Economic Analysis
The development of coal-based energy conversion plants at the scale envisioned in this report will increase U.S. domestic energy supply by more than 10% and lower domestic energy prices by more than 33% from where they would be without coal conversion. Higher domestic energy production, lower energy prices, and the economic stimulus from coal British thermal units (Btu) energy conversion plant construction contribute to cumulative gains in real gross domestic product (GDP) of more than $3 trillion in discounted present value terms. Further, if some of the CO2 from these plants is used to enhance oil recovery, domestic oil production could increase more than 3 million barrels per day (bbl/d). This additional energy production would expand the cumulative discounted GDP gains to over $4 trillion. This section describes the methods used to obtain these estimates.
Methodological Overview
Estimating the economic impacts from coal Btu energy conversion may at first seem a daunting task. The breadth of the conversion scenarios discussed above affect all segments of the energy industry, from natural gas, crude oil and petroleum, and electricity. Representation of how equilibrium energy prices and quantities adjust in each of these markets and their interactions in response to coal-based energy manufacturing is impossible given the resources and timeframe for this project. As a result, an aggregate energy supply and demand framework is adopted for this study.
This approach greatly simplifies the analysis, distilling the effects down to a few key parameters, such as:
- the price elasticity of aggregate energy demand;
- the elasticity of gross domestic product to energy price changes; and
- the output multipliers associated with energy output and plant construction.
This study does not estimate these parameters from primary data but instead uses estimates that appear in the economic literature.
Given the simple approach employed in this study, the scenarios discussed are aggregated into one key variable: the quantity of Btus delivered to energy consumers. This involves making assumptions about the size of Btu conversion plants and the thermal efficiencies of the conversion processes.
Another key assumption involves timing. The actual adoption of these technologies in the marketplace depends upon how energy prices and energy conversion plant costs evolve over time. We avoid making assumptions about such specific factors and instead use a smooth extrapolation technique that attempts to model a process of steady and accelerating adoption of Btu energy conversion technologies over to the year 2025.
Scenario Development
The first step in the economic analysis is to establish the goal for the production of Btu from the coal conversion technologies discussed above. These targets are presented in Figure 4.1. The first four scenarios listed are driven by an assumed, targeted amount of coal production to the year 2025. In essence, these scenarios assume that the additional units of energy supply from these coal technologies will be consumed by the energy consumers.
The scenario for coal to product ethanol is driven by a target of 10% of the vehicle fleet supplied from ethanol. Coal is used as a fuel to convert biomass into ethanol. This scenario is not included in the economic analysis below because the net energy contribution from coal is not clear and because it is a relatively minor part of the overall Btu energy conversion vision presented above.
Time Path of Plant Construction
The next step in the analysis is to determine a path for annual production of Btus from coal to reach these targets. First, the number of plants is determined by taking the total amount of coal in the first four scenarios and dividing by an assumed 6 million tons of annual coal consumption per Btu conversion plant. This coal consumption amount per plant implies roughly 212 coal Btu energy conversion plants in the year 2025.
Given this target number of plants, a plant construction schedule is then developed. For this, we assume construction of two plants beginning in the year 2007. In subsequent years, an additional 1.5 plants on average are started. The next key assumption is that it takes four years to build these plants. This means, for example, that the two plants begun in 2007 do not begin producing Btus until 2010. The plants started in 2008 then go into production in 2011 and augment the production from the plants started in the previous year. Defining Nt as the number of Btu conversion plants operating in year t and NCt as the number of plants under construction in year t, the number of plants operating in any given year after 2010 is given by the following formula:
The incremental Btus of marketable energy product from coal energy conversion in quadrillion Btus, Qt , is obtained by the following equation:
where CE is the average conversion efficiency, which is calculated as a weighted average of the individual thermal efficiencies presented with the weights computed from the coal quantities in Figure 4.1. These thermal efficiencies and weights are presented in Figure 4.2:
The number of new construction starts and plants operating each year are presented in Figure 4.3. Notice that plant starts cease in 2022. Incremental coal use in million tons and in quadrillion Btus appears in columns four and five of Figure 4.3. Total energy output from coal conversion in 2025 amounts to 12.7 quadrillion Btus. This energy production is achieved by the gradual ramping up of the number of operating coal conversion plants that results from the construction of these plants over time and the assumed four-year construction period. These plants include electric power generation facilities, coal methane production plants, coal-to-liquids plants and plants that produce hydrogen. In reality, Btu coal energy conversion plants will produce multiple product streams, with most producing electric power along with either methane or, most likely, a slate of liquid products, including methanol, gasoline, diesel fuel and jet fuel. Delineating these plant configurations with a greater degree of specificity is a topic for additional research.
To assess the margin of error from our aggregate approach, a more detailed analysis was undertaken that allows the amount of coal consumed per plant and the implied plant size to differ by each coal conversion scenario. Figure 4.4 presents a more detailed set of calculations. For each of the scenarios, coal use, output and capital cost per plant are presented. The estimated number of plants is higher because the scale of the hydrogen plants is smaller than the plant size assumed above. Nevertheless, the total amount of energy produced is very close, within 5%, of the estimate presented above. Hence, the aggregate methodology adopted here provides a reasonable estimate of the total amount of energy production from coal Btu conversion plants.
Also included in Figure 4.4 is the coal to produce ethanol scenario. This scenario involves 40 million tons of coal consumed in 383 plants that in total will produce about 10% of U.S. gasoline consumption in 2030. The hydrogen scenario would supply between 40 and 50 million fuel cell vehicles, which falls between 10 to 20% of transportation needs.
Capital Outlays and Direct Employment Impacts
Significant capital expenditures will be required to build these plants. Construction and operation also will generate employment gains. The time path for these direct impacts is calibrated to the time path of plant construction discussed in the previous section.
Annual capital expenditures are estimated by multiplying the stock of plants under construction by an average annual capital outlay, which is computed as a weighted average of capital costs for the four technologies. Coal-to-gas and coal-to-hydrogen plants are assumed to cost $1 billion, again assuming 6 million tons per year of coal consumption. The coal-to-liquids plant cost is assumed to be $3.6 billion for this plant size. Coal-to-electricity plants are assumed to cost $2.25 billion. Given a four-year plant life, the average annual capital outlay per plant is $590 million.
Construction jobs are estimated assuming 976 jobs per plant year based upon a study of the economic impact analysis of the Peabody Energy Park in Illinois. The operation of the mines and plants generates 414 jobs per plant per year. Total direct employment is determined by multiplying each of these estimates by the number of plants under construction and operating, respectively. The total number of plants under construction, annual capital outlays and employment are presented in Figure 4.5.
Impacts on Energy Markets
The additional energy production from coal conversion will lower equilibrium energy prices. Assuming energy producers in the United States are operating at full production, the extent of the price reduction from additional energy production from coal would depend upon the slope of the demand curve as illustrated in Figure 4.6.
Economists characterize demand-and-supply relationships using elasticities. An own-price elasticity of demand is defined as the percentage change in quantity for a given percentage change in price, and its solution for the percentage change in price is as follows:
The annual changes in quantities, which are the incremental supplies of energy products from coal conversion plants, are presented in Figure 4.7. To compute the percentage change in quantity, we use the long-term forecast of aggregate primary energy consumption produced by the EIA. Own-price elasticities of energy demand vary considerably by product depending upon the degree of substitution possibilities and between the short-run— when energy-consuming capital is for the most part fixed—and the long-run, when investment allows much greater flexibility to respond to changing relative energy prices. For example, the short-run own price elasticity of demand for gasoline is about -0.2, while the long-run elasticity is at least -0.7. For this study, we adopt an intermediate value of -0.3, which can be interpreted as an intermediate-run elasticity.
The resulting energy price reductions from coal conversion appear in Figure 4.7. Notice that by the end of the forecast horizon, aggregate energy prices would be more than 30% lower than the EIA base case forecast. This implies lower prices for electricity, natural gas, petroleum products and many other energy products. This is significant given that coal conversion augments the nation’s energy supply by more than 10% in 2025.
A smaller own-price elasticity of demand in absolute terms or a steeper demand schedule in Figure 4.7 would imply even sharper reductions in energy prices from coal energy conversion. Likewise, a larger absolute value on the own-price elasticity would imply a smaller impact on energy prices. Our elasticity of -0.3 can be viewed as a reasonable compromise between these two extremes.
Macroeconomics Impacts
These energy price reductions act like a tax cut for the economy, reducing the outflows of funds from energy consumers to foreign energy producers. In addition, the supply-side push from additional domestic energy production will directly increase the nation’s economic output. Finally, the plant construction will stimulate the economy at local, regional, and national levels.
To estimate these impacts, specifically the changes in Gross Domestic Product (GDP) resulting from coal conversion, published estimates of output multipliers are used. In this study, we use an output multiplier of 2.6 reported by Shields, et al. in 1996 which means that total output increases $2.60 for every dollar spent on coal energy conversion plant construction and every dollar generated from the resulting energy output. The elasticity of GDP with respect to energy prices is -0.048, which is the average of the range reported by S.A. Brown and M.K. Yucel in 1999, based upon an Energy Modeling Forum study by B.G. Hickman, et al. in 1987.1 Estimates of these three avenues of impacts of GDP are presented below in Figure 4.8. Total real 2004 dollar GDP gains by the year 2025 exceed $600 billion. The discounted present value of these gains, assuming a real discount of 3%, exceeds $3 trillion.
1 An earlier version of this study used the GDP electricity price elasticity of -0.14 used by A. Rose and B. Yang, which increases the present value of GDP gains to over $6 trillion. This elasticity apparently came from a study completed over 20 years ago by National Economic Research Associates. We were unable to verify the methods used to obtain this estimate and instead relied upon published estimates from the peer-reviewed literature.
The employment multiplier used to estimate the indirect and induced job gains from direct employment in construction and operation of energy conversions plants is 3.23, which is also drawn from the 1996 study by Shields, et al. For the response of employment to energy prices, we use the study by S.A. Brown and J.K. Hill from 1988 that surveyed the major economic forecasting services and found an elasticity between national employment and oil prices of -0.0193.
The employment impacts of the coal energy conversion scenario considered here are also significant. By the end of the forecast period, employment is more than 1.4 million higher than the base case (see Figure 4.9). Employment gains arise primarily from the impacts of lower energy prices. In this case, service sector employment is stimulated by the higher level of discretionary income available to consumers made possible by the lower energy prices from the additional production from the coal energy conversion complex.
These estimates should be considered only order of magnitude estimates given the wide range of uncertainty surrounding the coal energy conversion technology. In addition, such large-scale coal utilization could increase equilibrium prices for basic materials and services used to produce Btus from coal. To estimate these impacts, a general equilibrium model of energy markets and the economy is needed. Indeed, another possible area to explore is the impact of additional coal production on world energy markets. In fact, our analysis implicitly assumes that the coal energy conversion would affect world energy prices. Analysis of these economic relationships awaits further research.
Impacts of Enhanced Oil Recovery
The adoption of large-scale coal conversion would generate significant amounts of carbon dioxide (CO2) that could be either sequestered or used to enhance oil production. Enhanced oil recovery using CO2 already produces more than 200,000 barrels of oil per day, primarily in west Texas, which is supplied with CO2 via pipeline. Given the large pipeline network that overlays oil- and coal-producing regions, there is considerable potential to find low cost methods to deliver this CO2 to enhance oil production.
To estimate the enhanced oil production from coal conversion, we assume that 14,844 supercritical fluids (scf) CO2 is produced per ton of coal consumed, 187.5 barrels are produced per million scf of CO2 injected, and 30% of the total CO2 is utilized to enhance oil production. These assumptions yield additional oil production of nearly 3 million barrels per day. As a result, energy prices are nearly 50% lower than the EIA base case. The present value of cumulative GDP gains increases to more than $4 trillion. This rough analysis suggests that coal energy conversion coupled with CO2 recovery and enhanced oil recovery could yield very substantial economic benefits.
The 10 largest coal producers and exporters in the Indonesia:
- Bumi Resouces
- Adaro Energy
- Indo Tambangraya Megah
- Berau Coal
- Bukit Asam
- Baramulti Sukses Sarana
- Harum Energy
- Mitrabara Adiperdana
- Samindo Resources
- United Tractors
Source: The National Coal Council
