TY - JOUR

T1 - Mathematical modelling of greenhouse gas emissions from membrane bioreactors: A comprehensive comparison of two mathematical models

AU - Cosenza, Alida

AU - Mannina, Giorgio

AU - Mannina, Giorgio

AU - Ekama, George

PY - 2018

Y1 - 2018

N2 - This paper compares two mathematical models (Model I and Model II) to predict greenhouse gases emission from a University Cape Town (UCT) – membrane bioreactor (MBR) plant. Model I considers N2O production only during denitrification. Model II takes into account the ammonia-oxidizing bacteria (AOB) formation pathways for N2O. Both models were calibrated adopting real data. Model comparison was performed in terms of (i) sensitivity analysis (ii) best fit and (iii) model prediction uncertainty. On average 6% of factors of Model I and 9% of Model II resulted to be important. In terms of best fit, Model II had a better capability of reproducing the measured data. The average efficiency related to the N2O model outputs was equal to 0.33 and 0.38 for Model I and Model II, respectively. On average, 73% (Model I) and 86% (Model II) of measured data lay inside the uncertainty bands.

AB - This paper compares two mathematical models (Model I and Model II) to predict greenhouse gases emission from a University Cape Town (UCT) – membrane bioreactor (MBR) plant. Model I considers N2O production only during denitrification. Model II takes into account the ammonia-oxidizing bacteria (AOB) formation pathways for N2O. Both models were calibrated adopting real data. Model comparison was performed in terms of (i) sensitivity analysis (ii) best fit and (iii) model prediction uncertainty. On average 6% of factors of Model I and 9% of Model II resulted to be important. In terms of best fit, Model II had a better capability of reproducing the measured data. The average efficiency related to the N2O model outputs was equal to 0.33 and 0.38 for Model I and Model II, respectively. On average, 73% (Model I) and 86% (Model II) of measured data lay inside the uncertainty bands.

KW - Greenhouse gases; N2O modelling; Nutrient removal; WWTP; Nitrous Oxide; South Africa; Bioreactors; Greenhouse Gases; Models

KW - Sustainability and the Environment; Waste Management and Disposal

KW - Theoretical; Bioengineering; Environmental Engineering; Renewable Energy

KW - Greenhouse gases; N2O modelling; Nutrient removal; WWTP; Nitrous Oxide; South Africa; Bioreactors; Greenhouse Gases; Models

KW - Sustainability and the Environment; Waste Management and Disposal

KW - Theoretical; Bioengineering; Environmental Engineering; Renewable Energy

UR - http://hdl.handle.net/10447/325915

UR - http://www.elsevier.com/locate/biortech

M3 - Article

VL - 268

SP - 107

EP - 115

JO - Bioresource Technology

JF - Bioresource Technology

SN - 0960-8524

ER -