The energy consumption and greenhouse gas (GHG) emissions associated with urban water systems have come under scrutiny in recent times, as a result of increasing interest in climate change, to which urban water systems are particularly vulnerable. The approach most commonly taken previously to modelling these results has been to consider various urban water system components in great detail, but in isolation from the rest of the system. This piecewise approach is suboptimal, since it systematically fails to reveal the relative importance of the energy consumption and GHG emissions associated with each system component in the context of the entire urban water system. Hence, it was determined that a new approach to modelling the energy consumption and GHG emissions associated with urban water systems was necessary. It was further determined that the value derived from such a model would be greatly enhanced if it could also model the water consumption and wastewater generation associated with each system component, such that integrated policies could be developed, aimed at minimising water consumption, wastewater generation, energy consumption and GHG emissions concurrently. Hence, the following research question was posed: How should the relationships between the water consumption, wastewater generation, energy consumption and GHG emissions associated with the operation of urban water systems be modelled such that the impact of various changes to the system configuration made at different spatial scales can be determined within the context of the entire system? In this research project, life cycle assessment ideas were employed to develop such a new modelling methodology. Initially, the approach was developed at the building-scale, such that the end uses of water present in a selected building and any associated appliances could be modelled, along with the fraction of the citywide water supply and wastewater systems directly associated with providing services to that building. This vast breadth of scope was delivered by considering only the operational life cycle stage of each urban water system component, excluding both the pre- and post-operational life cycle stages of the associated infrastructure. The value of this pilot model was illustrated by several case studies, focused on residential buildings connected to the centralised water supply and wastewater systems in Melbourne, Australia. Later, the approach was extended to the city-scale by using probabilistic distributions of each input parameter, such that all of the end uses of water present in a city, and all of the associated building-scale appliances could be modelled, along with the associated complete water supply and wastewater systems. The value of this city-scale model was illustrated by applying it to model a hypothetical case study city, resembling Melbourne, Australia in many ways. Due to a lack of data, this application was limited to the residential sector of the case study city, along with the fraction of the citywide water supply and wastewater systems directly associated with providing services to that sector. The results generated by the pilot and city-scale models showed that the new modelling methodology could be employed at a wide range of scales to assess the relative importance of each modelled urban water system component in terms of the specified results. Importantly, the high resolution of those results enabled the identification of the underlying causes of the relative importance of each urban water system component, such that efficient and effective approaches to reducing each result for each system component could be developed. Interestingly, for the specific case studies investigated, it was revealed that some commonly neglected system components were actually extremely important, such as domestic hot water services, a trend found to be largely driven by hot water consumption in showers.

In recent years, the issues of energy dependency and renewable energy options have gained recognition with not only policy-makers but also mainstream consumers. Understanding consumer beliefs and preferences related to these issues is therefore relevant as innovative renewable energy markets have the potential to change conventional consumer purchasing decisions. This paper investigates the beliefs and behaviors of U.S. consumers related to E85 ethanol from corn and cellulosic feedstocks. Four distinct market segments are created so that the ethanol market can be investigated more in-depth. Overall familiarity with ethanol as an alternative fuel is high; however, individual segments vary on beliefs related to corn and cellulosic ethanol, purchasing Flex-Fuel Vehicles, general concern for the environment, and many other factors. In order to successfully market ethanol to a diverse market, the preferences, beliefs and behaviors of these four distinct segments should be taken into account. While environmental concern has waxed and waned over time, issues like as climate change have come to the forefront of both domestic and international discussion and policy. The role of greenhouse gas emissions in contributing to climate change has been acknowledged. As a major source of emissions, transportation fuels are an obvious source of potential reductions in greenhouse gas emissions. This study segments consumers into four distinct market segments and uses a contingent choice method to determine willingness to pay for reductions in greenhouse gas emissions through purchases of E85 ethanol blends. Overall, willingness to pay is estimated at about 0.18 cents per gallon for each percentage in emissions reductions when compared with gasoline containing no ethanol (E0). Willingness to pay for emissions reductions varies in significance and degree across the four market segments. The diversity between the four segments implies that marketing plans should take into account the heterogeneity of consumers and make efforts to account for their varied needs and preferences.

This doctoral thesis contains three essays on the economics of climate change and the electricity sector. The first essay deals with the subject of greenhouse gas (GHG) emissions and economic growth. The second essay addresses the issues of climate change policies, especially the role of the emergent innovative technologies, and the restructuring of the electricity sector. The third essay presents a model of transmission investments in electric power networks. Chapter One studies the impacts of climate change on economic growth in the world economies. The paper contains explicit formalization of the depletion process of exhaustible fossil fuels and the phase of technology substitution. The impacts of climate change on capital flows and welfare across countries are also investigated. The restructuring of the electricity sector is studied in Chapter Two. It also analyzes how climate change policies can benefit from emergent innovative technologies and how emergent innovative technologies can lower GHG emissions. It is shown that the price of electricity is strictly rising before emergent innovative firms with zero GHG emissions enter the market, but strictly declining as the entry begins. In Chapter Three, a model of electricity transmission investments from the perspective of the regulatory approach is formulated. The Mid-West region of Western Australia, a sub-system of the South West Interconnected System is considered. In contrast with most models in the literature that deal only with network deepening, this model deals with both network deepening and network widening. Moreover, unlike the conventional investment models which are static and deal only with the long run, this model is dynamic and focuses on the timing of the infrastructure investments. The paper is a study of an optimal transmission investment program which is part of the optimal investment program for an integrated model in which investments in transmission and investments in generation are made at the same time.

Buildings are a significant energy consumer and are responsible for an increasingly large percent of worldwide greenhouse gas emissions, currently between 30 and 40 percent. Energy efficiency presents unique opportunities for building owners to reduce their environmental footprint and add value through cost savings, tax deductions, and increased market value. An analysis of 183 samples of efficiency measures in seven technology categories found that 74% of efficiency investments had a positive net present value. Building automation system and chiller plant improvements had the highest mean energy and carbon dioxide savings per square foot. Additionally, building automation systems had, on average the highest return on investment, approximately $800 above the cost of implementation per one thousand square feet. Only building envelope modifications had a negative mean return on investment. Building automation system upgrades avoided an average of 350 pounds of CO2e for every dollar spent, reducing a building’s total carbon footprint by as much as 28%. The results suggest that a significant opportunity for cost, energy, and emission savings is available across all technology categories.

This doctoral thesis contains three essays on the economics of climate change and the electricity sector. The first essay deals with the subject of greenhouse gas (GHG) emissions and economic growth. The second essay addresses the issues of climate change policies, especially the role of the emergent innovative technologies, and the restructuring of the electricity sector. The third essay presents a model of transmission investments in electric power networks. Chapter One studies the impacts of climate change on economic growth in the world economies. The paper contains explicit formalization of the depletion process of exhaustible fossil fuels and the phase of technology substitution. The impacts of climate change on capital flows and welfare across countries are also investigated. The restructuring of the electricity sector is studied in Chapter Two. It also analyzes how climate change policies can benefit from emergent innovative technologies and how emergent innovative technologies can lower GHG emissions. It is shown that the price of electricity is strictly rising before emergent innovative firms with zero GHG emissions enter the market, but strictly declining as the entry begins. In Chapter Three, a model of electricity transmission investments from the perspective of the regulatory approach is formulated. The Mid-West region of Western Australia, a sub-system of the South West Interconnected System is considered. In contrast with most models in the literature that deal only with network deepening, this model deals with both network deepening and network widening. Moreover, unlike the conventional investment models which are static and deal only with the long run, this model is dynamic and focuses on the timing of the infrastructure investments. The paper is a study of an optimal transmission investment program which is part of the optimal investment program for an integrated model in which investments in transmission and investments in generation are made at the same time.

This paper examines the informal economy’s greenhouse-gas (GHG) emissions and whether it poses a problem to the effectiveness of international frameworks designed to reduce GHG emissions. With the results of a literature review conducted on the relation between the informal economy and regulations and results on 160 nations’ theoretical informal-economy emissions over time, this paper finds that the informal economy does hinder the ability of governments to manage GHG emissions. This paper then discusses how this aspect of the world’s economy limits the efficacy of international frameworks to reduce GHG emissions. Suggestions are made on how to incorporate this sector into the proposed frameworks. The paper concludes with summarizing the main findings and proposals for further research.

Activity-based travel demand model systems are increasingly being deployed to microsimulate daily activity-travel patterns of individuals. However, a critical dimension that is often missed in these models is that of vehicle type choice. The current dissertation addresses this issue head-on and contributes to the field of transportation planning in three major ways. First, this research develops a comprehensive vehicle micro-simulation framework that incorporates state-of-the-art household vehicle type choice, usage, and evolution models. The novelty of the framework developed is that it accommodates all the dimensions characterizing vehicle fleet/usage decisions, as well as accommodates all dimensions of vehicle transactions (i.e., fleet evolution) over time. The models estimated are multiple discrete-continuous models (vehicle type being the discrete component and vehicle mileage being the continuous component) and spatial discrete choice models that explicitly accommodate for multiple vehicle ownership and spatial interactions among households. More importantly, the vehicle fleet simulator developed in this study can be easily integrated within an activity-based microsimulation framework. Second, the vehicle fleet evolution and composition models developed in this dissertation are used to predict the vehicle fleet characteristics, annual mileage, and the associated fuel consumption and green-house gas (GHG) emissions for future years as a function of the built environment, demographics, fuel and related technology, and policy scenarios. This exercise contributes in substantial ways to the identification of promising strategies to increase the penetration of alternative-fuel vehicles and fuel-efficient vehicles, reduce energy consumption, and reduce greenhouse gas emissions. Lastly, this research captures several complex interactions between vehicle ownership, location, and activity-travel decisions of individuals by estimating 1) a joint tour-based model of tour complexity, passenger accompaniment, vehicle type choice, and tour length, and 2) an integrated model of residential location, work location, vehicle ownership, and commute tour characteristics. The methodology used for estimating these models allows the specification and estimation of multi-dimensional choice model systems covering a wide spectrum of dependent variable types (including multinomial, ordinal, count, and continuous) and may be viewed as a major advance with the potential to lead to redefine the way activity-based travel model systems are structured and implemented. / text

Canada’s emissions are nearly 30 per cent above its Kyoto target. Kathryn Harrison is looking to understand why some countries are leading the way and why others are falling short.

Recently, electric vehicles (EVs) have been gaining attention in passenger transportation due to their greater fuel economy and reduced greenhouse gas (GHG) emissions compared to conventional vehicles (CVs). The amount of GHG emissions reduction from EVs depends on the energy sources used to generate electricity. Wind is a clean, renewable energy source and EVs charged from wind-generated electricity do not produce any emissions. However, wind is variable in nature. This thesis examines the potential impact of EVs on reducing a jurisdiction’s vehicular GHG emissions using locally available wind-electricity. Four methods of charging EVs using wind-electricity are considered, with grid-electricity as a backup, and the overall well-to-wheels GHG emission reductions are discussed. The thesis includes a case study of Summerside. The results show that up to 68% of the EVs’ demands were met with wind-electricity, and Summerside’s vehicular GHG emissions were reduced by between 56% and 73% when compared to CVs.

The quality of the human experience depends on a dramatic change in how we think about economics and, more specifically, about the relationship between human economic activity and the natural world. The continued pursuit of a growth agenda threatens the health and stability of global ecological systems, jeopardizes the wellbeing of many people, and undermines opportunities for future generations. In an era of sustainability challenges, we must measure the impacts of economic activity and use that information toward designing more sustainable human systems. This dissertation supports an ecological economic worldview by extending biophysical based measures to local scale applications to improve understanding of environmental impact at the urban and sub-regional scale. To account for environmental impact, I test two calculation approaches: one to estimate municipal ecological footprint values and one to measure environmental impact at a neighbourhood level. The novel calculation approaches account for environmental impact at finer scales of resolution than has traditionally been applied. I also explore drivers of environmental impact using Halifax Regional Municipality as a case study. I examine the relationship between direct GHG emissions and socio-economic and wellbeing variables using a multivariate model. Those reporting to be married, young, low income, and living in households with more people have correspondingly lower direct GHG emissions than other categories in respective groupings. Respondents with lifestyles that generate higher GHG emissions did not report to be healthier, happier or more connected to their communities, suggesting that individuals can experience similar degrees of wellbeing largely independent of their GHG emissions. I explored whether where we live influences direct GHG emissions. Findings indicate that individuals living in the suburbs generate similar GHG emissions to those living in the inner city, challenging a widely held assumption that living in the inner city is better for sustainability. These results underscore the importance of understanding the spatial distribution of GHG emissions at the sub-regional scale. The research offers new insights to measure and understand environmental impact at the local level toward supporting ecologically informed decision-making.