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Transcript of Water Research 2005
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PROPOSAL OF A WATER TREATMENT PLANT QUALITY INDEX
This paper focuses on developing a quality index for measuring the
results of a conventional water treatment plant. It aims to provide a
useful tool that allows the effective plants comparison by means of a
methodology beyond compliance with drinking water regulations.
The research procedure used in formulating this WTPQI was based
on the methodology used in beginning of 1970s for developing the Water
Quality Index (WQI) and like this one it attempted to incorporate many
aspects of the Delphi method. Afterwards, the WTPQI was applied to ten
different Brazilian conventional water treatment plants which average
flow rate range from 100 to 4300 L/s and all of them utilize rectangularbasin as settling unit. The results pointed out the WTPQI usefulness as a
plant evaluation tool. It was verified a clear tendency that plants
achieving more elevated WTPQI is the same that achieving good
performance in terms of filtered water turbidity. In such way the WTPQI
can arise as a reliable tool to manage water supply systems in near
future.
Suggested keywords: Water treatment plant quality index, watertreatment plant evaluation, water treatment.
INTRODUCTION AND RELEVANCE
Factors limiting water treatment plant performance was usually
related to (i) the suitability between the raw water characteristics and the
treatment process train, (ii) the ratio between the influent flow rate and
the water treatment plant capability and, probably the most important,(iii) the operation accuracy. Also, the global evaluation of a plant have to
join the finished water quality which is related with the dosage and the
type of coagulant, the run filters, the possibility of short circuits and other
factors. This multiplicity of factors has been raising many difficulties to
the professionals to set up the reliable hierarchy among them. This
hierarchy would define more accurately the activities of the water supply
system managers in terms of operation and/or enlargement of the water
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without large investments also.
The option of a quality index was justified by the use of easy
available data related to the operational routine of the plant. It will permit
a good comprehension by the population (as WQI does), because in many
situations the responsible for the application of financial resources does
not have a clear knowledge about the processes concerning the water
treatment. The mentioned comprehension by the public will help the use
of the WTPQI as a tool for the population consciousness by the relevance
of a good performance of the water treatment plants, minimizing in a
second instance the outbreak risks thru the drinking water.
OBJECTIVE
The paper proposes a Water Treatment Plant Quality Index (WTPQI)
as an evaluation tool for the water supply system administrations become
the comparisons among different plants more precise. Additionally, the
paper proposes: i) to list the intervenient parameters on the performance
of water treatment plants; ii) to define an hierarchy for these parameters
according to their role in performance of the plants; iii) to validate the
WTPQI basing on the daily operational data of ten conventional water
treatment plants with different sizes.
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LITERATURE REVIEW
Optimization and Evaluation of Water Treatment Plants
The water treatment for human consumption, as one of most
important features of sanitary engineering, has been facing a clear
dichotomy last years. The successive drinking water regulations have
been presenting more restrictive in terms of the number of parameters
and their maximum levels. On the other side, there is a progressive
deterioration of the natural water quality by means concentrated and
diffuse pollution mainly as a consequence of human activities.
In a first moment more restrict levels to the filtered water turbidity
were focused on the higher efficiency of the chlorination in inactivation of
pathogenic microorganism, and in a second phase toward the perspective
to increase the protozoa removal. In this last context, many researches
have emphasized a higher removal associated to finished water with
turbidity lower than 0,1 NTU. As an example, a research was carried out
with some filters in pilot and actual scale monitored during two years. It
was demonstrated the more consistent Giardia and Crypto removal was
reached with low filtered water turbidity (0,1 to 0,2 NTU), despite the
determination coefficient was not high (r2 = 0,64). Furthermore, when the
performance of water treatment plant varied with the fluctuations of raw
water quality a high variability in cyst concentration was observed in the
effluent (NIEMINSKI & ONGERTH, 1995, apudLECHEVALIER & AI, 2004).
The development of a methodology to optimize the water treatment
plants began in USA and Canada in the end of 1980s with the objective to
increase the protection against some pathogenic microorganisms. Named
Composite Correction Program (CCP), some objectives of this
methodology were to define the best performance of sedimentation,
filtration and disinfection processes. There was established the highest
settled water and filtered water turbidity values of 2 NTU and 0,1 NTU,
respectively, with a permissible peak after backwashing of 0,3 NTU by
less than 15 minutes.
The CCP optimization concepts were expanded to many other
activities. The program Partnership for safe wateremployed CCP such as
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a basis to the development of its Phase III with the objective to improve
the treatment for a better water quality. This program was developed by
the association of six American entities, and in May 1988 217 water
treatment plants supplying more than 90 million people were taking part
of it (GUIDELINES FOR PHASE IV, 2003)
In 1984 the DEP (Department of Environmental Protection) of
Pennsylvania, with the objective to assure the distributed water quality,
made a start the implementation of the FPPE program (Filter Plant
Performance Evaluation) aiming to determine the plant effectiveness in
terms of the particle removal at same range size of the cysts and oocysts
of protozoa. Until 1996 290 plants were evaluated and in 1988 more than
60 % were producing effluent with turbidity higher than 0,2 NTU. In 1996
this percentage was reduced to 4 %.
Afterwards some CCP concepts were inserted in the FPPE
program. There was done the capacity evaluation of each water
treatment plant with a current use of standard sheets to obtain temporal
series of raw, settled and filtered waters. By means the comparison of
these graphs there was possible to assess the plant capacity to produce
better quality water despite the changes of raw water (CONSONERY et al.,
1997).
The Delphi Methodology
The Delphi method concept can be understood as a product of a
Rand Corporation project in 1950s, concerning the application of the
opinion of specialists. It can be developed in two different techniques. The
more common is the pen andpaperversion. In this situation, a monitor
elaborates a questionnaire that is sent to a group of respondents. When
these questionnaires return, the monitor summarizes the results and
basing on them develops a new one. The group of respondents has at
least one chance to change his opinion. This technique is known
conventional Delphi. The other one, named Delphi conference, the
monitor is substituted by a computer program, which makes the printout
simultaneously and returns the responses to the respondents. After the
last response, the software makes a report and the new questionnaire.
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This method has an advantage to carry out the process in real time. In
both ways, some characteristics define the method: (i) the anonymity; (ii)
the interaction; (iii) the feedback; (iv) the statistical representation of the
results (LINSTONE & TUROFF, 1975).
Taylor & Ryder (2003) utilized the Delphi methodology to define a
management plan of 25 multiple uses reservoirs. This information
concerned basically the necessary water levels to guarantee the survival
of fishes. Questionnaires were elaborated for each reservoir and were
sent to 26 specialists and the number of respondents by reservoir varied
from 2 to 8. It was possible to the same specialist answered questionnaire
related to more than one reservoir. The first questionnaire asked them
about a list of the more vulnerable species and the period in which each
species was particularly sensible to the variations of the reservoir level. In
the second questionnaire, the specialists reevaluated their responses in
function of the opinion of the entire group. The research has gotten a
return of 85 % and a high convergence of opinions for all reservoirs. The
research showed the applicability of Delphi methodology to deal with
several information to the management of complex environmental
questions.
The index development
The transmission in an intelligible way to the population the data
and the parameters of water treatment plants is not an easy task.
However, it is not a question restricted to this specific area. There were
many efforts trying to reproduce in only value the meaning of a data set.
Brown et al. (1970) employed the Delphi methodology to develop
the Water Quality Index (WQI) based on the opinion of a group of 142
water quality specialists. This research was composed by three
questionnaires. In the first a list with 35 parameters, randomly selected,
was sent to the group. For each parameter, the respondents had to
choose among three options: include, no include and undecided. There
was possible to include other parameters that were absent in this first list.
The respondent had to assign values for each parameter selected as
include from 1 to 5.
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The results of this first round were sent to the respondents with the
second questionnaire opening the possibility to the respondents compare
their responses with the other ones, and, occasionally, reevaluate them.
There was a request of a list including the 15 most important parameters.
In the third questionnaire, for each one of the 9 selected parameters, the
respondent had to draw a curve as, in his judgment, the best way to
represent the influence of this parameter in water quality. The nine
average curves employed to define the WQI were a combination of the
responses of all respondents. Among 142 specialist invited in the first
round, 94 (66 %) returned the first questionnaire in time to take part in
the second round, and from this group 82 % completed and returned the
second questionnaire.
The WQI value was defined upon a sum represented by the
Equation 1:
=
=n
i
ii qwWQI1
(1)
in which:
WQI: the water quality index, a number between 0 and 100;
wi: the unit weight of ith parameter, a number between 0 and 1;qi: the quality of the ith parameter, a number between 1 and 100,
extracted from the respective curve;
n: number of parameters.
Based on the same methodology employed in the development of
the WQI, Nages et al. (2001) proposed an index system to assess the
recreation water quality in New Zealand. They used the Delphi
methodology to resume the judgment of 18 specialists from consultingengineering, environmental management companies, research institutes
and universities.
The remarkable new in this research was the final definition of the
index. Distinctly of the WQI, there were not established weights for each
parameter and the index of a specific water source will be the lowest
value extracted from these curves. The justification was an aggregation of
many individual scores could hide a low value of a specific parameter.METHODOLOGY
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The present work can be defined such as an applied research with
the objective to provide a quantity tool to help the water supply system
managers, and a quality one to classify the performance of the water
treatment plants by means numerical methods. The universe of this
research was limited by the conventional water treatment plants, with
horizontal sedimentation basins, treating typical raw water to produce
filtered water turbidity lower than 0,5 NTU and absence of total coliform
in compliance to the Brazilian Drinking Water Standards.
The methodology to formulation the WTPQI was based on the same
utilized to the development of the WQI. In such way, after the
establishment of all parameters, and respective weights and grading
criteria, there were defined two different formulations in terms of a
summation and a multiplicative forms:
i
N
i
n
j
QjWjWTPQI = =
=
1 1
(2)i
N
i
n
j
WjjQWTPQI
= =
=
1 1
(3)
where:
Wj: weight rated to each parameter established by the judgment of the
specialists;
Qj: value rated to the water treatment plant for each parameter selectedaccording to the developed criterion;
j: each parameter included in the index;
i: each group of parameters to comprise the index such as rapid mix,
flocculation, sedimentation, filtration, disinfection, and operational
factors;
n: number of parameters included in the index;
N: total number of groups of parameters that will constitute the index.The methodology to the development of the WTPQI was divided in
three phases (opinion research, definition of the grading criteria, and the
index validation) as follow.
Opinion research
There was carried out an opinion research to select the intervenient
parameters to be included in the WTPQI, and the respective weights, with
18 professionals with expertise in water treatment. Of the total panel, 16completed and returned both questionnaires. The group was selected
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focusing different professional formations and distinct geographical areas
of Brazil.
This research was constituted in two different phases according to
the Delphi characteristics. After the literature review, there was
elaborated a first list of the intervenient parameters in water treatment as
shown in Table 1.
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TABLE 1- Parameters included in the first questionnaireGRM Rapid Mix Velocity Gradient VF Flow-through VelocityTRM Rapid Mix Detention Time QL Weir Loading Rate
Jtest Routine Jar Test Realization Tfilt Filtration RateGf Flocculation Velocity Gradient Drf Run FilterTf Flocculation Time Exp Filter bed expansion
Gp Velocity gradient thru the ports of flocculator Vupf Upflow water wash velocityNc Number of compartments Lair
Washing with auxiliary airscour
VcAverage velocity in the flocculated waterchannel
Lwater
Washing with auxiliary surfacewater system
GpsVelocity gradient thru the ports ofsedimentation basin
Tc Detention time in the clearwell
GinVelocity gradient thru the inlet baffle ofsedimentation basin
NclNumber of compartments ofthe clearwell
VsSedimentation Surface Loading Rate orTerminal Settling Velocity
ILInstruction level of theoperational staff
This list was utilized in the elaboration of the first questionnaire sent
to 18 professionals selected. The panel was composed by graduate
professionals responsible by researches in water treatment, designs and
operation of water treatment plants, regarding universities, sanitation
companies and consulting engineering of six Brazilian states in the two
most developed and populous regions like showed in Table 2.
TABLE 2: Professional fields of participants in the panel
Plant operator 2Designer 4Researcher 7
Researcher/Designer
1
Designer/Operator
1
Researcher/Operator
1
The first questionnaire was divided in three parts. The first one has
presented an introduction explaining all phases of research and showing
to the participant his role in it. The second part has explicated all
instructions for a correct filling of the questionnaire. Finally, the third part
was constituted by the initial list (Table 1) of the parameters which the
respondent would have to evaluate by one the categories include, no
include and undecided, and he could suggest additional parameters
absent in the first list. After his judgment, the respondent would have to
rate (up to 100) only those parameters marked include according to their
relevance to water treatment.
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After the finish of the first phase, there was elaborated a report with
numerical summary of the responses of all participants. It was
incorporated in this report the inclusion percentage of each parameter,
average, median, mode, quartiles, and an abstract of the commentaries,
the participants responses and a column to review their initial responses.
After an evaluation of the opinion of the entire group, the respondents
were asked to review their responses, keeping or modifying them.
The parameters included in the index were divided into six groups
according to the step of the conventional treatment such as, per example,
Rapid mix, Flocculation, Sedimentation, Filtration, Disinfection, and
Operational quality. Based on the weights rated to the parameters by the
panel it was determined the weight of each group in function of the
treatment effectiveness. The main reason for the separation in groups
was the possibility to comprise a complete index, formed in function of
the indexes of each step of the water treatment. In such way, it will be
possible to identify which group is responsible by an eventual low grade
of the water treatment plant.
Development of the grading criteria
After the definition of the parameters included in the index and their
respective weights, the following phase of the research was begun. In this
phase it was established the grading criteria based on the premises set
up by the Brazilian Technical Standards Association (1990) and the
literature.
Validation of the WTPQI
The final phase of the research was composed by a comparative
study between the final grade provided by the index to a specific water
treatment plant and the monitoring data in terms of filtered water
turbidity. The scope of this last phase was to choose the final formulation
of the index (summation or multiplicative), and to verify the validation of
the grade provided by the index to the treatment. In other words,
whether the water treatment plant evaluated with a high WTPQI had
presented a good performance concerning the filtered water turbidity.
With this objective, the developed index, in summation and
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multiplicative forms, was applied to ten conventional water treatment
plants of two most important Brazilian states with average flow rate range
from 100 to 4300 L/s. These plants were selected according to the
easiness of access and the reliability of the monitoring data provided by
the respective directions.
The comparison between the WTPQI and the filtered water turbidity
was done with tables in which were presented the day, the WTPQI
(summation and multiplicative), and the mean values of filtered water
turbidity for six months data of 2003 and 2004 (three months related to
the drought season and three months to the rainy season). There were
calculated the following values for each season according to the Brazilian
and American Drinking Water Standards:
time percentage of the operation plant with filtered water turbidty
0,5 NTU;
time percentage of the operation plant with filtered water turbidty
0,3 NTU;
time percentage of the operation plant with filtered water turbidty
0,1 NTU;
value lower than 95% of the filtered water turbidity values.
For verifying whether the WTPQI was correlated to the filtered water
turbidity values, there were calculated linear and non-linear correlation
coefficients. This analysis focused to assess whether an occasional
reduction of the WTPQI was followed by higher filtered water turbidity
levels.
The last analysis was based on the premise about a plant with good
performance probably will produce a high water quality even when a
variable raw water quality as influent, or the finished water turbidity will
not change with occasional alterations of raw water characteristics. For
this, there were calculated the correlation coefficients (r) among raw,
settled and finished waters for each plant.
RESULTS AND DISCUSSION
Participants responses and the definition of the weights for each
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parameter
The first round of the research was carried out from January to April
2004 with 89 % of returning among 18 questionnaires. The
justifications and comments from the first questionnaire were sent to
the respondents in the second round with the objective to show the
opinions of the other participants. No parameter listed in the first
questionnaire (Table 1) was dismissed, and among the parameters
suggested by the respondents none was inserted in the second round
because the necessary information about them was not easily
accessible or the parameter was very subjective. Per example, there
were some suggestions in terms of general situation of the
laboratory, plant versatility, and others. Other kinds of suggestions
concerning the raw water quality were not accepted because this
index focused to evaluate the treatment despite the raw water
characteristics. Beyond this fact, none new parameters were
suggested by more than three respondents.
As previously mentioned, the respondents were instructed to assign
values from 0 to 100 for only the selected parameters marked include.
This rating system was chosen to become easier the filling of the
questionnaires because. However it was relevant the relative importance
of each parameter and the weight assigned by the respondent in a
proportion with the total points distributed by him. Therefore, the final
score of each parameter was divided from the total points distributed by
the respondent and the sum of all distributed points have totalized 100.
It is shown in Figure 1 the relative importance of each parameter in
terms of global performance of the water treatment plants. According to
the panel, the rate filtration is the most relevant parameter, answering by
approximate 9 % of the performance, agreeing with the tendency of the
national and international water drinking standards to reduce the finished
water turbidity. The settling velocity and the flocculation velocity
gradient, with the filtration rate, were responsible by 23 % of the plant
efficiency. The first parameter represents the assurance of the settling of
flocs and the second the suitable formation of them.
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FIGURE 1: Accumulated median of the weights of each parameter
By the observation of the vertical bars shown in Figure 1, it is
possible to verify the highest ranges among the responses to the most
significant parameters, emphasizing the agreement of the respondents
concerning the relevance of them, but a clear disagreement in terms of
the weight to be assigned.
Based on these results, the weights for the WTPQI determination
would have to be defined. In this context, what would be the best way for
this scatter of results? Maybe other rounds could help to reach a higher
convergence, but this option was not suitable in function of the time
expended in each round. Moreover, it should be noted there was a little
change expressed in the second questionnaire and several respondents
did not modify their scores. In such way, two important decisions were
taken to the definition of the final weights: (i) avoiding the influence of
extreme points, the median was chosen as the best measurement of the
group opinion; (ii) all parameter were included and the weights weremultiplied by the inclusion rate of each parameter, so the parameters
with 100 % inclusion rate had their weights were kept, and the others had
theirs reduced.
For the development of grading criteria some parameters were
unified. As an example, the Tf and Gf parameters were rated as a couple
and the weight is the sum of each one. The Lair and Lwater parameters were
transformed in only parameter named Laux (auxiliary wash), the weight ofit was defined as a median of all weights assigned to them. In the same
14
TFILT
Vs
Gf
IL
GMR T
f
Jtest
QL
Gin T
cGp
Gps
Drf
Vupf
VF
Vc
Exp
TMR
Nc
LAIR
Ncl
LWATER
0 , 0 0
0 , 0 5
0 , 1 0
0 , 1 5
0 , 2 0
0 , 2 5
0 , 3 0
0 , 3 5
0 , 4 0
0 , 4 5
0 , 5 0
0 , 5 5
0 , 6 0
0 , 6 5
0 , 7 0
0 , 7 5
0 , 8 0
0 , 8 5
0 , 9 0
0 , 9 5
1 , 0 0
1 , 0 5
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context, it was defined the group of Exp and Vupfparameters because the
inclusion of both would be overrating the same aspect related to the bed
filter wash. Finally, the last transformation was carried out dividing each
weight from total score, for all weights sum was 1. The final weight of
each parameter is shown in Table 3.
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TABLE 3: Final weights of all parameters
GroupParame
terWeight
Group Parameter
Weight
Rapid MixGMR 0,06 Filtratio
nTfilt 0,09
TMR 0,03 Drp 0,04
Flocculation
Gf-Tf 0,14 Exp 0,04Gp 0,04 Laux 0,03Nc 0,03 Disinfect
ionTc 0,05
Vc 0,03 Nl 0,02
Sedimentation
Gps 0,04 Operation
Jtest 0,07Gin 0,05 IL 0,06Vs 0,08VF 0,04QL 0,06
Development of grading criteria
After the definition of weights for each parameter there was
necessity to establish the grading criteria. In reality, this definition is
substituting the mentioned curves drawn by the respondents for the WQI.
In this phase, as explicated in the methodology, the parameters were
divided into six groups: Rapid mix, Flocculation, Sedimentation, Filtration,
Disinfection and Operation.
Due to the limit to the size of the paper, there will be detailed,
among 19 parameters, only the settling velocity (surface loading rate)
integrating of the group Sedimentation. The function of this step of
treatment is to remove by gravity the flocs to lower the solids
concentration on filters. Among the intervenient factors to the
sedimentation effectiveness the more important are the settling velocity,
the inlet and outlet arrangements, and sludge removal.
The high variability of size, density, and particle shape has been
presenting difficulty to develop a mathematical model for flocculant
settling. In such way, the ideal horizontal-flow sedimentation basin, even
its simplicity, was applied to estimate the particle behavior. Some simple
suppositions characterize this model: (i) in sedimentation zone the
particles settle in analogous way as in rest tank with the same depth; (ii)
the flow and particle concentration are uniform all over the transversal
section; (iii) there is not scouring when the particles reach the sludge
zone.
The grading criterion was defined based on the rate Vs/Vs,
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considering Vs the surface loading rate with a progressive increasing of 5
% from the design rate on and Vs was considered the highest surface
loading rate established by The Brazilian Technical Standards Association
(40 m3/m2.day). Of course, all plants which sedimentation basins were
operating with surface loading rates lower than that received the
maximum grade.
In a real sedimentation basin the terminal settling velocity of the
particles tends to increase in function of the differential settling. In this
way the sedimentation effectiveness will be higher than that estimated by
the ideal model. In contrast with differential settling, the wind effects, the
different temperatures, the currents as a result of distinct densities, and
other factors caused short-circuits, floc rupture and scouring of settled
sludge reducing the sedimentation efficiency. Due the difficulty to
synthesize the influence of these factors and considering the positive
effects of differential settling can compensate these negative effects, for
the Vs grading criterion, shown in Figure 2, it was utilized the ideal model
already described.
Vs
0
10
20
30
40
50
60
70
80
90
100
0 10 20 30 40 50 60 70 80 90 100 110 120
Vs (m3/m2.d)
Score
1000m3/day 1000 < Cap < 10000 m3/day >10000m3/day
FIGURE 2: Grading criterion established for Vs
WTPQI Application
Finally, after the definition of the weights and the grading criteria
the final phase of the research was to apply the WTPQI, in multiplicative
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and summation forms (equations 2 and 3), to ten water treatment plants.
The plants were not identified because the focus of this research was to
evaluate the applicability of the WTPQI, and there was no intention to
assess the plant performance which managers permit the free access to
the plant data. As previously mentioned, there were utilized six months
data, in terms of drought and rainy seasons for three months each. As an
example, the WTPQI was calculated and presented in Table 4.
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TABLE 4: Determination of the WTPQI for one of the plants of the sample
GroupParameter
Daily datamedian for
eachparameter in
six months
Score
Weights
Weights xScore
Weights ^Score
Score bygroup(Sum
)
Score bygroup
(Mul)
Rapid MixGMR (s-1) 1340,65 100 0,06 6,00 1,32 9,00 1,52TMR (s) 0,40 100 0,03 3,00 1,15
Flocculation
GF (s-1) 35,18
30 0,14 4,20 1,61
9,04 2,09
TF (s) 835,87Flocculator type
Hydraulic
Gp (s-1) 55,11 1 0,04 0,04 1,00Nc 5 60 0,03 1,80 1,13Vc (m/s) 0,29 100 0,03 3,00 1,15
Sedimentation
Gpss-1) 19,29 100 0,04 4,00 1,20
25,24 3,40
Gin (s-1) 8,19 100 0,05 5,00 1,26
Vs(cm/min) 3,02 80 0,08 6,40 1,42
VF (cm/s) 0,26 100 0,04 4,00 1,20QL (L/s.m) 1,64 100 0,06 6,00 1,32
Filtration
Filter typeDownflow
Dual media100 0,09 9,00 1,51
17,03 2,17
Tfilt(m/dia)
279,66
Drf Filteredvolume(m3/m2/run)
475,30
100 0,04 4,00 1,20Washwater volume(m3/m2/filter)
6,06
Exp (%) 32 100 0,04 4,00 1,20
LauxSurface wash(scrapping)
1 0,03 0,03 1
Disinfection
ResidualCl (mg/L)
0,8710 0,05 0,5 1,12
1,5 1,21
T (min) 1,47pH 7
Ncl
The water was
introduced inthe bottom ofthe tank and,
after thechlorine
dosage, flowedover a chicane
50 0,02 1 1,08
Operation
IL Superior 100 0,07 7,00 1,38
13 1,82Jar test
According tothe change of
raw waterturbidity
100 0,06 6,00 1,32
WTPQI 74,81 51,62
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After the WTPQI determination, the main point was the final
definition by multiplicative or summation forms for the WTPQI equation.
The distinction between both equations was focused in the possibility of a
plant with a low grade, in a specific parameter, has its final score more
significantly affected when the multiplicative form is utilized. The plants
with a more uniform grading among the parameters keep the final score
approximately constant by both equations. The question, which answer
intends to reach in the following analysis, is: only parameter with low
score will have a significant impact in the global performance of the plant
is able to justify the option by the multiplicative form of the WTPQI
equation?
For evaluating the applicability of the index, its values were
compared to filtered water turbidity. This comparison was done by means
scatter graphs determining the correlation between The WTPQI (in both
forms), and the percentage of daily mean values of filtered water lower
than 0,5 and 0,3 NTU. Also, there were made graphs in terms of the
WTPQI and the turbidity value higher than 95 % filtered water turbidity
values. For the last validation of the WTPQI, there was accomplished
another scatter graph concerning the index and the daily filtered water
turbidiy. With the exception this last graph, all ones were divided in
drought and rainy season.
The correlation was exploited to evaluate the association degree
between the index and the filtered water turbidity percentage lower than
a previous established value. The filtered water turbidity was selected as
the mark to assess the WTPQI applicability because, besides to be a
parameter of treatment effectiveness, all plants have been monitoring it.
For a better comparison among the obtained values, they were
organized in Table 5, outstanding the more significant results (R2), and
also including the correlation with the percentage below 0,7 NTU, as an
intermediary between the maximum level (1,0 NTU) and the
recommended 0,5 NTU. For the rainy season, it is possible to observe that
the multiplicative form (Equation 3) presented more significant results
when compared with the filtered water turbidity percentage lower than
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0,1 and 0,3 NTU, and with the value higher than 95 % of turbidity data.
On the other hand, the summation form (Equation 2) has showed more
significance for the percentage lower than 0,5 and 0,7 NTU. However, in
the drought season, despite the better results with summation form, the
WTPQI values were correlated with high p values. This fact indicates a no
correlation among these variables.
Table 5 Linear correlation coefficients (R)Percentage of filtered water turbidity values below the established limit
Rainy Season Drought Season
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the answer is yes. Based on this analysis it is supposed that only
parameter, such as Vs or Gcor, can affect the plant performance as much
as to decide by a final low grading even all other parameters are suitable.
This decision was confirmed by the highest correlation values for the
WTPQI multiplicative when more restrict filtered water turbidity standards
were utilized.
Afterwards, it was evaluated whether establishing of goals to the
filtered water turbidity was inducing to a correlation between then and
the WTPQI. In this context, there were elaborated scatter graphs between
the daily WTPQI values and the daily average of filtered water turbidity,
for ten plants with six months data. It was characterized a correlation
between then, a little higher to the summation form for the linear
correlation (r) and the same to the multiplicative form in terms of the no-
linear correlation (Table 7).
Table 6: Correlation between filtered water turbidity and the WTPQI for alldataR r2
WTPQI - S -0,47 0,22 -0,37
WTPQI - M -0,39 0,15 -0,42
With the finality to evaluate the possible correlation between the
raw water and settled water turbidity, and between the settled and
filtered water turbidity, the linear correlation coefficients were calculated
for all plants which data were available, as shown in Table 8.
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Table 7: Correlation between turbidity values of Raw/Settled Water and Settled/Filtered Water
Plants
Raw Water/SettledWater
Raw Water/FilteredWater
R r2 R r2
WTP 1 0,557 0,310 0,130 0,017
WTP 3 0,571 0,326
WTP 4 0,778 0,605WTP 5 0,527 0,278 0,636 0,405
WTP 6 0,561 0,314 0,475 0,226
WTP 7 0,451 0,204 0,399 0,159
WTP 8 0,754 0,569 0,642 0,412
WTP 9.A 0,714 0,510 0,652 0,425
WTP 9.B 0,532 0,283 0,783 0,613
WTP 9 B and A Before and after enlargement
The plants with good performance have to be able to produce
constant quality filtered water independently of the raw water quality. Infunction of this premise and the Table 8 data, the WTP 7 presented the
best results for sedimentation and the WTP 2 the same for filtration. On
the other hand, the WTP 4 and the WTP 9B presented the worst
performance for sedimentation and filtration, respectively.
In this context, another question arose. Do the water treatment
plants producing filtered water with a regular quality have the higher
WTPQI values? Trying to solve this question, there were elaborated thegraphs shown in Figure 3, with the WTPQI (summation and multiplicative
forms) on the horizontal axis and the r2 values (obtained for settled and
filtered water) on the vertical axis.
r 2 ( s e t t le d t u r b i d i t y / fi l t e r e d t u r b i d i ty ) x W T P Q I
W T P Q I S u m m a t i o n : r 2 : r 2 = 0 , 0 2 8 7 ; r = 0 , 1 6 9 3 , p = 0 , 7 1 6 7
E T A I I
E T A V
E T A V I
E T A V I I
E T A V I I IE T A I X . A
E T A I X . B
7 6 7 8 8 0 8 2 8 4 8 6 8 8 9 0 9 2 9 4
W T P Q I S u m m a t io n
- 0 , 1
0 , 0
0 , 1
0 , 2
0 , 3
0 , 4
0 , 5
0 , 6
0 , 7
r2
r 2 ( s e t t l e d t u r b i d i t y / f i lt e r e d t u b i d i t ) x W T P Q I
W T P Q I M u l t ip l ic a t iv e f o r m : r 2 : r 2 = 0 , 1 9 7 1 ; r = - 0 , 4 4 3 9 , p = 0 , 3 1 8 4
E T
E T A V I I
E T A V I I I
6 4 6 5 6 6 6 7 6 8 6 9 7 0 7 1 7 2 7 3 7 4 7 5 7 6 7 7 7 8
W T P Q I M u l t i p l i c a t i v e f o r m
0 , 1 5
0 , 2 0
0 , 2 5
0 , 3 0
0 , 3 5
0 , 4 0
0 , 4 5
0 , 5 0
r2
FIGURE 3: Scatter plots r2 x WTPQI for summation and multiplicative forms(rainy season)
It was observed in these graphs that the affirmative answer for theprevious question was completely rejected for the WTPQI summation.
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Despite its low magnitude, for the multiplicative form, the results were
significantly better than those obtained by the summation form.
The supremacy of the WTPQI multiplicative can be confirmed
comparing it with the correlation between settled and filtered water
turbidity. In other words, the plants with the lowest WTPQI multiplicative
values presented too the lowest correlation between settled and filtered
water turbidity. Also, the WTPQI usefulness was verified by the
comparison of the results obtained by the WTP B and WTP A,
demonstrating the index sensibility to the plant improvements followed
by the enhancing of filtered water quality.
CONCLUSIONS
It was verified that two rounds were not enough to reach a higher
consensus among the respondents for a definition of the weights mainly
to the more relevant parameters. For some parameters the dispersion
increased after the second round. Concerning the parameters hierarchy,
the questionnaires demonstrated an evident consensus about the more
relevant to the treatment effectiveness. According to a tendency of the
national and international standards, which have been emphasizing
progressively the reduction of filtered water turbidity, the rate filtration
was chosen the most relevant parameter by the panel.
Despite some limitation in function of the sample size of ten water
treatment plants, the significant correlations pointed out a tendency of
the plants producing good filtered water quality usually present high
WTPQI values. The higher correlation values were presented to the WTPQI
multiplicative when more restrict standards were established. However,
for plants with high scores in all parameters the final WTPQI is
approximately the same for both formulations.
Based on the premise of plants with good performance must be able
to produce regularly high filtered water quality, despite the changes of
raw water, the WTPQI multiplicative was more efficient than the WTPQI
summation. It was evident when the comparison was made in terms of r2
values between settled and filtered water turbidity, showing more
sensible and able to classify the plants, conferring better scores to those
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with a more accurate performance.
Finally, the correlations confirmed the principles in which the
grading criteria for 19 parameters were based on, and the WTPQI
multiplicative as a good indicator to make the plants hierarchy. In this
way, the WTPQI multiplicative may be an interesting tool to the water
supply system administrations.
RECOMMENDATIONS
Evidently, a more complete analysis has to involve, besides the
WTPQI and the finished water quality, an index for the raw water in terms
of its higher or lower treatment feasibility. New researches may improve
the WTPQI increasing its accuracy, basing on the disagreements arose in
these two rounds. Also, a research opinion about the developed grading
criteria may contribute significantly to the better index accurateness.
Finally, the WTPQI application to a higher number of plants would be
useful to confirm, or not, this tendency.
REFERENCES
BRAZILIAN TECHNICAL STANDARDS ASSOCIATION (ABNT) Water
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CONSONERY, P. J.; GREENFIELD, D N. & LEE, J. J. - Pennsylvanias filtration
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NIEMINSKI, E. C. & ONGERTH, J. E. Removing Giardia and Cryptosporidium
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