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Figure A5. 1: Example of SRT vs. length of operating time for accumulating system model Eq. A5- 13 with XP = 0.225 kg COD/d and X0= 15 kgCOD Near start-up where X 0 >> X P ⋅ te , Eq. A5- 13 becomes 2 t X e SRT = 2 ⋅ X P 0 and dSRT dt X = X P 0 t e After extended period of operation when X P ⋅ te >> X 0 , Eq. A5- 13 becomes 1 = t 2 SRT e and dSRT dt = SRT [d] 1 2 100 75 50 25 0 0 50 100 150 200 Real time t e [d] 208 SRT = 1/2 t e Eq. A5- 14 Eq. A5- 15 i.e. in a system with little initial seeding, a sufficiently long time after commissioning, and provided that the solids accumulation rate does not change substantially with time we are left with the neat solution that the sludge age increases at half of actual time i.e. dSRT = 0.5 dt. This model of sludge age is clearly fairly simplistic and only applies to a pseudo-steady-state condition where changes in overall sludge load do not affect the rate of excess sludge production XP such as those that prevailed in the pilot-scale ABR. • Sludge production should in fact be regarded as ultimate sludge production i.e. consist of inert particulate material originating from the influent and biomass produced from digestion of biodegradable COD that will be ultimately retained in the reactor. Thus a single value for excess sludge production can only be determined or applied when considering a long, stable period of operation in the accumulating system. • The simplest method of determining XP is from experimental data where XP is calculated from overall sludge load data using Eq. A5- 7. • Alternatively, XP may be estimated using a model such as that of Zeeman and Lettinga (Eq. A5-4, Zeeman and Lettinga, 1999) or a similar construction e.g. XP = amount of inert solids from influent that remain in the reactor unchanged + amount of COD which is ultimately converted to biomass
X X = P Inert ⋅ where Xinert is the amount of particulate inert COD in the influent [mgCOD/ℓ] and f XI , eff ( 1− f ) ( COD − COD − X ⋅ ( 1− f ) ) HRT XI , eff + in out HRT Inert 209 XI , eff Eq. A5- 16 is the fraction of the influent particulate inert COD that appears in the effluent during pseudo-steady-state operation. • This model makes no allowance for solids that are initially retained and later released through e.g. physical displacement or sludge decay. These effects are implicitly contained in the single XP value. This is not an unreasonable approach since it would be impossible to determine rate constants for these processes if modelled explicitly without long-term solids residence time distribution tests. However, the exclusion from the model may result in overestimation of sludge age if the ultimate sludge production from a package i of influent COD is overestimated from short-term experimental data. • Finally, the sludge ages calculated from this model are fundamentally different to those calculated for a steady-state system since the probability distribution for solids leaving the reactor are fundamentally different, particularly when considering different micro-organism sub-populations with differing retention characteristics. Thus comparison of sludge ages calculated with the two different methods should be undertaken with care since the behaviour of sludge (e.g. in terms of methanogenic activity) from an accumulating system may well be substantially different to one of the same calculated sludge age from a steady-state system. Specifically, conclusions from other studies that methanogenesis establishes for sludge ages longer than a specific value will not necessarily be valid for the accumulating system with SRT calculated as above.
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ANALYSIS OF A PILOT-SCALE ANAEROBIC
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i DECLARATIONS I, Katherine Maria F
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My deepest thanks must be extended
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vii TABLE OF CONTENTS ANALYSIS OF A
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5.3 Feed characteristics and loadin
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xi LIST OF TABLES Table 1.1: List o
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xiii LIST OF FIGURES Figure 1.1: Gr
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Figure 5.1 Installation of the ABR
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Figure 6.8: WEST® representation o
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xix LIST OF ABBREVIATIONS A-HRT App
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1 1 INTRODUCTION The work presented
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obtained from anaerobic systems rel
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• Lalbahadur (MTech, 2005) perfor
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1.7 ORGANISATION OF THE THESIS This
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9 2 LITERATURE REVIEW A detailed re
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• Disintegration of composite par
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Homoacetogens are one of the most v
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Most of the control in anaerobic di
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therefore the sensitivity of the ov
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∆Gº (W) [kcal] -10 -8 -6 -4 -2 L
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For systems with low potential for
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design of the digester in which the
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2.2.2 Expanded granular sludge bed
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fact that for most non-ideal flow s
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hydrolysis steps to convert them to
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from the clarified zone between the
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Table 2.4: Typical pathogen surviva
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Table 2.5: Studies using anaerobic
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• There is no requirement for bio
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Kennedy and Barriault (2005) perfor
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methanogenic (Akunna and Clark, 200
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and 6 h with no significant differe
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2.5.1.12 Granule formation in ABRs
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• A baffled reactor is described
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2.5.3.4 Scanning electron microscop
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spacing on flow patterns in a singl
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Figure 3.5: Orthographic projection
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PLC calculated the fraction of that
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epresent buulk conditionns. Compart
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The rreactor was initially commmiss
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Phase I Phase II Phase III Phase IV
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Table 4.1: Characteristics of degri
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Table 4.2: Pilot-scale ABR approxim
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COD [mgCOD/ℓ] 2000 1800 1600 1400
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4.3.5 Phosphorus Figure 4.8 present
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Observation of sludge in compartmen
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Another interesting observation is
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4.4.3 pH pH measurements were perfo
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esult in low pH values. The reasons
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4.5 SUMMARY: PHASE I - OPERATION AT
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than the optimal range for methanog
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5 EXPERIMENTAL PHASES II-IV: KINGSB
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sludge on a number of occasions. Wh
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On days 99 and 100 of Phase III, a
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5.3.2 Analysis of variations in fee
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Table 5.2: Pilot-scale ABR average
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5.4.1.2 Phase III In Phase III, (Fi
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Phase II: Alkalinity [mgCaCO3/ℓ]
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Eq. 5-1 However, at a COD/SO4 2- ra
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wastewater was probably higher than
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5.5.2.2 Damping Figure 5.12 and Fig
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• The outflow COD values were not
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• Information about the volume of
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As with the total volume of sludge
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It is not clear why the rate of acc
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most compartments was exactly 6.5,
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Soluble COD [mg/ℓ] 600 500 400 30
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pathogens and parasites, which may
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% Probe of DAPI % Probe of DAPI % P
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later compartments at all. Furtherm
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and 4, with decreasing observations
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• The mechanism of sludge build-u
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Table 5.6: Inflow and outflow chara
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Behling et al. (1997) studied the p
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organisms in previous compartments.
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velocities. Unfortunately, these tw
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Thus for a fixed sludge load, at hi
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sampling was not possible since in
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Wentzel (2006) recommends a COD to
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6.2.1.4 Calculation of CH4 producti
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organically bound N) or that N accu
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All VFA is consumed in the process,
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However, these assumptions are clea
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The calculated pH value is compared
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influent alkalinity will increase d
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The original objective to develop a
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• It was not possible to simulate
Page 182 and 183: employed for a medium strength wast
Page 184 and 185: 6.6.4 Alternative baffle design Thi
Page 186 and 187: 6.7.3 Monitoring requirements The m
Page 188 and 189: compartments (Section 6.1.1) pH val
Page 190 and 191: generally about anaerobic digestion
Page 192 and 193: 7.1.1.6 Effect of sludge age on bio
Page 194 and 195: 7.1.2.4 Critical design parameters
Page 196 and 197: 172
Page 198 and 199: Batstone D. J., Keller J., Angelida
Page 200 and 201: Gopala K. G. V. T. (2007). Treatmen
Page 202 and 203: MacLeod F. A., Guiot S. R. and Cost
Page 204 and 205: Sasse L. (1998). Decentralised wast
Page 206 and 207: Wanasen (2003). Upgrading conventio
Page 209 and 210: METTHODS OFF SAMPLINNG AND ANNALYSI
Page 211 and 212: 3.6 Enumeration of total coliforms
Page 213 and 214: that the means are the same, or con
Page 215 and 216: And the significance of the regress
Page 217 and 218: ADDITIONAL RESULTS 193 APPENDIX A3
Page 219 and 220: Table A3. 1 cont. Phase I Phase II
Page 221 and 222: each of the eight compartments were
Page 223 and 224: 3.2 Pathogen indicator organisms A
Page 225 and 226: APPLIED VS. APPARENT HYDRAULIC RETE
Page 227 and 228: 19 h apparent HRT 14 h apparent HRT
Page 229 and 230: 205 APPENDIX A5 CALCULATION OF SOLI
Page 231: i.e. the average SRT of an accumula
Page 236 and 237: iodegradable organic material may b
Page 238 and 239: Substituting Eq. A6- 1 in Eq. A6- 7
Page 240 and 241: 1.5 Implementation of steady-state
Page 242 and 243: X = 7⋅ Y = 7 Z = 7⋅ A = 7⋅ (
Page 244 and 245: Dama, P., Bell J., Naidoo, V., Foxo
Page 246: Lalbahadur T. (2004) Characterisati
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