Energy Transition

To deepen understanding of the relation between economic development and energy demand, this study estimates the Engel curves that relate per-capita energy consumption in major economic sectors to per-capita GDP. Panel data covering up to 123 nations are employed, and measurement problems are treated both in dataset construction and in estimation. Time and country fixed effects are assumed, and flexible forms for income effects are employed. There are substantial differences among sectors in the structure of country, time, and income effects. In particular, the household sector's share of aggregate energy consumption tends to fall with income, the share of transportation tends to rise, and the share of industry follows an inverse-U pattern.

Transportation represents almost 28 percent of the United States’ energy demand. Approximately 95 percent of U.S. transportation utilizes petroleum, the majority of which is imported. With significant domestic conventional gas resources, optimistic projections of unconventional natural gas resources, and the growing international liquefied natural gas (LNG) market, gas prices are expected to remain lower than oil. While natural gas currently provides approximately 24 percent of the United States’ energy consumption, there has been no significant growth in the natural gas vehicle market in the past fifteen years. Natural gas has comparative environmental advantages to gasoline and diesel, with lower CO2 emissions per mega joule of fuel consumption. A natural gas powered vehicle fleet could reduce the country’s fuel costs, dependence on imported fuel, and greenhouse gas emissions. To fully comprehend the future role of natural gas vehicles in the United States, all the major technological and market forces affecting the successful deployment of this vehicle technology must be analyzed interdependently under market and energy policy-regulated scenarios.

I investigate the potential role of natural gas in transportation using a computable general equilibrium (CGE) model of the global economy that is resolved for the US and other major countries and regions. To do so, I add a dedicated compressed natural gas (CNG) vehicle option to the Emissions Prediction and Policy Analysis (EPPA) Model as an option to the conventional internal combustion engine (ICE) vehicle. The model projects changing prices of fuel and other goods over time, given specification of resource availabilities. With the CNG vehicle specification I am able to evaluate the effect of the CNG option on transportation emissions, oil imports, natural gas use, and other economic indicators. I consider different policy scenarios for the future, including the adoption of a targeted emissions cap policy to see how that affects the competitiveness of CNG vehicles.

Several conclusions about the potential role of nature gas vehicles in the United States are drawn from this analysis. First, NG vehicles will reduce household transportation emissions in proportion to their share of the vehicle fleet. Second, stringent emissions policies will stimulate the penetration of natural gas vehicles, but high vehicle costs and infrastructure may hinder their deployment. There is a correlation between increased NG vehicle use and the reduction of oil imports. In the long term, development of cleaner alternative fuels with similar infrastructure to gasoline may hamper CNG vehicle growth.

As policy makers consider strategies to reduce greenhouse gas emissions, they need to understand the available options and the conditions under which these options become economically attractive. This paper explores the economics of carbon capture and sequestration technologies as applied to electric generating plants. The MIT Emissions Prediction and Policy Analysis (EPPA) model, a general equilibrium model of the world economy, is used to model two of the most promising carbon capture and sequestration (CCS) technologies. The CCS technologies are based on a natural gas combined cycle plant and an integrated coal gasification combined cycle plant. Additionally, the role of natural gas combined cycle plants without capture and sequestration is modeled to represent a rapidly growing generation technology. These technologies have been fully specified within the EPPA model by production functions and we simulate how they perform under different policy scenarios. The results illustrate how changing input prices and general equilibrium effects influence technology choices between gas and coal capture plants and other technologies for electricity production. Results reflect the application of the technologies to the United States.

The electricity sector is a major source of carbon dioxide emissions that contribute to global climate change. Over the past decade wind energy has steadily emerged as a potential source for large-scale, low carbon energy. As wind power generation increases around the world, there is increasing interest in the impacts of adding intermittent power to the electricity grid and the potential costs of compensating for the intermittency. The goal of this thesis research is to assess the costs and potential of wind power as a greenhouse gas abatement option for electricity generation. Qualitative and quantitative analysis methods are used to evaluate the challenges involved in integrating intermittent generation into the electricity sector. A computable generation equilibrium model was developed to explicitly account for the impacts of increasing wind penetration on the capacity value given to wind. The model also accounts for the impacts of wind quality and geographic diversity on electricity generation, and the impacts of learning-by-doing on the total cost of production. We notice that the rising costs associated of intermittency will limit the ability of wind to take a large share of the electricity market. As wind penetration increases, a greater cost is imposed on the wind generator in order to compensate for the intermittency impacts, making the total cost from energy from wind more expensive. Because the model explicitly accounts for the impacts of intermittency, the decision to add wind power to the grid is based on the marginal cost of adding additional intermittent sources to the system in addition to the cost of generating wind energy.
(cont.) This model was incorporated into the MIT Emissions Prediction and Policy Analysis model in order to analyze the adoption of wind technology under three policy scenarios. In a business as usual scenario with no wind subsidies or carbon constraints, wind energy generation rises to 0.80 trillion KWh in 2090 and accounts for 9% of the total electricity generation. In a scenario that stabilized greenhouse gases at 550 parts per million, high carbon penalties motivate the entry of 1.16 trillion KWh of wind energy generation in 2055 that accounts for 22% of the total electricity generation. With a production tax credit subsidy for wind generation, wind energy generation increases by average of 12% over the base case scenario during the years the policy was in effect. However, when the subsidy tapers off, wind generation in later periods remains unchanged.

This technical note documents the inventory of non-CO2 greenhouse gas (GHG) and traditional air pollutant emissions for the MIT Emissions Prediction and Policy Analysis model version five (EPPA 5). The non-CO2 GHG species considered include methane (CH4), nitrous oxide (N2O), hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), and sulfur hexafluoride (SF6). Traditional air pollutants include carbon monoxide (CO), sulfur dioxide (SO2), nitrous oxides (NOx), ammonia (NH3), black carbon (BC), organic carbon (OC), and non-methane volatile organic compounds (NMVOCs). In considering non-CO2 GHG data sets, we evaluate bottom-up inventories from the Emissions Database for Global Atmospheric Research version 4.1 (EDGAR v4.1), the “U.S. Environmental Protection Agency Global Non-CO2 Anthropogenic Emissions: 1990-2020” report (EPA 2006), and a recent inventory from the Global Trade Analysis Project (GTAP v7). For traditional air pollutants we consider EDGAR v4.1 and EDGAR-HTAP v1. Since EPPA 5 is also used in connection with the MIT Integrated Global System Model (IGSM) to study environmental effects, good agreement with measured GHG concentrations is crucial and we compare bottom-up and top-down estimates to gauge for consistency. We conclude that the EDGAR v4.1 inventory is best suited for benchmarking non-CO2 GHGs in EPPA 5 due to good disaggregation between economic sectors and species, and because it provides the closest fit with top-down estimates.

The way we power our homes and cars and factories is one of the most important choices our society faces. Perhaps it’s the push of climate change, air pollution, resource depletion, and national security. Or maybe it’s the pull of new technologies and newfound energy supplies that may be cheap and clean. Either way, most experts expect that we are heading toward a virtual revolution in the power and energy industries over the next few decades.

But whether we can revolutionize our energy infrastructure—and how, exactly, we would do it—is not simply a question of technology. Economics will play a deciding role in what unfolds. For alternative technologies to be chosen among the mix of energy sources, they must be able to compete in the energy market. The future costs of energy technologies and the ever-changing price of conventional energy sources will determine the success of alternatives over conventional, fossil fuel-powered technologies.

Efforts to reduce carbon emissions significantly will require considerable improvements in energy intensity, the ratio of energy consumption to economic activity. Improvements in energy intensity over the past thirty years suggest great possibilities for energy conservation: current annual energy consumption avoided due to declines in energy intensity since 1970 substantially exceed current annual domestic energy supply.
    While historic improvements in energy intensity suggest great scope for energy conservation in the future, I argue that estimates of avoided energy costs due to energy conservation are overly optimistic. Avoided costs are likely to be significantly higher than estimates from recent energy technology studies suggest once behavioral responses are taken into account.
    I then analyze a data set on energy intensity in the United States at the state level between 1970 and 2001 to disentangle the key elements of energy efficiency and economic activity that drive changes in energy intensity. Rising per capita income plays an important role in lower energy intensity. Higher energy prices also are important. Price and income predominantly influence intensity through changes in energy efficiency rather than through changes in economic activity.

We describe several scenarios for economic development and energy use in East Asia based on the MIT Emissions Prediction and Policy Analysis (EPPA) model, a computable general equilibrium model of the world economy. Historic indicators for Asian economic growth, energy use, and energy intensity are discussed. In the Baseline scenario, energy use in East Asia is projected to increase from around 120 EJ in 2005 to around 220 EJ in 2025. Alternative scenarios were developed to consider: (1) How fast might energy demand grow in East Asia and how does it depend on key uncertainties? (2) Do rising prices for energy affect growth in the region? (3) Would growth in East Asia have a substantial effect on world energy markets? (4) Would development of regional gas markets have substantial effects on energy use in the region and on gas markets in other regions? Briefly, we find that with more rapid economic growth, demand in East Asia could reach 430 EJ by 2025, almost twice the level in the Baseline; rising energy prices place a drag on growth of countries in the region of 0.2 to 0.6% per year; world crude oil markets could be substantially affected by demand growth in the region, with the price effect being as much as $25 per barrel in 2025; and development of regional gas markets could expand gas use in East Asia while leading to higher gas prices in Europe.

(Document available by request)

We describe several scenarios for economic development and energy use in East Asia based on the MIT Emissions Prediction and Policy Analysis (EPPA) model, a computable general equilibrium model of the world economy. Historic indicators for Asian economic growth, energy use, and energy intensity are discussed. In the Baseline scenario, energy use in East Asia is projected to increase from around 120 EJ in 2005 to around 220 EJ in 2025. Alternative scenarios were developed to consider: (1) How fast might energy demand grow in East Asia and how does it depend on key uncertainties? (2) Do rising prices for energy affect growth in the region? (3) Would growth in East Asia have a substantial effect on world energy markets? (4) Would development of regional gas markets have substantial effects on energy use in the region and on gas markets in other regions? Briefly, we find that with more rapid economic growth, demand in East Asia could reach 430 EJ by 2025, almost twice the level in the Baseline; rising energy prices place a drag on growth of countries in the region of 0.2 to 0.6% per year; world crude oil markets could be substantially affected by demand growth in the region, with the price effect being as much as $25 per barrel in 2025; and development of regional gas markets could expand gas use in East Asia while leading to higher gas prices in Europe.

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