A first analysis of the atmospheric measurements from TANSO/GOSAT

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau em Mestre em Engenharia Física

Thermo-hydro-mechanical analysis of CO2 injection into deep aquifers

One of the biggest challenges for humanity is global warming and consequently, climate changes. Even though there has been increasing public awareness and investments from numerous countries concerning renewable energies, fossil fuels are and will continue to be in the near future, the main source of energy. Carbon capture and storage (CCS) is believed to be a serious measure to mitigate CO2 concentration. CCS briefly consists of capturing CO2 from the atmosphere or stationary emission sources and transporting and storing it via mineral carbonation, in oceans or geological media. The latter is referred to as carbon capture and geological storage (CCGS) and is considered to be the most promising of all solutions. Generally it consists of a storage (e.g. depleted oil reservoirs and deep saline aquifers) and sealing (commonly termed caprock in the oil industry) formations. The present study concerns the injection of CO2 into deep aquifers and regardless injection conditions, temperature gradients between carbon dioxide and the storage formation are likely to occur. Should the CO2 temperature be lower than the storage formation, a contractive behaviour of the reservoir and caprock is expected. The latter can result in the opening of new paths or re-opening of fractures, favouring leakage and compromising the CCGS project. During CO2 injection, coupled thermo-hydro-mechanical phenomena occur, which due to their complexity, hamper the assessment of each relative influence. For this purpose, several analyses were carried out in order to evaluate their influences but focusing on the thermal contractive behaviour. It was finally concluded that depending on mechanical and thermal properties of the pair aquifer-seal, the sealing caprock can undergo significant decreases in effective stress.

Analysis and visualization of energy use for university campus

The reduction of greenhouse gas emissions is one of the big global challenges for the next decades due to its severe impact on the atmosphere that leads to a change in the climate and other environmental factors. One of the main sources of greenhouse gas is energy consumption, therefore a number of initiatives and calls for awareness and sustainability in energy use are issued among different types of institutional and organizations. The European Council adopted in 2007 energy and climate change objectives for 20% improvement until 2020. All European countries are required to use energy with more efficiency. Several steps could be conducted for energy reduction: understanding the buildings behavior through time, revealing the factors that influence the consumption, applying the right measurement for reduction and sustainability, visualizing the hidden connection between our daily habits impacts on the natural world and promoting to more sustainable life. Researchers have suggested that feedback visualization can effectively encourage conservation with energy reduction rate of 18%. Furthermore, researchers have contributed to the identification process of a set of factors which are very likely to influence consumption. Such as occupancy level, occupants behavior, environmental conditions, building thermal envelope, climate zones, etc. Nowadays, the amount of energy consumption at the university campuses are huge and it needs great effort to meet the reduction requested by European Council as well as the cost reduction. Thus, the present study was performed on the university buildings as a use case to: a. Investigate the most dynamic influence factors on energy consumption in campus; b. Implement prediction model for electricity consumption using different techniques, such as the traditional regression way and the alternative machine learning techniques; and c. Assist energy management by providing a real time energy feedback and visualization in campus for more awareness and better decision making. This methodology is implemented to the use case of University Jaume I (UJI), located in Castellon, Spain.