Open AccessEvaluation of Al-Thagher Wastewater Treatment Plant
Author(s) -
Abdulhussain A. Abbas,
Yasameen Tahseen Yousif,
Heider Hamid Almutter
Publication year - 2021
Publication title -
periodica polytechnica. civil engineering/periodica polytechnica. civil engineering (online)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.406
H-Index - 19
eISSN - 1587-3773
pISSN - 0553-6626
DOI - 10.3311/ppci.18513
Subject(s) - effluent , total dissolved solids , total suspended solids , biochemical oxygen demand , chemical oxygen demand , wastewater , water quality , environmental science , suspended solids , sewage treatment , chloride , wastewater quality indicators , environmental engineering , sewage , sulfate , mathematics , pulp and paper industry , chemistry , ecology , biology , organic chemistry , engineering
This study aims to evaluate the performance of the sewage treatment plant in Al-Thagher city, in the north of Basrah governorate, the southern part of Iraq. The plant’s performance was estimated based on an analysis of influent and effluent wastewater quality data that represented the monthly averages from Feb. 2017 to Dec. 2018. The results show that the values of temperature (T), pH, ammonia (NH3–N), chemical oxygen demand (COD) and biological oxygen demand (BOD) in all collected samples from the effluent of the plant met the Iraqi water quality standard (IWQS), whereas the values of electrical conductivity (EC), total dissolved solids (TDS), total suspended solids (TSS), sulfate (SO4–2), chloride (Cl–1) and phosphate (PO4–P) met the Iraqi water quality standard (IWQS) in some months and did not meet the standard in other months. The average removal efficiencies were in the following order: COD (77.12%) > BOD (77.03%) > TSS (62.26%) > NH3–N (59.99%) > PO4–P (12.42%) > Cl–1 (1.97%). The removal percentages for the remaining parameters had negative values. The Canadian Council of Ministers of the Environment water quality index (CCME WQI) value of the treated water was 51.80 and classified as “marginal.” The coefficients of determination between each parameter in influent or effluent were calculated. Finally, linear regression equations between these parameters were formulated so that the value of one parameter could be used to predict the value of a different parameter.