Climate change mitigation

Summary

Climate change mitigation is action to limit climate change by reducing emissions of greenhouse gases or removing those gases from the atmosphere. The recent rise in global average temperature is mostly due to emissions from burning fossil fuels such as coal, oil, and natural gas. Mitigation can reduce emissions by transitioning to sustainable energy sources, conserving energy, and increasing efficiency. It is possible to remove carbon dioxide () from the atmosphere by enlarging forests, restoring wetlands and using other natural and technical processes. Experts call these processes carbon sequestration. Governments and companies have pledged to reduce emissions to prevent dangerous climate change in line with international negotiations to limit warming by reducing emissions. Solar energy and wind power have the greatest potential for mitigation at the lowest cost compared to a range of other options. The availability of sunshine and wind is variable. But it is possible to deal with this through energy storage and improved electrical grids. These include long-distance electricity transmission, demand management and diversification of renewables. It is possible to reduce emissions from infrastructure that directly burns fossil fuels, such as vehicles and heating appliances, by electrifying the infrastructure. If the electricity comes from renewable sources instead of fossil fuels this will reduce emissions. Using heat pumps and electric vehicles can improve energy efficiency. If industrial processes must create carbon dioxide, carbon capture and storage can reduce net emissions. Greenhouse gas emissions from agriculture include methane as well as nitrous oxide. It is possible to cut emissions from agriculture by reducing food waste, switching to a more plant-based diet, by protecting ecosystems and by improving farming processes. Changing energy sources, industrial processes and farming methods can reduce emissions. So can changes in demand, for instance in diets or the way we build and travel in cities.

Categories

Official source

https://en.wikipedia.org/wiki/Climate_change_mitigation

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With the increasing strength and frequency of climate change events, the urgency to mitigate climate change impact is ever so important. Canada reported his Nationally Determined Contribution (NDC) and submitted its ambition to reduce his Greenhouse Gas (GHG) emissions by 40-45% by 2030 compared to 2005 and reach net-zero emissions by 2050. Interest for energy system modelling has been increasing for planning future energy systems, as a result of growing concern for sustainable development and transition towards renewable energies. Nevertheless, planning a decarbonization of energy system can potentially lead to environmental burden shifting, and can increase impacts on other environmental impacts such as ecosystem quality or human health. Thus, this project aims towards integrating Life Cycle Analysis (LCA) and more specifically Life Cycle Impact Assessment (LCIA) within Energy Systems Modelling, in order to minimize not only climate change impacts, but human health and ecosystem quality. In addition, a dual spatial resolution was integrated in the model in order to increase data precision and computational efficiency. The results show that a low-carbon energy system, based on the optimization of GHG emissions allows to greatly reduce all the environmental impacts under analysis, compared to an all economic- based energy system, but a multi-objective optimization allows to simultaneously reduce impacts on ecosystem quality and human health, while reducing GHG emissions and keeping good economical and technical performances. The results also show that it is theoretically possible for Canada to keep on track with their emission reduction ambition by 2030, by deploying more renewable energies. This project does not allow assessing Canada’s potential to reach net-zero emissions, as environmental impacts from carbon capture technologies are still to be characterized and integrated in the model.

2022

A mixture model to take into account diluted gas in liquid flow: applications to aluminium electrolysis

Emile Tryphon Pierre Soutter

Aluminium is a metal sought in the industry because of its various physical properties. It is produced by an electrolysis reduction process in large cells. In these cells, a large electric current goes through the electrolytic bath and the liquid aluminium. This electric current generates electromagnetic forces that set the bath and the aluminium into motion. Moreover, large quantities of carbon dioxide gas are produced through chemical reactions in the electrolytic bath: the presence of these gases alleviates the density of the liquid bath and changes the dynamics of the flow. Accurate knowledge of this fluid flow is essential to improve the efficiency of the whole process.The purpose of this thesis is to study and approximate the interaction of carbon dioxide with the fluid flow in the aluminium electrolysis process.In the first chapter of this work, a mixture-averaged model is developed for mixtures of gas and liquid. The model is based on the conservation of mass and momentum equations of the two phases, liquid and gas. By combining these equations, a system is established that takes into account the velocity of the liquid-gas mixture, the pressure, the gas velocity and the local gas concentration as unknowns.In the second chapter, a simplified problem is studied theoretically. It is shown that under the assumption that the gas concentration is small, the problem is well-posed. Moreover, we prove a priori error estimates of a finite element approximation of this problem.In the third chapter, we compare this liquid-gas model with a water column reactor experiment. Finally, the last chapter shows that the fluid flow is changed in aluminium electrolysis cells when we take into account the density of the bath reduced by carbon dioxide. These changes are quantified as being of the order of 30% and explain partially the differences between previous models and observations from Rio Tinto Aluminium engineers.

EPFL2022

To reduce the CO2 footprint of construction materials, concrete producers blend their cement with Supplementary Cementitious Materials (SCMs). SCMs such as fly ash or blast furnace slag are mostly the byproducts of other industries. And while SCMs are chosen to match the properties of the common Ordinary Portland cement (OPC), their addition to the cement recipe may alter the chemistry of the system. These changes may lead to different mechanical and transport properties of the cement-based structure which may, in turn, affect its long-term resistance to harmful external agents. Therefore, understanding the relationship between cementâs microstructure and the degradation mechanisms is key for optimizing the design of new cementitious materialsIn this context, chloride attack is the most common reason for steel rebars to corrode especially when exposed to external chloride (seawater, deicer saltsâŠ). At low w/c ratios (typically 13) pore solution, the C-S-H surface develops a negative surface charge density. Electrostatic interactions between the surface and the ions in the pore solution result in a redistribution of the ionic species in two layers of charge at the interface of the solid i.e. the Electrical double layer (EDL). In nanoscopic pores, the EDL is dominated by atomic phenomena which are thought to interfere with the mobility of ions and chloride in particular. In order to understand and quantify the surface effects and their influence on ionic transport, we firstly propose an atomistic model of the EDL formation based on the use of the Metropolis Monte Carlo algorithm. This model is used to compute the ionic distributions and electrochemical potentials of electrolytes at equilibrium in nanoscopic pores. These quantities constitute the main driving forces of ionic transport at the pore scale. The microstructure parameters including the surface charge density of C-S-H, the ionic strength (and pH) of the pore solution, and the pore size are equally investigated and their effect on chlorideâs behavior quantified. Among the other parameters, the model also provides quantitative information on the effect of calcium ions which are thought to play a major role in the binding of chloride on C-S-H. The next step consists in using the calculated atomic-scale properties of the EDL in order to resolve the transport problem at the pore scale and compute microscopic diffusivities of chloride. This is achieved by using the molecular computations from the Monte Carlo (MC) engine in order to implement a modified version of the classical Poisson-Boltzmann system. The method is compared to the classical Finite element analysis of the Poisson-Nernst-Planck (PNP) equations and the data are discussed in the light of established experimental results in the literature.

EPFL2022