Forthcoming and Online First Articles

International Journal of Global Warming

International Journal of Global Warming (IJGW)

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International Journal of Global Warming (17 papers in press)

Regular Issues

  • Recent Developments on Open Thermochemical Energy Storage towards Decarbonized Building Space Heating and Cooling   Order a copy of this article
    by Asli Akyol Inada, Marzieh Rezaei, Devrim Aydin 
    Abstract: Thermal energy storage (TES) is one of the key technologies to achieve sustainability and mitigate the global warming impact. Among the all TES methods, thermochemical energy storage (TCES) presents promising features including relatively high energy density and long term heat storage potential. Accordingly, this study presents an overview with a focus on reaction and sorption-based open TCES systems. Within the study, material, reactor and process integration aspects of open TCES systems both for heating and cooling applications are evaluated. This study could provide important insights on future development of TCES materials and technologies.
    Keywords: thermochemical energy storage; heating; cooling; salt; solar energy; sorption; dissolution; reactor; process.
    DOI: 10.1504/IJGW.2024.10060563
  • Transforming Blackwater from Multi-Storey Residential Buildings: A Sustainable and Novel Closed-Loop Approach to Reusable Water and Biogas   Order a copy of this article
    by Venkata Sai Policherla, K. Srinivas Reddy 
    Abstract: One of the most challenging issues in underdeveloped nations is the treatment of domestic blackwater. This study adopts environmentally conscious solar ETC powered MED technology to treat wastewater and biogas digester for handling human waste. This study proposes an integrated solution for a 100-family neighbourhood, processing 3,900 litres of wastewater and 160 kg of faeces each day. In April, the MED unit achieves a 49.25% recovery rate during 5 hours/day operation, yielding 13.22 tonnes of distillate annually. It also generates 1,875.37 kg methane and 55.27 tonnes of organic fertiliser each year. System performance is analysed using a MATLAB R2020a-based mathematical model.
    Keywords: domestic waste; multi-effect distillation; MED; reusable water; biogas digester; fertiliser; decentralised unit.
    DOI: 10.1504/IJGW.2024.10060569
  • Analytical Hierarchy Process and Data Envelopment Analysis for Assessment of Renewable Energy Sources   Order a copy of this article
    by Müjgan Bilge Eriş, Kemal Tepret, Hande Çavuş Arslan, Çağrı Özgün Kibiroğlu 
    Abstract: Most of the energy resources consumed today come from fossil fuels which are non-renewable and cause harmful effects on the environment. Technological improvements and increasing energy deficit have made countries to prioritize the exploration of alternative options and place greater emphasis on renewable energy resources. In this research, the analytic hierarchy process (AHP) and data envelopment analysis (DEA) techniques are used to assess the relative efficiency and generate priority rankings for a set of renewable energy resources in T
    Keywords: analytic hierarchy process; AHP; data envelopment analysis; DEA; energy efficiency; renewable energy resources; multi-criteria decision making.
    DOI: 10.1504/IJGW.2024.10062237
  • Investigation of the effect of solar energy use in buildings on reducing carbon dioxide emissions   Order a copy of this article
    by Ebru Hancioğlu 
    Abstract: The aim of this study was to examine the reduction in CO2 emissions by using solar modules. In the article, the energy analysis of Narldere Nursing Home and Rehabilitation Centre (NNHRM) an exemplary public building in Izmir, was discussed. In this study, it was determined that if 1,500 kWp PV Panels were used, approximately 63.58% of the facilitys electricity needs would be met by PV panels. It was revealed that by using the use of PV panels, an improvement of 6.98% in primary energy, 12.27% in CO2 emissions and 7.51% in PER would be achieved. The repayment period is calculated as 7.1 years.
    Keywords: energy analysis; solar energy; energy consumption; CO2 emission.
    DOI: 10.1504/IJGW.2024.10062931
  • High-resolution Precipitation Prediction in Bangladesh via Ensemble Learning   Order a copy of this article
    by Yichen Wu, Jiaxin Yang, Lipon Chandra Das, Zhihua Zhang, M. James C. Crabbe 
    Abstract: As a developing agricultural country, Bangladesh is vulnerable to the effects of climate change, so accurate precipitation prediction is of great value to Bangladesh in achieving sustainable development. Traditional climate simulation models and prediction tools find it challenging to meet the growing needs on high spatial resolution. In this paper, we developed a XGBoost-based spatio-temporal precipitation prediction model and then generated high-resolution precipitation distribution maps in Bangladesh from 2025 to 2035, where the spatial resolution can reach 0.1
    Keywords: XGBoost model; precipitation prediction; Bangladesh.
    DOI: 10.1504/IJGW.2024.10063129
  • Estimation of the carbon footprint from road transportation: a case study   Order a copy of this article
    by Samed Aksoy, Ebru Koçak 
    Abstract: This research aims to estimate the carbon footprint of road transport in Aksaray, Turkey. The study used the Intergovernmental Panel on Climate Change tier 1 and tier 2 methodologies and found alarming increases in CO2 emissions from benzene and diesel, indicating a significant environmental impact. The results also highlight the need for ongoing monitoring and regulation of benzene and LPG emissions due to methodological differences. However, diesel emissions showed consistent assessment approaches between tier 1 and tier 2 methodologies. These findings provide valuable insights into the region's evolving carbon footprint, emphasising the need for precise methodologies for effective environmental management.
    Keywords: road transportation; carbon footprint; IPCC; tier 1; tier 2; ANOVA; global warming; emissions; air pollution.
    DOI: 10.1504/IJGW.2024.10063186
  • Post-combustion CO2 capture in a CI engine using adsorbent - a numerical and experimental study   Order a copy of this article
    by Sushil Rathore, Bamunusinghe Arachchige Umesh Maduwantha, Maniarasu R, S. Murugan 
    Abstract: This research explores the feasibility of using a biomass-based adsorbent to reduce carbon dioxide (CO2) emissions from a compression ignition (CI) engine. A numerical study of counter-pressure is performed in a capture unit using permeability factors of an adsorbent. The adsorbent is kept in two positions to examine its gas adsorption performance. Numerical results ensure acceptable back pressure and superior capture efficiency. The capture unit is designed under the permissible counter-pressure limit and coupled to the exhaust of a CI engine. The adsorbent exhibited simultaneous CO, CO2, HC, and NO reduction by 6.5%, 18%, 9.8%, and 12%, respectively.
    Keywords: adsorbent; adsorption; carbon dioxide; diesel engine; greenhouse gas emissions; post-combustion capture unit.
    DOI: 10.1504/IJGW.2024.10063457
  • Spatiotemporal Distribution, Trend Forecasting, and Key Factors Analysis of CO2 Concentration in Shanghai, China   Order a copy of this article
    by Xulong Wu, Jinye Zhang, Ziyue Hu, Ruibei Liu, Hui Lv 
    Abstract: We analysed Chinas spatial and temporal CO2 concentration patterns in this study. Advanced interpolation techniques including Kriging and PCHIP were employed to process GOSAT CO2 Level 3 products to improve spatial resolution and bridge temporal gaps. Furthermore, a SARIMA(1,0,2) (1,1,2)12 model was developed to forecast CO2 concentration of Shanghai for the next year. Utilising a MLR approach (R2 = 0.995, DW = 3.356), our findings underscored the dominant roles of GDP ( = 0.814) and population ( = 0.253) in driving CO2 concentration upward in Shanghai, while NDVI ( = 0.240) emerged as a crucial factor in reducing CO2 levels.
    Keywords: CO2; Shanghai; GOSAT; SARIMA; multiple linear regression; MLR.
    DOI: 10.1504/IJGW.2024.10063637
  • Assessment of Heavy Metal Contamination and Removal using Ceratophyllum demersum L.: A Case Study   Order a copy of this article
    by Aybike Gül Karao?lu, Mehmet Kobya, Aysegul Y.G. Kara, Esra Me?e, Melike Tepe 
    Abstract: Assessment of heavy metal contamination in aquatic ecosystems continues to remain challenging. In this regard, Ceratophyllum demersum L. (C. demersum L.) is a common species found in rivers and can be used as a bioindicator to see the accumulation of heavy metals in the plant body. In this study, we aimed to investigate the accumulation of toxic metals and their effects on photosynthetic pigment content in plants for different seasons. The highest metal accumulations were observed in October 2019. The mean boron concentrations were 399 mg/kg in October 2019, while they were measured as 163 mg/kg in July 2020, most probably due to the decreasing agricultural activities in the studied area. However, the highest metal concentrations (aluminium 3941 mg/kg and iron 5161 mg/kg) were measured in July 2010. Moreover, the pigment content values were decreased with the increasing metal concentration in plants. The highest pigment content of 4.7
    Keywords: Ceratophyllum demersum L.; heavy metals; abiotic stresses; phytoremediation.
    DOI: 10.1504/IJGW.2024.10063790
  • National flood risk index in climate change scenarios   Order a copy of this article
    by Pedro Lopes, Filipe Duarte Santos 
    Abstract: Extreme weather events are gaining a global notoriety due to their increasing impacts. The need to adapt must be in line with the best practices by including the frequency and intensity of extremes in climate change scenarios, enabling the discovery of new hotspots and critical areas. This work develops a Flood Risk Index for continental Portugal, by combining three flood components: physical susceptibility, exposure, and the frequency of severe precipitation events in climate change scenarios. To accomplish this task 3,653 simulations of daily precipitation projections were conducted using a spatial-temporal statistical downscaling approach.
    Keywords: flood risk; statistical downscaling; climate change; precipitation; weather extremes; INLA; spatial-temporal modelling; Bayesian statistics; ERA5; CanESM2.
    DOI: 10.1504/IJGW.2024.10064047
  • Exploring the Complex Relationship Between Income and Gender Inequality on GHG Emissions in EU Countries   Order a copy of this article
    by Mihaela Simionescu, Muhammad Zahid Rafique 
    Abstract: This research explores how income and gender inequality affect greenhouse gas emissions in EU-27 countries between 2002 and 2020. The study aims to contribute to global climate change mitigation efforts. The results show that as the Gini index increases, GHG emissions decrease. However, the impact of the gender pay gap is limited to higher quantiles and is positively related to emissions. Other factors such as GDP per capita, globalisation index, urban population, human capital index, foreign direct investment, and renewable energy consumption have varying effects on emissions. These findings can be useful in formulating economic and environmental policies.
    Keywords: Income inequality; Gender pay gap; Gini index; GHG emissions.
    DOI: 10.1504/IJGW.2024.10064055
  • Local Climate and Weather Changes in Pakistan -An Assessment through Historical Temperature Data   Order a copy of this article
    by Amna Bano, Minzah Shehzad, Saira Tariq, Zaira Tariq, Jamshaid Iqbal, Shehroz Siddiqui, Ammad Ahmad 
    Abstract: Present study evaluates the current and future climate and weather patterns in Pakistan through analysing the historic trends in temperature data spanning 20-year period from 2002 to 2021. Pakistan had an unstable and variable seasonal and monthly temperature pattern throughout the past two decades. Notably, whereas the winter season has showed an increasing temperature trend, the spring, summer, and autumn seasons have exhibited a declining tendency in temperature. Study predicts that average temperatures might increase by around 1% throughout the winter and summer seasons over the subsequent ten years (20222031). Monthly temperature fluctuations were in the range of 1.36%7.33% from 20022021 whereas, a future temperature variation from 0.65.29 % is expected during next two decades. Currently Pakistan needs to improve its resilience and adaptation capacity to temperature fluctuations as identified by this study.
    Keywords: climate change; weather; temperature; Pakistan; temperature variations.
    DOI: 10.1504/IJGW.2024.10064206
  • Impact of Climate Change on Water Requirements of Wheat and Potato in Eastern India   Order a copy of this article
    by Arpita Ghosal, Abhijit Saha, Manoj Kumar Nanda, Manish Naskar 
    Abstract: With the objective of investigating the impact of future climate (20202095) on the crop water demand of some principal rabi crops, viz, wheat, potato in eastern India, weather data were generated from MarkSim
    Keywords: global circulation models; GCMs; RCP 4.5; RCP 8.5; seasonal potential evapotranspiration; SPET; seasonal water requirement; SWR; India.
    DOI: 10.1504/IJGW.2024.10064215
  • Assessment of Carbon Trading within Blockchain and Subfield of Artificial Intelligence: a Review   Order a copy of this article
    by Sofya Morozova, Arif Karabuga, Zafer Utlu 
    Abstract: How can blockchain and AI revolutionise carbon trading? This article explores this question by reviewing the literature on blockchain's potential to create smart contracts for carbon trading. It also illustrates step-by-step guidance to write a smart contract that covers the essential aspects of the market. It is suggested that blockchain technology can address some shortcomings of the current system while usage of the data provided by ML makes contract actually smart.
    Keywords: carbon trading; blockchain; artificial intelligence; AI.
    DOI: 10.1504/IJGW.2024.10064244
  • Spatio-temporal pattern evolution and spatial convergence of greenhouse gas emission efficiency in China's cities: Analyses based on exploratory spatial data analysis and spatial econometric models   Order a copy of this article
    by Kaifeng Wang, Dalei Wu, Junyu Li 
    Abstract: This paper integrates greenhouse gas (GHG) emissions into the emission efficiency (GEE) index using data envelopment analysis (DEA) and dynamically explores GEE's spatial heterogeneity, correlation, and convergence, offering evidence and insights for optimising China's spatial pattern of GHG emission reduction. Findings indicate that GEE in the 285 sample cities grew by 18% on average during 20042018. East-west spatial heterogeneity and positive spatial autocorrelation of GEE progress are evident, and high-high clustering areas of the GEE index gradually shift eastward. GEE displays significant conditional -convergence, emphasising the need for tailored emission reduction strategies, considering economic and social differences among cities.
    Keywords: greenhouse gases; GHGs; efficiency; spatial heterogeneity; spatial dependence; convergence.
    DOI: 10.1504/IJGW.2024.10064263
  • Experimental and Machine Learning Research on a Multi-Functional Trombe Wall System   Order a copy of this article
    by Andaç Batur Çolak, Marzieh Rezaei, Devrim Aydin, Ahmet Selim Dalkilic 
    Abstract: Performance prediction tools can assist architects and engineers in designing and sizing TWs without the extensive effort, time, and costs associated with experimental evaluations. This study aims to develop an artificial neural network (ANN) model for predicting the performance of a multi-functional TW by using 57 experimental datasets and the Levenberg-Marquardt algorithm as the training algorithm. The developed model was found to be capable of TW performance prediction with error rates < 0.23%. The performance parameters for the ANN model, namely the mean squared error (MSE) and the coefficient of determination (R), were calculated to be 0.034 and 0.99917, respectively.
    Keywords: Trombe wall; heating; buildings; artificial neural network; ANN; Levenberg-Marquardt; global warming; sustainable architecture.
    DOI: 10.1504/IJGW.2024.10064276
  • Role of Income in Pollution and Growth across Belt and Road Initiative countries: New Insights from Dynamic Functional Regression Model   Order a copy of this article
    by Mohanned Hael, Haiqiang Ma, Fahmi Alselwi, Mushref Mohammed, Khin Sandi Myint, Hamas AL-kuhali 
    Abstract: This study employed Function-On-Scalar Regression (FOSR) to model the complex nexus and spatial-temporal dynamic impact of income distribution on carbon dioxide emissions (CO2) and Economic Growth (EG) for 80 Belt and Road Initiative (BRI) countries (19902021). Results discovered a robust positive nexus between income, CO2, and EG across the spatial-temporal BRI domain. Increased income levels are associated with heightened EG, subsequently driving higher CO2. Decreased income levels were linked to reduced EG and a corresponding decline in CO2 intensity. Accordingly, we suggested policy implications to guide BRI towards a balanced and sustainable development pattern.
    Keywords: function-on-scalar regression; penalized least square estimator; dynamic modelling; economic growth; carbon emissions; income level; Belt and Road Initiative (BRI).
    DOI: 10.1504/IJGW.2024.10064383