Evaluation of Textile Wastewater Treatment via ETP in Bangladesh

Mohammad Biplab Mia, Mohammad Biplab Mia, Md Jahangir Alam, Mithun Biswas, Md Mahedi Hasan Moon and Md Rasel Ahammed
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Mohammad Biplab Mia: School of Civil Engineering, Beijing Jiaotong University, Beijing, China.
Mohammad Biplab Mia: School of Civil and Transportation Engineering, Hohai University, Nanjing, China.
Md Jahangir Alam: School of Civil and Transportation Engineering, Hohai University, Nanjing, China.
Mithun Biswas: School of Civil and Transportation Engineering, Hohai University, Nanjing, China.
Md Mahedi Hasan Moon: School of Civil Engineering, Beijing Jiaotong University, Beijing, China.
Md Rasel Ahammed: Department of Geotechnical Engineering, China Institute of Water Resources and Hydropower Research (IWHR), Beijing, China.

International Journal of Research and Scientific Innovation, 2024, vol. 11, issue 5, 356-368

Abstract: Textile liquid waste possesses a substantial biochemical oxygen demand and total suspended solids, hence posing a significant risk of contaminating adjacent water bodies if not appropriately managed. The primary aim of the study is to examine the pH condition of water from the inlet and outlet of the ETP (Effluent Treatment Plant) in two specific regions. Two natural groups in Bangladesh include Tonga Bari, Ashulia, Savar, and Dhaka. Another natural group is “The Emakulet Textile Ltd,†located in Purboponchash, Dhamrai, Dhaka. Raw liquid waste was collected from two textile industry and applied some test procedure in the laboratory by varying different design parameters such as pH, DO (Dissolved Oxygen), BOD5 (Biochemical Oxygen Demand), COD (Chemical Oxygen Demand), TDS (Total Dissolved Solids), TSS (Total Suspended Solids), Turbidity, Fe2+, pH was tested by a pH meter at 25℃ temperature. DO also tested by a sensor machine (FLEXA) which shows the values of dissolved oxygen in ETP waste water. To collect BOD5 value needed 5 days minimum also used MnSO4, H2SO4 to get BOD5 value from the incubator. Turbidity was tested by Digital Turbidity meter.

Date: 2024
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