International Journal of Global Warming (21 papers in press)

Regular Issues

• Classification and Analyzing Air Quality with Machine Learning Algorithms: A Case Study on the 2023 Kahramanmara? Earthquake  
  by CEMAL AKTÜRK, TARIK TALAN, ADEM KORKMAZ 
  Abstract: Air pollution is a danger that negatively affects all ecosystems on a global scale. One of the methods used to reveal this danger with numerical data is the Air Quality Index (AQI). AQI allows the classification of air pollution by calculations made according to the concentration of pollutants in the air. The aim of the study is to estimate AQI with machine learning methods in order to estimate air pollution. For this purpose, air gas data of the Kahramanmara? region of Turkey were analyzed. The algorithms provided an estimation accuracy between 91% and 99%.
  Keywords: Air Quality; Air Quality Index; Machine Learning; Artificial Intelligence.
  DOI: 10.1504/IJGW.2025.10068987
   
  
• Investigating the Use of Fuzzy Systems in Managing Carbon Emissions and Sinks in Rural Areas  
  by Xu Fang 
  Abstract: To get to carbon peaks and neutrality, it is essential to have a better idea of how area carbon pollution and a low-carbon economy work in time and place. From 2015 to 2022, Sichuan Provinces carbon emissions were found by dividing them into four main categories: energy use, industry output, forest activity, and garbage release. They also observed at how it changed over time and found the primary sources of carbon pollution. The super-SBM-undesirable model checked how low-carbon efficient Sichuan Province and its 21 towns were. The most significant source of carbon pollution in the area was energy use, especially power plants and energy centres for factories.
  Keywords: Temporal and spatial distribution; carbon emissions; low-carbon efficiency; Sichuan Province; inventory accounting method; Super-SBM-Undesirable model.
  DOI: 10.1504/IJGW.2025.10069137
   
  
• Carbon Savings achieved by Mineralising CO2 into Precipitated Calcium Carbonate: Calculation on a Pilot Project in a Thermal Power Plant  
  by Jingqi Tian, Mengqian Zhang, Zhiguo Sun, Chunhong Ding, Jing Ma, Lihong Cai 
  Abstract: Mineralization is among the most successful CCUS technologies, carbonizing CO2 into CaCO3 permanently. A pilot project at a thermal plant produces carbon-negative precipitated calcium carbonate, requiring 1.05 tonnes of carbide slag, 0.06 tonnes of NH4Cl, 242.5 kWh of energy, 0.2 tonnes of water, 4.27 Nm3 of air, and 0.44 tonnes of CO2 for each tonne of product. Carbon footprint calculated by the emission factor technique is -0.2199 t CO2/t CaCO3 (slurry application) and -0.1219 t CO2/t CaCO3 (dry powder application). Primary carbon emission is from energy-consuming media, with green energy expected to reduce carbon emissions significantly.
  Keywords: CCUS; Mineralisation; CaCO3; Carbon Emission; Emission Reduction.
  DOI: 10.1504/IJGW.2025.10069261
   
  
• Multiscale Associations Between Global Surface Temperature Anomaly and El Nino-Southern Oscillation  
  by Ying Zhao, Meng Gao 
  Abstract: The El Nino-Southern Oscillation (ENSO) involves sea surface temperature and atmospheric variations in the eastern equatorial Pacific. This study integrates wavelet transform with Pearson correlation coefficient (PCC) to create a multiscale similarity measurement. The approach captures varying durations and frequencies, analysing transient, non-periodic, and non-stationary signal characteristics. Using global surface air temperature (SAT) data, we assess ENSOs impact on the global climate at various time scales, underscoring the importance of multiscale decomposition by comparing correlations among ENSO outer nodes over different scales.
  Keywords: wavelet analysis; time series; Pearson correlation.
  DOI: 10.1504/IJGW.2025.10069728
   
  
• Construction of Low-Carbon Economic Enterprise Management Mode Based on Grey Digital Model  
  by Xintong Du, Yang Yang, Haifeng Guo 
  Abstract: This study explores the issue of constructing a low-carbon economic enterprise management model based on grey digital models. By analysing enterprise strategies and conducting model performance comparison experiments, the results show that the MAPE, MSE, and MAE values of the model in this paper are 0.275, 0.001, and 0.003, respectively, far lower than those of other models, with high prediction accuracy. The fitting degree of the model in this paper is 0.9997, which is better than that of other models, indicating strong performance support. Research shows that grey digital models have significant advantages in building low-carbon management models.
  Keywords: Low Carbon Economy; Enterprise Management Model; Construction Mode; Grey Digital Model.
  DOI: 10.1504/IJGW.2025.10069834
   
  
• Perception of the Residents in the Arctic Region towards Climate Change: a Case Study  
  by Sujeong Im, Seungho Lee, Eungul Lee 
  Abstract: This study investigated the perceptions of residents toward climate change and its impact in the Arctic. A questionnaire survey, and the integrated climate observation and reanalysis data of Cambridge Bay were analysed. Arctic residents were aware of climate change and its impacts, and were seriously worried as it adversely affected the local community. Inuit were less concerned about climate change, while hunters were more sensitive to its impacts. Changes in animal and plant distribution and sea ice extent are key concerns, as they threaten traditional culture. The findings can assist in prioritizing plans to mitigate climate change in the Arctic.
  Keywords: Arctic region; climate change impacts; hunting activity; Inuit community; questionnaire survey.
  DOI: 10.1504/IJGW.2025.10069860
   
  
• Global Warming Modelling Simulation based on the Numerical Weather Prediction system  
  by Jayant Shaligram Brahmane, Kiran Shrimant Kakade, Ameya Patil, Jaya Chitranshi, Arjita Jain, Pankaj Ramesh Natu 
  Abstract: Accurately and efficiently simulating the climate and predicting the weather are universal goals in the realm of human advancement. Despite its status as the gold standard, numerical weather prediction (NWP) faces challenges due to inherent atmospheric uncertainty and high processing costs, particularly in the post-Moores Law era. This article summarises the most significant models and noteworthy advances in climate modelling and data-driven weather forecasting. These models reduce prediction times from hours to seconds, outperforming state-of-the-art NWP techniques in over 90% of the variables. Data-driven climate models can accurately reproduce climate patterns across periods ranging from decades to centuries, significantly reducing computational effort and increasing efficiency. However, despite their numerous advantages, data-driven techniques also have notable limitations. These include difficulty in interpreting forecasts, challenges in evaluating model uncertainty, and overly cautious predictions under extreme conditions. The proposed system achieves an accuracy of 96.7%.
  Keywords: data-driven model; deep learning; weather forecasting; climate modelling; Numerical Weather Prediction (NWP).
  DOI: 10.1504/IJGW.2025.10069922
   
  
• 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
   
  
• Macro Monitoring and Early Warning Evaluation of Environmental Protection of Industrial Economy under the Target of Carbon Neutrality  
  by Ali Chen, Peifeng Cai, Jing Wang 
  Abstract: The article proposes the digitised carbon neutrality blockchain technology (DCN-BT) system, which combines blockchain and AI-driven sensor data to monitor industrial emissions in real-time. DCN-BT makes data more transparent, improves early warning accuracy to 97.43%, reduces industrial carbon intensity by 50%, and achieves 5% annual energy saving. DCN-BT creates a scalable, data-driven solution to balance economic growth with environmental sustainability by fusing multi-sensor data with blockchain validation. This proposed system helps governments and industries achieve carbon neutrality utilising advanced digital technologies that ensure efficient carbon tracking, predictive analytics, and better decision-making.
  Keywords: Carbon neutrality; Carbon emission; blockchain technology; Macro-monitoring.
  DOI: 10.1504/IJGW.2025.10070033
   
  
• Self-Organising Fuzzy Sliding-Mode Controller for Wastewater Treatment  
  by Varuna Kumara, Ezhilarasan Ganesan 
  Abstract: Wastewater Treatment Process (WWTP) has attracted increasing interest in protecting natural waters. However, the operation of WWTP is difficult because of physical, chemical, and biological phenomena associated with treatment units. Therefore, this paper suggested a self-organising Fuzzy-based Sliding-Mode Control (FSMC) for enhancing WWTP operation performance. Simulations and testing demonstrate Self-Organising Fuzzy based SMC (SO-FSMC's) superior control performance. This comprehensive analysis enables the understanding of how FSMC, coupled with JAYA optimisation, influences the distribution of specific chemical species throughout the treatment process. Accordingly, the adopted method attains very less computational time of 2.718s, which is higher than other existing algorithms. Accordingly the result shows that the proposed SO-FSMC method outperforms other techniques in terms of exergy efficiency, yielding values of 3.00E+11 for bioreactor 1, 1.99913 for bioreactor 2, 17.999 for bioreactor 3, 1.97094 for bioreactor 4, and 1.9739 for bioreactor 5.
  Keywords: Wastewater treatment process; Fuzzy control; SMC controller; Optimization.
  DOI: 10.1504/IJGW.2025.10070148
   
  
• 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
   
  
• Investigation on the Quantitative Relationship between Financial Economic Progress and Environmental Management from the Perspective of Low Carbon Sustainability  
  by Xiaojun She 
  Abstract: This study analyses the coupling coordination relationship between carbon emissions, economic development, and environmental management in various provinces in China from 1997 to 2020. The results show that low carbon emissions have a positive impact on the coordination relationship among the three. Guangdong Province ranks first in the coupling coordination degree of carbon emissions, economic development, and environmental management by virtue of its open policy, carbon rights trading, and industrial transformation. Its economic development has always been at the forefront of the country, providing a reference for studying the quantitative relationship between economic development and environmental management.
  Keywords: Financial and Economic Progress; Environmental Management; Low Carbon Sustainable; Coupling Coordination Model; Weighted Topsis Comprehensive Evaluation Method.
  DOI: 10.1504/IJGW.2025.10070294
   
  
• 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
   
  
• An IoT-driven Enterprise Energy Efficiency Optimisation Model: a Path analysis for Promoting a Green Economy  
  by Liang Zhao, Enhua Li, Xiuyun Zheng 
  Abstract: Companies are reconsidering energy use for conservation. Path analysis provides an IoT-driven green economy enterprise energy efficiency optimisation model (IoT-E3OM) real-time energy usage data from industrial, logistics, and facilities management IoT sensors and actuators. Multiple linear regression assesses process optimisation, equipment efficiency, behavioural interventions, and renewable energy integration, while path analysis examines causal relationships impacting energy efficiency. Energy management with environmental aims may enhance business efficiency and profitability. IoT-E3OM betters prior models in energy prediction (97.8%), efficiency (96.5%), accuracy (95.4%), energy consumption (10.2%) and mean absolute error (7.3%). This approach improves Sustainability through energy management and green economics.
  Keywords: Enterprise Energy efficiency; Optimization; Internet of Things; Path Analysis; Green Economy; Multiple Linear Regression Analysis; Research Hypothesis.
  DOI: 10.1504/IJGW.2025.10070713
   
  
• Revisiting the Environmental Phillips Curve (EPC) Hypothesis: a Nonlinear Panel Data Approach  
  by Chengllin Huang, Siok Kun Sek, Wai Mun Har 
  Abstract: This study re-examines the EPC hypothesis between unemployment and carbon emissions across 19912021, using a novel of pooled mean group nonlinear autoregressive distributed lag model and panel quantile regression. Diverging from prior linear assumptions, we extend the examination on the nonlinear nexus by incorporating the asymmetries of unemployment in the estimation. Results are compared across emission and unemployment extremes. Results reveal no short-term EPC validity but uncover a complex long-term nexus: rising unemployment reduces emissions in high-unemployment economies, yet increases them in low-emission countries. Conversely, falling unemployment drives emission growth in carbon-intensive nations, reflecting rebound effects from industrial recovery.
  Keywords: Carbon dioxide emission; Panel data; PMG-NARDL model; Panel quantile regression; EPC hypothesis.
  DOI: 10.1504/IJGW.2025.10070714
   
  
• 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
   
  
• Problems and Strategies of Carbon Emission Reduction in the Nitrogen Fertilizer Industry: a Case Study of China  
  by Hang Li, Mengshuo Liu, Suyu Li, Bingbing Yan, Yajuan Jin, Li Wang 
  Abstract: As the world's population continues to grow, carbon emissions from the nitrogen fertilizer industry have become a pressing issue. This study focuses on two key aspects of nitrogen fertiliser production and application. It not only reviews the current situation of greenhouse gas emissions from China's nitrogen fertiliser industry, and identifies the problems in its low-carbon development, but also explores solutions to achieve carbon reduction from both technological and policy perspectives. Using China as an example, the study aims to provide experience for carbon reduction in the nitrogen fertilizer industry in other countries around the world.
  Keywords: Greenhouse gas emissions; Nitrogen fertilizer industry; Emission reduction strategies; Climatic change.
  DOI: 10.1504/IJGW.2025.10070910