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A solution of taste and odor problem with activated carbon adsorption in drinking water: detailed kinetics and isotherms
(Desalination Publications, 2022) Alver, Alper; Baştürk, Emine; Altaş, Levent; Işık, Mustafa
In this study, 2-methylisoborneol (2-MIB) and geosmin (GSM) adsorption pathways on steam-ac-tivated wood-originated powder activated carbon were investigated. Firstly, EN 12903 analysis was carried out, giving information about the activation, origin, and suitability of usability as an adsorbent in drinking water treatment plants of activated carbon, and it was found that it was activated by steam, was of wood origin, and suitable for the basic requirements for the adsorption of 2-MIB and GSM. A series of experiments including contact time, the concentration of metab-olites, initial pH of the solution, and dosage of activated carbon were performed on raw surface water samples. Many kinetic and isotherm models known in the literature have been applied to explain the 2-MIB and GSM adsorption on powdered activated carbon (PAC). As a striking feature of the isotherm models, it was concluded that the multilayer physical and/or chemical adsorptions of 2-MIB (R2 = 0.636) and GSMBET(R2 = 0.777) occurs on the macro and mesopores BET of PAC, the adsorption capacity of PAC is higher for 2-MIB (kF = 0.146, qe = 0.9904) than for GSM (kF = 0.023, qe = 0.9252), and the adsorption of GSM (RL = 0.970) and 2-MIB (RL = 0.951) on PAC are reversible. Among the kinetic models, the pseudo-second-order model was found to be the most successful in describing the adsorption of 2-MIB and GSM on the PAC. According to the pseudo-second-order kinetic model, the chemical or physical adsorption situation is not in equi-librium. Therefore, the intraparticle diffusion model applied to find the adsorption mechanism shows that 2-MIB and GSM are physically adsorbed on the external surface of the PAC in the first 16 min, and diffusion from macropores to meso and micropores occurs during the next 74 min. More time is needed for the adsorption to reach equilibrium.
Adaptive neuro-fuzzy inference system modeling of 2,4-dichlorophenol adsorption on wood-based activated carbon
(John Wiley and Sons Inc., 2020) Alver, Alper; Baştürk, Emine; Tulun, Şevket; Şimşek, İsmail
Phenolic compounds cause significant problems both in drinking water and wastewater due to their toxicity, high oxygen requirements, and low biodegradability. They are listed as primary pollutants by the United States Environmental Protection Agency and the European Union. In this study, the adsorption efficiency of 2,4-dichlorophenol (2,4-DCP) on activated carbon, which is commonly used in treatment plants, was investigated under different experimental conditions including adsorbent dose, initial phenol concentration, initial pH, and contact time. As a result of experimental studies, it was determined that the adsorption isotherm and kinetics could be perfectly fitted to Langmuir and the assumption of pseudo-second order model, respectively. Then, the adaptive neuro-fuzzy inference system (ANFIS) model was developed, which was the primary purpose of this study. The correlation between training and testing data and the ANFIS output was over 0.999. The generalization ability of the model was found to be 0.999. The input variables such as adsorbent dosage (14.2%), initial concentration (14.6%), initial pH (13.9%), and the contact time (57.2%) showed a higher effect on 2,4-DCP removal efficiency in the sensitivity analysis. To summarize, modeling studies that are frequently preferred in treatment plants for the removal of different pollutants will reduce the number of experiments harmful to human health and save time, labor, and economy.
Adaptive neuro-fuzzy interference system modelling for chlorpyrifos removal with walnut shell biochar
(Elsevier B.V., 2021) Tulun, Şevket; Akgül, Gökçen; Alver, Alper; Çelebi, Hakan
Accumulation of chlorpyrifos (CP), a pesticide, causes a significant environmental problem in food, surface/ground waters further to human health. The removal of the CP pollutant in surface/wastewater could be achieved by biochar due to the improved physical and chemical properties. In this work, the CP removal capacities of biochar samples derived from walnut shells at various temperatures from 450 to 900 °C were investigated. The experiments were performed as laboratory batch type study and the adsorption efficiency was determined at various conditions such as adsorbent dosage (10–500 mg/L), sorbate concentrations (100–1500 µg/L), contact time (0–300 min), initial pH (3–10), and the number of recycle. By subtracting the pyrolysis temperature from 450 °C to 900 °C, the surface areas were found to increase from 12.9 m2/g to 353.3 m2/g, respectively. The 143 experimental data were evaluated by a pair of kinetics and isotherm models and the Adaptive Neural Fuzzy Inference System (ANFIS). The developed ANFIS model was 98.56% successful in predicting the CP removal efficiency depending on the adsorption conditions. Walnut Shell Biochar (WSBC) can be applied for CP adsorption with 86.64% removal efficiency under optimum adsorption conditions (adsorbent = 250 µg/L, sorbate = 1000 µg/L, pH = 7.07 and contact time 15 min) thanks to its improved porosity. It was determined that the biochar samples could be reused 5 times.
Aksaray ili düzenli depolama sahası sızıntı suyu karakterizasyonu ve elektrokimyasal arıtılabilirliği
(Aksaray Üniversitesi Fen Bilimleri Enstitüsü, 2012) Alver, Alper; Altaş, Levent
Sızıntı sularının değişken karakteri, kompleks yapısı ve yüksek kirletici içeriği nedeniyle çevresel ortamları kirletme potansiyeli oldukça yüksektir. Sızıntı suyu miktarı genel olarak çöp içindeki neme ve depolama sahasına düşen yağış oranına bağlı olarak değişir. Sızıntı sularının özellikleri; depolanan katı atığın niteliği yanında içerdiği yüksek organik ve azotlu maddelere, ağır metallere, organik ve inorganik tuzlara bağlı olarak değişir. Sızıntı suyu karakterizasyonu; deponi yaşı ve buna bağlı olarak işletilen arıtma tesisinin verimliliği açısından önemlidir. Bu çalışmada, Aksaray Düzenli Katı Atık DepolamaSahası'ndan aylık periyodlarla sızıntı suyu örneklemesi yapılmış ve karakterizasyon için her bir örnekte belirli parametrelerin (KOİ, BOİ, TA, TF, AKM, pH, alkalinite, sıcaklık, TKA, TOK, toplam sertlik, orto-fosfor, toplam fosfor ve ağır metaller) analizleri yapılmıştır. Sızıntı suyu analizlerine göre deponinin ?genç? yaşa sahip olduğu (BOİ/KOİ = 0.44-0.8) bulunmuştur. Yapılan karakterizasyon çalışmalarında KOİ, BOİ ve TKA derişimlerinin mg/L cinsinden sırasıyla 8365-44000, 5500-30000 ve 630-1940 değişim gösterdiği bulunmuştur. Karakterizasyon belirleme çalışmaları esnasında ayrıca sızıntı suyu elektrokimyasal arıtıma tabi tutulmuş ve %75'e varan KOİ giderimi elde edilmiştir.
Carbamazepine Adsorption onto Giant Macroporous Silica and Adaptive Neuro-Fuzzy Inference System Modeling
(Springer Nature, 2024) Alver, Alper; Yılmaz, Bahar Akyüz; Bilican, Behlül Koç; Baştürk, Emine; Kaya, Murat; Işık, Mustafa
There is an imperative need to eliminate pharmaceutical residues from aquatic environments due to their hazardous properties, including toxicity, mutagenicity, and carcinogenicity, particularly when present in water sources. Conventional water treatment methods have proven insufficient in addressing nano-pollutants such as pharmaceutical residues. Consequently, the ongoing quest for economically viable, sustainable, and environmentally friendly removal mechanisms persists. In this particular study, we employed Giant Macroporous Silica (GMS) derived from marine sponges as a promising biosorbent. GMS exhibits commendable characteristics, including a high specific surface area, swift mass transfer capabilities, and non-discriminatory adsorption qualities. The efficacy of GMS in adsorbing carbamazepine (CBZ), a common drug residue, was scrutinized under diverse experimental conditions, including a sorbate/sorbent ratio ranging from 0.005 to 1.500 weight ratio, contact times spanning from 0 to 240 min, and initial pH values ranging from 5 to 9. Remarkably, at a concentration of 1000 µg L?1, GMS demonstrated an attractive adsorption rate (98.88%) of carbamazepine at pH 7.07, within 90 min. To enhance our understanding, we developed an ANFIS model utilizing the experimental parameters as inputs. The developed model exhibited a high correlation coefficient of 0.9944% and a root mean square error (RMSE) of 1.6693, indicating its dependability in accurately predicting the adsorption of CBZ on GMS. The results of our study highlight the efficacy of GMS in adsorbing CBZ, suggesting its considerable potential for adsorbing other pharmaceutical residues and nano-pollutants.
Catalytic ozonation by iron coated pumice for the degradation of natural organic matters
(MDPI, 2018) Alver, Alper; Kılıç, Ahmet
The use of iron-coated pumice (ICP) in heterogeneous catalytic ozonation significantly enhanced the removal efficiency of natural organic matters (NOMs) in water, due to the synergistic effect of hybrid processes when compared to sole ozonation and adsorption. Multiple characterization analyses (BET, TEM, XRD, DLS, FT-IR, and pH(PZC)) were employed for a systematic investigation of the catalyst surface properties. This analysis indicated that the ICP crystal structure was alpha-FeOOH, the surface hydroxyl group of ICP was significantly increased after coating, the particle size of ICP was about 200-250 nm, the BET surface area of ICP was about 10.56 m(2) g(-1), the pH(PZC) value of ICP was about 7.13, and that enhancement by iron loading was observed in the FT-IR spectra. The contribution of surface adsorption, hydroxyl radicals, and sole ozonation to catalytic ozonation was determined as 21.29%, 66.22%, and 12.49%, respectively. The reaction kinetic analysis with tert-Butyl alcohol (TBA) was used as a radical scavenger, confirming that surface ferrous iron loading promoted the role of the hydroxyl radicals. The phosphate was used as an inorganic probe, and significantly inhibited the removal efficiency of catalytic NOM ozonation. This is an indication that the reactions which occur are more dominant in the solution phase.
Characterization and electrocoagulative treatment of landfill leachates: A statistical approach
(Institution of Chemical Engineers, 2017) Alver, Alper; Altaş, Levent
The purpose of this research was to comprehensively evaluate the characterization and the optimization of electrocoagulation for sanitary landfill leachate treatment in Aksaray/Turkey. This is the first study conducted with regard to both the characterization and the electrochemical treatment of leachate in Aksaray province. For this purpose, leachate samples were collected in situ at a monthly interval for a period of 13 months and physicochemical parameters and heavy metals were monitored. Meteorological data were also recorded for the same sampling period to calculate the leachate production amount (LPA) and to correlate between the physicochemical parameters. The results were statistically analyzed by using Pearson correlations analysis, SPSS software. In the next step, the leachate was treated by the electrocoagulation (EC) method with aluminum and iron plate electrodes together in a laboratory-scale batch process. The effects of process variables such as current densities, time, and pH were investigated for chemical oxygen demand (COD) removal. Stepwise regression analysis was done for determining which variable, acting independently, best explains or predicts the variation in the removal efficiency of COD. As a result of this study, a feasible model containing variables of the electrocoagulation process on COD removal was derived using stepwise regression analysis. © 2017
Determining the contribution of the wastewater treatment plant to the sustainable environment with water footprint indicators
(Springer, 2023) Kalya, Esra; Alver, Alper
Millions of cubic meters of water are polluted every day as a result of industrialization and other human activities. The contribution of the Wastewater Treatment Plant, which was built to prevent this pollution, to the water cycle was examined through water footprint indicators in this study. In the study, the wastewater treatment plant was evaluated for treated and non-treated cases, and the contribution of the plant to the grey water footprint was determined from the difference between the two cases. Wastewater Treatment Plants not only save the volume of water in the receiving environment but also protect the water quality. This study revealed that as a result of the treatment of industrial and domestic mixed wastewater with a pollution load of 396.297 mg biochemical oxygen demand L-1, 924.245 mg chemical oxygen demand L-1, 26.139 mg total nitrogen L-1 2.76 mg total phosphorus L-1, and 426.861 mg total suspended solids L-1, in the Wastewater Treatment Plant, it recovered an average of 14,375,243 m(3) of freshwater per month in the water cycle by protecting the Class III (medium) water quality of receiving environment. The calculations made in the study are based on the Water Footprint Assessment Manual. The volume of recovered water is 19 +/- 14 times larger than the inlet flow of wastewater treatment. On the other hand, the total amount of freshwater consumed directly and indirectly in the wastewater treatment is 3696 m(3) month-1. 97.093% of the indirect blue water footprint is used for the generation of electrical energy. This study reveals all aspects of the Wastewater Treatment Plants contribution to the sustainable environment with the natural water cycle and the protection of the receiving water quality.
Development of adaptive neuro-fuzzy inference system model for predict trihalomethane formation potential in distribution network simulation test
(American Institute of Physics, 2021) Alver, Alper; Baştürk, Emine; Kılıç, Ahmet
Trihalomethanes (THMs), which is one of the major classes of DBP known to be highly cytotoxic and genotoxic, were formed and modeled under controlled conditions by laboratory-scale distribution network simulation test. The formation potentials of THM depending on the parameters such as natural organic matter, bromide, chlorine, pH, and contact time were determined. Subsequently, the Adaptive Neuro-Fuzzy Inference System (ANFIS) model was developed using these parameters as inputs and THM formation potentials as output, and the correlation coefficient was 0.9817. In the range of the inputs, the ANFIS model representing the simulation test results were compared with THM formations of an actual distribution network system in dry and wet seasons. As a result, the predictions of the ANFIS model were little affected by the unidentified factors that were not used in model training but are known to affect THM formations in real waters and gave more consistent results than the EPA model.
Disinfection by-products formation potential along the Melendiz River, Turkey; associated water quality P parameters and non-linear prediction model
(Springer, 2018) Alver, Alper; Baştürk, Emine; Kılıç, Ahmet
Organic matters in raw water have a potential to generate harmful disinfection byproducts such as trihalomethanes (THMs) and haloacetic acid (HAA) during the chlorination process. The aim of this study was to investigate the trihalomethane formation potential (THMFP) and haloacetic acid formation potential (HAAFP) in Melendiz River and to determine the effect of several factors including water quality parameters, distance, and seasonal variation. Water samples (n= 93) were collected at Melendiz River during December 2015-November 2016. The range of THMFP and HAAFP was 47.28-3348.73 mu g/L and 41.42-4952.68 mu g/L, respectively. ANOVA analysis was performed to understand the impact of the seasonal and/or distance changes on DBPs formation. It was found that the seasonal variations (sig. <= 0.01) are more effective than distance variations (sig. > 0.80) at Melendiz River. Finally, a non-linear statistical model was developed based on Multiple Stepwise Regression Analysis using highly correlated water quality parameters with TTHM and THAA 5 in Pearson Correlation Analysis. According to the results, among all factors, flow, dissolved organic carbon (DOC), UV254, UV272 , bromide, temperature, and additional chlorine dose have a remarkable effect on THMFP and HAAFP. Especially, the Pearson correlation (P) values for the DOC and the Chlorine dosages are 0.583, 0.786 and 0.994 and 0.865 for THMFP and HAAFP models, respectively. In addition to this, the high R-2 (0.95) values were obtained when compared to other predictive models. The local model development should be utilized because each water source has different organic characterization. For this reason, the development of local models for each water source is important for achieving more consistent results.
Efficient purification of aqueous solutions contaminated with sulfadiazine by coupling electro-Fenton/ultrasound process: optimization, DFT calculation, and innovative study of human health risk assessment
(Springer Science and Business Media Deutschland GmbH, 2023) Nasab, Ehsan Abbasi; Nasseh, Negin; Damavandi, Sobhan; Amarzadeh, Mohamadamin; Ghahrchi, Mina; Hoseinkhani, Atefeh; Alver, Alper; khan, Nadeem A.; Farhadi, Asadollah; Danaee, Iman
In the current work, the hybrid process potential of ultrasound (US) and electro-Fenton (EF), named sono-electro-Fenton (SEF), was fully investigated for sulfadiazine (SDZ) degradation. The decontamination in the integration approach was revealed to be greater than in individual procedures, i.e., EF process (roughly 66%) and US process (roughly 15%). The key operating process factors (i.e., applied voltage, H2O2 content, pH, initial concentration of SDZ, and reaction time) affecting SDZ removal were evaluated and optimized using Box-Behnken Design (BBD). In addition, an adaptive neuro-fuzzy inference system (ANFIS) as an efficient predictive model was applied to forecast the decontamination efficiency of SDZ through the SEF process based on the same findings produced from BBD. The results revealed that the predictability of SDZ elimination by the ANFIS and BBD approaches exhibited an excellent agreement (a greater R 2 of 0.99%) among the both models. Density functional theory was also employed to forecast the plausible decomposition elucidation by the bond-breaking mechanism of organic substances. Plus, the main side products of SDZ degradation during the SEF process were tracked. Eventually, the non-carcinogenic risk assessment of different samples of natural water containing SDZ that was treated by adopting US, EF, and SEF processes was examined for the first time. The findings indicated that the non-carcinogenic risk (HQ) values of all the purified water sources were computed in the permissible range.
Evaluation of conventional drinking water treatment plant efficiency according to water quality index and health risk assessment
(Springer, 2019) Alver, Alper
The objective of this research is to investigate the effluent water quality of a treatment plant in Turkey fed from surface and groundwater, according to water quality index (WOI) and health risk assessment (HRA). In order to achieve this goal, the quality of the influent and effluent water of the treatment plant was monitored monthly from January 2017 to January 2019. Water quality parameter results were compared with the Turkish drinking water standards and the World Health Organization (WHO), revealing that all parameters were within approved limits. Principal component analysis (PCA) was applied to determine the water quality parameter impacts in the overall quality of water and the most attractive parameters were trace elements, heavy metals, NH3-N, NO3, and TKN. To evaluate water quality and the impacts on human health, WQI and HRA, including hazard quotient (HQ) and hazard index (HI), were used. The WQI values were calculated by taking into account PCA results. WQI results demonstrated that the influent and effluent of water treatment plant values have a small number of WQI ranking that expressed the water category was “excellent” for drinking purpose. Finally, metal contamination in influent and effluent waters was assessed and the associated health risks to rural populations were estimated for different age groups, children and adults in the service area of the treatment plant. The health risk assessment with similar to WQI results, the acute, sub-chronic, and chronic risks of trace elements was “negligible” level, i.e., to a level affecting 1 person in 1,000,000 inhabitants.
Gümüş nanopartiküller eşliğinde katalitik ozonlama prosesleri ile sucul ortamdan doğal organik maddelerin giderimi: Ozonlama ürünlerinin belirlenmesi
(Gazi Üniversitesi, 2020) Alver, Alper; Altınışık Tağaç, Aylin
Bu çalışmada, yüzeysel sulardaki doğal organik maddeleri temsilen sentetik olarak hazırlanmış hümik asit (HA) çözeltilerinin gümüş bazlı nanopartiküllerle zenginleştirilmiş montmorillonit (AgNP@MMT] katalizörlüğünde ozonlama prosesleri ile arıtılabilirliği araştırılmıştır. Katalizör dozlarının değiştirildiği arıtım çalışmalarında doğal organik maddenin (DOM) bozunumu ve alifatik-aromatik yapısındaki değişimleri izlenilmiştir. Katalizör miktarındaki artışa bağlı olarak ÇOK giderimindeki değişkenlik %67,80- 76,61 arasında olmuştur. Ayrıca heterojen katalitik ozonlamada •OH radikallerinin varlığı organik radikal harcayıcı olarak bilinen tert bütil alkol (TBA) kullanılarak kanıtlanmıştır. Arıtma işlemi sonrasında çıkış suları klorla dezenfeksiyon işlemine tabi tutulmuş ve oluşan Trihalometan (THM) ve Haloasetik Asit (HAA) türleri kantitatif olarak diğer oksidasyon ara ürünleri ise kalitatif olarak tespit edilmiştir. THM ve HAA oluşum potansiyelleri, katalizör dozu ve süre artışına bağlı olarak maksimum %79,50ve %80,40 oranında azalmıştır. Katalitik ozonlama ile HA’nın bozunumu sonucunda oluşan küçük molekül ağırlığına sahip ara ürünler, ortamdaki •OH ile tekrar reaksiyona girmekte ve farklı ara ürün gruplarını oluşturmaktadır. Ortamda tespit edilen ara ürünlerin yapısı incelendiğinde genel olarak aldehit, keton ve asit gruplarının baskın olduğu görülmüştür. Analiz sonuçları oluşan en önemli aldehitler arasında Benzaldehit ve 2,4-dihidroksi-6- (2'- oksoheptil) benzaldehit’in olduğunu göstermiştir.
Innovative and cost-effective approaches to enhance nutrient removal and energy efficiency in conventional wastewater treatment plants
(Academic Press, 2025) Alver, Alper; Küçükbayrak, Mustafa
The 42 Evler Wastewater Treatment Plant (WWTP), originally operated as a conventional activated sludge (CAS) system, was transformed into an advanced biological system using the Modified Ludzack-Ettinger (MLE) process scheme, significantly improving nutrient removal and energy efficiency. Integrating anoxic-aerobic zones and optimizing microbial dynamics enhanced treatment performance, with total nitrogen (TN) and total phosphorus (TP) removal efficiencies increasing from 28.1 % to over 80 % and from 56.4 % to 89.6 %, respectively. These improvements were achieved alongside a 32.9 % reduction in energy consumption. Detailed microbial analyses identified key new species, such as Nitrosomonas and Thiobacillus, whose roles in nitrification and denitrification pathways were pivotal for improving treatment performance. Integrating anoxic-aerobic zones, advanced aeration systems, and optimized sludge management further contributed to the system's sustainability. Evaluating pollutant removal efficiencies before and after the upgrade, supported by statistical analyses, confirmed significant improvements in BOD5, COD, TN, TP, and TSS removal. The microbial community was comprehensively assessed, revealing the specific roles of microorganisms in nutrient removal and process optimization. These advancements align with stringent discharge standards and global environmental goals, demonstrating how microbial insights and process innovations can modernize wastewater treatment. The upgraded system provides a scalable and efficient framework for addressing environmental and operational challenges in wastewater management.
Katalitik ozonlama işlemi ile sulardan dezenfeksiyon yan ürünleri öncüleri gideriminin araştırılması
(Aksaray Üniversitesi Fen Bilimleri Enstitüsü, 2017) Alver, Alper; Kılıç, Ahmet
Demir kaplı pomzanın (DKP) heterojen katalitik ozonlamada kullanılması, tekil ozonlama ve adsorpsiyonla karşılaştırıldığında hibrit proseslerin sinerjik etkisinden dolayı sucul çözeltideki dezenfeksiyon yan ürünlerinin (DYÜ) öncüsü olarak bilinen doğal organik maddenin (DOM) giderim verimini önemli ölçüde arttırmaktadır. Katalizör yüzey özelliği, ozon uygulama verimliliği ve hidroksil radikallerinin (OH•) oluşumu açısından önemli bir faktördür. Bu yüzden DKP yüzeyindeki katalitik reaksiyon mekanizması sistematik olarak reaksiyon kinetikleri kullanılarak incelenmiştir. Karakterizasyon analizleri (XRD, FT-IR, TEM, BET, DLS ve pHPZC) yüzey yapısındaki kaplama prosedürünün etkinliğini ve katalizör yüzeyinin fiziko-kimyasal özelliklerini araştırmak için gerçekleştirilmiştir. DOM bozunmasına heterojen katalitik ozonlamada direk/dolaylı ozonlamanın ve yüzey adsorpsiyonun katkıları katalizörün yüzey kaplaması dolayısıyla oluşan OH• varlığı, organik radikal harcayıcı olarak bilinen tert bütil alkol (TBA) kullanılarak reaksiyon kinetiği analizleri ile ortaya konulmuştur. İnorganik kirletici olarak fosfat kullanılmıştır ve çözeltideki OH• harcamasına bağlı olarak katalitik DOM ozonlamasındaki giderim verimini önemli bir şekilde engellediği fakat ara yüzey reaksiyonlarını engellemediği ortaya konulmuştur. DKP sucul çözeltideki DOM bozunması için etkili bir yeşil katalizördür.
Modeling azo dye removal by sono-fenton processes using response surface methodology and artificial neural network approaches
(Elsevier, 2019) Baştürk, Emine; Alver, Alper
Textile industry wastewaters, which cause serious problems in the environment and human health, include synthetic dyes, complex organic pollutants, surfactants, and other toxic chemicals and therefore must be removed by advanced treatment methods. Determination of appropriate treatment conditions for efficient use of advanced treatment methods is an important and necessary step. In the last thirty years, the Artificial Neural Network-Genetic Algorithm (ANN-GA) and Response Surface Methodology (RSM) have emerged as the most effective empirical modeling and optimization methods especially for nonlinear systems. Reactive Red 195 azo dyestuff was chosen as the target pollutant. The color removal efficiency was modeled and optimized as a function of Sono-Fenton conditions such as H2O2 dosage, Fe2+ dosage, initial pH value, ultrasound power, and ultrasound frequency, using ANN-GA and RSM. The generalization and predictive ability of these methods were compared using the results of the 46 experimental sets generated by the Box-Behnken design. The mean square errors for these models are 3.01612 and 0.00295, and the regression coefficients showing the superiority of ANN in determining nonlinear behavior are 0.9856 and 0.9164, respectively. In optimal conditions, the prediction errors with hybrid ANN-GA and RSM models are 0.002% and 3.225%, respectively.
Optimization of landfill leachate oxidation at extreme conditions and determination of micropollutants removal
(Desalination Publications, 2017) Argun, Mehmet Emin; Alver, Alper; Karataş, Mustafa
The advanced oxidation of macro- and micro-organic pollutants from the landfill leachate using the Fenton reaction was investigated. Central composite design with response surface methodology was applied to evaluate the interaction and relationship between operating variables (i.e., pH, reaction time, ferrous iron and H2O2 dosages) and to develop the optimum operating condition. Based on statistical analysis, quadratic models for the two responses (chemical oxygen demand [COD] and aromatic content [UV254]) proved to be significant with very low probability values (<0.001). The obtained optimum conditions were 1,755 mg/L Fe2+ and 26,422 mg/L H2O2 concentration, pH 3.72 and 99 min reaction time. The results obtained by the predicted model were 70, and 54% removal for COD and UV254, respectively, with optimum conditions. The predicted results fitted well with the results of the laboratory experiment. A wide range of analysis was conducted for micropollutants and some volatile organic compounds, pharmaceuticals, pesticides, plasticizers, polycyclic aromatic hydrocarbons and heavy metals were detected. Removal efficiencies of some micropollutants including bis(2-ethylhexyl)phthalate, anthracene, benzene hexachloride, dieldrin, diuron, chlorpyriphos and diclofenac were between 90% and 99% with Fenton oxidation at the optimum condition. It was also determined that heavy metals decreased as a result of co-precipitation after oxidation.
Prediction of full-scale filtration plant performance using artificial neural networks based on principal component analysis
(Elsevier, 2020) Alver, Alper; Kazan, Zeynep
To obtain standard water quality is one of the most crucial issues must be discussed. To get higher water quality, the separation and purification processes must be applied. In this study, 44 water quality parameters were monitored between May 2018 and February 2019 in order to evaluate the efficiency of a full-scale filtration plant which uses particulate-, micro- and ultrafiltration processes as a pre-treatment and applied reverse osmosis as the post-treatment. A crucial research question of this study was thus whether the Ultrafiltration (UF) and Reverse Osmosis (RO) systems performance about the elimination of monitored parameters. The most striking results from the monitoring study reveal that the pre-treatment processes are not suitable for separation of uni/polyvalent ions. The hypothesis that will be tested for both systems; the UF process was efficient for microbial and nitrogen parameters and the RO was efficient for separation of anions and metals that are identified priority hazardous substance. Then, the purification performance of a filtration plant was evaluated using the Artificial Neural Network (ANN) model based on the Principal Component Analysis (PCA) that used to reduce the number of input water parameters. PCA components were used as input in the model and according to the results of Pearson Correlation Analysis, the conductivity parameter which was directly or indirectly related with almost all parameters was used as output. Consistency of created ANN model with real data was 98.758% and mean square errors was 0.00293.
Removal of aspartame by catalytic ozonation with nano-TiO2 coated pumice
(Elsevier Ltd., 2019) Alver, Alper; Baştürk, Emine
Aspartame is widely used as an artificial sweetener and has been ubiquitously detected in various water sources, it is unstable and can produce some harmful degradation products under certain storage conditions. In this study, the degradation of aspartame through adsorption, single ozone, and catalytic ozonation was investigated. In order to create an eco-friendly catalyst, pumice surface was covered with nano-TiO2 and physicochemical surface properties of the catalyst were systematically investigated by SEM, EDX, FT-IR, BET, DLS, and pHPZC analysis. It was proved by SEM and EDX analysis that the nanostructures were homogeneously dispersed onto the catalyst surface and the surface of the catalyst was enriched at 5.5% by weight relative to the uncoated state. After coating, the catalyst surface area expanded by about 10 times and the pore diameters from 0.008 to 0.044. After characterization studies, the role of sole adsorption and sole ozonation in catalytic ozonation has been tried to be determined by using different doses of aspartame, catalyst, and ozone. In the catalytic ozonation experiments, reaction kinetics were analyzed in the presence of tert-butyl alcohol (TBA) that is a radical scavenger, and it was confirmed that the activity of •OH radicals increased after using n-TCP as a catalyst. The results demonstrated that sole ozonation and adsorption of aspartame was not effective for removal. The rate of removal increased significantly with combining adsorption and ozonation. Synergism percentage was calculated to be 91.53. The benefit of surface adsorption, hydroxyl radicals, and sole ozonation to catalytic ozonation was determined as 2.96%, 72.20%, and 24.84%, respectively. Although ozonation of aspartame was initiated by •OH radical, both •OH– radical and O3 might be involved in the aspartame removal.
Removal of exhaust gas with advanced solar photocatalytic asphalt applications
(Springer Verlag, 2022) Bolakar Tosun, Hümeyra; Alver, Alper; Baştürk, Emine
Air pollution in developing and developed countries, especially in urban and industrial areas, is one of the biggest problems of the world. Air pollution can lead to various adverse outcomes such as condensation of the greenhouse effect, acid rain and public health problems. The most significant source of environmental pollution in urban areas is road transportation. This study aimed to determine the effectiveness of solar photocatalytic asphalt materials in reducing the air pollution problem (NOx-nitrogen oxides) caused by the vehicles. The photocatalytic asphalt material, which can be enhanced by solar rays, was produced by applying nano titanium dioxide (TiO2) to asphalt pavements under suitable heat treatment using the spraying and direct additive methods. Scanning electron microscopy and X-ray diffraction analyses were performed to determine the physicochemical and morphological characteristics of the material. Following the characterization study, the photocatalytic activity capacities of the asphalt material produced by both methods was determined. Experiments on NOx removal were carried out under different conditions including catalyst dosage, humidity, temperature, initial NOx concentration and contact time. According to the results, conventional asphalt pavements and TiO2 photocatalytic asphalt pavements were compared in terms of NOx removal efficiency. The optimum conditions were determined as follows: catalyst utilization method = spraying modification, catalyst dosage = 1.5 g/L, humidity = 35%, temperature = 25°C and, initial pollutant concentration CO = 2,500 ppm, NO = 750 ppm, NO2 = 75 ppm and NOx = 825 ppm. In conclusion, it was determined that photocatalysts can be used functionally to solve environmental problems and the solar radiation could be used for the removal of nitrogen and oxide derivatives successfully.

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