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https://hdl.handle.net/20.500.12451/260

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Synthesis of copper oxide nanoparticles obtained from blackberry (rubus fructicous) leaves and their use in environmental samples
(Gheorghe Asachi Technical University of Iasi, Romania, 2025) Yakut, Şennur Merve; Karataş, Mustafa
The efficacy of an environmentally friendly synthesis method for the removal of paracetamol residue from wild blackberry leaves was investigated in the context of this study. The synthesis involved the formation of copper oxide (CuO) nanoparticles. The dimensions of the nanoparticles were determined to be between 11 and 26 nanometers, with a spherical and crystalline structure. The elemental analysis revealed that the material contained 95% CuO. The pharmaceutical active ingredient paracetamol was removed from wastewater using copper oxide nanoparticles (CuONPs). The advanced oxidation process (UV/H2O2) was employed to remove the target pharmaceutical substance, which was analyzed using HPLC (high performance liquid chromatography device). The results demonstrated that the UV/H2O2 process achieved a 97% removal rate. Furthermore, the copper ion remaining in the environment after paracetamol removal was quantified and found to be 419.6 µg L-1. A kinetic model study was conducted, and it was determined that the method was suitable for the pseudo-second-order kinetic model. In addition to being environmentally friendly, this method is also economical and easy to implement.
Predictive insights into arsenic remediation: Advancing electro and chemical coagulation through machine learning models
(Elsevier Ltd, 2025) Dönmez Öztel, Merve; Alver, Alper; Akbal, Feryal; Altaş, Levent; Kuleyin, Ayşe
Arsenic contamination in water sources remains a critical environmental and public health challenge, mainly due to the toxicity of its trivalent (As(III)) and pentavalent (As(V)) forms. This study compares advanced predictive modeling to enhance arsenic remediation, comparing electrocoagulation (EC) and chemical coagulation (CC) processes for their efficiency and cost-effectiveness. Higher As(III) removal rates were achieved using iron and aluminum electrodes in EC (up to 99 % in 5 min using Fe electrodes) compared to CC (up to 90 % using Fe(II) coagulant). The study's results highlight the operational advantages of EC, including a 40 % cost reduction due to lower chemical usage and sludge production. Machine learning models, including Support Vector Machines (SVM), Regression Trees, Random Forest, and Gradient Boosting, were developed to predict removal efficiencies under diverse operational conditions. SVM exhibited the highest predictive accuracy for As(III) removal in EC with Fe electrodes (MSE = 0.340, R2 = 0.954). At the same time, Regression Trees outperformed other models for As(V) removal in CC with Fe(III) coagulants (MSE = 0.371, R2 = 0.997). These techniques are highly effective in optimizing arsenic removal processes, allowing for precise regulation of treatment parameters and reducing dependence on trial-and-error methods. The findings highlight electrocoagulation with iron electrodes as a sustainable and cost-effective approach to arsenic remediation, particularly for As(III), while underscoring the transformative role of predictive modeling in water treatment. This study successfully integrates experimental insights with machine learning, driving improvements in the efficiency and adaptability of arsenic removal technologies.
Impact of seasonal variations and water quality parameters on the formation of trihalomethanes and haloacetic acids in drinking water treatment processes
(Academic Press, 2025) Alver, Alper; Baştürk, Emine; Kılıç, Ahmet
n this study, the combined effects of seasonal variations and water treatment processes on the formation of disinfection by-products (DBPs), focusing on trihalomethanes (THMs) and haloacetic acids (HAAs) within a full-scale conventional drinking water treatment plant, were investigated. The seasonal analysis revealed that autumn exhibited the highest levels of disinfection by-product formation potential (DBPFP), with trihalomethane formation potential (THMFP) and halo acetic acid formation potential (HAAFP) reaching 255 μg/L and 241 μg/L, respectively, likely due to increased organic matter from leaf fall and runoff. In contrast, winter exhibited the lowest concentrations, with THMFP at 150 μg/L and HAAFP at 56 μg/L. It is attributed to lower temperatures that limit organic matter reactivity. Correlations between 24 water quality parameters and DBPFP types were also examined, identifying critical parameters with the highest correlations. These parameters, including UV254 absorbance and total organic carbon, were used to develop regression models sensitive to seasonal changes and treatment stages. Among the treatment units, the coagulation and aeration stages achieved notable reductions in THM precursors, whereas HAA precursors were less effectively removed, persisting into secondary treatment stages. Chloroform was the predominant THM species, with a peak concentration of 100 μg/L in autumn, decreasing to 76 μg/L in summer, possibly due to increased volatilization in warmer months. For HAAs, dichloroacetic acid displayed the highest seasonal variability, peaking in autumn at 28 μg/L. These findings highlight the need for seasonally adaptive treatment strategies, particularly during high-risk autumn periods when DBPFP levels are elevated. This study provides actionable insights into optimizing treatment protocols to improve DBP control, emphasizing seasonal adjustments’ critical role in ensuring compliance with water quality standards.
Seasonal dynamics and pre-treatment influences on NOM fractions and THM formation potential in a drinking water reservoir: A case study in Aksaray, Turkey
(Elsevier Ltd, 2025) Alver, Alper; Baştürk, Emine; Kılıç, Ahmet
In this study, the seasonal variations of natural organic matter (NOM) and the effects of pre-chlorination and pre-ozonation on disinfection by-product (DBP) formation in Mamasın Dam were investigated. NOM was classified into hydrophilic acids (HIA), hydrophobic neutrals (HON), and other fractions to assess their contributions to trihalomethanes (THMs). Seasonal differences were significant, with total organic carbon (TOC) peaking at 6.564 mg/L in summer due to increased biological activity and dropping to 3.173 mg/L in winter. Pretreatment influenced NOM distribution, with pre-ozonation effectively reducing reactive HON and HIN fractions, leading to a decrease in THM formation potential (THMFP) from 292.5 μg/L in raw summer water to 247.9 μg/L. Regression models (R2 > 0.999) confirmed that HIA and HIN were the dominant THM precursors across all THM species. Model performance was further validated using 10-fold cross-validation, yielding high predictive accuracy across all THM species and confirming the absence of overfitting. Pre-ozonation was more effective than pre-chlorination in lowering THMFP, particularly chloroform, highlighting its superior potential for DBP control. These findings emphasize the critical role of seasonal changes and treatment strategies in NOM reactivity and DBP mitigation. This study provides a framework for fraction-specific and adaptive treatment approaches to improve drinking water safety.
From garbage to biosorbent: overview raw and hexane purified almond shells for nickel (II) ions removal
(Springer Science and Business Media Deutschland GmbH, 2025) Koçyiğit, Hasan; Gök, Gülden; Çelebi, Hakan
The main purpose of the experimental study is to examine Ni(II) biosorption capacities of raw (RAS) and hexane pretreated (HPAS) almond shells by applying them to wastewater. In the context of the study, batch experiments were conducted to investigate the influence of various parameters, including temperature, RAS and HPAS dosages, pH, and contact time, on the removal efficiency of Ni(II). FTIR and SEM–EDX analyses were performed to determine the functional groups and surface morphology of RAS and HPAS. Adsorption capacities were calculated using different isotherm and kinetic models with the obtained experimental data. It was determined that under optimum conditions (2 g RAS/HPAS, pH 5.87, 10 min, 20 °C), maximum removal efficiencies of Ni(II) for RAS and HPAS were 72% and 81.25%, respectively. The equilibrium adsorption fitted the Langmuir isotherm and pseudo-second-order kinetic. The optimum adsorption capacities for RAS and HPAS were found to be 3.60 and 5.67 mg/g, respectively. Four separate error functions were used to evaluate the suitability of isotherm and kinetic models under equilibrium conditions: MPSD, HYBRID, NSD, and ARE. The findings of the error analysis showed that the HYBRID functions were the smallest in all models. The thermodynamic parameters showed that the process was feasible and exothermic. Experimental results demonstrate that RAS and HPAS are economical and readily available adsorbents for the removal of Ni(II) from aqueous solution. It was also found to give satisfactory results for the removal of Ni(II) without the need for rather expensive modified methods.
Comprehensive evaluation of machine learning models for real-world air quality prediction and health risk assessment by AirQ+
(Springer Science and Business Media Deutschland GmbH, 2025) Koçak, Ebru
This study extensively examines five distinct machine learning models used to predict hourly air particulate matter concentrations. The study used real-world data, including pollutant levels and various meteorological parameters, for model training and evaluation, making the study more reliable and effective. The study focused on capturing short-term trends in pollutant concentrations and meteorological conditions. Results showed varied model performances. The Ridge Regression model exhibited a moderate R2 value of 0.44 for PM2.5 prediction and an impressive R2 of 0.91 for PM10 prediction. Support Vector Regression showed strength in PM2.5 prediction (R2 = 0.83) but faced challenges in forecasting PM10. Random Forest and Extra Trees Regression demonstrated robust overall performance, particularly in PM10 forecasting (R2 = 0.75). Extreme Gradient Boosting displayed competitive results for both PM2.5 and PM10 (R2 = 0.80 and 0.81). Each model's identified strengths and limitations provide valuable insights for air quality management, offering a foundation for future research and the development of machine learning models in the continuous pursuit of accurate and timely air quality predictions. The AirQ+ model was used to estimate the health effects of PM2.5 exposure and predict the long-term mortality rates associated with PM2.5. The average estimated attributable proportion for all years is 10.2% (with a range of 6.5% to 13.2%). The results show differing trends in estimated mortality rates, underscoring the need for targeted interventions to reduce the public health risks associated with exposure to polluted air.
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.
Investigation of adsorption behavior of eriochrome black T on mesoporous silica aerogel: experimental and molecular modeling studies
(Yaycı, 2025) Sönmez, G.; Akyüz, L.
Remediating organic dye pollution remains a concern in contemporary water management practices. Developing low-cost and high-surface-area adsorbents synthesised by nanotechnology to eliminate organic dyes is an essential issue in water treatment. Recently, silica aerogels, a kind of nanomaterials, have been investigated as adsorbents due to their high porosity, high surface area, and low cost. This study aimed to synthesize and characterize tetraethoxysilane (TEOS)-based silica aerogel (SA) to assess its efficacy in removing eriochrome black T (EBT), which is a potentially hazardous dye. Based on adsorption studies, the optimal adsorption conditions were found to be 0.2 g adsorbent dosage, pH 2, 120 min contact time, 10 mg L-1 initial EBT concentration, and a temperature of 40 degrees C. The adsorption data were best fitted with a remarkably high correlation coefficient of R2 = 0.999 in the pseudo-second-order model. According to the results of the adsorption isotherm model analysis, the R2 values for the Temkin, Freundlich, and Langmuir models were determined to be 0.971, 0.935, and 0.954, respectively, particularly at the optimally determined temperature of 40 degrees C. Thermodynamically, the process is exothermic and spontaneous. In addition to experimental studies, the WB97x-D level of the Density Functional Theory was used to elucidate the detailed adsorption mechanism between SA and EBT in the water phase. The experimental results are consistent with the computational parameters describing the primary adsorption mechanism, including physisorption processes via electrostatic attraction, van der Waals interactions, and hydrogen bonding.
The Relationship of the Change in Hydrogeochemical Features and Lithium Values of Kızılırmak Basin (Nevsehir-Central Anatolia) Water with Tectonic Fields
(Technical University of Kosice, 2024) Demircioğlu, Ramazan; Elhatip, Hatim
In this study, in particular, the relationship between high lithium values and geological environments was examined. To determine this, the geology, structural geology, hydrogeology, and hydrogeochemistry of the area in the north of the Gülşehir-Yeşilöz sub-basin of the Kızılırmak Basin were investigated. For hydrogeological studies, 19 water samples were collected in May and September. Tectonically, this area has a horst-graben structure. The relationships between the water analysis values of the study area and the tectonic areas were investigated. In particular, the lithium content of the waters in the study area was investigated. Hydrogeochemical properties and seasonal changes in water resources were studied in detail, and their relationship with tectonic areas was evaluated. Water analyses were carried out during wet and dry periods to determine temporal hydrogeochemical changes. According to the analysis, the waters in the area are of Ca-HCO3 and Ca-Mg-HCO3 facies. In addition, there are water samples with high lithium content in the study area. IDW and Kernel diagrams of these were prepared. It was found that these high values were influenced by the rocks formed in the ancient sea and saline lake environments. The region with the highest lithium value is in the formations that represent the former salt lake environment. High lithium (Li) values are generally higher in the region within the Kızılırmak graben. Lithium values in this area were determined as 241.3 µg/L, 154.5 µg/L, 155.2 µg/L, 156.8 µg/L, and 155.6 µg/L.
Bibliometric Insights into Microplastic Pollution in Freshwater Ecosystems
(Multidisciplinary Digital Publishing Institute (MDPI), 2024) Yıldırım, Gökhan; Anindita, Monisha; Pan, Xiao; Rahman, Sumya; Alim, Mohammad A.; Shaik, Rehana; Rahman, Ataur
Microplastic pollution in freshwater ecosystems has emerged as a significant environmental concern, warranting comprehensive investigation, and understanding. This study employs bibliometric analysis to systematically review and synthesize the existing literature on microplastic pollution in freshwater environments from 2013 to 2023. The exponential growth in research output was uncovered by analyzing 885 documents sourced from the Web of Science database, with an average annual growth rate of 73.13% and an average document citation of 30.17. Our findings highlight the dominance of primary and secondary microplastics as pollutants, their ecological consequences, and the resultant socio-economic implications. Notably, the Science of the Total Environment and Environmental Pollution journals emerge as leading publication venues, while China, Germany, and the USA lead in research contributions, underlining the global nature of microplastic pollution research. The analysis further outlines the most commonly cited works, identifying pivotal studies that have shaped current understanding and future research directions. This bibliometric analysis provides a comprehensive overview of the research landscape on microplastic pollution in freshwater ecosystems, helping researchers to identify knowledge gaps and emerging trends. These insights can guide future research directions and inform policymakers and stakeholders on where scientific efforts should be concentrated to better understand and address the impacts of microplastic pollution.
Mapping of heavy metal pollution density and source distribution of campus soil using geographical information system
(Nature Research, 2024) Gök, Gülden; Tulun, Şevket; Çelebi, Hakan
In this study, the pollution intensity, spatial distribution, and index-based risk distribution in campuses, which are a small prototype of cities, were mapped and the sources of heavy metals in the soil were investigated. Soil samples were taken from 9 different points from the Aksaray University Central campus, which was determined as the study area. It has been determined that the pH value in the collected soil samples varies between 8.7 and 11.0. This situation created an effect on reducing the accumulation and mobility of heavy metals in the soil. When the study area was evaluated based on the geo-accumulation index, Pb heavy metal was much denser in the places indicated as circulation areas and where students were actively present. Based on the pollution load index, it was concluded that 75% of the study area was moderately/highly polluted, and the rest consisted of unpolluted soils. Pearson correlation analysis and APCS-MLR analyses conducted to determine the source distribution showed that the contributions of natural sources, mixed sources of industrial and traffic activities, agricultural activity-based sources, and other sources were 57.49%, 21.44%, 12.67%, and 8.40%, respectively. Pb is mainly related to the mixed sources of industrial and traffic activities. Therefore, to clear up its long-term impact on the accumulation of heavy metals in the soil, it is important to conduct continuous heavy metal monitoring in the soil throughout the campus.
Fıstık kabuğu ile sulardan metilen mavisi gideriminin atık yönetimi yaklaşımıyla incelenmesi
(Uludağ Üniversitesi, 2024) Çelebi, Hakan; Tulun, Şevket; Şimşek, İsmail; Bahadır, Tolga; Bilican, İsmail
Boyar maddelerin kullanımının yaygınlaşması, özellikle tekstil endüstrisinin gelişmesi su kirliliğinin en önemli nedenlerinden bir olan boya kirliliğini oluşturmaktadır. Günümüzde metilen mavisi (MM), tekstil endüstrisinde yaygın olarak kullanılan boyar maddedir. Bu çalışmada, atık olarak kabul edilen ham yer fıstığı kabuğunun (YFK) adsorbent olarak kullanılarak metilen mavisinin (MM) giderim şartları incelenmiştir. Herhangi bir işlem yapılmadan alınan YFK adsorbentinin farklı dozlarda (0,1, 0,5, 1, 2, 3, 5 g), işletme sürelerinde (5, 10, 15, 30, 45, 60, 90, 120, 150 dk), pH değerlerinde (2, 4, 6, 8, 10, 12) ve sıcaklıklarında (20, 25, 30, 35, 40 °C) giderim verimine etkileri araştırılmıştır. Yapılan çalışmalarda, en uygun adsorpsiyon şartları: YFK miktarı 0,5 g, işletme süresi 15 dakika, pH 4, sıcaklık 20 °C olarak bulunmuştur. İzoterm modellerinin korelasyon değerleri incelendiğinde en yüksek korelasyon değeri Langmuir izotermine (R2=0,9999) olduğu belirlenmiştir. Gerçekleşen adsorpsiyon mekanizması YFK’nın yüzeyinde tek bir tabaka halinde MM tutulduğu sonucuna varılmıştır. Herhangi bir işlem yapılmadan kullanılan YFK’nın yeşil atık yönetimi yaklaşımı ile boyar madde giderimi için uygun bir adsorbent olarak kullanılabileceği belirlenmiştir.
Sulardan Bentonit ile Nikel ve Kadmiyum gideriminde sıcaklık, doz, boyut ve temas süresinin etkilerinin incelenmesi
(Afyon Kocatepe Üniversitesi, 2024) Güllü, Özlem; Çetin Aslan, Nahide Feyza
Ağır metaller, birikim özelliği ve sucul ortamlardan uzaklaştırılmasındaki güçlük gibi nedenlerle suların kalitesinin bozulup kirlenmesine yol açmaktadır. Nikel ve kadmiyum da bu ağır metalar arasında yer almaktadır. Adsorban olarak Eskişehir bölgesinden temin edilen bentonitin kullanıldığı bu çalışmada sentetik olarak hazırlanan sudaki nikel ve kadmiyumun giderimi amaçlanmıştır. Bentonit kili üzerine nikel ve kadmiyumun maksimum adsorpsiyonunu sağlamak amacıyla pH değeri, adsorban dozu, karıştırma süresi, hız ve metal iyonu konsantrasyonu gibi parametreler incelenmiş, analiz edilmiş ve optimizasyonu sağlanmıştır. Deneysel veriler Langmuir ve Freundlich adsorpsiyon izotermine uyarlamıştır. 0.1 Adsorban boyutu deneylerinde ise en yüksek verim, Nikel için 0,5 mm olarak belirlenirken kadmiyum için ise >2 mm boyutta tespit edilmiştir. Deneysel verilerin Langmuir ve Freundlich adsorpsiyon modellerine uyduğu görülmektedir. Çalışma sonucunda, Eskişehir bölgesinden elde edilen bentonit kilinin sulu çözeltiden kadmiyumun ve nikelin uzaklaştırılması için etkili bir şekilde kullanılabileceği ortaya konmuştur.
Sentetik atıksulardan reaktif sarı 145 boyasının uzaklaştırılması: yer fıstığı kabuklarının adsorban olarak değerlendirilmesi
(Süleyman Demirel Üniversitesi Mühendislik Fakültesi, 2024) Çelebi, Hakan; Bilican, İsmail; Şimşek, İsmail; Bahadır, Tolga; Tulun, Şevket
Hem sektörel hem de evsel kullanımlarla açığa çıkan tarım ve gıda atıkları besin zincirinin en önemli atıklarındandır. Tüm dünyada değerli özelliklere sahip bu atıklar doğrudan çöp alanlarına atılmaktadır. Bu çalışmada, atık olarak çöpe atılan yer fıstığı kabukları toz formda Reaktif Sarı 145’in sentetik çözeltiden giderimi amacıyla kullanılmıştır. Değerlendirme için, sabit karıştırma hızı (150±5 rpm) ve 10±3 mg/L Reaktif Sarı 145 dozunda; pH, temas süresi, fıstık kabuğu dozu ve sıcaklık faktörlerinin etkileri incelenmiştir. Fıstık kabuğunun yapısı ve yüzey kimyası FTIR, pHZPC, ve SEM ile ortaya konulmuştur. FTIR pikleri, fıstık kabuğu yüzeyi üzerinde Reaktif Sarı 145’in tutunabildiğini gösteren spesifik fonksiyonel grupların varlığını ispatlamıştır. Fıstık kabuğu yüzeyindeki gözenekli yapının Reaktif Sarı 145 giderimi için avantajlı olduğu görülmüştür. Optimum şartlarda (Fıstık kabuğu dozu: 0,5 g, pH: 2,0, süre: 30 dakika, sıcaklık: 20 oC) Fıstık kabuğu için yaklaşık %75 Reaktif Sarı 145 verimi elde edilmiştir. Fizisorpsiyonun ön planda olduğu ve tek katmanlı adsorpsiyonun gerçekleştiği sürecin Langmuir ve yalancı ikinci derece modellerine uyduğu görülmektedir. Termodinamik verileri sürecin kendiliğinden ve endotermik gerçekleştiğini göstermiştir. Maksimum adsorpsiyon kapasitesi Reaktif Sarı 145 için 9,438 mg/g olarak tespit edilmiştir. Sonuçlar, fıstık kabuğunun, Reaktif Sarı 145 giderimi için hem umut verici hem de alternatif çevre dostu bir adsorbent olduğunu desteklemektedir.
Quantifying water footprint: A study on the academic and administrative personnel at Konya Technical University
(Techno Press, 2024) Mesutoğlu, Özgül Çimen
This study endeavours to quantify the water footprint of academic and administrative personnel at Konya Technical University. Water footprint assessment, a critical metric for evaluating human impact on water resources, is increasingly recognized as a vital aspect of sustainable resource management. The research involves surveying participants on their water consumption habits, particularly focusing on preferences related to food and sugar intake. Preliminary findings indicate diverse responses in terms of food preference, with a majority favouring low intake. The study aimed to determine the water footprint of the campus in relation to personal consumption behaviours by asking the questions in the "Water Footprint Network (WFN)" to a total of 476 people at the campus, including both the academic and administrative staff. According to the WFN, the average water footprint of the staff was determined as 1694 m3/year.
Efectiveness of electrochemical softening for removing hardness in real groundwater
(Efectiveness of electrochemical softening for removing hardness in real groundwater, 2024) Ulusoy, Merve; Şimşek, İsmail
The applicability of electrochemical treatment which stands out with its advantages over other methods to the removal of hardness in real groundwater was investigated in this study. This treatment method was directly applied in a stainless steel cell used as the anode. Spiral stainless steel with a large surface area was utilized as the cathode. The effects of pH (5.00–11.00), current density (1.89–15.15 mA cm?2), HCO3/Hardness ratio: (0.8/1–1.4/1), and operating time (5–40 min.) parameters on the removal efficiency were investigated. As a result of the experiments, the optimal conditions (initial pH: 7.24, current density: 11.36 mA cm?2, HCO3/Hardness ratio: 1/1, operating time: 20 min.) were determined. Under these conditions, 90% hardness removal and 92% alkalinity removal efficiencies were achieved. The energy consumption for electrochemical softening of 1 L groundwater was calculated as 0.0379 kWh L?1, and the energy consumption per 1 kg of CaCO3 was calculated as 56.90 kWh kg?1CaCO3. Additionally, the cathode surface to which the hardness causing ions adsorbed was imaged using Scanning Electron Microscopy, and Fourier Transform Infrared Spectroscopy analysis of the precipitate on the cathode was performed. The obtained experimental data were statistically evaluated using the multiple linear regression model and the most important independent variable was determined as time.
Assessment and modeling of benzene micropollutant in surface waters proximal to coal-fired thermal power plants
(Taylor and Francis Ltd., 2024) Çimen Mesutoğlu, Özgül; Gök, Oğuzhan
Micropollutants of priority have gained significant attention due to their rising concentrations and persistence in aquatic environments. Among these significant micro-pollutants is benzene, released into the environment because of mining activities, thermal power plants, and certain industrial operations, thereby contributing to environmental contamination. This study monitored benzene concentrations in the Orhaneli River over a year, employing an artificial neural network (ANN) approach to formulate a predictive model for benzene micropollutant concentrations. To provide input to the ANN, Principal Component Analysis (PCA) was employed, utilizing parameters such as precipitation, temperature, humidity, pH, flow rate, dissolved oxygen, conductivity, total organic carbon, and total nitrogen. Eleven backpropagation algorithms were compared, with the Levenberg-Marquardt algorithm identified as the optimal training algorithm. For the selected training algorithm, an optimized number of 6 neurons in the hidden layer provided the best predictions for benzene concentrations. The three-layered optimized ANN model achieved an impressive correlation coefficient (R2) of 0.9889.
Investigation of methylene blue adsorption from aqueous solutions with different carbon nanocomposites
(Springer Nature, 2024) Namal, Osman Önder
In this study, adsorption of methylene blue dye from aqueous solutions was studied using two different nanocomposite materials as graphene oxide–clay (GO-C) and graphene oxide–pumice (GO-P). The experimental studies were carried out on the effect of composition ratio, adsorption kinetics, adsorption isotherms and adsorption thermodynamics together with the effect of solution pH. The adsorption systems for both nanocomposite materials reached equilibrium within about the first 30 min, and the obtained equilibrium concentrations were 78.4 and 21.2 mg/g, respectively, for GO-C and GO-P. It has been concluded that pore diffusion is not only controlling mechanism for the diffusion of dye molecules and the chemisorption was determined as the rate-limiting step. The maximum adsorption capacities for GO-C and GO-P were determined as 89.28 and 22.57 mg/g, respectively, according to results from the Langmuir isotherm model. Thermodynamic findings revealed that the adsorption systems have an endothermic nature. Adsorption capacities significantly increased above pH 8, reaching their maximum values at pH 12 (140.81 ve 142.32 mg/g for GO-C and GO-P, respectively).
Utilization of peanut shell: investigating the adsorption mechanism and optimization of red 195 and reactive black-5
(Springer Nature, 2025) Çelebi, H.; Bahadır, T.; Tulun, Ş.; Şimşek, İ.; Bilican, I.
In this study, peanut shells (PS) called waste were utilized in powdered form for the removal of Red 195 (R-195) and Reactive Black-5 (RB-5) from synthetic wastewater solutions. Various operational parameters such as PS dosage (0.1–5.0 g), pH (2–12), contact time (5–150 min.), and temperature (20–40 °C) were investigated to optimize the batch adsorption process. FTIR, TGA, pHZPC, and SEM analyses were conducted to investigate the structural features and surface chemistry of PS. FTIR analyses revealed the existence of specific functional groups on the PS surface capable of successfully adsorbing R-195 and RB-5. TGA results demonstrated thermal stability for all prepared samples. SEM highlighted the porous structure of PS, which is advantageous for dye adsorption. The process, characterized by physical adsorption predominance and single-layer adsorption, was well-fitted to Langmuir and PFO for both dyes. Maximum removal efficiencies of 95.30% for RB-5 at pH 2.0 and 94.00% for R-195 at pH 2.5 were determined. Thermodynamic factors suggested that the adsorption of R-195 and RB-5 onto PS occurred spontaneously and exhibited an endothermic nature. Due to the interaction with a higher number of functional groups, PS exhibited a higher maximum adsorption capacity for R-195 (27.027 mg/g) compared to RB-5 (10.989 mg/g). The results support the idea that PS can act as an efficient and eco-friendly adsorbent, capable of removing both R-195 and RB-5.
Estimation of the carbon footprint from road transportation: a case study
(Inderscience Publishers, 2024) Aksoy, Samed; Koçak, Ebru
This research aims to estimate the carbon footprint of road transport in Aksaray, Turkey. The study used the Intergovernmental Panel on Climate Change tier 1 and tier 2 methodologies and found alarming increases in CO2 emissions from benzene and diesel, indicating a significant environmental impact. The results also highlight the need for ongoing monitoring and regulation of benzene and LPG emissions due to methodological differences. However, diesel emissions showed consistent assessment approaches between tier 1 and tier 2 methodologies. These findings provide valuable insights into the region’s evolving carbon footprint, emphasising the need for precise methodologies for effective environmental management.

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