Water treatment

0.30 0.25 0.20 0.15 0.10 0.05 0.00 Y = 0.0469X + 0.0282 R 2 = 0.92 0 2 4 6 0.40 0.35 0.30 0.25 0.20 0.15 0.10 0.05 0.00 Y = 0.0097X + 0.0211 R 2 = 0.9726 0 10 20 30 40 A Figure A3-2 Suspend solids (m g /l) by Standard M ethod B Suspend Solid (m g /l) by Standard M ethod Standard curve for suspended solids (mgl -1 ) versus absorbance at 810 nm in samples taken from effluents of CGF pilot units (A) and Full scale plants (B). Samples were taking again from CGF effluents and were analysed for SS with both Gooch and spectrophometric methods. The obtained results were used to validate spectrophometric method. Descriptive statistics of data originated from pilot plant samples are presented in table A3-1. These data have a lineal regression given by the equation Y = 0.047X + 0.028 (r 2 = 0.92), in which Y and X are suspended solid values obtained by the spectrophometric and Gooch methods respectively. The data originated from full-scale plants have a lineal regression given by the equation Y = 0.0097X + 0.0211 (r 2 = 0.97). Table A3-1 Descriptive statistics of SS measurements (mgl -1 ) with samples taken from effluents of CGF pilot units using both Gooch and spectrophometric methods. Descriptive Statistic Method Gooch Spectrophometric Mean 2.82 2.75 Standard Deviation 2.46 2.50 Minimum 0.40 0.10 Maximum 12 11 Data (number) 58 58 Based on the results obtained with samples from both pilot and full-scale plants the spectrophometric method was used for SS measurements with samples having low turbidity values, below 20 NTU. Comparison between the statistical evaluation for gravimetric and spectrophometric methods was made with t-student test verifying that the slope of these line will be 1. The result with 5% of statistical significance level indicate that does not exist statistic evidence for disprove the hypothesis. Applying the same test and statistical significance level, the result indicated that does not exist statistical evidence for deny that the Y intercepted was 0. In others words, with 5% of statistical significance level, both procedures can be used to estimate SS concentrations. Furthermore, the adopted spectrophometric method can be used for the determination of suspended solids when great amount of analyses are required because is faster than the volumetric procedure described and recommended in the Standard Methods. References APHA, AWWA and WPCF, (1989). Satandard Methods for the Examination of Water and Wastewater. Joint Editorial Board. Washington, DC 20005. USA. Sawyer, C.; McCarty, P., and Parkin, G, (1994). Chemistry for Environmental Engineering, McGraw Hill International Editions, Fourth edition. USA. Krawzyk, D. and Gonglewski, N, (1959). Sewage and industrial wastewater, Vol. 31, Pp 1159-1164. A3-2

Annex 4: Example of F-Test (Analysis of Variance) application This example presents an application of F-Test (Analysis of Variance) to mean suspended solids (SS) removal efficiencies in DyGF units during Phase I, Period I, of this research work. The statistical model used is the randomised block design as represented by equation A4-1.(Vargas, 1991) Yij = µ + τi + βj + εij (A4-1) Y ij: SS removal efficiencies in i-treatment levels (i = 1,2,3, because three DyGF filtration rates were tested during Period I) with j-blocks (j = 1,2,3,4,.......,33, because there were b = 33 blocks, sampling sessions or repetitions per each filtration rate during Period I). µ: Mean SS removal efficiency of all Y ij values, without distinguishing between treatment levels. τ i : Effect due to i-treatment level. In this case i takes values between 1 and 3. τ i represents D y GF filtration rate i tested during Period I: τ 1 . = 0.9mh -1 , τ 2 = 1.3 mh -1 , and τ 3 = 1.4 mh -1 , (t = 3). β j : Effect due to block j of observed values in each sampling session, with j changing from 1 to b, b = 33 SS-sampling sessions during Period I. ε ij : Random variation associated with the i-treatment level in the j-block of observed values (the experimental error) The basic assumption (null hypothesis) used to apply the model described in the equation A4-1 is that all observed values during test runs, divided among several groups according to treatment levels and sampling sessions, are all from the same population. This means that there are not statistically significant differences between the group means. In this case the null (H o ) and the alternate (H a ) hypotheses are as follows. H 0 : τ 1 = τ 2 = τ 3, Ha: τ i ≠ τ k (i≠k), filtration Rate differences in DyGF units do not imply statistically significant differences in the mean SS-removal efficiencies of all DyGF units, Vs, filtration Rate differences in DyGF units does imply statistically significant differences in at least a pair of DyGF mean SS-removal efficiencies. The process to accept or reject the null hypothesis (H o ), with an established level of significance (α), involves the F-Test, after the British statistician, Sir Ronald A. Fisher, who developed the method called analysis of variance (ANOVA) on which the F-test rests (Fisher, 1947, quoted by Mesa, 1999; Rowntree, 1981). The calculations required by the ANOVA technique to decide about Ho are summarised in the table A.4-1 Table A4-1 Summary of Analysis of Variance (ANOVA) with the randomised blocks design. Source of Variation Degrees of Freedom Sum of squares (SS) Mean square (MS) F c Treatment (between) t –1 SSTreat SSTreat/(t –1) = MSTreat MSTreat / MSE Blocks (between) b – 1 SSBlocks SSBlocks/(b – 1) = MSBlocks MSBlocks / MSE Error (within) (t –1)(b –1) SSE SSE/((t –1)(b –1)) = MSE Total tb - 1 SST H 0 is rejected when F c > F (α, t-1, (t-1)(b-1)), where F (α, t-1, (t-1)(b-1)) is the F-distribution with t-1 and (t-1)(b-1) degrees of freedom for the numerator and denominator respectively. α is the significance level of the test. A general notation for the observed data used in this example is shown in the table A.4-2. A4-1

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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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TABLE OF CONTENTS 1. INTRODUCTION 1

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4 MULTISTAGE FILTRATION EXPERIENCIE

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1 INTRODUCTION Water is essential f

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Table 1.2 Access to WS&S in Colombi

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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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adjustment, are among the technolog

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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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- 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
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- Page 256 and 257: R 1 = (total orifice area / lateral
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- Page 270: Table A7-1. Descriptive statistics
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- Page 280: Net present value (US$) of MSF and