Sürdürülebilir Yeşil Kampüs Koleksiyonu / Sustainable Green Campus Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7755
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Article Citation - WoS: 16Citation - Scopus: 20Groundwater Recharge Estimation Using Hydrus 1d Model in Alaşehir Sub-Basin of Gediz Basin in Turkey(Springer Verlag, 2019) Tonkul, Serhat; Baba, Alper; Şimşek, Celalettin; Durukan, Seda; Demirkesen, Ali Can; Tayfur, GökmenGediz Basin, located in the western part of Turkey constituting 2% land of the country, has an important groundwater potential in the area. Alasehir sub-basin, located in the southeast of the Gediz Basin and subject to the extensive withdrawal for the irrigation, constitutes the study area. Natural recharge to the sub-basin due to precipitation is numerically investigated in this study. For this purpose, 25 research wells, whose depths range from 20 to 50 m, were drilled to observe the recharge and collect the necessary field data for the numerical model. Meteorological data were collected from 3 weather stations installed in the study area. The numerical model HYDRUS was calibrated using the field water content data. Soil characterization was done on the core samples; the aquifer characterization was performed, and the alluvial aquifer recharge due to precipitation was calculated. As a result, the computed recharge value ranges from 21.78 to 68.52 mm, with an average value of 43.09 mm. According to the numerical model, this amount of recharge corresponds to 10% of the amount of annual rainfall.Article Citation - WoS: 2Citation - Scopus: 2A Deterministic and Stochastic Assessment for Exposure and Risk of Arsenic Via Ingestion of Edible Crops(Springer Verlag, 2019) Can Terzi, Begüm; Gündüz, Orhan; Sofuoğlu, Sait CemilNatural arsenic contamination is a critical problem for various places around the world. Simav Plain (Kutahya, Turkey) is one such area that was shown to have natural arsenic contamination in its waters and soils. Arsenic exposure through ingestion of edible crops cultivated in Simav Plain and associated health risks were assessed in this study. To achieve this objective, arsenic levels in 18 crop species were estimated based on measured soil arsenic concentrations. Individual and aggregate non-carcinogenic and carcinogenic risks associated with ingestion of arsenic-contaminated crops were then assessed with scenario-based deterministic point estimates and stochastic population estimates. Monte Carlo simulation was used for the estimation of population health risks. Accordingly, wheat was found as the highest-ranked crop specie for the both types of health risks, followed by tomato and potato, which are three of the most consumed crops in the region. The risk levels estimated in this study were relatively high, indicating consumption of crops grown in the plain may be posing significant health risks even at lower-bound estimates. Consuming wheat, tomato, potato, and their products from uncontaminated sources was found to reduce the aggregate risks up to 88% implicating the importance of proposing suitable management measures for similar risk-prone areas.Article Citation - WoS: 2Citation - Scopus: 3Integrating Spatiotemporal Dynamics of Natural Capital Security and Urban Ecosystem Carbon Metabolism(Springer Verlag, 2018) Demirkesen, Ali Can; Evrendilek, FatihThe purpose of the study is to address and quantify the increase in urban expansion and carbon (C) metabolism burden on ecosystem service value (ESV), net ecosystem productivity (NEP), and C storage of urban footprint. Urban footprint is required to meet the demands arising from economic consumption and production as well as waste accumulation and assimilation. Spatiotemporal changes in main land covers (LCs) were detected using remotely sensed data (Landsat 5 and 8, and digital elevation model) between 1987 and 2016. Changes in ESV and C influx, efflux and pools associated with LC dynamics were approximated using global proxies for a western Mediterranean region in Turkey of 54,162 km2. Urban expansion over the 29-year period decreased ESV by 22% ($7.28 ± 0.4 billion), NEP by 4.3% (2.3 ± 9 Gg C), and total ecosystem C pool by 10.9% (1008.3 ± 1006 Gg C) and led to a 62.8% appropriation of the total NEP (50.1 ± 51 Gg C) of the urban footprint in 2016. The main cause of the environmental degradation across the study region was the loss of the seminatural areas. Our findings emphasize that the deterioration rate of ecosystems should be slowed down by natural capital-friendly decisions and should not exceed rehabilitation rate of damaged ecosystems in the face of rapidly increasing burdens of the cities on their footprint.Article Citation - WoS: 19Citation - Scopus: 29Modeling of an Activated Sludge Process for Effluent Prediction—a Comparative Study Using Anfis and Glm Regression(Springer Verlag, 2018) Araromi, Dauda Olurotimi; Majekodunmi, Olukayode Titus; Adeniran, Jamiu Adetayo; Salawudeen, Taofeeq OlalekanIn this paper, nonlinear system identification of the activated sludge process in an industrial wastewater treatment plant was completed using adaptive neuro-fuzzy inference system (ANFIS) and generalized linear model (GLM) regression. Predictive models of the effluent chemical and 5-day biochemical oxygen demands were developed from measured past inputs and outputs. From a set of candidates, least absolute shrinkage and selection operator (LASSO), and a fuzzy brute-force search were utilized in selecting the best combination of regressors for the GLMs and ANFIS models respectively. Root mean square error (RMSE) and Pearson’s correlation coefficient (R-value) served as metrics in assessing the predicting performance of the models. Contrasted with the GLM predictions, the obtained modeling results show that the ANFIS models provide better predictions of the studied effluent variables. The results of the empirical search for the dominant regressors indicate the models have an enormous potential in the estimation of the time lag before a desired effluent quality can be realized, and preempting process disturbances. Hence, the models can be used in developing a software tool that will facilitate the effective management of the treatment operation.Article Citation - WoS: 32Citation - Scopus: 37Mcdm Analysis of Wind Energy in Turkey: Decision Making Based on Environmental Impact(Springer Verlag, 2018) Değirmenci, Sinem; Bingöl, Ferhat; Sofuoğlu, Sait CemilDevelopment of new wind energy projects require complex planning process involving many social, technical, economic, environmental, political concerns, and different agents such as investors, utilities, governmental agencies, or social groups. The aim of this study is to develop a tool combining Geographic Information System (GIS) and Multi-Criteria Decision-Making (MCDM) methodologies, and its application for Turkey as a case study. A variety of constraints and criteria were identified based on a literature review and regulations gathered from variety of agencies, use of which resulted in determination of infeasible sites. Then, pairwise comparisons were carried out using analytic hierarchy process as the MCDM method to estimate relative importance of the criteria, and to visualize a suitability map with three classes. As the final stage, decision making was carried out based on environmental impact where 45.5% of the Turkish territory was found as infeasible area. Sixty percent of the remaining area are covered by the moderate suitability class, followed by the highly suitable area (20.3%) and low suitable area (19.8%). The output of this study can be used by energy planners to estimate the extent that wind energy can be developed based on public perception, administrative, and environmental aspectsArticle Citation - WoS: 3Citation - Scopus: 3Channel and Queue Aware Joint Relay Selection and Resource Allocation for Miso-Ofdma Based User-Relay Assisted Cellular Networks(Springer Verlag, 2018) Baştürk, İlhan; Özbek, BernaUser-relay assisted orthogonal frequency division multiple access (OFDMA) networks are cost-effective solutions to meet the growing capacity and coverage demands of the next generation cellular networks. These networks can be used with multiple antennas technology in order to obtain a diversity gain to combat signal fading and to obtain more capacity gain without increasing the bandwidth or transmit power. Efficient relay selection and resource allocation are crucial in such a multi-user, multi-relay and multi-antenna environment to fully exploit the benefits of the combination of user-relaying and multiple antennas technology. Thus, we propose a channel and queue aware joint relay selection and resource allocation algorithm for multiple-input single-output (MISO)-OFDMA based user-relay assisted downlink cellular networks. Since, the proposed algorithm is not only channel but also queue-aware, the system resources are allocated efficiently among the users. The proposed algorithm for the MISO-OFDMA based user-relay assisted scheme is compared to existing MISO-OFDMA based non-relaying and fixed relay assisted schemes and it is also compared with the existing single-input single-output (SISO)-OFDMA based user-relay assisted scheme. Simulation results revealed that the proposed scheme outperforms the existing schemes in terms of cell-edge users’ total data rate, average backlog and average delay.Article Citation - WoS: 2Citation - Scopus: 4Removal of Metals and Metalloids From Acidic Mining Lake (aml) Using Olive Oil Solid Waste (osw)(Springer Verlag, 2019) İlay, Remzi; Baba, Alper; Kavdır, YaseminThe acidic mining lakes have low pH values and high metal and metalloid concentrations. In this study, the ability of low-cost olive oil solid waste (OSW) to remove Al, As, Cd, Fe, B and Ti ions from aqueous solutions in short term has been evaluated. Adsorption capacities (mg g−1) of OSW (1:5–1:10 w/v) were 764.06–411.75 for Al, 0.26 for As, 0.07–0.14 for Cd, 2181.5–2406.5 for Fe, 23.70–82.50 for B and 0.12–0.0.34 for Ti. OSW addition increased acidic mine water (AMW) pH from 2.41 to 3.2 with 1:5 and from 2.41 to 2.7 to 1:10 mixing ratio, respectively, after 10 min. The best gradual decrease has been observed with different ratio of OSW applications on B and Ti concentrations. OSW adsorbs 32.41% and 62.68% of B at the ratio of 1:5 and 1:10 and 55.29% and 83.04% of Ti at the ratio of 1:5 and 1:10 (OSW:AMW) mixtures, respectively. The results show that OSW has great potential for metal removal from acidic mine water.Book Part Citation - WoS: 2Citation - Scopus: 2Energetic and Exergetic Design Evaluations of a Building Block Based on a Hybrid Solar Envelope Method(Springer Verlag, 2018) Mert, Yelda; Saygın, NicelTo achieve sustainable development, there needs to be a focus on decreasing use of non-renewable energy sources and greenhouse gas emissions. In this regard, many studies focus on the strong relationship between energy and the environment. This study aimed to introduce the exergy analysis method into the urban planning field to find out the amount of exergy, rather than energy, that can be conserved in a building block when a solar envelope-based design is applied. In addition to the known energy-efficient design parameters, a criterion for the solar envelop method is integrated into a single method. This hybrid method includes taking into account the requirements for orientation, spacing, landscaping, and building form, as well as the building height properties as proposed in the solar envelop method. The solar envelop method depends on understanding the changing position of the sun throughout the day and year. If this dynamic behavior can be a factor in the design of an urban area, environmental friendliness, sustainability, and reduced energy consumption can comprehensively be achieved in cities.Article Citation - WoS: 14Citation - Scopus: 2Climate Change Mitigation With Renewable Energy: Geothermal(Springer Verlag, 2011) Baba, AlperOn a global scale, there is increasing evidence that climate is changing and of a discernible human influence. Many of scientists are confident that if current emissions of greenhouse gases continue, the world will be warmer, sea levels will rise and regional climate patterns will change. According to some scientist, global temperatures are expected to rise faster over the next century than over any time during the last 10,000 years. From this token, geothermal energy is now considered to be one of the most important alternative energy sources to minimize climate change. Geothermal technologies for power generation or direct use operate with little or no greenhouse gas emissions. Geothermal energy is generally accepted as being an environmentally-friendly energy source, particularly when compared to fossil fuel energy sources. Geothermal resources have long been used for direct heat extraction for district urban heating, industrial processing, domestic water and space heating, leisure and balneotherapy applications. Geothermal energy is used in more than 80 countries for direct heat application and 24 countries for power generation. Re-injection of fluids maintains a constant pressure in the reservoir, thus increasing the field's life and reducing concerns about environmental impacts. Geothermal energy has several significant characteristics that make it suitable for climate change mitigation.Article Citation - WoS: 11Citation - Scopus: 14Categorization of Species Based on Their Micrornas Employing Sequence Motifs, Information-Theoretic Sequence Feature Extraction, and K-Mers(Springer Verlag, 2017) Yousef, Malik; Nigatu, Dawit; Levy, Dalit; Allmer, Jens; Henkel, WernerBackground: Diseases like cancer can manifest themselves through changes in protein abundance, and microRNAs (miRNAs) play a key role in the modulation of protein quantity. MicroRNAs are used throughout all kingdoms and have been shown to be exploited by viruses to modulate their host environment. Since the experimental detection of miRNAs is difficult, computational methods have been developed. Many such tools employ machine learning for pre-miRNA detection, and many features for miRNA parameterization have been proposed. To train machine learning models, negative data is of importance yet hard to come by; therefore, we recently started to employ pre-miRNAs from one species as positive data versus another species’ pre-miRNAs as negative examples based on sequence motifs and k-mers. Here, we introduce the additional usage of information-theoretic (IT) features. Results: Pre-miRNAs from one species were used as positive and another species’ pre-miRNAs as negative training data for machine learning. The categorization capability of IT and k-mer features was investigated. Both feature sets and their combinations yielded a very high accuracy, which is as good as the previously suggested sequence motif and k-mer based method. However, for obtaining a high performance, a sufficiently large phylogenetic distance between the species and sufficiently high number of pre-miRNAs in the training set is required. To examine the contribution of the IT and k-mer features, an information gain-based feature ranking was performed. Although the top 3 are IT features, 80% of the top 100 features are k-mers. The comparison of all three individual approaches (motifs, IT, and k-mers) shows that the distinction of species based on their pre-miRNAs k-mers are sufficient. Conclusions: IT sequence feature extraction enables the distinction among species and is less computationally expensive than motif calculations. However, since IT features need larger amounts of data to have enough statistics for producing highly accurate results, future categorization into species can be effectively done using k-mers only. The biological reasoning for this is the existence of a codon bias between species which can, at least, be observed in exonic miRNAs. Future work in this direction will be the ab initio detection of pre-miRNA. In addition, prediction of pre-miRNA from RNA-seq can be done.