title: Waste settlement in bioreactor landfill models.
abstract: Prediction of landfill settlement is one of the important parameters that affects the design and maintenance of bioreactor landfills. Due to the large number of variables involved in the settlement mechanism, accurate prediction of landfill settlement is a real challenge. The operational protocol of a landfill, the presence of municipal sludge from treatment plants, the addition of soybean peroxidase (SBP) enzymes, and the fraction of organic matter in the municipal solid waste (MSW) have to be reflected in the parameters of any model used to predict the settlement of MSW. In this work, a biodegradation-induced settlement model incorporating two parameters (A and B) was developed. The settlement data of two researchers were used to estimate the parameter values with two different approaches; the first considered the overall experiment and results, and the second separated the aerobic phase, if present, from the anaerobic phase. The rate of initial settlement occurring under aerobic conditions has been greater than that under anaerobic conditions. Parameters increased with the increase in the concentration of enzymes and with the presence of sludge in both aerobic and anaerobic stages. Increasing organic content of MSW has resulted in the enhancement of the biodegradation rate and settlement. This has been reflected on the higher values of the parameters compared to their values in the absence of organic waste.
authors.affiliation: Ryerson University, 350 Victoria Street, Toronto, ON, Canada, M5B 2K3. selagrou@ryerson.ca
authors.forename: Sherien A
authors.initials: SA
authors.lastname: Elagroudy
authors.forename: Mohamed H
authors.initials: MH
authors.lastname: Abdel-Razik
authors.forename: Mostafa A
authors.initials: MA
authors.lastname: Warith
authors.forename: Fikry H
authors.initials: FH
authors.lastname: Ghobrial
mesh_terms: D001673:Biodegradation, Environmental; D019149:Bioreactors; D019245:Compressive Strength; D004534:Egypt; D007700:Kinetics; D008962:Models, Theoretical; D010544:Peroxidases / Q000378:metabolism; D013025:Glycine max / Q000201:enzymology; D013997:Time Factors; D018505:Waste Management / Q000295:instrumentation / Q000379:methods*; D014874:Water Pollutants, Chemical
chemical_list: D014874:Water Pollutants, Chemical; D010544:Peroxidases