Sürdürülebilir Kalkınma Amaçları
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- ArticleYalnız künye2026Change-point detection and trend magnitude estimation in long-term streamflow records of a transboundary river basin under climate change
Tanas Savaş, Gülçin; Ertugay, Neşe; Katipoğlu, Okan Mert
Global climate change is reshaping basin hydrology by altering precipitation timing, evaporative demand, runoff generation, and groundwater recharge, which makes long-term streamflow trend detection essential for sustainable water resources management and climate adaptation. In this study, monthly, seasonal, and annual streamflow trends from three gauging stations in the upper Euphrates basin (D21A001, E21A019, and E21A051) were evaluated using an integrated non-parametric framework that combines Mann–Kendall (MK), Spearman’s rank correlation (SRC), Sequential Mann–Kendall (SMK), innovative trend analysis (ITA), and ITA slope (ITAS). This multi-method design allowed consistent identification of trend direction, magnitude, and temporal transition behavior, while also improving interpretive robustness across stations with different streamflow characteristics. The results show a clear common signal: streamflow weakening is most pronounced in the spring to early summer period, although the strength and timing vary by station. E21A019 shows a relatively coherent declining trend across methods, particularly during April–June and at seasonal and annual scales, indicating a stronger tendency toward streamflow reduction compared to the other stations. E21A051 shows a seasonally contrasting regime, with increasing tendencies in winter and late summer/early autumn (notably January–February and August–September), but decreasing trends during spring and early summer, implying intra-annual redistribution rather than uniform change. D21A001 presents weaker trend magnitudes overall, yet decreasing tendencies are still evident in late spring, early summer, and autumn. Across methods, MK and SRC consistently support the trend directions, while ITA/ITAS better highlight magnitude and seasonal contrast. Overall, the findings provide robust evidence of long-term streamflow change and hydrological pressure in the upper Euphrates basin. They can support adaptive and transboundary water management planning, while attribution to specific climatic or anthropogenic drivers requires direct analysis of the relevant forcing variables.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2025Assessment of Heavy Metal Contamination in Sugar Beet (Beta Vulgaris) Plant Along Erzincan–Erzurum Highway in Eastern Anatolia Region
Ertugay, Mustafa Fatih; Ozdokur, Kemal Volkan; Ertugay, Neşe
In this study, it was aimed to determine the traffic and agricultural activity-induced heavy metal including arsenic (As), cadmium (Cd), cobalt (Co), chromium (Cr) and lead (Pb) pollution of sugar beet plants (Beta Vulgaris) grown along the Erzincan-Erzurum D100-25 highway and to reveal the possible change in the amount of heavy metals in sugar beet plants depending on distance to the highway. For this purpose, sugar beet plants were collected from 5 points of 10, 20, 30, 40 and 50 meters away from the highway and heavy metal levels of the samples were determined by inductively coupled plasma mass spectrometry (ICP-MS). The results showed that sugar beet plants were contaminated with various heavy metals such as Cr (585.5-2687.8 µg kg-1) > Co (143.4-500.7 µg kg-1) > Pb (52.1-476.7 µg kg-1) > As (9.1-112.4 µg kg-1) > Cd (4.4-65.2 µg kg-1) depending on the distance from the highway. It was determined that heavy metal pollution levels in sugar beet plants decreased with distance from the motorway and there was a high correlation (As: 0.977; Cd: 0.944; Co: 0.995; Cr: 0.989 and Pb: 0.999) between distance and heavy metal content.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2025Elektrikli Araçların Hava Kalitesi Üzerine Etkisi: PM₁₀, NO₂, SO₂ ve CO Parametreleri Üzerinden Bir Değerlendirme
Seyhan, Aslıhan Kurnuç; Ertugay, Neşe
Hava kirliliği, küresel ölçekte halk sağlığını tehdit eden en önemli çevresel sorunlardan biri olarak öne çıkmaktadır. Bu kirliliğin başlıca kaynaklarından biri olan ulaşım sektörü, artan motorlu taşıt sayısıyla birlikte atmosferdeki zararlı gaz konsantrasyonlarını belirgin şekilde yükseltmektedir. Son yıllarda elektrikli araç teknolojilerinde yaşanan gelişmeler, düşük emisyon profilleri sayesinde hava kalitesinin iyileştirilmesinde etkili bir çözüm olarak değerlendirilmektedir. Bu çalışmada, 2016–2024 yılları arasında Türkiye’de trafiğe kayıtlı motorlu kara taşıtlarının illere göre dağılımı esas alınarak toplam araç sayısının %65’inden fazlasını oluşturan ve taşıt yoğunluğu bakımından en üst sıralarda yer alan iller (örneğin İstanbul, Ankara, İzmir vb.) seçilerek, bu illere ait 2016–2024 yılları arasındaki PM₁₀, NO₂, SO₂ ve CO hava kirletici parametrelerine ilişkin veriler analiz edilmiştir. Aynı dönemde elektrikli ve hibrit araç sayılarındaki değişim göz önünde bulundurularak, araç teknolojilerindeki dönüşümün hava kirliliği üzerindeki etkileri değerlendirilmiştir. Elde edilen bulgular, özellikle PM₁₀, SO₂ ve CO konsantrasyonlarında yıllar içinde belirgin ve kademeli bir azalma olduğunu ortaya koymaktadır. Bu azalma, elektrikli araçların yaygınlaşması, fosil yakıt kullanımının sınırlandırılması, pandemi döneminde sanayi ve ulaşım faaliyetlerinin geçici olarak azalması gibi çok faktörlü yapısal değişimlerle ilişkilendirilmiştir. Ancak bazı illerde NO₂ seviyelerinin artmaya devam ettiği ve ulaşım kaynaklı emisyonların hâlen ciddi bir problem olduğu görülmüştür. Sonuç olarak, elektrikli araçların hava kalitesini iyileştirmede önemli bir potansiyel taşıdığı; ancak bu etkinin sürdürülebilir çevre politikaları, yenilenebilir enerji entegrasyonu ve toplu taşımanın güçlendirilmesi gibi çok boyutlu stratejilerle desteklenmesi gerektiği vurgulanmaktadır.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2025The assessment of rice cultivars widely produced in Turkey in terms of arsenic, cadmium, aluminum and copper: effect of soaking methods and household cooking
Özdokur, Kemal Volkan; Özdokur, Seyhan; Güneş, Abdulaziz; Ertugay, Neşe; Ertugay, Mustafa Fatih
Industrialization-driven heavy metal contamination is a growing concern, as residues are increasingly found in foods and tap water due to soil absorption by plants. This study aimed to assess the amount of heavy metals including arsenic, cadmium, aluminum, and copper in widely produced domestic rice cultivars in Türkiye, and to evaluate the effect of pretreatments and domestic cooking on the concentration of heavy metals. Six different rice cultivars were analyzed using inductively coupled plasma-mass spectrometry to determine the levels of heavy metals. Among these six cultivars, the highest heavy metal contamination and also the most consumed was selected to evaluate the effect of soaking processes accompanied by acetic acid (0.25, 0.50, 0.75, and 1%) and salt (1%) at different soaking times (2, 4, 8, and 12 h) and domestic cooking. The concentrations of heavy metals in the primary rice cultivar with the highest contamination were 64.9, 1.3, 2476.7 and 3185.2 μgkg−1 dry weight, respectively. The results showed that soaking in salt (1%) and acetic acid (1%) before cooking was the most effective treatment for removing heavy metals (As = 57.8%, Cd = 100%, Al = 98%, and Cu = 85.7%) at a soaking time of 12 h.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2025Adsorption of reactive red 2 from aqueous solutions by microwave activated carbon from Thuja Plicata cone powder: kinetic, isotherm, thermodynamic studies and characterisation
Ertugay, Neşe; Keleş Güner, Eda
This study investigates, for the first time, the potential of Thuja plicata (TP) cone-derived activated carbon for the removal of the azo dye Reactive Red 2 (RR2) from aqueous solutions. Activated carbon was produced via microwave irradiation to enhance the adsorption capacity of the raw material. The prepared activated carbon (TPAC), synthesised using a chemical activating agent, was characterised by Scanning Electron Microscopy (SEM), Energy Dispersive X-ray Spectroscopy (EDX), and Fourier Transform Infrared Spectroscopy (FTIR). SEM analysis demonstrated that TPAC exhibited increased surface porosity and an irregular morphology after adsorption at the optimal pH. EDX results confirmed that carbon and oxygen were the dominant elements, with elevated contents post-activation. BET analysis indicated a decrease in the specific surface area from 66.64 to 20.35 m2 g−1 after RR2 adsorption, likely due to pore blockage. Batch adsorption experiments were conducted to evaluate the influence of several parameters, including solution pH, adsorbent dosage, initial dye concentration, and temperature. The maximum removal efficiency (54%) was achieved at pH 3 with an adsorbent dosage of 0.01 g. The adsorption capacity increased with rising dye concentration, reaching a maximum of 309.56 mg g−1 at 60 mg L−1. Adsorption isotherms, kinetics, and thermodynamic properties were also evaluated. The Freundlich isotherm model exhibited the best fit to the equilibrium data, indicating multilayer adsorption on a heterogeneous surface. Kinetic data were best described by the pseudo-second-order model, suggesting that chemisorption was the rate-limiting step. Thermodynamic analysis confirmed that the adsorption of RR2 onto TPAC was a spontaneous and exothermic process.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2025Application of Time Series Methodologies for Robust Forecasting of Atmospheric Pollutant Concentrations: PM10, SO2, NO2, NOx, and O3 in an Urban Environment
Katipoğlu, Okan Mert; Elshaboury, Nehal; Kartal, Veysi; Ertugay, Neşe; Kilinc, Huseyin Cagan; Şenocak, Serkan; Pande, Chaitanya Baliram
In recent years, the concentration of air pollutants has risen significantly due to urbanization and increased transportation. Erzincan province, due to its geographical location, is one of the region's most severely impacted by air pollution. Consequently, it is essential to accurately estimate air quality parameters to effectively analyze and manage the associated health risks. This study utilized a time series methodology to examine hourly air quality parameters, including particulate matter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), nitrogen oxides (NOx), and ozone (O3) throughout the year 2022 in Erzincan province. Various predictive techniques, such as feed-forward neural networks, group method of data handling, long short-term memory (LSTM), and least squares boosting tree methods, were employed for the analysis. For estimating air quality parameters, values delayed by up to 4 h—determined as the effective time period through correlation analysis—were utilized. Prediction performance was evaluated using eight different statistical parameters and visualization techniques. Notably, air quality parameters can be effectively estimated using historical data, with the LSTM model demonstrating superior performance compared to other models in this estimation. Furthermore, the most accurate predictions for O3 values were achieved using the LSTM algorithm, yielding an R2 of 0.93 and a root mean square error (RMSE) of 6.02. The findings of this study can aid policymakers in developing water resource management strategies, pollution control policies, and measures to combat climate change.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2024Semiconductor Catalyst: Investigation for the Degradation of BB9 Azo Dye by Sonophotocatalytic Process
Ertugay, Neşe; Acar, Filiz Nuran
The degradability of an azo dye, Basic Blue 9 (BB9), by heterogeneous sonocatalytic, photocatalytic, and sonophotocatalytic oxidation process was examined using simultaneous irradiation of UV-C at 254 nm and power ultrasound at 20 kHz accompanied with a heterogeneous catalyst zinc oxide (ZnO) in the study. The effect of ZnO dose and initial dye concentration was investigated on the dye degradation in sonocatalytic, photocatalytic, and sonophotocatalytic processes at pH 5.5 (natural pH). The results obtained from the experimental studies were evaluated with the parameters of color removal, pseudo-first-order rate constant, and half-life time. It was observed that the degradation of BB9 dye by the sonophotocatalytic process was higher compared to both sonocatalytic and photocatalytic degradation. as follows: 97.46, 48.64 and 56.88 %. The combination of sono and photocatalytic showed a remarkable synergistic effect in BB9 degradation. The kinetics of sonophotocatalytic oxidations, depending on the initial BB9 dye concentration, were found to follow the Langmuir-Hinshelwood model. In addition, the effect of ZnO on the sonophotocatalytic oxidation process was higher compared to titanium dioxide and zero-valent iron as follows: 97.47, 80.77 and 80.62 %.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2024Modeling of irrigation water quality parameter (sodium adsorption ratio) using hybrid swarm intelligence-based neural networks in a semi-arid environment at SMBA dam, Algeria
Achite, Mohammed; Katipoğlu, Okan Mert; Elshaboury, Nehal; Kartal, Veysi; Aktürk, Gaye; Ertugay, Neşe
Sodium adsorption rate (SAR), which significantly affects soil and plant health, is determined according to the concentration of sodium ions, calcium, and magnesium in irrigation water. Accurate estimation of SAR values is vital for agricultural production and irrigation. In this study, hybrid swarm intelligence-based neural networks are used to model sodium adsorption ratio in irrigation water quality parameters in a semi-arid environment at Sidi M’Hamed Ben Aouda (SMBA) dam, Algeria. For this, the nature-inspired optimization techniques of particle swarm optimization (PSO), genetic algorithm (GA), Jaya algorithm (JA), artificial bee colony (ABC), and firefly algorithm (FFA) and the signal processing technique of variational mode decomposition (VMD) have been combined with artificial neural networks (ANN). Correlation matrices were used to select the data entry structure in the established models. Water quality parameters with a statistically significant and medium to high relationship with SAR values were presented as input to the model. The overall performance was measured using various statistical metrics, scatter diagrams, Taylor diagrams, correlograms, boxplots, and line plots. In addition, the effect of input parameters on model estimation was evaluated according to Sobol sensitivity analysis. As a result, the GA-ANN algorithm demonstrated superior performance (MSE = 0.073, MAE = 0.193, MAPE = 0.048, MBE=-0.16, R2 = 0.934, WI = 0.968, and KGE = 0.866) based on the statistical indicators, indicating better results compared to other models. The second-best model, ABC-ANN (MSE = 0.084, MAE = 0.233, MAPE = 0.066, MBE=-0.135, R2 = 0.897, WI = 0.965, and KGE = 0.920) was also selected. The weakest prediction outputs were obtained from the VMD-ANN model. The accurate and reliable estimation of SAR in irrigation water has the potential to facilitate improvements in agricultural irrigation management and agricultural production efficiency for farmers, agricultural practitioners, and policymakers.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2024A novel metaheuristic optimization and soft computing techniques for improved hydrological drought forecasting
Katipoğlu, Okan Mert; Ertugay, Neşe; Elshaboury, Nehal; Aktürk, Gaye; Kartal, Veysi; Pande, Chaitanya Baliram
Drought is one of the costliest natural disasters worldwide and weakens countries economically by causing negative impacts on hydropower and agricultural production. Therefore, it is necessary to create drought risk management plans by monitoring and predicting droughts. Various drought indicators have been developed to monitor droughts. This study aims to forecast Streamflow Drought Index (SDI) values with various novel metaheuristic optimization-based Artificial Neural Network (ANN) and deep learning models to predict 1-month lead-time hydrological droughts on 1, 3, and 12-month time scales in the Konya closed basin, one of the driest basins in Turkey. To achieve this goal, the ANN model was integrated with the Firefly Algorithm (FFA), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) techniques and compared against long short-term memory (LSTM) networks. While establishing the SDI prediction model, lag values exceeding the 95% confidence intervals in the partial autocorrelation function graphs were used. Model performance was evaluated according to scatter matrix, radar, time series, bee swarm graphs, and statistical performance metrics. As a result of the analysis, the PSO-ANN hybrid model with (R2:0.468–0.931) at station 1611 and the FFA-ANN hybrid model with (R2:0.443–0.916) at station 1612 generally have the highest accuracy.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2022Direct Blue 71 Degradation in the Presence of ZVI and H2 O2 Advanced Fenton Process: Determination of Optimum Conditions and Kinetics
Ertugay, Neşe; Acar, Filiz Nuran
This study investigated color and COD removal of azo dye Direct Blue 71 (DB71) by a Fenton-like process in zero-valent iron (Fe0 = ZVI). The UV–vis spectra of DB71 exhibit three main absorption bands – two in the UV region and one in the visible region. UV–vis spectra showed that the azo linkages in the molecule structure of the dyes were destroyed during the decolorization. The influence of various operational parameters such as pH, ZVI dosages, hydrogen peroxide (H2 O2) concentrations and temperature are studied to determine the optimum conditions for color and COD removal. pH is highly effective parameter of decolorization and COD destruction in this work. However, H2 O2 concentration and ZVI dosages were not only effective in the removal of COD for 100 mgL-1 initial DB71 concentration. Therefore, the optimum ZVI:H2 O2 ratio is based on determining the value of COD removal. Optimum conditions were accepted to be pH of 2.5, ZVI:H2 O2 ratio 4:1 and 20ºC temperature. The result indicated that 100% of decolorization efficiency was achieved within 20 min in the range of 150-400 mg/L initial DB71 concentrations by using optimal conditions. Residual COD values were 15.38, 22.35, 22.58, 27.04, 31.86 mg/L for 150, 200, 250, 300, 400 mg/L initial DB71 concentrations at the end of reaction time, respectively. Additionally, increasing the reaction temperature from 20 to 40ºC negatively affected the decolorization and degradation rate DB71. The experimental kinetic data are fitted very well the Behnajady–Modirshahla–Ghanbery model for color removal of DB71 dye.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2018The Removal of Crystal Violet (CV) Dyestuff by Wheat Bran: Kinetic Studies
Ertugay, Neşe
Treatment of waste water containing dye from widespread use of dyestuff is an important environmental issue. For this reason, color removal processes from waste water of the textile industry containing dyestuffs gaining importance in terms of ecological. Nowadays, alternative methods are needed in order to efficiently and economically remove the dyestuffs in large volume wastewater. In the study, the adsorption of Crystal Violet (CV) which is common in textile waste waters on the wheat bran was investigated. The different initial dye concentrations, pH values, adsorbent concentrations and temperature parameters were tested in order to determine the effects of adsorption on the CV dyestuff and optimum conditions were provided. The highest removal was obtained at the natural pH (6.24). As the amount of adsorbent increased up to certain value, the removal of dyestuff increased. Besides, it was observed that the adsorption reached a balance at 120 minutes and the removal efficiency decreased as the dyestuff concentration increased. However, increasing the temperature from 25°C to 45°C increased the removal of the dyestuff. The suitability of experimental data with Langmuir and Freundlich isotherms and pseudo-first and pseudo-second order kinetic models has been investigated. The parameters of these models and the thermodynamic parameters of the adsorption process were calculated. As part of characterization studies, the functional groups in the biosorption mechanism were examined and structural changes after biosorption were observed by Fourier Transform Infrared (FTIR) and Scanning Electron Microscopy (SEM) analyzes were performed for the wheat bran before and after the adsorption studies.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2018The degradation of landfill leachate in the presence of different catalysts by sonolytic and sonocatalytic processes
Kocakaplan, Nihal; Ertugay, Neşe; Malkoç, Emine
In the study, the degradation of landfill leachate by single ultrasound (sonolytic) and sonolytic combined with Fe2+ and TiO2 catalysts was carried out in laboratory conditions. The effect of pH and ultrasonic wave amplitude was also investigated in terms of color removal, total organic carbon (TOC) and chemical oxygen demand (COD) from leachate by the sonolytic degradation process. In this process, the color removal efficiency was recorded as 81.81% at 620 nm, pH = 2.0 and 70% wave amplitude. The sonocatalytic degradation of landfill leachate accompanied by different catalysts was studied by using the 70% wave amplitude at pH = 2.0 and room temperature for 20 min. The sonocatalytic degradation of leachate by using Fe2+ and TiO2 was found to be significantly higher than sonolytic degradation (p < 0.05). As the Fe2+ concentration increased from 1.0 to 3.0 mg/L, the COD and color removal of leachate significantly decreased (p < 0.05) from 50 to 35.7% and from 95.5 to 90.9%, respectively. The experimental data obtained from sonocatalytic degradation was analyzed using the Behnajady–Modirshahla–Ghanbery (BMG) kinetic models and found to be compatible. The results showed that the combination of catalyst and sonolysis was a highly effective way to remove color, COD and TOC from landfill leachate.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2017Investigation of pH effect by Fenton-like oxidation with ZVI in treatment of the landfill leachate
Ertugay, Neşe; Kocakaplan, Nihal; Malkoç, Emine
In this study, effect of pH by Fenton-like with zero-valent iron (ZVI) process, advanced oxidation process in the leachate treatment, was investigated. The effect of pH value on colour and COD removal from leachate was determined at five initial pH values, 2.0, 2.5, 3.0, 3.5 and 4.0 (ZVI = 0.05 g/L, H2O2 = 150 mg/L). The highest colour and COD yield were obtained at pH 2.0. The colour removal was 87.9% (in 620 nm wavelength) and the COD removal was 74%. Experimental data from COD degradation with the Fenton-like process were analysed by using the zero-, first-, second-order and BMG kinetic models.
RDL Kalıcı Kaydıİncele - Conference ObjectYalnız künye2016The removal of COD and color by Fenton oxidation from leachate of Erzurum municipal solid waste landfill
Kocakaplan, Nihal; Ertugay, Neşe; Malkoç, Emine; Aslan, I.; Polat, K.; Bayrak, Y.; Ekinci, A.; Dadasoglu, F.; Turkoglu, E.A.; Akdemir, A.O.
The optimal conditions for treatment of leachate were determined as pH = 2.5, Fe2+= 2mg/L and H2O2= 100mg/L. Under the optimal conditions, approximately 90% color (at 620nm), 84% color (at 525nm), 74% color (at 436nm) and 47.8% COD removal efficiency from leachate were achieved after 20min of reaction. Depending on the results obtained experiments, Fenton process has been used successfully in removal of COD and color in landfill leachate.
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