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4.9 Rank Sum Test Two means may be compared using a t-test if the data described by the means is normally distributed. If not, either a transformation should be applied to the data in order to obtain normal distributions, or a distribution-free test should be used (Davies and Goldsmith, 1977 p. 74). The rank-sum test is a distribution-free test that uses the rank-order of the data : For 2 data sets with n1 and n2 number of observations • The data sets are combined and ranked in order of increasing value • Rank 1 is assigned to the lowest value, rank 2 to the next etc. until the highest value which is assigned rank n1+n2. • n1 = smaller sample size; n2 = larger sample size; n = n1+n2 • R is the sum of ranks of the smaller sample ′ 1 • R = n1 ⋅ ( n + ) − R • The critical value M is available in statistical tables or can be calculated from and u = 2.58 for α = ( n + 1) n1 n1n 2 M = ( n + 1) − u 2 12 where u = 1.96 for α = 0.05 (double - sided test) 0.01 (double - sided 192 test) • If R or R’
ADDITIONAL RESULTS 193 APPENDIX A3 This appendix contains additional data that were obtained during operation of the pilot-scale ABR that was not included explicitly in the body of the thesis. 1 TABLE OF ANALYSES AND RESPONSIBLE PERSONS Table A3. 1 presents lists of analyses and people responsible for supervising, sampling, analysis, data capture and data analysis for all of the data presented in this thesis. 2 PHASE I: OPERATION OF PILOT-SCALE ABR AT UMBILO WWTP 2.1 Influent characteristics Time series concentration data showed considerable scatter, making it difficult to gain an impression of the distribution of the data when looking at a time vs. concentration plot. The rank probit plot presents the data ranked according to concentration and plotted against the equivalent ranked data point from a normal distribution with the same mean and standard deviation as the data set. If the data are normally distributed, the data points fall on a x=y 45º diagonal line. Deviations from the 45º line indicate that the distribution of the data deviates from the normal distribution. These plots make it very easy to understand the scatter of the data since percentile lines may be drawn in corresponding to values at selected percentiles determined from the ranked data. Rank probit plots are presented for COD, alkalinity, free and saline ammonia, phosphate, total solids and pH of the Umbilo influent wastewater.
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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
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
Page 174 and 175: The calculated pH value is compared
Page 176 and 177: influent alkalinity will increase d
Page 178 and 179: The original objective to develop a
Page 180 and 181: • 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 the significance of the regress
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 and 232: i.e. the average SRT of an accumula
Page 233: X X = P Inert ⋅ where Xinert is t
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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