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International Journal of Global Warming

 

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International Journal of Global Warming (19 papers in press)

 

Regular Issues

 

  • Characterizing households vulnerability to climate change in Pyapon district in the delta region of Myanmar   Order a copy of this article
    by Tun Oo Aung, Guido Van Huylenbroeck, Stijn Speelman 
    Abstract: In the delta areas of Myanmar, the rising sea level causes saltwater intrusion and flooding. The resulting reduction in cultivated area and reduced crop productivity threatens livelihoods that are dependent on agriculture. A households vulnerability to these phenomena is determined by demographic factors and the social and economic characteristics of farm households. In order to understand vulnerability, it is relevant to study the effects of these factors. This paper has two main objectives: firstly to evaluate the factors determining farm households vulnerability to climate change-induced natural hazards and saltwater intrusion and, secondly, to study the correlation statistics between these factors. A total of 178 respondents from 20 villages in Pyapon district in Myanmar were interviewed. The study found that smallholder households (owning less than 2.428 ha) were most vulnerable to natural hazards, with an average household vulnerability score of 0.608, compared to households with larger landholdings which have a score of 0.589. Moreover, the Spearman correlation test explains that 14 out of the 23 selected variables were significantly correlated with the household vulnerability index. It was found that adequate provision of seeds, accessible markets, private and public extension services, enhancement of climate change adaptation measurements by farm households, and other infrastructure are necessary to reduce the vulnerability of farm households in the Pyapon district of Myanmar.
    Keywords: Saltwater intrusion; Climate Change Adaptation; Principal Component Analysis (PCA); Vulnerability Index.

  • Assessment of CMIP5 climate models over South Asia and climate change projections over Pakistan under representative concentration pathways   Order a copy of this article
    by Nadia Rehman, Muhammad Adnan, Shaukat Ali 
    Abstract: Future climate change projections from global climate models (GCMs) are the primary drivers of regional downscaling and impacts research. Climate projections are also in increased demand from disaster management agencies, policymakers, and other stakeholders. A set of 36 global climate models from the coupled model inter-comparison project phase 5 (CMIP5) is assessed for their performance over South Asia region for making future climate projection with a focus on Pakistan and its sub-regions. A suite of statistics was calculated to assess the credibility of GCMs with the observed statistics. The results show that GCMs have the ability to approximately capture the spatial patterns of temperature; however, the accuracy of precipitation simulation is relatively low. The future projection generated by the GCMs shows that temperature in Pakistan will increase in the 21st century by around 6.7°C under the RCP 8.5 scenarios and with increasing latitude, this warming is getting accelerated.
    Keywords: CMIP5; global climate models; GCMs; representative concentration pathways; RCPs; temperature; precipitation; climate change projections; Pakistan; global warming.

  • Predicting the Different Engine Parameters of a Rubber Seed Oil-Ethanol Dual Fuel engine using Artificial Neural Networks   Order a copy of this article
    by Femilda Josephin, V. Edwin Geo, Ankit Sonthalia, BHARATIRAJA CHOKALINGHAM, Fethi ALOUI 
    Abstract: The present study investigates the potential of artificial neural network for predicting the performance and emission characteristics of a compression ignition engine. A number of experiments are performed using diesel, rubber seed oil (RSO) and rubber seed oil methyl ester (RSOME) as the primary fuel, injected into the cylinder, and ethanol as the secondary fuel injected into the intake port in a compression ignition dual fuel engine. The experimental data obtained is used for training and testing the neural network. From the total data, 70% of the data is randomly selected for training the network, 15% data for cross-validation and the remaining 15% data for testing the networks performance. The predictions are performed using feed forward back propagation training algorithm. Engine load and ethanol energy share data is used as input to the network, and it predicts brake thermal efficiency (BTE), brake specific energy consumption (BSEC), NOx, HC, CO, and smoke. The prediction performance of the network is measured by comparing it with experimental data. The coefficient of determination (R2), Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE) are used for measuring the performance of the network. After training and testing R2values are in the range of 0.99309 0.99996 and MAPE values are in the range of 0.00364.3227 for both training and testing data along with small mean square errors. The measurement of statistical error shows that ANN can predict BTE, BSEC, NOx, HC, CO and smoke for a dual fuel engine with high accuracy.
    Keywords: Artificial neural network; Ethanol; Dual fuel engine; Rubber seed oil; Rubber seed oil methyl ester.

  • Statistically Downscaled Projections of CORDEX South Asia using Quantile Mapping approach over Pakistan Region   Order a copy of this article
    by Burhan Ahmad, Ghulam Rasul 
    Abstract: Apprehending regional scale climate information from global scale climate models brings uncertainties primarily due to insufficient incorporation of climate information at local scale. We implemented the Quantile Mapping (QM) approach based on in‒situ data that removed the systematic biases in the regional scale simulations of the CORDEX South Asia data for maximum temperature, minimum temperature, and precipitation that covers the Pakistani domain. Post processed results were modelled into Probability Density Functions (PDFs) to identify climate change shifts in various statistical moments. The PDF based analysis for temperature reported negatively skewed patterns in distributions for projections as compared to baseline which forced shifting of percentiles and means towards extreme magnitude regimes. The PDF based analysis for precipitation displayed lower kurtotic values with fatter and lengthier tails in the projections as compared to baseline which suggested higher frequencies of precipitation extremes to occur in the times to come.
    Keywords: Statistical Downscaling; Quantile Mapping; CORDEX South Asia; Climate Projections; Probability Density Functions; Pakistan Region.

  • Local government climate change mitigation and adaptation ranking assessment   Order a copy of this article
    by Anton Kole, Joanna Ellison 
    Abstract: Climate change awareness in local areas is critical, and this study assessed levels of mitigation and adaptation of local government areas (LGAs), across the rural/ urban State of Tasmania. Fourteen indicators were developed in energy, transport, awareness, and physical carbon sink sectors, and allocated quantitative parameters for ranking. Results were mapped using geographical information systems software. Higher energy results occurred on the two large northern islands both with solar and wind generation facilities, and around some cities with energy efficient street lighting systems. Highest transport scores occurred in the remoter west, and around most cities, but mostly not in agricultural areas. Higher awareness levels and overall scores were found around city areas. Higher physical scores resulted from community tree plantings and carbon sequestering vegetation. This study shows how geographic trend mapping can improve understanding of spatial differences in climate change mitigation and adaptation, to improve prioritised allocation of assistance policy.
    Keywords: Mitigation; climate change; local government area; Tasmania; Australia; Ranking.

  • Methodology for a Techno-Economic Evaluation of Electricity Production and GHG Emissions Estimation in Landfill Sites   Order a copy of this article
    by Murat Gokcek 
    Abstract: Landfills are active digester fields that contain all types of classified waste that decomposes under anaerobic conditions and produces greenhouses gases causing global warming such as methane. In the present study, it was aimed to assess the potential of electricity generation and GHG emissions for a municipal solid waste landfill that is situated in Sivas, Turkey. The USEPA-LandGEM model was employed to determine the landfill gas generation capacity. The internal combustion engines with the rated power sizes in the range of 330 - 1946 kW were selected in order to generate electric energy by using the biogas formed in the landfill. The levelized cost of electricity (LCOE) method was employed for the purpose of calculating the generation cost of unit electricity. According to the results of the model, the maximum total gas production rate was estimated to be 14.395
    Keywords: Landfill gas to energy; Levelized cost of electricity; Municipal solid waste; Electricity generation potential.

  • Enhancement of Landfill Gas Production and Waste Stabilization by Using Geotextile Filter in a Bioreactor Landfill   Order a copy of this article
    by Cevat YAMAN, Yusuf Küçükağa, Burcu Pala, Gülşah Delice, Nafiz Eyüp Korkut, Abdurrahman Akyol, Serdar Kara 
    Abstract: Optimizing the methane production period is potentially a better way to manage and control the greenhouse gas impact of landfill gas (LFG). The aim of this study is to enhance biodegradation and methane production of municipal solid waste (MSW). In this study, two laboratory scale anaerobic bioreactors are used to evaluate the potential to increase the rate of LFG production and waste stabilization by using a polymeric geotextile filter in the bioreactor. The simulated bioreactor is equipped with a geotextile filter (LBR-GT) and showed a greater performance than the control reactor (LBR-C) in terms of the LFG production rate and the waste stabilization period. Although a negligible amount of LFG is still being produced, a total of 1194 L and 1128 L of LFG were produced from the LBR-GT and the LBR-C respectively. This study showed that the rate of LFG production is enhanced by the geotextile since the LBR-GT produced 85% of its total LFG in only 1 month whereas the LBR-C produced 85% of its total LFG in more than 3 months. To monitor the waste stabilization performance, the total settlements (waste reduction) in the reactors are also determined. The results of this study suggest there is a benefit of using geotextiles to enhance the operation of a landfill as a bioreactor and to control the greenhouse gas impact of LFG.
    Keywords: Solid waste; landfill gas; geotextile; landfill bioreactor; greenhouse gas.
    DOI: 10.1504/IJGW.2019.10016044
     
  • How to model a complex national energy system? Developing an integrated energy systems framework for long-term energy and emissions analysis   Order a copy of this article
    by Matthew Davis, Mohammad Ahiduzzaman, Amit Kumar 
    Abstract: In order to manage an energy system responsibly and maintain its benefits indefinitely, science-based decision-making should be valued during energy policy making and energy management. This research presents a framework for developing a scientific tool with the Long-range Energy Alternatives Planning (LEAP) system for evaluating energy consumption and greenhouse gas (GHG) emission mitigation pathways for a national energy system. The framework developed is applied to create a bottom-up (technology-explicit), data-intensive (over 2 million data points), multi-regional (13 integrated regions) energy model of Canada, one of the worlds most energy and emission intensive nations. Model accuracy was validated with historical data showing emissions varied 0-1.2% proving the framework can provide accurate assessments. The model was used to generate baseline Canadian energy-emissions outlooks to 2050 that do not currently exist in literature. The developed framework provides robust capabilities that are helpful for energy efficiency analysis, energy planning, and GHG mitigation assessment.
    Keywords: energy model; GHG emissions; Canada; energy outlook; emission outlook; energy system; bottom-up; integrated; accounting-based; energy analysis; emission analysis; energy policy; energy management; LEAP.

  • Future realities of climate change impacts: An integrated assessment study of Canada   Order a copy of this article
    by Mohammad Khaled Akhtar, Slobodan P. Simonovic, Jacob Wibe, Jim MacGee 
    Abstract: This paper presents an integrated assessment model for use with climate policy decision making in Canada. The feedback based integrated assessment model ANEMI_CDN represents Canada within the global society-biosphere-climate-economy-energy system. The model uses a system dynamics simulation approach to investigate the impacts of climate change in Canada and policy options for adapting to changing global conditions. The disaggregation techniques allow ANEMI_CDN to show results with various temporal resolutions. Two Canadian policy scenarios are presented as illustrative examples to map policy impacts on key model variables, including population, water-stress, food production, energy consumption, and emissions under changing climate over this century. The main finding is a significant impact of a carbon tax on energy consumption. Two policy scenario simulations provide additional insights to policy makers regarding the choice of adaptation/mitigation options along with their implementation time.
    Keywords: system dynamics simulation; climate change; integrated assessment modeling; society-biosphere-climate-economy-energy system; water resources management; disaggregation.

  • Patterns and Influencing Factors of Spatio-Temporal Variability of Soil Organic Carbon in Karst Catchment   Order a copy of this article
    by Zhenming Zhang, Yunchao Zhou, Shijie Wang, Xianfei Huang 
    Abstract: The patterns of spatio-temporal variability of the soil organic carbon (SOC) stored in karst catchment were investigated, to provide a scientific basis for estimating SOC storage in karst regions and selecting technical measures for soil carbon sequestration. In this paper, field sampling, laboratory measurement, geostatistics, and geographic information system (GIS) were combined, to investigate the patterns and influencing factors of SOC's spatio-temporal variability in Houzhai catchment from 1980 to 2015. The results showed that according to the soil samples of the entire catchment, the SOC content averaged 21.98 g/kg in 1980 and 25.07 g/kg in 2015, with an increase of 3.09 g.kg-1 (14.58%). Over the three and a half decades, SOC in this region showed weakened spatial structure, reduced correlation, and broken spatial distribution. Moreover, SOC in both periods presented a pattern of high values in the east and low values in the west, high in the periphery and low in the center, and high in the south and low in the north. However, some local values were highly variable in embedded or block distribution. The key factors that could affect spatio-temporal variability of SOC in Houzhai catchment included the soil types, land utilization, and major environmental factors.
    Keywords: Soil organic carbon; temporal and spatial distribution; influencing factors; small watershed; Karst;.

  • Determining the effect of deforestation on sustainable water supply in a semi-arid mountainous watershed by using Storm Water Management Model   Order a copy of this article
    by Mahmut Reis, Hurem Dutal 
    Abstract: Forest ecosystems provide a major part of ecosystem services for a human being. Especially in arid or semi-arid mountainous region, forest contributes groundwater recharge and consequently low flow by reducing runoff and increasing infiltration due to its soil and structural characteristics. In this study, the effect of deforestation on sustainable water supply in a semi-arid mountainous watershed was determined by using runoff as an indicator of groundwater recharge. SWMM (Storm Water Management Model) was used to simulate deforestation scenarios and effect of rainfall intensity. Total 60 soil samples, 30 disturbed and 30 undisturbed, were also taken from surface soil of forest, rangeland and agricultural areas. According to result, runoff amount increases from 1.505 cm3/sec to 2.509 cm3/sec with increase ratio of 66.71%, 1.881 cm3/sec with increase ratio of 24.98% and 1.658 cm3/sec with increase ratio of 10.17% during 10 mm/day rainfall event in conversion of forest to urban, agriculture and rangeland scenarios, respectively. It was also determined that rainfall intensity had more effect on runoff than deforestation in the study area. Structural properties of forest areas was dominant factor affecting runoff, because there is no statistically significant difference between hydrological soil properties of forest, agriculture and rangeland areas in the study area. The study clearly shows that deforestation can lead to decrease groundwater recharge, and consequently decrease in low flow which is important for ecosystem sustainability in especially drought periods are characteristic of Mediterranean region in the watershed.
    Keywords: deforestation;runoff amount; SWMM; forest ecosystem services.

  • The role of macroeconomic development on carbon emissions for 15 Asian countries: Panel ARDL Approach   Order a copy of this article
    by Wen-Cheng Lu 
    Abstract: This article utilized the panel autoregressive distributed lag model (ARDL) to examine the link between macroeconomic developments and carbon emissions for 15 Asian countries from 1990 to 2013. The results of the panel ARDL model showed that there existed long-run equilibrium relationships between principal macroeconomic variables and carbon emissions in the sample. The long-run elasticity of renewable energy and fossil fuels energy consumption with respect to CO_2 emissions was calculated as -0.299 and 0.967, respectively. The long-run elasticity of GDP, financial development, urban population density, and industry value added share with respect to CO_2 emissions was calculated as 0.473, 0.079, -0.633, and -0.10, respectively. FDI was significantly negatively related to CO_2 emissions which was calculated as -0.06 in the short-run. These results suggested that FDI inflow was not yet an environmental threat for Asian economies. Renewable energy and upgrades to industry value added share will help various governments mitigate carbon emissions.
    Keywords: Carbon emissions; industry value added; foreign direct investment; energy consumption; macroeconomic development;; renewable energy.

  • Current trends in scientific research on global warming: A bibliometric analysis.   Order a copy of this article
    by Jose Luis Aleixandre-Tudo, Maxima Bolanos-Pizarro, Jose Luis Aleixandre, Rafael Aleixandre-Benavent 
    Abstract: The objective of this paper was to contribute to a better understanding of the scientific knowledge in global warming, as well as to investigate the evolution of the research knowledge on the topic through the published papers included in Web of Science database. A bibliometric and social network analyses was performed to obtain indicators of scientific productivity, impact and collaboration between researchers, institutions and countries. A subject analysis was also carried out taking into account the keywords assigned to papers and subject areas of journals. A number of 1,672 articles from 2005 to 2014 were analysed. The results showed Journal of Climate (n=95) and Geophysical Research Letters (n=78) as the most productive journals and Climate Change (n=722), Model (n=216) and Temperature (n=196) as the most frequent keyword. A steadily increased in the research conducted on global warming was clearly identified during the last decade. A vast amount of journals publishing papers on the topic including several subject areas, such as Meteorology, Atmospheric sciences, Environmental sciences, Geosciences, Ecology, Energy and Fuels, Economics and Oceanography, among others, including high impact factor journals of general purpose, was also observed. The network of collaboration between countries showed the central position of United States, Germany, United Kingdom and France.
    Keywords: Global warming; research trends; scientific collaboration; bibliometric analysis; social network analysis.

  • Long term analysis of the subtropical jet over the Arabian Peninsula   Order a copy of this article
    by Falah Al Dalabeeh, Emad Imreizeeq, Hajar Alnaqi 
    Abstract: In this study, the long term change of the Arabian Peninsula subtropical jet stream (APJS) is investigated for winter time of the period 1980-2014, using data retrieved from NCEP/NCAR reanalysis of the geopotential heights 300 hPa, 200 hPa and 150 hPa. The value and position of the monthly mean of the maximum zonal wind in the jet core are determined for the mentioned period and analyzed. Also 200 hPa wind speed data of three selected points with different latitudes and longitudes are analyzed. We found that the APJS has experienced a pronounced change. It is shifting poleward and eastward for about 1.5o in January and 2.5o in February also its speed has a slight increase during autumn and more pronounced in winter. However, it is decreasing during spring and the beginning of summer. Furthermore, while the jet is steady at 300 hPa, it is intensified with increasing height, except in March where it is weakening in general. The analysis of points of different positions shows that the wind speed is broadly decreasing in the tropics, whereas the wind speed increases in the subtropics. The time series analysis of the u-component of the jet maximum series, in general, indicated non-randomness, implying 3-4 years for December and 2-3 years and 8 years for January and February of periodicity.
    Keywords: long term changes; trends; spectral analysis; Arabian Peninsula; Subtropical jet stream.

  • Global warming analysis for greenhouse gases impacts comparable to carbon-free nuclear energy using neuro-fuzzy algorithm   Order a copy of this article
    by T.A.E. H.O. WOO 
    Abstract: As one of energy characteristics, the importance of climate effects has been increasing due to the side-effect such as the draught, flood, heavy snow and so on. The nonlinear artificial intelligence can be reasonably applied in the analysis of the simulations, because the human-brain mimicking algorithm can show the practicable results. Basically, the quantifications in the study results are based on the randomly generated numbers where the Monte Carlo methods are applied. The Boolean numbers are generated in the variable constructions. Furthermore, there are multiplications in Population which are decided by the expert judgments. The causes loops for CO2 and Temperature are obtained. In addition, there is the result of variable Albedo vs. normalized Temperature with dimensionless values. Global collaboration can prepare and control the global warming as the geological scale aspect as well as the collaborated idea utilization that can develop the carbon minimizing technology and green energy development.
    Keywords: Global warming; Neuro-fuzzy; Nuclear energy; Artificial intelligence.

  • Thermodynamic assessment of the impact of the climate change on the honeybees   Order a copy of this article
    by Mustafa Özilgen, Cennet Yıldız 
    Abstract: Honeybees are among the most sensitive biological species to the changes in environmental conditions. Since pollination is necessary for the cultivation of more than 75% of the crops used directly by the people worldwide, any injury to the honeybee population due to the climate change may jeopardize the food security. Thermodynamic parameters which may affect the honeybees in the case of an anticipated temperature change, including the total of the average global warming temperature increase, plus the usual seasonal temperature changes, plus the large temperature fluctuations caused by the climate change, are assessed. Work performance and entropy generation by the honeybees while resting, foraging for nutrients outside the hive and fanning the hive are assessed based on sucrose metabolism. The minimum entropy generation accounted was 1.2 x10-7 W/g honeybee K while the 1-7 h old young honeybees were resting under atmospheric pressure with 0.5 M of sucrose supply at 15 μl/min flow rate in the hive. The maximum entropy generation, 7.2 x10-5 W/g honeybee K, was accounted during foraging at 35oC at shade with 0.5 M of unlimited sucrose supply. With 3,000 honeybees, work performance was 3.17 kJ/kg dry air, heat generation was 4.44 kJ/kg dry air and the entropy generation is 161.6 W/g honeybee K while raising the temperature of the hive by 1oC. On the other hand, they have to perform 4.5 kJ/kg dry air of work, generate 7.27 kJ/kg dry air of heat and 308.9 W/g honeybee K of entropy to reduce the temperature of the hive by 1oC. The results show that during cooling by 1oC the honey bees performed 1.4 folds of work and generated 1.9 folds of entropy when compared to that of heating by 1oC, implying that global warming may create 90% more entropy stress on the honeybees, when compared to that of a potential global cooling.
    Keywords: Thermodynamic modeling; honeybee; climate change.

  • Carbon footprint of the generation of bioelectricity from sugarcane bagasse in a sugar and ethanol industry   Order a copy of this article
    by Monica Carvalho, Valdir Bernardino Da Silva Segundo, Mariane Gama De Medeiros, Nataly Albuquerque Dos Santos, Luiz Moreira Coelho Junior 
    Abstract: Brazil indicated a commitment of reducing greenhouse gas emissions at the Paris Conference in 2015, which has led the Brazilian government to incentivize the use of renewable energy sources. Biomass is a renewable energy source that can be used to produce electricity, with its availability mainly connected to the sugar and alcohol sector in Brazil. The study presented herein applied the Life Cycle Assessment methodology to the generation of electricity from sugarcane bagasse and from diesel in thermoelectric power plants, and verified the potential to mitigate climate change. The production of electricity from sugarcane bagasse presented a low carbon footprint (0.227 kg CO2-eq/kWh), much lower than the diesel thermoelectric process (1.060 kg CO2-eq/kWh). Considering that diesel-based electricity could be substituted by bioelectricity, the result would be overall avoided emissions of -0.833 kg CO2-eq/kWh. The progressive use of sugarcane bagasse as a source of electricity presents therefore the potential to help mitigate climate change, being part of a wider scheme for the substitution of fuels.
    Keywords: sugarcane bagasse; electricity; bioenergy; life cycle assessment; carbon footprint.

  • Biogas Production in Semi-continuous-flow Reactors Using Fresh Water Hyacinth from the Chao Phraya River   Order a copy of this article
    by Nusara Sinbuathong, Wannapa Kratay, Netchanok Sombat, Suchat Leungprasert, Suriya Sawanon 
    Abstract: Biogas production was studied from the digestion of water hyacinth (WH), co-digestion of WH with cow dung and co-digestion of pretreated WH with dilute sodium hydroxide (NaOH). The reactors were fed with 20% by fresh weight of the substrate mixture of various ratios in semi-continuous-flow reactors at 30
    Keywords: anaerobic digestion;bioenergy;biogas;co-digestion;cow dung;greenhouse gas; methane;pretreatment;water hyacinth.

  • Heating Design Temperatures, Freezing Degree-Hours and Number of Freezing Hours for Selected Cities in Turkey   Order a copy of this article
    by Saban Pusat 
    Abstract: In this study, the heating design temperatures (HDTs), the freezing degree-hours (FDHs) and the number of freezing hours (NFHs) were examined for the selected cities in Turkey. Eight cities were selected for the analyses, which represent the different climatic regions of Turkey. In the analyses, the typical meteorological year (TMY) data was used. Therefore, the obtained results may be used as a general knowledge for the selected cities. According to the results of this study, the yearly minimum and maximum FDHs were calculated as 27.2 and 13842.5 for Adana and Sivas, respectively (the case 1). The minimum and maximum NFHs were obtained as 25 and 2355 for Adana and Sivas, respectively (the case 1). Sivas had the highest FDH and NFH values for all the cases. Therefore, Sivas had the highest risk of freezing and icing. Additionally, there was not a significant risk of freezing and icing in Adana, Denizli, İstanbul and Trabzon. The HDTs were calculated for the selected cities, which were the most current data for Turkey and different from the traditional data used by the Authorities. In the literature, there has not been much study on the topic of freezing and design temperature. Therefore, this study contributes to the Turkish and world literature.
    Keywords: Freezing; icing; degree-hour; freezing degree-hour; number of freezing hour; Heating design temperature; Turkey.