scholarly journals Uncertainty Analysis of Life Cycle Greenhouse Gas Emissions from Petroleum-Based Fuels and Impacts on Low Carbon Fuel Policies

2011 ◽  
Vol 45 (1) ◽  
pp. 125-131 ◽  
Author(s):  
Aranya Venkatesh ◽  
Paulina Jaramillo ◽  
W. Michael Griffin ◽  
H. Scott Matthews
Keyword(s):  
Life Cycle ◽  
Uncertainty Analysis ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Low Carbon ◽  
Gas Emissions

Incorporating uncertainty analysis into life cycle estimates of greenhouse gas emissions from biomass production

2011 ◽  
Vol 35 (7) ◽  
pp. 2619-2626 ◽  
Author(s):  
David R. Johnson ◽  
Henry H. Willis ◽  
Aimee E. Curtright ◽  
Constantine Samaras ◽  
Timothy Skone
Keyword(s):  
Life Cycle ◽  
Uncertainty Analysis ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Biomass Production ◽  
Gas Emissions

scholarly journals Analysis of the Potential for Reducing Life Cycle Greenhouse Gas Emissions from Motor Fuels

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3744
Author(s):  
Delfina Rogowska ◽  
Artur Wyrwa
Keyword(s):  
Life Cycle ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Ghg Emissions ◽  
Low Carbon ◽  
Fuel Production ◽  
Gas Emissions ◽  
Motor Fuels ◽  
Process Heating ◽  
The Impact

The assessment of life cycle greenhouse gas emissions of motor fuels is important due to the legal obligations and corporate social responsibility of the petroleum industry. Combining the Life-Cycle Assessment with optimization methods can provide valuable support in the decision-making process. In this paper, a mathematical model of a refinery was developed to analyze the impact of process optimization on GHG emissions at the fuel production stage. The model included ten major refinery units. Fuel production costs were minimized by taking into account the number of constraints. The analysis was performed in two steps. First, the model was run for the reference case of fuels composition. Then, more than twelve thousand model runs were performed. In each model, the fuel composition was changed. This change represented the exogenous pressures and resulted in different flows of mass, energy and GHG emission at the refinery. The most favorable results in terms of GHG emissions were then identified and analyzed. Additionally, the impact of using low-carbon fuels for process heating was evaluated. The study showed that fuel blending management could lead to the reduction of GHG emissions by 0.4 gCO2-eq/MJ while the use of low-carbon fuel for process heating results in a reduction of GHG emissions by 2 ca. gCO2-eq/MJ.

Low-Carbon Russia: Prospects after the Crisis

2009 ◽  
pp. 107-120 ◽  
Author(s):  
I. Bashmakov
Keyword(s):  
Economic Growth ◽  
Potential Energy ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Low Carbon ◽  
Modeling Tools ◽  
Gas Emissions ◽  
Scenario Approach

On the eve of the worldwide negotiations of a new climate agreement in December 2009 in Copenhagen it is important to clearly understand what Russia can do to mitigate energy-related greenhouse gas emissions in the medium (until 2020) and in the long term (until 2050). The paper investigates this issue using modeling tools and scenario approach. It concludes that transition to the "Low-Carbon Russia" scenarios must be accomplished in 2020—2030 or sooner, not only to mitigate emissions, but to block potential energy shortages and its costliness which can hinder economic growth.

scholarly journals Impact of Cycle Time and Payload of an Industrial Robot on Resource Efficiency

Robotics ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 33
Author(s):  
Florian Stuhlenmiller ◽  
Steffi Weyand ◽  
Jens Jungblut ◽  
Liselotte Schebek ◽  
Debora Clever ◽  
...  
Keyword(s):  
Life Cycle Assessment ◽  
Life Cycle ◽  
Energy Consumption ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Resource Efficiency ◽  
Life Cycle Costs ◽  
Gas Emissions ◽  
Cycle Times ◽  
The Individual

Modern industry benefits from the automation capabilities and flexibility of robots. Consequently, the performance depends on the individual task, robot and trajectory, while application periods of several years lead to a significant impact of the use phase on the resource efficiency. In this work, simulation models predicting a robot’s energy consumption are extended by an estimation of the reliability, enabling the consideration of maintenance to enhance the assessment of the application’s life cycle costs. Furthermore, a life cycle assessment yields the greenhouse gas emissions for the individual application. Potential benefits of the combination of motion simulation and cost analysis are highlighted by the application to an exemplary system. For the selected application, the consumed energy has a distinct impact on greenhouse gas emissions, while acquisition costs govern life cycle costs. Low cycle times result in reduced costs per workpiece, however, for short cycle times and higher payloads, the probability of required spare parts distinctly increases for two critical robotic joints. Hence, the analysis of energy consumption and reliability, in combination with maintenance, life cycle costing and life cycle assessment, can provide additional information to improve the resource efficiency.

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