Sürdürülebilir Kalkınma Amaçları

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• MakaleAçık Erişim2024Scopus SJRQ2/r/munzur/2262
  Leachate treatment via electrocoagulation–coal-based powdered activated carbon process: Efficiencies, mechanisms, kinetics, and costs

  Ogedey, Aysenur; Oguz, Ensar

  This study aims to improve COD, NH3-N, and turbidity removal from Bingöl's leachate using a single-reactor integrated electrocoagulation (EC)–coal-based powdered activated carbon (CBPAC) process under various experimental conditions. In the EC-CBPAC process, three stainless-steel cathodes and three aluminum electrodes were connected to the negative and positive terminals of the power supply, respectively. The initial concentrations in the leachate were 1044 mg O2/L for COD, 204 mg/L for NH3-N, and 57 NTU (or 71.25-mg (NH2)2H2SO4/L) for turbidity, respectively. After a 40-min EC-CBPAC process, with a CBPAC dosage of 5 g/L and pH of 5 for COD and turbidity, and 9.5 for NH3-N, the optimum removal efficiencies for COD, NH3-N, and turbidity were achieved at 92%, 40%, and 91%, respectively. When the EC process was applied without CBPAC under the same experimental conditions, the removal efficiencies of COD, NH3-N, and turbidity were 87%, 28%, and 54%, respectively. Before and after the EC-CBPAC process, the Brunauer–Emmett–Teller (BET) surface area, pore volume, and mean pore diameter of the CBPAC were found to be (888 m2/g, 0.498 cm3/g, and 22.28 Å) and (173 m2/g, 0.18 cm3/g, and 42.8 Å), respectively. The optimum pseudo-first-order (PFO) rate constants for COD, turbidity, and NH3-N were determined to be 3.15 × 10−2, 4.77 × 10−2, and 8.8 × 10−3 min−1, respectively. With the current density increasing from 15 to 25 mA/cm2, energy consumption, unit energy consumption, and total cost increased from 68.7 to 122.4 kWh/m3, 6.948 to 15.226 kWh/kg COD, and 0.85 to 1.838 $/kg COD, respectively. Practitioner points: EC-CBPAC process has greater COD, NH3-N, and turbidity removal efficiency than EC process. COD and turbidity achieved their optimum disposal efficiencies at 92% and 91%, respectively, at pH 5 The most efficient disposal efficiency for NH3-N was observed to be 40% at pH 9.5. EC-CBPAC process increased removal efficiencies for COD, NH3-N, and turbidity by 20%, 19%, and 38%, respectively, compared with EC alone. The turbidity, NH3-N, and COD disposal fitted PSO model due to high correlation values (R2 0.94–0.99).

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  AtıfScopus3·WoS3·OpenAlex3

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• MakaleYalnız künye2023Scopus SJRQ2/r/munzur/1573
  Deep learning based an effective hybrid model for water quality assessment

  Utku, Anıl; Utku, Esen Damla; Kutlu, Banu

  Water, which is very important for life and civilizations on Earth, has been a source of life for all living things. However, freshwater resources gradually decrease due to climate change, pollution, and population growth. Water pollution is the quality changes that occur due to various activities of people, change the chemical, biological, and physical properties of water, restrict or prevent its use, and disrupt ecological balances. The water quality criteria determined to keep this pollution under control ensure the safe use of water. Water quality observations have gained more importance today due to intense environmental concerns and water pollution. This situation revealed the necessity of water quality assessment for water source use. In this study, the CNN-LSTM-based hybrid model was proposed to assess water quality. The proposed model was compared with AdaBoost, DT, GNB, kNN, LGBM, RF, and LSTM according to accuracy, precision, recall, F-score, and AUC. The proposed model has 98.81% accuracy, 99.03% precision, 99.65% recall, 99.33% F-score, and 93% AUC. Practitioner Points: CNN-LSTM hybrid model was developed to water quality assessment. The proposed model is compared with established techniques like AdaBoost, DT, GNB, kNN, LGBM, RF, and LSTM. The developed model has 98.81% classification accuracy. Experimental results show that the developed model will ensure the use of safe water according to water quality criteria.

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  AtıfScopus7·WoS4·OpenAlex8

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• MakaleÖn baskısı açık2016Scopus SJRQ2/r/munzur/4153
  Cytokine Responses in Gills of Capoeta umbla as Biomarkers of Environmental Pollution

  Danabas, Durali; Yildirim, Nuran Cikcikoglu; Yildirim, Numan; Onal, Ayten Oztufekci; Uslu, Gulsad; Unlu, Erhan; Danabas, Seval; Ergin, Cemil; Tayhan, Nilgun

  Immunological biomarkers reflect the effects of exposure to environmental contaminants. In this study, the suitability and sensitivity of cytokine responses, interleukin 1 beta (IL-1 beta), interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-alpha) in gill tissues of Capoeta umbla (Heckel, 1843), collected from different regions, as early warning indices of environmental pollution and ecosystem health was evaluated. Fish and water samples were taken from ten stations in March and September 2011 and 2012. Tumor necrosis factor-alpha, IL-1 beta and IL-6 levels were determined in samples of the gill tissues by using an ELISA kit. Significant variations of TNF-alpha, IL-1 beta and IL-6 levels observed between stations and seasons. The results of this study show that seasonal variations of cytokine responses in gills of Capoeta umbla are sensitive to the contaminants present in Uzuncayir Dam Lake (Tunceli, Turkey) water and are valuable biomarkers for environmental pollution and ecosystem health.

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  AtıfWoS5·OpenAlex4

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