State Greenhouse Gas Emissions: Comparison and Analysis
Congressional research reportDec 5, 2007
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Prepared for Members and Committees of Congress
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Instituting policies to manage or reduce greenhouse gas (GHG) emissions would likely impact
different states differently. Understanding these differences may provide for a more informed
debate regarding potential policy approaches. However, multiple factors play a role in
determining impacts, including alternative design elements of a GHG emissions reduction
program, the availability and relative cost of mitigation options, and the regulated entities’
abilities to pass compliance costs on to consumers.
Three primary variables drive a state’s human-related GHG emission levels: population, per
capita income, and the GHG emissions intensity. GHG emissions intensity is a performance
measure. In this report, GHG intensity is a measure of GHG emissions from sources within a state
compared with a state’s economic output (gross state product, GSP). The GHG emissions
intensity driver stands apart as the main target for climate change mitigation policy, because
public policy generally considers population and income growth to be socially positive.
The intensity of carbon dioxide (CO2) emissions largely determines overall GHG intensity,
because CO2 emissions account for 85% of the GHG emissions in the United States. As 98% of
U.S. CO2 emissions are energy-related, the primary factors that shape CO2 emissions intensity are
a state’s energy intensity and the carbon content of its energy use.
Energy intensity measures the amount of energy a state uses to generate its overall economic
output (measured by its GSP). Several underlying factors may impact a state’s energy intensity: a
state’s economic structure, personal transportation use in a state (measured in vehicle miles
traveled per person), and public policies regarding energy efficiency.
The carbon content of energy use in a state is determined by a state’s portfolio of energy sources.
States that utilize a high percentage of coal, for example, will have a relatively high carbon
content of energy use, compared to states with a lower dependence on coal. An additional factor
is whether a state is a net exporter or importer of electricity, because CO2 emissions are attributed
to electricity-producing states, but the electricity is used (and counted) in the consuming state.
Between 1990 and 2000, the United States reduced its GHG intensity by 1.6% annually.
Assuming that population and per capita income continue to grow as expected, the United States
would need to reduce its GHG intensity at the rate of 3% per year in order to halt the annual
growth in GHG emissions. Therefore, achieving reductions (or negative growth) in GHG
emissions would necessitate further declines in GHG intensity.
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Introduction ..................................................................................................................................... 1
Greenhouse Gas Emission Drivers.................................................................................................. 2
Greenhouse Gas Emissions Intensity .............................................................................................. 4
Greenhouse Gas Emissions Intensity in the States.................................................................... 5
Carbon Dioxide Intensity and Its Drivers........................................................................................ 6
Energy Intensity ........................................................................................................................ 6
Economic Structure............................................................................................................. 7
Personal Transportation ...................................................................................................... 8
Public Policy ....................................................................................................................... 8
State Climate....................................................................................................................... 9
Gross State Product............................................................................................................. 9
Conclusions....................................................................................................................... 10
Carbon Content of Energy Use ............................................................................................... 10
Electricity Generation ........................................................................................................11
Electricity Exports/Imports............................................................................................... 12
Consequences of Differences in State Emissions Drivers in the Context of a Federal
Greenhouse Gas Emissions Reduction Program ........................................................................ 13
Greenhouse Gas Intensity Levels in the Context of an Emissions Reduction Program ................ 16
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Table 1. Comparison of GHG Emission Drivers for the 10 U.S. States with the Highest
GHG Emissions Levels in 2003 ................................................................................................... 3
Table 2. Average Annual Rates of Change for GHG Emissions and Drivers for the Entire
United States: 1990-2000 ............................................................................................................. 3
Table 3. States with the Five Highest and Five Lowest GHG Intensity Levels (2003)................... 5
Table 4. States with the Five Highest and Five Lowest Energy Intensity Levels (2003
data).............................................................................................................................................. 6
Table 5. States with High Percentages of Gross State Product Based on High- or LowEnergy Intensive Sectors (2003 data)........................................................................................... 7
Table 6. States with the Five Highest and Five Lowest Vehicle Miles Traveled Per Capita
(2003) ........................................................................................................................................... 8
Table 7. States With the Five Highest and Five Lowest Carbon Contents of Energy Use
(2003) ......................................................................................................................................... 10
Table 8. States with the Highest Percentage of In-State Electricity Generated from Coal
and Zero-Emission Energy Sources (2003).................................................................................11
Table 9. States with High Percentages of Exported and Imported Electricity in Terms of
Overall Energy Use (2003)......................................................................................................... 12
Table 10. GHG Emissions Intensity Average Annual (Negative) Growth Rates (19902003) for the 10 States with the Most GHG Emissions in 2003 ................................................ 17
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Table A-1. GHG Emissions and GHG Emissions Drivers for All 50 States, Listed
Alphabetically (2003 data) ......................................................................................................... 18
Table A-2. GHG Emissions and GHG Emissions Drivers for All 50 States, Ranked by
GHG Emissions (2003 data) ...................................................................................................... 20
Table A-3. Average Annual Growth Rates (1990-2003) for GHG Emissions and GHG
Emissions Drivers for All 50 States............................................................................................ 21
Table A-4. CO2 Emissions Intensity and CO2 Emissions Intensity Drivers for All 50
States, Listed Alphabetically (2003 data)................................................................................... 23
Table A-5. CO2 Emissions Intensity and CO2 Emissions Intensity Drivers for All 50
States, Ranked by CO2 Emissions Intensity (2003 data)............................................................ 25
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Appendix. Select Tables with Data for All 50 States..................................................................... 18
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Author Contact Information .......................................................................................................... 26
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There is a broad agreement in the scientific community that the earth’s climate is changing and
that the primary cause over the past few decades is an increasing concentration of greenhouse
gases (GHGs) in the atmosphere. Most climate scientists have concluded that human activities—
e.g., fossil fuel combustion, land clearing, and industrial and agricultural operations—have played
a central role in climate change, particularly in recent decades.1
A variety of efforts that seek to address climate change are currently underway or being
developed on the international, national, and sub-national level (e.g., individual state actions or
regional partnerships). These efforts cover a wide spectrum, from research initiatives to GHG
emission reduction regimes.2
If Congress establishes a federal program to manage or reduce GHG emissions, the emission
requirements would likely impact different states differently. However, predicting the different
impacts of policies is a complicated task, because multiple factors play a role. Such factors
include alternative design elements of a GHG emissions reduction program, the availability and
relative cost of mitigation options, and the regulated entities’ abilities to pass compliance costs on
to consumers.
Underlying climate change policy discussions are GHG emissions and the factors that determine
their levels and growth. One of the primary factors is GHG emissions intensity. In this report,
GHG emissions intensity is a measure of GHG emissions from state sources divided by the state’s
overall economic output, or gross state product.3 Because carbon dioxide (CO2) is the primary
GHG in the vast majority of states, the report focuses on CO2 emissions intensity and its
determining factors. These factors vary significantly across state lines. An analysis of these
factors and how they compare among the states may contribute to a more informed debate
regarding potential policy approaches.
1
This report does not address the debates associated with climate change science or the role of human activity in
climate change. For a discussion of these issues, see CRS Report RL33849, Climate Change: Science and Policy
Implications, by (name redacted).
2
See CRS Report RL33826, Climate Change: The Kyoto Protocol, Bali "Action Plan," and International Actions, by
(name redacted) and (name redacted); CRS Report RL31931,
Climate Change: Federal Laws and Policies Related to
Greenhouse Gas Reductions, by (name redacted) and (name redacted); CRS Report RL33812, Climate Change: Action
by States To Address Greenhouse Gas Emissions, by (name redacted).
3
GHG emissions intensity is a performance measure. When looking at emissions on an economy-wide scale, gross
domestic product (GDP) or gross state product (GSP) is typically used. However, other economic outputs, such as a
tons of steel or cement, may be used to analyze the emissions intensity of specific sources or economic sectors. A
higher GHG intensity value (compared to other states) indicates that a state generates more emissions per economic
output (i.e., GSP) than other states.
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Greenhouse Gas Emissions Data in This Report
Greenhouse gas (GHG) emissions data can be described in several different ways, which may lead to inconsistencies
when comparing data from different sources.
In this report, GHG emissions include the following gases: carbon dioxide (CO ), nitrous oxide, methane,
perfluorocarbons, hydrofluorocarbons, and sulfur hexafluoride. Only emissions from human-related activities are
included. To examine the emissions data in aggregate, data from the six gases are converted (based on the global
warming potential of the gas) into a single unit of measure: million metric tons of carbon dioxide-equivalents
(MMTCO E). One million metric tons equals one teragram (10 grams), a measure used by some sources to describe
emission levels. Moreover, other reports may provide emissions data in metric tons of carbon-equivalents. To
convert carbon-equivalents to CO -equivalents, multiply carbon-equivalents by 44/12.
Unless otherwise noted, the data in this report come from the World Resources Institute’s Climate Analysis
Indicators Tool (CAIT). The CAIT state data are compiled using the Environmental Protection Agency’s State
Inventory Tool and default data for each state. Many states have prepared their own emissions inventories with more
precise data, but most of these inventories only cover 1990 emissions. Although there may be slight data
discrepancies between CAIT and the state inventories, CAIT serves as a homogeneous data source, providing
estimates for all states and all GHGs through 2003.
This report does not include land use, land use changes, or forestry (LULUCF) in emissions or intensity data. Data
from these sources are generally considered less robust than data from other sources.
2
12
2
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Three broad factors influence GHG emission levels in a nation or state: population, per capita
income, and GHG emissions intensity of the economy. A state’s GHG emission levels can be
approximated by multiplying together these three variables. Equation 1 expresses this
relationship:
Equation 1:
GHG Emissions
=
(MMTCO2E)
Population
(Persons)
X
Per Capita Income
(GSP/Person)
X
GHG Intensity
(MMTCO2E / GSP)
The equation indicates that each of the variables can play a significant role in shaping a state’s
GHG emissions. For instance, if one of these variables increases, while the other two remain
constant, GHG emissions will increase. The three emissions drivers do not operate independently
of one another: a change in one variable may influence another variable.4
The three variables—population, per capita income, and GHG emissions intensity—differ
substantially among the states and play varying roles when determining a state’s GHG emissions.
Table 1 shows this relationship for the 10 U.S. states with the highest GHG emission levels in
2003. These 10 states accounted for almost 50% of total U.S. GHG emissions in 2003. A similar
table for all 50 states is included in the Appendix to this report.
4
For further discussion see CRS Report RL33970, Greenhouse Gas Emission Drivers: Population, Economic
Development and Growth, and Energy Use, by (name redacted) and (name redacted); see also Kevin Baumert, et al., 2005,
Navigating the Numbers: Greenhouse Gas Data and International Climate Policy, World Resources Institute.
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. Comparison of GHG Emission Drivers for the 10 U.S. States with the
Highest GHG Emissions Levels in 2003
Table 1
State
GHG Emissions
Population
Per capita Income
MMTCO2E
in 1,000s
GSP/person
GHG Intensity
TCO2E / $million
of GSP
Texas
782
22,134
34,837
1,015
California
453
35,466
37,787
338
Pennsylvania
301
12,351
33,224
734
Ohio
299
11,438
33,174
1,308
Florida
271
16,982
30,548
523
Illinois
269
12,650
37,818
561
Indiana
269
6,192
33,082
1,315
New York
244
19,238
41,731
304
Michigan
212
10,068
34,260
614
Louisiana
210
4,481
29,375
1,591
Average for all
50 States
132
5,702
35,404
921
Prepared by Congressional Research Service (CRS) with data from the World Resources Institute
(WRI), Climate Analysis Indicators Tool.
Source:
Table 1 provides a snapshot of information. Annual changes (or growth rates, which can be either
positive or negative) in the GHG emission drivers will influence whether GHG emissions rise or
fall. In order to reduce emissions, the sum of the three variable rates—population, income, and
intensity—must be negative. To put this goal in perspective, consider the annual average rates of
change for the United States between 1990 and 2000 (Table 2):
. Average Annual Rates of Change for GHG Emissions and Drivers for the
Entire United States: 1990-2000
Table 2
GHG Emissions
1.4%
Population
=
1.2%
Per Capita Income
+
1.8%
GHG Intensity
+
-1.6%
Source: Prepared by CRS with data from the WRI, Climate Analysis Indicators Tool.
Table 2 reveals that the growth rates were positive for both U.S. population and per capita
income during the 1990s. Although GHG intensity decreased during that time period, the decline
was not enough to offset the increases from the other two variables, and GHG emission levels
increased by 1.4% annually.
Annual growth rates for GHG emissions and the emission drivers vary significantly among the
U.S. states. The Appendix contains a table listing the growth rates for all 50 states. In some
states, GHG intensity declines were well above average declines, but these annual reductions
were offset by increases in population, per capita income, or a combination of the two.
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Of the three GHG emission drivers—population, per capita income, and GHG emissions
intensity—the most relevant in terms of climate change policy is GHG intensity. Decreases in
population and/or per capita income would contribute to lowering a state’s GHG emissions.
However, growth in population and personal income is generally considered a positive social
outcome, and policies that would seek to directly limit these emissions drivers are essentially
outside the bounds of public policy.
GHG intensity is a simple measure of GHG emissions per unit of output. Although most GHG
reduction regimes address actual emissions,5 the national target in the United States—as
announced by the Bush Administration—aims to reduce the GHG emissions intensity of the
national economy. In 2002, the Bush Administration set a voluntary target of reducing the ratio of
U.S. GHG emissions to the U.S. Gross Domestic Product (GDP) by 18% by 2012. According to
the Administration, meeting this target would reduce intensity beyond that of intensity reductions
expected under a business-as-usual scenario. Based on data available in 2002, GHG emissions
intensity was projected to decline by 14% under a business-as-usual scenario. Critics of the
Administration’s intensity target have pointed out that (1) the intensity target is more precisely
quantified at 17.5%;6 and (2) more recent data indicate that the U.S. intensity declined by 16.2%
between 1990 and 2002. Thus, some observers have described the effect of the intensity target as
“negligible.”7
Intensity targets are sometimes viewed with skepticism, because the intensity target proponents
may imprecisely describe (or overstate) how reductions in emissions intensity would affect actual
emission levels.8 For example, the Administration has stated that meeting the U.S. emissions
intensity target would lead to GHG emission reductions.9 Arguably, such a description can be
misleading, because the reductions would occur within the context of increasing U.S. emissions.
In other words, U.S. emissions would continue to increase, but if the intensity target is met, the
emissions increase would be less than business-as-usual. Moreover, there is some uncertainty as
to whether the “reductions” will be achieved at all. The Administration’s projected reductions are
based on GDP forecasts. If the GDP increases at higher than projected rates, absolute emissions
can increase beyond business-as-usual scenario, while still meeting the intensity target.
Although some have questioned the environmental efficacy of intensity targets (i.e., their ability
to lower GHGs), the effectiveness of an emissions target depends primarily on its stringency, not
5
For example, the European Union’s Emissions Trading Scheme and the Kyoto Protocol require actual emission
reductions. Reduction programs under development at the state level also require actual reductions (e.g., California and
the Regional Greenhouse Gas Initiative).
6
Although the Administration’s supporting document uses 18%, the document also states that the goal is to reduce
intensity from 183 to 151 (metric tons of carbon equivalent per million dollars of gross domestic product), a 17.5%
reduction.
7
See Herzog, Timothy, et al., 2006, Target Intensity: An Analysis of Greenhouse Gas Intensity Targets, WRI Report,
pp.15-16.
8
See, Pew Center on Global Climate Change, Analysis of President Bush’s Climate Change Plan, at
http://www.pewclimate.org/policy_center/analyses/response_bushpolicy.cfm.
9
The Executive Summary describing the intensity target states: “the President’s commitment will achieve 100 million
metric tons of reduced emissions in 2012 alone, with more than 500 million metric tons in cumulative savings over the
entire decade.” See http://www.whitehouse.gov/news/releases/2002/02/climatechange.html.
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whether it applies to emissions intensity or absolute emissions.10 Meeting an aggressive intensity
target can result in actual emission reductions, if the intensity decrease outpaces the combined
increases in population and per capita income. In fact, if the United States is to reduce its
emissions, while maintaining population and per capita income growth rates, a stringent reduction
in GHG emissions intensity would be required.
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The GHG intensity levels display a considerable range among the 50 states. Table 3 lists the
states with the five highest and five lowest GHG intensity values (based on 2003 data). The table
shows that the ends of the spectrum differ by more than an order of magnitude.
Table 3. States with the Five Highest and Five Lowest GHG Intensity Levels (2003)
States with Five
Highest GHG Intensity
Levels
GHG Intensity
(TCO2E / $million of
GSP)
Wyoming
West Virginia
North Dakota
Montana
Alaska
Average for all 50 states: 979
3,799
3,097
2,885
1,755
1,662
Source:
States with Five Lowest
GHG Intensity Levels
Connecticut
New York
Massachusetts
California
Rhode Island
GHG Intensity
(TCO2E / $million of
GSP)
286
304
327
338
349
Prepared by CRS with data from the WRI, Climate Analysis Indicators Tool.
What factors determine a state’s intensity and lead to the wide variances among the states? In the
United States, carbon dioxide (CO2) emissions have historically accounted for 85% of the
nation’s GHG emissions, excluding land use changes and forestry. In all but four states,11 CO2
emissions accounted for at least 80% of the state’s GHG emissions in 2003. As the dominant
GHG, the intensity of CO2 emissions significantly impacts the overall GHG intensity. If Table 3
were to rank states based on CO2 emissions intensity, the results would be nearly identical.12 Due
to the dominance of CO2 emissions in the vast majority of states, this report focuses on its role in
driving overall GHG emissions intensity, and thus GHG emissions. (Note that the Appendix
contains a table listing CO2 emissions intensity and its drivers for all 50 states).
10
See Herzog, Timothy, et al., 2006, Target Intensity: An Analysis of Greenhouse Gas Intensity Targets, WRI Report,
pp.15-16.
11
The four states that emit relatively large percentages of non-CO2 GHG emissions include South Dakota (47%), Idaho
(38%), Nebraska (32%), and Iowa (26%).
12
Wyoming, West Virginia, North Dakota, Alaska, and Louisiana rank 1st through 5th (Montana 6th); the five states
with the lowest CO2 emissions intensity are identical, but California and Massachusetts switch positions.
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Approximately 98% of the U.S. CO2 emissions in 2003 were from energy use.13 The primary
factors that determine CO2 emissions intensity in a state are its energy intensity and the carbon
content of its energy use (or fuel mix).14 The relationship between CO2 emissions intensity,
energy intensity and carbon content of energy use is shown in Equation 2.
Equation 2:
CO2 Emissions Intensity
=
(CO2/GSP)
Energy Intensity
X
Carbon Content of Energy
(toe/GSP)
(TCO2/toe)
Note: The units cited above include gross state product (GSP), tons of carbon dioxide-equivalent (TCO2), and
tons of oil equivalent (toe).
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Energy intensity is the amount of energy a state consumes—typically measured in tons of oil
equivalent (toe)—per its level of economic output (gross state product). Table 4 shows the states
with highest and lowest energy intensity levels in 2003. A comparatively high energy intensity
figure indicates a states uses more energy (toe) per economic output (GSP) than other states.
There is wide gulf (a factor of five) between states at either end of the spectrum.
Multiple factors influence a state’s energy intensity. This section of the report compares energy
intensity levels with five potential drivers: economic structure, transportation use, public policy,
state climate, and gross state product. An overall assessment of the factors and their interactions
with energy intensity is provided at the end of this section.
Table 4. States with the Five Highest and Five Lowest Energy Intensity Levels (2003
data)
States with Five Highest
Energy Intensities
Energy Intensity (toe
/ $million of GSP)
Louisiana
Alaska
Wyoming
North Dakota
West Virginia
Average for all 50 states: 0.29
0.71
0.69
0.61
0.50
0.56
Source:
States with Five Lowest
Energy Intensities
New York
Connecticut
Massachusetts
California
Rhode Island
Energy Intensity (toe
/ $million of GSP)
0.13
0.14
0.14
0.15
0.16
Prepared by CRS with data from the WRI, Climate Analysis Indicators Tool.
13
The other portion (2.5%) came from industrial activity. This estimate excludes land use changes. WRI, Climate
Analysis Indicators Tool.
14
When non-CO2 gases—e.g., methane, nitrous oxide—are part of the GHG intensity calculus, other factors come into
play. Approximately 50% of non-CO2 GHGs are generated by agricultural activities, and these emission levels may be
influenced by changes in related economic markets.
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A state’s economic structure likely plays an important role. For instance, a primary economic
factor is whether the state’s economy is based more on high-energy industries15 or low-energy
industries.16 A state with a GSP based on a high ratio of high-energy industries is likely to have a
higher overall energy intensity than a state with proportionately more low-energy sectors (e.g.,
finance, professional services).
Table 5 lists (1) the five states with the highest percentages of their GSP resulting from highenergy intensive industries; and (2) the five states with the highest percentages of their GSP based
on low-energy intensive industries. A comparison of Table 4 and Table 5 indicates a
correspondence between energy intensity and a state’s economic structure. The top-three highest
energy intensity states are also the top-three in percentage of their GSP from high-energy sectors;
three of the top-five lowest energy intensity states are also among the top-six states for GSP based
on low-energy sectors. Of the 25 states with the highest percentages of their GSPs based on highenergy sectors, 19 of these states are ranked in the top-25 for energy intensity.
Table 5. States with High Percentages of Gross State Product Based on High- or
Low-Energy Intensive Sectors (2003 data)
State
Percentage of
GSP from
High-Energy
Sectors0
Wyoming
Louisiana
Alaska
West Virginia
Texas
50-State Average
32
23
22
17
14
7%
State
Delaware
Hawaii
New York
Maryland
Connecticut / Rhode Island
50-State Average
Percentage of
GSP from
Low-Energy
Sectorsb
79
76
75
71
70
61%
Prepared by CRS with data from Bureau of Economic Analysis, at http://bea.gov/index.htm.
a. For this table, as for the rest of this report, high-energy sectors include the following North American
Industry Classification System (NAICS) primary and secondary groupings: mining, utilities, primary metal
manufacturing, paper manufacturing, petroleum and coal products manufacturing, and chemical
manufacturing.
b. For this table, as for the rest of this report, low-energy sectors include the following North American
Industry Classification System (NAICS) primary groups: information; finance and insurance; real estate;
professional/technical services; management of companies; administration and waste services; education;
health care and social assistance; arts, entertainment, recreation; accomodation and food; other services;
and government.
Source:
15
For this report, high-energy sectors include the following North American Industry Classification System (NAICS)
primary and secondary groupings: mining, utilities, primary metal manufacturing, paper manufacturing, petroleum and
coal products manufacturing, and chemical manufacturing.
16
For this report, low-energy sectors include the following North American Industry Classification System (NAICS)
primary groups: information; finance and insurance; real estate; professional/technical services; management of
companies; administration and waste services; education; health care and social assistance; arts, entertainment,
recreation; accomodation and food; other services; and government.
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The transportation sector accounts for over a quarter (28%) of total energy consumption in the
United States.17 Within the transportation sector, personal transportation—i.e., cars, light trucks,
and motorcycles—accounts for the majority of energy use (64% in 2004).18 A measure that tracks
personal transportation use in a state is vehicle miles traveled (VMT) per person. A state’s per
capita VMT is another factor that likely impacts a state’s energy intensity.
As Table 6 indicates, there is a significant range between states with the most and least
VMT/person. The five states—New York, Hawaii, Alaska, Rhode Island, and New Jersey—on the
low end of the spectrum averaged 7,598 VMT/person in 2003; the five states—Wyoming,
Vermont, Alabama, Oklahoma, and Mississippi—on the other end averaged 14,186 VMT/person
in 2003.19
Table 6. States with the Five Highest and Five Lowest Vehicle Miles Traveled Per
Capita (2003)
States of Highest Rank
Vehicle Miles
States of Lowest
Vehicle Miles
Traveled Per
Rank
Traveled Per
Capita
Wyoming
Vermont
Oklahoma
Alabama
Mississippi
Average for all 50 states: 10,571
Source:
18,367
13,432
13,048
13,045
13,036
Capita
New York
Hawaii
Alaska
Rhode Island
New Jersey
7,020
7,476
7,630
7,783
8,083
Prepared by CRS with data from the WRI, Climate Analysis Indicators Tool.
There is a general correspondence between a state’s per capita VMT and energy intensity. Of the
25 states with the lowest energy intensity levels, 17 of them are also in the group of 25 states with
the fewest VMT/person.20 However, there are several dramatic exceptions to this correlation. For
example, Alaska ranks third for lowest VMT/person, but second for highest energy intensity.
Conversely, Vermont has the second highest VMT/person, but has a relatively low energy
intensity (ranks 15th). Such exceptions demonstrate that multiple factors play a role and that
energy intensity drivers may have varying impacts in different states.
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States can seek to reduce energy intensity through public policy action. Some states have enacted
policies or regulations that are more stringent or broader in scope than federal standards,
17
The industrial (32%), residential (22%), and commercial (18%) sectors consumed the remaining proportions. See
CRS Report RL31849, Energy: Selected Facts and Numbers, by (name redacted) and (name redacted).
18
U.S. Department of Energy, 2007, Transportation Energy Data Book (Edition 26), table 2.6.
19
Based on WRI CAIT data.
20
Likewise, of the 25 states with higher energy intensity levels, 17 are also among the 25 states with higher
VMT/person.
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supporting improvements in efficiency standards for electricity generation, buildings, and/or
appliances. For example, 12 states have established energy efficiency standards for appliances
that are more stringent than federal requirements.21 The American Council for an Energy-Efficient
Economy (ACEEE) published an energy efficiency scorecard that ranks the states based on their
energy efficiency policies.22 The ACEEE scores show a relationship with highest and lowest
energy intensity levels among the states. Of the states with low energy intensity levels, all were
ranked highly by the ACEEE scorecard.23 Conversely, the states with high energy intensities
received low ACEEE rankings.24 In addition, of the 25 states ranked highly by ACEEE for public
policy, 19 of the states are among the 25 states with the lowest energy intensities.
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Natural factors, such as a state’s climate, may influence energy intensity in some states, but the
degree of influence is difficult to determine. A state’s overall climate helps determine the amount
of energy needed to heat or cool residential, commercial, and industrial buildings. A measurement
used to evaluate this concept is the “degree day,” which includes heating degree days (HDDs) and
cooling degree days (CDDs).25 In the United States, HDDs outnumber CDDs by a factor of five
to one, thus states in colder climates generally have the most degree days.
An examination of energy intensity and degree days for all 50 states does not indicate an overall
correlation between these two measures. While several states rank highly for both degree days
and energy intensity,26 many of the states with low energy intensities—e.g., New York,
Connecticut, and Massachusetts—are among the top 25 states in terms of degree days. In
addition, many of the states with few degree days are among the top 25 states in terms of energy
intensity. The lack of an overall correlation between degree days and energy intensity does not
rule out the influence of climate. Climate may play a supplemental role that is perhaps obscured
by more influential factors.
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The size of a state’s economy (the denominator of energy intensity) can be an important part of
the equation. Of the states with the 25 lowest GSPs, 17 of the states are in the top-25 for energy
intensity. A sudden increase/decrease in a variable that alters energy consumption will likely yield
21
EPA, Map: State Energy Efficiency Actions - State Appliance Efficiency Standards (as of 1/1/2007), at
http://www.epa.gov/cleanenergy/stateandlocal/activities.htm.
22
American Council for an Energy-Efficient Economy (ACEEE), 2007, The State Energy Efficiency Scorecard for
2006, at http://aceee.org.
23
Including ties, California and Connecticut ranked first; Massachusetts ranked 4th; New York ranked 7th; and Rhode
Island 9th.
24
Louisiana was ranked 40th; Alaska ranked 41st; Wyoming ranked 49th; North Dakota ranked 51st; and West Virginia
ranked 35th.
25
The “degree-day” is a metric used to assess the demand for heating and/or cooling needs. Both heating degree days
(HDDs) and cooling degree days (CDDs) are based on differences from a temperature of 65 °F, a base temperature
considered to have neither heating nor cooling needs. For example, 10 HDDs are generated for a day with an average
daily temperature of 55 °F. Higher HDDs (e.g., Alaska) and CDDs (e.g., Florida) indicate greater heating or cooling
needs, respectively.
26
Three of the five states (see Table 6) with high energy intensities—Wyoming, Alaska, and North Dakota—are in the
top five for number of degree days.
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a more pronounced effect in states with lower GSPs. In contrast, the effects of drastic changes
may be less pronounced in states with larger GSPs. Four of the states with high energy intensities
rank near the bottom in terms of absolute GSP (in 2003): Alaska (45th), Wyoming (50th), North
Dakota (48th), and West Virginia (40th). Conversely, California and New York, which are among
the top five states with lowest energy intensities, are ranked first and second, respectively.
However, in the other states listed above (Table 4), the size of GSP may play a lesser role. For
example, Louisiana, the state with the highest energy intensity, ranked 24th for total GSP in 2003.
ȱ
Other than a state’s climate, each of the factors discussed above shows a relationship with energy
intensity. Most of the states with high energy intensity levels are at the extreme end of the range
for more than one of the underlying factors; many of the states with low intensities also have
corresponding rankings with one or more underlying factors. However, there are sometimes
dramatic exceptions. The exceptions highlight the diversity among the states and indicate the
difficulty in making conclusions that apply in all states.
In addition, for states that have multiple factors steering towards higher energy intensity, it is
difficult to determine which factor is dominant. Perhaps the most extreme example of this
difficulty is Wyoming, which has the third highest energy intensity. Wyoming ranks first for
percentage of energy-intensive industries, first for VMT/person, fourth for number of degree
days, last (50th) for absolute GSP, and 49th in ACEEE’s public policy scorecard. All of these
rankings point towards increased energy intensity, thus creating a challenge to identify the
primary influence in states such as Wyoming.
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The second driver of CO2 emissions intensity is the carbon content of energy use in a state.
Energy sources vary in the amount of carbon released per unit of energy supplied (e.g., British
Thermal Unit). A state that uses a greater proportion of high-carbon energy sources will have
higher CO2 emissions per unit of energy use than a state that utilizes more low-carbon energy
sources. Table 7 shows the states with the five highest and five lowest carbon contents of energy
use (measured in tons of CO2 per tons of oil equivalent, toe).
Table 7. States With the Five Highest and Five Lowest Carbon Contents of Energy
Use (2003)
States with Highest
Carbon Content of
States with Lowest
Carbon Content of
Carbon Contents of
Energy Use (TCO2 /
Carbon Contents of
Energy Use (TCO2 /
Energy Use
1000 toe)
Energy Use
1000 toe)
West Virginia
Wyoming
North Dakota
Montana
Utah
Average for all 50 states: 2,527
Source:
5,780
5,460
4,770
3,480
3,470
Idaho
Oregon
Washington
Vermont
Connecticut
1,210
1,540
1,660
1,660
1,890
Prepared by CRS with data from the WRI, Climate Analysis Indicators Tool.
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A state’s electricity sector is especially important in the context of a state’s carbon content of
energy use. The electricity sector produces a substantial portion of CO2 emissions in many states
and is the highest emitting sector in the United States, accounting for approximately 40% of U.S.
CO2 emissions.
Electricity can be generated from a variety of energy sources, which vary significantly by their
ratio of CO2 emissions per unit of energy. A coal-fired power plant emits almost twice as much
CO2 (per unit of energy) as a natural gas-fired facility.27 Some energy sources—e.g.,
hydropower,28 nuclear, wind, or solar—do not directly release any CO2 emissions. Although the
transportation sector contributes a significant percentage of CO2 emissions in most states (and
33% of U.S. CO2 emissions in 2003—the second highest sector), this sector utilizes a more
homogenous fuel portfolio. In contrast to fuels used to generate electricity, transportation fuels do
not demonstrate as much variance in their CO2 emissions per unit of energy.29 Thus for the
purposes of examining a state’s carbon content of energy use, this report focuses on the electricity
sector.
Compared to the other states, the five states with high carbon contents in their fuel mix utilized a
relatively large percentage of coal for electricity generation in 2003. Conversely, the five states
with the lowest levels generated electricity from a relatively high percentage of zero-emission
energy sources in 2003. In general, hydropower and nuclear power dominate the zero-emission
subcategory in terms of use, but the zero-emission sources also include wind, solar, geothermal,
and the sources that fall within the Energy Information Administration’s (EIA) “other
renewables” category.30 Table 8 lists the states that utilized the greatest percentages of coal to
generate electricity and the states with the highest percentages of zero-emission energy sources.
Table 8. States with the Highest Percentage of In-State Electricity Generated from
Coal and Zero-Emission Energy Sources (2003)
State
Percentage of In-State
Electricity Generated from
Coal
State
Percentage of In-State Electricity
Generated from Zero-Emissions Energy
Sources
West
Virginia
Wyoming
98%
Vermont
100%
97%
Idaho
96%
27
The Energy Information Administration website provides a table listing the amount of CO2 generated per unit of
energy for different energy sources, at http://www.eia.doe.gov/oiaf/1605/coefficients.html.
28
Some studies have found that hydroelectric dams may be a source of GHG emissions. Dam reservoirs can emit
methane through plant decomposition, but this effect varies by location, being more pronounced in warmer climates.
See e.g., World Commission on Dams, 2000, The Report of the World Commission on Dams, at http://www.dams.org/
report/.
29
In 2003, petroleum accounted for 97% of the energy consumed in the U.S. transportation sector. EIA, Energy Power
Monthly, March 2004, Table 2.5, at http://www.eia.doe.gov/.
30
These additional sources include wood and other wood waste, black liquor, biogenic municipal solid waste, landfill
gas, sludge waste, agriculture byproducts, and other biomass (EIA, Electric Power Monthly, March 2004, Table
1.13B). Although these sources do yield CO2 emissions when used as fuels, their combustion does not provide
additional CO2 emissions to the atmosphere (i.e., they would have produced CO2 emissions at some point via natural
processes). Thus, for this report they are counted as zero-emission energy sources.
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State
Percentage of In-State
Electricity Generated from
Coal
State
Percentage of In-State Electricity
Generated from Zero-Emissions Energy
Sources
Indiana
North
Dakota
Utah
94%
94%
Washington
Oregon
82%
70%
94%
New
Hampshire
66%
Prepared by CRS with data from Energy Information Administration, Electric Power Monthly (March
2004), at http://www.eia.doe.gov/.
Source:
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Another important factor that affects a state’s carbon content of energy use is whether the state is
a net importer or exporter of electricity. States consume fuels (e.g., coal, natural gas, etc.) to
generate electricity, but the electricity may be exported to and used in another state. The method
for accounting for these exchanges influences the level of a state’s carbon content of energy use.
In the above carbon content of energy data (Table 7), if one state uses an energy source (e.g.,
coal) to generate electricity and then sells the electricity to a consumer in a second state, the CO2
emissions are attributed to the generating state, but the energy use is attributed to the consuming
state.31
Table 9 lists the states in which electricity exports accounted for high percentages of energy use.
Likewise, the table lists the states in which imported electricity accounted for high percentages of
energy use. The import/export factor is especially prominent for states with high carbon content
levels. The top four states for carbon content of energy use in 2003—West Virginia, Wyoming,
North Dakota, and Montana—exported substantial portions of electricity in that year. Of the five
states with low carbon content levels, the import/export factor appears most relevant in Idaho,
where imported electricity accounted for 41% of its total energy use in 2003.
Table 9. States with High Percentages of Exported and Imported Electricity in Terms
of Overall Energy Use (2003)
State
Percentage of
Energy Consumed
That Is Exported
Electricity
West Virginia
Wyoming
North Dakota
44%
42%
36%
State
Idaho
Delaware
Rhode Island
Percentage of
Energy Consumed
That Is Imported
Electricity
41%
28%
22%
31
From a mathematical perspective, in a net exporting state the numerator (tCO2) of the equation (tCO2 / toe) would
increase, but the denominator (toe) would remain the same. The reverse would occur in importing states.
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State
Percentage of
Energy Consumed
That Is Exported
Electricity
Montana
New Hampshire
28%
23%
State
Maryland
Virginia
Percentage of
Energy Consumed
That Is Imported
Electricity
20%
17%
Prepared by CRS with data from Energy Information Administration, State Energy Data System
http://www.eia.doe.gov/emeu/states/_seds.html.
Source:
Some may argue that this characteristic of the data artificially inflates the carbon content of
energy use in exporting states, while artificially lowering the measure in states that import a
significant amount of electricity. Consider Wyoming and Idaho, two states at opposite extremes of
the carbon contents of energy use range. Two coal-fired power plants located in Wyoming are
partially owned by electricity providers that serve customers in Idaho. Idaho customers are
receiving some amount of coal-fired electricity from Wyoming (and Oregon and Nevada).32 This
electricity is counted as energy use in Idaho, while the CO2 emissions are attributed to Wyoming
(or Oregon or Nevada).
From another perspective, the example is less a critique of the carbon content of energy measure,
and more a highlight of how electricity generation and use is measured. There is no system in
place to physically track electricity upon generation. Therefore, it is impossible to precisely
attribute imported electricity to its energy source.33 Moreover, exported electricity may come
from energy sources other than coal. States may export electricity generated from low- or zerocarbon energy sources, such as hydropower or nuclear. This factor adds another layer of
complexity to the accounting. As the above Wyoming/Idaho example demonstrates, rough
approximations might be established based on ownership data, but it may be difficult (if not
impossible) to precisely assign the CO2 emissions from an exporting state to the importing state.
Thus, states that appear to be using low-carbon energy sources, may be importing high-carbon
energy, in the form of electricity.
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As noted above, the states have, in some cases, vastly different levels of GHG emissions intensity
and related underlying variables. If Congress were to enact a federal GHG emissions reduction
program, these differences may lead to a wide range of impacts in the states. The range of impacts
would depend on the logistics of the emissions reduction program and the ability of regulated
entities to spread compliance costs.
32
Idaho Power, which serves customers in Idaho, is a partial owner of coal-fired power plants in these states. See EIA,
Annual Electric Generator Report (Database 860), at http://www.eia.doe.gov; see also http://www.idahopower.com.
33
Per telephone conversation with EIA official, July 30, 2007.
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If Congress creates a mandatory GHG emissions reduction regime, the program would assign
(directly or indirectly) a cost to emissions of carbon (or carbon-equivalents in the case of some
GHGs). The stringency, scope, and design of the reduction regime would play a large role in
determining costs and how the costs are distributed. For instance, Congress could include specific
provisions—e.g., a safety-valve or revenue recycling—that would control costs or ease the
burden on particular groups.34
Regardless of how Congress might design a GHG reduction program, a mandatory GHG
reduction regime would affect states differently. In particular, the states’ different energy
intensities and carbon content of energy use indicate the states would experience different effects.
States with relatively high levels of carbon content in their energy use (Table 7) would likely see
higher energy prices. These states typically use a high percentage of coal to generate electricity,
thus electricity prices would likely increase in these states.35 The consumers’ responses to these
price increases would help determine impacts. Consumers may choose to conserve energy use or
switch to alternative sources. The carbon price imposed by the emission reduction regime would
provide incentives to switch from high-carbon to low-carbon fuel (e.g., from coal to natural gas).
However, such a switch may be limited by the technology and infrastructure existing in a state,
particularly in the electricity generation sector. Conventional coal-fired power plants in operation
today, which account for approximately 50% of all electricity generation, cannot simply switch to
another fuel source.
The producers of coal-fired electricity may be able to pass along the additional carbon costs to
consumers, but some state regulations may hinder a company’s ability to include the additional
costs in electricity prices. Differences in the states’ regulatory structures may influence which
groups ultimately pay for the additional carbon costs. In states with tighter regulatory control over
prices, power companies may bear a relatively higher cost; in other states, consumers of
electricity may bear a higher percentage of the costs, where companies are less constrained in
passing costs along to customers in the form of higher prices.
Depending on particular design elements of the emissions reduction program, some of these
potential disproportionate effects might be alleviated. For example, if producers are expected to
pay a higher percentage of the additional carbon costs, some of the emission allowances might be
provided for free. If consumers are anticipated to pay a higher proportionate cost, the allowances
could be auctioned. The auction’s revenues could be returned to consumers, particularly to lowincome households, which would be especially impacted by higher electricity bills.
As discussed above, a state’s import/export ratio of electricity may influence its carbon content of
energy use (or fuel mix). This component adds a further layer of complexity when assessing the
potential impacts of a carbon price. For example, depending on how emission allowances might
be distributed under a federal cap-and-trade system, states that are net energy providers may
receive financial gains, at least in the short-term. For instance, if power plants can pass along the
mitigation costs (of carbon reduction) in higher electricity prices and receive their emission
allowances for free (often referred to as “grandfathering”) the companies may benefit
34
For more discussion of these issues, see CRS Report RL33799, Climate Change: Design Approaches for a
Greenhouse Gas Reduction Program, by (name redacted).
35
Raymond Kopp, 2007, Greenhouse Gas Regulation in the United States, Resources for the Future Discussion Paper.
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financially.36 These potential gains to the likely regulated entities (e.g., coal-fired power plants)
have been described as “windfall profits,” and have been recently observed in the European
Union’s Emission Trading System.37 The gains would be temporary, because under most cap-andtrade proposals, the cap decreases over time; thus, regulated entities would receive fewer
allowances as the program progresses.
If Congress enacts an emissions reduction program, states with high levels of energy intensity are
likely to face higher costs than states with low energy intensity levels. As Table 4 shows, the high
and low energy intensity levels can differ by a factor of four, which suggests that the impacts
between the states at the ends of the spectrum could vary dramatically.
Energy intensity levels are shaped by multiple factors. Some of these factors may be based on
behavior or actions. These factors may be altered through public policy. For example, states could
initiate policies or support programs that seek to change the driving behavior (i.e., VMT) of its
citizens. Other factors—especially a state’s ratio of high and low carbon intensive industries—are
more structural, and thus more difficult (if not impractical) to alter through public policy.
In addition, depending on the degree to which a state’s energy intensity is influenced by its
climate, a newly-imposed carbon price may have a greater impact. In these states, the demand for
energy may be less elastic (i.e., responsive to price changes) than other states, because energy is
more critical for daily life necessities, such as home heating. Low-income citizens may face a
disproportionate burden, as a share of income, of price increases in states with substantial heating
and/or cooling needs.
States with high energy intensity may have a high percentage of carbon-intensive industries (e.g.,
manufacturing). These industries would likely see an increase in their operational costs due to the
new carbon price, but they may be able to include the additional carbon costs in the price of their
products (e.g., paper, cement, steel), thus spreading the costs to consumers in other states.
However, passing along the carbon price to consumers may not be financially viable for
producers. The ability of producers to pass along the carbon price would be determined by the
competitiveness of the market and consumers’ willingness to pay higher prices or forego
purchases for a particular good. Consumers may seek out product substitutes or lower cost
suppliers (which could include foreign producers not subject to a domestic carbon price).
From another perspective, higher levels in emissions drivers, particularly the energy intensity
variable, may suggest a state has comparatively more “low hanging fruit” or lower-cost options to
meet emission reduction requirements. As noted above, the states with high energy intensities
were also ranked poorly by ACEEE’s energy efficiency scorecard. Although these states’ energy
intensity levels are primarily due to economic structure, there may be room for improvement—
via “no regrets” energy efficiency policies—within the framework of their economic structure.
Along these lines, states that currently use a substantial percentage of high-carbon fuels for
energy purposes (particularly for electricity generation) may have more options in a carbonconstrained regime than states that are already utilizing a high percentage of low-carbon energy
36
In a market-based system (e.g., cap-and-trade), emission allowances can be used to comply with an individual
company’s cap or sold to other parties subject to the cap. As such, allowances are a form of currency and would
provide an infusion of funds.
37
The vast majority of emissions allowances were distributed for free under the European program. See National
Commission on Energy Policy, 2007, Allocating Allowances in a Greenhouse Gas Trading System, p.11.
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sources. For instance, if states in both categories were required to reduce current emissions by a
set percentage, states using high-carbon fuels may seek low-carbon fuel substitutes, but states
using low-carbon fuels would be limited in this regard. This comparison does not suggest that
switching to low-carbon fuels will be easy (or inexpensive), but these states may have more ways
to find emission reductions.
Moreover, low-carbon fuel substitutes may not be distributed evenly across the states. Some
states that currently use large proportions of high-carbon energy sources may be in better
positions—in terms of natural resource endowments and geography—than other states looking
for low-carbon substitutes. For example, there is more wind energy potential in the western and
mid-western states than in states in the Southeast.38
The above comparison also highlights the importance of selecting a baseline year for an emission
reduction program. If emissions caps are compared to 1990 levels, it would reward states for
reductions made during the 1990s. If the reduction program’s baseline is 2000, for example, the
reductions made before that year would not count, and these states may have more difficulty
finding lower-cost options.
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Several members in the 110th Congress have introduced proposals that would establish a nationwide GHG reduction program. Any emissions reduction regime would necessitate declines in
GHG intensity. The declines needed would depend on the level of absolute reductions mandated
by the enacted program.
To stabilize national GHG emission growth, the entire United States would need to achieve
annual reductions in GHG intensity of approximately 3% (assuming population and income
continue to grow at a combined rate of 3%). Only four states—Delaware (3.7%), New Mexico
(3.7%), Utah (3.4%), and Arizona (3.3%)—exceeded this annual rate of decline between 1990
and 2003; the average decline among all states was 1.7%.39
Reducing GHG emissions in the United States would necessitate further declines in GHG
intensity. Several legislative proposals in the 110th Congress would require GHG emissions to
return to 1990 levels by 2020.40 To meet this objective, national GHG intensity would need to
decline annually (starting in 2010) by 5.0%.41
38
See National Renewable Energy Laboratory, Map of U.S. Annual Average Wind Power, at http://rredc.nrel.gov/
wind/pubs/atlas/maps.html#2-6.
39
The contrast between individual state intensity levels and the states’ average level is only for comparison purposes.
When calculating the states’ average intensity level, all states are counted equally. Because of the significant variance
in emissions between large and small states, the states’ average intensity level may not coincide with the national
intensity level. Ten states comprise approximately 50% of U.S. GHG emissions. The actions of these states will likely
have greater effect on the national GHG intensity.
40
For example, S. 280 (Lieberman), S. 309 (Sanders), S. 485 (Kerry), H.R. 620 (Olver), and H.R. 1590 (Waxman).
41
This calculation assumes: (1) U.S. population will grow annually by 0.9% (U.S. Census Bureau, at
http://www.census.gov/cgi-bin/ipc/idbsum.pl?cty=US)); (2) incomes will increase annually by 2.1% (the rate of
increase from 1975 to 2003, WRI, Climate Analysis Indicators Tool); (3) GHG emissions were 6,240 MMTCO2E in
(continued...)
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To put this goal in perspective, consider the 10 states that emitted the most GHGs in 2003
(accounting for approximately 50% of total U.S. emissions) and the GHG intensity annual
average rates of change (between 1990 and 2003) for these states (Table 10). These states would
likely need to make further reductions in GHG intensity if the national GHG intensity levels are
to decline annually by 5% starting in 2010. Many of these states would need to more than double
their current annual GHG intensity declines to reach a negative growth rate of 5%.
Table 10. GHG Emissions Intensity Average Annual (Negative) Growth Rates (19902003) for the 10 States with the Most GHG Emissions in 2003
State
GHG Emissions Intensity Average
Annual Growth Rates (1990-2003)
Texas
-2.5
California
-1.9
Pennsylvania
-2.1
Ohio
-1.7
Florida
-1.6
Illinois
-1.6
Indiana
-2.1
New York
Michigan
Louisiana
-1.6
-2.6
-0.6
Source:
Prepared by CRS with data from the WRI, Climate Analysis Indicators Tool.
(...continued)
1990 (U.S. EPA, 2007, U.S. Inventory of Greenhouse Gas Emissions and Sinks 1990-2005, at http://www.epa.gov/
climatechange), and are projected to be 7,632 MMTCO2E in 2010 (based on a 1.0% annual average growth rate
between 1990 and 2005).
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Table A-1. GHG Emissions and GHG Emissions Drivers for All 50 States, Listed
Alphabetically (2003 data)
State
Alabama
Alaska
Arizona
Arkansas
California
Colorado
Connecticut
Delaware
Florida
Georgia
Hawaii
Idaho
Illinois
Indiana
Iowa
Kansas
Kentucky
Louisiana
Maine
Maryland
Massachusetts
Michigan
Minnesota
Mississippi
Missouri
Montana
Nebraska
Nevada
New
Hampshire
New Jersey
Emissions
GHG
Population
Per capita
Income
GHG Intensity
MMTCO2E
in 1,000s
GSP/person
TCO2E / $million of
GSP
164
46
96
81
453
107
46
19
271
186
23
24
269
269
108
101
164
210
26
90
92
212
120
76
163
41
65
48
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
4,495
648
5,582
2,724
35,466
4,546
3,482
817
16,982
8,750
1,246
1,367
12,650
6,192
2,942
2,727
4,114
4,481
1,307
5,507
6,440
10,068
5,059
2,874
5,712
917
1,737
2,241
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
27,140
42,784
31,294
25,971
37,787
39,144
45,875
54,667
30,548
34,228
34,180
26,906
37,818
33,082
32,481
31,668
28,739
29,375
28,632
36,164
43,850
34,260
39,146
23,281
32,123
25,389
34,593
36,933
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
1,343
1,662
551
1,138
338
600
286
426
523
621
550
651
561
1,315
1,133
1,166
1,385
1,591
693
450
327
614
606
1,131
886
1,755
1,088
574
22 =
1,286 X
35,821 X
469
137 =
8,633 X
42,435 X
373
ȱȱȱ
ŗŞȱ
ȱ ȱ ȱDZȱȱȱ¢ȱ
ȱ
State
GHG
Emissions
Population
Per capita
Income
GHG Intensity
MMTCO2E
in 1,000s
GSP/person
TCO2E / $million of
GSP
New Mexico
New York
North Carolina
North Dakota
Ohio
Oklahoma
Oregon
Pennsylvania
Rhode Island
South Carolina
South Dakota
Tennessee
Texas
Utah
Vermont
Virginia
Washington
West Virginia
Wisconsin
Wyoming
66
244
168
57
299
124
51
301
13
92
27
141
782
69
8
143
95
133
123
72
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
1,878
19,238
8,416
633
11,438
3,504
3,561
12,351
1,075
4,142
764
5,834
22,134
2,356
619
7,376
6,130
1,809
5,467
501
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
28,590
41,731
34,288
31,464
33,174
27,047
32,825
33,224
33,904
28,809
33,671
32,523
34,837
30,115
31,693
38,108
36,612
23,708
33,799
37,857
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
1,236
304
581
2,885
788
1,308
435
734
349
771
1,060
745
1,015
977
399
507
421
3,097
666
3,799
Prepared by CRS with data from the WRI, Climate Analysis Indicators Tool.
Note: The calculations above are based on the Equation 1 (provided again below), but the units have been
altered to make the figures more presentable and easier to compare. In particular, note that in the above table
the population figure for each state is in 1,000s; and the GHG intensity figure is presented in metric tons (instead
of million metric tons) of CO2E and in million dollars of GSP (instead of one dollar of GSP).
Source:
Equation 1:
GHG Emissions
(MMTCO2E)
=
Population
(Persons)
ȱȱȱ
X
Per Capita Income
(GSP/Person)
X
GHG Intensity
(MMTCO2E / GSP)
ŗşȱ
ȱ ȱ ȱDZȱȱȱ¢ȱ
ȱ
Table A-2. GHG Emissions and GHG Emissions Drivers for All 50 States, Ranked by
GHG Emissions (2003 data)
Emissions
GHG
Population
Per capita
Income
GHG Intensity
MMTCO2E
in 1,000s
GSP/person
TCO2E / $million
of GSP
State
Rank
Texas
California
Pennsylvania
Ohio
Florida
Illinois
Indiana
New York
Michigan
Louisiana
Georgia
North
Carolina
Alabama
Kentucky
Missouri
Virginia
Tennessee
New Jersey
West Virginia
Oklahoma
Wisconsin
Minnesota
Iowa
Colorado
Kansas
Arizona
Washington
South Carolina
Massachusetts
Maryland
Arkansas
Mississippi
1
2
3
4
5
6
7
8
9
10
11
782
453
301
299
271
269
269
244
212
210
186
=
=
=
=
=
=
=
=
=
=
=
22,134
35,466
12,351
11,438
16,982
12,650
6,192
19,238
10,068
4,481
8,750
X
X
X
X
X
X
X
X
X
X
X
34,837
37,787
33,224
33,174
30,548
37,818
33,082
41,731
34,260
29,375
34,228
X
X
X
X
X
X
X
X
X
X
X
1,015
338
734
788
523
561
1,315
304
614
1,591
621
12
168 =
8,416
X
34,288
X
581
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
164
164
163
143
141
137
133
124
123
120
108
107
101
96
95
92
92
90
81
76
4,495
4,114
5,712
7,376
5,834
8,633
1,809
3,504
5,467
5,059
2,942
4,546
2,727
5,582
6,130
4,142
6,440
5,507
2,724
2,874
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
27,140
28,739
32,123
38,108
32,523
42,435
23,708
27,047
33,799
39,146
32,481
39,144
31,668
31,294
36,612
28,809
43,850
36,164
25,971
23,281
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
1,343
1,385
886
507
745
373
3,097
1,308
666
606
1,133
600
1,166
551
421
771
327
450
1,138
1,131
ȱȱȱ
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
ŘŖȱ
ȱ ȱ ȱDZȱȱȱ¢ȱ
ȱ
GHG
Emissions
Population
Per capita
Income
GHG Intensity
MMTCO2E
in 1,000s
GSP/person
TCO2E / $million
of GSP
State
Rank
Wyoming
Utah
New Mexico
Nebraska
North Dakota
Oregon
Nevada
Alaska
Connecticut
Montana
South Dakota
Maine
Idaho
Hawaii
New
Hampshire
Delaware
Rhode Island
Vermont
33
34
35
36
37
38
39
40
41
42
43
44
45
46
72
69
66
65
57
51
48
46
46
41
27
26
24
23
=
=
=
=
=
=
=
=
=
=
=
=
=
=
501
2,356
1,878
1,737
633
3,561
2,241
648
3,482
917
764
1,307
1,367
1,246
X
X
X
X
X
X
X
X
X
X
X
X
X
X
37,857
30,115
28,590
34,593
31,464
32,825
36,933
42,784
45,875
25,389
33,671
28,632
26,906
34,180
X
X
X
X
X
X
X
X
X
X
X
X
X
X
3,799
977
1,236
1,088
2,885
435
574
1,662
286
1,755
1,060
693
651
550
47
22 =
1,286
X
35,821
X
469
48
49
50
19 =
13 =
8 =
817
1,075
619
X
X
X
54,667
33,904
31,693
X
X
X
426
349
399
Source:
Prepared by CRS with data from the WRI, Climate Analysis Indicators Tool.
Table A-3. Average Annual Growth Rates (1990-2003) for GHG Emissions and GHG
Emissions Drivers for All 50 States
State
Alabama
Alaska
Arizona
Arkansas
California
Colorado
Connecticut
Delaware
Florida
Georgia
Hawaii
GHG Emissions
1.4%
1.9%
2.5%
1.6%
0.7%
2.2%
0.4%
-0.2%
2.1%
1.6%
0.1%
ȱȱȱ
Population
=
=
=
=
=
=
=
=
=
=
=
0.8%
1.2%
3.2%
1.1%
1.3%
2.5%
0.4%
1.5%
2.1%
2.3%
0.9%
Per capita Income
+
+
+
+
+
+
+
+
+
+
+
1.9%
-2.3%
2.7%
2.4%
1.3%
2.7%
1.5%
2.1%
1.7%
2.0%
-0.6%
GHG Intensity
+
+
+
+
+
+
+
+
+
+
+
-1.2%
3.1%
-3.3%
-1.8%
-1.9%
-2.9%
-1.5%
-3.7%
-1.6%
-2.6%
-0.2%
Řŗȱ
ȱ ȱ ȱDZȱȱȱ¢ȱ
ȱ
State
GHG Emissions
Idaho
Illinois
Indiana
Iowa
Kansas
Kentucky
Louisiana
Maine
Maryland
Massachusetts
Michigan
Minnesota
Mississippi
Missouri
Montana
Nebraska
Nevada
New Hampshire
New Jersey
New Mexico
New York
North Carolina
North Dakota
Ohio
Oklahoma
Oregon
Pennsylvania
Rhode Island
South Carolina
South Dakota
Tennessee
Texas
Utah
Vermont
Virginia
Washington
West Virginia
2.2%
1.2%
1.4%
1.1%
0.9%
1.4%
0.0%
1.6%
0.9%
0.3%
0.4%
1.5%
2.1%
1.9%
1.1%
1.6%
2.8%
2.4%
0.7%
1.0%
0.4%
2.3%
1.4%
0.7%
1.1%
2.1%
0.2%
2.3%
2.3%
1.6%
1.3%
1.4%
1.2%
1.3%
0.8%
0.9%
0.1%
ȱȱȱ
Population
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
2.3%
0.8%
0.8%
0.4%
0.7%
0.8%
0.5%
0.5%
1.1%
0.5%
0.6%
1.1%
0.8%
0.8%
1.1%
0.7%
4.8%
1.1%
0.8%
1.6%
0.5%
1.8%
-0.1%
0.4%
0.8%
1.7%
0.3%
0.5%
1.3%
0.7%
1.4%
2.0%
2.4%
0.7%
1.3%
1.7%
0.1%
Per capita Income
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
2.6%
2.0%
2.6%
2.6%
1.8%
2.1%
0.1%
1.4%
1.4%
2.3%
2.4%
2.7%
2.0%
2.0%
1.8%
2.4%
0.8%
2.8%
1.6%
3.2%
1.4%
2.1%
3.1%
2.1%
1.5%
3.1%
2.0%
1.7%
1.9%
3.6%
2.5%
2.0%
2.3%
2.0%
1.8%
1.6%
1.9%
GHG Intensity
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
-2.7%
-1.6%
-2.1%
-1.9%
-1.6%
-1.5%
-0.6%
-0.3%
-1.5%
-2.5%
-2.6%
-2.2%
-0.7%
-0.9%
-1.7%
-1.5%
-2.7%
-1.5%
-1.7%
-3.7%
-1.6%
-1.7%
-1.6%
-1.7%
-1.2%
-2.6%
-2.1%
0.0%
-0.9%
-2.5%
-2.5%
-2.5%
-3.4%
-1.5%
-2.2%
-2.4%
-1.8%
ŘŘȱ
ȱ ȱ ȱDZȱȱȱ¢ȱ
ȱ
State
Wisconsin
Wyoming
GHG Emissions
1.2%
0.9%
Population
=
=
0.8%
0.8%
Per capita Income
+
+
2.6%
1.0%
GHG Intensity
+
+
-2.2%
-0.8%
Prepared by CRS with data from the WRI, Climate Analysis Indicators Tool.
Note: The sum of the GHG emissions driver rates may not precisely equal the rate of GHG emissions in all
cases. Nevertheless, the general relationship holds true.
Source:
Table A-4. CO2 Emissions Intensity and CO2 Emissions Intensity Drivers for All 50
States, Listed Alphabetically (2003 data)
State
CO2 Emissions
Intensity
=
Energy Intensity
X
Carbon Content of
Energy Use
TCO2 / $million
of GSP
=
toe / $million GSP
X
TCO2 / 1000 toe
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
0.42
0.69
0.20
0.40
0.15
0.19
0.14
0.18
0.21
0.25
0.18
0.32
0.21
0.36
0.31
0.33
0.40
0.71
0.32
0.20
0.14
0.23
0.23
0.45
0.25
0.41
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
2,690
2,300
2,570
2,180
1,900
2,620
1,890
2,140
2,260
2,220
2,740
1,210
2,320
3,140
2,640
2,780
3,030
2,080
1,940
2,050
2,170
2,320
2,220
2,100
2,950
3,480
Alabama
Alaska
Arizona
Arkansas
California
Colorado
Connecticut
Delaware
Florida
Georgia
Hawaii
Idaho
Illinois
Indiana
Iowa
Kansas
Kentucky
Louisiana
Maine
Maryland
Massachusetts
Michigan
Minnesota
Mississippi
Missouri
Montana
ȱȱȱ
1,178
1,624
517
933
295
509
269
392
478
569
502
404
497
1,221
839
935
1,247
1,508
647
411
308
557
510
993
770
1,442
Řřȱ
ȱ ȱ ȱDZȱȱȱ¢ȱ
ȱ
State
CO2 Emissions
Intensity
=
Energy Intensity
X
Carbon Content of
Energy Use
TCO2 / $million
of GSP
=
toe / $million GSP
X
TCO2 / 1000 toe
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
0.27
0.20
0.18
0.18
0.31
0.13
0.23
0.50
0.26
0.40
0.23
0.24
0.16
0.34
0.26
0.30
0.40
0.25
0.20
0.22
0.22
0.46
0.25
0.61
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
2,630
2,610
2,490
1,940
3,440
2,030
2,190
4,770
2,620
2,740
1,540
2,690
1,990
1,990
2,040
2,150
2,270
3,470
1,660
2,000
1,660
5,780
2,260
5,460
Nebraska
Nevada
New Hampshire
New Jersey
New Mexico
New York
North Carolina
North Dakota
Ohio
Oklahoma
Oregon
Pennsylvania
Rhode Island
South Carolina
South Dakota
Tennessee
Texas
Utah
Vermont
Virginia
Washington
West Virginia
Wisconsin
Wyoming
737
528
446
346
1,088
271
511
2,400
728
1,114
356
678
330
701
558
672
933
885
332
443
365
2,719
571
3,473
Prepared by CRS with data from the WRI, Climate Analysis Indicators Tool.
Note: In all but four states, the product of the energy intensity value and carbon content of energy use value is
slightly lower than the CO2 emissions intensity value. This difference reflects the small percentage (on average
2%) of the states’ CO2 emissions that come from sources outside the energy sector (e.g., agricultural).
Source:
ȱȱȱ
ŘŚȱ
ȱ ȱ ȱDZȱȱȱ¢ȱ
ȱ
Table A-5. CO2 Emissions Intensity and CO2 Emissions Intensity Drivers for All 50
States, Ranked by CO2 Emissions Intensity (2003 data)
State
Wyoming
West Virginia
North Dakota
Alaska
Louisiana
Montana
Kentucky
Indiana
Alabama
Oklahoma
New Mexico
Mississippi
Kansas
Texas
Arkansas
Utah
Iowa
Missouri
Nebraska
Ohio
South Carolina
Pennsylvania
Tennessee
Maine
Wisconsin
Georgia
South Dakota
Michigan
Nevada
Arizona
North Carolina
Minnesota
Colorado
Rank
CO2 Emissions
Intensity
TCO2 / $million
of GSP
=
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
3,473
2,719
2,400
1,624
1,508
1,442
1,247
1,221
1,178
1,114
1,088
993
935
933
933
885
839
770
737
728
701
678
672
647
571
569
558
557
528
517
511
510
509
ȱȱȱ
X
Carbon Content of
Energy Use
=
Energy
Intensity
toe / $million
GSP
X
TCO2 / 1000 toe
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
0.61
0.46
0.50
0.69
0.71
0.41
0.40
0.36
0.42
0.40
0.31
0.45
0.33
0.40
0.40
0.25
0.31
0.25
0.27
0.26
0.34
0.24
0.30
0.32
0.25
0.25
0.26
0.23
0.20
0.20
0.23
0.23
0.19
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
5,460
5,780
4,770
2,300
2,080
3,480
3,030
3,140
2,690
2,740
3,440
2,100
2,780
2,270
2,180
3,470
2,640
2,950
2,630
2,620
1,990
2,690
2,150
1,940
2,260
2,220
2,040
2,320
2,610
2,570
2,190
2,220
2,620
Řśȱ
ȱ ȱ ȱDZȱȱȱ¢ȱ
ȱ
State
Hawaii
Illinois
Florida
New Hampshire
Virginia
Maryland
Idaho
Delaware
Washington
Oregon
New Jersey
Vermont
Rhode Island
Massachusetts
California
New York
Connecticut
Rank
CO2 Emissions
Intensity
=
TCO2 / $million
of GSP
502
497
478
446
443
411
404
392
365
356
346
332
330
308
295
271
269
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
X
Carbon Content of
Energy Use
=
Energy
Intensity
toe / $million
GSP
X
TCO2 / 1000 toe
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
=
0.18
0.21
0.21
0.18
0.22
0.20
0.32
0.18
0.22
0.23
0.18
0.20
0.16
0.14
0.15
0.13
0.14
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
2,740
2,320
2,260
2,490
2,000
2,050
1,210
2,140
1,660
1,540
1,940
1,660
1,990
2,170
1,900
2,030
1,890
Prepared by CRS with data from the WRI, Climate Analysis Indicators Tool.
Note: In all but four states, the product of the energy intensity value and carbon content of energy use value is
slightly lower than the CO2 emissions intensity value. This difference reflects the small percentage (on average
2%) of the states’ CO2 emissions that come from sources outside the energy sector (e.g., agricultural).
Source:
ȱȱ ȱ
(name redacted)
Analyst in Environmental Policy
#redacted#@crs.loc.gov
, 7-....
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