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Water treatment

Annex 5: Residence times

Annex 5: Residence times in coarse gravel filtration units A5.1. Modelling residence-time distribution. A useful model for residence time distribution is shown in figure A5-1, in which virtual completely mixed (CM) reactors in series are used to simulate hydraulic behaviour of real reactors. The number of CM reactors can have any integer value from 1,0 to n. In general, the sum of the volumes of all the virtual reactors is equal to the volume of the real system being modelled. V = V 1 + V 2 + V 3 + ................. + V n (A5-1) Figure A5-1. Virtual CM reactors in series for modelling the hydraulic performance of real reactors. As shown in the figure A5-1, at time t o , a slug or step dose of tracer is added to the influent side of the CM reactors. The tracer concentration C n at the effluent side of the CM reactors is given by the equation A5-2 (Nauman and Buffham, 1983, quoted by Clark, 1996; Galvis and Perez, 1985), C n/C o = F(t) = n n−1 [(nθ) /(n − 1)! ] e −nθ (A5-2) In which C n , is referred to the maximum expected concentration Co in the last reactor; F (t) is the cumulative residence time distribution; θ = t/To, being To equal to the total volume of reactor (V) divided by the flow (Q); and n, the number of CM reactors in series. Equation A5-2 is a one-parameter (for n) model. As shown in figure A5-2, equation A5-2 allows obtaining curves of dimensionless residence time density versus θ, dimensionless time. As the number reactors increases, the residence time density moves from the exponential distribution of the single perfectly mixed tank (n = 1) to a distribution that increasingly seems to be centred at θ = 1. Therefore, as n approaches ∞, the residence-time density for the reactors in series approaches the residence-time density for ideal plug flow. This is one of the chief strengths of the reactors in series model. Using equation A5-2, a general expression (equation A5-3) can be obtained for calculating 1 – F (t), which is the fraction of the flow that remains in the reactor system for a period longer than t: 1- F(t) = n (nθ) ∑ e (i − 1)! i=1 i-1 .-nθ (A5-3) Applying equation A5-3 for different number (n) of reactors, it can be obtained figure A5-3 and table A5-1, that show the relation between 1-F (t) and θ and the percentages of flow discharges at different fractions θ respectively. A5-1

Figure A5-2 Residence time density for different number (n) of CM reactors in series Figure A5-3 Residence time characteristics of CM reactors in series. A5-2

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Development and Evaluation of Multi

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ACKNOWLEDGEMENTS To my supervisor,

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ABBREVIATIONS ABNT: Acuavalle: ACV:

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SOCs: Synthetic Organic Chemicals S

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u c V V f Vs uniformity coefficient

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4 MULTISTAGE FILTRATION EXPERIENCIE

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1 INTRODUCTION Water is essential f

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Table 1.5 Safe drinking water cover

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1.2 Multiple Barriers Strategy and

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2 OVERCOMING THE LIMITATIONS OF SLO

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On January 14, 1829, Simpson’s on

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With increasing life expectancy, en

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Table 2.2 Treatments steps recommen

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In table 2.3, WHO guideline values

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2.5 The Slow Sand Filtration Proces

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When the particles are very close t

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in which p 0 is the clean media por

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Yao et al (1971) related the remova

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compensate for the increase in the

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can be applied, but intermittent op

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Table 2.4 Comparison of design crit

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Although accepted as indirect indic

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50% when the temperature falls from

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Figure 2.9 Flow diagram of the wate

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ut higher running costs, since more

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Headloss and flow control. Final he

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Figure 2.13 Influence of flow condi

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Operation and maintenance (O & M).

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in parallel (Galvis, 1983; Smet et

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cleaning simple, DyGF should behave

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case of Dortmund (Germany), the HGF

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Table 2.9 Data about three experien

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Some points of discussion about HGF

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and 600-800 NTU) and different filt

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the HGF units of Aesch (see table 2

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in spite of the low removal efficie

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order to overcome the water quality

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full-scale units. In this research,

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3 MULTISTAGE FILTRATION STUDIES WIT

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in the case of UGFL. Initially, it

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• Bigger and better-instrumented

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l Figure 3.7 Plan view of Cinara's

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The present research work was divid

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Table 3.1. Design parameters, grave

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Figure 3.9. Piezometer distribution

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were used to collect samples for DO

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were poured into a funnel using fil

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H 0 : H a : Treatment levels workin

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3.2 Results and Specific Discussion

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3.2.2 Dynamic gravel filtration (Dy

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Mean faecal coliform removal effici

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Table 3.10 Comparative analysis of

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DyGF-A had flow reductions in the r

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The experimental data used to produ

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Previous observations were further

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ates (figure 3.17 B). However, at t

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Longer “initial-ripening” perio

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Table 3.17. Descriptive statistics

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100 Filtration rate = 0.3 mh -1 100

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After the present experience, faeca

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nature of the organic matter and th

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Table 3.24 Comparative analyses of

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3.2.4.3. Filtration run lengths and

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deep bed filter (data not included

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and operational considerations Pard

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than in sand samples from other SSF

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Step dose tracer tests were made at

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for HGFS and from 3 to 5 for HGF. T

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Constant and declining filtration r

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The efficiency levels summarised be

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Surface area of CGF and SSF units.

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community based organisations and l

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systems. All these systems were fed

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Parts of the suburban settlements o

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Figure 4.2. Layout of Retiro MSF pl

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Traditionally, in the WS&S of Colom

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Photo 4.10. Partial cleaning activi

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Figure 4.3 Location of full-scale M

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4.4.1.3 Main characteristics of mul

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Figure 4.4 Layout of Restrepo MSF p

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Figure 4.6 Layout of Javeriana MSF

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Figure 4.9 Layout of Cañasgordas M

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Figure 4.11. Layout of Ceylan MSF p

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Table 4.4 Descriptive statistics fo

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Water sources in the coffee region

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Filterability results seem to under

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Table 4.8 Mean removal efficiencies

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The length of this ripening period

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in Peru (Pardon, 1989) and Colombia

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Photo 4.24 Drainage facilities in u

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the Cauca Valley. This is not the c

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Pardon (1989) reports similar evide

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5. COST OF MULTI-STAGE FILTRATION P

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ecame formally established as WS en

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Models for assessing construction q

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MSF system can then be calculated o

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5.7 Cost Model for the Cali Area an

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Table 5.8. Annual labour costs due

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5.8 General Discussion The followin

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systems. The differences between MS

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guideline for colour is < 15 PCU (W

• Page 214 and 215: Table 6.1. Individual (at each trea
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• Page 218 and 219: As shown in tables 6.1 and 6.3, col
• Page 220 and 221: UGFL 0.45 UGFS 0.45 (32;51;85) (44;
• Page 222 and 223: Table 6.4. An example of identifica
• Page 224 and 225: MSF technology showed great flexibi
• Page 226 and 227: In harmony with the new development
• Page 228 and 229: epresents the risk the community ha
• Page 230 and 231: The selection of MSF alternatives i
• Page 232 and 233: scouring and transporting away prev
• Page 234 and 235: REFERENCES ABNT, (1989) NB-592 Proj
• Page 236 and 237: Craun, G.F., Bull, R.J., Clark, R.M
• Page 238 and 239: Drinking Water Disinfection, ed. by
• Page 240 and 241: Huisman, L. (1989) Plain Sedimentat
• Page 242 and 243: Mendenhall, W. and Sincich, T. (199
• Page 244 and 245: Ridley, J.E. (1967) Experience in t
• Page 246 and 247: Visscher, J.T. and Galvis, G. (1992
• Page 248 and 249: ANNEXES Annex 1: Accessories for Mu
• Page 250 and 251: aw water. The red colour is used fo
• Page 252 and 253: Annex 2: Design of Manifolds Manifo
• Page 254 and 255: + q 2 Q1 (1.2 qn + qn) (2.2 qn) = =
• Page 256 and 257: R 1 = (total orifice area / lateral
• Page 258 and 259: 0.30 0.25 0.20 0.15 0.10 0.05 0.00
• Page 260 and 261: Table A.4-2 General notation for th
• Page 262 and 263: Box A4-3. Sum of Square Error (SSE)
• Page 266 and 267: Table A5-1 Percentage of incoming w
• Page 268 and 269: Annex 6 Number and Type of Valves N
• Page 270: Table A7-1. Descriptive statistics
• Page 274 and 275: Tables A7-3 Removal efficiencies of
• Page 276 and 277: Tables A7-5 Removal efficiencies of
• Page 278 and 279: Construction quantities of DyGF com
• Page 280: Net present value (US\$) of MSF and
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