International Journal of Global Warming (46 papers in press)

Regular Issues

• AIR POLLUTION PREDICTION MODEL FOR ESTIMATING AND FORECASTING PARTICULATE MATTER PM2.5 CONCENTRATIONS USING SOSE-RMLP APPROACH  
  by Kanpur Rani, Vallikannu N 
  Abstract: With the poor air quality and air pollution issues, several countries around the globe are facing a challenging aspect. The main intention of air pollution modelling is to reliably predict the noxious air contaminants with their levels of concentrations in the forecasting model. There were several traditional methods employed in the prediction of air quality, however due to the existence of huge uncertainties of Emission Inventory (EI) there is a need for improvements and refinements in the accurate prediction. Hence, san approach to estimate the urban forecasting prediction of air quality that employs a statistical method with optimization strategy for enhancing the prediction of air pollution. The proposed work attempts to introduce a new model for air pollution prediction and forecasting model analysis using processes such as preliminary processing using statistical method termed ordinal scaled encoding-based filtering process (SOSE). Initially, the dataset collected by TEPA (Taiwan Environmental Protection Agency from 2012 to 2017) is considered as the training data for building the classifier forecasting model and it is tested by the 2018 collected data. The process of feature extraction is carried with the use of Iterative Fisher based Feature extraction process with ranking strategy. The features extracted are then optimized with the use of Convergent Artificial Bee Colony optimization (CABC) strategy to get optimized choice of features extracted. At last, the classification mechanism is employed by means of Residual Multilayer perceptron (RMLP) classifier model which in turn predicts the error rate of prediction classifier at varied time period and for varied regions of Taiwan. Thus, the performance analysis was carried out in terms of MAE, RMSE, and MAPE and is compared with existing methods to prove the effectiveness of proposed scheme.
  Keywords: Air pollution; Air Quality Index; air quality prediction; Residual Multi-layer Perceptron; Ordinal Scaled Encoding-based filtering process (SOSE); Taiwan Environmental Protection Agency; Convergent Artificial Bee Colony optimization (CABC); MAE; RMSE; and MAPE.
  
  
• Analysis of the 160 years' time series of daily rainfall in Brisbane  
  by Alberto Boretti 
  Abstract: The composite time series of daily rainfall for Brisbane from 1860 to 2022 shows evidence of natural oscillations and the absence of any growing or reducing trend. The linear trend has a slope of only −2 μm/year, which is statistically insignificant. Similarly insignificant is the acceleration, calculated as double the 2nd order coefficient of the parabolic trend, at +0.02 μm/year². Higher than February 2022 single-day rainfall, three-day consecutive rainfall, or single-month rainfall, were measured in the past. The natural oscillations have, amongst others, clear inter-annual, decadal, and multi-decadal cycles, of lengths slightly less than 10, about 20, about 40, and 65-80 years (quasi-60 years). We conclude that the climate for south-eastern Queensland is characterised by a fairly stable rainfall pattern, dominated by wet and dry cycles.
  Keywords: Australia; droughts; floods; natural variability; rainfall.
  
  
• The Impact of Information and Communication Technology on Youth Ecological Behavior: A Global Cross-country Perspective on Environmental Citizenship and Ethics  
  by Ibrahim Niankara 
  Abstract: This paper evaluates the mediating role of information and communication technology (ICT) on the endogenous relationship between pro-environmental activity participation (PAP) and youth engagement in digital and physical climate activism globally. To this end, the study relies on a bootstrap sample of 168036 respondents from 40 countries, extracted from the 2018 Programme for International Students Assessment (PISA), along with endogeneity switching methods implemented through discrete choice modeling under random utility maximization. The findings reveal significant but mixed influences of ICT on youths marginal utility from ecological behavior uptake, based on the nature and place of ICT access and usage. In addition, factors including youths personal characteristics, along with their home, parental and family background are found to importantly drive their choices to participate in pro-environmental activities, and also to engage in signing environmental and social petitions online, as well as boycotting products or companies for environmental and social reasons.
  Keywords: Climate change; Climate activism; COP26; ICT; Sustainable development; Pro-environmental behavior.
  
  
• Historical extreme winters of Istanbul: The factors that contributed to severe winters during the 20th and 21st centuries  
  by Veli Yavuz, Mervegül Özda?, Anthony R. Lupo, Neil I. Fox, Ali Deniz 
  Abstract: In this study, the analysis of the extreme winters that occurred in Istanbul between the years 401-2022 was carried out. Until the 21st century, the extremely low temperatures and heavy snowfalls in the province sometimes lasted for days, sometimes for weeks, which adversely affected daily life and especially transportation. In the 21st century, snow depths measured between half a meter and one meter have been effective rather than low temperatures. By examining the extreme events that took place between the 18th and 21st centuries as reference, the statistics for the future occurrence of these events until 2050 and 2100 are presented. The most important factor in the occurrence of four events in only 22 years in the 21st century has been the positive trend in sea surface temperature (SST) anomalies.
  Keywords: Extreme winter; severe weather; snowfall; SST; extreme weather; Bosphorus; Golden Horn; Istanbul; Turkey; Black Sea.
  
  
• Climate change as a risk to human security. A systematic literature review focusing on vulnerable countries of Africa: Causes and adaptation strategies  
  by Artur Saraiva, Ana Monteiro 
  Abstract: The main purpose of this research is to systematically review the literature to understand how climate change influences stability and human security. The results identified from the bibliometric analysis allowed the identification of four dominant themes in the literature explaining the climate change and human security nexus: (1) Food security related to agricultural systems; (2) Water security associated with water scarcity and management; (3) Humanitarian crises, emphasizing conflict and climate migration; (4) Adaptation and mitigation strategies. The results underline the ineffectiveness of current responses to climate change, suggesting the urgency of action to reduce its impact on communities most prone to the effects, particularly in fragile states in sub-Saharan Africa. The study highlights some recommendations to policy and institutional leaders for a sustainable adaptation at the social, ecological, and economic dimensions. Adds a theoretical contribution by explaining the nexus of climate change, human security, and conflict, proposing a new dimension for the concept of human security - ecological security.
  Keywords: climate change; human security; food security; water security; ecological security; migrations; sustainable adaptation; Africa.
  
  
• Emergence, Distribution Dynamics and Drivers of Global High-emission countries Since the Industrial Revolution  
  by Hansunbai Li, Yu Ye, Hongxia Li, Qian Ye 
  Abstract: The fossil fuels CO2 emission since the Industrial Revolution is associated with critical development rights driven by economic and population growth. We defined high-emission countries as major emitters whose emission contributed 80% to global emission based on descending order of national emission, and analysed their emergence, distribution dynamics and drivers, which expect to unravel the processes of their emission surges and entwined carbon inequality in history. Our results show that (i) Thirty-one countries formed the group of high-emission countries and hardly exit from group. (ii) High-emission countries appeared in Europe first, then spread to North America, Asia and finally throughout all continents. (iii) Population growth and economic growth stimulated the rapid emission growth of earliest industrialized countries and several short phases after industrialization finished, respectively. Blend impacts transformed most developing countries to high-emission countries after World War II. We also discussed glooming climate mitigation ambitions because of pervasive carbon inequity.
  Keywords: FFCO2; high-emission countries; distribution dynamics; emission threshold; emission drivers.
  
  
• Comparison of hydrogen production with the help of the plastic digesting organisms and by pyrolysis  
  by Cennet Yildiz, Ali Bahadir Olcay, Mustafa Özilgen 
  Abstract: Plastic waste collected from the landfills may be washed, shredded, digested by plastic-eating microorganisms centrifuged and sent back to the landfill. If the generated water should be electrolyzed, in the case of processing 10% of the annually generated plastic waste, 24.2 Mt of plastic may be eliminated and 2.4 x103 kWh of energy may be recovered with the energy recovery ratio of 0.8. This ratio would be 2 in the case of pyrolysis, indicating that pyrolysis may be 2.5 folds more efficient than the microbial process. Moreover, pyrolysis occurs at high temperatures and is much faster than the microbial process. If we can find a safe way to innoculate the dump sides with the plastic digesting microorganisms, hydrogen may be generated without the production of carbon dioxide and water, the plastic waste may be reduced in the long run.
  Keywords: plastic waste; landfills; hydrogen-generating organisms; pyrolysis; waste reduction.
  
  
• Role of the COVID-19 imposed lockdown in climate change  
  by Arsalan Rasheed 
  Abstract: As the transmission of COVID-19 increases rapidly, the whole world adopted the lockdown activity with restriction of human mobility to prevent its spread. Everyone thinks of the COVID-19 negatively however; it has some positive aspects too. Before COVID-19, all over the world are being suffered by a high level of urban air pollution especially in the form of CO2, SO2, NO2 and particulate matter. During the COVID-19 pandemic, lockdown and limited human engagement with nature accompanied by social distance, have proven to be beneficial for nature. As a result, significant reduction in environmental pollution and improvement in the quality of air, cleaner rivers, less noise pollution, undisturbed and calm wildlife was observed. Knowledge gained from the studies suggests that a substantial relationship exists between the contingency measures and environmental health. It is concluded that the COVID-19-induced lockdown has a positive impact on the global warming, a major issue of the 21st century.
  Keywords: positive impacts; COVID-19; SARS-COV-2; coronavirus; lockdown; environment; global warming.
  
  
• EXPERIMENTAL INVESTIGATION OF SELECTIVE CATALYTIC REDUCTION SYSTEM ON CI ENGINE FOR NOX REDUCTION USING UREA AND ANIMAL URINE AS CATALYST  
  by Raju Tirpude, Pravin Katare, Sanjay Rajurkar, Gajanan Awari, Yasin Karagoz, Ahmet Selim Dalkilic, Somchai Wongwises 
  Abstract: The most effective and widely used post-combustion oxide of nitrogen reduction processes available in the automotive and power generation industries are selective catalyst reduction systems. A chemical reaction, where vaporized ammonia is gathered from the combination of urea and purified water, is used by selective catalyst reduction systems. Conversion of nitrogen oxide to nitrogen and water is the main target. Production of modified selective catalyst reduction device was conducted in the fist process. Secondly, the collection and preparation of Diesel exhaust solution using various pure urea and urine (cow and sheep urines) with varying concentrations was carried out to inject the tail pipe via the selective catalyst reduction system feed pump to assist in reducing oxide of nitrogen. From the results, it was concluded that there can be a significant improvement in oxide of nitrogen emissions using urea, cow and sheep urines in the modified selective catalyst reduction.
  Keywords: CI engine; SCR; NOx; Catalyst; Cow urine; Sheep urine; NOx.
  
  
• Evaluation of building design strategies of according to the effects of climate change by simulation-based optimization: A case study for housing in different climate regions  
  by Kubra SUMER HAYDARASLAN, Yalcin YASAR 
  Abstract: The life of the buildings has been extended with technological developments. It is predicted that 75-90% of the existing buildings will continue to be used in 2050. Buildings have an important place in total energy consumption and carbon emissions. With the measures taken in buildings, it is possible to reduce energy consumption by 25-40%. In this study, it has been studied to reduce the energy consumption of existing buildings by taking into account the effects of climate change. In the study, a numerical study was conducted on reducing PEC and CO2 emissions in existing buildings. The suggestions for the buildings were created based on the optimum building envelope, mechanical system, and building form group. These optimum suggestions were optimized with the NSGA II algorithm, taking into account the climate change scenarios from 2020 to 2080. As a result, the province with the lowest decrease in PEC and CO2 emissions was Kirikkale (PEC 36%, CO2 33%); the province with the highest number was Isparta (PEC 69%, CO2 75%). Regionally, the region with the lowest decrease in PEC and CO2 emissions was the Aegean Region (PEC 41%, CO2 42%); the region with the highest number was the Mediterranean Region (PEC 68%, CO2 72%).
  Keywords: Building energy consumption; CO2 emission; simulation-based optimization; NSGA II; climate change.
  
  
• Quantifying the cooling effect of urban heat stress interventions  
  by Aiman Mazhar Qureshi, Ahmed Rachid, Debbie Bartlett 
  Abstract: This review evaluates the existing studies of blue, green, and grey interventions based on field measurements and modeling aiming to quantify the cooling impact that reduces outdoor heat stress. Based on findings from literature, it is concluded that water bodies can reduce the mean air temperature (Tₐ) by 3.4°C and Universal Thermal Climate Index by 10.7°C, while natural vegetation can improve Tₐ by 2.3°C and Physiological Equivalent Temperature (PET) by 10.3°C during summer. Vertical greenery systems provide cooling effect of Tₐ up to 4°C, whereas architectural shades reduce it by approximately 3.8°C and PET up to 6.9°C under shade structure.
  Keywords: Interventions; urban heat stress; urban heat island; mitigation; cooling effect.
  
  
• Revisiting the Relationship Between Income Inequality and CO2 Emissions in US: New Evidence from CS-ARDL model  
  by Oguzhan Batmaz, Ferhat Citak, Muhammad Abdul Kamal 
  Abstract: Both theoretically and empirically, the association between income inequality and CO2 emissions is ambiguous. Hence, considering the short- and long-term dynamics of income inequality on carbon emissions, as well as the heterogeneity of the emission distribution, this paper employed Cross-Sectional Autoregressive Distributed Lag (CS-ARDL) approach over the period 1990-2018 and extended revisiting the effect of income inequality on carbon emissions across US states by considering Human Development Index. The study finds that higher income inequality tends to exacerbate US carbon emissions in the long term. Additionally, the study validates the EKC hypothesis by demonstrating that carbon emissions rise with lower income levels and diminish with higher income levels. Population growth leads to increased carbon emissions in the short and long term, while human development index has a negative impact on carbon emissions in the short run. The findings are vigorous to various causality tests. Policy recommendations are further discussed.
  Keywords: Income inequality; carbon emissions; the U.S. states; CS-ARDL.
  DOI: 10.1504/IJGW.2023.10053837
   
  
• NO and Performance Characteristics of a CI Engine Operated on Emulsified Fuel  
  by Fatih OKUMUS, Görkem KÖKKÜLÜNK, Güven GONCA, Ibrahim KAYA 
  Abstract: Emulsified fuels are among the alternative solutions nowadays when global warming and emissions are on the hot topic. In this context, thermal analysis and optimization of engines operating with emulsified fuels are important. In this research, the experimental and computational results of an engine running on emulsified fuel containing 10% water are shown. The investigated engine in experimental method is a naturally aspirated, single-cylinder diesel engine with a direct injection system. In the experimental setup, in-cylinder pressure, power output, specific fuel consumption and NO emission data have been obtained from the engine operating with emulsified fuel containing 10% water, and it have been used to fit some coefficients of the two-zone combustion model used for the computational method. After fitting the coefficients, the effect of design parameters, which are bore, stroke, inlet pressure and temperature, compression ratio, equivalence ratio, residual gas fraction, cylinder wall temperature, and start of injection time, on engine performance parameters have been investigated. According to the parametric results of the model, NO emissions have increased with increasing bore, stroke, cylinder wall temperature, compression ratio, air temperature and pressure. As opposed to it have decreased with increasing residual gases and changing equivalence ratio while it have decreased after saddle point with increasing injection time. As a result, the greatest reductions in NO emissions have been 91.28% and 88.21% in cases where it is 15% and 15 crack angle more than the original values for waste gas fraction and ignition time, respectively.
  Keywords: Engine design; Emulsified fuel; NO emissions; Combustion model.
  
  
• Urban cooling effect of rivers: Its role in climate change mitigation  
  by Maria Angela J. Tamoria, HyeMin Park 
  Abstract: Natural landscapes, such as rivers, can moderate intense heat in cities and provide a salubrious environment. This study aimed to evaluate how different urban forms affect the urban cooling effect of rivers. Landsat 8 satellite images were used to extract the water index, vegetation, bare land/non-vegetated land, built-up area, built-up density, and vegetation density from two study sites. The impact of urban forms on the cooling effect of rivers was analyzed through ordinary least squares method via exploratory regression analysis and scatter plot diagrams. Analysis revealed that natural landscapes have a positive relationship with surface temperature, whereas other urban forms have a negative trend. Although both sites displayed the same trend for every urban form, statistical analysis revealed different adjusted R
  Keywords: Urban Cooling Effect; Urban Form; Exploratory Regression.
  DOI: 10.1504/IJGW.2023.10052979
   
  
• Efficient Data Pruning using Optimal KNN for Weather Forecasting in Cloud Computing  
  by Benil T. , P.Krishna Kumar , R. Bharathi  
  Abstract: the meteorological area and fusses unambiguously to assist them in numerical weather prediction The numerical weather prediction is used as an indicator to predict atmospheric conditions. The researchers suggest numerous machine-learning techniques to evaluate the numerical equations in Numerical Weather Prediction (NWP). The methods so far provide good results, but they are not entirely accurate. Handling the historical data of the weather is difficult, but it is the best method to use. Therefore, we are proposing a new k-Nearest Neighbor classifier, which is implicated in managing the pruning of missing values in the dataset. The proposed new KNN is called optimal k-Nearest Neighbor, which is an improved method used to opt out the exact data needed for the prediction. The performance is evaluated using the Seattle rainfall datasets. Our results show that the best KNN algorithm can improve the accuracy of classification while taking the least amount of time.
  Keywords: K-Nearest Neighbor; Numerical weather prediction; Cloud Computing; Weather Forecasting.
  
  
• High resolution spatial-temporal downscaling model for historical daily precipitation using INLA  
  by Pedro Garrett, Filipe Santos, Rui Perdigão 
  Abstract: Precipitation and precipitation extremes have long been challenging to estimate. Significant progress has been made with successive generations of Earth System Models capable of simulating our climate with a global coverage. In this paper, a new statistical approach is presented based on the Integrated Nested Laplace Approximation (INLA) method to downscale historical daily precipitation rates. The spatial and Spatio-temporal structures was used in a Bayesian approach, to produce a daily 5km regular grid for continental Portugal. Results show the capability of the method to provide fast results aligned with the observations, but still underestimating precipitation events higher than 100 mm/day.
  Keywords: Statistical downscaling; climate change; precipitation; weather extremes; INLA; spatial-temporal modelling; Bayesian statistics; ERA5; reanalysis; historical climate.
  
  
• Hydrogen generation from anaerobic co-digestion and statistical evaluation using machine learning algorithms  
  by Chinmay Deheri, Saroj Kumar Acharya 
  Abstract: Hydrogen generation from anaerobic co-digestion of food waste and cow dung was statistically predicted using machine learning models. Laboratory scale experiments were performed using CaO2 and CaCO3 as additives. Maximum hydrogen generation of 115.28 and 109.47 mL g-1 TS was obtained using CaO2 and CaCO3. Further, the Pearson correlation matrix evaluated the correlation between the operational parameters such as inoculum to substrate (I/S) ratio, pH, and reactor temperature with the output parameter (hydrogen generation). I/S ratio showed the highest correlation of 0.94 with hydrogen generation compared to the other parameters. Moreover, four regression models were created using machine learning (ML) algorithms such as Linear Regression (LR), Decision Tree Regression (DTR), Random Forest Regression (RFR), and Support Vector Regression (SVR) to predict hydrogen production. Hydrogen generation was accurately predicted by the ML models with an r2 score greater than 0.9 and an RMSE value less than 1.
  Keywords: Machine learning; Anaerobic co-digestion; Hydrogen; Waste biomass.
  
  
• When will dockless bike sharing achieve a carbon balance? A case study of Nanjing, China  
  by Mingzhuang Hua, Jinyang Zhang, Xuewu Chen, Wendong Chen 
  Abstract: As an environment-friendly travel mode, dockless bike sharing (DBS) has recently become very popular in China. It is of great significance to quantitatively evaluate the environmental benefits of DBS. This paper estimated the carbon dioxide (CO2) emission reduction of DBS by combining the one-month journey data of Hellobike, the DBS market survey, and the modal shift data in Nanjing, China. The life cycle assessment was administered to determine the carbon emission during the life cycle of DBS. In the case study of Nanjing, 38.6% of DBS trips are originally from motorized modes. And the carbon emission factor of DBS is found to be 22.53 g CO2/km. Based on the above findings, it takes about 842 days to strike a balance between the carbon emission in the life cycle and the emission reduction benefit. This research will significantly help transportation planners and decision-makers committed to the sustainable development of the DBS system.
  Keywords: Dockless bike sharing; Emission reduction; Life cycle assessment; Modal shift.
  
  
• Post-Fire Behavior Estimation of Eco-Friendly Cement Based Composites  
  by Müzeyyen Balcikanli Bankir, Kevser ünsalan, Omer Faruk Cansiz 
  Abstract: In cement based composites, bond behavior is an important specialty throughout the service life of structure, especially it exposed to elevated temperature. Since there is a lot of CO2 emission during the production of cement, the necessity of using by-products that can be substituted in order to limit its consumption emerges. To improve the post-fire behavior of eco-friendly composites, by-products such as blast furnace slag, fly ash and silica fume are used. Since the adherence loss could not be measured in structures, it is necessary to estimate without any touch. So, estimation models are designed based on dual, triple and quaternary combinations of independent variables. As a result, the model created by mix, T and FS shows the best performance.
  Keywords: Post-fire; adherence; eco-friendly composite; by-product.
  
  
• Creation of Carbon Footprint Originating from Road Transportation in Turkey and Digital Mapping of It  
  by Ayben Polat Bulut, Seyma Ceylan Demirel 
  Abstract: In this study, the carbon footprint created by the greenhouse gases originating from road transportation in Turkey was calculated. In emission calculations, the methodology recommended by the Intergovernmental Panel on Climate Change and determined by the Tier 1 and Tier 2 approaches was used. As a result of the study, it was observed that the CO2 emission, which was 95689 GgCO2 in 2018 according to the Tier 1 method, decreased to 92424 GgCO2 in 2020, and the CO2 emission, which was 417359 GgCO2 in 2018 in the Tier 2 method, decreased to 404631 GgCO2 in 2020. Among the fuels used, it was determined that the diesel fuel type had the highest CO2 emission in both methods. Among the provinces, it was determined that Istanbul, Ankara and Izmir have the highest CO2 emissions, respectively. CO2 emissions were calculated for each province and presented visually on maps prepared using the ARCGIS method.
  Keywords: carbon footprint; greenhoouse gases; road transportation; carbon dioxide; global warming.
  
  
• Ascertaining the Impact of Balancing the Flood Dataset on the Performance of Classification based Flood Forecasting Models for the River Basins of Odisha  
  by Vikas Mittal, T.V. Vijay Kumar, Aayush Goel 
  Abstract: The climate shift being observed due to Global warming has led to an increase in the frequency of natural hazards. Floods, which are the most recurrent and devastating of natural hazards, continue to take their toll on human lives and livelihoods. These losses could be avoided by designing models that can forecast floods at early stages, i.e. before they turn into disasters. This paper focuses on the designing of classification based flood forecasting models for the flood affected districts in the river basins of Odisha. Existing classification based models forecast floods using an imbalanced dataset. This paper attempts to ascertain whether balancing the flood dataset would result in the improvement of the existing classification based flood forecasting models. Experimental results showed that balancing the flood dataset using SMOTE and its variants have resulted in an improvement in the performance of classification based flood forecasting models.
  Keywords: Natural Hazard; Floods; Disaster; Flood Forecasting; Machine Learning; Data Oversampling; SMOTE.
  
  
• Comprehensive Analysis of Offshore Wind Farm and Evaluation of Wind Energy Potential: a case study of University of Southampton  
  by Ilter Sahin Aktas 
  Abstract: The aim of this paper is to provide 40% of electricity consumption of Highfield Campus at the University of Southampton. The wind data is observed during the year of 2019 at three different heights, 10 m, 25m and 45 meter and obtained wind velocities are found as 6.34, 7.1, 7.48 m/s, respectively. According to the collected data, the best location for the wind turbine is proposed to be on the coast of the Isle of Wight. The system is designed with an installed capacity of 3.45 MW wind turbine. Based on the hub height and rotor diameter results run in MATLAB environment, two different solutions of turbine were given. Providing energy requirement of the campus with wind energy, there will be a decrease of approximately 20,000 tCO2 emissions per year. The diameter of the rotor and the hub height are calculated approximately 126 m and 158 m, respectively.
  Keywords: Wind energy; offshore wind power; greenhouse gas emission.
  DOI: 10.1504/IJGW.2023.10052767
   
  
• Carbon footprint of T-shirts made of Cotton, Polyester or viscose  
  by Junran Liu, Lirong Sun, Yiqi Guo, Wei Bao, Ying Zhang, Laili Wang 
  Abstract: TCarbon footprint (CFP) is an effective tool for calculating and assessing greenhouse gas (GHG) emissions and removals in a product life cycle using a single impact category of climate change. This study performed the CFP calculation and assessment for cotton T-shirt, polyester T-shirt and viscose T-shirt, complying with the system boundary from raw material extraction phase to end-of-life. Results demonstrated that yarn manufacturing contributes most of the CFP (36.1%-50.5%), followed by the product use phase (30.6%-48.3%) and fabric manufacture phase (19.6%-20.3%). Energy consumption is the main contributor to CFP in production processes. Additionally, the carbon sequestration effect of plant-derived fibres such as cotton and viscose played an important role to offset GHG emissions in the life cycle of T-shirts. The effect of carbon sequestration is more significant with the increase of product service life. Findings of this study can provide carbon emission reduction references for enterprises and consumers. In order to reduce the CFP in the entire life cycle of T-shirts, it was recommended that enterprises innovate production technology and increase the proportion of renewables in energy structures to replace the use of fossil energy, and consumers prolong the life cycle of products.
  Keywords: carbon footprint; carbon sequestration; life cycle; garment manufacture; plant-derived fibre.
  
  
• Potential Impact of Climate Change on Shifting the Calendar of Rainfed Crops Produced in Jordan  
  by Luna Al Hadidi, Amer Sweity 
  Abstract: Climate change alters the usual pattern of rainfall distribution and temperature in the East Mediterranean region. We investigated the impact of climate change on true season onset, and crop calendar for field crops grown in areas with Semi-Arid-Sub-Humid Mediterranean climate. Analysis showed a clear reduction of annual rainfall for the zone with rainfall more than200mm, and above 1oC rise in air temperature for all zones. Generally, the rainfall reduction occurred, in descending order, along the South-North direction. A new approach is proposed to identify the true season onset and the end of the effective rainy season. Shifting the true season onset consequently reduces the crop growing season and hence the yield. Reducing annual rainfall and the length of effective rainfall season, rising air temperature, and the sharp increase in the number of heatwaves will have profound negative impacts on both plant growth and yield.
  Keywords: Climate Change; Season Onset; Crop Calendar; Mediterranean Climate; global warming; seasonal variation.
  
  
• EUs green taxonomy analysis incorporated with energy-mix by machine learnings (ML) for climate mitigations  
  by SEWON LEE, CHANGHO HAN, CHANG HYUN BAEK, T.A.E. H.O. WOO 
  Abstract: It is analyzed for the European Union (EU)s green taxonomy incorporated with energy-mix by nonlinear algorithms where the uncertainties of the energy-mix are described by the artificial intelligence (AI). There are simulations of dynamical configuration of the EUs taxonomy incorporated with the energy-mix. The trends of Precision, Recall, Specificity, and Accuracy are converged after 30th year. It is done for the comparisons using a new factor of energy-mix consideration. Figure shows the comparison with and without Energy-Mix. The differences between two values are bigger around 20th and 30th years and it is not much near 50th year. This analysis by the EUs green taxonomy could give the solutions in finding the optimizing of environment and energy productions.
  Keywords: Climate; Taxonomy; Energy-Mix; Artificial Intelligence (AI); Machine Learning (ML).
  
  
• Impact of Building Thermal Characteristics on Urban Climates in Dalian, China  
  by Wenqian Zhou, Xiangli Li, Lin Duanmu, Yang Li 
  Abstract: The impact of building thermal parameters and building energy-saving technologies on the urban climate was presented in this study. Taking Dalian, this work used correlation analysis to find out a strong linear relationship between building thermal parameters and outdoor temperature. The intermediate parameter should be the building energy consumption, directly affecting the ambient climate. Simulation results showed that the air temperature rose by 0.88 K-1.85 K when air conditioners were on. In addition, the changes in the urban thermal and humid environment with the development of building energy-saving technologies were discussed. High albedo/green roofs were shown to be effective countermeasures to mitigate the urban heat island effect by about 1.0 K. Considering the geographical and meteorological characteristics of coastal areas, different green roof designs are recommended for urban areas. This work can provide some scientific guidance for urban energy-saving planning in coastal areas.
  Keywords: Weather Research and Forecasting model; Land use type; Building thermal performance; Building energy-saving technology; Urban microclimate.
  
  
• Characterization, function and emission free pyrolysis of agricultural residue  
  by Velmurugan Vellaipandian, Chellaiah Muthu, Chandrasekar Nainar Pandian, Yogita Shukla 
  Abstract: Huge quantity of agricultural residues is disposed by Open Field Burning (OFB) in India. It gives to an adverse condition in the atmosphere. To prevent it, a Pyrolyser, is used in this study. Dry leaves, paddy straw and corn straw are burnt separately in OFB and in pyrolyser. The biomass decomposition thermally at 4500C is standardized in the pyrolyser. The Carbon dioxide, Carbon monoxide, Nitrogen oxide, Sulphur di-oxide and Particulate matter are considerably reduced at pyorlyser burning. 30% of agricultural residue is converted into biochar which can be used to retain nutrients in the soil and carbon sequestration.
  Keywords: Paddy Straw; Dry Leaves; Corn Straw; Emission; Particulate Matter; Pyrolyser; Bio-char; Open Field Burning.
  
  
• Identification and prediction of land use changes based on Artificial Neural Network and CA-Markov in order to sustainable land-use planning  
  by Amanehalsadat Pouriyeh 
  Abstract: This study aims to model land-use changes of a city in the center of Iran during 1991-2021 using the Artificial Neural Network and the CA-Markov models. The land-use maps were prepared by the maximum Likelihood method. The land use map of 2001-2013 was used to model the land-use changes of 2021 and predict the land use map of 2030. The results of the prediction based on the two models showed that urban development will occur with the conversion of mountainous areas and barren lands and gardens and agricultural lands. The city's growth towards barren lands and mountainous areas makes the region prone to floods.
  Keywords: Artificial Neural Network; CA-Markov; Land Change Modeler (LCM); Maximum Likelihood algorithm; Land Use Change; Change Detection; Flood.
  
  
• LEVELIZED COST OF STORAGE ANALYSIS FOR AN ENERGY STORAGE SYSTEM BASED ON REVERSIBLE SOLID OXIDE CELL TECHNOLOGY  
  by Muiz Adekunle Agbaje, Ali Volkan Akkaya 
  Abstract: The Levelized cost approach is employed in this study to analyze the cost of a distributed scale standalone reversible solid oxide cell (ReSOC) based energy storage system. The Levelized cost of storage (LCOS) and the storage cost (SC) of the ReSOC system are computed and compared with other storage technologies. The LCOS and SC of the considered system are determined as 0.36 $/kWh and 0.09 $/kWh/cycle, respectively. Also, 156 tons/year emission reduction was achieved. The system analysis showed that the scale, capital and electricity cost, and roundtrip efficiency highly influence the system's economic performance.
  Keywords: Levelized cost of storage; energy storage; reversible solid oxide cell; economic analysis; emission reduction.
  
  
• An Assessment on the quality of groundwater in Chennais urbanized areas  
  by Annie Jose, Srinivas Yasala 
  Abstract: Large cities like Chennai often rely on piped water supply to meet residents' needs on a daily basis and so the existence of groundwater is actually a gift. The quality of groundwater is deteriorating as a result of population growth and poor waste management. Hence, it is essential to constantly check the groundwater's quality. In light of this, the goal of this study is to evaluate the quality of the drinking water in urbanised regions along the Adyar and Cooum rivers. From 26 Groundwater samples, physico-chemical, chemical and biological parameters were measured that are collected during the pre-monsoon season. A comparison was made between the results and the WHO and BIS standards. Then, the Drinking Water Quality Index (DWQI) was determined. The results are satisfactory but continuous monitoring and the improvement in the quality of water should be taken into consideration.
  Keywords: Groundwater quality; Pre-monsoon season; DWQI; Physico- chemical parameters; Chemical parameters; biological parameters; satisfactory.
  
  
• Sustainable and Cleaner Stone Wool Production with Double Density Layered Manufacturing  
  by Enis Altuntop, Dogan Erdemir 
  Abstract: This paper uses numerical analysis and experimental results to show how density-layered stone wool production can help us save carbon emissions while maintaining the same product quality. This new product can save up to 44% percent of raw materials, energy, and carbon emissions spent. Making it more common will drop stone wool prices and make energy consumption even smaller. Even though there are many applications for using stone wool, the main product scope is heat insulation for construction. Density layered stone wool will make a game-changer effect.
  Keywords: Stone wool; Rock wool; Heat insulation; Density-layered insulation material; Heat conduction; Integrated chain management; Life-cycle accounting; Environmental management; Life Cycle Assessment (LCA).
  
  
• Global temperatures, CO2 concentrations and oceans  
  by Allan Emrén 
  Abstract: During the last 170 years, global temperature and atmospheric CO2 concentration have increased. The greenhouse effect of CO2 is supposed to increase temperatures. Published data on global temperature, CO2 data, and data on sea ice in the Arctic have been investigated. It is seen that support for human activities to cause the observed increases is weak. Rather, it is found that the rate of change in CO2 concentration is controlled by global temperature rather than vice versa. The trend in the correlation between temperature and growth of CO2 concentration indicates that to stop the concentration from growing, the temperature has first to be decreased to 1 K below the mean value during 1981-2010. This makes it questionable if attempts by humans to modify the global temperature, or the concentration of CO2 in the atmosphere will give any noticeable result. Furthermore, a correlation is found between seasonal variations in CO2 concentrations and Arctic sea ice quantities. Several mysteries remain, e.g. what is the real cause of global warming, and why has there been a rapid increase in the atmospheric quantity of CO2 since 1750?
  Keywords: climate; global temperature; carbon dioxide; arctic ice; fossil fuel; carbon dioxide derivative; seasonal variation; sea water; carbonate; Henry's law; climate crisis; tipping point.
  
  
• Kinetics of methylene blue dye adsorption from water using modified fly ash  
  by Shuyue Zhang, Qi Zhu, Yuanfeng Hui 
  Abstract: The effective removal of dye from wastewater is important to curb its harmful effects on the environment and human health. In this study, a combined acidic/ultrasonic method was used to modify fly ash (FA) and utilize it as an adsorbent for methylene blue (MB) dye. The absorption rate of MB reached a maximum of 89.12% at a MB concentration of 30 mg/L, pH of 10, temperature of 20
  Keywords: modify fly ash; methylene blue dye; absorption; aid/ultrasonic method?kinetic models.
  
  
• Analysing the determinants of heatwave risk for small and medium enterprises: A case study  
  by Hrishikesh Mahadev Rayadurgam, Prakash Rao 
  Abstract: The development of natural disaster vulnerability is influenced by several factors and examining these underlying interactions aids in improving vulnerability assessments and reducing heatwave (HW) impact. The partial least squares structural equation modelling (PLS-SEM) was used to understand the correlation among various risk determinants of small and medium enterprises (SMEs) in Visakhapatnam, on the east coast of India. The results indicate that the physical infrastructure (0.50), employees and workers (0.31), and hazard likelihood and perception (0.38) vulnerability directly influence the SME risk. The analysis enables in identifying SME Risk determinants and areas of prioritisation for SME adaptation measures.
  Keywords: Small and Medium Enterprise; Climate Risk; Vulnerability; Heatwave; PLS-SEM.
  
  
• Review on technologies for improving energy efficiency of Waste Water Treatment Plants (WWTP): The case of the Hellenic Water Supply and Sewerage Company (EYATH SA)  
  by Effrosyni Giama, Aikaterini Christodoulou, Agis Papadopoulos 
  Abstract: Water is a natural resource as well as a key issue for all European economies, strongly related to climate change. This paper presents the different technologies which can ensure energy upgrade and reduction of CO2 emissions in Waste Water Treatment Plants (WWTP) focusing mainly in energy efficiency upgrade which is prerequisite for the reduction of CO2. Also, within the goals of this paper a rating methodology is described based on Water Treatment Energy Indicators (WTEI) and parameters such as effluent flow, nutrient removal, biochemical oxygen demand (BOD), chemical oxygen demand (COD), suspended solids, orthophosphate (PO43-), ammonia (NH4+) and nitrate (NO3-) are estimated and determined at various stages of a Wastewater Treatment Plant (WWTP). Finally, a quantitative evaluation of WTEI in Thessaloniki Water Supply and Treatment Company, Greece, is presented as a case study, benchmarking energy and water treatment indicators to evaluate the energy efficiency and the effect of water to the nexus complex.
  Keywords: waste water treatment plants; water-energy indicators; energy efficiency; circular economy.
  
  
• An Equilibrium Modelling and a Parametric Study of Gasification Process.  
  by A.PRUTHVI DEEP, SUJIT KARMAKAR 
  Abstract: In the present work, a fixed bed gasifier is modelled using a commercially available software called Cycle -Tempo. The gasifier performance is studied for varying steam to fuel ratio (SFR), equivalence ratio (ER), gasification operating temperature, moisture content of feedstock. The addition of steam as a gasifying agent along with air improves the H2/CO ratio, thus aiding in the hydrogen enrichment of syngas. Considering the combined effects of ER and SFR, the H2 constituent in syngas rises at lower ER and higher SFR values. The heating value of syngas tends to rise for lower ER and SFR values.
  Keywords: Gasification; Syngas; Steam to Fuel Ratio; Equivalence Ratio; Cold gas efficiency.
  
  
• Assessment of Biomethane Potential of Cotton Stalk using Response Surface Methodology  
  by Oznur Yildirim, Mahmut Altinbas, Bestami Ozkaya 
  Abstract: Nowadays energy policies, providing sustainability criteria, encourage energy production from renewable resources. Cotton stalks are one of the most common agricultural wastes in Turkey and the world. Evaluating the potential of using cotton stalks in biomethane production is important in terms of both waste management and sustainable energy production. In this study, the optimum F/I and organic loading ratio were investigated for biomethane production from cotton stalk waste with Response Surface Methodology (RSM). The R2 value, which shows the accuracy of the second-order polynomial equation obtained from the model, was found to be 0.9978 and 0.9876 for biomethane and VFA, respectively. As a result of thermal acid pretreatment, the maximum biomethane potential (114.19 ml/g VS) was obtained from cotton stalk wastes under F/I 0.25 and OL 35 g VS/L conditions. In addition, changes in cotton stalk after pretreatment were observed by FE-SEM and FTIR analysis. Biomethane production has been proven and modeled to be achievable using only the solid phase formed after pretreatment.
  Keywords: anaerobic digestion; biomethane; cotton stalk; response surface methodology.
  
  
• Experimental and statistical evaluation of biohythane fueled thermal barrier coated engine using machine learning algorithms  
  by Chinmay Deheri, Saroj Kumar Acharya 
  Abstract: Machine learning (ML) algorithms, Linear Regression (LR), Random Forest Regression (RFR), Decision Tree Regression (DTR), and Support Vector Regression (SVR), were utilized to predict the performance, combustion, and emission of thermal barrier coated (TBC) compression ignition engine fuelled with various blends biohythane and diesel. The mixture of supplied gaseous fuel was blended with 85-95% biomethane and 5-15% biohydrogen. Results indicated that up to 15% of biohydrogen enrichment with TBC improved the engine BTE by 6% compared to the diesel-only mode. Combustion parameters such as in-cylinder pressure and heat release rate were improved up to 16.5-20% with TBC. Further, HC, CO, and smoke emissions were reduced up to 16.2, 29.1, and 62.6 %, respectively, with TBC and biohythane. Evaluating the ML models, DTR produced the best prediction, with an R2 value range between 0.9-0.99 and an RMSE range between 0.1-0.9. It is closely followed by RFR, SVR, and LR, respectively.
  Keywords: Machine learning; Thermal barrier coating; Engine performance; Combustion; Emission.
  
  
• Influences of a Novel Pre-Chamber Design on the Performance and Emission characteristics of a Spark Ignition Engine Fuelled with Natural Gas  
  by Mehmet Cakir, Guven Gonca 
  Abstract: The effects of a novel pre-combustion chamber design on engine efficiency and emission characteristics were investigated at full and partial loads in the presented experimental and computational study. The original engine was converted to a pre-combustion chambered engine by modifying the cylinder head. Also, a combustion simulation model was developed for the spark ignition engine with pre-combustion chamber and fuelled with natural gas. The experimental performance data of the engine with pre-combustion chamber was compared to theoretical data obtained by using a combustion model. Maximum difference between the experimental results and model data was found lower than 10%. Moreover, it has been observed that the pre-chamber engine is more efficient at low loads and speeds.
  Keywords: Lean burn engine; Pre-chamber design; Two-zone combustion model.
  
  
• Evaluation of the Suitability of Dental Filling Materials for Green Production by WASPAS Method  
  by Fehim Findik, Alparslan Serhat Demir, Mine Büsra Gelen Mert 
  Abstract: Dental materials are used for restoration purposes in hundreds of millions of patients worldwide each year. In recent years, changes in the legislation of various countries and increasing social awareness have increased the expectation of products suitable for green production. In this study, the suitability of some dental filling materials for green production is discussed from various angles. Weighted Aggregated Sum Product Assessment (WASPAS) method was applied for a total of 14 sub-criteria in 5 main categories determined for green production. The results show that Ni-Fe-Cr alloy is the most suitable dental filling material for green production in many respects.
  Keywords: Green production; Dental materials; WASPAS; MCDM; Filling materials.
  
  
• Analysis of economic growth and carbon dioxide emissions in East Africa  
  by Twahil Hemed Shakiru, Qing Liu, Muhammad Asif Khan 
  Abstract: The present study examined the factors that determine CO2 emissions in East Africa. Employing a quantile regression technique, the study specifically analyzed data on CO2 emissions, GDP per capita, electricity consumption, labor force, and urban population in a period from 1989 to 2020. The results show that economic growth and electricity consumption increases CO2 emissions. It is recommended that policymakers in East Africa adopt and promote renewable energy sources that will help meet the rising demand for electricity by replacing traditional sources, such as coal, gas, and oil.
  Keywords: Keywords: "Panel unit root test; Panel quantile regression; Fisher panel cointegration; CO2 emissions; Electricity consumption; Economic growth".
  
  
• Projecting Potential Evapotranspiration under Climate Change Scenarios Using the LARS-WG Model in the Lake Ziway Watershed, Ethiopia  
  by Wondimu Hailesilassie, Sirak Tekleab, Tenalem Ayenew 
  Abstract: The purpose of this study is to project potential evapotranspiration (PET) in Ethiopia\'s Lake Ziway Watershed in response to climate change scenarios using the ensemble mean of five GCMs of CMIP5 for the years 20412060 under the RCP4.5 and RCP8.5. PET\'s future projection was based on the LARS-WG model\'s forecast of future temperatures. LARS-WG\'s calibration and validation results show that the model can generate future climatic data. The results revealed that the increment in PET under scenario of RCP8.5 is higher than RCP 4.5. Its change would be at its lowest in October, with the greatest increase occurring in April, May, and June. The PET increase is sensible largely in the spring. On an annual basis, PET will range from 7.73% to 15.70% as mean temperature rises from 1.67
  Keywords: Climate change; GCMs; Lake Ziway Watershed; LARS-WG; Potential evapotranspiration.
  
  
• Determination of global warming potential of dairy cattle farms  
  by Atilgan Atilgan, Roman Rolbiecki, Hasan Ertop, Joanna Kociecka, Ercüment Aksoy, Burak Saltuk 
  Abstract: Dairy cattle breeding is carried out intensively in the Eastern Anatolia Region (Turkey) and is a source of methane emissions. This study calculated global warming potentials arising from enteric fermentation and manure management of existing dairy cattle farms in this region between 2016 and 2020 using the Tier-1 method defined by the IPCC. As a result, it has been found that the global warming potential of this region is 20287.68x103 tons of CO2 in total. The total CH4 value in the research area was 966.08 x103 tons. Furthermore, it has been determined that 98.02% of these emissions are enteric CH4, and 1.98% are CH4 originating from fertilizer management. Therefore, it is seen that enteric CH4 constitutes a large part of the total CH4 emissions. For this reason, CH4 emissions can be controlled by choosing silage feeds in feed selection and adding minerals and vitamins to silage feeds.
  Keywords: dairy cattle; carbon dioxide; global warming; methane.
  
  
• Survey on Environmental Awareness, Attitudes and Behaviors of Undergraduate Students in Taiwan  
  by Angela Yi Jing Tsai, Alex Yong Kwang Tan 
  Abstract: This research aimed to understand the environmental awareness, attitudes and behaviors of undergraduates from Tzu Chi University, a university that actively promote environmental protection. Survey results showed that their environmental awareness were very high, with strong and favorable environmental attitudes, while their environmental behaviors ranged from slightly below neutral to relatively high and hence differed from other local undergraduates, general Taiwanese public and undergraduates from other regions. Class standings of sophomores and above performed better for several environmental behaviors. Undergraduates with higher moral norms regarding environmental protection exhibited higher environmental awareness, attitudes and behaviors. The influences of gender were non-significant.
  Keywords: Environmental awareness; Environmental attitudes; Environmental behaviors; Taiwanese undergraduates; Tzu Chi university; class standings; moral norms; gender.
  
  
• Reducing the Impact of Heat Waves on Human Population through Avenue Vegetation: A Mathematical Modelling Study  
  by Priya Verma, Maninder Singh Arora, J.B. Shukla 
  Abstract: In this paper, a mathematical model is proposed to study the effect of heat waves on the human population and to reduce the intensity of heat waves with the help of avenue vegetation. Model analysis suggests that the intensity of heat waves decreases and the density of the human population increases as the intrinsic growth rate and carrying capacity of avenue vegetation are increased. It is also found that the emission rate of carbon dioxide in the atmosphere and the growth rate coefficient of atmospheric temperature destabilise the system. The numerical simulation of the model confirms these analytical results.
  Keywords: carbon dioxide; heat wave; avenue vegetation; human population; equilibrium; stability.
  
  
• Block level annual and seasonal rainfall changes over Indian Sundarbans during 1901-2100  
  by Manish Naskar, Javed Akhter, Lalu Das 
  Abstract: Present study has analysed historical (1901-2005) and future (2006-2100) rainfall patterns over the Indian Sundarbans using observational data and multiple global climate models from CMIP5 experiment. Increasing trends of monsoon and annual rainfall along with decreasing trends in winter rainfall have been found over most of the blocks during historical period. CMIP5 RCP 4.5 and 8.5 based future projections also suggest an increase in monsoon (1-6.5mm/year) and annual rainfall (1.7-8.9 mm/year) by the end of the 21st century. However, RCP 8.5 scenarios indicate a decline in winter rainfall (0.02-0.3 mm/year) which may further amplify the salinity problem of this region.
  Keywords: Sundarbans; Rainfall; GCMs; CMIP5; RCP.