Firomsa Bidira, Z. Asmelash, S. Kebede, Abrham Bekele
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The color (99.6%) and turbidity (99.4%) were removed by combining ECO with UV/ H2 O2 , which produces high amounts of hydroxyl ions (OH- ), oxidizes large amounts of contaminants, and increases efficiency. These results were obtained at pH 7, current of 0.40 AMP, and 1.5 g CaCl2 after 40 minutes of electrolysis. The operating factors were pH, electrolyte dosage, time, current and H2 O2 , which plays a major role in increasing the removal capacity of photoelectrochemical oxidation for coffee processing waste water treatment. CaCl2 was once more wonderful in the removal of organic compounds from coffee processing effluents. Conclusion: Therefore, the introduction of this ultraviolet light is a powerful oxidant with H2 O2 , which can improve pollution control. An analysis of variance (ANOVA) with a 95% confidence interval can be used to determine the magnitude of the independent variable.","PeriodicalId":51877,"journal":{"name":"Environmental Health Engineering and Management Journal","volume":null,"pages":null},"PeriodicalIF":1.3000,"publicationDate":"2023-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimization and evaluation of the process variable’s effect on color and turbidity removal from coffee processing wastewater: Using a photoelectrochemical oxidation process\",\"authors\":\"Firomsa Bidira, Z. Asmelash, S. Kebede, Abrham Bekele\",\"doi\":\"10.34172/ehem.2023.01\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Background: Coffee is the foundation of Ethiopia’s economy, but the wastewater generated by coffee processing cannot be properly treated, therefore, causing various environmental problems. 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引用次数: 0
摘要
背景:咖啡是埃塞俄比亚的经济基础,但是咖啡加工过程中产生的废水得不到适当处理,因此造成了各种环境问题。方法:采用电化学氧化(ECO)和光电化学氧化(PECO)结合UV和过氧化氢(UV/H2 O2)对咖啡加工废水中的有机化合物进行还原,并对其着色和浊度产生影响。考察了氢溶解度(pH)、氯化钠和氯化钙(NaCl和CaCl2)浓度、电流和电解时间、H2 O2用量等实验参数对电解效果的影响。结果:采用响应面法(RSM)和Microsoft Excel对结果进行调查和分析。通过ECO与UV/ H2 O2结合去除色度(99.6%)和浑浊度(99.4%),产生大量羟基离子(OH-),氧化大量污染物,提高效率。这些结果是在pH为7、电流为0.40 AMP、1.5 g CaCl2电解40分钟后得到的。pH、电解液投加量、时间、电流和H2 O2是提高光电氧化处理咖啡加工废水去除率的主要因素。CaCl2在去除咖啡加工废水中的有机化合物方面表现得更加出色。结论:该紫外光的引入是一种具有较强氧化作用的h2o2氧化剂,可以改善污染的控制。具有95%置信区间的方差分析(ANOVA)可用于确定自变量的大小。
Optimization and evaluation of the process variable’s effect on color and turbidity removal from coffee processing wastewater: Using a photoelectrochemical oxidation process
Background: Coffee is the foundation of Ethiopia’s economy, but the wastewater generated by coffee processing cannot be properly treated, therefore, causing various environmental problems. Methods: In this research, electrochemical oxidation(ECO) and photo electrochemical oxidation(PECO) are combined with UV and hydrogen peroxide (UV/H2 O2 ) to reduce organic compounds in coffee processing effluent with color and turbidity effect. The effects of various experimental parameters such as hydrogen solubility (pH), sodium chloride and calcium chloride (NaCl and CaCl2 ) concentrations, current and electrolysis time, and H2 O2 dose were investigated. Results: The results were investigated and analyzed using response surface methodology (RSM) and Microsoft Excel. The color (99.6%) and turbidity (99.4%) were removed by combining ECO with UV/ H2 O2 , which produces high amounts of hydroxyl ions (OH- ), oxidizes large amounts of contaminants, and increases efficiency. These results were obtained at pH 7, current of 0.40 AMP, and 1.5 g CaCl2 after 40 minutes of electrolysis. The operating factors were pH, electrolyte dosage, time, current and H2 O2 , which plays a major role in increasing the removal capacity of photoelectrochemical oxidation for coffee processing waste water treatment. CaCl2 was once more wonderful in the removal of organic compounds from coffee processing effluents. Conclusion: Therefore, the introduction of this ultraviolet light is a powerful oxidant with H2 O2 , which can improve pollution control. An analysis of variance (ANOVA) with a 95% confidence interval can be used to determine the magnitude of the independent variable.