PERFORMANCE EVALUATION OF WATER QUALITY AND RESIDUAL SLUDGE PROPERTIES FROM Al-WIHDA WATER TREATMENT PLANT BASED ON EXPERIMENTAL WORK

Roaa kadhim; Reem J. Channo; Israa A. Al-Baldawi; Basim H. khudhair

doi:10.30572/2018/KJE/160207

Authors

Roaa kadhim Civil Engineering Department, College of Engineering, University of Baghdad, Baghdad, Iraq https://orcid.org/0009-0005-1351-9287
Reem J. Channo Civil Engineering Department, College of Engineering, University of Baghdad, Baghdad, Iraq https://orcid.org/0000-0002-2083-952X
Israa A. Al-Baldawi Civil Engineering Department, College of Engineering, University of Baghdad, Baghdad, Iraq
Basim H. khudhair Civil Engineering Department, College of Engineering, University of Baghdad, Baghdad, Iraq

DOI:

https://doi.org/10.30572/2018/KJE/160207

Keywords:

Al-Wihda WTP, Artificial neural network, Residual sludge, Water treatment plant, Water quality

Abstract

Evaluation of residual sludge and water quality of a treatment plant is an integrated activity through the analysis of physical and chemical properties related to health, environment, and specific water used. This study aimed to address the characteristics and properties of the raw water, treated water, and the residual sludge from Al-Wihda water treatment plant (WTP) based on two stage. The first is the historical data from 2018 to 2023 and the results showed that the maximum amount of sludge produced was 259.2 kg/1000 m3 exceeded the reported limit, while turbidity and TSS have a significant contribution to the amount of sludge produced by Al-Wihda WTP. The second, experimental tests were carried out for the residual sludge in the sedimentation tank for the duration (15 July-15 December, 2023) and the results showed that the maximum TSS in residual sludge was about 1585 m3/d, while the maximum COD was about 200 mg/L which exceeded the Iraqi standard limit (100 mg/L). The study concluded that residual sludge is dependent on the amount of TSS contained in the raw water and contains high amount of COD that could be used for the treatment of saline wastewater.

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References

Abed, H. Z., and Khudair, M. K. (2023) “modeling of turbidity distribution in water networks using PMS Model - Al-Saray Sector in Kufa City as a case study”, Kufa Journal of Engineering. Kufa, Najaf, IRAQ, 14(3), pp. 48–68. doi: 10.30572/2018/KJE/140304. DOI: https://doi.org/10.30572/2018/KJE/140304

Ahmad, T., Ahmad, K., Alam, M. (2016) ‘Sustainable management of water treatment sludge through 3‘R’ concept’, Journal of Cleaner Production, 124, 1–13, https://doi.org/10.1016/j.jclepro.2016.02.073. DOI: https://doi.org/10.1016/j.jclepro.2016.02.073

Ahmad, T., Ahmad, K., and Alam, M. (2018) ’Characterization and constructive utilization of sludge produced in clariflocculation unit of water treatment plant’, Materials Research Express, 5, 1-17, 10.1088/2053-1591/aab23a. DOI: https://doi.org/10.1088/2053-1591/aab23a

Al Nageim, H. (2024) “wastewater sludge ash in the production of a novel cold mix asphalt (CMA): Durability, Aging and Toxicity Characteristics”, Kufa Journal of Engineering. Kufa, Najaf, IRAQ, 15(1), pp. 147–162. doi: 10.30572/2018/kje/150109. DOI: https://doi.org/10.30572/2018/kje/150109

Anjithan, K. (2016) Management Practices of Water Treatment Sludge in Sri Lanka and Re-use Potential of Sludge Material. Master, University of Moratuwa.

APHA (American Public Health Association) (2012) Standard Methods for the Examination of Water and Wastewater (22nd ed.). American Water Works Association (AWWA) and Water Environment Federation (WEF).

Crittenden, J.C., Trussell, R.R., Hand, D.W., Howe, K.J. and Tchobanoglous, G. (2012) MWH’s Water Treatment: Principles and Design. John Wiley & Sons Inc., Hoboken, New Jersey. DOI: https://doi.org/10.1002/9781118131473

Dassanayake, K. B., Jayasinghe, G. Y., Surapaneni, A., & Hetherington, C. (2015) ‘A review on alum sludge reuse with special reference to agricultural applications and future challenges’, Waste Management, 38(1), 321–335, 10.1016/j.wasman.2014.11.025. DOI: https://doi.org/10.1016/j.wasman.2014.11.025

Dias, R., Daam, M.A., Diniz, M. , Maurício, R. (2023) ‘Drinking water treatment residuals, a low-cost and environmentally friendly adsorbent for the removal of hormones - A review’, Journal of Water Process Engineering, 56, 104322, 10.1016/j.jwpe.2023.104322. DOI: https://doi.org/10.1016/j.jwpe.2023.104322

Enviseng Environmental Consulting Services (2012) ‘Wastewater Treatment Plant Sludge and Biosolids (Heavy Metals, Nutrients, Pathogens, Alum Recovery)’, Beneficial Practice and Appropriate Technology Guide, 1.

IBM SPSS Neural Networks 20 (2011), Guide from IBM Software Group.

Kukreja, H., Bharath, N., Siddesh, S.C., and Kuldeep, S. (2016) ‘An introduction to artificial neural network’, International Journal Advance Research Innovations, Ideas Education, 1, 27-30.

Mohsin, Rusol & Khudhair, Basim. (2021) ‘Treatability influence of municipal sewage effluent on surface water quality assessment based on Nemerow pollution index using an artificial neural network’, IOP Conference Series Earth and Environmental Science. 877, 1-12. DOI: https://doi.org/10.1088/1755-1315/877/1/012008

Nayeria and Mousavi, (2022) ‘Review A comprehensive review on the coagulant recovery and reuse from drinking water treatment sludge’, Journal of Environmental Management, 319, 115649, 10.1016/j.jenvman.2022.115649. DOI: https://doi.org/10.1016/j.jenvman.2022.115649

Nguyen, M.D., Thomas, M., Surapaneni, A., Moon, E.M., Milne, N.A. (2022) ‘Beneficial reuse of water treatment sludge in the context of circular economy’, Environmental Technology Innovation, 28, (9), 102651, 10.1016/j.eti.2022.102651. DOI: https://doi.org/10.1016/j.eti.2022.102651

Omondi, A.N., Ouma,Y. & Mburu, S., and Mecha, A. C. (2024) ‘Optimization of Reservoir Water Quality Parameters Retrieval and Treatment Using Remote Sensing and Artificial Neural Networks’, Journal of Digital Food Energy & Water Systems, 5, 159-176, 10.36615/2x3qd014. DOI: https://doi.org/10.36615/2x3qd014

Qrenawi, L. I. and Rabah, F. K.J. (2021) ‘Sludge management in water treatment plants: literature review’, Int. J. Environment and Waste Management, 27, 93-125, https://doi.org/10.1504/IJEWM.2021.111909. DOI: https://doi.org/10.1504/IJEWM.2021.111909

Sawalkar, N. T., Jadhav, S.W., Pawar, A.A. (2024) ‘Prediction of Optimum Dosage of Coagulant in Water Treatment Plant: A Comparative Study between Artificial Neural Network and Random Forest’, International Research Journal on Advanced Engineering Hub (IRJAEH), 2, 1408 –1420, https://doi.org/10.47392/IRJAEH.2024.0194. DOI: https://doi.org/10.47392/IRJAEH.2024.0194

Serajuddin, M.d., Chowdhury, A.I, Mahmudul Haque, M.d., Ehteshamul Haque, M.d. (2019) ’Using Turbidity to Determine Total Suspended Solids in an Urban Stream: A Case Study’, 67, 83-88, 10.14445/22315381/IJETT-V67I9P214. DOI: https://doi.org/10.14445/22315381/IJETT-V67I9P214

Syed, R.Q., Edward, M.M., and Gaung, Z. (2000) Wastewater treatment plants: Planning, Design and Operation. Book (ch 24).

Trach, Y., Trach, R., Kuznietsov, P., Pryshchepa, A., Biedunkova, O., Kiersnowska, A., Statnyk, I. (2024) ‘Predicting the Influence of Ammonium Toxicity Levels in Water Using Fuzzy Logic and ANN Models’, Sustainability 2024, 16, 5835, https:// doi.org/10.3390/su16145835. DOI: https://doi.org/10.3390/su16145835

Turner, T., Wheeler, R., Stone, A. (2019) ‘Potential Alternative Reuse Pathways for Water Treatment Residuals: Remaining Barriers and Questions—a Review’, Water Air Soil Pollute, 230, 227, https://doi.org/10.1007/s11270-019-4272-0. DOI: https://doi.org/10.1007/s11270-019-4272-0

WHO (2017). Guidelines for drinking-water quality: first addendum to the fourth edition.

Xiao, W., Hui, L., Meili,W., Tianying, Z., Jiawei, L., and Yongdi, L. (2024) ‘Resistance to salt stresses by aerobic granular sludge: sludge property and microbial community’, Frontiers of Environmental Science and Engineering, 18(101), 10.1007/s11783-024-1861-y. DOI: https://doi.org/10.1007/s11783-024-1861-y