO2

CH4 CO2

Fig. 1 Schematic overview about main greenhouse gas emissions sources at wastewater treatment plant level.

Greenhouse gases of concern



The emission is attributed to the treatment process itself (direct emission)and the energy consumption of the wastewater treatment plant (indirect emission).

Indirect emissions: aeration power, pumping power, heating power, consumption of fossil fuels, dosing of chemicals

Direct emissions: aerobic biological oxidation of organic matter and endogenous respiration

COHNSOrganic matter

+ O2 + NutrientsBacteria

𝐂𝐎𝟐 + NH3 + C5H7NO2

C5H7NO2Cell mass composition

+ O2Bacteria

𝟓𝐂𝐎𝟐 + 2H2O + NH3 + energy

Carbon dioxide (CO2)



Carbon dioxide (CO2)

Influent 147 g CO2 ∙ pe-1 ∙ d-1

Effluent 18 g CO2 ∙ pe-1 ∙ d-1

Sewage sludge 44 g CO2 ∙ pe-1 ∙ d-1

Stripping 85 g CO2 ∙ pe-1 ∙ d-1

Nitrification, denitrification, phosphorous precipitation

15 g CO2 ∙ pe-1 ∙ d-1

∑ 100 g CO2 ∙ pe-1 ∙ d-1 or 36.5 kg CO2 ∙ pe-1 ∙ a-1

Energy consumption 35 kWh ∙ pe-1 ∙ a-1

Specific emissions 0.62 kg CO2 ∙ kWh-1 → 22 kg CO2 ∙ pe-1 ∙ a-1

∑ 58.5 kg CO2 ∙ pe-1 ∙ a-1

Table 1 Exemplary calculation of CO2 emissions for a typical wwtp (Kapp 1991).

Ambition of the EU: Cars produce max. 120 g ∙ km-1

One single person in one car could drive 487.5 km



Methane is either emitted from a wwtp after it enters the plant via stripping from the incoming wastewater, or after it is formed at the plant itself

Dissolved methane (?): Anaerobic digestion of the surplus sludge → Dewatering of digested sludge → Reject water → Stripped from aeration tanks

𝐂𝐇𝟒 → CH3OH → HCHO → HCOOH → 𝐂𝐎𝟐 + H2O

Further sources at wwtp

Sludge thickeners

Storage tanks

Surface diffusion from sludge leaving the wwtp (anaerobic biodegradation)

Methane (CH4)



Stratified sewer biofilms: (1) fermentative heterotrophs (2) sulphate-reducing bacteria (3) methanogenic archaea

Table 2 Sulphate-reducing and methanogenic reactions in the sewer system.

Reactions

FermentationC6H12O6 + 2H2O → 𝟐𝐂𝐇𝟑𝐂𝐎𝐎𝐇+ 2CO2 + 4H+

C6H12O6 + 2H2 → 2CH3CH2COOH + 2H2OCH3CH2COOH + 2CO2 → 𝐂𝐇𝟑𝐂𝐎𝐎𝐇+ CO2 + 3H2

Sulphate-reducing bacteria(SRB)

𝐀𝐜𝐞𝐭𝐚𝐭𝐞− + 𝐒𝐎𝟒𝟐− → 𝟐𝐇𝐂𝐎𝟑

− + 𝐇𝐒−

Propionate− +3

4SO4

2− → CH3COO− + HCO3

− +3

4HS− +

1

4H+

Butyrate− +1

2SO4

2− → 2CH3COO− +

1

2HS− +

1

2H+

Lactate− +1

2SO4

2− → Acetate− + HCO3− +

1

2HS−

Methanogens4H2 +𝐇𝐂𝐎𝟑

− + H+ → 𝐂𝐇𝟒 + 3H2O𝐀𝐜𝐞𝐭𝐚𝐭𝐞− + H2O → 𝐂𝐇𝟒 + HCO3

−

Homoacetogenesis4H2 + 𝟐𝐇𝐂𝐎𝟑

− + H+ → 𝐀𝐜𝐞𝐭𝐚𝐭𝐞− + 4H2O

Lactate− → 11

2Acetate− +

1

2H+

Methane (CH4)



Table 3 Methane emissions reported in full-scale studies.

Wastewater treatment plant / unit

Quantity kgmethane ∙ kginfluent COD-1 [%] Reference

NitrificationColeshill wwtp, UK

0.3 – 24 g ∙ h-1

(668 kg ∙ a-1)0.07 (from removed COD) Aboobakar et al. 2014

Coleshill wwtp, UK 14,000 CO2-eq ∙ a-1 0.07 (from removed COD) Aboobakar et al. 2014

Sewer20 – 120 mgCOD ∙ L-1

40 – 250 t ∙ a-1 ./. Guisasola et al. 2008, 2009

Durnham wwtp, USA(grit removal, primary settling,aeration tanks, secondary settling)

39 g ∙ person-1 ∙ a-1

(35,698 gCO2 ∙ person-1 ∙ a-1)0.34 Czepiel et al. 1993

Kralingseveer wwtp, Netherlands 306 g ∙ person-1 ∙ a-1 1.13 Daelman et al. 2012

Kralingseveer wwtp, Netherlands11 g ∙ kgCOD, influent

-1 1.10 Daelman et al. 2013

Avedøre wwtp, Denmark 4.99 – 92.3 kg ∙ h-1 ./. Yoshida et al. 2014

Methane (CH4)



Is assumed to be formed via (1) heterotrophic denitrification (2) autotrophic nitrification (3) nitrifier denitrification (4) “Anammox”

NA

R

cNor/qNorNirS/NirK

unknown

cNorNirKHAOAMO

HZS

NXR

NA

R

NirS

NirK

NH4+ NH2OH NO2

- N2ONO

NO3-

N2O

NO2- N2ONO N2

HA

O

NXR

N2H4

HD

H

NO

cNo

r

HZS

Fig. 2 Nitrous oxide emissions during nitrification, nitrifier denitrification, nitrate ammonification and denitrification. AOB (red), ammonia oxidizing bacteria; NOB (green), nitrite oxidizing bacteria; anammox (orange); denitrifiers (black).

Nitrous oxide (N2O)



Area/Volume ratio, aeration pattern, HRT

Dissolved oxygen (DO) concentration: DO < 1 mg ∙ L-1 N2O emission (Nitrification) N2Omax DO = 0.4 mg ∙ L-1 & N2Omin DO = 2.0 mg ∙ L-1 (Nitrification)

Temperature and salinity

Fig. 3 Oxidation ditches at wwtp “Düsseldorf (left picture) and “Bochum Ölbachtal” (right picture).

Factors affecting N2O stripping



4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 10.0

10

100

1000

Zone 1

FA inhibition

to Nitrobacter &

Nitrosomonas

Zone 4

FNA inhibition

to Nitrobacter

Zone 2

FA inhibition

to Nitrobacter

FA 0.1 FA 1 FA 10 FA 150 FNA 0.2 FNA 2.8

pH

HN

O2-N

& N

O2-N

[m

g L

-1]

Zone 3

Complete nitrification

10

100

1000

HN

O2-N

& N

H4-N

[m

g L

-1]

Fig. 4 Boundary conditions of free ammonia and free nitrous acid inhibition to nitrifying organisms. FA = free ammonia, FNA = free nitrous acid.

COD/N ratio > 4, “Ölbachtal” COD/N = 10.34 (march 2015)

pH has a minor effect on N2O emissions

Factors affecting N2O stripping



N2O emission(% of N-influent)

Remarks Reference

0.035 – 0.05 Emitted from aerated areas; low fluxes at non-aerated areas Czepiel et al. 1995

0.001 – 0.04 Dependent on COD:N ratio Benckiser et al. 1996

0.01 – 0.08Emission decreased with shorter aeration periods Kimochi et al. 1998

2.3Emission increased with decreasing oxygen concentration (aerated stage) and increasing nitrite concentration (anoxic stage)

Kampschreur et al. 2008b

0.6 – 25 Correlation between N2O and nitrite accumulation Foley et al. 2010

0.003 – 2.59 Aerobic zones contributed more N2O fluxes than anoxic zones Ahn et al. 2010

0.07 – 0.15 Aerobic period was the main source of N2O emissions Rajagopal & Béline 2011

2.2 – 8.2N2O emission decreased with decrease of COD:NN2O emission decreased with increase in DO level

Quan et al. 2012

0.02 – 2.6 Emitted from secondary clarifiers Mikola et al. 2014

Table 4 N2O emissions from full-scale wastewater treatment plants. Selected publications.

Nitrous oxide (N2O)



Simulation of N2O emissions at full-scale level using an extended ASM3 model.

The potential of N2O and CH4 stripping during wastewater treatment using the salting-out approach.

Temperature dependency of N2O production pathways using stable 15N and 16O isotopes (SBR approach).

Research aims in Future Water



Model Reference

ASM1 Samie et al., 2011

ASM Mampaey et al., 2013; Ni et al., 2011; Snip et al, 2014

ASMN Corominas et al., 2012; Snip et al., 2014

ASMG1 Guo et al., 2012; Guo & Vanrolleghem, 2014

ASM3 (extended) Project “NoNitriNox”

BSM1 Snip et al., 2014

BSM2Flores-Alsina et al., 2011, 2014; Guo et al., 2012; Jeppsson et al., 2007; Nopens et al., 2010; Sweetapple et al., 2013, 2014a, 2014b; Volcke et al., 2007

BSM2G Corominas et al., 2012; Flores-Alsina et al., 2014

Bridle (static approach) Corominas et al., 2012; Flores-Alsina et al., 2011; Monteith et al., 2005

Table 5 Modelling frameworks for the simulation of GHG.

No validated modeling framework exist for full-scale wwtp

Modeling of greenhouse gases



ASM 1mCOD, nitrogen

ASM 1 (1987)COD, nitrogen13 fractions8 processes

ASM 2 (1995)COD, nitrogen, phosphorous

19 fractions19 processes

ASM 2d (1999)COD, nitrogen, phosphorous


ASM 3 (1999)COD, nitrogen, phosphorous


ASM 3 + EAWAG biop (2001)COD, N, P


ADM1 (2002)Anaerobic


Models of the IWA (International Water Association)

Fig. 5 Evolution of ASM modeling approaches.



Process

Compounds

Process RateXB SS SO

Growth of heterotrophic

biomass1 −

1

Y−1 − Y

Yμ ∙

SSKS ∙ SS

∙ XB

Decay of biomass −1 0 −1 b ∙ XB

ASM3 & Main principles of IWA models

Table 6 Formalized description of models in a Petersen-Matrix. X = particulate, S = soluble.

P1: Hydrolysis P2: Aerobic storage P3: Anoxic storage P4: Aerobic growth P5: Anoxic growth P6: Aerobic endogenous respiration of

heterotrophs P7: Anoxic endogenous respiration of

heterotrophs

P8: Aerobic respiration of XSTO P9: Anoxic respiration of XSTO P10: Nitrification P11: Aerobic endogenous respiration

of autotrophs P12: Anoxic endogenous respiration of

autotrophs P13: Aeration



Experience and expertise in mathematical modelling

Research topics we address using mathematical modeling approaches Wastewater

Sewage sludge

Co-fermentation

Manure

Renewable raw materials (NawaRo)

Micropollutants

Aerobic granules

Microbial Fuel Cells (MFC) at wwtp level

Separation of material flows

Water bodies

Soil filters

Storm water treatment and disposal




„Einsatz und Anpassung anerkannter Simulationsmodelle für verschiedene Klimazonen als Beitrag zur effizienten, kostengünstigen Bemessung und Betriebsoptimierung von Abwasserreinigungsanlagen“ (BMBF)

„Simulation von Belebungsanlagen mit den Modellansätzen ASM sowie Simulation von Anaerobanlagen und Teichanlagen“ (Teilprojekt C.1.1) (BMBF) → ASM

„Einsatz von mathematischen Prozessmodellen zur Optimierung, Stabilisierung und Regelung des anaeroben Abbauprozesses von pflanzlicher Biomasse“ (BMBF)→ ADM1

„Intensivierung des anaeroben Biomasseabbaus zur Methanproduktion aus nachwachsenden Rohstoffen – Modellierung und Prozesssteuerung, Anlagenbetrieb und mikrobiologische Analytik“ (BMBF) → ADM1



ADM1Lübken M., Kosse P., Koch, K., Gehring, T., Wichern, M., 2015. Influent fractionation for modeling continuous anaerobic digestion processes In: Georg Gruebitz et al., Biogas Science and Technology, Springer International Publishing (available 14th

September 2015)

ADM1Kosse P., Lübken M., Wichern M., 2015. Microalgal-derived biomethanization and biohydrogen production – A review of modeling approaches In: Ales Prokop et al., Algal Biorefineries Vol. 2, Springer International Publishing

ADM1Lübken M., Koch K., Gehring T., Horn H., Wichern M., 2015. Parameter estimation and long-term process simulation of a biogas reactor operated under trace elements limitation, Applied Energy (142), pp. 352 - 360

ASM3Gehring T., Silva J. D., Kehl O., Castilhos Jr. A. B., Costa R. H. R., Uhlenhut F., Alex J., Horn H., Wichern M., 2010. Modelling waste stabilization ponds with extended version of ASM3. Water Sci. Technol. 61 (3), pp. 713 - 720


ASM3 bio-PWichern M., Lübken M., Blömer R., Rosenwinkel K.-H.,2003. Efficiency of the Activated Sludge Model No. 3 for German wastewater on six different WWTPs. Water Sci. Technol. 47 (11), pp. 211 - 218

ADM1, ASM3, ASM3 bio-P AQUASIM, RWQM No.1, Monte Carlo method,

sensitivity analysis, parameter fitting, genetic algorithms

Between 2005 – 201514 papers

16 conference manuscripts9 book chapters

TextbookWichern, M., 2010. Simulation biochemischer Prozesse in der Siedlungswasserwirtschaft: Lehrbuch für Studium und Praxis. Deutscher Industrieverlag. ISBN-10: 3835631799



Fig. 6 Basic ASM3 model in SIMBA# water.

Simulation of WWTPs using SIMBA# water

Fig. 8 COD influent fractionation.

Raw data has to be checked for mass balances (C, N, P, Q). Backbone for modeling!



Fig. 7 ASM3 biop model in SIMBA# water for wwtp Wesel. Excerpt from the Master thesis by Arne Steinkamp (2015).

Modeling wwtp Wesel

400 450 500 550 600 650 700

0.0

0.5

1.0

1.5

15

20

25

30

35

40

45

Concentr

ation [g m

-3]

Time [d]

COD measured COD simulated

N2O simulated



State of the art: FTIR (Fourier Transform Infrared Spectroscopy) About 60.000 € per device

Not suitable for conventional wwtp (open system)

Inspired by Daelman et al. 2012 and Weisenberger & Schumpe 1996

The solubility of gases in water depends on temperature, pressure, polarity and salinity.

Quantification of GHG – A salting-out approach

Fig. 8 FTIR measurements at wwtp “Bochum Ölbachtal”. Taken from project thesis Karina Kraus, UTRM (RUB).



Fig. 10 The solubility of N2O in wastewater on basis of salinity and temperature.


0 1 2 3 4 5 6 7

0.0

0.5

1.0

1.5

2.0

2.5 0 °C

5 °C

10 °C

15 °C

20 °C

25 °C

30 °C

35 °CSolu

bili

ty [g L

-1]

c NaCl [mol L-1]

Fig. 9 Chemical structures and dipole moments of CO2(non-polar), CH4 (non-polar) and N2O (polar). Water uses dipole-dipole forces to dissolve the gases (hydrate shell). Water uses ion-dipole forces to dissolve salts (hydrate shell). Ion-dipole forces are stronger than dipole-dipole forces.



Table 7 Comparison of the salting-out effect of NaCl and NaH2PO4. Solubilities have been calculated using Henry’s law constants (at 293.15 K) of 3.3 ∙ 10-4 mol ∙ m-3 ∙ Pa-1 (CO2), 1.56 ∙ 10-5 mol ∙ m-3 ∙ Pa-1 (CH4) and 2.80 ∙ 10-4 mol ∙ m-3 ∙ Pa-1 (N2O). Sol = solubility. Pressure = 1019 hPa.

Agent Solubility [g ∙ L-1] c [mol ∙ L-1]

Sol-Gas without

salt addition

[g ∙ L-1]

Sol-Gas after salt

addition

[mg ∙ L-1]

Gas left in

solution [%]

Car

bo

n d

ioxi

de

(CO

2)

NaH2PO4 850 7.08

1.70

22.89 1.35

NaCl 359 6.14 333.64 19.65

Me

than

e (

CH

4)

NaH2PO4 850 7.08

0.0255

0.09 0.36

NaCl 359 6.14 2.82 11.06

Nit

rou

s o

xid

e (

N2O

)

NaH2PO4 850 7.08

1.26

9.17 0.73

NaCl 359 6.14 189.22 15.06

Selection of salting-out agent




Fig. 11 Experimental setup. Gas syringe (total volume 100 mL), 100 mL Schott flask, collecting bag with PTFE septum, 50 mL sample volume. Clarus 580 GC, PerkinElmer, Inc., Waltham, USA.



Results from N2O method development (DIN 38 402 part 51)

Mandel's fitting test for mathematical verification of linearity Calibration using 10 different concentrations

If test-value ≤ F-value (99 %) → linearity

If test-value (TF) ≥ F-value (99 %) → no linearity (evidence for a statistical outlier)

Variance homogeneity test 10 measurements of the lowest and highest concentration

test-value ≤ F-value (95 %) → okay! (Variances are similar)

Further characteristic values Limit of detection, quantification



1 2 3 4 5 6 7 8 9 10 11 12

0.00

0.25

0.50

0.75

1.00

1.25

1.50

N2O

[g

L

-1]

Attempts

NaCl NaH2PO

4

1.24

Fig. 12 Retrieved N2O concentrations using NaCl and NaH2PO4. Excerpt from Bachelor thesis by Kristin Lüdiger (2015).

Results from N2O method development



Outlook

Finalization of the method development for GHG quantification using the salting-out approach and ultrasound. Improvement on equipment (GC-MS)

Ultrasound approach

Method development according to DIN 38 402 part 51

Development of a ASM3 model in SIMBA# water that is suitable for full-scale applications. If possible using FTIR data from Helsinki Viikinmäki wastewater treatment plant



References (I)

Aboobakar, A., Jones, M., Vale, P., Cartmell, E., Dotro, G., 2014. Methane emissions from aerated zones in a full-scale nitrifying activated sludge treatment plant. Water Air & Soil Pollution 225 (1)

Ahn, J.H., Kim, S., Park, H., Rahm, B., Pagilla, K., Chandran, K., 2010. N2O emissions from activated sludge processes, 2008−2009: Results of a national monitoring survey in the United States. Environmental Science & Technology 44 (12), 4505–4511.

Benckiser, G., Eilts, R., Linn, A., Lorch, H.-J., Sümer, E., Weiske, A., Wenzhöfer, F., 1996. N2O emissions from different cropping systems and from aerated, nitrifying and denitrifying tanks of a municipal waste water treatment plant. Biology and Fertility of Soils 23 (3), 257–265.

Corominas, L., Flores-Alsina, X., Snip, L., Vanrolleghem, P.A., 2012. Comparison of different modeling approaches to better evaluate greenhouse gas emissions from whole wastewater treatment plants. Biotechnol. Bioeng. 109 (11), 2854–2863.

Czepiel, P., Crill, P., Harriss, R., 1995. Nitrous oxide emissions from municipal wastewater treatment. Environmental Science & Technology 29 (9), 2352–2356.

Czepiel, P.M., Crill, P.M., Harriss, R.C., 1993. Methane emissions from municipal wastewater treatment processes. Environmental Science & Technology 27 (12), 2472–2477.

Daelman, M R J, van Voorthuizen, E M, van Dongen, L G J M, Volcke, E I P, van Loosdrecht, M C M, 2013. Methane and nitrous oxide emissions from municipal wastewater treatment - results from a long-term study. Water Science & Technology 67 (10), 2350–2355.

Daelman, M.R., van Voorthuizen, Ellen M., van Dongen, Udo G.J.M., Volcke, E.I., van Loosdrecht, Mark C.M., 2012. Methane emission during municipal wastewater treatment. Water Research 46 (11), 3657–3670.

Flores-Alsina, X., Arnell, M., Amerlinck, Y., Corominas, L., Gernaey, K.V., Guo, L., Lindblom, E., Foley, J., Haas, D. de, Yuan, Z., Lant, P., 2010. Nitrous oxide generation in full-scale biological nutrient removal wastewater treatment plants. Water Research 44 (3), 831–844.

Gehring T., Silva J. D., Kehl O., Castilhos Jr. A. B., Costa R. H. R., Uhlenhut F., Alex J., Horn H., Wichern M., 2010. Modelling waste stabilization ponds with extended version of ASM3. Water Sci. Technol. 61 (3), pp. 713 – 720.



Guisasola, A., Haas, D. de, Keller, J., Yuan, Z., 2008. Methane formation in sewer systems. Water Research 42 (6-7), 1421–1430.

Guisasola, A., Sharma, K.R., Keller, J., Yuan, Z., 2009. Development of a model for assessing methane formation in rising main sewers. Water Research 43 (11), 2874–2884.

Guo, L., Porro, J., Sharma, K.R., Amerlinck, Y., Benedetti, L., Nopens, I., Shaw, A., Van Hulle, S. W. H., Yuan, Z., Vanrolleghem, P.A., 2012. Towards a benchmarking tool for minimizing wastewater utility greenhouse gas footprints. Water Science & Technology 66 (11), 2483.

Guo, L., Vanrolleghem, P.A., 2014. Calibration and validation of an activated sludge model for greenhouse gases no. 1 (ASMG1): prediction of temperature-dependent N2O emission dynamics. Bioprocess Biosyst Eng 37 (2), 151–163.

Jeppsson, U., Pons, M.-N., Nopens, I., Alex, J., Copp, J.B., Gernaey, K.V., Rosen, C., Steyer, J.-P., Vanrolleghem, P.A., 2007. Benchmark simulation model no 2: general protocol and exploratory case studies. Water Science & Technology 56 (8), 67.

Kampschreur, M.J., van der Star, Wouter R.L., Wielders, H.A., Mulder, J.W., Jetten, M.S., van Loosdrecht, Mark C.M., 2008b. Dynamics of nitric oxide and nitrous oxide emission during full-scale reject water treatment. Water Research 42 (3), 812–826.

Kapp, H., 1991. Beitrag der Abwasserbehandlung zur CO2-Belastung der Umwelt. In: Umweltbeeinflussung durch Abwasserbehandlungsanlagen. Stuttgarter Berichte zur Siedlungswasserwirtschaft, Band 114, S. 109 – 120.

Kimochi, Y., Inamori, Y., Mizuochi, M., Xu, K.-Q., Matsumura, M., 1998. Nitrogen removal and N2O emission in a full-scale domestic wastewater treatment plant with intermittent aeration. Journal of Fermentation and Bioengineering 86 (2), 202–206.

Kosse P., Lübken M., Wichern M., 2015. Microalgal-derived biomethanization and biohydrogen production – A review of modeling approaches In: Ales Prokop et al., Algal Biorefineries Vol. 2, Springer International Publishing.

Lübken M., Gehring T., Wichern M., 2010. Microbiological fermentation of lignocellulosic biomass: Current state and prospects of mathematical modeling, Appl Microbiol Biotechnol (85), pp. 1643 – 1652.

Lübken M., Koch K., Gehring T., Horn H., Wichern M., 2015. Parameter estimation and long-term process simulation of a biogas reactor operated under trace elements limitation, Applied Energy (142), pp. 352 – 360.

References (II)



Mampaey, K.E., Beuckels, B., Kampschreur, M.J., Kleerebezem, R., van Loosdrecht, M. C.M., Volcke, E.I., 2013. Modelling nitrous and nitric oxide emissions by autotrophic ammonia-oxidizing bacteria. Environmental Technology 34 (12), 1555–1566.

Mikola, A., Heinonen, M., Kosonen, H., Leppänen, M., Rantanen, P., Vahala, R., 2014. N2O emissions from secondary clarifiers and their contribution to the total emissions of the WWTP. Water Science & Technology 70 (4), 720.

Monteith, H.D., Sahely, H.R., MacLean, H.L., Bagley, D.M., 2005. A rational procedure for estimation of greenhouse-gas emissions from municipal wastewater treatment plants. wer 77 (4), 390–403.

Ni, B.-J., Ruscalleda, M., Pellicer-Nàcher, C., Smets, B.F., 2011. Modeling nitrous oxide production during biological nitrogen removal via nitrification and denitrification: Extensions to the general ASM models. Environ. Sci. Technol. 45 (18), 7768–7776.

Nopens, I., Benedetti, L., Jeppsson, U., Pons, M.-N., Alex, J., Copp, J.B., Gernaey, K.V., Rosen, C., Steyer, J.-P., Vanrolleghem, P.A., 2010. Benchmark Simulation Model No 2: finalisation of plant layout and default control strategy. Water Science & Technology 62 (9), 1967.

Nopens, I., Porro, J., Shaw, A., Snip, L., Vanrolleghem, P.A., Jeppsson, U., 2014. Balancing effluent quality, economic cost and greenhouse gas emissions during the evaluation of (plant-wide) control/operational strategies in WWTPs. Science of The Total Environment 466-467, 616–624.

Quan, X., Zhang, M., Lawlor, P.G., Yang, Z., Zhan, X., 2012. Nitrous oxide emission and nutrient removal in aerobic granular sludge sequencing batch reactors. Water Research 46 (16), 4981–4990.

Rajagopal, R., Béline, F., 2011. Nitrogen removal via nitrite pathway and the related nitrous oxide emission during piggery wastewater treatment. Bioresource Technology 102 (5), 4042–4046.

Samie, G., Bernier, J., Rocher, V., Lessard, P., 2011. Modeling nitrogen removal for a denitrification biofilter. Bioprocess Biosyst Eng 34 (6), 747–755.

References (III)



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urban water management and environmental engineering ... · m. sc. pascal kosse energy balance and...

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