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Seasonal influent characterization, model calibration, SRT and energy usage for nitrogen removal at a full scale wastewater plant

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Please use this identifier to cite or link to this item: http://hdl.handle.net/1928/20782

Seasonal influent characterization, model calibration, SRT and energy usage for nitrogen removal at a full scale wastewater plant

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Title: Seasonal influent characterization, model calibration, SRT and energy usage for nitrogen removal at a full scale wastewater plant
Author: Raoufi, Roozbeh
Advisor(s): Schuler, Andrew
Committee Member(s): Howe, Kerry
Thomson, Bruce
Schuler, Andrew
Department: University of New Mexico. Dept. of Civil Engineering
Subject: wastewater characterization
denitrification
Solids Retention Time
model calibration
Chemical Oxygen Demand (COD)
LC Subject(s): Sewage--Purification--Nitrogen removal.
Denitrification.
Degree Level: Masters
Abstract: This study focused on factors affecting biological denitrification in wastewater treatment. Denitrification is a process in which heterotrophic bacteria use nitrate as an electron acceptor (in the absence of oxygen) and organic carbon as an electron donor (commonly measured as chemical oxygen demand, or COD). The availability of sufficient COD is commonly the limiting factor for denitrification at many wastewater plants, with some plants having to purchase external carbon sources (such as acetic acid) to meet stringent nitrogen limits. The objective of this study was to evaluate the effects of different primary effluent characteristics (COD components), solid retention times (SRTs), and temperatures on denitrification rates in a full scale system, including evaluation of seasonal effects. In order to investigate seasonal variations, four seasonal sampling campaigns were conducted (October 2010, January 2011, May 2011, and July 2011) at the Southside Water Reclamation Plant (SWRP), which is a predenitrifying plant using the Modified Ludzack Ettinger, or MLE process located in Albuquerque, New Mexico, USA. The sampling events were conducted to measure the different COD and nitrogen components of the primary influent and primary effluent of the plant to calibrate a BioWinTM (version 3.1, EnviroSim Associates Ltd.) model. It was determined that denitrification during the warm season (May and July) were mostly similar to each other and different from the sampling periods data during the cold season (October and January), in terms of COD and nitrogen fractionation. However, the fluctuation of calculated BioWin fractions between seasons suggested building a specific model for each season. The components of COD included soluble, particulate, readily biodegradable, and slowly biodegradable COD, and their effects on denitrification potential were evaluated in batch experiments with sludge from the treatment plant to determine how these components affected denitrification rates. It was found that denitrification rates are different during the particulate COD oxidation compared to the non-particulate (glass fiber filtrate) COD oxidation, while RBCOD and colloidal COD did not show a big difference in terms of nitrate removal capacity. Solids Residence Time (SRT) is a very important operational parameter in a full-scale system and directly influences the effluent quality. Higher SRTs are associated with high bioreactor biomass concentrations, which can provide improved effluent quality, but imposes higher solids loading rates on secondary clarifiers and potentially higher rates of oxygen demand. The effects of different SRT values on the denitrification and solids loading rates were investigated using BioWinTM simulator calibrated based on the COD characterization work. It was determined that an SRT of approximately 7 days is the optimum SRT for the plant in order to keep effluent nitrate and ammonia concentrations below the permit levels, consume the minimum energy in the aeration tanks, provide maximum methane production, and impose the minimum solids loading to the final clarifiers.
Graduation Date: May 2012
URI: http://hdl.handle.net/1928/20782


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RRaoufi masters thesis 121911 (Final version).pdf 3.240Mb PDF View/Open Roozbeh Raoufi's Master's Thesis

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