Textile Wastewater Treatment Modelling and Design Using Stoat Graph and Summary Statistic Model

  • Desalegn Abdissa Akuma Chemical Engineering School, Jimma Technology Institute, Jimma University, Jimma city, Ethiopia
  • Ketema Beyecha Hundie


Without properly treated wastewater released from the textile industry contains organic and
inorganic pollutants that cause environmental problems like water body contamination, which
causes marine life disappearance, soil contamination, and air pollution. Treatment of textile
industry wastewater is difficult due to pollutant types existing like BOD, COD, toxic heavy
metals, organic particle matter, inorganic particle matter, color, etc. The multi-component
wastewater pollutant needs proper designs to remove such pollutants. Dire Dawa textile
wastewater treatment plant (design) and simulation was the objective of this study. The method of
this study was experimental and software modelling. STOAT model software is the best capable
of simulation treatments plants, and the time to complete the simulation was 3 days. The STOAT
graphic and statically data analysis model efficiently removed the multi-components of pollutants
effluent from Dire Dawa textile industry. Some pollutant parameter measures before design model
are SS 350 mg/L, DS 2000 mg/L, ammonia 55 mg/L, BOD 350 mg/L, nitrate 0 mg/L and DO 12
mg/L. The effluent of wastewater treatment plant model simulation results are 2 mg/L SS,
ammonia 8.82 mg/L, BOD 2.5 mg/L, and nitrate increases from 0 to 58 mg/L by ammonia
oxidation. Totally 98.7% SS, 99% BOD, and 84% ammonia were removed in the design model. In
the sludge outlet, nitrate contents increase due to nitrification being processed rather than

Jun 28, 2022
How to Cite
AKUMA, Desalegn Abdissa; HUNDIE, Ketema Beyecha. Textile Wastewater Treatment Modelling and Design Using Stoat Graph and Summary Statistic Model. Pakistan Journal of Analytical & Environmental Chemistry, [S.l.], v. 23, n. 1, p. 32-40, june 2022. ISSN 2221-5255. Available at: <http://pjaec.pk/index.php/pjaec/article/view/817>. Date accessed: 14 aug. 2022. doi: http://dx.doi.org/10.21743/pjaec/2022.01.03.