Improving our Understanding of the Differences between Fixed and Moving Bed Media IFAS Systems for Design, Operations and for Real Time Control of Plants (in Aquifas+) to Simultaneously Enhance Nutrient Removal and Minimize GHG Emissions

Sen, Dipankar; Lodhi, A.; Randall, Clifford W.; Gold, Lenny; Brandt, Karen; Copithorn, Rip; Pehrson, Richard; Chandran, Kartik

doi:10.2175/193864710798182501

Cited by 2 publications

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“…This points to the need for simulation of methanogens in the biofilm in the denitrification filters. The methanogens can convert excess methanol to methane if the COD concentrations are sufficiently high in certain sections of the biofilter and the oxidized-N has been consumed Sen et al 2010). This component was added to the third generation of the model (Aquifas+).…”

Section: Resultsmentioning

confidence: 99%

“…The void space among media particles was measured at 40%, which represented the water volume in a space filled with media and submerged in water. The model includes the equations for uptake, oxidation, and reduction of chemical oxygen demand (COD), ammonium-nitrogen, oxidized nitrogen, and sludge production in a biofilm that is structured in a format that is compatible with the IWA publications for activated sludge and biofilms Sen et al 2010). The equations for the biofilm were structured in a manner that was compatible with simultaneous operation with the activated sludge model.…”

Section: Process Calculationmentioning

confidence: 99%

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Full Scale Denitrification Filtration and Process Modeling Using a Steady State Mathematical Framework

Zhu¹,

Sen²,

Vegso³

et al. 2011

proc water environ fed

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Biological denitrification is a process where nitrate is reduced to nitrogen gas in a step-wise manner by electron donors (usually methanol, acetic acid, or ethanol) in the absence of oxygen. A fixed-film denitrification process is basically a biofilm process, which fundamentally consists of two simultaneous steps, substrate diffusion and biological reaction. The mathematical framework for both steady state and dynamic one-dimensional models is well established. However, there is limited modeling and simulation of full scale plants with tertiary denitrification filters with external carbon addition. In this work, performance data were reviewed for the denitrfication filters at Central Johnston County Wastewater Treatment Plant, Smithfield, North Carolina. A process model was established using AquaNET Aquifas (Aquaregen, Mountain View, CA). The model successfully predicted the process performance and the nitrate profiles in a pilot denitrification study and subsequently the model was applied to the denitrification system at Central Johnston County Wastewater Treatment Plant typically during the summer and winter seasons. The model was successful in predicting effluent nitrate concentrations but failed to predict the effluent soluble chemical oxygen demand concentrations in the winter season when the filters were overdosed with methanol. It was demonstrated that the model can be applied to situations with a wide range of nitrate loading from 0.07 lbs/ft 2 /day (0.34 kg/m 2 /day) to 1.02 lbs/ft 2 /day (4.98 kg/m 2 /day). It was hypothesized that methanogens were produced under the anoxic environment and consumed the excessive carbon source. The temperature effect was also discussed and an Arrhenius coefficient of 1.03 was found appropriate for process simulation.

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Section: Resultsmentioning

confidence: 99%

Section: Process Calculationmentioning

confidence: 99%

Full Scale Denitrification Filtration and Process Modeling Using a Steady State Mathematical Framework

Zhu¹,

Sen²,

Vegso³

et al. 2011

proc water environ fed

Self Cite

View full text Add to dashboard Cite

show abstract

“…Coarse bubble diffusers will reduce the bubble surface area (which reduces emissions) and increase the air flow (which increases air flow). An analysis of results with coarse bubble diffusers in IFAS and conventional systems for configuration used at the Broomfield, CO WWTP is presented by Sen et al, (2010).…”

Section: Figure 2: Graph Showing Impact Of Changing Do Levels On the mentioning

confidence: 99%

Differences in GHG and Nitric Oxide Emissions for Activated Sludge and Biofilm ENR processes based on Aeration, MCRT, Mixing and Media, and Control of Emissions and Nutrients by Enhancing Process Models in an ENR Operations Simulator (Aquifas)

Lodhi¹,

Sen²,

Randall³

et al. 2010

proc water environ fed

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Practicing wastewater process engineers use mathematical models when planning, designing, optimizing, evaluating, and performing problem solving work related to proposed or existing municipal and industrial WWTPs. This paper presents the result of research on the extension of ASM2d to model GHG emission using Aquifas+ WWTP simulator. A significant increase in the number of components and processes defined in ASM2d was carried out to develop a more sophisticated mathematical model for Aquifas+. New components representing N 2 O, NO and NO 2 are introduced in the model to simulate the nitrification processes by the ammonium oxidizing bacteria (AOB), followed by NO 2 oxidation by nitrite oxidizing bacteria (NOB). The denitrification is broken up into four steps for ordinary heterotrophs (OHO) and polyphosphate accumulating bacteria (PAO) to go from nitrate to nitrite to nitric oxide to nitrous oxide and then to nitrogen gas. The physical portion of the model includes equations for diffusion of NO 2 and NO into the atmosphere. These equations are related to the type of aeration and mixing. Unlike ASM2d, which uses the same coefficient for several reactions, Aquifas+ uses a substantially larger number of coefficients, such as the ability to specify different half saturation constants for DO (K DO ) for fermenters, OHO and PAO under aerobic conditions, OHO and PAO for inhibition under anoxic conditions, and each step of AOB nitrification. A similar set of equations were constructed for the biofilm models. The mathematical technique used to invert the larger matrix of equations was improved to enable faster and accurate solutions. The faster algorithms were necessary for applying the model as a real time operations simulator and controller inside enhanced nutrient removal plants in Maryland, USA. The simulator can simultaneously optimize the plant operations for GHG emissions and effluent nutrients. Additionally, it is designed to optimize the plant for energy and chemical consumption for the biological treatment and water reuse applications at plants in developed and emerging markets.

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Improving our Understanding of the Differences between Fixed and Moving Bed Media IFAS Systems for Design, Operations and for Real Time Control of Plants (in Aquifas+) to Simultaneously Enhance Nutrient Removal and Minimize GHG Emissions

Cited by 2 publications

References 1 publication

Full Scale Denitrification Filtration and Process Modeling Using a Steady State Mathematical Framework

Full Scale Denitrification Filtration and Process Modeling Using a Steady State Mathematical Framework

Differences in GHG and Nitric Oxide Emissions for Activated Sludge and Biofilm ENR processes based on Aeration, MCRT, Mixing and Media, and Control of Emissions and Nutrients by Enhancing Process Models in an ENR Operations Simulator (Aquifas)

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