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 40 percent of U.S. final energy use. They account for
roughly 10 percent of direct U.S. CO2 emissions and roughly 40 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.
CO2 emissions consistent with a 450 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 40% 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 ©2010 by the IAEE. All rights reserved.
*
Joint Global Change Research Institute, Pacific Northwest National Laboratory, 5825 University
Research Court, College Park, MD 20740.
** School of Public Policy and Management, Tsinghua University, Beijing, China.
†
Corresponding author. Email: [email protected]. Tel: 301-314-6758.
145
146 / The Energy Journal
substantially in upcoming decades (EIA, 2007; EIA, 2008).1 Buildings directly
account for about 10% of CO2 emissions from primary fossil fuel combustion in
the U.S., and they account for nearly 40% of the national total if electricity-related
emissions are also considered (EIA, 2008). 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 CO2 emissions. This topic
is currently receiving substantial attention from researchers and policy-makers
(Levine et al., 2007; McKinsey Global Institute, 2007).
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., 2007).
Hence, the long-term evolution of the buildings sector and building technologies
is an important strategic concern. In the long term, CO2 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 2005,
per-capita floorspace increased from 55 to 70 square meters per person in the
residential sector, and from 20 to 26 square meters per person in the commercial
sector. Combined with population growth, this amounted to an 80% expansion in
total floorspace between 1975 and 2005. All else equal, growth in floorspace is
associated with increases in building service demands and energy consumption
(e.g. Battles, 2004; Wilson and Boehland, 2005; Gerencher, 2006). 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).
Climate Policy and the Long-Term Evolution of the U.S. Buildings Sector / 147
of residential floorspace has declined by about 50% since 1978 (EIA, 1979;
EIA, 2007) and air conditioning energy consumed per unit of floorspace has
increased by 45% over the same time period (EIA, 1979; EIA, 2007). 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,
2001), 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 1990’s
(EIA, 2008), and the same is expected to happen in the residential sector in the
upcoming decade (EIA, 2007). Electrification is of particular interest for the
present study not only because electricity generation accounts for the majority
of the energy-related CO2 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., 2008a; Richels and Blanford,
2008).
The CO2 emissions intensity of electric generation is the fourth aspect of
historical CO2 emissions from the buildings sector that will play a role in future
emissions. Between 1980 and 2006, the average emissions intensity of electricity
generation in the U.S. dropped from 186 kg CO2 per GJ of electricity to 160 kg CO2
per GJ (EIA, 2008). 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 1980, and 38% in 2006 (IEA,
2007). Conversely, oil, a more carbon-intensive fuel source for electricity, dropped
from 11% to 3% over the same time period (IEA 2007). 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 CO2 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 CO2 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?
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 CO2 emissions and the policies for constraining these
emissions from a long-term, global perspective (for reviews see Nakicenovic and
Swart, 2000; Clarke et al., 2007). 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 CO2 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. CO2 emissions consistent with a 450 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., 2004),
as implemented within the Object-oriented Energy, Climate, and Technology
Systems framework (ObjECTS; Kim et al., 2006). MiniCAM has been used in
a wide range of scenario analysis and technology studies (e.g. Nakicenovic et
al., 2000; Clarke et al., 2007; Clarke et al., 2008a). MiniCAM combines partialequilibrium economic models of the global energy system (Edmonds and Reilly,
1985; Edmonds et al. 2004) and global land use (Sands and Leimbach, 2003),
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, 2002). MiniCAM is considered an integrated
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 1990 and 2005 historical data, and the model
calculates equilibria in all markets in 15-year time periods to 2095. 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. (2007), 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.
2.2.1 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
150 / 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 2.3.2
2.2.2 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,
2006). The commercial “other” demands consist largely of ventilation, cooking,
refrigeration, distribution transformers, and water treatment and pumping (EIA,
2007; TIAX, 2006).
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:
di,t = φi,t si Pi,t– bi
(1)
In Equation (1), di,t is the demand for the service i per unit of floorspace
in time period t, φi 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.
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 si 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. Pi is the average price of delivering
the service, weighted between all technologies providing the service, and bi 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:
dH,t = sHφH,t ut a HDDt PH,t– bH – G (2)
dC,t = sCφC,t ut a CDDt PC,t– bC + 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.
2.2.3 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.
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 CO2 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.
2.2.4 Base Year Model Inputs and Calibration
Energy consumption by fuel by the buildings sector in 1990 and 2005 is
from the Annual Energy Review (EIA, 2008) and is assigned to building services
according to the Annual Energy Outlook (EIA, 1996; EIA, 2007). 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 (2007) and National Energy Modeling Systems stock models (U.S. DOE,
2004). Incandescent and fluorescent lighting efficiency is based on NCI (2002),
and solid-state lighting efficiency is based on NCI (2006). Office equipment,
appliances, and other efficiencies are indexed to 2005. Non-energy costs for
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 10% 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 (2004). 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, 2007).
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. 2008a for more detailed documentation).
Electricity generation technologies are assumed to be long-lived (between 30 and
60 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 CO2
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 CO2 emissions
are priced, electric generation costs also include the emissions costs, equal to the
CO2 emissions intensity of the technology multiplied by the CO2 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
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. (2008a).
Table 1. Scenarios of Building Technology Levels, Building Service
Demand Levels, and Climate Policy
Name
TechnologyDemand
Policy
Ref-high
Adv-high
Reference
Advanced
High
High
None
None
Ref-low
Adv-low
Reference
Advanced
Low
Low
None
None
Ref-high-450
Adv-high-450
Reference
Advanced
High
High
450
450
Ref-low-450
Adv-low-450
Reference
Advanced
Low
Low
450
450
2.4.1 General Assumptions
Population and GDP are the ultimate drivers of future service demands,
energy consumption, and CO2 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 2095 is roughly three times that
of today (see Figure 2). The U.S. population follows Census projections through
2050 (U.S. Census Bureau, 2004), 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 CO2 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.,
2007; Richels and Blanford, 2008). 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., 2008a). Expansion of nuclear power beyond present-day deployment
is not allowed, and it is similarly assumed that carbon capture and storage is
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
140
Population (millions)
500
120
400
100
80
300
60
200
40
100
0
1990
20
2005
2020
2035
Population
2050
2065
2080
GDP per capita (thousand 2005$)
160
600
0
2095
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 CO2 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 (2008). Note however that bioenergy costs increase with deployment
due to consequent declining yields and due to pricing of CO2 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.
2.4.2 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
156 / The Energy Journal
Figure 3. Floorspace Demand by Residential and Commercial Sectors, for
High and Low Demand Scenarios
Total floorspace (billion sq. m)
60
50
40
30
20
10
0
1990
2005
2020
2035
2050
2065
2080
2095
Ref-high Residential
Ref-high Commercial
Ref-low Residential
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 2005 and the end of
the century because population nearly doubles. High demand scenarios increase
this demand further, by 30% 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, 2007). 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.
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 2005 to 2050, for High
and Low Demand Scenarios
High Demand Service Residential Low Demand
Commercial Residential Commercial
Heating 0% 0% 0% 0%
Cooling 25% 25% 0% 0%
Water Heating 0% 0% 0% 0%
Lighting 0% 0% 0% 0%
Residential Appliances 10% n/a 0% n/a
Residential Other 45% n/a 0%
n/a
Commercial Office n/a 45% n/a 0%
Commercial Other n/a 25% n/a 0%
2.4.3 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 (2007) and TIAX (2006), 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 2007). 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 (2001). Reference assumptions are based on 30% improvement by 2050,
and 60% improvement by 2095, in the aggregate building shell efficiency of new
construction, as compared with the 2005 stock.
The Advanced set of assumptions departs from the Reference starting
in the first time period, 2020. In this year, equipment stock average efficiencies
are generally based on the EIA (2007) projections for the year 2030. Office
equipment improvement is based on Kawamoto et al. (2001), and technologies
providing “other” services follow the high efficiency pathways outlined in TIAX
(2006). 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
158 / The Energy Journal
also show accelerated improvements in building shell efficiency, with the
average shell efficiency of new construction, relative to 2005 homes, being 60%
improved in 2050 and 90% improved in 2095 (parameterization based on BEopt
program; Christensen et al., 2005). In addition, the Advanced scenarios feature
new, energy-saving technologies available at the same cost as conventional
technologies starting in 2035. 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., 2008b). In any
case, no effort is made in this analysis to associate research investments with
particular technology outcomes.
2.4.4 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 CO2 emissions. The
U.S. emissions pathway is part a global climate policy that starts before 2020, and
is designed to stabilize global atmospheric concentrations of CO2 at 450 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.
(2008a; 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 CO2 nears the target level (450 ppmv), as shown in Figure 4.
The emissions constraints imply a price on CO2 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 CO2 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 CO2 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 CO2 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 CO2
prices and policy costs, in spite of having a common emissions pathway.
Climate Policy and the Long-Term Evolution of the U.S. Buildings Sector / 159
Figure 4. Annual Fossil and Industrial CO2 Emissions in the United States,
With and Without Global Policy to Stabilize Atmospheric CO2
Concentrations at 450 ppmv, and CO2 Emissions Prices in the
U.S.
10
350
300
8
CO2 price (2005$ / t)
CO2 emissions (Gt / yr)
9
7
250
6
200
5
4
150
3
100
2
50
1
0
1990
2005
2020
2035
2050
2065
2080
0
2095
Ref-high
All 450 scenarios
CO2 price (Ref-high-450)
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 2005 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.,
2000), 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.
160 / The Energy Journal
Figure 5. Service Demands per Unit of Floorspace, 1990 to 2095, Indexed to
2005, Under Reference Building Technology Assumptions
95
20
65
80
20
20
50
35
20
20
20
05
90
19
20
20
20
20
20
20
20
Heating
20
0.0
95
0.2
0.0
80
0.4
0.2
65
0.6
0.4
50
0.8
0.6
35
1.0
0.8
20
1.0
05
1.2
90
1.2
19
Ref-low
1.4
20
Ref-high
1.4
Cooling
1.5
1.0
0.5
0.0
1990
Water Heating
2005
2020
2035
2050
Res. Other
2065
2080
2095
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 2005 levels through 2095.
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 CO2 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
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,
1990 to 2095
Total final energy (EJ / yr)
40
35
30
25
20
15
10
5
0
1990
2005
2020
2035
2050
2065
Ref-high
Ref-low
2080
2095
Adv-high
Adv-low
Figure 7. U.S. Buildings Final Energy Consumption by Fuel, With and
Without National Emissions Constraint
biomass
electricity
gas
liquids
gas 450
2095
2080
2065
2050
biomass 450
2035
2020
2005
1990
25
20
15
10
5
0
95
80
20
65
20
50
20
20
35
20
20
90
19
20
20
20
20
20
20
20
05
0
20
0
95
5
80
5
65
10
50
10
35
15
20
15
05
20
90
20
19
Adv-low and Adv-low-450
25
20
Ref-high and Ref-high-450
25
electricity 450
liquids 450
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
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-450)
50
45
biomass
40
biomass 450
2005 $ / GJ
35
gas
30
gas 450
25
electricity
20
electricity 450
15
liquids
10
liquids 450
5
0
1990
2005
2020
2035
2050
2065
2080
2095
(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 CO2 emissions from the buildings sector in all four scenarios, shown in
Figure 10, it also drives a corresponding increase in emissions from the electricity
sector. Total CO2 emissions from building energy use (including electricityrelated emissions) depend on the amount of electricity consumed, and the CO2
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 CO2 emissions intensity of electricity generation declines from 160
kg CO2 per GJ at present to between 120 and 130 kg CO2 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 CO2 per GJ, respectively (IPCC, 1997). The net effect of
the different futures of building technologies and service demands on total CO2
emissions from the buildings sector is shown in Figure 10. 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.
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
Ref-high
35
30
30
25
25
EJ / yr
35
20
20
15
15
10
10
5
5
2065
2080
0
1990
2095
2005
2020
40
Coal
20
Nuclear
0
Gas
Oil
Biomass
Hydro
Wind
Solar
Geothermal
20
19
80
2050
50
2035
20
2020
20
2005
90
0
1990
Ref-high-450
40
20
EJ / yr
40
2035
2050
2065
2080
2095
Figure 10. Total (Including Electricity Sector) and Primary Fossil CO2
Emissions from the U.S. Buildings Sector, For Scenarios with
No Emissions Constraint
4.5
CO2 emissions (Gt / yr)
4
Total: Ref-high
3.5
Total: Adv-high
3
Total: Ref-low
2.5
Total: Adv-low
Primary: Ref-high
2
Primary: Adv-high
1.5
Primary: Ref-low
1
Primary: Adv-low
0.5
0
1990
2005
2020
2035
2050
2065
2080
2095
The wide range of CO2 emissions among the no-policy scenarios
should serve as a reminder that market-based carbon instruments are not the
only means to reduce CO2 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
164 / The Energy Journal
buildings sector in an unconstrained case exceeds the total for the full economy
for the 450 ppmv concentration goal analyzed in this paper.
3.2 450 ppmv Climate Policy
All scenarios with climate policy are assigned a national CO2 emissions
pathway, which causes CO2 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 CO2 emissions. The
CO2 prices required to meet the national emissions constraints differ by scenario
(see Table 3), as the scenarios differ both in the amount of CO2 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 100 GW (Adv-low-450) and 200 GW (Ref-high-450) of installed
capacity by 2095. This technology switching has the effect of reducing the CO2
emissions intensity of electricity generation, from 160 kg CO2 per GJ in 2005 to
roughly 20 kg CO2 per GJ in 2095 in the policy scenarios. This reduces the taxrelated price increases to electricity consumers below what they would be if the
CO2 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., 2008b). In the buildings sector, low-cost heat
pumps for space heating and water heating appear to be especially important
(Kyle et al., 2008), as they lower the costs of electrification of services whose
cheapest options are generally fossil fuel-based.
Climate Policy and the Long-Term Evolution of the U.S. Buildings Sector / 165
Figure 11. T
echnology Choice in Residential Heating, and Total Heating
Service Demand in the Residential Sector (Indexed to 2005),
With and Without Emissions Constraints
Energy consumption by technology
1.2
4
3.5
3
2.5
2
1.5
1
0.5
0
1
0.8
0.6
EJ / yr
0.4
0.2
95
20
65
50
35
80
20
20
20
20
20
20
05
20
19
95
80
20
50
35
20
05
65
20
20
20
20
20
90
90
0
20
19
Indexed service output per unit of
floorspace
High-ref
High-ref-450
High-ref: Gas furnace
High-ref: Electric heat pump
High-ref-450: Gas furnace
High-ref-450: 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 CO2 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 10). This is due to the decarbonization of electricity
generation described above. The scenario with advanced building technologies
and low service demands (Adv-low-450) still has the least buildings-related CO2
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 CO2 prices and total policy costs.
Total discounted national policy costs, calculated based on the costs of
CO2 abatement by all sectors of the economy from the present through 2095,
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-450),
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 40%. 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
166 / The Energy Journal
Figure 12. T
otal (Including Electricity Sector) and Primary Fossil CO2
Emissions from the U.S. Buildings Sector, for Scenarios with
National Emissions Constraint
CO2 emissions (Gt / yr)
3
Total: Ref-high-450
2.5
Total: Adv-high-450
2
Total: Ref-low-450
Total: Adv-low-450
1.5
Primary: Ref-high-450
1
Primary: Adv-high-450
Primary: Ref-low-450
0.5
Primary: Adv-low-450
0
1990
2005
2020
2035
2050
2065
2080
2095
and low service demands in the buildings sector are not redundant in reducing
policy costs. Per-capita floorspace demands and the quantity and nature of
services demanded in buildings are relevant for CO2 emissions mitigation costs,
even when advanced building technologies are in use.
As a final sensitivity analysis, we note that in a future with unrestricted
expansion of nuclear power and availability of CCS at large scale, we observe a
greater degree of decarbonization of the electric power sector in response to the
national CO2 emissions constraint. In fact, CO2 emissions from the electricity
sector as a whole become negative in the long-term due to the use of bioenergy
with CCS. The long-term electricity prices in these scenarios would be about 35%
lower than observed in this study (see Figure 8). However, we observe the same
degree of electrification in the buildings sector as in the core scenarios in this
study, shown in Figure 7; the relative share of buildings sector total final energy
supplied by each fuel remains constant both with and without expanded nuclear
energy and CCS in the electric power sector. This is because the opportunity to
achieve low-cost abatement of CO2 emissions in the electric power sector has the
effect of reducing CO2 emissions prices for the whole economy, fossil fuels as
well. In other words, electrification of the buildings sector in response to a climate
policy does not appear to be sensitive to the technological abatement options
available in the electric power sector. Moreover, advanced technologies and low
service demands in the buildings sector still reduce cumulative discounted policy
costs by 27%; even with an optimistic future for CO2 abatement in the electric
power sector, there is still substantial economic value in advanced technologies
and low service demands in the buildings sector.
Climate Policy and the Long-Term Evolution of the U.S. Buildings Sector / 167
Table 3. CO2 Emissions Prices by Period, and Total Discounted Policy
Costs By Building Technology and Demand Scenario
CO2 prices (2005$ / t CO2)
Scenario
Ref-high-450
Ref-low-450
Adv-high-450
Adv-low-450
2020
2050
2095
16
4.3
11
2.2
119
109
106
102
315
302
294
283
Cumulative
discounted cost
(Billion 2005$)
1054
775
819
623
4. Conclusions
This paper presents a detailed U.S. buildings sector module embedded
within the MiniCAM integrated assessment model, which enables the consideration
of detailed end-use dynamics within the context of long-term, global approaches
to address climate change. It isolates the drivers of building energy demands,
such as floorspace growth, service demand evolution, and the efficiency of the
technologies in use. This allows for explicit consideration of the consequences
of different futures of service demand and technological improvement within the
context of the changing energy system in the U.S. over the coming century.
Application of the buildings module leads to several insights regarding
the role of the buildings sector in addressing climate change over a century-long
timescale. First, the evolution of building service demands will be important for
future energy consumption and CO2 emissions of the buildings sector, even when
advanced, energy-saving technologies are in use. Understanding the drivers of
building floorspace demands, and consumer behaviors that determine the levels
of services demanded, is clearly an important topic of research, complementary
to the promotion of energy efficiency.
Second, the suite of advanced building technologies in this study appears
capable of stabilizing future U.S. buildings sector energy consumption and CO2
emissions. However, this is insufficient to meet the national CO2 emissions
constraints of the 450 ppmv CO2 concentration policy analyzed in this study.
Without the climate policy, the energy consumed by the buildings sector alone is
responsible for more CO2 emissions than the nation is permitted with the policy,
even when building service demands are low and advanced building technologies
are deployed. This is because of the stringency of the policy analyzed, and because
without the policy, the CO2 emissions intensity of electricity generation remains
high. Electrification of buildings, a great deal of which might be expected absent
climate policy, does not constitute a strategy to reduce national CO2 emissions
unless it is coupled with a substantial decrease in the CO2 emissions intensity of
electricity generation, as was caused by the climate policy in this study. At the
same time, it is also fair to say that if electrification is one part of a building sector
168 / The Energy Journal
approach to climate action, then we can expect much of this step to take place
irrespective of climate policy.
Third, advanced building technologies are important not only for
reducing final energy demand, but for allowing the buildings sector to switch to
low-emissions fuels as they become available. In this context, the most important
technologies may not be the ones that reduce final energy demands the most,
but rather the technologies that can displace fossil fuels from the services where
they are currently the most economical choices (space heating, water heating, and
cooking). This study focused on the critical role of electricity, and electrification
of building services. The role of end-use technology in facilitating electrification
was important for reducing CO2 emissions mitigation costs both with and without
expanded nuclear energy and carbon capture and storage systems applied to
electricity generation facilities. However, note that electrification was only
important for reducing CO2 emissions when coupled with a large-scale reduction
in the CO2 emissions intensity of electricity generation, as witnessed with the
national emissions constraint in this study. We also note that fuel-switching
in buildings is not limited to electricity; in the future, solar thermal energy,
geothermal energy, or hydrogen may all contribute in this role.
The analysis presented in this paper suggests a number of possible
avenues for further work. Integrated green building design could be considered
by incorporating coupled sets of technologies that work together to provide
the complete suite of building energy services at a lower cost. Building solar
technologies that could be considered include day-lighting, hot water heating and
cooking equipment. Extension of the model to other world regions would allow a
global analysis of building energy technologies, which is particularly important in
developing regions as they make a transition to modern energy systems. Finally,
this model would allow an integrated consideration of temperature feedback
effects on building energy use, particularly in the context of efforts to stabilize
CO2 concentrations.
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Acknowledgments
The authors are indebted to the U.S. Department of Energy’s Office
of Energy Efficiency and Renewable Energy for support of the research of this
paper. The authors are also indebted to the U.S. Department of Energy’s Office of
Science, the Electric Power Research Institute, and other sponsors of the Global
Energy Technology Strategy Program (GTSP; http://www.pnl.gov/gtsp/index.
stm) for their support of the MiniCAM integrated assessment modeling framework.
The authors would like to thank David Belzer and David Winiarski from Pacific
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Climate Policy and the Long-Term Evolution of the U.S. Buildings Sector / 171
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buildings module.
Appendix
Table A-1. Summary of Technology Efficiencies (Energy Out / Energy In)
in the Residential Sector, in Reference and Advanced Scenarios
Reference
Advanced
Service
Technology
Building shell
Unit
W/m2
2005
0.232
2050
0.182
2095
0.150
2050
0.163
2095
0.125
Heating
Gas furnace
Gas heat pump
Electric furnace
Electric heat pump
Oil furnace
Wood furnace
out / in
out / in
out / in
out / in
out / in
out / in
0.82
n/a
0.98
2.14
0.82
0.40
0.90
n/a
0.99
2.49
0.86
0.42
0.97
n/a
0.99
2.79
0.93
0.44
Same as Ref
1.75
2.45
Same as Ref
2.94
4.12
Same as Ref
Same as Ref
Cooling
Air conditioning
out / in
2.81
3.90
4.88
4.59
Water
Heating
Gas water heater
Gas HP water heater
Electric water heater
Electric HP water heater
Oil water heater
out / in
out / in
out / in
out / in
out / in
0.56
n/a
0.88
n/a
0.55
0.61
n/a
0.93
2.46
0.56
0.64
n/a
0.97
2.75
0.59
0.79
0.88
1.75
2.45
Same as Ref
2.75
3.45
Same as Ref
Lighting
Incandescent lighting lumens/W
Fluorescent lighting lumens/W
Solidstate lighting
lumens/W
14
60
100
15
75
112
16
94
125
Same as Ref
Same as Ref
156
245
7.19
Appliances Gas appliances
Electric appliances
indexed
indexed
1.00
1.00
1.12
1.23
1.26
1.38
Same as Ref
1.44
2.01
Other
indexed
indexed
indexed
1.00
1.00
1.00
1.12
1.08
1.12
1.25
1.21
1.25
Same as Ref
1.40
1.96
Same as Ref
Other gas
Other electric
Other oil
172 / The Energy Journal
Table A-2. Summary of Technology Efficiencies (Energy Out / Energy In)
in the Commercial Sector, in Reference and Advanced Scenarios
Reference
Advanced
Service
Technology
Building shell
unit
W/m2
2005
0.281
2050
0.217
2095
0.194
2050
0.214
2095
0.164
Heating
Gas furnace
Gas heat pump
Electric furnace
Electric heat pump
Oil furnace
Wood furnace
out / in
out / in
out / in
out / in
out / in
out / in
0.76
n/a
0.98
3.10
0.77
0.40
0.84
n/a
0.99
3.56
0.81
0.42
0.94
n/a
0.99
3.98
0.85
0.44
Same as Ref
1.75
2.45
Same as Ref
3.95
4.41
Same as Ref
Same as Ref
Cooling
Air conditioning
out / in
2.80
3.87
4.84
4.42
Water
Heating
Gas water heater
Gas HP water heater
Electric water heater
Electric HP water heater
Oil water heater
out / in
out / in
out / in
out / in
out / in
0.82
na
0.97
na
0.76
0.93
na
0.98
2.46
0.80
0.93
na
0.98
2.75
0.83
Same as Ref
1.75
2.45
Same as Ref
2.75
3.45
Same as Ref
Lighting
Incandescent lighting lumens/W
Fluorescent lighting lumens/W
Solidstate lighting
lumens/W
14
76
100
15
95
112
16
119
125
Same as Ref
Same as Ref
156
245
Office
Office equipment
indexed
1.00
1.25
1.57
1.72
Other
Other gas
Other electric
Other oil
indexed
indexed
indexed
1.00
1.00
1.00
1.17
1.17
1.17
1.31
1.31
1.31
1.36
1.90
1.36
1.90
Same as Ref
6.92
2.41
Table A-3. Percent of Energy Consumption Assumed to Contribute To
Internal Gain Energy, by Service, and the Fraction of the
Year During Which Internal Gain Energy is Added to Cooling
Demands or Subtracted From Heating Demands
Residential
Heating
Cooling
Water Heating
Lighting
Residential Appliances
Residential Other
Commercial Office
Commercial Other
0%
0%
12%
80%
66%
86%
n/a
n/a
Commercial
Portion of year in operation
0%
0%
3%
92%
n/a
n/a
80%
17%
25%
10%
n/a
n/a
n/a
n/a
n/a
n/a