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Due to the large number of samples for COD analysis (72 samples in duplicate) COD analyses were performed using small samples and a closed reflux / spectrophotometric method. For samples known to contain particulate matter, this method is less accurate than an open reflux method with larger sample size and back-titration. The School of Chemical Engineering Biochemical Engineering Laboratory could only accommodate 10 samples for open reflux COD analysis at a time. Therefore it was felt that the loss of accuracy using the closed reflux method would be less than the accuracy lost by storing the samples for the week that would be required to complete the analyses using the open reflux method. For similar reasons, samples were only analysed in duplicate rather than in triplicate as was usually favoured for these types of measurements. Figure 5.11 presents flow rate data for the duration of the campaign. An average flow rate of 3440 ℓ/d was obtained during the campaign. This corresponded to an A-HRT of 21.8 h. 5.5.1 Diurnal variation of inflow characteristics Figure 5.12 and Figure 5.13 present data from COD, alkalinity and pH analyses from the ABR inflow and outflow. Outflow curves have been back-transposed 16 h in time to show possible correspondence between inflow and outflow data. (The rationale for the selection of 16 h is presented in Appendix A4 and Section 5.5.2.3). 5.5.1.1 Inflow COD concentration The inflow COD profile (Figure 5.12) showed a diurnal variation in load, with highest COD concentrations observed between 10h00 and 14h00, and lowest COD loads between 01h00 and 05h00. There were no corresponding peaks or troughs on the outflow COD profile. The outflow COD concentration remained around 200 mg/ℓ, while filtered COD values were fairly constant at 64 ± 6 mgCOD/ℓ. The purpose of the campaign was to determine how representative the regular measurements made by the project team were given the diurnal variation of wastewater characteristics. • Regular sampling usually took place between 09h00 and 15h00 and yielded an average inflow COD concentration of 715 mgCOD/ℓ (project-team COD concentration data for Phase III). The average COD concentration for the period 09h00 to 15h00 obtained from the 24 h sampling campaign was 751 mgCOD/ℓ. • The average inflow COD value calculated from all available Phase III data (project team and municipality data) was 676 mgCOD/ℓ. The overall average inflow COD concentration value for the 24 h campaign was 564 mgCOD/ℓ Thus it appears that routine sampling was done at a time when wastewater strength was greater than the average wastewater concentration, resulting in calculation of average wastewater strength and OLR that was higher than was actually experienced by the ABR. Generally, both the volumetric flow rate of wastewater received by a wastewater treatment plant, and the wastewater strength will follow a diurnal pattern with a significant decrease due to reduced water use at night time. A flaw existed in the design of the flow control programme in that a constant volumetric flow was delivered to the pilot-scale ABR irrespective of the strength of the wastewater. Thus the pilot-scale ABR received on average a lower strength of wastewater than the rest of the plant would have received. The flow-weighted average value for COD concentration in Kingsburgh WWTP 100
wastewater was probably higher than that experienced by the pilot-scale ABR, as shown in the averages presented above, where a difference of more than 100 mgCOD/ℓ was observed. COD [mg/ℓ] Time (Outflow Samples) 01:00 1800 04:00 07:00 10:00 13:00 16:00 19:00 22:00 01:00 1600 1400 1200 1000 Figure 5.12: Phase III: 24 h sampling campaign COD concentrations and pH values showing diurnal variation in inflow and outflow streams from the pilot-scale ABR. Shading indicates night (for inflow sampling). Alkalinity [mgCaCO 3/ℓ] 800 600 400 200 0 Figure 5.13: Phase III: 24 h sampling campaign COD and alkalinity concentrations showing diurnal variation in inflow and outflow streams from the pilot-scale ABR. Shading indicates night (for inflow sampling). 101 04:00 8 09:00 12:00 15:00 18:00 21:00 00:00 03:00 06:00 09:00 12:00 Time (Inflow samples) 01:00 500 450 400 350 300 250 200 150 100 Outflow COD Inflow COD pH in pH out Time (outflow samples) 04:00 07:00 10:00 13:00 16:00 19:00 22:00 01:00 COD in COD out Inflow Alkalinity Outflow Alkalinity Filtered outflow COD 04:00 1200 09:00 12:00 15:00 18:00 21:00 00:00 03:00 06:00 09:00 12:00 Time (Inflow samples) 800 400 0 -400 -800 -1200 -1600 -2000 7 6 5 4 3 2 1 0 -1 COD [mg/ℓ] pH
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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
Page 74 and 75: 2.5.3.4 Scanning electron microscop
Page 76 and 77: spacing on flow patterns in a singl
Page 78 and 79: Figure 3.5: Orthographic projection
Page 80 and 81: PLC calculated the fraction of that
Page 82 and 83: epresent buulk conditionns. Compart
Page 85 and 86: The rreactor was initially commmiss
Page 87 and 88: Phase I Phase II Phase III Phase IV
Page 89 and 90: Table 4.1: Characteristics of degri
Page 91 and 92: Table 4.2: Pilot-scale ABR approxim
Page 93 and 94: COD [mgCOD/ℓ] 2000 1800 1600 1400
Page 95 and 96: 4.3.5 Phosphorus Figure 4.8 present
Page 97 and 98: Observation of sludge in compartmen
Page 99 and 100: Another interesting observation is
Page 101 and 102: 4.4.3 pH pH measurements were perfo
Page 103 and 104: esult in low pH values. The reasons
Page 105 and 106: 4.5 SUMMARY: PHASE I - OPERATION AT
Page 107 and 108: than the optimal range for methanog
Page 109 and 110: 5 EXPERIMENTAL PHASES II-IV: KINGSB
Page 111 and 112: sludge on a number of occasions. Wh
Page 113 and 114: On days 99 and 100 of Phase III, a
Page 115 and 116: 5.3.2 Analysis of variations in fee
Page 117 and 118: Table 5.2: Pilot-scale ABR average
Page 119 and 120: 5.4.1.2 Phase III In Phase III, (Fi
Page 121 and 122: Phase II: Alkalinity [mgCaCO3/ℓ]
Page 123: Eq. 5-1 However, at a COD/SO4 2- ra
Page 127 and 128: 5.5.2.2 Damping Figure 5.12 and Fig
Page 129 and 130: • The outflow COD values were not
Page 131 and 132: • Information about the volume of
Page 133 and 134: As with the total volume of sludge
Page 135 and 136: It is not clear why the rate of acc
Page 137 and 138: most compartments was exactly 6.5,
Page 139 and 140: Soluble COD [mg/ℓ] 600 500 400 30
Page 141 and 142: pathogens and parasites, which may
Page 143 and 144: % Probe of DAPI % Probe of DAPI % P
Page 145 and 146: later compartments at all. Furtherm
Page 147 and 148: and 4, with decreasing observations
Page 149 and 150: • The mechanism of sludge build-u
Page 151: Table 5.6: Inflow and outflow chara
Page 154 and 155: Behling et al. (1997) studied the p
Page 156 and 157: organisms in previous compartments.
Page 158 and 159: velocities. Unfortunately, these tw
Page 160 and 161: Thus for a fixed sludge load, at hi
Page 162 and 163: sampling was not possible since in
Page 164 and 165: Wentzel (2006) recommends a COD to
Page 166 and 167: 6.2.1.4 Calculation of CH4 producti
Page 168 and 169: organically bound N) or that N accu
Page 170 and 171: All VFA is consumed in the process,
Page 172 and 173: 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
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employed for a medium strength wast
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6.6.4 Alternative baffle design Thi
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6.7.3 Monitoring requirements The m
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compartments (Section 6.1.1) pH val
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generally about anaerobic digestion
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7.1.1.6 Effect of sludge age on bio
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7.1.2.4 Critical design parameters
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172
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Batstone D. J., Keller J., Angelida
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Gopala K. G. V. T. (2007). Treatmen
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MacLeod F. A., Guiot S. R. and Cost
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Sasse L. (1998). Decentralised wast
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Wanasen (2003). Upgrading conventio
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METTHODS OFF SAMPLINNG AND ANNALYSI
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3.6 Enumeration of total coliforms
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that the means are the same, or con
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And the significance of the regress
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ADDITIONAL RESULTS 193 APPENDIX A3
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Table A3. 1 cont. Phase I Phase II
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each of the eight compartments were
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3.2 Pathogen indicator organisms A
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APPLIED VS. APPARENT HYDRAULIC RETE
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19 h apparent HRT 14 h apparent HRT
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205 APPENDIX A5 CALCULATION OF SOLI
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i.e. the average SRT of an accumula
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X X = P Inert ⋅ where Xinert is t
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iodegradable organic material may b
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Substituting Eq. A6- 1 in Eq. A6- 7
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1.5 Implementation of steady-state
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X = 7⋅ Y = 7 Z = 7⋅ A = 7⋅ (
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Dama, P., Bell J., Naidoo, V., Foxo
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Lalbahadur T. (2004) Characterisati
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