Carbon Capture and Storage Potential Contribution to Mitigate Climate Change By Angel Mario Baca, M.A. The University of Texas at Austin, 2009 Supervisor: Dr. Eric Bickel This thesis evaluates the potential of the Carbon Capture and Storage technologies to mitigate climate change. This work emerged from the current debate regarding when CCS technologies are going to be ready in a commercial-scale, or whether they are going to be economically viable. Geologically, the world contains enough room for storing CO2 emissions, but it is still unsolved if leakage can be controlled and monitored. This research focuses on the development of an economic model to estimate the value of CCS.. This model uses equations from the DICE (Dynamic Integrated model on Climate and the Economy). Then, it estimates what change in temperature could occur, and computes the present value of damages to the economy. Moreover, emissions are simulated using the 40 scenario emissions from the Intergovernmental Panel on Climate Change. As the main conclusion of this model, CCS has to be deployed in almost in the entire number of fossil fuel plants around the world and has to be done in the next 30 years to see CCS having an impact, otherwise it would be relatively small and not worth it. Moreover, CCS technologies are part of the components to reduce climate change, but not the main one. It is required that governments, companies, and institution focus their efforts in working collaboratively towards the enforcement of new policies and development of more technologies. / text

Worldwide, the residential sector is a major consumer of energy. Both the rate at which we consume energy and our use of non-renewable energy resources have come under pressure to change. These changes may occur to some extent by conservation techniques. However, due to living standard expectations, these changes will primarily rely on technology. Many technological opportunities exist to reduce the conventional energy consumption and greenhouse gas (GHG) emissions of the residential sector, such as: improving energy efficiency, introducing alternative energy conversion technologies, and increasing the use of renewable energy resources. The accurate estimate of the impact that a new technology has on residential sector energy consumption and GHG emissions requires a versatile, reliable, detailed, and high-resolution analytical model. Such models account for the wide range of climate, energy supply, and housing stock characteristics, and are useful for decision makers to evaluate and parametrically compare a wide range of energy efficiency measures and technology strategies when applied to the residential sector. This dissertation presents the development of a new energy consumption and GHG emissions model of the Canadian residential sector. This new model is detailed with regard to the housing stock, comprehensive with regard to the treatment of end-uses (including thermodynamic behaviour and occupant behaviour), and possesses the capability, resolution, and accuracy to assess the impact upon energy consumption and GHG emissions due to the application of alternative and renewable energy technologies to the residential sector. The new model is titled the Canadian Hybrid Residential End-Use Energy and GHG Emissions Model (CHREM). The CHREM advances the state-of-the-art of residential sector energy consumption and GHG emissions modeling by three principal contributions: i) a database of 16,952 unique house descriptions of thermal envelope and energy conversion system information that statistically represent the Canadian housing stock; ii) a “hybrid” modeling approach that integrates the bottom-up statistical and engineering modeling methods to account for occupant behaviour, and provide the capacity to model alternative and renewable energy technologies, such as solar energy and energy storage systems; and iii) a method for the accumulation and treatment of energy and GHG emissions results.

Industrial ecology is a field of study that encourages the use of closed-loop material cycles to achieve sustainability. Loop closing requires the movement of materials over space, and has long been practiced in the iron and steel industry. Iron and steel (ferrous) scrap generated in the U.S. is increasingly exported to countries in Asia, lengthening the transportation distance associated with closing the loop on the iron and steel life cycle. In order to understand the environmental cost of transporting this commodity, an activity-based maritime transportation model and a theoretical in-land transportation model are used to estimate emissions generated. Results indicate that 10.4 mmt of total emissions were generated, and emissions increased by 136 percent from 2004 to 2009. Increases in the amount of emissions generated are due to increases in the amount of scrap exported and distance it is transported.

This thesis discusses enhancements to the Global Demand Model (GDM). The model addresses the need to predict: a) number of flights Worldwide by Origin-Destination (OD) airport pair, b) the number of seats (surrogate of demand) by OD airport pair, c) the fleet evolution over time, d) fuel consumption by OD pair and aircraft type, and emissions by OD pair and aircraft type. The model has developed an airline fleet assignment module to predict changes to the airline fleet in the future. Specifically, the model has the capability to examine the fuel and emission benefits of next generation N+1 aircraft and advanced NASA's N+2 aircraft are adopted in the future. / Master of Science

Le Transport A la Demande (TAD) est un système de transport qui propose un usage collectif des véhicules automobiles, par opposition à l’usage des véhicules personnels (VP). Situé entre le fonctionnement des taxis et celui des transports en commun classiques, il propose un service à la fois flexible dans le temps et dans l'espace à la manière des taxis, favorisant le partage des véhicules, comme les transports en commun. Il est ainsi présenté comme une réponse pour une mobilité durable. Dans les esprits, les TAD sont souvent associés à une réduction des émissions de polluants et sont mis en place principalement dans des territoires ruraux. Pourtant, le simple regroupement effectué par les TAD suffit-il pour que la mise en place des TAD soit profitable à l’environnement ? Dans ce travail de recherche de doctorat, un outil d’évaluation de l'impact environnemental d’un système de Transports À la Demande (TAD) destiné aux collectivités territoriales a été mis au point. Pour que choix soit durable, au sens du développement durable, le service doit être le plus adapté au contexte local en minimisant les émissions de substances dans l’atmosphère proche tout en conservant une qualité de service suffisante pour concurrencer l'usage du véhicule personnel. Un paramètre, directement impliqué dans les émissions de polluant, est souvent négligé dans les approches : le réseau routier. On cherche donc à identifier des lois et des seuils relatifs aux émissions de polluants produites par le fonctionnement d’un TAD : dans quelle mesure le réseau routier influe-t-il sur les performances environnementales des TAD ou sur la capacité de regroupement des clients dans les véhicules ? Selon quelles caractéristiques de service (fenêtres de temps autorisées) ? Plus globalement, est-ce que l’optimisation d’un même type de TAD est équivalente d’un réseau routier à un autre, du point de vue des émissions de polluants ? Aucun outil intégré permettant d’effectuer cette tâche n’étant disponible, nous avons mis au point une chaîne de traitement géomatique permettant d’estimer les quantités de polluants émises sur les tronçons de route dans le cadre du fonctionnement particulier des TAD et de les cartographier pour analyser leur répartition spatiale. Cet outil associe un SIG à un modèle d’émission que nous avons adapté à notre problématique (GREEN-DRT). Il est ressorti des différents scénarios simulés que les TAD ne sont pas systématiquement une solution pertinente dans un objectif de réduction globale des émissions de polluants sur un territoire donné. Le constat de la faible pertinence environnementale de ce mode de transport sur les territoires les moins denses (type zones rurales) a été fait, pourtant, ce sont sur ces territoires que les TAD sont développés en France. À défaut d’engendrer une réduction des émissions, ils ont souvent un rôle social important en se positionnant non pas comme une alternative à la voiture personnelle, mais en permettant à des populations captives de se déplacer. Il s’agit de ce cas de minimiser les émissions de polluants provoquées par le fonctionnement du service. / The Demand Responsive Transport (DRT) is a transportation system which offers a collective use of motor vehicles, in opposite of personal vehicles use. Between the functioning of taxis and classical public transport, it offers a service that is flexible in time and space like taxis, promoting the sharing of vehicles, like public transports. It is why it is present as a solution for a sustainable mobility. In the minds, DRT are often associated to a reduction of exhaust emissions and so are developed in rural areas. However, is grouping travellers enough to make DRT gainful for environment?In this doctoral research, an assessment tool of the environmental impact of DRT systems has been developed. To ensure that choice is sustainable in the sense of sustainable development, the service must be adapted to the local context by minimising emissions of substances in the near atmosphere while maintaining a sufficient quality of service when competing against personal vehicle use. A parameter directly involved in pollutant emissions, is often overlooked in approaches: the road network. We therefore search for identify laws and thresholds relating to pollutant emissions generated by the functioning of a DRT: how the road network does it affect the environmental performance of DRT or on the skill to grouping customers in vehicles? Depending on what service features (time windows allowed)? More generally, is that the optimization of the same type of DRT is equivalent to a road network to another, from the perspective of pollutant emissions? As any integrated tool to perform this task is available, we have developed a geomatics processing to estimate the quantities of pollutants emitted on road sections within the particular functioning of DRT and to cartography it to analyse their spatial distribution. This tool combines a GIS to an exhaust emissions model that we have adapted to our questioning (GREEN-DRT).

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On-road vehicles are a major source of transportation carbon dioxide (CO2) greenhouse gas emissions in all the developed countries, and in many of the developing countries in the world. Similarly, several criteria air pollutants are associated with transportation, e.g., carbon monoxide (CO), nitrogen oxides (NOx), and particulate matter (PM). The need to accurately quantify transportation-related emissions from vehicles is essential. Transportation agencies and researchers in the past have estimated emissions using one average speed and volume on a long stretch of roadway. With MOVES, there is an opportunity for higher precision and accuracy. Integrating a microscopic traffic simulation model (such as VISSIM) with MOVES allows one to obtain precise and accurate emissions estimates. The new United States Environmental Protection Agency (USEPA) mobile source emissions model, MOVES2010a (MOVES) can estimate vehicle emissions on a second-by-second basis creating the opportunity to develop new software ―VIMIS 1.0‖ (VISSIM/MOVES Integration Software) to facilitate the integration process. This research presents a microscopic examination of five key transportation parameters (traffic volume, speed, truck percentage, road grade and temperature) on a 10-mile stretch of Interstate 4 (I- 4) test bed prototype; an urban limited access highway corridor in Orlando, Florida. iv The analysis was conducted utilizing VIMIS 1.0 and using an advanced custom design technique; D-Optimality and I-Optimality criteria, to identify active factors and to ensure precision in estimating the regression coefficients as well as the response variable. The analysis of the experiment identified the optimal settings of the key factors and resulted in the development of Micro-TEM (Microscopic Transportation Emissions MetaModel). The main purpose of Micro-TEM is to serve as a substitute model for predicting transportation emissions on limited access highways in lieu of running simulations using a traffic model and integrating the results in an emissions model to an acceptable degree of accuracy. Furthermore, significant emission rate reductions were observed from the experiment on the modeled corridor especially for speeds between 55 and 60 mph while maintaining up to 80% and 90% of the freeway‘s capacity. However, vehicle activity characterization in terms of speed was shown to have a significant impact on the emission estimation approach. Four different approaches were further examined to capture the environmental impacts of vehicular operations on the modeled test bed prototype. First, (at the most basic level), emissions were estimated for the entire 10-mile section ―by hand‖ using one average traffic volume and average speed. Then, three advanced levels of detail were studied using VISSIM/MOVES to analyze smaller links: average speeds and volumes (AVG), second-bysecond link driving schedules (LDS), and second-by-second operating mode distributions (OPMODE). This research analyzed how the various approaches affect predicted emissions of CO, NOx, PM and CO2. v The results demonstrated that obtaining accurate and comprehensive operating mode distributions on a second-by-second basis improves emission estimates. Specifically, emission rates were found to be highly sensitive to stop-and-go traffic and the associated driving cycles of acceleration, deceleration, frequent braking/coasting and idling. Using the AVG or LDS approach may overestimate or underestimate emissions, respectively, compared to an operating mode distribution approach. Additionally, model applications and mitigation scenarios were examined on the modeled corridor to evaluate the environmental impacts in terms of vehicular emissions and at the same time validate the developed model ―Micro-TEM‖. Mitigation scenarios included the future implementation of managed lanes (ML) along with the general use lanes (GUL) on the I-4 corridor, the currently implemented variable speed limits (VSL) scenario as well as a hypothetical restricted truck lane (RTL) scenario. Results of the mitigation scenarios showed an overall speed improvement on the corridor which resulted in overall reduction in emissions and emission rates when compared to the existing condition (EX) scenario and specifically on link by link basis for the RTL scenario. The proposed emission rate estimation process also can be extended to gridded emissions for ozone modeling, or to localized air quality dispersion modeling, where temporal and spatial resolution of emissions is essential to predict the concentration of pollutants near roadways