Impact of source water quality on total organic carbon and trihalomethane removal efficiency in a water treatment plant: a case study of Upper Awash, Ethiopia

被引:1
|
作者
Assefa, Emeru [1 ]
Jabasingh, Anuradha [2 ]
Mulugeta, Eyobel [3 ]
Dessalegne, Meseret [1 ]
Teju, Endale [4 ]
机构
[1] Addis Ababa Univ, Ethiopian Inst Water Resources, Addis Ababa, Ethiopia
[2] Addis Ababa Inst Technol, Chem & Biochem Engn, Addis Ababa, Ethiopia
[3] Bio & Emerging Technol Inst, Addis Ababa, Ethiopia
[4] Haramaya Univ, Coll Nat & Computat Sci, Dept Chem, Haramaya, Ethiopia
关键词
modeling; removal efficiency; seasonal variation; total organic carbon; trihalomethanes (THMs); water quality; SURFACE-WATER; HEAVY-METAL; COAGULATION; MATTER; RIVER;
D O I
10.2166/wh.2024.276
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This study addresses the limited understanding of factors affecting the efficiency of water treatment plants in reducing trihalomethane (THM) formation through total organic carbon (TOC) removal, highlighting significant challenges in improving treatment effectiveness. The aim of this study was to examine the influence of water quality on the efficiency of water treatment plants to remove TOC and reduce THM formation. Linear regression and correlation analyses were conducted to examine the relationship between water quality parameters and THM concentrations. The results showed that there was a negative relationship between turbidity, metals, and TOC concentration with TOC removal efficiency. Positive correlations were found between parameters and the formation of THMs in water. Of these parameters, water temperature was observed to have relatively less influence on THM formation. It was observed that seasonal variations in water quality affect the efficiency of TOC removal and THM content in treated water. THM levels in chlorinated water were found to be within the permissible range of the World Health Organization's drinking water quality guidelines. However, it is still important to maintain continuous monitoring and take measures to reduce THMs. The model demonstrated a strong correlation (R-2 = 0.906) between predicted and measured THM values.
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页码:337 / 349
页数:13
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