International Journal of Global Warming (20 papers in press)

Regular Issues

• Investigation and Performance Evaluation of a Solar PV/T-Based Multi-Generation Plant for Clean Hydrogen Production  
  by Fatih Y?lmaz, Murat Ozturk, Re?at Selba? 
  Abstract: This research focuses on the thermodynamic analysis of a solar photovoltaic/thermal (PV/T)-based combined plant that uses energy and exergy efficiency to generate clean power, hot water, cooling, and hydrogen. This newly developed scheme is organized by a solar PV/T unit, a transcritical Rankine cycle (tRC) with an ejector, and a PEM electrolyzer. A comprehensive parametric analysis and dynamic modeling are fulfilled to determine the system performance changes. According to the analysis results, the developed plant can generate 9.153 kW of net electricity, 88.39 kW of cooling load, 151.9 kW of hot water, and 0.00002395 kg/s of green hydrogen. Finally, the system had 25.80% energy efficiency and 11.63% exergy efficiency.
  Keywords: Energy; exergy; solar PV/T; green hydrogen; transcritical Rankine Cycle.
  DOI: 10.1504/IJGW.2025.10070013
   
  
• Energy Monitoring and Performance Evaluation of New Generation Photovoltaic Modules  
  by Aykut Güzel, Mehmet Azmi Aktacir 
  Abstract: This study compares bPV and mPV modules with single-axis solar tracking systems (SAST) and fixed system installations in Sanliurfa, Turkey. The performance of the PV modules is evaluated by creating a comprehensive data set over one year. The results provide valuable insights for designing more effective and efficient systems for solar projects. SAST achieved 9.91% more bifacial gain for bPV technologies and 8.23% more energy output for mPV technologies than the fixed system. Tracking bifacial technology increased output per watt by 23.07% compared to fixed monofacial technologies, with the best performance ratio of 0.89 for the year.
  Keywords: bifacial photovoltaic module; bifacial gain; single axis solar tracking; performance ratio; IEC 61724-1.
  DOI: 10.1504/IJGW.2025.10070026
   
  
• GIS-Based Evaluation of Impact of Land Use on Bioclimatic Comfort Levels  
  by Tuba Rastgeldi Dogan, Can Bülent Karakuş 
  Abstract: The aim of this study is to reveal the relationship between bioclimatic comfort levels and land use determined by the weighted overlap method and Universal Thermal Climate Index (UTCI) method using environmental climate parameters (ECP) for the years 1990-2018 in ?anl?urfa province. The relationship between bioclimatic comfort levels and land use was determined with the help of Geographic Information Systems (GIS). According to the results of this study, the most bioclimatically comfortable areas determined according to both methods in 1990 and 2018 overlapped with agricultural areas and this overlap was more evident in the annual period, spring and autumn.
  Keywords: Bioclimatic comfort; GIS; land use; ?anl?urfa.
  DOI: 10.1504/IJGW.2025.10070274
   
  
• Modelling the Solar-Powered Electrocoagulation Process for Textile Wastewater Treatment Using IoT Technology  
  by Fatma Didem Alay, Benan Yazıcı Karabulut, Harun Çiğ, Fatma Zuhal Adalar 
  Abstract: This study designs and simulates a sustainable textile wastewater treatment system that aligns with green transformation principles. The proposed model integrates electrocoagulation powered by photovoltaic energy to reduce carbon footprint and operational costs. An IoT-based control unit, including hardware and software components, is simulated to facilitate measurement, management, monitoring, and control of all devices and data flows. The system uses a Raspberry Pi module connected to sensors measuring key water quality parameters, enabling real-time monitoring and control through a cloud-based application interface. Simulation results validate the effectiveness of the proposed system in achieving sustainable and intelligent wastewater management.
  Keywords: Electrocoagulation; Textile Wastewater Treatment; Internet of Things; Photovoltaic System; Simulation; Process Optimization; Renewable Energy.
  DOI: 10.1504/IJGW.2025.10070371
   
  
• The Impact of Agri-Voltaic Systems on Carbon Reduction: Pathway to Net-Zero Emissions by 2050  
  by Aykut Güzel, Serkan ÇA?, Yusuf Can Demir, Mehmet Azmi Aktacir 
  Abstract: In experimental and simulation studies conducted in Sanliurfa for agricultural PV systems, this study determined that the bPV module in SAST reached the highest energy production capacity with 23% more energy compared to mPV modules in the fixed system. Furthermore, it was determined that using PV systems can prevent 1.702.865 t-CO2-eq/MWh carbon emissions for electricity consumed in irrigation activities in Sanliurfa in 2023. This study emphasises that using PV systems in energy-intensive areas such as agricultural irrigation will contribute to reducing carbon emissions in line with the IEA's Net Zero 2050 targets.
  Keywords: Bifacial PV; Single-Axis Solar Tracker; Agrivoltaics; PVsyst; Carbon Reduction.
  DOI: 10.1504/IJGW.2025.10070498
   
  
• Effects of the Hydrothermal Carbonization Conditions on the Energy Yields of Hydrochar derived from Treatment Sludge  
  by Özlem Demir, Betül F?rat 
  Abstract: Hydrothermal carbonisation is a promising technology that can convert to biomass to hydrochar. One of used biomass is treatment sludge with many advantages such as high organic content. Hydrochar derived sludge can be used for several proposes in environmental researches. Solid/liquid fraction, temperature and operation time are the main parameters for the hydrothermal carbonisation. In this study, these conditions were optimised using Box-Behnken statistical design in terms of energy yields. According to the results, the highest heating value is obtained as 18.29 MJ/kg with solid/liquid ratio of 0.09, the time of three hours and temperature of 185.82
  Keywords: Energy; calorific value; high heating values (HHV) treatment sludge; hydrothermal carbonization; hydrochar; Box-Behnken Statistical Design.
  DOI: 10.1504/IJGW.2025.10070499
   
  
• Electrical Efficiency Analysis of Building Integrated Photovoltaic/Thermal Systems in hot Climates: Comparison of Bifacial and Monofacial Panals  
  by Yusuf Can Demir, Aykut Güzel, Mehmet Azmi Aktacir 
  Abstract: This study investigates the performance of a Building Integrated Photovoltaic/Thermal (BIPV/T) system with bifacial and monofacial panels in Sanliurfa's summer conditions. Experiments were conducted with different fan speeds, air gap distances, and cooling strategies. Results show that bifacial panels achieved 18.19% higher efficiency than monofacial panels and performed better in high temperatures. Increasing the air gap distance has enhanced efficiency, especially in bifacial panels, due to the reflective surface behind the panel. Artificial cooling further boosted efficiency, emphasising its potential for hot climates. It was observed that BIPV/T performance was significantly enhanced through optimised airflow, panel technology, and cooling methods.
  Keywords: Building Integrated Photovoltaic/Thermal (BIPV/T); Bifacial and Monofacial Panel; Cooling Strategies; Energy Efficiency; Hot Climate Performance.
  DOI: 10.1504/IJGW.2025.10070709
   
  
• Assessing Inter-City Carbon Flow Dynamics in the Context of Multivariate Urbanisation: A Study Based on Spatiotemporal Big Data  
  by Wen Zhang, Zhao Jing, Wei Xuan, Junhan Tang, Liwei Zhao, Chaoyang Zhu 
  Abstract: This study delves into the inter-city carbon flow dynamics within urban clusters from the perspective of multivariate urbanisation. This article employs network analysis techniques to trace the dynamics of carbon flows across 41 cities in the Yangtze River Delta (YRD) multiple perspectives, including economic, social, public housing, and ecological urbanization. Utilising advanced gravitational models, Social Network Analysis (SNA), and Quadratic Assignment Procedures (QAP), it evaluates the characteristics of carbon flow networks and identifies key influencing mechanisms. Our network analysis provides a unique vantage point on regional carbon emissions strategies, harmonising them with multifaceted urbanisation for sustainable, long-term development.
  Keywords: New Urbanization; Multivariate Systems; Spatial Structure; Regional Carbon Mitigation; Carbon Flow.
  DOI: 10.1504/IJGW.2025.10070874
   
  
• Assessment of Different Index Methods' Effects on the Parameters of Meteorological Drought in the Context of Global Climate Change  
  by Yavuz Avsaroglu, Oguz Simsek, Veysel Gumus, Ahmet Erhan Eren 
  Abstract: In this study, meteorological drought analysis is evaluated on 3-, 6- and 12-month time scales at four stations in Istanbul. The Standardised Precipitation Index, based on only precipitation data, and the Standardised Precipitation EvapotranspirationIn data, considering potential evapotranspiration values with Thornthwaite and dex, hinged on precipitation and temperature Hargreaves equations, are used for drought analyses. The innovative trend analysis is used to determine the trends of droughts. As a result, no significant differences were found in the temporal distribution of drought in all the methods used. The increase in severity of the index values calculated at the stations was remarkable after 2007.
  Keywords: Istanbul; meteorological drought; SPI; SPEI; Thornthwaite; Hargreaves; ITA; trend.
  DOI: 10.1504/IJGW.2025.10070995
   
  
• Mitigation of Carbon Dioxide Emission from Potable Water Treatment using Biochar in Terms of Water-Carbon Nexus: a Green Carbon Capture Index  
  by Pelin Yapicioglu, Mehmet İrfan Yesilnacar 
  Abstract: The main objective was the mitigation of CO2 emissions originated from potable water treatment using malt dust derived biochar (MD). This study recommended a new green carbon capture approach depended on biochar application to reduce the carbon dioxide (CO2) emissions resulted from water supply treatment in terms of water-carbon nexus. A new carbon capture index (GCI) towards green growth depended on biochar application was developed and validated. The determination of the effect of water quality on CO2 emission and the validation of the GCI were obtained by Monte Carlo Simulation. Averagely, 27.62% of mitigation on CO2 emissions from water supply treatment was reported using three types of biochar. The results showed that the highest carbon capture capacity related to the MD1 which was derived at the minimum pyrolysis temperature with averagely 0.987 of GCI.
  Keywords: potable water treatment; carbon capture; malt dust derived biochar; mitigation; water- carbon nexus.
  DOI: 10.1504/IJGW.2025.10070998
   
  
• Cereal Crops Yield and Climate Change: a Case Study  
  by Munisakhon Shamsieva, Muhammad Bilal 
  Abstract: This study investigated vital climate-related and non-climate-related factors on cereal crop yield in Uzbekistan using annual data from 1992 to 2022 with an error correction model. The findings revealed that temperature positively correlates with cereal crop yield in the short run and CO2 emissions negatively impact yield in the long run. Non-climate factors, such as freshwater withdrawal for agriculture, significantly impact cereal yield. Given the ground reality of Uzbekistan's agriculture, flood irrigation is a typical irrigation mode, so sustainable irrigation practices like drip irrigation/sprinklers should be implemented. Crop diversification to less CO2-emitting crops is essential to dispelling adverse climate shocks.
  Keywords: CO2 emissions; fertiliser; freshwater withdrawal; precipitation; Uzbekistan.
  DOI: 10.1504/IJGW.2025.10071083
   
  
• Navigating Canadian Renewable Energy Landscape through Bibliometric and Machine Learning Insights  
  by Samaneh Shirinnezhad, Davoud Ghahremanlou 
  Abstract: Canada targets a 40% reduction in greenhouse gas emissions by 2030, focusing on renewable energy. Analysing 1,796 publications (2015-2024) using AI-driven topic modelling, this study reveals Canada's strong focus on solar and wind research, with an emerging interest in energy storage for smart grids and Indigenous-led energy projects. Key gaps identified include underrepresentation of marine energy research, economic analysis of renewable integration, and insufficient policy evaluation. The study concludes that diversifying research towards technologies like geothermal, improving economic assessments, and creating policies considering socio-economic factors are crucial for Canada's energy transition, with future research requiring expanded databases and computational resources.
  Keywords: bibliometric analysis; Canada; renewable energy; decarbonization; sustainable development goals; SDG7; machine learning; topic modelling; Latent Dirichlet Allocation; LDA.
  DOI: 10.1504/IJGW.2025.10071285
   
  
• Evaluating 38 Years of Coral Coverage Trends on the Great Barrier Reef: Insights into Resilience and Temperature Correlation  
  by Alberto Boretti 
  Abstract: This study investigates the relationship between global warming and coral reef health, focusing on the Great Barrier Reef (GBR). Contrary to claims of widespread decline due to warming-induced bleaching, long-term data from the Australian Institute of Marine Science (AIMS) reveal that coral cover is at its highest since monitoring began in 1985. Using satellite air temperature data as a robust proxy for ocean warming, the analysis identifies no consistent correlation between rising temperatures and reduced coral cover. Coral bleaching is reframed as an adaptive response, with most corals demonstrating rapid recovery. These findings challenge prevailing narratives of coral fragility, emphasizing the GBR’s resilience and adaptive capacity in the face of climate change. The study advocates for balanced scientific discussions that incorporate both threats and recovery dynamics in coral ecosystems.
  Keywords: Great Barrier Reef; global warming; coral bleaching.
  DOI: 10.1504/IJGW.2025.10071364
   
  
• Cloud Computing based Green and Low-Carbon Building Energy Consumption Monitoring and Forecasting  
  by Yujin Liu, Kai Wang 
  Abstract: This paper proposes a green and low-carbon building energy consumption monitoring system based on cloud computing. By integrating the ARIMA model and K-means clustering, the system achieves real-time prediction and automatic identification of energy consumption, thereby enhancing intelligence and response speed. Cloud computing enhances system scalability and plays a key role in monitoring large-scale building groups. Furthermore, by integrating green computing with energy management methods, the study demonstrates that the optimised buildings exhibit significantly improved energy efficiency and a substantially increased proportion of renewable energy usage.
  Keywords: Building Energy Consumption Monitoring; ARIMA Models; K-means Clustering Method; Cloud Computing; Green Computing and Energy Management Methods.
  DOI: 10.1504/IJGW.2025.10071470
   
  
• Model Performance Evaluation With Siamese Neural Network In Hydrologic Modeling  
  by Huseyin Yildirim Dalkilic, Ahmet Baran, Baris Yilmaz, Eyyup Yildiz 
  Abstract: Global warming impacts water resources, altering the hydrological cycle, availability, and quality, posing challenges for sustainable use. This study applied hydrological modelling to evaluate future scenarios in the F?rat Basin using flow data. Gated Recurrent Unit (GRU) and Long Short-Term Memory (LSTM) models were assessed using conventional performance indicators. A Siamese Neural Network (SNN) with Graphical Similarity Rate (GSR) calculation was introduced to simplify evaluation and reduce parameter complexity. Results showed high model performance, with SNN providing statistically equivalent outcomes to traditional metrics, offering a novel approach to hydrological modelling challenges.
  Keywords: Deep Learning Methods; Global Similarity Rate; Hydrological modeling; Model performance evaluation; Siamese Neural Network; Sustainable water management.
  DOI: 10.1504/IJGW.2025.10071613
   
  
• Towards Low-Carbon Development: could Public Data Openness become an Accelerator for Reducing Carbon Emission Intensity in China?  
  by Yongcheng Yin, Yunfeng Xing, Xin Luo 
  Abstract: Low-carbon development is crucial for addressing climate change. Public data openness has considerable potential in this regard. Therefore, in this study, we aimed to analyse the effect of public data openness on carbon emission intensity. The results show that public data openness effectively reduces carbon emission intensity. In particular, promoting green technological innovation, enhancing digital financial services, and enhancing public environmental participation are effective channels for strengthening the impact of public data openness on carbon emission intensity. This study offers a scientific reference for governments worldwide to explore the role of public data openness policies in achieving carbon peaking.
  Keywords: public data openness; carbon emission intensity; staggered difference-in-differences model.
  DOI: 10.1504/IJGW.2025.10071730
   
  
• Ground Penetrating Radar Echo Signal Processing and Ecological Environment Detection Algorithm under the Background of Carbon Neutrality  
  by Sijia Chen, Qingquan Wang, Yuan Guo 
  Abstract: In response to noise interference in complex ecological environments, this paper constructs a new ground penetrating radar signal processing method to achieve carbon neutrality. Multi-scale wavelet transform and adaptive filtering denoising are used, combined with graph neural networks (GNN) feature extraction to model spatiotemporal dependencies, and dynamic time domain enhancement is used. The improved extreme gradient boosting (XGBoost) associates the detection signal with environmental changes and adjusts the detection parameters in real time. This method has a signal-to-noise ratio of 20.1 dB and noise suppression of 20.4 dB under 60 dB noise, and the GNN matching accuracy reaches 73%.
  Keywords: Carbon Neutrality; Ground Penetrating Radar; Echo Signal; Ecological Environment Detection; Wavelet Transform; Graph Neural Network.
  DOI: 10.1504/IJGW.2025.10071731
   
  
• Air-pollution Prediction in Smart City using Convolutional Long Short-Term Memory (ConvLSTM) Model  
  by Sankarsan Panda, M. Sri Geetha, Rajasekar A, Chandrakanth P 
  Abstract: People all over the world could die from the air we breathe. We can't do much to stop air pollution until we know more about it and guess what will happen. We use the cutting-edge Graph Convolutional Network (GCN) design and the cutting-edge deep prediction Convolutional Long Short-Term Memory (ConvLSTM) model to guess what the PM2 5 levels will be in different parts of the city every hour over time. We can't get data for our deep learning model from studying particles or the air. We use info from many places instead, like camera data and pictures The TROPOMI multispectral imager on Sentinel-5P works as it should. The name of it is "Fire Radiative Power ". This is true because the PM2 5 data we used to train our deep-learning model is typical of the data from the ground. We can get a better picture of the PM2 5 level.
  Keywords: Air-pollution; deep learning; FBProphet; LSTM-FC; ARIAX-MLP method; ConvLSTM model; XGB prediction model; Dataset.
  DOI: 10.1504/IJGW.2025.10071762
   
  
• Decision Support System for Urban Transportation Carbon Emission Based on Big Data Analysis  
  by Jingli Zhao 
  Abstract: With the rapid increase in the number of motor vehicles, the problem of carbon emissions from urban transportation has become increasingly prominent, seriously affecting air quality. This paper builds a carbon emission decision support system based on the IVE model, and effectively reduces emission errors by correcting carbon emission factors. The experimental results verify the feasibility and practical value of the model in urban transportation carbon emission assessment.
  Keywords: Big Data; Carbon Emission; Decision Support System; IVE Carbon Emission Model; CALINE3 Model.
  DOI: 10.1504/IJGW.2025.10071765
   
  
• Analysis of Integrated Energy System Coupling Small Modular Reactor with Renewable Energy Sources  
  by Gülcan Koca, Adnan Sozen 
  Abstract: As renewable energy systems (RESs) are highly variable and depends on geographical conditions, they are considered along with thermal energy systems as hybrid systems. In the study, small modular nuclear reactor (SMR), parabolic trough collector (PTC), and wind energy are integrated to produce more reliable electricity. PTC is used to heat the main flow; wind energy is used for the self-consumption of the proposed system. Total increment of 8,8% in the electricity generation, and between 17-51 MW wind energy are achieved. The efficiency of the proposed system is 33,48%. The proposed system is 2,7% more efficient than the SMR system.
  Keywords: Renewable energy; Solar energy; Wind energy; Nuclear energy; Small modular reactor; Hybrid system; Energy; Efficiency.
  DOI: 10.1504/IJGW.2025.10071833