waste management

1. Main Stages of Water Treatmnet Plant

2. Pulsator Mechanism
 Works like a gentle up-and-down
motion in the clarifier.
 This movement helps to shake up
the particles and encourage them
to settle down, making it easier to
remove impurities and clean the
water effectively.

3. Main Objectives
 Determine the most effective alum dose within a
specified range for optimal coagulation in the
water treatment process.
 Evaluate and understand the performance
variations among the four clarifier phases to
identify the most efficient phase for water
treatment.

4. Water Treatment Terminology and
Definitions
Turbidity : Cloudiness or haziness of water due to suspended particles like sediment, silt, and
organic matter. Measured in nephelometric turbidity units (NTU).
pH : Measure of the acidic or basic nature of the solution.
Alkalinity : Measurement of the water buffering capacity/ability to resist changes of pH with
addition of acid or base.
Alum : Aluminium sulphate, is a common coagulant used in water.
treatment processes.
Coagulant : Chemical substances added to water during treatment to remove suspended
particles and contaminants.
Raw water : Untreated water from its natural source, such as rivers, lakes, or groundwater.

5. Methodology
01. Data Pre-processing
Cleaning, transforming, and organizing raw data to make it suitable for
analysis.
02. Descriptive Statistics Summarize and describe the main features of a dataset.
03. Data Visualization
Graphical representations of data to help understand trends, patterns,
and relationships.
04. Check Normality and Homogeneity
of Variance
Before using ANOVA, check the data meets the assumptions of
normality and homogeneity of variance.
05. Mean Comparison
Determine the most effective clarifier and the optimal range of alum
dosage for water treatment.
06. Efficiency Calculation
Assessing the turbidity removal efficacy across different phases of
treatment
The dataset was analysed with R software and organized
with MS Excel, including efficiency calculations.

6. Results and
Discussion

7. Find the most appropriate Alum dose range
 Alum doses range 25mg/L and 30mg/L, have stable levels. But dose 10 shows spikes.
 pH values show inverse relationship with alum dose.

8. Correlation Analysis
 Alum and pH - Strong negative correlation
 Alum and turbidity - Moderate negative correlation
 Alum and alkalinity - Weak negative correlstion
Alum releases hydrogen ions (H⁺) when it dissolves.
Help to flocculation process.

9.  Acceptable levels of drinking water
quality range for,
• Turbidity - Below 2 NTU
• pH - Between 6.5 to 8.5
• Alkalinity - Below 200ppm
 Lowest turbidity value of 0.8803 NTU
was recorded at at 30 mg/L alum dose.
Mean Values of Turbidity pH and Alkalinity with Alum
Dose

10. Mean Values of Turbidity with Alum Dose
 Turbidity of the water generally
decreased due to the alum's
ability to clump together particles.
 At a certain point, adding more
alum caused turbidity to increase
because of the excess alum in the
water.
 We can suggest 20-40 mg/L (30 ±
10) range was the appropriate
dose range for Jar test.

11. Compare and find the best clarifier
 Sharp peak occurs around day 150, but clarified water turbidity consistently maintains low levels
across all phases.
 Raw water pH fluctuates between 7 and 8.5, and clarified water pH maintains stable levels within 7
to 8 range within 5 months in four phases.

12. Correlation Analysis
 Raw water turbidity and the turbidity of the four phases of clarified water are weakly
positive correlated.
 It indicating that the clarifier system can accommodate a wide range of turbidity levels
without significant fluctuation.

13. Normality and homogeneity of variance
Phase P value of turbidity P value of pH
Clarified Water 01 0.2793 0.2682
Clarified Water 02 0.4361 0.7632
Clarified Water 03 < 0.0001 0.8728
Clarified Water 04 0.0019 0.0026
 CW1_Turb, CW2_Turb, CW1_pH,
CW2_pH, and CW3_pH approximately
normally distributed.
 CW3_Turb, CW4_Turb and CW4_pH
indicate a deviation from normal
distribution.
 Levene's Test showed that the variances of turbidity levels across four phases of clarifiers are
not uniform and p-value of 0.3404 ( > 0.05) indicating equal variances of pHs.

14. 3.1.4. Kruskal Wallis Test and Wilcoxon Rank Sum Test
 The Kruskal Wallis Test, with a small P-value (2.2 × 10−16
) revealed significant differences in
turbidity and pH levels across four clarifier phases.
Comparing Means P value of turbidity P value of pH
CW_1 and CW_2 < 0.0001 0.0023
CW_1 and CW_3 < 0.0001 0.0002
CW_1 and CW_4 < 0.0001 < 0.0001
CW_2 and CW_3 0.9785 < 0.0001
CW_2 and CW_4 < 0.0001 < 0.0001
CW_3 and CW_4 < 0.0001 0.0336
 No significant difference in turbidity
levels between CW2_Turb and
CW3_Turb.
 Other turbidity pairs indicate strong
evidence of significant differences
between these groups.

15. Boxplot and Mean graph
 CW3 and CW2 showed similar turbidity median, with CW3 having larger variance.
 CW4 had the lowest median and mean turbidity values, demonstrating its exceptional
performance in clarifying water.

16. Turbidity Removal Efficiency
Efficiency(%) =
𝑹𝒂𝒘 𝒘𝒂𝒕𝒆𝒓 𝒕𝒖𝒓𝒃𝒊𝒅𝒊𝒕𝒚 − 𝑪𝒍𝒂𝒓𝒊𝒇𝒊𝒆𝒅 𝒘𝒂𝒕𝒆𝒓 𝒕𝒖𝒓𝒃𝒊𝒅𝒊𝒕𝒚
𝑹𝒂𝒘 𝒘𝒂𝒕𝒆𝒓 𝒕𝒖𝒓𝒃𝒊𝒅𝒊𝒕𝒚
∗ 𝟏𝟎𝟎

17. Turbidity Removal Efficiency
 The efficiency graph illustrates significant fluctuations in April, July, and September across
the four phases of clarifiers.
 CW4 is the most efficient phase for turbidity removal in water treatment processes.

18. Conclusion
 According to the results, the best alum dosage range for jar testing is 20 – 40 mg/L
(30 ±10), which indicates the ideal dosage for efficient particle removal.
 After a detailed comparison of turbidity levels between the clarifier phases, phase 4
showed the best technique for removing turbidity.
 Based on these findings, we can leverage the clarified water phase 4 mechanism to
enhance the quality of drinking water and use it for other phases.
 Additionally, the optimal turbidity removal range identified in the jar test results
suggests an effective approach for achieving improved water clarity.

19. References
Issa, H. (2017). Evaluation of Water Quality and Performance for a Water Treatment Plant: Khanaqin City
as a Case Study. Journal of Garmian University, 3(Khanaqine Conference), 802–821.
https://doi.org/10.24271/garmian.64
Khudhair, Z. S., Zubaidi, S. L., Ortega-Martorell, S., Al-Ansari, N., Ethaib, S., & Hashim, K. (2022). A
Review of Hybrid Soft Computing and Data Pre-Processing Techniques to Forecast Freshwater Quality’s
Parameters: Current Trends and Future Directions. https://doi.org/10.3390/environments9070085
Kowalik, T., Bogdal, A., Borek, Ł., & Kogut, A. (2015). The effect of treated sewage outflow from a
modernized sewage treatment plant on water quality of the Breń river. Journal of Ecological
Engineering, 16(4), 96–102. https://doi.org/10.12911/22998993/59355
Marinović Ruždjak, A., & Ruždjak, D. (2015). Evaluation of river water quality variations using multivariate
statistical techniques: Sava River (Croatia): A case study. Environmental Monitoring and Assessment,
187(4), 1–14. https://doi.org/10.1007/s10661-015-4393-x
Nordmann, E., McAleer, P., Toivo, W., Paterson, H., & DeBruine, L. M. (2022). Data Visualization Using R
for Researchers Who Do Not Use R. Advances in Methods and Practices in Psychological Science, 5(2).
https://doi.org/10.1177/25152459221074654

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21. ● Pulsator technology
The sludge formed during flocculation is made up of an expansion mass called “sludge bed”. Water,
that has coagulated beforehand, arrives from the bottom of the device and flows through this sludge
bed to emerge clarified at the top of the settling tank. The sludge bed is kept in expansion with the
help of a pulsating operation.
● vacuumizing
The air chamber is depressurised by pumping out the air that it contains resulting in a gradual rise in
level until a height of 0.6 to 1 m above the water level is reached. During this phase, the sludge bed
settles down with the effect of gravity.
● flushing – decompression
When the high level is reached in the air chamber, the vacuum-breaking valve opens; water then
flows at great speed through the manifolds creating a flushing effect. The sludge bed is
decompressed. The excess sludge (water impurities and reagents) flows into the concentrators
where it is extracted at regular intervals.
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