Climate Policy and the Long-Term Evolution of the U.S. Buildings Sector

Transcription

1 Climate Policy and the Long-Term Evolution of the U.S. Buildings Sector Page Kyle *, Leon Clarke*, Fang Rong**, and Steven J. Smith* Buildings are the dominant driver of daily and seasonal electric load cycles, and account for 4 percent of U.S. final energy use. They account for roughly 1 percent of direct U.S. CO 2 emissions and roughly 4 percent once indirect emissions from electricity generation are included. This paper explores the possible evolution of this sector over the coming century, its potential role in climate action and response to climate policies, and the potential benefits of advances in building technologies for addressing climate change. The paper presents a set of scenarios based on a detailed, service-based model of the U.S. buildings sector that is embedded within a long-term, global, integrated assessment model, MiniCAM. Eight scenarios are created in total, combining two sets of assumptions regarding U.S. building service demand growth, two sets of assumptions regarding the improvements in building energy technologies, and two assumptions regarding long-term U.S. climate action a no-climateaction assumption and an assumption of market-based policies to reduce U.S. CO 2 emissions consistent with a 45 ppmv global target. Through these eight scenarios, the paper comments on the implications of continued growth in building service demands, the ability of efficiency measures to reduce emissions, and the strong link between decarbonization of electricity generation and building sector emissions. 1. Introduction The buildings sector presently accounts for about 4% of final energy use in the United States, and, according to many experts, is expected to grow The Energy Journal, Vol. 31, No. 2. Copyright 21 by the IAEE. All rights reserved. * Joint Global Change Research Institute, Pacific Northwest National Laboratory, 5825 University Research Court, College Park, MD 274. ** School of Public Policy and Management, Tsinghua University, Beijing, China. Corresponding author. pkyle@pnl.gov. Tel:

2 146 / The Energy Journal substantially in upcoming decades (EIA, 27; EIA, 28). 1 Buildings directly account for about 1% of CO 2 emissions from primary fossil fuel combustion in the U.S., and they account for nearly 4% of the national total if electricity-related emissions are also considered (EIA, 28). The services provided by buildings, such as warm homes in the winter, cooked food, and home entertainment, are supplied by a wide range of technologies, and many experts believe that there are a number of low-cost opportunities to deploy more advanced building technologies in the short term to reduce energy consumption and CO 2 emissions. This topic is currently receiving substantial attention from researchers and policy-makers (Levine et al., 27; McKinsey Global Institute, 27). However, building energy demands are both a near-term and a long-term concern with respect to climate change. Although near-term reductions are called for to begin action on climate change, the dramatic emissions reductions required to ultimately stabilize greenhouse gas concentrations will take place well beyond the next several decades, and they will continue in perpetuity (Clarke et al., 27). Hence, the long-term evolution of the buildings sector and building technologies is an important strategic concern. In the long term, CO 2 emissions from the buildings sector will depend on many unknown factors, including technology, the expansion of the buildings sector, the types of services provided by buildings, the types of fuels consumed to provide building services, and emissions from fuel production and distribution. Insofar as the historical evolution of the buildings sector provides insights into the future, four aspects are of particular interest with respect to energy demands and climate change. First, per-capita residential and commercial floorspace have each been increasing in recent decades. From 1975 to 25, per-capita floorspace increased from 55 to 7 square meters per person in the residential sector, and from 2 to 26 square meters per person in the commercial sector. Combined with population growth, this amounted to an 8% expansion in total floorspace between 1975 and 25. All else equal, growth in floorspace is associated with increases in building service demands and energy consumption (e.g. Battles, 24; Wilson and Boehland, 25; Gerencher, 26). A range of social, cultural, economic, political, and demographic factors have contributed to the increase in per-capita floorspace demand, such as increased per-capita income, emergence and growth of low-density suburbs, and consumer preferences. Future floorspace demand will depend on many of the same factors. Second, the nature and composition of building service demands have changed. For example, office equipment and other miscellaneous electronics provide services that were either not available or not widespread several decades ago, but are currently large consumers of energy in both the residential and commercial sectors. The amount of energy that is consumed to heat one unit 1. Total final energy, also called total delivered energy, consists of the energy value of the sum of all fuels consumed by end users. The lower heating value is used throughout this study. This measure does not include energy transformation losses in primary fuel extraction (e.g. mining) or secondary fuel production (e.g. electricity generation, fuel refining).

3 Climate Policy and the Long-Term Evolution of the U.S. Buildings Sector / 147 of residential floorspace has declined by about 5% since 1978 (EIA, 1979; EIA, 27) and air conditioning energy consumed per unit of floorspace has increased by 45% over the same time period (EIA, 1979; EIA, 27). In addition to improvements in the efficiency of heating technologies, this shift has been driven by shifts in new home construction towards warmer climate zones (EIA, 21), a general increase in the use of air conditioning across all climate zones, and increased internal gain energy from lights and other operating equipment. Related to these changes in building services, the third salient aspect of the historical evolution of the buildings sector is that electricity is supplying an increasing share of total final energy consumption by buildings. Electricity became the dominant fuel consumed by the commercial sector in the early 199 s (EIA, 28), and the same is expected to happen in the residential sector in the upcoming decade (EIA, 27). Electrification is of particular interest for the present study not only because electricity generation accounts for the majority of the energy-related CO 2 emissions from the buildings sector, but because the emissions intensity of electricity generation is itself variable, and heavily influenced by future climate policies (Clarke et al., 28a; Richels and Blanford, 28). The CO 2 emissions intensity of electric generation is the fourth aspect of historical CO 2 emissions from the buildings sector that will play a role in future emissions. Between 198 and 26, the average emissions intensity of electricity generation in the U.S. dropped from 186 kg CO 2 per GJ of electricity to 16 kg CO 2 per GJ (EIA, 28). This aggregate measure reflects a number of developments; for instance, the share of electricity produced from natural gas and nuclear power, two relatively low-carbon energy sources, have both increased. Together they accounted for 26% of electricity generation in 198, and 38% in 26 (IEA, 27). Conversely, oil, a more carbon-intensive fuel source for electricity, dropped from 11% to 3% over the same time period (IEA 27). In addition to changes in the fuel mix, there have been efficiency improvements owing to capital stock turnover and improvements in electricity generation technologies. Much of the natural gas-fired capacity built in the last two decades has consisted of combined cycle plants, which have higher average fuel efficiency and therefore lower carbon intensity than conventional gas combustion turbines. As policy makers and technology planners grapple with strategies to reduce CO 2 emissions over the coming century, uncertainties about these forces and their interactions loom large. How effectively and deeply will advanced building technologies reduce emissions? Can deployment of these technologies themselves lead to the requisite emissions reductions? What sorts of reductions in building services will be required in the long-term to address climate change? Will electrification continue, and what will that imply for the character of the response of the buildings sector to the sorts of CO 2 prices that will be required in the long-term to address climate change? Are there technologies that can speed electrification? To what degree can the development and deployment of advanced building technologies reduce the economic burden of emissions reductions?

4 148 / The Energy Journal Finally, how important is the rate of floorspace growth in determining the difficulty of meeting climate goals? In order to assess these questions, the present study uses a model of the U.S. buildings sector nested in MiniCAM, a global, integrated assessment model of energy, agriculture, greenhouse gas concentrations, and climate change. Integrated assessment models have been used to explore the socioeconomic and technological drivers of CO 2 emissions and the policies for constraining these emissions from a long-term, global perspective (for reviews see Nakicenovic and Swart, 2; Clarke et al., 27). They are especially useful for exploring climate policies from a global, long-term perspective and for understanding feedbacks between different components in the systems represented. Detailed exploration of the buildings sector in an integrated assessment framework is itself a methodological advance. Integrated assessment models have historically tended to focus detail on the supply side of the energy sector considering, for example, fuel competition in electricity generation or liquid fuel production while treating the demand for energy in aggregate fashion. In this study, a detailed representation of the U.S. buildings sector is used, in order to explicitly address how the long-term evolution of the buildings sector the demand drivers, the technologies that supply buildings services, and the fuels consumed interacts with the remainder of the energy system, both with and without a policy to stabilize atmospheric CO 2 concentrations. The study presents eight scenarios, combining two sets of assumptions regarding U.S. building service demand growth, two sets of assumptions regarding the improvements in building energy technologies, and two assumptions regarding long-term U.S. climate action a no-action assumption and an assumption of a market-based policy to reduce U.S. CO 2 emissions consistent with a 45 ppmv global target. The study design and scenario assumptions are detailed in the following section. Section 3 explores the results of the analysis, and Section 4 provides several concluding thoughts. 2. Study Design 2.1 MiniCAM Overview This analysis is conducted using MiniCAM (Edmonds et al., 24), as implemented within the Object-oriented Energy, Climate, and Technology Systems framework (O bj ECTS; Kim et al., 26). MiniCAM has been used in a wide range of scenario analysis and technology studies (e.g. Nakicenovic et al., 2; Clarke et al., 27; Clarke et al., 28a). MiniCAM combines partialequilibrium economic models of the global energy system (Edmonds and Reilly, 1985; Edmonds et al. 24) and global land use (Sands and Leimbach, 23), with a suite of coupled gas-cycle, climate, and ice-melt models, integrated in the Model for the Assessment of Greenhouse-Gas Induced Climate Change (MAGICC, Wigley and Raper, 22). MiniCAM is considered an integrated

5 Climate Policy and the Long-Term Evolution of the U.S. Buildings Sector / 149 assessment model because it combines representations of emissions-producing sectors (e.g. energy and agriculture) with a model of the Earth system, allowing for analysis from drivers of emissions all the way through to future greenhouse gas concentrations, radiative forcing, and temperature change. Future demands in MiniCAM are generally linked to population growth, labor force participation rates, and labor productivity, all of which are exogenous inputs. MiniCAM, as used in this study, has 14 regions, one of which is the United States. Model parameters are calibrated to 199 and 25 historical data, and the model calculates equilibria in all markets in 15-year time periods to 295. The model is not forward-looking; investment decisions in any single time period are not based on future prices of energy, for example. MiniCAM is used to examine long-term, large-scale changes in global and regional energy systems. Detailed model components, such as the buildings module described here, are designed to allow analysis of long-term future development within an integrated framework that provides consistent, endogenously determined supplies, demands, and prices in energy, agricultural, and, where applicable, greenhouse gas emissions markets. 2.2 Overview of the U.S. Buildings Module The U.S. buildings sector module, updated from Rong et al. (27), is shown schematically in Figure 1, and consists of a residential and a commercial sector. Each sector is characterized by the total floorspace in the sector along with a representative set of building characteristics such as building shell efficiency. Each sector demands a range of building services, which are supplied by competing technologies that consume any of the following fuels: natural gas, electricity, liquid fuels, or biomass. The energy required to meet a given level of service demand depends on the efficiencies of the technologies chosen to serve the demand. The remainder of this section discusses the buildings module, working from left to right in Figure 1, addressing floorspace, service demands, technology choice, and energy consumption Floorspace Floorspace growth is especially important for future energy consumption and emissions from the buildings sector, and it is one of the primary drivers of building service demands. However, it is difficult to model how the future demand for floorspace might change over time, as it will depend on a range of non-economic factors such as consumer preferences, the density of future development (and consequent effects on prices of buildings and real estate), and the climatic distribution of future demographic shifts. Hence, rather than provide a structural analysis of possible floorspace evolution in this paper, we have chosen instead to explore the implications of floorspace growth using two exogenous

6 15 / The Energy Journal Figure 1. Schematic of the U.S. Buildings Sector in MiniCAM scenarios of floorspace evolution. The two floorspace scenarios will be discussed in Section Service Demands The building service demands represented in MiniCAM are shown in Figure 1. Residential and commercial buildings tend to demand similar types of services; each sector demands space heating, space cooling, lighting, and water heating. In the residential sector, appliances consist of refrigerators, freezers, clothes washers, clothes dryers, stoves, and dishwashers. The residential other services consist of many disparate sources; the largest energy users are currently televisions and set top boxes, and home office equipment (TIAX, 26). The commercial other demands consist largely of ventilation, cooking, refrigeration, distribution transformers, and water treatment and pumping (EIA, 27; TIAX, 26). In MiniCAM, building service demand levels are driven by floorspace. The formula for building service demands per unit of floorspace (with the exception of heating and cooling; see below) is as follows: d i,t = φ i,t s i P i,t bi (1) In Equation (1), d i,t is the demand for the service i per unit of floorspace in time period t, φ i is an exogenous service expansion parameter that represents 2. It is important to note that floorspace demand in MiniCAM does respond to building energy service prices. However, because energy costs only account for a small portion of total buildings costs, this effect is relatively small and is not discussed further in this study.

7 Climate Policy and the Long-Term Evolution of the U.S. Buildings Sector / 151 non-price-based growth of the service per unit of floorspace, and s i is a calibration coefficient. Exogenous service growth may be assumed for services whose future demand growth per unit of floorspace is expected to grow with income, such as home entertainment and office equipment. P i is the average price of delivering the service, weighted between all technologies providing the service, and b i is the price elasticity of the demand for the service. The price term stands for the price of the service, not the prices of the input fuels. This means that the price elasticity is a service price elasticity, to be distinguished from energy price elasticities. 3 Service prices include capital and operating costs in addition to energy costs, all represented in cost per unit of service output. The formulations for heating and cooling demands are more complex in order to account for the interactions of internal gains, building shell characteristics, and climate. Heating and cooling demands per unit of floorspace in both the residential and commercial sectors are based on the following formulations: d H,t = s H φ H,t u t a HDD t P H,t b H G (2) d C,t = s C φ C,t u t a CDD t P C,t b C + G (3) In these equations, u represents the shell efficiency (an aggregate indicator of average thermal conductivity) of the building, a is building shell area per square foot of floorspace, HDD and CDD are heating degree days and cooling degree days, and G represents the internal gains from other equipment operating within the building shell. Internal gain energy is only applied to heating and cooling demands during the fraction of the year during which heating and cooling services are in operation. An exogenous portion of energy consumption that contributes to internal gains is assigned to each building technology. Because heating and cooling service demands are dependent on heating and cooling degree days, the model can feasibly assess climate-related feedbacks on buildings. However, this feature is not exercised in this study Technology and Technology Choice Most services in the buildings sector can be provided by several competing representative technologies, listed in Table A-1 and Table A-2. Technologies are discrete; in any time period, each has a single average stock efficiency and a single non-energy cost that consists of the sum of levelized capital and operating costs, expressed per unit of output. Building technologies are not vintaged; 3. Empirical analyses have focused on fuel price elasticities (see, for example, Dahl 1993). Service prices include capital and other costs in addition to energy costs. On this basis, service price elasticities should be higher than energy price elasticities. On the other hand, long-run fuel-price elasticities include fuel and technology changes over time that will lead to larger changes in energy demand than in service demand. All other things being equal, this would imply that long-run fuel-price elasticities should be larger than long-run service-price elasticities. Short-term fuel-price elasticity numbers should eliminate these fuel and technology changes.

8 152 / The Energy Journal while base year fuel and technology preferences are carried forward to future periods according to calibration parameters, there is nothing preventing stock turnover between any two 15-year time periods. Future technology capital costs and efficiencies are scenario variables, which can be altered to model different futures of technology evolution. The efficiency of a technology in the buildings sector determines its energy requirements (and therefore its energy costs) per unit of service output, allowing the total cost of delivering a service to be computed per unit of output. This total service cost is used as the basis for technology competition in MiniCAM. All models with multiple discrete technologies must have a method to allocate market share among the options. For this purpose, MiniCAM uses a logit formulation based on the service costs of the competing technologies (Clarke and Edmonds, 1993; McFadden, 1974; McFadden, 1981). The logit approach posits that every market includes a range of different suppliers and purchasers, and each supplier and purchaser may have different needs and may experience different local prices. Therefore, not all purchasers will choose the same technology just because the average price of that technology is lower than the average price of the competing technologies. The logit approach allocates market shares based on prices, but ensures that higher-priced goods can gain some share of the market. Because technology options in MiniCAM are discrete, consumers can choose between different technologies, but consumer choices do not change the characteristics of the technologies themselves. For example, when the price of electricity increases through a price on CO 2 emissions, buildings sector consumers may switch toward solid state lighting from fluorescent or incandescent lighting, but they may not use more efficient versions of any of these technologies and thereby increase the stock average efficiency of the technology. This means that the efficiency responses to changing prices are more muted in the current version of the model than they might be in reality Base Year Model Inputs and Calibration Energy consumption by fuel by the buildings sector in 199 and 25 is from the Annual Energy Review (EIA, 28) and is assigned to building services according to the Annual Energy Outlook (EIA, 1996; EIA, 27). The fraction of energy consumption that is assumed to be released as internal gain energy is shown by end-use service in Table A-3, as is the fraction of the year during which this energy is either added to cooling demands or subtracted from heating demands. Base year efficiencies and non-energy costs of each technology in the buildings module are shown in Table A-1 and Table A-2. Efficiencies of equipment for space heating, space cooling, water heating, and residential appliances are based on EIA (27) and National Energy Modeling Systems stock models (U.S. DOE, 24). Incandescent and fluorescent lighting efficiency is based on NCI (22), and solid-state lighting efficiency is based on NCI (26). Office equipment, appliances, and other efficiencies are indexed to 25. Non-energy costs for

9 Climate Policy and the Long-Term Evolution of the U.S. Buildings Sector / 153 each building service technology are calculated from capital and operating costs, levelized over the expected lifetime of the equipment assuming a 1% discount rate, and divided by the expected output to generate an estimate of cost per unit of service output. Costs, capacities, and expected equipment lifetimes for heating, cooling, and water heating technologies are from NCI (24). Expected output for a given technology is calculated as the energy consumption by all units times the stock average equipment efficiency, divided by the number of units in operation (EIA, 27). 2.3 The Electric Power Sector Because of the importance of electricity generation to greenhouse gas emissions from U.S. buildings sector energy use, this section briefly outlines the representation of the electric power sector in MiniCAM, common to all scenarios in the present study (see Clarke et al. 28a for more detailed documentation). Electricity generation technologies are assumed to be long-lived (between 3 and 6 years), so in any future time period a certain portion of the electricity demand will be supplied by power plants built in previous time periods. The remainder is supplied by new investment. As with technologies in the buildings sector, the market share for this new investment is allocated among competing electric sector technologies using a two-level nested logit choice model, with specific technologies (e.g. conventional pulverized coal power plants and integrated gasification combined cycle coal power plants) nested within fuel types (e.g. coal, gas). The electric power sector has nine fuel types: coal, gas, oil, biomass, hydroelectricity, nuclear power, solar, wind, and geothermal. Electric sector technologies compete according to costs per unit of electricity produced, which are equal to the sum of fuel costs, non-fuel costs, and any other cost penalties for intermittency or CO 2 emissions. Fuel costs are equal to the endogenous market equilibrium price of the given input fuel multiplied by its exogenous input-output coefficient (the number of units of fuel required to produce one unit of electricity). Equilibrium fuel prices are calculated based on exogenous regional and global supply curves, combined with all other fuel demands by regional and global markets. Non-fuel costs consist of the sum of levelized capital and operations and maintenance costs, and are exogenous. Costs of intermittent renewable technologies also include additional backup costs, which are endogenous, and increase as a function of the renewable share of total electric system capacity. Finally, in scenarios in which CO 2 emissions are priced, electric generation costs also include the emissions costs, equal to the CO 2 emissions intensity of the technology multiplied by the CO 2 price. 2.4 Overview of the Scenarios The scenarios analyzed in this study, presented in Table 1, consist of eight different futures of building technology improvement, building service demand growth, and climate policy. Many model assumptions are common between all

10 154 / The Energy Journal scenarios, such as the socioeconomic demand drivers or features of the energy supply system. These assumptions are briefly summarized; more comprehensive documentation can be found in Clarke et al. (28a). Table 1. Scenarios of Building Technology Levels, Building Service Demand Levels, and Climate Policy Name Technology demand Policy Ref-high Reference High None Adv-high Advanced High None Ref-low Reference Low None Adv-low Advanced Low None Ref-high-45 Reference High 45 Adv-high-45 Advanced High 45 Ref-low-45 Reference Low 45 Adv-low-45 Advanced Low General Assumptions Population and GDP are the ultimate drivers of future service demands, energy consumption, and CO 2 emissions in MiniCAM. Annual U.S. labor productivity growth is assumed to remain constant at 1.5 percent through the end of the century, and per-capita economic output in 295 is roughly three times that of today (see Figure 2). The U.S. population follows Census projections through 25 (U.S. Census Bureau, 24), and is assumed to grow through the end of the century, as declining fertility rates are balanced by continued immigration (see Figure 2). There are a number of future energy supply technologies that may reduce the aggregate CO 2 emissions intensities of the production of electricity, liquid fuels, or hydrogen. Examples include nuclear energy, renewable energy, bioenergy, or carbon capture and storage (CCS). In fact, a wide body of literature highlights the importance of low-cost, low-emission energy transformation technologies in reducing the costs of greenhouse gas mitigation (Clarke et al., 27; Richels and Blanford, 28). However, the feasibility and costs of largescale deployment of these technologies, as would be required to meet a longterm greenhouse gas mitigation target, are not known. Social, environmental, and technical issues all pose potential barriers to large expansions of nuclear power, for instance. Other technologies such as carbon capture and storage or engineered geothermal systems face substantial research and development hurdles, and large-scale deployment might face as-yet unforeseen technical or economic barriers. Due to this uncertainty regarding the potential availability of low-cost, low-emissions energy transformation technologies, the core analysis in this study assumes a modest future in this regard (the Reference Scenario in Clarke et al., 28a). Expansion of nuclear power beyond present-day deployment is not allowed, and it is similarly assumed that carbon capture and storage is

11 Climate Policy and the Long-Term Evolution of the U.S. Buildings Sector / 155 Figure 2. Assumed U.S. Economic Output and Population in all Scenarios Population (millions) GDP per capita (thousand 25$) Population GDP per capita not an option. Note however that due to the potentially important role of these technologies, an additional sensitivity analysis is conducted in which expanded nuclear energy and CCS at electric power plants is allowed. In scenarios in this study, technological options allowing CO 2 emissions abatement in the electric power sector include biomass, biomass-derived gaseous or liquid hydrocarbon fuels, wind, solar, and geothermal energy. Rooftop photovoltaic-generated electricity competes with grid-produced electricity to supply residential and commercial buildings, using supply curves from Denholm and Margolis (28). Note however that bioenergy costs increase with deployment due to consequent declining yields and due to pricing of CO 2 emissions from land conversion. As well, wind and solar electricity incur backup and storage-related costs at high levels of deployment, owing to the intermittency of the resources. As such, the price of energy thus produced will tend to increase Service Demand Assumptions Two sets of assumptions pertaining to future building service demands are analyzed in this study (high demand and low demand; see Table 1). The high demand assumptions represent a continuation of the historical trends of increasing per-capita demands for floorspace, and growth in per-floorspace demands of residential and commercial cooling, office equipment, and other services. Note that in future periods, this other category includes new services that do not presently exist. The low demand assumptions, in contrast, posit a scenario in which future per-capita floorspace demands, and future building service demands per unit of floorspace, do not continue to grow with income. Future floorspace and

12 156 / The Energy Journal Figure 3. Floorspace Demand by Residential and Commercial Sectors, for High and Low Demand Scenarios 6 Total floorspace (billion sq. m) Ref-high Residential Ref-low Residential Ref-high Commercial Ref-low Commercial building service demands are therefore driven only by population growth, and influenced by the prices of floorspace and individual building services. Such a scenario might reflect developments such as densification of suburbs, or a cultural shift in preferences towards smaller and simpler homes. Future floorspace trajectories for both high and low demand scenarios are shown in Figure 3. Note that even without income-driven growth in floorspace demands (Ref-low), total floorspace nearly doubles between 25 and the end of the century because population nearly doubles. High demand scenarios increase this demand further, by 3% at the end of the century. The assumptions pertinent to specific building service demands per unit of floorspace in high and low demand scenarios are shown in Table 2. High demand scenarios include growth in cooling service demand, commercial office equipment, and residential and commercial other services per unit of floorspace. Growth in cooling service demand may reflect continued population shifts towards warmer climates, or increased use of air conditioners in houses that are presently unequipped. Residential other and commercial office services are assumed to have the most future growth, in agreement with recent historical trends and near-term expectations (EIA, 1996; EIA, 27). Growth of other services is assumed to be lower in the commercial sector than in the residential sector, as the commercial other services are less likely to be directly influenced by income.

13 Climate Policy and the Long-Term Evolution of the U.S. Buildings Sector / 157 Table 2. Assumptions of Non-price-related Growth in Building Service Demands Per Unit of Floorspace from 25 to 25, for High and Low Demand Scenarios High Demand Low Demand Service residential Commercial Residential Commercial Heating % % % % Cooling 25% 25% % % Water Heating % % % % Lighting % % % % Residential Appliances 1% n/a % n/a Residential Other 45% n/a % n/a Commercial Office n/a 45% n/a % Commercial Other n/a 25% n/a % Building Technology Assumptions As with service demands, two sets of assumptions about future building technologies are investigated in this paper: Reference and Advanced (see Table 1). The specific assumptions to each of these technology suites are presented in Table A1 and Table A2. The Reference assumptions represent steady improvement in the performance of existing building technologies, with near-term improvement rates based on EIA (27) and TIAX (26), followed by modest long-term improvement rates. It is assumed that low-cost, energy-saving fluorescent lighting displaces incandescent lighting for most domestic applications, starting in the near future (see Energy Independence and Security Act of 27). Costs of building technologies are also generally assumed to decrease at a modest rate in the future. In Reference technology scenarios, new, energy-saving technologies, such as solid state lighting and heat pump water heaters, do become available over time, but at higher costs than conventional technologies. Residential building shell efficiency is parameterized based on a stock model calibrated to historical heating and cooling demands per unit of floorspace in five climate zones, based on EIA (21). Reference assumptions are based on 3% improvement by 25, and 6% improvement by 295, in the aggregate building shell efficiency of new construction, as compared with the 25 stock. The Advanced set of assumptions departs from the Reference starting in the first time period, 22. In this year, equipment stock average efficiencies are generally based on the EIA (27) projections for the year 23. Office equipment improvement is based on Kawamoto et al. (21), and technologies providing other services follow the high efficiency pathways outlined in TIAX (26). This represents a more rapid deployment of energy-saving technologies in the near term, either through standards, consumer preferences, or policies that address market barriers to energy savings in buildings. Advanced scenarios

14 158 / The Energy Journal also show accelerated improvements in building shell efficiency, with the average shell efficiency of new construction, relative to 25 homes, being 6% improved in 25 and 9% improved in 295 (parameterization based on BEopt program; Christensen et al., 25). In addition, the Advanced scenarios feature new, energy-saving technologies available at the same cost as conventional technologies starting in 235. These advanced technologies may become available through larger investment through government and private sector research and development programs, spillovers from other industries, learning by doing, or a serendipitous process of scientific discovery (see Clarke et al., 28b). In any case, no effort is made in this analysis to associate research investments with particular technology outcomes Climate Stabilization Policy In order to examine the behavior of the U.S. buildings sector in an emissions-constrained economy, and to examine the roles of future technology and service demand in the buildings sector, the four demand and technology scenarios are also run with a policy that constrains national CO 2 emissions. The U.S. emissions pathway is part a global climate policy that starts before 22, and is designed to stabilize global atmospheric concentrations of CO 2 at 45 ppmv. The specific U.S. emissions pathway in this study, which is common to all scenarios with a climate policy, is from the Reference Technology Scenario in Clarke et al. (28a; see Figure 4). As with any economically efficient path to stabilization, emissions reductions become increasingly stringent over time, to minimize retirement of existing capital stocks, to take advantage of advanced technologies that become available later in the century, and to reflect the time value of money (Wigley et al., 1996). Emissions approach a constant level as the atmospheric concentration of CO 2 nears the target level (45 ppmv), as shown in Figure 4. The emissions constraints imply a price on CO 2 emissions, which effectively increases the prices of hydrocarbon fuels according to their respective carbon contents. All sectors see the same emissions prices, so the marginal abatement cost of CO 2 emissions reduction is equal across the economy. That is, while more abatement may take place in the electric sector than in the buildings sector, for instance, the cost of the last ton of CO 2 abated is equal between all sectors, which minimizes the total economic cost of the policy. Energy transformation sectors and final energy consumers have incentive to use technologies with low emissions, both primary (direct) and secondary (upstream). Service demands also decrease in response to higher fuel prices. The price on CO 2 that is required to meet emissions constraints depends on the amount of emissions that need to be cut, the availability of technologies capable of reducing emissions, and the price elasticity of the service demands. Because the demand and technology scenarios investigated in this study will have different emissions absent a policy, and different technologies available for reducing emissions, scenarios will have different CO 2 prices and policy costs, in spite of having a common emissions pathway.

15 Climate Policy and the Long-Term Evolution of the U.S. Buildings Sector / 159 Figure 4. Annual Fossil and Industrial CO 2 Emissions in the United States, With and Without Global Policy to Stabilize Atmospheric CO 2 Concentrations at 45 ppmv, and CO 2 Emissions Prices in the U.S. CO2 emissions (Gt / yr) Ref-high All 45 scenarios CO2 price (Ref-high-45) CO2 price (25$ / t) 3. Results and Discussion 3.1 No Climate Policy Figure 5 shows the evolution of service demands per unit of floorspace in the Ref-low and Ref-high scenarios (reference building technology, low and high building service demand growth, and no climate policy). The low building service demand scenarios assume lower floorspace (see Figure 3) and lower growth rates for specific building service demands per unit of floorspace (see Figure 5). The services that grow the most relative to 25 levels in the Ref-high scenario residential and commercial other services and commercial office equipment are relatively constant in the future in the Ref-low scenario. Lighting service consumption per unit of floorspace grows in both the Refhigh and Ref-low scenarios, even though there is no exogenous growth assumed for lighting service demands in either scenario. This is because of the assumption that much of the incandescent lighting stock is replaced by relatively efficient and cost-effective fluorescent lighting. The observed growth in service demand is due to a decrease in service prices (i.e. the rebound effect; see Greening et al., 2), an effect that must be considered in assessing the role of any technology advancement in reducing energy consumption. Heating and cooling demands per unit of floorspace both decline over time due to improvements in building shells.

16 / The Energy Journal Figure 5. Service Demands per Unit of Floorspace, 199 to 295, Indexed to 25, Under Reference Building Technology Assumptions 4 Ref-high 1.4 Ref-low Heating Cooling Water Heating Res. Other Lighting Comm. Other The effect is more prominent for heating than cooling because the increase in other demands tends to create internal gains that reduce heating requirements and increase cooling requirements. Although not considered here, climate change could be expected to further contribute to this trend. The overall effect of service demand growth on total final energy consumption by buildings can be seen in Figure 6. The lower demand assumption case combined with reference building technology assumptions (Ref-low) leads to an approximate stabilization of total final energy at 25 levels through 295. That is, the population-driven growth in building service demands is roughly counter-balanced by the improvements in energy efficiency assumed to take place in the reference building technology scenarios. A similar outcome is, coincidentally, achieved under high service demand growth assumptions if building technology is assumed to advance at the rates in the advanced technology scenarios (Adv-high). With respect to total final energy consumption by buildings, therefore, the effects of advanced technologies are similar to the effects of low service demand growth, under the assumptions in this paper. Moreover, the impacts of service demand and technology assumptions are cumulative; as shown in Figure 6, the scenario with low building service demands combined with advanced building technologies shows a long-term decrease in buildings sector final energy demand. The future buildings sector CO 2 emissions in these four scenarios are dependent not only on total final energy consumption, but on the types of energy consumed. The growth in the office and other services in Ref-high, and the decline in heating energy use are particularly important because the services with the most growth tend to be fueled by electricity, whereas heating is mostly

17 Climate Policy and the Long-Term Evolution of the U.S. Buildings Sector / 161 Figure 6. U.S. Buildings Sector Final Energy Consumption by Scenario, 199 to 295 Total final energy (EJ / yr) Ref-high Adv-high Ref-low Adv-low Figure 7. U.S. Buildings Final Energy Consumption by Fuel, With and Without National Emissions Constraint 25 Ref-high and Ref-high Adv-low and Adv-low biomass gas electricity liquids biomass 45 electricity 45 gas 45 liquids 45 supplied by fossil fuels. In addition, the office and other equipment contribute to internal gain energy, further decreasing heating service demands and increasing cooling service demands. The net effect of these dynamics in building services is that all of the scenarios in this analysis continue the historical trend of electrification in buildings

18 162 / The Energy Journal Figure 8. Prices of Fuels Delivered to U.S. Buildings, With and Without National Emissions Constraint (Ref-high and Ref-high-45) 25 $ / GJ biomass biomass 45 gas gas 45 electricity electricity 45 liquids liquids 45 (see Figure 7). In addition to service demand evolution, several other trends also contribute to the electrification of the buildings sector. Assumed improvement in electric-powered heat pumps, particularly in advanced technology scenarios, tend to increase the market share of electricity in providing space heating and water heating. A second driver of electrification is the consumer response to fuel price changes. While gas and oil prices tend to increase as low-cost reserves are depleted, electricity prices decrease due to assumed improvements in the performance of electricity generation technologies, relatively stable coal prices, and deployment of cost-effective renewable energy (see Figure 8 and Figure 9). Although electrification leads to a long-term stabilization or decline in primary CO 2 emissions from the buildings sector in all four scenarios, shown in Figure 1, it also drives a corresponding increase in emissions from the electricity sector. Total CO 2 emissions from building energy use (including electricityrelated emissions) depend on the amount of electricity consumed, and the CO 2 emissions intensity of electricity generation. Although the average emissions intensity of electricity generation declines over time in all scenarios in this study, due to technological improvement in fossil-fired technologies and deployment of renewable energy, electricity nevertheless remains a relatively emissions-intensive fuel through the end of the century in scenarios without a climate policy (see Figure 9 for the generation mix). The CO 2 emissions intensity of electricity generation declines from 16 kg CO 2 per GJ at present to between 12 and 13 kg CO 2 per GJ at the end of the century. For comparison, the emissions intensities of natural gas and fuel oil are about 56 and 77 kg CO 2 per GJ, respectively (IPCC, 1997). The net effect of the different futures of building technologies and service demands on total CO 2 emissions from the buildings sector is shown in Figure 1. Note that the scenarios show considerable divergence in total emissions, starting in the first future time period, which has implications for how buildings will interact with the remainder of the energy system when national emissions constraints are imposed.

19 Climate Policy and the Long-Term Evolution of the U.S. Buildings Sector / 163 Figure 9. U.S. Electricity Generation by Fuel, With and Without National Emissions Constraint 4 Ref-high 4 Ref-high EJ / yr 25 2 EJ / yr Coal 4 Gas Oil 2 Nuclear Biomass Hydro Wind Solar Geothermal Figure 1. Total (Including Electricity Sector) and Primary Fossil CO 2 Emissions from the U.S. Buildings Sector, For Scenarios with No Emissions Constraint 4.5 CO2 emissions (Gt / yr) Total: Ref-high Total: Adv-high Total: Ref-low Total: Adv-low Primary: Ref-high Primary: Adv-high Primary: Ref-low Primary: Adv-low The wide range of CO 2 emissions among the no-policy scenarios should serve as a reminder that market-based carbon instruments are not the only means to reduce CO 2 emissions. Research and development activities and complementary policies such as technology standards and land use planning can serve as powerful levers to address climate change and reduce U.S. energy demands more broadly. Nonetheless, even with the combination of low service demand growth and advanced building technologies, the total emissions from the

20 164 / The Energy Journal buildings sector in an unconstrained case exceeds the total for the full economy for the 45 ppmv concentration goal analyzed in this paper ppmv Climate Policy All scenarios with climate policy are assigned a national CO 2 emissions pathway, which causes CO 2 emissions to depart from the reference emissions pathways starting in the first future model time period (see Figure 3). Emissions reductions are achieved by placing an economy-wide price on CO 2 emissions. The CO 2 prices required to meet the national emissions constraints differ by scenario (see Table 3), as the scenarios differ both in the amount of CO 2 emissions that need to be cut in order to comply with the target level, and in the buildings sector technological options available for achieving the necessary reductions. Even in spite of the assumed restrictions on deployment of nuclear power and carbon capture and storage in the electricity sector, electricity generation nevertheless shifts towards the low-carbon technologies that are available (see Figure 9). These technologies include intermittent renewables paired with largescale electricity storage, and natural gas combined cycle plants. Of particular note to the buildings sector, rooftop photovoltaic, which accounts for less than 2% of buildings electricity consumption in scenarios without a climate policy, increases to supply about 8% of all electricity consumed by buildings. This represents between 1 GW (Adv-low-45) and 2 GW (Ref-high-45) of installed capacity by 295. This technology switching has the effect of reducing the CO 2 emissions intensity of electricity generation, from 16 kg CO 2 per GJ in 25 to roughly 2 kg CO 2 per GJ in 295 in the policy scenarios. This reduces the taxrelated price increases to electricity consumers below what they would be if the CO 2 emissions intensity of electricity generation were left unchanged. As shown in Figure 8, policy-related price increases are proportionally less for electricity than for other fuels over time. End-use sectors, such as buildings, generally have two options for responding to the fuel price increases brought about by a greenhouse gas mitigation policy: (1) technology switching (towards more efficient technologies, or towards lower-emissions fuels), and (2) reducing service demands. Examples of both of these trends are shown in Figure 11. The policy causes consumers to switch from gas furnaces to electric heat pumps, but on the whole, the climate policy also causes heating service demands to decrease. This technology switching in buildings underscores an important point about advanced technology and costs of emissions mitigation: advanced technologies are important not only for reducing fuel requirements to provide end-use services, but for facilitating fuel-switching to low-emissions fuels as they become available (Clarke et al., 28b). In the buildings sector, low-cost heat pumps for space heating and water heating appear to be especially important (Kyle et al., 28), as they lower the costs of electrification of services whose cheapest options are generally fossil fuel-based.

21 Climate Policy and the Long-Term Evolution of the U.S. Buildings Sector / 165 Figure 11. Technology Choice in Residential Heating, and Total Heating Service Demand in the Residential Sector (Indexed to 25), With and Without Emissions Constraints EJ / yr 199 Energy consumption by technology Indexed service output per unit of floorspace High-ref High-ref High-ref: Gas furnace High-ref: Electric heat pump High-ref-45: Gas furnace High-ref-45: Electric heat pump The net effect of the climate policy on the buildings sector is to further the historical trend of electrification: electricity supplies an even greater share of total final energy delivered to buildings than what already is observed in no-policy scenarios (see Figure 7). While total electricity demands are slightly increased in response to a policy, total CO 2 emissions from building energy use are far lower with a climate policy (shown for policy scenarios in Figure 12 and for nopolicy scenarios in Figure 1). This is due to the decarbonization of electricity generation described above. The scenario with advanced building technologies and low service demands (Adv-low-45) still has the least buildings-related CO 2 emissions of the four policy scenarios, which is important for reducing economywide policy costs. Low-cost abatement from any one sector, buildings in this case, reduces the burden on all other sectors of the energy system, and results in lower system-wide CO 2 prices and total policy costs. Total discounted national policy costs, calculated based on the costs of CO 2 abatement by all sectors of the economy from the present through 295, are shown for the four policy scenarios in Table 3. Relative to the scenario with reference building technology and high building service demands (Ref-high-45), low future service demands in the buildings sector reduce policy costs by 26%, and advanced technologies reduce costs by 22%. The scenario with both low demands and advanced technologies shows a cost reduction of 4%. Note that these changes are due to different assumptions for the buildings sector only. If corresponding changes were also made in other end use sectors cost changes would be even larger. These figures not only underscore the importance of future building service demand levels; they also point out that the effects of advanced technology