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    Effects of trace elements (Fe, Cu, Ni, Co and Mg) on biomethane production from paper mill wastewater
    (Walter De Gruyter Gmbh, 2023) Toprak, Dilan; Yilmaz, Tulay; Gulpinar, Kerem; Yucel, Amine; Cakmak, Yakup; Ucar, Deniz
    Trace elements have a significant effect on biochemical reactions and therefore the presence of optimum levels of trace elements is essential for bioreactor performances. In this study, the effects of five trace elements on biomethane production have been investigated. Experimental studies have been carried out with multiple batch reactors at 15 day HRT and mesophilic temperatures. The optimum concentrations for each of the trace elements Fe, Cu, Ni, Co and Mg were found as 5, 0.5, 0.5, 0.5 and 100 mg/L, respectively. Among tested trace elements, Cu was the one which provided the highest biomethane production. Cu addition was resulted in a 46 % increase in biomethane production followed by Co with 24 %. The biomethane production rate for these two trace elements was 191.70 and 110.77 ml CH4/g COD, respectively. Optimum levels for Ni, Fe and Mg increased biomethane production rate by approximately 14.3, 10 and 17 % compared to control groups, respectively. Because the exact amount of trace element requirement for each industry/reactor is different, specific case studies should be performed for each application. These results could be used as initial trace element concentrations for further continuous studies.
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    Extracellular azo dye oxidation: Reduction of azo dye in batch reactors with biogenic sulfide
    (Taylor & Francis Ltd, 2022) Toprak, Dilan; Demir, Ozlem; Ucar, Deniz
    In this study, the sulfide-based reduction of azo dyes (Acid Blue 264) was investigated. Sulfate was reduced to sulfide with an ethanol-fed sulfate reduction reactor and the sulfide produced was used to reduce azo dyes in separate batch reactors using sulfide as the electron carrier. The Box-Behnken experiment design method was used to identify how operational parameters affect the decolorization efficiency. As independent variables, initial dye concentration, sulfide concentration and reaction time were selected while dye removal was considered as the response function. Based on the Box Behnken design, the higher regression coefficient (R-2=0.9397) shows that the experimental results are in good agreement with model predictions. At the initial dye concentration of 80 mg/L, the highest dye removal efficiency, about 82.39%, was obtained at the sulfide concentration of 50 mg/L and the reaction time of 25 h. This study showed that Box Behnken's model prediction was a suitable approach for identifying the best conditions for dye removal.