Yazarlar
- Katipoğlu, Okan Mert(57)
- Akın, Fatih(15)
- Manga, Muge(12)
- Achite, Mohammed(11)
- Balli, Esra(11)
- Kartal, Veysi(10)
- Yilmaz, Harun(10)
- Destek, Mehmet Akif(9)
- Elshaboury, Nehal(8)
- Demirci, Oğuz Kürşat(7)
- Ganjehsarabi, Hadi(7)
- Yilmaz, Ilker(7)
- Cam, Omer(6)
- Cengiz, Orhan(6)
- Dinçer, Selin(6)
- Elbeltagi, Ahmed(6)
- Manga, Müge(6)
- Seyhan, Aslıhan Kurnuç(5)
- Sigeze, Ciler(5)
- Çatık, Abdurrahman Nazif(5)
- Abdallah, Mohammed(4)
- Acar, Reşat(4)
- Ballı, Esra(4)
- Bazrafshan, Ommolbanin(4)
- Berhail, Sabri(4)
- Dogan, Ahmet(4)
- Kilic, Ugur(4)
- Kuziboev, Bekhzod(4)
- Makhmudov, Samariddin(4)
- Mohammadi, Babak(4)
- Pande, Chaitanya Baliram(4)
- Pandey, Kusum(4)
- Sari, İdris(4)
- Sarıgöl, Metin(4)
- Uzun, Sinem(4)
- Çatik, Abdurrahman Nazif(4)
- Acar, Resat(3)
- Bakirci, Kadir(3)
- Dalkilic, Huseyin Yildirim(3)
- Ekici, Selcuk(3)
Yayınlar
- ArticleAçık Erişim2025Singular Spectrum Analysis for Noise Reduction and Feature Extraction in Hybrid Deep Learning Models: Integrating Meteorological Variables for Improved SGI Predictions
Koç, Erdal; Katipoğlu, Okan Mert
Within the scope of this study, a range of advanced machine learning and deep learning models—including Singular Spectrum Analysis (SSA), Adaptive Neuro-Fuzzy Inference System (ANFIS), Categorical Boosting (CatBoost), Convolutional Neural Network (CNN), Deep Autoencoder, Deep Neural Network (DNN), Gated Recurrent Unit (GRU), and Long Short-Term Memory (LSTM)—were employed to estimate the Standardized Groundwater Index (SGI) in Erzincan Province. SSA was utilized as a preprocessing technique to decompose input variables such as precipitation, relative humidity, temperature, and past SGI values into distinct components including trend, seasonality, cyclicality, and noise. These decomposed components were then fed into the artificial intelligence models to construct hybrid forecasting frameworks. The performance of each hybrid model was evaluated using multiple statistical indicators and visual analyses. The findings demonstrated that incorporating all SSA-derived subcomponents as inputs generally improved the monthly SGI prediction accuracy. However, for 12-month SGI predictions, the results were more variable, with both improvements and deteriorations observed depending on the model configuration. Additionally, the elimination of noise components was found to enhance both model generalization capability and overall prediction performance. Among the models tested, ANFIS emerged as the most effective in capturing GWD dynamics. To further investigate variable importance, Sobol sensitivity analysis was applied to the ANFIS outputs. The analysis revealed that previous SGI-1 values (t − 1) and relative humidity were the most influential inputs in predicting current SGI-1 (t) values.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2025Time-varying dynamics of energy and sustainability uncertainty
Kuziboev, Bekhzod; Çatık, A.Nazif; Pícha, Kamil; Makhmudov, Samariddin; Matyakubova, Aziza; Balli, Esra
This article examines the link between energy-related uncertainty and sustainability uncertainty by utilizing monthly data from November 2002 to October 2022. To this aim, wavelet coherence and time-varying parameter vector autoregression (TVP-VAR) methodologies are utilized. Wavelet coherence results uncover statistically significant long-term correlation between energy and sustainability uncertainties, particularly during periods of global economic crises. The time-varying responses reveal that the impact of energy-related uncertainty shocks is positive over the analysis period. The impacts of energy-related uncertainty are found to be more pronounced during the turbulent periods, such as the 2008 global financial crisis and the COVID-19 pandemic. The time-varying impact of global economic activity on the sustainability uncertainty does not follow a stable trajectory, and it is not statistically significant. The time-varying impact of financial stress on the sustainability uncertainty is not stable, including both positive and negative effects over the analysis period. The results generally reveal the complex interconnections between energy markets, economic conditions, and sustainability issues. This evidence highlights the importance of policymakers taking these connections into account when formulating strategies for energy security and sustainable development, particularly during periods of global economic uncertainty.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2025Explainable artificial intelligence to explore the intrinsic characteristics of climatic parameters governing meteorological drought forecasting: opening the black box
Ozupek, Ertugrul; Teke, Alihan; Celik, Nuri; Kavzoglu, Taskin
Meteorological drought, exacerbated by global climate change, is a recurrent and complex catastrophe that disrupts water resources, agriculture, and economies worldwide. Forecasting future drought conditions is therefore of utmost importance in facilitating effective intervention and adaptation strategies. Artificial intelligence and machine learning techniques have gained attention owing to their potential in forecasting drought severity. However, they are often criticized for their black-box nature and lack of explainability and interpretability. To address this issue, this study explores the potential of local and global explainable artificial intelligence (XAI) tools, including SHAP and LIME, to extract intrinsic characteristics from different drought indices, including Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) and climatic parameters (temperature, relative humidity, and wind speed). These techniques were applied to understand the driving forces behind drought events under different scenarios. SHAP was used to provide global model explanations, revealing how climatic parameters varied in importance across stations and scenarios, while LIME was employed to offer local explanations for specific predictions, highlighting the role of lag time and the significance of each parameter in individual forecasting scenarios. Using data from four meteorological stations in the Konya province of Türkiye, spanning 1965 to 2023, six ensemble-based machine learning models were employed to forecast SPI and SPEI values at 6-month and 12-month scales, resulting in a total of 768 scenarios. Widely used evaluation metrics, namely MSE, RMSE, MAE, MAPE and were employed to compare model performances. The prediction accuracy ranged from 0.513 to 0.864 values, and CatBoost emerged as the best-performing method in the scenario in which SPEI-12 (t), SPEI-12 (t-1), temperature (T), and wind speed (W) were used as inputs. The global explanation using the SHAP revealed that climatic parameters had varying degrees of impact across stations and scenarios, whereas the influence of lag time was significant in the predictive models. Alongside these considerations, LIME and SHAP methods were applied to investigate the status of the parameters at local and global levels. LIME and SHAP analyses also revealed that T and W parameters played less decisive roles at all stations than SPEI(t) and SPEI(t-1) parameters. The conclusion drawn from the current investigation may offer more explainability when working with machine learning algorithms in drought prediction studies, which could be critical for predicting future drought events.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2025Analysis of drought patterns and categories based on the Standard Precipitation-Temperature Index (SPTI): application of fuzzy c-means clustering and principal component analysis
Berhail, Sabri; Katipoğlu, Okan Mert
This study deals with climate variability issues in the Kebir Rhumel basin, situated in northeastern Algeria. This region is experiencing significant changes in climate parameters, which will affect the region’s water resources, agriculture, and overall ecosystem health. The main goal of this study is to examine the severity and frequency of drought from 1981 to 2019. It used the Standard Precipitation-Temperature Index (SPTI), which was recently developed, and clustering methodologies such as c-means and k-means to examine the variation in rainfall patterns characterized by intervals of intense drought and heavy precipitation. These methods help assess the impact of these disturbances in water availability, which result in challenges for agricultural productivity and water management. Additionally, this study points out the significant trend in temperatures over the reported timeline, which aligns with global warming patterns; this intensifies the effect of drought and impacts the region’s water resources. The southeastern and western parts of the basin are areas that experience continuous extreme drought, and different levels of severe drought have been observed over decades. When comparing the results with existing methods, this research has revealed unique climatic trends in this basin area through clustering techniques applied to SPTI results. In particular, 45% of the stations indicate moderate wetness, 35% of the stations experience extreme wetness, and 20% of the stations are extremely dry. Each of these climatic patterns poses distinct challenges for water resource management. These findings demonstrate the complex interplay between rainfall variability, temperature increases, and drought severity. They underscore the urgent need for adaptive water management strategies and plans to address climate change impacts.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2025Enhancing hydrological time series forecasting with a hybrid Bayesian-ConvLSTM model optimized by particle swarm optimization
Kilinc, Huseyin Cagan; Apak, Sina; Ergin, Mahmut Esad; Ozkan, Furkan; Katipoğlu, Okan Mert; Yurtsever, Adem
Hydrological time series forecasting often relies on addressing the inherent uncertainties and complex temporal dependencies embedded in the data. This study presents an innovative hybrid framework, the Bayesian-ConvLSTM-PSO model, specifically designed to tackle these challenges. The framework synergistically combines 1D convolutional neural networks (CNNs), a convolutional Bayesian network, multi-head attention, and long short-term memory (LSTM) networks, with parameters optimized through particle swarm optimization (PSO). The fusion of the convolutional Bayesian network and 1D convolutional neural networks enhances feature robustness by capturing both probabilistic uncertainties and spatial patterns effectively. The multi-head attention model further amplifies this by focusing on the most relevant features, improving the learning process and ensuring better representation of complex temporal dependencies. The proposed model is rigorously tested on daily streamflow data from three flow measurement stations (FMS): Ahullu (D14A014), Kızıllı (D14A080), and Erenkaya (D14A127). Experimental results reveal that the Bayesian-ConvLSTM-PSO model achieves significant performance gains across various evaluation metrics, including root mean square error (RMSE), mean absolute error (MAE), determination coefficient (R2), Kling–Gupta efficiency (KGE), and bias factor (BF). Notably, the model demonstrates exceptional accuracy with an R2 of 0.9950, a KGE of 0.9950, and a bias factor of 0.0003, surpassing the results of PSO-1D CNN-LSTM and benchmark models, such as DNN, DNN-LSTM, and 1D ConvLSTM. These compelling findings underscore the potential of the Bayesian-ConvLSTM-PSO framework as a robust and effective tool for applications in river engineering and hydrological time series forecasting.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2025Comparative analysis of Brazil-Russia-India-China-SouthAfrica-Turkiye in terms of environmental pollution indicators using multi criteria decision making methods
Karabulut, Turgut; Manga, Müge
This study aims to determine the ranking of criteria contributing to environmental pollution for Brazil-Russia-India-China-South Africa-Turkiye countries using multi-criteria decision-making methods based on average data for 2023. It also aims to rank the selected countries according to their performance. Environmental pollution criteria include carbon dioxide emissions, ecological footprint, per capita national income, renewable energy in primary energy consumption, trade, net foreign direct investment inflows, population, environmental policy stringency index and environmentally related technologies. The findings were determined according to the expert opinion-based method as follows: fossil energy use (0.123), carbon dioxide emissions (0.118), population (0.108), per capita national income (0.104), trade (0.099), environmental technologies (0.095), net foreign direct investment inflows (0.094), ecological footprint (0.093), environmental policy stringency index (0.090) and renewable energy in primary energy consumption (0.075). Accordingly, the ranking of the countries—from best to worst—was Turkiye, India, Brazil, South Africa, China and Russia. However, according to the objective method, the variable weights were determined as population (0.152), net foreign direct investment inflows (0.121), environmental technologies (0.118), national income per capita (0.108), fossil energy use (0.101), trade (0.095), ecological footprint (0.094), renewable energy in primary energy consumption (0.089), carbon dioxide emissions (0.062), environmental policy stringency index (0.055). Accordingly, the ranking of the countries—from best to worst—was Turkiye, India, South Africa, Brazil, China and Russia.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2025Integrated Emission and Cost Analysis of Battery-Electric Vehicles up to 2035
Demirci, Oğuz Kürşat
This study quantifies when battery-electric vehicles (BEVs) reach total cost of ownership (TCO) parity with their internal-com-bustion counterparts and characterises the cradle-to-grave greenhouse-gas (GHG) intensity trajectory to 2035. Our contribution is a transparent, Python-based framework that integrates battery-cost learning, ownership economics and life-cycle impacts within a harmonised scenario set, and links them to policy timing, ISO 15118-20-ready bidirectional charging and power-system carbon intensity. Drawing on a systematic synthesis of 221 peer-reviewed sources (2013–2025), the model runs annually for a representa-tive C-segment BEV across three scenarios (Reference, Fast-Progress, Slow-Progress; 2024–2035). The results indicate that, under the median battery-pack price learning trajectory, BEV TCO falls below the ICE benchmark around 2029 (2028–2032 across sce-narios), while life-cycle GHG intensity declines from approximately 73 to 34 g CO2-eq km-1 by 2035, spanning 29–42 g km-1 depending on grid decarbonisation. Global sensitivity analysis identifies battery price as the principal driver of TCO outcomes and grid carbon intensity as the principal driver of emissions outcomes. Results are reported for three regional aggregates (OECD average, EU-27 and China), and the policy discussion highlights contrasts for the United States to contextualise cross-market dif-ferences. Policy alignment on three fronts—parity-linked purchase-incentive phase-outs, rapid deployment of ISO 15118-20-ready bidirectional charging, and stronger recycled-content targets—shortens time to cost competitiveness and amplifies the climate ben-efits of large-scale electrification.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2025Enhanced thermal performance of a flat-plate solar water heating system using nanofluids: a TRNSYS-based analysis
Uzun, Sinem; Seyhan, Aslıhan Kurnuç
This study examines the potential of nanofluids to enhance the thermal efficiency of flat-plate solar water heating systems (SDHW) through numerical modeling using TRNSYS software. Improving the efficiency of such systems is critical for increasing the viability and sustainability of solar thermal technologies, particularly in regions with high solar potential like Türkiye. Three different nanofluids (Al2O3, TiO2, and CuO) were evaluated for their ability to improve heat transfer and system performance. Simulation results revealed that incorporating 0.1% Al2O3 into the working fluid increased the collector outlet temperature from 97 °C (with pure water) to 120 °C, indicating a 23% improvement. Comparable enhancements were observed with TiO2 and CuO nanofluids. Furthermore, collector efficiency, which typically ranges between 35 and 40% under peak solar conditions, was elevated to approximately 45% with the use of nanofluids. These findings suggest that nanofluids significantly improve thermal performance and energy conversion efficiency in SDHW systems. The results highlight the practical potential of nanofluids in advancing solar thermal technology and promoting cleaner, more efficient renewable energy solutions.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2024Analitik Hiyerarşi Süreci (AHS) Metodu İle Of İlçesi’nde (Trabzon) Heyelan Risk Duyarlılığı Analizi
Şenol, Celal; Taş, Mehmet Akif; Yanik, Muhammet Enes
Çalışma alanı olan Trabzon’a bağlı Of ilçesinde topografik özellikler ve iklim hususiyetleri bakımından heyelan afetinin gerçekleşme potansiyeli yüksektir. Son yüz yılda 26’sı ölümle sonuçlanan onlarca heyelan afetine maruz kalan Trabzon’da sadece Of ilçesi 4 adedi ölümlü olmak üzere onlarca maddi hasarlı heyelan afetinden etkilenmiştir. Ortalama eğim ve yükseltinin fazla olması ve yağışın yıllık miktarının (1659,4 mm) ülke ortalamasının (643 mm) oldukça üzerinde olması bu durumu ortaya çıkaran en önemli etkenlerdir. Bu bağlamda Coğrafi Bilgi Sistemleri (CBS) kullanılarak uluslararası mecrada etkinliği ve geçerliliği olan metotlarla heyelan risk analizlerinin yapılması oldukça önemli bir hale gelmiştir. Bu analiz yöntemlerinden olan ve heyelan risk analizi çalışmalarında son yıllarda en çok kullanılan yöntemlerden biri olan ve Analytical Hierarchy Process (AHP) olarak literatüre geçen Analitik Hiyerarşi Süreci (AHS) çalışma alanına uyarlanmıştır. SentinelHub, NASA, Corine, HGM, MTA gibi birçok ulusal ve uluslararası kuruluştan elde edilen veriler ışığında Of ilçesinin AHS ile heyelan risk analizi oluşturulmuştur. Bunun sonucunda ilçenin heyelan bakımından %23’lük bir bölümüne tekabül eden 60 km2 alanında riskli ve çok riskli, %26’sına tekabül eden 67,7 km2 alanında orta ve %51’ine karşılık gelen 132,4 km2 alanda düşük ve çok düşük heyelan riski tespit edilmiştir. Bu analizler sonucunda elde edilen bilgiler dikkate alınarak gerek afet yönetim sürecinde gerekse diğer ilgili alanlarda çalışan paydaşların heyelan afetine karşı hazırlıklı olmaları amaçlanmıştır.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2024Endüstri 4.0 ve Çevresel Sürdürülebilirlik Arasındaki İlişki: Avrupa Birliği Ülkeleri Üzerine Ampirik Bir Analiz
Akın, Fatih; Dinçer, Selin
Endüstri 4.0 olarak bilinen dördüncü sanayi devrimi ve beraberinde getirdiği dijital dönüşüm tüm dünyada her geçen gün etkisini artırmaktadır. Bu eksende Endüstri 4.0 ile yaşanan dijital değişim bireylerin yaşamlarında ve çalışma hayatlarında köklü değişimleri beraberinde getirmektedir. Bireylerin yanı sıra çeşitli endüstrilerin üretim süreçlerinin iyileştirilmesinde de Endüstri 4.0 oldukça dikkat çekmektedir. Diğer taraftan 18. yüzyılda Sanayi Devrimi ile başlayan olumsuz çevresel etkilerin yanı sıra sürekli artan tüketim talebini karşılamak için kullanılan ve tükenmekte olan doğal kaynaklar ülkeleri harekete geçirmektedir. Avrupa Birliği ülkelerinde de Endüstri 4.0 ile ilişkili teknolojilerin benimsenmesini teşvik etmek amacıyla politikalar uygulandığı bilinmektedir. Bu anlamda Endüstri 4.0'ın sürdürülebilir ekonomik büyüme, kalkınma ve çevreye katkı sağlayabileceği fikri gündeme gelmektedir. Bu çalışma Avrupa Birliği’ne üye 27 ülkede Endüstri 4.0 ve çevresel sürdürülebilirlik arasındaki kısa ve uzun dönemli ilişkiyi araştırmayı amaçlamaktadır. Bu amaçtan yola çıkarak çalışmada, 1996-2020 dönemi için panel ARDL/PMG analiz yöntemi kullanılarak çevreyi temsilen ekolojik ayak izi, Endüstri 4.0’ı temsilen ise teknoloji patenti değişkenleri kullanılmıştır. Ayrıca ekonomik büyüme ve enerji tüketimi değişkenleri kontrol değişken olarak kullanılmıştır. Bulgular, Avrupa Birliği ülkelerinde uzun dönemde patent sayısındaki artışın ekolojik ayak izini azalttığını ortaya koymaktadır. Diğer taraftan çalışmada, Avrupa Birliği ülkelerinde ekonomik büyüme ve enerji tüketiminin ekolojik ayak izini artırdığı tespit edilmiştir. Çalışma bulguları, Avrupa Birliği ülkelerinde Endüstri 4.0 teknolojilerinin sürdürülebilir çevre üzerinde önemli etkisinin bulunduğunu ortaya koymaktadır.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2024Climate Change Education in Digital Magazine Format: Evaluation of the M-IKLIM Application
Kenan, Adem; Hazar, Fatma Nur; Akyol, Seda
The purpose of this research is to develop a mobile magazine application (M-IKLIM) that provides content on climate change for middle school students within the scope of the TÜBİTAK (The Scientific and Technological Research Council of Turkey) 2209/A project, and to evaluate the usability of this application. The research was conducted using the Design-Based Research (DBR) method. The study group consists of middle school students. The Mobile Application Satisfaction Questionnaire (MASQ), developed by Namlı (2010), was used as the data collection tool. The obtained data were analyzed using descriptive statistics and correlation analyses. In the descriptive analyses, the mean and standard deviation values of each survey question were calculated. In the correlation analyses, the relationships among the survey data were examined. According to the research results, the M-IKLIM application was generally evaluated positively by the students. Students indicated that the application is user-friendly and suitable for its purpose. The survey results show that the application is generally understandable and not complex. Correlation analyses revealed that user-friendly interfaces and the safety of the application increase student satisfaction. However, it was determined that improvements need to be made in some areas. In future studies, it is recommended to analyze user feedback in more detail and continuously improve the application based on this feedback.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2024Sürdürülebilir Çevre Perspektifinde Türkiye’nin Ekolojik Açığı ve Yakınsama Analizi: Fourier KSS Birim Kök Testi
Akçayır, Ömer; Akın, Fatih
Yerkürenin ürettiği biyokapasitenin oldukça üzerinde tüketilen rezervlerin kendisini yenilemesine imkan vermeksizin ortaya çıkan ekolojik açık giderek artmakta ve gelecek nesillerin refahları hızla yok olmaktadır. Sürdürülebilir bir ekonomik büyüme için bir takım çabalar ortaya konulsa da, ekolojik açığın sürdürülebilirliği merak konusudur. Literatürde çok sayıda çalışmada, çevresel sürdürülebilirlik ve uzun dönem tahmini için yakınsama analizlerini uygulamış, ülke grupları arasında yakınsamanın varlığı araştırılmıştır. Çalışmada, 1961-2022 yılları arasında Türkiye’nin de dâhil olduğu 6 ülke, 4 kıta, 13 bölge ve dünya ortalamasına ait kişi başına düşen ekolojik açık verileri, Christopoulos ve León-Ledesma (2010) tarafından ortaya atılan Fourier tabanlı F-KSS birim kök testleri ile analiz edilmiştir. Uzun dönemde dünya ortalamasının ve birçok ülke ya da bölgenin ekolojik ayak izlerinin biyokapasitenin üzerinde olduğu ve düzelme seyri göstermediği sonucuna ulaşılmıştır. Ayrıca Türkiye‘nin, açıkların sürdürülemez olduğu bulgusuyla diğer 23 seriye yakınsayıp yakınsamadığı analiz edilmiştir. Türkiye’nin uzun vadede Çin, Doğu Asya, Afrika ve dünya ortalamasına yakındığı sonucuna ulaşılmıştır. Avrupa’nın “karbon nötr kıta” vizyonu ile ortaya koyduğu, son dönemlerde yapmış olduğu hukuki düzenlemeler ve yaptırımlardan sonuç almaya başladığı çıkarımıyla, Türkiye’nin bu çevresel düzenlemelere çok hızlı entegrasyonun gerektiği düşünülmektedir.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2024İnternet Kullanımının Ekolojik Ayak İzi Üzerindeki Etkisi: Türkiye Örneği
Özgün, Fergül; Akın, Fatih
Bilgi ve iletişim teknolojilerinin çevre kirliliğini artıracağını öne süren görüşler olmakla birlikte, bilgi ve iletişim teknolojilerindeki gelişmelerin çevre kirliliğini azaltarak çevresel kaliteyi yükselteceğini savunan görüşler de mevcuttur. Bu çalışma, çevresel kalite ile bilgi ve iletişim teknolojileri arasındaki ilişkiyi Türkiye örneği üzerinden incelemektedir. Böylece Türkiye’de hangi görüşün geçerli olduğunun uygulamalı olarak test edilmesi amaçlanmaktadır. Çevresel kaliteyi temsilen ekolojik ayak izi, bilgi ve iletişim teknolojilerindeki gelişmeleri temsilen internet kullanan bireylerin oranı kullanılmıştır. Açıklayıcı değişken olarak da ekonomik büyüme ve enerji tüketimi modele eklenmiştir. Artırılmış Otoregresif Dağıtılmış Gecikmeli (ARDL) sınır testinin uygulandığı analizde 1993-2022 arasındaki yıllık veriler yer almaktadır. Analiz sonuçlarına göre kısa dönemde internet kullanım oranının ekolojik ayak izi üzerinde pozitif ancak anlamsız bir etkisi vardır. Uzun dönemde ise internet kullanımının ekolojik ayak izi üzerindeki etkisi negatif ve anlamlıdır. Türkiye’de internet kullanım oranının artması ekolojik ayak izini azaltarak çevresel kaliteyi olumlu yönde etkilemektedir. Ekonomik büyüme göstergesinin hem kısa hem uzun dönemde ekolojik ayak izine etkisi pozitif, enerji tüketiminin etkisi ise uzun dönemde negatif ve anlamsızdır.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2024Erzincan Binali Yıldırım Üniversitesi Yalnızbağ Yerleşkesinin İklim Değişikliğine Karşı Duyarlılığının Belirlenmesi ve Bazı Yeşil Altyapı Öneri Senaryoları
Yılmaz, Hasan; Gökhan, Askan
Bu çalışmada, Erzincan Binali Yıldırım Üniversitesi Yalnızbağ Yerleşkesinin iklim değişikliğine karşı duyarlılığı incelenmiş ve çeşitli yeşil altyapı senaryoları önerilmiştir. Araştırmanın temel amacı, yerleşkenin mevcut yeşil altyapı sisteminin iklime dirençli olup olmadığını belirlemek ve bu sistemlerin iklime dirençli hale getirilip getirilemeyeceğini değerlendirmektir. Çalışmada, kentlerin iklim değişikliğine uyum sağlama çabalarının önemi vurgulanmış ve açık kentsel yeşil alanların bu çabaların başarısındaki kritik rolü ele alınmıştır. Daha yaşanabilir kentsel çevre ve kampüsler oluşturmaya yönelik bir çok yeni kavramlar (Eko-kent, yaşanabilir kent, sürdürülebilir kampüs, sürdürülebilir kent, dirençli kent, akıllı kent gibi) gündeme gelmekte olup, bazı ülkelerde iyi uygulama örnekleri hayata geçirilmiştir. Erzincan Binali Yıldırım Üniversitesi Yalnızbağ Yerleşkesinin iklim değişikliğine karşı duyarlılığını belirleyerek, değişik yeşil altyapı öneri senaryoları ile yerleşkenin iklim değişikliğinin olumsuz etkilerine karşı dirençli duruma getirilebilmesi amacı ile yeşil altyapı senaryoları üzerinde durulmuştur. Yerleşkenin iklim değişikliğine duyarlı duruma getirilmesine yönelik öneri yeşil altyapı senaryoları; • Kurağa dayanıklı bitki türü kullanımı • Yapı yüzeyi bitkilendirmesinin artırılması • Yağmur hasad bahçelerinin oluşturulması • Biyohendeklerin oluşturulması • Su tüketimini azaltıcı yöntemlerin geliştirilerek yerleşkenin iklim değişikliğine duyarlı duruma getirilmesine yönelik öneri yeşil altyapı senaryoları oluşturulmuştur. Bu çalışma ile kentte ve kampüste yapılacak peyzaj tasarımlarında, suyun sürdürülebilirliğini sağlayacak uygulamaların nasıl yapılması gerektiği noktasında yol gösterici olması hedeflenmektedir.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2024Erzincan’da İklim Değişikliği Sürecinde Kuraklığa Toleranslı İklim Dostu Süs Bitkilerinin Kullanımı
Aslay, Meral; Kalenderoğlu, Hakan; Gökhan, Askan
Bu çalışma, Türkiye'nin iklim değişikliğinin olumsuz etkilerinin giderek daha belirgin hissedildiği ve su stresi yaşayan ülkeler arasında bulunmasından dolayı, peyzaj planlamalarında kurakçıl peyzaj yaklaşımını ön plana çıkarmak amacıyla yürütülmüştür. Çalışmanın materyalini Erzincan Bahçe Kültürleri Araştırma Enstitüsüne ait süs bitkileri koleksiyon bahçesindeki türler ile Erzincan kent merkezi ve 8 farklı ilçesinde bulunan bazı doğal bitkilerden oluşan Ağlayan gelin (Fritillaria imperialis), Allı Gelin (Hesperis isatidea), Çöven (Gypsophila sp.) Osman çiçeği (Vinca soneri), Yayla süseni (İris spuria ssp. Musulmanica), Püsküllübaş (Muscari tenuiflorum), Keşişbaşı (Muscari azureum), Yaban lalesi (Tulipa julia), Sümbül (Hyacinthus orientalis), Çiriş (Eremurus spectabilis), Mürver otu (Sambucus ebulus L), Camışkıran (Sicilia siberica subsp. armena), Boyacı sumağı (Cotinus coggyria) peyzaj değeri olan doğal türler oluşturmaktadır. Çalışma doğal bitki türlerinin kentsel planlamaya dahil edilmesinin sağlayacağı mali avantajların belirlenmesi, varsa eksikliklerin giderilmesine yönelik öneriler sunulması, iklim dostu tasarımlarım artırılması, bitkilerin günümüz iklim şartlarına uyum sağlanabilmesi ve bu alanda çalışan peyzaj mimarları, kentin karar vericileri, şehir plancıları ve araştırmacılar için bir referans teşkil etmesi amaçlanmaktadır. Erzincan Binali Yıldırım Üniversitesi Yalnızbağ Yerleşkesinde oluşturulan ‘Kurakçıl Mini Botanik Bahçesinde’ kültüre alınan 13 farklı türün tamamına yakınının gerek peyzaj özellikleri gerekse iklim değişikliği sürecinde peyzaj tasarımının ana öğesi haline getirebilecek türler olduğu tespit edilmiştir. Kentin karar vericileriyle yapılacak görüşmelerle, bu türlerin gelecekteki peyzaj planlamalarında kullanılması teşvik edilecektir. Böylece, iklim dostu peyzaj planlamaları için kaynak değeri oluşturulacaktır.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2024Examining the Effects of Renewable Energy and Economic Growth on Carbon Emission in Canada: Evidence from the Nonlinear ARDL Approaches
Erdoğan, Esma; Serin Oktay, Duygu; Manga, Müge; Bal, Harun; Algan, Neşe
Increasing industrial activities trigger the intense use of fossil fuels and increase the number of carbon emissions in the atmosphere. Countries with a high share in current carbon emissions need to expand their use of renewable energy sources. Canada is an important energy producer and consumer globally. In this regard, its decisions are important for the future development of global emissions. This study examines the asymmetric effects of economic growth, renewable energy, and non-renewable energy consumption on carbon emissions in Canada from 1965 to 2017. In the first stage of the analysis, unit root testing was performed for the variables. For this, Lee-Strazicich (2003), ADF and PP unit root tests were used. The nonlinear ARDL method was used to analyze the relationship between variables. and Measures: In order to analyze the relationship between the variables in the established model, renewable energy consumption (%), non-renewable energy consumption (%), and carbon emissions (per capita-Mt). In addition, the economic growth (constant price 2010- US$) parameter was added to the model as a control variable. The findings support that energy consumption, economic growth, and renewable energy have an asymmetric effect on carbon emissions in the long run. The positive shock in renewable energy reduces carbon emissions, and a unit increase in renewable energy reduces carbon emissions by 1.29%. Besides, the negative shock in economic growth greatly deteriorates the quality of the environment; that is, a 1% reduction in economic growth causes emissions to increase by 0.74% in the long run. On the other hand, positive shocks in energy consumption have a positive and significant effect on carbon emissions. A 1% increase in energy consumption causes 1.69% carbon emissions. There are important policy implications for Canada to eliminate carbon emissions, increase the share of renewable energy sources and achieve its economic growth targets. In addition, Canada needs to reduce its consumption of non-renewable energy (such as gasoline coal, diesel, and natural gas).
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2024Impact of Internet Use on Ecological Footprint: Panel Data Analysis for Fragile Five Countries (Brazil, India, Indonesia, South Africa, and Turkiye); [Wpływ korzystania z Internetu na ślad ekologiczny: analiza danych panelowych dla pięciu krajów niestabilnych (Brazylia, Indie, Indonezja, Republika Południowej Afryki i Turcja)]
Akın, Fatih; Özgün, Fergül
In addition to the views that claim that the development of information and communication technologies will result in less environmental pollution and better environmental quality, there are also views that claim that it will increase environmental pollution. In this study, the relationship between environmental quality and information and communication technologies for the 1995–2021 period for the Fragile Five countries was examined using the panel augmented autoregressive distributed lag (ARDL) bounds test method. Ecological footprint was used to represent environmental quality, and the proportion of individuals using the internet was used to represent developments in information and communication technologies. In addition, economic growth, energy consumption, and financial development are included in the model as explanatory variables. According to the results of this study, internet use reduces the ecological footprint in both the short and long run. While financial development reduces the ecological footprint in the long run, energy consumption increases both in the short and long run. Economic growth, on the other hand, increases the ecological footprint in the short run. In line with these results, expanding internet use in the Fragile Five Countries may increase environmental quality.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2024The effects of financial development, trade and energy consumption on environmental degradation: Evidence from APEC countries
Balli, Esra; Çatik, Abdurrahman Nazif; Uğur, Mehmet Sedat; Sigeze, Ciler
This paper investigates the relationship among CO2 emissions, energy consumption, economic growth, financial development, and trade in APEC countries based on quarterly data from 1985:Q4 to 2020:Q4 utilizing the Method of Moments Quantile Regression (MMQR). The results demonstrate that both GDP and energy consumption have a positive and statistically significant effect on CO2 emissions. However, this effect diminishes as the conditional quantile of CO2 increases. Additionally, the study reveals that financial development has a positive and significant impact on CO2 emissions, with its influence increasing at higher quantiles. The MMQR estimates suggest that increasing trade openness has led to improvements in environmental quality. Based on these findings, it is recommended that APEC countries implement environmentally friendly policies to achieve sustainable economic development in the region. Hence, it is essential for financial development, energy consumption, and trade openness policies to align with strategies aimed at reducing environmental degradation.
RDL Kalıcı Kaydıİncele - ArticleAçık Erişim2024Analyzing the dynamical relationships between meteorological and hydrological drought of Wadi Mina basin, Algeria using a novel multiscale framework
Achite, Mohammed; Simsek, Oguz; Sankaran, Adarsh; Katipoğlu, Okan Mert; Caloiero, Tommaso
Understanding the relationship between hydrological and meteorological drought in drought-prone regions is critical for proper reservoir management. This study presents a novel multiscale framework for investigating the associations between hydrological and meteorological drought based on the Time-Dependent Intrinsic Correlation (TDIC) method. Firstly, the characteristics of short, medium and long term standardized precipitation index (SPI) and the standardized runoff index (SRI) of the Wadi Mina basin (Algeria) have been analyzed based on data from 6 rainfall and hydrometric stations. Then an Improved Complete Ensemble Empirical Mode Decomposition with adaptive noise (ICEEMDAN) method is used to decompose the most correlated SPI and SRI series to different scales. A stronger association between the two types of droughts is evident in the low-frequency trend component regardless of the station, but their evolution pattern does not remain the same. Subsequently, a TDIC based running correlation analysis is performed between the modes to examine the SPI–SRI associations over the time domain and across the time scales. TDIC analysis has proven the dynamic behavior in the SPI–SRI associations bearing frequent alterations in nature and strength across the process scales and along the time domain. In general, at the intra-annual scales the SPI–SRI correlations are mostly weak positive with localized alterations to negative along the time domain, whereas the relationship is dominantly strong positive and long range at inter-annual scales up to 4 years. This dynamic behavior in the SPI–SRI association and the evolution pattern of trend decipher that the rainfall processes are not directly transferred to streamflow drought, but it also gets controlled by many other local meteorological processes.
RDL Kalıcı Kaydıİncele - ArticleYalnız künye2024Determination of optimum insulation thickness of building walls according to four main directions by accounting for solar radiation: A case study of Erzincan, Türkiye
Köse Özturan, Merve; Kurnuç Seyhan, Aslıhan
Reducing heat transfer from the building will reduce the energy cost required to heat the building. Significant energy savings of 25 % to 50 % can be achieved when the appropriate thickness of thermal insulation is applied to the building walls. In this study, calculations were made to determine the optimum insulation thickness of some thermal insulation materials used to reduce the heat transfer from buildings in Erzincan, located in Türkiye's fourth climate zone. The optimum thickness of the thermal insulation to be applied to the external walls was determined using the heating degree day method, taking into account the effect of solar radiation according to the four main directions. Optimum insulation thicknesses and payback periods were calculated for combinations of two building materials (pumice and bricks), four fuels (fuel oil, LPG, natural gas, and coal), and three insulation materials (XPS, EPS, and Rock wool). The numbers of heating degree days were calculated as 2229 in the north, 1425 in the east and west, and 1118 in the south direction for the four main wall directions. The lowest optimum insulation thickness for these heating degree day values, which minimizes the total heating cost, was obtained for pumice/XPS/natural gas combination. The optimum insulation thicknesses for this combination were calculated as 0.037 m in the north, 0.025 m in the east and west, and 0.02 m in the south direction. The calculated payback periods for all combinations range from 0.9 to 4 years and the payback period of Pumice/XPS/Natural Gas combination is 4 years.
RDL Kalıcı Kaydıİncele
