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Tremendous growth in the number of automobiles in developed and developing global economies has exorbitantly boosted competition for petroleum products. Petroleum products derived from fossil fuels are predominantly responsible for environmental pollution as unburnt hydrocarbon (HC), carbon monoxide (CO), oxides of nitrogen (NOx) & carbon dioxide (CO2) emissions are released from the fossil fuel combustion. In the view of increasing environmental pollution and stringent emission norms, the present study is concentrated on using Jatropha biodiesel as an alternate fuel source to run variable compression ratio (VCR) diesel engine. The characteristics of VCR diesel engine emission have been evaluated under different compression ratio (CR), operating conditions of load & pressure of fuel injection. In this research work, Jatropha biodiesel diesel blend B30 (30% biodiesel and 70% diesel) and B0 (100% diesel) have been taken as fuel to run the engine. For conducting experiments, load has been varied from 0 to 12 Kg, CR from 14 to 18 and FIP from 180 to 270 bar as per the model of Response Surface Methodology experiments. The experimental investigation showed that the use of the B30 blend reduces HC & CO emissions by about 16.7% and 24% correspondingly in comparison to diesel. However noteworthy rise in NOx & CO2 emissions rate recorded by using the B30 blend as that of diesel. It has been shown that with enhancing in load & CR, HC&CO emissions decreased significantly however increase in CO2 and NOx observed. Advancing FIP, significantly decreases HC & CO emissions as well as tends to increase NOx and CO2 emissions.

Tremendous growth in the number of automobiles in developed and developing global economies has exorbitantly boosted competition for petroleum products. Petroleum products derived from fossil fuels are predominantly responsible for environmental pollution as unburnt hydrocarbon (HC), carbon monoxide (CO), oxides of nitrogen (NOx) & carbon dioxide (CO2) emissions are released from the fossil fuel combustion. In the view of increasing environmental pollution and stringent emission norms, the present study is concentrated on using Jatropha biodiesel as an alternate fuel source to run variable compression ratio (VCR) diesel engine. The characteristics of VCR diesel engine emission have been evaluated under different compression ratio (CR), operating conditions of load & pressure of fuel injection. In this research work, Jatropha biodiesel diesel blend B30 (30% biodiesel and 70% diesel) and B0 (100% diesel) have been taken as fuel to run the engine. For conducting experiments, load has been varied from 0 to 12 Kg, CR from 14 to 18 and FIP from 180 to 270 bar as per the model of Response Surface Methodology experiments. The experimental investigation showed that the use of the B30 blend reduces HC & CO emissions by about 16.7% and 24% correspondingly in comparison to diesel. However noteworthy rise in NOx & CO2 emissions rate recorded by using the B30 blend as that of diesel. It has been shown that with enhancing in load & CR, HC&CO emissions decreased significantly however increase in CO2 and NOx observed. Advancing FIP, significantly decreases HC & CO emissions as well as tends to increase NOx and CO2 emissions.

In strategic energy planning, human-oriented factors are uncertain and lead to unpredictable challenges. Thus, decision-makers must contextualize the target society to address these uncertainties. More precisely, uncertainties lead to performance gaps between assumed and actual sustainability target outcomes. This study proposed a new framework that considers vital elements, including occupant motivation, preference, socioeconomic characteristics, and building features (MPSEB). To utilize this model, a thorough face-to-face survey questionnaire was administered to measure these elements. This study explored how these elements affect the patterns of residential energy consumption in a region with numerous expat communities of various ethnic and cultural backgrounds. In particular, the study investigated the patterns of energy behaviors and human-building interactions among the residents of Qatar by collecting empirical evidence and conducting a subsequent survey analysis. Machine learning approaches were employed to explore the survey data and determine the interdependencies between features, as well as the significance of the fundamental factors influencing human-building interactions. The XGBoost method was used to conduct a feature importance analysis to determine factors contributing to residential energy consumption. The results revealed the primary behavioral and socioeconomic factors that affect residential energy consumption, and confirmed the influence of human factors in Qatar while considering its diverse population. This publication was made possible by an NPRP award [ NPRP13S-0206–200272 ] from the Qatar National Research Fund (a member of Qatar Foundation ). The statements made herein are solely the responsibility of the authors. The open access publication of this article was funded by the Qatar National Library (QNL).

In strategic energy planning, human-oriented factors are uncertain and lead to unpredictable challenges. Thus, decision-makers must contextualize the target society to address these uncertainties. More precisely, uncertainties lead to performance gaps between assumed and actual sustainability target outcomes. This study proposed a new framework that considers vital elements, including occupant motivation, preference, socioeconomic characteristics, and building features (MPSEB). To utilize this model, a thorough face-to-face survey questionnaire was administered to measure these elements. This study explored how these elements affect the patterns of residential energy consumption in a region with numerous expat communities of various ethnic and cultural backgrounds. In particular, the study investigated the patterns of energy behaviors and human-building interactions among the residents of Qatar by collecting empirical evidence and conducting a subsequent survey analysis. Machine learning approaches were employed to explore the survey data and determine the interdependencies between features, as well as the significance of the fundamental factors influencing human-building interactions. The XGBoost method was used to conduct a feature importance analysis to determine factors contributing to residential energy consumption. The results revealed the primary behavioral and socioeconomic factors that affect residential energy consumption, and confirmed the influence of human factors in Qatar while considering its diverse population. This publication was made possible by an NPRP award [ NPRP13S-0206–200272 ] from the Qatar National Research Fund (a member of Qatar Foundation ). The statements made herein are solely the responsibility of the authors. The open access publication of this article was funded by the Qatar National Library (QNL).

Abstract A deep plan layout and internal partitioning and resistances along the wind path in interior spaces make single-sided ventilation the only strategy possible for residential units. In this work, the potential of single-sided ventilation through the introduction of a balcony was investigated. The design of the wing wall at the balcony was investigated to determine its effect on the performance of single-sided indoor ventilation. The methodology used in was computer simulation (computational fluid dynamics or CFD) validated by data on an existing wind tunnel study and the measurements from a selected case study. CFD simulation was conducted on a simplified model of a medium-rise and low-cost residential building in Johor Bahru, Malaysia. Upon validation, the four wing wall depths and three wing wall angles were applied to the balcony, and each was evaluated numerically. Results showed that the provision of wing wall in the balcony could increase the indoor air velocity and airflow rate and improve the airflow distribution in the room if appropriately designed. The indoor ventilation performance was improved by increasing the wing wall size up to a certain depth and deviation of 22.5°. The provision of a balcony with wing walls can be a facade design alternative to improve indoor ventilation and possibly reduce energy consumption in buildings.

Abstract A deep plan layout and internal partitioning and resistances along the wind path in interior spaces make single-sided ventilation the only strategy possible for residential units. In this work, the potential of single-sided ventilation through the introduction of a balcony was investigated. The design of the wing wall at the balcony was investigated to determine its effect on the performance of single-sided indoor ventilation. The methodology used in was computer simulation (computational fluid dynamics or CFD) validated by data on an existing wind tunnel study and the measurements from a selected case study. CFD simulation was conducted on a simplified model of a medium-rise and low-cost residential building in Johor Bahru, Malaysia. Upon validation, the four wing wall depths and three wing wall angles were applied to the balcony, and each was evaluated numerically. Results showed that the provision of wing wall in the balcony could increase the indoor air velocity and airflow rate and improve the airflow distribution in the room if appropriately designed. The indoor ventilation performance was improved by increasing the wing wall size up to a certain depth and deviation of 22.5°. The provision of a balcony with wing walls can be a facade design alternative to improve indoor ventilation and possibly reduce energy consumption in buildings.

Abstract Renewable energy has gained popularity as an alternative to fossil fuels, which regularly emit large amounts of Greenhouse Gases and consume/withdraw large amounts of water, but renewable energy market penetration is still limited while fossil fuels are still the U.S.‘s dominant power source. This is due to resistance in the market, or in this case, the failure of renewable energy policies to achieve long-term environmental sustainability due to neglected external factors (economic, societal, etc.). No available literature analyzes potential sources and/or effects of this policy resistance, so this research investigates the underlying mechanisms in the renewable energy generation market by utilizing a system dynamics model. A two-alternative Generalized Bass Model was developed to simulate the renewable energy market (specifically with respect to solar PV and wind energy), including the environmental, societal, and economic concerns associated with each of the alternatives evaluated in this study, so as to identify and address possible causes of policy resistance and its subsequent effects on environmental impacts (esp. GHG emissions and water withdrawal rates). Based on this model, three separate policy areas (solar PV investments, wind power investments, and the elimination of fossil fuel subsidies) and various combinations thereof were proposed and tested within the context of the model. Based on the results of this study, it is highly recommended to invest as generously as possible into multiple renewable energy industries, reduce fossil fuel subsidies (in turn freeing up funding for renewable energy investments), and seek further advancement in renewable energy technologies (e.g. enhancing the useable lifetimes of wind turbines). A balanced policy have potential to increase the share of renewable's up to roughly 40% in the U.S. by 2050, as well as 17% and 32% GHG and water withdrawal reduction potential by 2050.

Abstract Renewable energy has gained popularity as an alternative to fossil fuels, which regularly emit large amounts of Greenhouse Gases and consume/withdraw large amounts of water, but renewable energy market penetration is still limited while fossil fuels are still the U.S.‘s dominant power source. This is due to resistance in the market, or in this case, the failure of renewable energy policies to achieve long-term environmental sustainability due to neglected external factors (economic, societal, etc.). No available literature analyzes potential sources and/or effects of this policy resistance, so this research investigates the underlying mechanisms in the renewable energy generation market by utilizing a system dynamics model. A two-alternative Generalized Bass Model was developed to simulate the renewable energy market (specifically with respect to solar PV and wind energy), including the environmental, societal, and economic concerns associated with each of the alternatives evaluated in this study, so as to identify and address possible causes of policy resistance and its subsequent effects on environmental impacts (esp. GHG emissions and water withdrawal rates). Based on this model, three separate policy areas (solar PV investments, wind power investments, and the elimination of fossil fuel subsidies) and various combinations thereof were proposed and tested within the context of the model. Based on the results of this study, it is highly recommended to invest as generously as possible into multiple renewable energy industries, reduce fossil fuel subsidies (in turn freeing up funding for renewable energy investments), and seek further advancement in renewable energy technologies (e.g. enhancing the useable lifetimes of wind turbines). A balanced policy have potential to increase the share of renewable's up to roughly 40% in the U.S. by 2050, as well as 17% and 32% GHG and water withdrawal reduction potential by 2050.