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• MakaleAçık Erişim2026Scopus SJRQ1/r/bayburt/14294
  Seasonal and Meteorological Variability of Total Suspended Particulate Matter (TSP) in the Semi-Urban Atmosphere of Bayburt: An Integrated Assessment Based on OpenAir, PCA, and HYSPLIT

  Paloluoglu, Cihan; Akmese Tarlan, Yasemin; Bayar, Serkan

  In this study, atmospheric Total Suspended Particulate Matter (TSP) concentrations in a semi-urban area of Bayburt Province were evaluated in terms of seasonal variation, temporal behavior with meteorological factors, and air-mass transport characteristics. TSP sampling was conducted using the active sampling method over 118 days during the cold and warm-seasons sampling campaign of 2022. A high-volume air sampler (HVAS) and glass fiber filters (GFFs) were used, and TSP concentrations were determined gravimetrically. The mean TSP concentration was 29.13 +/- 29.39 & micro;g/m(3) in cold-season sampling campaign and 43.69 +/- 27.62 & micro;g/m(3) in warm-season sampling campaign. According to standard tests, the seasonal difference was nominally statistically significant (p < 0.05; Cohen's d approximate to 0.51; Cliff's delta approximate to 0.38). However, this significance did not persist after adjusting for serial autocorrelation in the AR(1) model (p = 0.151). However, this comparison should be interpreted not as validated seasonal climatological data, but as a comparison between intermittent sampling studies conducted within a single calendar year. This is because the transition period from spring to summer was not included in the sampling, and the studies were not repeated from year to year. OpenAir analyses showed that high TSP concentrations were particularly associated with easterly and southerly airflows. No clear weekday/weekend difference was observed, although episodic increases occurred on several days. The first two principal components explained 77.8% of the total variance, while the high TSP loading on PC3 indicated complementary variability. NOAA-HYSPLIT backward air-mass trajectory analyses indicated regional transport pathways in most high-TSP episodes, whereas local atmospheric stagnation was prominent in one episode. Overall, the findings show that TSP variability in semi-urban areas should be evaluated together with seasonal-meteorological variability, potential local emission effects, and regional air-mass transport.

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• MakaleAçık Erişim2025Scopus SJRQ1/r/bayburt/11191
  Artificial neural network modelling of reactive red 45 Azo dye removal by peroxi-electrocoagulation

  Bayar, S.; Erdoğan, M.; Taşdemir, A.; Kaleli, A.; Paloluoglu, C.

  In the present study, the Peroxi-electrocoagulation process was employed to remove chemical oxygen demand and the decolorization of reactive red 45 dye wastewater. This process offers several advantages, including the oxidation of dye molecules by hydroxyl radicals and coagulation through iron hydroxide precipitation. The reactor was equipped with six iron electrodes, providing a total surface area of 546 cm2. The effects of applied current (0.3–0.18 A), hydrogen peroxide concentration (100–700 mg/L), initial pH (2.5–5.0), and dye concentration (100–500 mg/L) on chemical oxygen demand and color removal were investigated. Optimum operational conditions were determined to be applied current of 0.150 (corresponding to current density of 0.27 mA/cm2), pH of 3.0, H2O2 concentration of 600 mg/L, and dye concentration of 200 mg/L. Under these conditions, COD and color efficiencies reached 83% and > 99%, respectively. The specific energy consumption under optimal conditions was 33.4 kWh/kg COD with 82.8% COD removal. The findings indicate that increasing the applied current and H2O2 concentration enhances removal performance up to a certain threshold, beyond which no significant improvement is observed. This suggests that the availability of electrogenerated reagents governs the overall reaction efficiency. Additionally, an artificial neural network model was developed to predict COD and color removal efficiencies. The network employed a 4:10:2 architecture and was trained using a backpropagation algorithm. Input variables included applied current, pH, H2O2 concentration, and dye concentration. The model exhibited high predictive accuracy, with R2 of 0.9782 for COD removal and 0.9579 for Color removal, confirming the effectiveness of the ANN in modeling.

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  AtıfScopus3·WoS3·OpenAlex4

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• MakaleAçık Erişim2024/r/bayburt/16333
  Correlating Gas/Particle-Phase Concentration of Indicator Polychlorinated Biphenyls with Meteorological Factors in Bayburt, an Important University City of Turkey

  Paloluoğlu, Cihan

  This study was carried out in two seasons in Bayburt University Baberti Campus (BUBC) in Bayburt city, which is an important university city in Turkey. Gas and particle phase atmospheric concentrations of Urban atmospheric Indicator Polychlorinated Biphenyls (i-PCBs: PCB#28, 52, 101, 118, 138, 153, 180) were determined at first. Then, by using different methods, the interactions between i-PCB concentrations and meteorological factors were investigated. Gas and particle phases of atmospheric i-PCB samples were collected using a high-volume air sampler (HVAS) in BUBC . Following this stage, the samples were analyzed in a gas chromatography-mass spectrophotometer (GC-MS) by passing through appropriate extraction steps. According to the data obtained, the average gas phase ∑i-PCB concentration for the summer month was determined to be 11.314 pg/m3 during the sampling period while the average particle phase ∑i-PCB concentration was found to be 2.145 pg/m3. The average gas phase ∑i-PCB concentration was found to be 4.582 pg/m3 for the winter period while it was found to be 1.756 pg/m3 for the average particle phase ∑i-PCB concentration. In addition, the average total concentrations of i-PCBs were calculated to be 19.797 pg/m3. It was determined that meteorological factors especially temperature (from the Clausius–Clapeyron equation), wind velocity and direction, and rainfall have significant impacts on i-PCB concentration and its distribution. In light of these data, i-PCB concentrations determined in the gas phase were found to be higher than those in the particle phase. In addition, concentration rates determined in summer months were calculated to be higher compared to those calculated for winter months.

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• MakaleYalnız künye2022Scopus SJRQ2/r/bayburt/10974
  Determination of the gas/particle phase concentrations of PCBs in urban and rural atmosphere in Erzurum, Turkey

  Paloluoğlu, Cihan; Bayraktar, Hanefi

  Active sampling was conducted for the first time in Erzurum, Turkey, between August 2012 and January 2013, in order to investigate the presence of 82 polychlorinated biphenyls (PCBs) congeners. Urban and rural ambient air samples, including gas and particle phase atmospheric concentrations (GAPPACs) of PCBs, were collected simultaneously using high volume air sampler (HVAS) at two different sampling points of Erzurum. GAPPACs of PCB samples taken using HVAS in Palandöken Mountain Region (2565 m) and Ataturk University Campus (1870 m) were analyzed in GC–MS following appropriate extraction steps. Throughout the sampling period, total ambient air concentrations (gas phase + particulate phase) were 10 ± 6 and 27 ± 13 pg/m3 (mean) for Palandöken Mountain Region (PMR) and Atatürk University Campus (AUC), respectively. Low molecular weighted PCBs were found to be dominant in both rural an urban sampling sites. Meteorological parameters especially temperature (from Clausius–Clapeyron equation), wind direction, wind velocity, and precipitation were found to be effective on PCB concentration and distribution. The gas-particle distributions of PCBs in the summer and winter period were found to be 82% (gas phase) and 18% (particle phase) in the PMR and 90% (gas phase) and 10% (particle phase) in AUC, through Junge-Pankow adsorption model. In the light of these findings, total PCB concentrations detected in urban atmosphere (due to possible PCB sources) were observed to be higher than those determined in rural area.

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  AtıfScopus1·WoS1

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