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    A dual approach using response surface methodology and machine learning for optimization and enhancement of microalgae-based municipal wastewater treatment
    (Wiley, 2025) Kayan, İremsu; Ayman Öz, Nilgün
    BACKGROUND Municipal wastewater comprises both organic and inorganic contaminants. Especially in rural areas, conventional municipal treatment plants primarily focus on carbon removal; therefore, nutrient removal should be prioritized for preventing environmental pollution. Mixotrophic microalgae such as Nannochloropsis sp. have significant potential for both carbon and nutrient removal. However, microalgae-based wastewater systems can be affected by many parameters and, using response surface methodology and decision tree, a machine learning model can help to determine the optimal conditions for the systems to operate more efficiently. RESULTS The optimal removal conditions were determined by response surface methodology to be a light period of 21 h at an intensity of 8000 lx and a temperature value of 30 °C. Under these optimal conditions, the respective removal efficiency for chemical oxygen demand, total organic carbon, total Kjeldahl nitrogen, and orthophosphate was 53%, 34%, 87%, and 70%, respectively. Chlorophyll-a concentration increased by as much as 49%. Real municipal wastewater was used instead of synthetic wastewater, yielding closer approximations to real situations. CONCLUSION The present study has underscored innovative, data-driven approaches as core in ensuring sustainable wastewater management and sets a useful framework for future research, which could be done with the aim of refining the methods to enhance efficiency in treatment. © 2025 The Author(s). Journal of Chemical Technology and Biotechnology published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry (SCI).
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    Comparison of treatability of four different chlorophenol-containing wastewater by pyrite-Fenton process combined with aerobic biodegradation: Role of sludge acclimation
    (Academic Press, 2021) Kayan, İremsu; Ayman Öz, Nilgün; Kantar, Çetin
    Aerobic biodegradation combined with pyrite-Fenton process was used for the treatment of wastewater containing different chlorophenols (4-CP, 2,3-DCP, 2,4-DCP, 2,4,6-TCP). Fenton degradation using pyrite as the low cost iron catalyst was used as a pre-treatment step to lower the toxicity of CPs prior to aerobic biodegradation. Synthetic wastewater spiked directly with either 100 mg/L CPs or pyrite-Fenton pre-treated CPs was fed to the batch bioreactors inoculated with unacclimated or acclimated activated sludge using glucose as the C-source. The results show that the CP biodegradation under aerobic conditions was highly dependent on the type of CP treated. Except for 2,4-DCP, all other CPs investigated caused severe sludge toxicity, and thus significantly hindered glucose degradation by unacclimated sludge. The CP toxicity decreased in the order of: 2,4,6-TCP > 2,3-DCP > 4-CP > 2,4-DCP. The toxic effect was explained through an interaction of CPs with the lipid fraction of cell membrane. While the pyrite-Fenton pre-treatment improved the COD removal efficiency using unacclimated sludge, the sCOD removal efficiency was still less than the control reactor operated with no CP addition. With sludge acclimation, however, the sCOD removal efficiencies increased, and approached 74% for 2,4-DCP, 61% for 4-CP, 56% for 2,4,6-TCP and 46% for 2,3-DCP, suggesting an enhanced biomass tolerance to CP toxicity. On the other hand, the sludge acclimation combined with pyrite Fenton pre-treatment provided the best bioreactor performance for all CPs with the sCOD removal efficiencies reaching 81% for 2,4,6-TCP, 78% for 2,4-DCP, 73% for 4-CP and 62% for 2,3-DCP. This suggests that the dechlorination of CPs with Fenton process, in conjunction with sludge acclimation, not only reduced the sludge toxicity, but also enhanced the bioavailability of CP-containing wastewater for microorganisms, especially for highly chlorinated toxic CPs such as 2,4,6-TCP. Overall, the findings highlight the need for sludge acclimation for effective treatment of chlorophenol-containing wastewater by a combined pyrite-Fenton and aerobic biodegradation system.
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    Integrating response surface methodology and decision tree algorithms for valorization of cheese whey wastewater
    (Elsevier Science Inc, 2025) Kayan, İremsu; Ayman Öz, Nilgün
    Recently, the potential of microalgae in wastewater treatment has attracted attention. The goal of this study is to find optimum conditions for microalgae growth and the concentration of cheese whey wastewater (CWW) to get the best treatment efficiency by using response surface methodology (RSM) and the decision tree algorithm for different pollutant parameters. The study used reactors with different amounts of CWW and Nannochloropsis sp. to find the best concentrations for each parameter. The best concentration of CWW was found to be 8000 mgCOD/L, and the best concentration of Nannochloropsis sp. microalgae was found to be 2200 mgVS/L. It was found that Chemical Oxygen Demand (COD), Total Organic Carbon (TOC), Total Kjeldahl Nitrogen (TKN), and Orthophosphorus (Ortho-P) could be removed at different ranges, 77-96 %, 95-98 %, 51-97 %, and 60-99 % of CWW, respectively, depending on the different combinations of microalgae and CWW concentrations. The desirability values in RSM for COD, TOC, TKN, and Ortho-P parameters to be 0.99, 0.94, 0.78, and 0.63, respectively. The study suggests the marine microalgae (Nannochloropsis sp.) could be an alternative way to treat saline CWW, to create a circular economy. The machine learning (ML) method validates that RSM predictions are consistent and accurate. The results show that it is possible to combine traditional optimization methods with more advanced ML methods to facilitate the design and the operation of the treatment plants.