Environmental Engineering / Çevre Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/4321
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Article Citation - WoS: 5Citation - Scopus: 5A Hybrid Process for 2,4-Dichlorophenoxy Acetic Acid Herbicidal Treatment and Its Microbial Identification by Maldi-Tof Mass Spectrometry(Taylor and Francis Ltd., 2020) Doğdu Okçu, Gamze; Ökten, Hatice Eser; Yalçuk, ArdaThe feasibility of coupling photocatalysis and a biological treatment to remove a herbicide–2,4-dichlorophenoxy acetic acid (2,4-D)–from pure water was examined using batch experiments following three protocols: aerated (A-BR) and non-aerated biodegradation (NA-BR) alone, and intimately combined photodegradation and biodegradation (P-B). In view of a subsequent biological treatment, 15 and 180 min irradiation times were chosen in accordance with spectrophotometric and LC-MS/MS results that indicated the decrease in the COD/TOC ratio during photocatalysis. Pre-treatment led to a quick decrease in concentration of 2,4-D and COD during the biological process: a 78.79 ± 0.30% COD removal and 38.23 ± 3.12% 2,4-D elimination was measured after 5760 min in A-BR, and 80.89 ± 0.81% COD and 81.36 ± 1.37% 2,4-D removal was achieved after 2880 min in P-B. For species identification using matrix-assisted laser desorption/ionization (MALDI)-time of flight (TOF)-TOF/MS equipment, Aeromonas eucrenophila, Stenotrophomonas acidaminiphila, Ralstonia pickettii, Sphingobacterium multivorum and Acinetobacter towneri were identified with high accuracy, and they play important roles in the degradation of 2,4-D.Article Citation - WoS: 12Citation - Scopus: 15Assessment and Improvement of Indoor Environmental Quality in a Primary School(Taylor and Francis Ltd., 2017) Ekren, Orhan; Karadeniz, Ziya Haktan; Atmaca, İbrahim; Ugranlı Çiçek, Tuğba; Sofuoğlu, Sait Cemil; Toksoy, MacitThis study reports levels of indoor environmental quality variables before and after installation of heat recovery ventilation in a primary school located in an urban area in Izmir, Turkey. A CO2-based modeling was performed to determine the required flow rates that would comply with an international ventilation standard, followed by computational fluid dynamics modeling for best airflow distribution in a classroom. Temperature, CO2, PM2.5, and total volatile organic compounds were found at undesired levels, among which relative humidity, CO2, and PM2.5 were improved after the intervention. Reductions in the mean and maximum concentrations were 29% and 68% for CO2 and 29% and 46% for PM2.5. This intervention study was a part of the city-wide main project that aimed to increase awareness of the students and their families, teachers, and staff regarding importance of indoor environmental quality in both at school and home due to its possible effects on children's health and academic performance, one of the major challenges of today's societies all around the globe.Article Citation - WoS: 14Citation - Scopus: 22Forecasting Ambient Air So2 Concentrations Using Artificial Neural Networks(Taylor and Francis Ltd., 2006) Sofuoğlu, Sait Cemil; Sofuoğlu, Aysun; Birgili, Savaş; Tayfur, GökmenAn Artificial Neural Networks (ANNs) model is constructed to forecast SO 2 concentrations in Izmir air. The model uses meteorological variables (wind speed and temperature) and measured particulate matter concentrations as input variables. The correlation coefficient between observed and forecasted concentrations is 0.94 for the network that uses all three variables as input parameters. The root mean square error value of the model is 3.60 g/mt 3 . Considering the limited number of available input variables, model performances show that ANNs are a promising method of modeling to forecast ambient air SO 2 concentrations in Izmir.