Your SlideShare is downloading. ×
0
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Persentation
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×
Saving this for later? Get the SlideShare app to save on your phone or tablet. Read anywhere, anytime – even offline.
Text the download link to your phone
Standard text messaging rates apply

Persentation

569

Published on

0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total Views
569
On Slideshare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
Downloads
10
Comments
0
Likes
0
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
No notes for slide

Transcript

  • 1. ‫الرحيم‬ ‫الرحمن‬ ‫ال‬ ‫بسم‬ ‫العظيم‬ ‫ال‬ ‫صدق‬ ‫ال‬‫ية‬85‫ال‬ ‫سورة‬‫إسراء‬
  • 2. STUDYING CONSTRUCTED WETLANDS PERFORMANCE IN TREATING WASTEWATER By Abdallah Abdelazim Mahmoud M. Sc. of Sanitary Engineering Environmental Engineering Department Faculty of Engineering Zagazig University
  • 3. Dr.Dr. Diaa Eldin A. ElqussyDiaa Eldin A. Elqussy Prof.&Prof.& Ex-Deputy ChairmanEx-Deputy Chairman National Water Research CenterNational Water Research Center Dr.Dr. Ahmed Awad MohamedAhmed Awad Mohamed Prof.Prof. && Head of Agronomy DepartmentHead of Agronomy Department Faculty of Agriculture Suez Canal UniversityFaculty of Agriculture Suez Canal University Dr.Dr. Hazem Ibrahim M. SaleHazem Ibrahim M. Sale Prof. of Sanitary &Prof. of Sanitary & Environmental EngineeringEngineering Faculty ofFaculty of EngEng.. MenoufiaMenoufia UniversityUniversity Dr.Dr. Mahmoud Abd El-Shafy IbrahimMahmoud Abd El-Shafy Ibrahim Prof. of SanitaryProf. of Sanitary && Environmental EngineeringEngineering Faculty ofFaculty of EngEng.. MenoufiaMenoufia UniversityUniversity Supervised by
  • 4. ContentsContents This thesis is organized in six chapters & Appendices including the followings: Chapter (1): Introduction Chapter (2): Literature Review Chapter (3): Experimental work Chapter (4): Results and discussions Chapter (5): Theoretical Interpretation. Chapter (6): Conclusion and Recommendations.Conclusion and Recommendations.
  • 5. INTRODUCTIONINTRODUCTION
  • 6. Statement of ProblemStatement of Problem The drains in Egypt are currently suffering from increased pollution loads by discharge of untreated wastewater. Bilbeas drain and El-Qalyoubia Drain is two considered of the most polluted agriculture drains in Egypt.
  • 7. The largest drains in EgyptThe largest drains in Egypt El-Qalyoubia Drain 3.97million m3 /d Length=73.15Km Bilbeas Drain 3.14million m3 /d Length=66.0Km Bahr El-Baqar Drain Lake Manzalah
  • 8. A. Discharge of Domestic Wastewater into Drain Sources of the organic pollution in drainsSources of the organic pollution in drains
  • 9. B.B. Discharge of Industrial Wastewater into the DrainDischarge of Industrial Wastewater into the Drain
  • 10. C. Discharge of Solid Wastes into the DrainC. Discharge of Solid Wastes into the Drain
  • 11. D. Discharge of the Agricultural RunoffD. Discharge of the Agricultural Runoff
  • 12. ObjectivesObjectives of the Studythe Study 1-1-Investigating the effect of using constructedInvestigating the effect of using constructed wetlands in enhancing drain water qualitywetlands in enhancing drain water quality this was done for both Bilbeas and Bahr Elthis was done for both Bilbeas and Bahr El Baqar Drains.Baqar Drains. 2-2-Investigating the possibility of using aInvestigating the possibility of using a combined wetland system providing bothcombined wetland system providing both Surface Flow and Sub-Surface Flow thatSurface Flow and Sub-Surface Flow that benefits from both systemsbenefits from both systems 3-3-Investigating the effects of different inter-Investigating the effects of different inter- related parameters on the obtained results.related parameters on the obtained results.
  • 13. Wetlands Use in Wastewater TreatmentWetlands Use in Wastewater Treatment ** Constructed wetlands are currently widely usedConstructed wetlands are currently widely used for wastewater treatment providing secondary orfor wastewater treatment providing secondary or tertiary (polishing) level of treatment dependingtertiary (polishing) level of treatment depending on the design of work.on the design of work. •Constructed wetlands can further be divided intoConstructed wetlands can further be divided into two types namely Surface Flow (SF) System; andtwo types namely Surface Flow (SF) System; and Sub-Surface Flow (SSF) SystemSub-Surface Flow (SSF) System..
  • 14. Types of Wetland SystemsTypes of Wetland Systems Surface Flow Emergent Macrophyte Based Free floating Macrophyte Based Submerged Macrophyte Based Wetland Surface Flow Sub-Surface Flow Sub-Surface Flow Horizontal Flow Vertical Flow
  • 15. Surface Flow (SF) SystemSurface Flow (SF) System SF system typically consists of parallelSF system typically consists of parallel basins or channels with a relativelybasins or channels with a relatively impermeable bottom soil or subsurfaceimpermeable bottom soil or subsurface barrier, emergent vegetation, and shallowbarrier, emergent vegetation, and shallow water depth of 0.1 to 0.6m.water depth of 0.1 to 0.6m.
  • 16. Sub-Surface Flow (SSF) systemSub-Surface Flow (SSF) system SSF consist of channels or trenches withSSF consist of channels or trenches with relatively impermeable bottoms filled with sandrelatively impermeable bottoms filled with sand or rock media to support emergent vegetation.or rock media to support emergent vegetation. These systems are sometimes called (root zone).These systems are sometimes called (root zone). The system is known for its better oxygenationThe system is known for its better oxygenation capacity through introducing oxygen tocapacity through introducing oxygen to wastewater from the root zone thus the higherwastewater from the root zone thus the higher efficiency of removal for biodegradable waste.efficiency of removal for biodegradable waste.
  • 17. Design ConsiderationsDesign Considerations of Wetlandsof Wetlands  The required land area.The required land area.  Water Containment.Water Containment.  Water transport.Water transport.  The vegetation typesThe vegetation types  Determination of system sizeDetermination of system size  Reduction of specific water quality parametersReduction of specific water quality parameters such as BODsuch as BOD55, TSS, nutrients, trace inorganics, TSS, nutrients, trace inorganics and organics, pathogens, etc.and organics, pathogens, etc.  The principal variables, typically includingThe principal variables, typically including loading rate and inlet concentration.loading rate and inlet concentration.  Operational conditions (temperature and pHOperational conditions (temperature and pH value).value).
  • 18. EXPERIMENTALEXPERIMENTAL WORKSWORKS
  • 19. Locations of Experiments Location of Lake Manzala and Bilbeas Drain CW North Drain Canal Pumping station Locations of Experiments
  • 20. Lake Manzala Constructed Wetland ElementsLake Manzala Constructed Wetland Elements
  • 21. Lake Manzala CW ComponentsLake Manzala CW Components  Sedimentation basins: Two 250 m length, 90 m width and 1.5 m water depth, 25000 m3 sedimentation basins.  Ten beds planted with Phragmites Australis were constructed and run at different flow rates to assess the effect of these beds on enhancing water quality.  Each bed is 50 m width and 250 m length with an average depth of 0.40 m as to allow proper growth of the plants, each bed is divided into five cell (50m x 50m). Flow rates corresponding to low and high hydraulic loadings were 0.04 and 0.36 m3/m2/d (m/d) respectively.
  • 22. 1 2 3 4 5 6 7 8 9 10 C D E G D G D E G D G B A H Bahr El Baqar Drain Screw Pump B Sdeimentation Basin Sdeimentation Basin Surface flow Wetland High Flow Surface flow Wetland Low Flow Collecting Channel Distribution Channel CollectingChannel F F F F 1, 2, 3, ...... Cell No. A, B, C, ...... Smple location Note: SimplifiedSimplified Layout of the Main WetlandLayout of the Main Wetland and Sampling Locationand Sampling Location
  • 23. SF System at Lake ManzalaSF System at Lake Manzala
  • 24. B- Combined SF/SSF System at Bilbeas Four streams pilot At Bilbeas drain; at El-Sahafa bridge (KP. 35.0(
  • 25. Description of Experiment C1 C2 C3 F1 F2 F3 Bilbeas drain Typha plant Water hyacinths G1 G2 G3 9.0 12.0 15.0 18.5 5.0 2.0 40.0 1.0 pump pumps Pilot (1) Pilot (2) screen Cairo - Ismailia Road 22.5 Flow direction Drain water inlet (Embankment) Standard Cells The used channel (Drain Bed)(A) B1 B2 B3 D1 D2 D3 E1 E2 E3 Sex channels used in other studies
  • 26. Two main area (or cells) in series were prepared as follows: Cell (1) (Surface Flow/Sub-Surface Flow) 15 meter long by 5 meters wide at a depth consisting of 0.35 m gravel at (1- 4 cm ) diameter & 0.35 m water, planted with Typha Latofolia (cattail) with a density of one plant /m2 , the free flow of wastewater at a level of 35 cm over the planted gravel bed. Cell (2) Surface Flow (Floating Aquatic Plant) 7.5 meter long by 5 meters wide and A depth of 0.7 meter water. Water – hyacinths was introduced to this cell, density of one kilogram /m2 (covering approximately 66.7% of the total area of this cell). The Pilot Components
  • 27. The Pilot Plant Components Typha plant Water hyacinths 7.515.0 +0.35 +0.70 Polluted DrainWater Influent . FWS Section . SSF SectionInterface Layer between (FWS & SSF) CW Combined FWS/ SSF CW Effluent pipe Treated
  • 28. Operating conditions of the wetlandsOperating conditions of the wetlands ITEMS SF/SSF SF (FAP) Length (total) 15 m 7.5 m Width 5.0 m 5.0 m Depth 0.35 m gravel and 0.35 m water 0.7 m water Plant Typha latofolia (cattail) Water hyacinths Density 1 / m2 1 Kg / m2 HRT 3 days 2 days HLR 0.167 m3/ m2/d 0.333 m3/ m2/d Operating conditions of the wetlandsOperating conditions of the wetlandsOperating conditions of the wetlandsOperating conditions of the wetlands
  • 29. Analyses were conducted from Physical and chemical parameters including: ºC, pH, Ec TSS, TDS, DO and BOD5, COD, NH4 - N, NO3 - N, PO4 3- , Cu, Zn, Pb, and Cd and Fecal Coli form Light Interseption & Leaf Area IndexLight Interseption & Leaf Area Index Sodium Adsorption RatioSodium Adsorption Ratio Statistical AnalysesStatistical Analyses (Lake Manzala and Bilbeas Drain). In addition Redox potential (Eh) was measured,In addition Redox potential (Eh) was measured, and Hydraulic Conductivity (K) was estimated forand Hydraulic Conductivity (K) was estimated for the SSF section of Bilbeas CW.the SSF section of Bilbeas CW. ِِAnalyses
  • 30. Drains Water Characteristics  Bilbeas and El-Qalyoubia drains join together to form Baher El Baqar drain. Bahr El Baqar drain is an example for high polluted drain in Egypt. Main physico-chemical characteristics of raw drains water Parameter PH CODtot BODtot TSS NH4 -N DO Unit mg/L mg/L mg/L mg/L mg/L Bilbeas Drain 7.1 -7.8 95-136 33-115 70 -180 2.0-5.3 0.41-1.04 Bahr El- Baqar Drain 7.3 - 7.67.3 - 7.6 72-122 28-100 50 -130 1.8 - 4.5 1.0 -2.10
  • 31. A- Lake Manzala CW Results  Biochemical Oxygen Demand (BOD5)  Average BOD5 removal efficiency was 53% LFR and 47% of HFR . The maximum influent concentration of BOD5 is 65 mg/l and the minimum effluent is 24 mg/l 0 10 20 30 40 50 60 0 50 100 150 200 250 Bed Length (m( BOD5(mg/l( H. F. R. L. F. R. BOD Limit Variation of BOD5 along the bed length
  • 32. Results:Results:Results:Results:chemical Oxygen Demand (COD)  Average COD removal efficiency was 52% of LFR and 46% of HFR. The maximum influent concentration of COD is 140 mg/l and the minimum effluent is 62 mg/l 0 40 80 120 160 0 50 100 150 200 250 Bed Length (m) COD(mg/l) H. F. R. L. F. R. COD Limit Variation of COD along the bed length
  • 33.  The calculation ratio was between 0.4 to 0.6 during winter and highly fluctuation between 0.2 – 0.8 during summer. BOD:COD ratioBOD:COD ratio Results:Results:Results:Results: 0 0.2 0.4 0.6 0.8 1 M ay June July August Septem berO ctoberNovem berDecem berJanuaryFebruary M arch April Months BOD:COD BOD:COD BOD:COD ratio for wastewater during the study period
  • 34. Results:Results:Results:Results:Total Suspended Solids (TSS) The TSS values of the influent ranged from 90 to 130 mg/l throughout the study. In summer the mean TSS values of the influent was 110 mg/l, while some increase was observed in autumn. the lowest at the end of the treatment beds Raped flow rate with about 82.0 % removal, while the removal efficiency of TSS at the end of the slow flow rate of approx 89.0%. 0 25 50 75 100 125 0 50 100 150 200 250 Bed Length (m) TSS(mg/l) H. F. R. L. F. R. TSS Limit Variation of TSS Concentration along the bed length
  • 35. Results:Results:Results:Results: The mean of inlet concentration of DO in wastewater entering the Beds ranged from 0.80 to 1.30 mg/l. The concentration increased through Beds length and were the highest at the effluent side reaching about 8.0 mg/l for the Beds (LFR) Dissolved Oxygen (DO) Mean seasonal variation of DO values in inlet and outlet water 0 2 4 6 8 10 Inlet Outlet DOmg/l Summer Autumn Winter Spring
  • 36. B- Bilbeas Drain CW Results  Biochemical Oxygen Demand (BOD5) The mean of inlet concentration of BOD5 in wastewater entering the cells was about 110 mg/l. The BOD5 were the lowest at the end of the treatment cell 1 planted with Tupha latofolia with about 50% removal, the BOD5 at the end of the cell 2 with planted is Water hyacinths approx 18% BOD5 removal may be attribute to the voids between the gravel particles in the beds and accumulation of the sludge according to attached growth Influence of HRT on the Biochemical Oxygen Demand 0 20 40 60 80 100 120 0 1 2 3 4 5 HRT day Conc.BOD5mgl BOD5 measure BOD5 Limit Cell 1 Cell 2
  • 37. Results:Results:Results:Results: The maximum treatment removal efficiency of cell 1 is 44.7 %, and cell 2 is 20.90 % while the minimum treatment removal efficiency of cell 1 is 40.50 %, cell 2 is 20.0 %. chemical Oxygen Demand (COD) Influence of HRT on the Chemical Oxygen Demand 0 40 80 120 160 0 1 2 3 4 5 HRT day Conc.CODmgl COD measure CODLimit Cell 1 Cell 2
  • 38. Results:Results:Results:Results:Dissolved Oxygen (DO)  The mean of inlet concentration of DO in wastewater entering the Beds ranged from 0.32 to 0.75 mg/l. The concentration increased through Cell 1 about 5.10 mg/l. The concentration of DO were lower at the end of the cell 2 planted is Water hyacinths cell reaching about 4.84mg/l. Influence of HRT on the Dissolved Oxygen 0 1 2 3 4 5 6 0 1 2 3 4 5 HRT day Conc.DOmgl DO measure DOLimit Cell 1 Cell 2
  • 39. Results:Results:Results:Results:Total Suspended Solids (TSS)  Average TSS removal efficiency was 60% of cell 1 and 22% of cell 2. The particulate matter increased in the first reed bed followed by a decrease with distance along the bed. Influence of HRT on the TSS 0 40 80 120 160 200 0 1 2 3 4 5 HRT day Conc.TSSmgl TSS measure TSS Limit Cell 1 Cell 2
  • 40. Results:Results:Results:Results: TDS of influent wastewater ranged from 1100 to 1400mg/l. The maximum treatment removal efficiency of cell 1 is 15.60 %, cell 2 is 13..95 % while the minimum treatment removal efficiency of cell 1 is 10.80 %, cell 2 is 2.30 %. Total Dissolved Solids (TDS) Influence of HRT on the Total Dissolved Solids 0 500 1000 1500 2000 2500 0 1 2 3 4 5 HRT day Conc.TDSmgl TDS measure TDS Limit Cell 1 Cell 2
  • 41. Results:Results:Results:Results:Phosphorus (PO4 3- )  The influent range for Phosphorus PO4 3- was 1.90 – 3.50 mg/l. Average Phosphorus (PO4 3- ) removal efficiency was 23% of cell 1 and 15% of cell 2. Wetlands remove phosphorus through soil sorption, precipitation or plant uptake. Influence of HRT on the PO4 3- 0 0.5 1 1.5 2 2.5 3 0 1 2 3 4 5 HRT day Conc.PO4mg/l PO4 measure PO4 Limit Cell 1 Cell 2
  • 42. Results:Results:Results:Results:Trace Metals (Cadmium) In wastewater, cadmium typically occurs as Cd (II) and is most soluble at low pH in water with low hardness. Solute compounds with carbonate, sulfate, chloride, and hydroxides. Cadmium may be removed from solution by formation of cadmium sulfide. Influence of HRT on the Cadmium (Cd) 0 0.005 0.01 0.015 0.02 0.025 0 1 2 3 4 5 HRT day Conc.Cdmg/l Cd measure Cd limit Cell 1 Cell 2
  • 43. Redox Potential for Sedimentation Layer  The value of Eh is a mean of two measurements in the consecutive two layers (1.5 and 2.5cm) of the sediment. In general, all Eh values are negative overall the study period which extended for 12 months. The initial value of Eh was 80 mV at May and was decreased to 25 mV at July, then it dcreased to -40 at August. After this time the redox potential values were decreased with proceed time. The lowest value of Eh -135 mV was noticed at October where purification cell was drained and the sediment was flashed out.
  • 44. Redox Potential (Eh) at depth 1.5 & 2.5 cm  Due to the well Known fact that oxidation reactions are dominant at Eh values between -100 to +100 mV, the above findings indicate that reduction reactions in the sediment beginning after 4 months under conditions of this study. This means that continuous of purification without removal of the sediment will lead to release of heavy metals especially manganese, iron and copper and consequently decreased quality of water -150 -100 -50 0 50 100 M ay Ju n e Ju ly A u g u stS ep tem b er O cto b erN o v em b e rD e cem b er Ja nu a ry F eb ru ary M arch A p ril Month RedoxPotentialEh(mV) Eh mVflash out befor after -150 -100 -50 0 50 100 M a y J u n e J u ly A u g u s tS e p te m b e r O c to b erN o v em b e rD e c e m b er J a n u a ry F eb ru a ry M a rc h A p ril Month RedoxPotentialEh(mV) Eh mVflash out befor after
  • 45. Redox potential (Eh) and change of removal efficiency -150 -100 -50 0 50 100 M ay June July A ugustSeptem ber O ctoberN ovem berD ecem ber January February M arch A pril Month RedoxPotentialEh(mV) Eh mVflash out befor after 55 60 65 70 75 M ay June July AugustSeptem ber O ctoberNovem berDecem ber January February M arch April Month %RemovalBOD5 Effici.BOD5flash out afterbefor 50 55 60 65 70 M ay June July AugustSeptem ber OctoberNovem berDecem ber January February M arch April Month %RemovalCOD % Remo.flash out 70 75 80 85 90 M ay June July AugustSeptem ber O ctoberNovem berDecem ber January February M arch April Month %RemovalTSS Effici.TSS flash out 40 50 60 70 80 M ay June July A ugustSeptem ber O ctober N ovem ber D ecem ber January February M arch A pril Month %RemovalNH4-N % Removal %) .‫مضلع‬ (Removal flash out
  • 46. Effect of Leaf Area &Light Interception Water hyacinth light interception was 70.33% through leaves in addition to other interceptions as roots. Light penetration was 29.67% (as the leaf area index LAI=3.27) because water hyacinth leaves are wide, flat and increasing in numbers rapidly leading to high negative effect on light penetration and decrease the treatment efficacy. Typha latofolia (cattail.) light interception was 16.48% through leaves in addition to other interceptions as roots. So, light penetration was higher 83.16% (as leaf area index LAI = 0.41) because cattail leaves are narrow, in vertical position and increasing in numbers slowly. There for the negative effect of light is low leaving to a high treatment efficacy. Cells W (m) L (m) Plant type Density of Plants Average area of leaf / plant-cm2 Leave Area Index Light Interception% Cell 1 5 15 Cattial 1 / m2 2750.7 0.41 16.84 Cell 2 5 7.5 hyacinths 1 Kg / m2 12735.06 3.27 70.33
  • 47. Effect of Clogging on the Treatment Process During this part of the study a hydraulic conductivity test, was done the clean media, in 1.0m length in flow direction and total depth of channel 0.35m and width 0.4m. At flow rate 3.94m3 /day, the water depth upstream and downstream was measured and tabulated by using the following equation to calculated the value of K. Figure 3.6 shown the hydraulic conductivity test (Khalifa et al. 2003). h1 h2 Lb Q Cross-section a-a a a Figure 3.6: Hydraulic Conductivity test in open channe Q = { k b (h1 2 – h2 2 )} / 2L …………………(3.3)
  • 48. Effect of Clogging on the Treatment Process 0 5 10 15 20 25 30 35 M ay Ju n e Ju ly A u g u stS ep tem b er O cto b erN o v em b e rD e cem b er Ja nu a ry F eb ru ary M arch A p ril Month HydraulicCondictivity(Kc) m/hr Kc (m/hr) The relation between of average hydraulic conductivity with time. Maximum media clogged after four month the average hydraulic conductivity that values decreased from 29.67 m/hr to 14.51 m/hr. Total solids concentration in influent polluted water effect in average clogging. Generally, media clogging can be expected with the increasing of organic load in polluted water.
  • 49. 0 0.5 1 1.5 2 2.5 3 M ay Ju ne Ju ly A ugust S ep tem berO ctoberN ovem berD ece m ber JanuaryFebruary M arch A pril Month Qm 3 /day Q m3/day Hydraulic Conductivity (Kc) through the gravel mediathrough the gravel media From value of hydraulic conductivity calculations the maximum percentage of flow passing through the gravel media is about 20% of total applied flow rate. Figure show the amounts of flow rate through gravel media in cell 1 during this studies.
  • 50. The Correlation between Studied Parameters  Strong negatively correlation between temperatureStrong negatively correlation between temperature and DO. However, there are weak negativeand DO. However, there are weak negative correlations between temperature and BODcorrelations between temperature and BOD55,, COD, and TSS. On the other hand, temperatureCOD, and TSS. On the other hand, temperature is weakly positively correlated with pH, and someis weakly positively correlated with pH, and some heavy metals (e.g. Cu, and Zn).heavy metals (e.g. Cu, and Zn).  Such results may be attributing to the negativeSuch results may be attributing to the negative and positive effects of temperature on: (1)and positive effects of temperature on: (1) multiplications and growth rate of micro andmultiplications and growth rate of micro and macro flora, (2) decomposition rate of organicmacro flora, (2) decomposition rate of organic compounds, and (3) activities of chemical ioncompounds, and (3) activities of chemical ion speciesspecies
  • 51. Results:Results:Results:Results:  The pH of untreated wastewater has a weak negativeThe pH of untreated wastewater has a weak negative correlation with concentration of DO, BODcorrelation with concentration of DO, BOD55, COD,, COD, TSS, EC, NHTSS, EC, NH44-N, and some heavy metals (e.g. Fe, Cu, and-N, and some heavy metals (e.g. Fe, Cu, and Zn), while it has a weak positive correlation with NOZn), while it has a weak positive correlation with NO33-N-N  Almost these findings are logic and expected due toAlmost these findings are logic and expected due to one or more of: (1) releasing of organic compounds,one or more of: (1) releasing of organic compounds, especially organic acids, as a result of vigorousespecially organic acids, as a result of vigorous microbial activities, (2) increasing both TSS and ECmicrobial activities, (2) increasing both TSS and EC depress OH- ions concentration and thus decreasingdepress OH- ions concentration and thus decreasing pH, and (3) presence of heavy metals in readilypH, and (3) presence of heavy metals in readily soluble forms (reduced valence) occurred at loweringsoluble forms (reduced valence) occurred at lowering pH.pH. Correlation Coefficients
  • 52. Results:Results:Results:Results:Correlation Coefficients  Negative and significant correlations were foundNegative and significant correlations were found between DO and each of BODbetween DO and each of BOD55, COD, TSS, EC, NH, COD, TSS, EC, NH44-N,-N, POPO44 3-3- -P and heavy metals. However, the correlation-P and heavy metals. However, the correlation between DO and NObetween DO and NO33-N is strong positive. It well known-N is strong positive. It well known that nitrification is a biochemical process in which NHthat nitrification is a biochemical process in which NH44-- N is oxidized to NON is oxidized to NO33-N by nitrifying bacteria and thus-N by nitrifying bacteria and thus DO is a limiting factor for NODO is a limiting factor for NO33-N concentration.-N concentration.  Biological and Chemical Oxygen Demands (BODBiological and Chemical Oxygen Demands (BOD55 &COD) has strong positive correlation with&COD) has strong positive correlation with concentration of TSS, EC, NHconcentration of TSS, EC, NH44-N, PO-N, PO44 3-3- -P, Cu, and Fe,-P, Cu, and Fe, while it has a moderate positive correlation with Zn. Onwhile it has a moderate positive correlation with Zn. On the other hand, the correlation between both BOD5the other hand, the correlation between both BOD5 &COD with NO&COD with NO33-N is strong negative.-N is strong negative.
  • 53. THEORETICAL INTERPRETATION The first order removal model is widely used in constructed wetland design: Ce / Co = exp ( -KT. HRT ) ……… (2.6 ) KT = K20 * 1.06 (T – 20) ----------- (2.7 )KT = K20 * 1.06 (T – 20) ----------- (2.7 ) 0 0.2 0.4 0.6 0.8 0 50 100 150 200 250 300 Bed Length (m) Ce/CoRatio Theoretical Field Results Relationship between ammonia concentration and Bed length in Lake Manzala CW. 0 0.2 0.4 0.6 0.8 5 10 15 20 25 Bed Length (m) Ce/CoRatio Theoretical Field Results Cell 1 Cell 2 Relationship between ammonia concentration and Bed length in Bilbeas CW.
  • 54. 0 0.2 0.4 0.6 0.8 0 50 100 150 200 250 300 Bed Length (m) Ce/CoRatio Theoretical Field Results Relationship between BOD5 concentration and Bed length in Lake Manzala CW. 0 0.2 0.4 0.6 0.8 1 5 10 15 20 25 Bed Length (m) Ce/CoRatio Theoretical Field Results Cell 1 Cell 2 Relationship between BOD5 concentration and Bed length in Bilbeas CW. 0 0.2 0.4 0.6 0.8 0 50 100 150 200 250 300 Bed Length (m) Ce/CoRatio Theoretical Field Results Relationship between TSS concentration and Bed length in Lake Manzala CW. 0 0.2 0.4 0.6 5 10 15 20 25 Bed Length (m) Ce/CoRatio Theoretical Field Results Cell 1 Cell 2 Relationship between TSS concentration and Bed length in Bilbeas CW.
  • 55. ….
  • 56. Conclusions:Conclusions:Conclusions:Conclusions: The results of the experimental investigations conducted on rapid flow rate and slow flow rate applying various hydraulic loadings showed the followings: A- Lake Manzala CW • Wetland treatment cell could remove about 57.0% of the BOD5, while the design range was 50 – 70%. As for TSS the wetland treatment cell could remove about 79.5% of the load while the design range was 74 – 85%. • DO concentration in the treated effluent reached 6.8 mg/l and 5.6 mg/ • The mean influent NH4 -N was 6.53 mg/l while the middle of 3.83 mg/l followed by the same value up to the wetland outlet.
  • 57. Conclusions:Conclusions:Conclusions:Conclusions: • The concentration of Nitrate-N levels was highest at the end of the treatment beds reaching approx 13.10 mg/l and 11.60 mg/l for the treatment beds • Phosphorus removal along the beds was clearly denoted as thePhosphorus removal along the beds was clearly denoted as the influent concentration of 3.0 mg/l. POinfluent concentration of 3.0 mg/l. PO44 3-3- were the lowest at thewere the lowest at the end of the treatment beds with about 52.0%.end of the treatment beds with about 52.0%. • Results of biological contamination removal of FC. The FC wasResults of biological contamination removal of FC. The FC was reduced sharply from 28000 CFU/100 ml at inflow waterreduced sharply from 28000 CFU/100 ml at inflow water samples to 555 CFU/100 ml at the outlet.samples to 555 CFU/100 ml at the outlet. • The mean removal efficiency for Trace Metals was about 53%The mean removal efficiency for Trace Metals was about 53% for the Iron, 38 % Cupper, 48 % Zinc, and 52 %Lead.for the Iron, 38 % Cupper, 48 % Zinc, and 52 %Lead. Lake Manzala CW
  • 58. B- Bilbeas Drain CW Conclusions:Conclusions:Conclusions:Conclusions: • The removal of BODThe removal of BOD55 was about 50% in cell 1, 27 % in cell 2was about 50% in cell 1, 27 % in cell 2 • Wetland treatment cell could remove about 47.0% of the COD inWetland treatment cell could remove about 47.0% of the COD in cell 1, while remove about 23 % in cell 2.cell 1, while remove about 23 % in cell 2. • DO concentration in the treated effluent reached 5.6 mg/l for cell 1DO concentration in the treated effluent reached 5.6 mg/l for cell 1 planted with Tupha latofolia, reduced to 4.5 mg/l for cell 2 plantedplanted with Tupha latofolia, reduced to 4.5 mg/l for cell 2 planted with Water hyacinth.with Water hyacinth. • Removal efficiencies of TSS reached 73.5% and 23.5 % for cell 1Removal efficiencies of TSS reached 73.5% and 23.5 % for cell 1 and cell 2 consecutivelyand cell 2 consecutively • The mean removal efficiency for Trace Metals was about 42 % forThe mean removal efficiency for Trace Metals was about 42 % for the Iron, 51 % Cupper, 38.5 % Zinc, and 46.0 %Lead.the Iron, 51 % Cupper, 38.5 % Zinc, and 46.0 %Lead. • The mean removal efficiency for NHThe mean removal efficiency for NH44-N was about47 % for the-N was about47 % for the cell 1, and 18 % for the cell 2.cell 1, and 18 % for the cell 2.
  • 59. Bilbeas Drain CW Conclusions:Conclusions:Conclusions:Conclusions: The value of Eh is a mean of two measurementsThe value of Eh is a mean of two measurements conducted in the consecutive two layers (1.5 andconducted in the consecutive two layers (1.5 and 2.5cm) of the sediment. These results may be2.5cm) of the sediment. These results may be attributed to one or more of the reasons:attributed to one or more of the reasons:  The conversion from aerobic to anaerobicThe conversion from aerobic to anaerobic conditions with development the sedimentconditions with development the sediment  Vigorous microbial activity with timeVigorous microbial activity with time  The changes in temperature with differentThe changes in temperature with different monthsmonths  The changes in the dissolved oxygen content inThe changes in the dissolved oxygen content in the waterthe water
  • 60. Recommendation:Recommendation:Recommendation:Recommendation: • The study did not address the removal of pathogens which is another important parameter for treated wastewater • Studying the pollutant concentrations in soil and plant parts inStudying the pollutant concentrations in soil and plant parts in additions to water might explain more clearly the mechanisms ofadditions to water might explain more clearly the mechanisms of treating and removal of different pollutant types.treating and removal of different pollutant types. • Identifying the more efficient plant type for pollutant treatment in SF/SSF constructed wetland. Comparative studies are required to either select the best plant in pollutant removal. • Studying the environmental impact assessment on the surrounding area in order to foresee the consequence of introducing pollution to constructed wetlands. • High evaporation and vegetation evapo-transpiration rates in arid and semi-arid climatic regions have a direct impact on pollutant removal.

×