Environmental Engineering / Çevre Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/4321
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Article Citation - WoS: 13Citation - Scopus: 14Boron Removal From Geothermal Brine Using Hybrid Reverse Osmosis/Microbial Desalination Cell System(Elsevier, 2023) Jarma, Yakubu A.; Kabay, Nalan; Baba, Alper; Ökten, Hatice Eser; Gören, Ayşegül YağmurAgriculture sector leads worldwide as the most water consuming sector with water demand. Since natural water resources cannot keep up with the demand, a shift from conventional water resources to unconventional ones is needed. While geothermal water was gaining importance for its energy content, small-scale (<10 L/s) energy plants were not required to reinject their spent geothermal brine. As geothermal resources align with agricultural areas in Western Anatolia, discharge of untreated brine might have severe adverse effects on crop yields and soil quality. In this study, we investigated use of spent geothermal brine for irrigation after treatment with Reverse Osmosis/Microbial Desalination Cell (RO/MDC) hybrid process. Treatment efficiencies for B, COD, As, Li, Fe, Cr concentrations and energy production values were determined. Treated water was initially evaluated for irrigation considering three quality categories (I, II, and III) comprised of parameters such as electrical conductivity (EC), total dissolved solids (TDS), and sodium adsorption ratio (SAR), along with sodium, chloride and boron concentrations. Additionally, magnesium adsorption ratio (MAR) and permeability index (PI) were used to evaluate for irrigation suitability. Although B concentrations in MDC-treated permeate (3.29 mg/L) and concentrate (2.99 mg/L) streams were not low enough to meet Quality I criterion (<0.7 mg/L), they can be still utilized in irrigation of moderate-to-high tolerant plants. Furthermore, PI and MAR parameters pointed to suitability for irrigational use. © 2022Article Citation - WoS: 40Citation - Scopus: 47Boron in Geothermal Energy: Sources, Environmental Impacts, and Management in Geothermal Fluid(Elsevier, 2022) Mott, A.; Baba, Alper; Hadi Mosleh, Mojgan; Ökten, Hatice Eser; Babaei, Masoud; Gören, Ayşegül Yağmur; Feng, C.; Recepoğlu, Yaşar Kemal; Uzelli, Taygun; Uytun, Hüseyin; Morata, Diego; Yüksel Özşen, AslıThe problem of hazardous chemicals in geothermal fluid is a critical environmental concern in geothermal energy developments. Boron is among the hazardous contaminants reported to be present at high concentrations in geothermal fluids in various countries. Poor management and inadequate treatment of geothermal fluids can release excessive boron to the environment that has toxic effects on plants, humans, and animals. Despite the importance of boron management in geothermal fluid, limited and fragmented resources exist that provide a comprehensive understanding of its sources, transport and fate, and the treatment strategies in geothermal energy context. This paper presents the first critical review from a systematic and comprehensive review on different aspects of boron in geothermal fluid including its generation, sources, toxicity, ranges and the management approaches and treatment technologies. Our research highlights the origin of boron in geothermal water to be mainly from historical water-rock interactions and magmatic intrusion. Excessive concentrations of boron in geothermal fluids have been reported (over 500 mg/L in some case studies). Our review indicated that possible boron contamination in geothermal sites are mostly due to flawed construction of production/re-injection wells and uncontrolled discharge of geothermal water to surface water. The dominancy of non-ionic H3BO3 species makes the selection of the suitable treatment method for geothermal waters limited. Combining boron selective resins and membrane technologies, hybrid systems have provided effluents suitable for irrigation. However, their high energy consumption and course structure of boron selective resins encourage further research to develop cost-effective and environmentally friendly alternatives.Article Citation - WoS: 1Citation - Scopus: 1Groundwater Recharge Estiaton in the Alaşehir Sub-Basin Using Hydro-Geochemical Data; Alaşehir Case Study(Springer, 2021) Tonkul, Serhat; Baba, Alper; Şimşek, Celalettin; Demirkesen, Ali CanThe issue of groundwater recharge has gained importance in countries where there is not enough water supply to the aquifer. However, groundwater recharge is a difficult parameter to determine. This difficulty stems from factors such as the location of the area to be studied, time, cost, and hydrological data. Numerical, isotope, and chemical approaches are used in groundwater recharge investigations. Numerical and chemical approaches are more costly and time-consuming than chemical approaches. This study aims to ascertain alluvial aquifer recharge in Alaehir (Manisa) sub-basin using chemical approaches (Chloride Mass Balance Method) and its applicability. For this purpose, research wells were drilled at 25 different points in the alluvial aquifer, water sampling was done in wet and dry periods, and rainwater water samples were collected. Groundwater recharge was calculated by using chemical approaches from the chloride concentrations of the water samples collected. An annual average of 74.84 mm of recharge was found in the Alaehir sub-basin. This value corresponds to 16.38% of annual rainfall. At the same time, it was examined the groundwater and geothermal mixing mechanism to demonstrate the applicability of the Chloride Mass Balance Method. It was concluded that geothermal fluid in Alaehir sub-basin mixed with groundwater at a rate of 17%.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.