MODELING GREENHOUSE GAS EMISSIONS FROM ACTIVATED SLUDGE PROCESSES

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1 MDELING GREENUE GA EMIIN FRM ACTIVATED LUDGE RCEE pencer nowling, ugh Montieth, liver chraa and ank Andres ydromantis, Inc. 685 Main t. W., uite 302, amilton, ntario, Canada, L8G5 ABTRACT Dynamic simulation of activated sludge process is a common tool for wastewater treatment design and optimization. Most activated sludge models predict only the uptake of BD and nutrients, however, they can easily be supplemented with further information regarding greenhouse gas (GG) production to predict the generation of components such as C 2. Many published anaerobic digestion models contain information on generation of gases, including C 2 and C 4. Implementing the C 2 -supplented activated sludge and anaerobic digestion models together in a full plant model can provide a useful way to evaluate GG emissions under a wide variety of operating conditions. KEWRD model, simulation, process optimization, greenhouse, digestion, C 2, C 4, GG INTRDUCTIN The activated sludge process has been identified as a source of significant greenhouse gas (GG) emissions to the atmosphere (U E..A., 2005). Dynamic modeling and simulation can be used to evaluate and optimize wastewater treatment processes for treatment level, energy usage, sludge production, and a number of other factors. This paper discusses techniques for supplementing conventional activated sludge models such as AM (enze, et al, 987) with new information to calculate C 2 emissions. In addition, existing dynamic-mechanistic digester models, such as Anaerobic Digestion Model # (ADM) (Batstone, 2002), model C 2 and C 4 emissions. This paper will show how GG emissions can be modeled with a full plant model (simulating both liquid and solids trains), allowing modelers to examine the balance between treatment level, energy usage and GG emission rates. Background Dynamic-mechanistic modeling of wastewater treatment processes has become a common tool in the environmental engineering industry. The International Water Association (IWA) suite of activated sludge models (e.g. AM, enze et al., 987; and AM2d, enze et al., 999) were originally developed to evaluate and optimize the biological treatment process. These models have been supplemented with other sub-models to estimate other process-related parameters such as airflow requirements, energy usage and interactions with toxic and/or inhibitory substances. This same approach can be used to add new model information on C 2 emissions to conventional activated sludge biological models. 7206

2 LIQUID LINE MDELING Model Matrix Notation The model matrix approach described in the AM model (enze, et al., 987) provides a convenient way to supplement the existing AM model with new information. Constants describing the consumption and generation of C 2 associated with each model component (e.g. biomass, substrate, etc.) are listed in the conservation matrix, and stoichiometry for each process rate is generated from the mass balance of C 2. Table shows the model matrix for AM (for clarity, only CD components are shown). Table. CD components of AM, illustrating the Model Matrix concept. j rocess Aerobic growth heterotrophs Anoxic growth heterotrophs Aerobic growth autotrophs i Decay heterotrophs Decay autotrophs I I A U rocess rate μ m K + K + K N μ m η g K K K N N f - f f - f 4.57 A A μ ma K N N + N b B, b A B, A 6 Ammonification k a ND 7 8 ydrolysis organic compounds ydrolysis organic N - K A + A / k K / B K +, + K N + η h K K N + + N ρ ( ND / 7 ) B, Unbiodegradable soluble matter (g CD m -3 ) Readily biodegradable substrate (g CD m -3 ) articulate unbiodegradable matter 3 Enmeshed slowly biodegradable substrate (g CD m -3 ) Active heterotrophic biomass Active autotrophic biomass Unbiodegradable particulates from cell 3 xygen (g (-CD) m -3 ) where f p A = fraction of biomass leading to particulate products, gcd/gcd = heterotrophic yield, gcd/gcd = autotrophic yield, gcd/gn μ = heterotrophic maximum specific growth rate, /d K = readily biodegradable substrate half saturation coefficient, gcd/m3 7207

3 K = oxygen half saturation coefficient, g2/m3 K N = nitrate half saturation coefficient, gn/m3 η g = anoxic growth factor, - b h = heterotrophic decay rate, /d μ a = autotrophic maximum specific growth rate, /d K NA = ammonia half saturation coefficient for autotrophs growth, gn/m3 b a = autotrophic decay rate, /d K A = oxygen half saturation coefficient for autotrophs growth, g2/m3 K = maximum specific hydrolysis rate, /d K = slowly biodegradable substrate half saturation coefficient, gcd/gcd η h = anoxic hydrolysis factor, - k a = ammonification rate, m3/gcd/d The matrix is a very intuitive way to show the inter-relatedness of the model processes and components. There is one column for each component (also known as a state variable ), and one row for each process in the model. Each process (e.g. cell growth, cell death, hydrolysis) moves forward at a rate described by the kinetic equation in the right-hang column. In doing so, the various model components are generated or consumed according to the stoichiometry in the matrix. For example, as the heterotrophic biomass grows, it consumes (/ ) units of soluble substrate ( s ) and (- )/ units of oxygen ( o ), while producing unit of biomass ( ). upplementing The AM Model With C 2 toichiometry A new column can be added to the matrix to supplement the existing AM Model with a new submodel which describes the mass balance of C 2. This new column for the C 2 component contains the stoichiometry describing the production and consumption of C 2 for each process in the model, and is shown in Table 2. Table 2. Carbon Dioxide toichiometry for Wastewater rocesses j rocess i C 2 toichiometry Aerobic growth of heterotrophs icb ic 2 Anoxic growth of heterotrophs icb ic 3 Aerobic growth of autotrophs i CB 4 Decay of heterotrophs i + f icxu + ( f ) icxs 5 Decay of autotrophs i + f icxu + ( f ) icxs 6 Ammonification 7 ydrolysis organic compounds i C + icss 8 ydrolysis organic N CB CB 7208

4 Note that for some processes (e.g. processes 6 and 8, which are transformations of nitrogen), there is no C 2 stoichiometry, meaning that C 2 is not consumed or produced by this process. The newly augmented model is then capable of dynamically calculating the consumption and generation of C 2 in the activated sludge process. The dynamic-mechanistic nature of the model is able to simulate the daily diurnal changes in C 2 production as the activated sludge process deals with changes in influent flow and organic loading. A similar approach, using supplemental stoichiometry to determine C 2 generation from BD and/or CD removal has been used by Monteith, et al., (2005) and others. In most cases, however, the approach is for steady-state modeling only. The approach described above, where a mechanistic model such as AM is appended with further sub-models for C 2 mass balance, creates a dynamic tool that is capable at evaluating changes in C 2 production over time. LID LINE MDELING: ADM GA EMIIN The anaerobic digestion model ADM, as published, contains gas consumption/generation and transfer models for C 2 and C 4, and therefore does not require any supplementation. This allows engineers to be able to dynamically estimate mass emissions of GG compounds from wastewater treatment plants, including an understanding of the balance between GG emissions from aerobic vs. anaerobic processes. ADM models several different biomass populations, each of which breaks down various types of CD. The biological model matrix is large and complex, and beyond the scope of this paper (for details please see Batstone, et al., 2002, and Rosen and Jeppsson, 2002). owever, a simplified summary of the ADM model is shown in Figure. Composite Material Inert Material Carbohydrate roteins Lipids Monosaccharides Amino Acids Long-chain FAs hort-chain FAs Figure. implified ADM Model tructure. ydrogen Acetate Methane 7209

5 Note that the anaerobic breakdown of the composite CD material produces acetic acid and hydrogen gas, which are subsequently utilized by methanogens, producing methane. C 2 production and consumption at various stages of the digestion process are also modeled. Wastewater lant Emissions Example Figure 2 illustrates a conventional activated sludge plant model, as shown in the G- wastewater modeling software. The plant includes aeration basins, secondary activated sludge, and digestion. Note that in this model, the influent arrow represents a wastewater stream that has been characterized as primary clarifier effluent. Figure 2. ample Wastewater lant G- Model. Figure 3 illustrates the results of a typical wastewater simulation. ML and aeration basin dissolved oxygen are shown for a -day simulation with an influent that fluctuates in a diurnal pattern (both for load and flow rate). Effluent BD, T, and TKN are shown in Figure 4. Note that the effluent quality is at a conventionally acceptable level. 720

6 Figure 3. Diurnal Fluctuations in D level and ML. Figure 4. Diurnal Fluctuations in Effluent Quality. Figure 4 illustrates the results of the C 2 emissions from the aeration basin, as well as the C 4 emission from the digester. Note that the dynamic model not only allows engineers to estimate C 2 and C4 production, but also see how the emissions vary throughout the day. 72

7 Figure 5. C 2 and Methane roduction from Activated ludge rocess. CNCLUIN These types of models provide the process engineer with a tool that can estimate the amount of GG emissions under different operating conditions, and weighed against the corresponding level of treatment and operational energy cost. This tool can therefore be used by decisionmakers to evaluate the contribution of wastewater treatment plants to the global GG problem, and to evaluation options for mitigation of the emissions while still maintaining an acceptable level of treatment. REFERENCE Batstone D.J., Keller J., Angelidaki I., Kalyuzhnyi.V., avlostathis.g., Rozzi A., anders W.T.M., iegrist. and Vavilin V.A. (2002) Anaerobic Digestion Model No. (ADM). IWA cientific and Technical Report #3. IWA ublishing, London, England. enze M., Grady C..L. (Jr), Gujer W., Marais G.v.R and Matsuo T. (987) Activated ludge Model No.. IAWQ cientific and Technical Report No., IAWQ, London. 33pp. enze M., Gujer W., Mino T., Matsuo T., Wentzel M.C., Marais G.v.R. and Van Loosdrecht (999) Activated sludge model No. 2d. Wat. ci. Tech., 39 (), Monteith,., ahely,., MacLean,., and D. Bagley, A Rational rocedure for Estimation of Greenhouse-Gas Emissions from Muncipal Wastewater Treatment lants, Water Environment Research, 77 (4), Rosen, C., and Jeppsson, U. (2002) Anaerobic CT Benchmark Model Description, Version.2., Department of Electrical Engineering and Automation, Lund University, weden. 722