International Journal of Global Warming (13 papers in press)

Regular Issues

• Legal Comparative Study on Coordinated Development of Energy and Environmental Protection in Resource-Based Cities  
  by Weixian Chen, Yilin Zhang 
  Abstract: In order to ensure the stable development of resource-based cities and avoid excessive problems during the development process of resource-based cities. This article briefly analyses the main content of the coordinated development of energy and environmental protection in resource-based cities. Through legal comparison and slack-based measure (SBM) superstitious calculation, the backend operation and maintenance operations have been completed. Based on the big data front-end framework, implement mobile terminal operation mode monitoring. The efficiency of this method is about 32% higher than that of traditional methods.
  Keywords: Resource-based city; Energy; Environmental protection; Comparative law.
  DOI: 10.1504/IJGW.2026.10073257
   
  
• Image Processing Techniques for Monitoring Environmental Changes due to Global Warming  
  by Palanikumar S, Shrina Patel, Nagalakshmi T.J., N. Ashok Kumar 
  Abstract: This project used Google Earth Engine (GEE) to map and track how climate change changes public water sources. It shows a picture of the world's surface water in V1.4 size. We used the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Temperature-vegetation measure (TVX). After any of these weather events, the water might be different. Another is the amount of water and rain lost and given off. From 2000 to 2021, the study was done. The LUB has less open water because the Earth's surface is warmer. It was found that the rising and falling water levels were connected. What AT and ETa do to the LUB water is very important. They should all be -0.65 or -0.68. There wasn't a strong link between where the lake or river was and how much rain it got if the rho number was +0.25.
  Keywords: Support vector machine (SVM); Support Vector Regression (SVR); Land Surface Temperature (LST); Mann–Kendall (MK); NDVI-LST.
  DOI: 10.1504/IJGW.2026.10073448
   
  
• Impact of Green Development on the Achievement of China's Common Prosperity Goal and Its Spatial Characteristics  
  by Song Wang, Chaoquan Wang, Yuyao Cao, Xionghe Qin 
  Abstract: This study aims to explore the impact and spatial characteristics of green development on common prosperity, providing recommendations for government and relevant institutions. Based on uneven regional development and new economic geography theories, this study uses mediation and spatial econometric models to conclude that: 1) Green development promotes common prosperity, achieved by consumption, prosperity of capital and commodity markets. 2) Green development promotes convergence of certain regions common prosperity. 3) Green development promotes common prosperity in both local and neighbouring areas. Finally, this study proposes a series of green policies and measures to achieve the goal of common prosperity.
  Keywords: Common prosperity; Green development; Impact mechanism; Spatial effects; China.
  DOI: 10.1504/IJGW.2026.10073852
   
  
• Enhancing SWAT Model Performance for Climate Change Impact Studies in Watersheds with Missing Flow Data  
  by Abdulkadir Baycan, Gamze Tuncer Evcil, Osman Sönmez 
  Abstract: Hydrological models play a crucial role in assessing the impacts of climate change on water resources. This study evaluates the performance of single- and multi-site calibration approaches for the SWAT model in the Mudurnu River Basin, located in the Black Sea Region of Turkiye. The results indicate that both single- and multi-site calibration approaches yielded high model accuracy without significant differences in performance, providing 0.87, 0.87 R2, 0.87, 0.87 NSE, 3.6, 3.7 PBIAS, and 0.36, 0.36 RSR for validation, respectively. These findings suggest that single-site calibration at the basin outlet may be a practical alternative to multi-site calibration in small basins.
  Keywords: Climate change; SWAT model; hydrological calibration; missing flow data; water resource management.
  DOI: 10.1504/IJGW.2026.10074046
   
  
• Construction of Urban Low-Carbon Development Model Based on Digital Economy: Local Practice to Resist Global Warming  
  by Rijie Cong, Xin Zhang 
  Abstract: As global warming intensifies, cities face the challenge of fragmented pathways for low-carbon transformation. This paper establishes a multi-source carbon data system to clarify governance roles. It integrates transportation, building, and energy data to construct a digital twin city model, dynamically simulating emission reduction policies. It also uses graph neural networks to reveal coupling relationships and combines blockchain with federated learning to achieve multi-sector collaborative governance. Experiments demonstrate a collaborative governance index of 8.40, a 100% compliance rate for key indicators, and a 5.7% prediction error, validating the advantages of systematic low-carbon governance.
  Keywords: Digital Economy; Urban Low-Carbon Development; Carbon Data Elementization; Digital Twin Modeling; Federated Governance.
  DOI: 10.1504/IJGW.2026.10074161
   
  
• Is Digital Finance Green? Considering Digital Blind Spots and the Human Capital Threshold in Carbon Emission Reduction in China  
  by Tianyi Lei, PeiJun Wu, Lei Shi, Jiayuan Chen 
  Abstract: This study investigates the nexus between digital finance (DF) and carbon emission intensity (CEI), aiming to elucidate DF's role in fostering sustainable development. Findings indicate that DF contributes to a reduction in CEI, a conclusion robust to various tests for endogeneity and robustness. Mechanism testing uncovers the pathway through green innovation. Heterogeneity analysis reveals significant DF-induced reductions in CEI primarily in western China, with effects less pronounced in other regions. Moreover, DF's impact on CEI is notably stronger in non-resource-based cities compared to resource-dependent counterparts. It also reveals the 'digital blind spots' of DF and the influence of human capital.
  Keywords: Digital finance; Carbon dioxide emission intensity; Digital blind spot; Human capital threshold.
  DOI: 10.1504/IJGW.2026.10074191
   
  
• Carbon Emission Accounting of Municipal Solid Waste Incineration Disposal by means of Emission-Factor Approach  
  by Yanfeng Jiang, Fei Wang, Haibin Cui, Guojun Lv 
  Abstract: To deal with climate change, it is necessary to control the emissions of greenhouse gas (GHG), so allocation of carbon emission shares and carbon emission trading came into being. Combined with the actual operation of China's waste incineration power generation industry, this paper used the emission-factor approach to calculate all GHG emissions of power plants in detail. The results show that including the positive benefits from power generation, the net emissions from waste incineration disposal services were 84 667 tCO2e, which translated to 199.36 kgCO2e/t waste. Waste incineration reduced GHG emissions by 384.51 kgCO2e/t compared with traditional landfill treatment, indicating a good carbon emission reduction effect. This study clarifies all GHG sources within the accounting boundary, covers the details of each step of the calculation process, makes carbon emission data traceable, and promotes the participation of the waste incineration industry in the carbon trading market.
  Keywords: Municipal solid waste (MSW); Incineration disposal; Greenhouse gas (GHG); Carbon emission accounting; Emission-factor approach; Carbon trading.
  DOI: 10.1504/IJGW.2026.10074206
   
  
• Research on the Coupling Coordination of Economic-Social-Environment System under Sustainable Development Goals - from Digital Technology-Driven Perspectives  
  by Yuhan Zhang, Mengyue Li, Yuting Zhao, Xiujuan Gong, Xue Li, Pan Jiang, Liang Liu 
  Abstract: Digital technology is essential for sustainable development. This study analyses the spatiotemporal evolution of the coupling coordination degree (CCD) of China’s economic-social-environment (ESE) system and the impact of digital technology on CCD, focusing on regional heterogeneity and nonlinear relationships. Findings indicate: (1) the CCD of the ESE system is imbalanced, exhibiting positive spatial autocorrelation. (2) Digital technology promotes the CCD of the ESE system, with the strongest effect in central China. (3) Digital technology innovation exerts an inverted U-shaped relationship with CCD. This research proved that digital technology is effective in enhancing the CCD of the ESE system.
  Keywords: sustainable development; economic-social-environment system; coupling coordination; digital technology.
  DOI: 10.1504/IJGW.2026.10074551
   
  
• Identification The Impact of Climate Change on Extreme Weather Events in Indonesia Maritime Continent Using NEX-GDDP-CMIP6 Data  
  by Amalia Nurlatifah, Prawira Yudha Kombara, Aisya Nafiisyanti, Rahmawati Syahdiza, Haries Satyawardhana, Aulia Arip Rakhman, Finkan Rahma Yuditya, Latifa Hanum Zain, Rifda Amara Aulia, Khodja Ummi Medina, Aulia Rahma Effendi, Nurul Hidayati, Rehanda Umamil Hadi 
  Abstract: Global climate change challenges regions like the Indonesia Maritime Continent (IMC), where greenhouse gas emissions drive extreme weather. This study examines future changes in extreme rainfall using NEX-GDDP-CMIP6 data. Historical (19842014) and projected (20152060) data reveal that under high-emission scenarios (SSP58.5), consecutive dry days (CDD) may rise 15%, from 10 to 12 days annually by 2060. Very heavy precipitation days (R20mm) could increase by 25%, from 11 to 14 days. These trends pose dual risks: drought and heightened flooding. Adaptation strategies are critical to address threats to agriculture, infrastructure, and public health in vulnerable IMC areas.
  Keywords: Climate change; NEX-GDDP-CMIP6; Extreme rainfall; Consecutive Dry Days (CDD); Number of days with rainfall exceeding 20mm or more (R20mm).
  DOI: 10.1504/IJGW.2026.10074647
   
  
• Asymmetric Multifractality and Emission Efficiencies of CO2 Concentrations across some Countries  
  by Youshuai Feng, Yang Li 
  Abstract: This paper examines the asymmetric multifractality and emission efficiencies of CO2 concentrations in several countries. The results indicate that there are multifractal and asymmetric autocorrelations in CO2 concentration fluctuations across various countries. The autocorrelations of CO2 fluctuations in Russia exhibit distinct multifractal behaviours under different trends, while those in the remaining countries are all anti-persistent under different trends. Additionally, India has the highest degree of asymmetry in its CO2 concentration fluctuations. Furthermore, the study reveals that the UK has the lowest emission efficiency in terms of CO2 concentration, whereas Russia exhibits the highest.
  Keywords: CO2 concentration; Multifractality; Asymmetric; Efficiency.
  DOI: 10.1504/IJGW.2026.10074700
   
  
• Leverage Effect of Green Finance on Renewable Energy Investment Based on Machine Learning  
  by Yue Wang, Wei Li 
  Abstract: This study constructs a machine learning-econometrics hybrid framework to analyse the leverage effect of green finance on renewable energy investment (REI). Using random forests and gradient boosting decision trees, green finance is identified as the strongest driver, and a critical threshold (0.65) is determined. Panel threshold regression confirms the shift in leverage, with the marginal effect increasing from 0.28% to 0.68%. Climate risk significantly attenuates this effect, particularly in western China. Counterfactual simulations suggest that integrating green finance with carbon markets can boost REI by 22%, providing quantitative support for climate policy design.
  Keywords: Green Finance; Renewable Energy Investment; Machine Learning; Leverage Effect; Gradient Boosting Decision Tree.
  DOI: 10.1504/IJGW.2026.10074833
   
  
• Algorithm for Mining the Relationship between Carbon Emissions and Financial Ecosystem under the Background of Climate Change  
  by Yan Hou, Shuling Yang 
  Abstract: To address the shortcomings of traditional mining algorithms in handling the non-stationary and high-dimensional nature of carbon finance data, this paper employs a PSO-FP-Growth algorithm. This algorithm uses PSO to adaptively search for optimal support and confidence, combined with an FP-tree to efficiently mine frequent itemsets. Through incremental updates and local fine-tuning, the algorithm avoids rebuilding the entire tree to accommodate time-varying data. Experiments show that the algorithm achieves a mining efficiency of 92.3% with an average confidence level of 0.78. Even in an 80-dimensional scenario, it maintains an efficiency of 85.7%, demonstrating high practicality
  Keywords: Carbon Emissions; Financial Ecosystem; Correlation Mining; PSO-FP-Growth Algorithm; Mining Efficiency.
  DOI: 10.1504/IJGW.2026.10074883
   
  
• Effect of Stand Silvicultural Characteristics and Tree Growth on the Damages caused by Bark Beetles: a Case Study  
  by Elisavet Oikonomou, Gerasimos Thanasis, Marianthi Tsakaldimi, Petros Ganatsas 
  Abstract: The aim of this study was to analyse the structure of the beetle-attacked Pinus brutia forest stands in northern Greece, to determine the silvicultural characteristics and growth of the affected trees, to explore any correlation of infestation rates with above parameters, and then to suggest appropriate silvicultural treatments to prevent or mitigate such attacks. ?he results showed that the affected stands are pure, even-aged with relative high stem density, as a result of non-tending. Growth of the infected trees was satisfactory in the first 5-28 years, then it gradually decreases, and it is reduced after insect infestation. The reduction was found higher in the stands of high infestation rate (30-50% of the total number of trees), which are characterized by high tree density. Selection thinning and gradual conversion to mixed stands are suggested to increase stand resistance and promote tree vigor and forest health.
  Keywords: Reforestation; Turkish pine; stand structure; ennobling thinning; bark-eating insects.
  DOI: 10.1504/IJGW.2026.10075155