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1.) What do you think of the argument made by the authors? Do you think they are realistic? Overly optimistic? Too cautious? Perhaps more importantly, is there anything that is missing from this picture? What form of energy/kind of energy isn’t being addressed? (Energy and Env science article attached)

2.) Review this article on stalled green energy transition in Africa. Do you agree with the general recommendations/conclusions? What do you think this means for changes in other parts of the world?

https://www.bbc.com/news/science-environment-55620…

Energy &
Environmental
Science
PAPER
Cite this: Energy Environ. Sci.,
2015, 8, 2093
100% clean and renewable wind, water, and
sunlight (WWS) all-sector energy roadmaps for
the 50 United States†
Mark Z. Jacobson,*a Mark A. Delucchi,b Guillaume Bazouin,a Zack A. F. Bauer,a
Christa C. Heavey,a Emma Fisher,a Sean B. Morris,a Diniana J. Y. Piekutowski,a
Taylor A. Vencilla and Tim W. Yeskooa
This study presents roadmaps for each of the 50 United States to convert their all-purpose energy systems (for
electricity, transportation, heating/cooling, and industry) to ones powered entirely by wind, water, and sunlight
(WWS). The plans contemplate 80–85% of existing energy replaced by 2030 and 100% replaced by 2050. Conversion would reduce each state’s end-use power demand by a mean of B39.3% with B82.4% of this due to
the efficiency of electrification and the rest due to end-use energy efficiency improvements. Year 2050 end-use
U.S. all-purpose load would be met with B30.9% onshore wind, B19.1% offshore wind, B30.7% utility-scale
photovoltaics (PV), B7.2% rooftop PV, B7.3% concentrated solar power (CSP) with storage, B1.25% geothermal
power, B0.37% wave power, B0.14% tidal power, and B3.01% hydroelectric power. Based on a parallel grid
integration study, an additional 4.4% and 7.2% of power beyond that needed for annual loads would be supplied
by CSP with storage and solar thermal for heat, respectively, for peaking and grid stability. Over all 50 states,
converting would provide B3.9 million 40-year construction jobs and B2.0 million 40-year operation jobs for
the energy facilities alone, the sum of which would outweigh the B3.9 million jobs lost in the conventional
energy sector. Converting would also eliminate B62 000 (19 000–115 000) U.S. air pollution premature mortalities per year today and B46 000 (12 000–104 000) in 2050, avoiding B$600 ($85–$2400) bil. per year (2013
dollars) in 2050, equivalent to B3.6 (0.5–14.3) percent of the 2014 U.S. gross domestic product. Converting
would further eliminate B$3.3 (1.9–7.1) tril. per year in 2050 global warming costs to the world due to U.S.
emissions. These plans will result in each person in the U.S. in 2050 saving B$260 (190–320) per year in energy
Received 25th April 2015,
Accepted 27th May 2015
costs ($2013 dollars) and U.S. health and global climate costs per person decreasing by B$1500 (210–6000) per
year and B$8300 (4700–17 600) per year, respectively. The new footprint over land required will be B0.42% of
DOI: 10.1039/c5ee01283j
U.S. land. The spacing area between wind turbines, which can be used for multiple purposes, will be B1.6% of
www.rsc.org/ees
may therefore reduce social and political barriers to implementing clean-energy policies.
U.S. land. Thus, 100% conversions are technically and economically feasible with little downside. These roadmaps
Broader context
This paper presents a consistent set of roadmaps for converting the energy infrastructures of each of the 50 United States to 100% wind, water, and sunlight
(WWS) for all purposes (electricity, transportation, heating/cooling, and industry) by 2050. Such conversions are obtained by first projecting conventional power
demand to 2050 in each sector then electrifying the sector, assuming the use of some electrolytic hydrogen in transportation and industry and applying modest
end-use energy efficiency improvements. Such state conversions may reduce conventional 2050 U.S.-averaged power demand by B39%, with most reductions
due to the efficiency of electricity over combustion and the rest due to modest end-use energy efficiency improvements. The conversions are found to be
technically and economically feasible with little downside. They nearly eliminate energy-related U.S. air pollution and climate-relevant emissions and their
resulting health and environmental costs while creating jobs, stabilizing energy prices, and minimizing land requirements. These benefits have not previously
been quantified for the 50 states. Their elucidation may reduce the social and political barriers to implementing clean-energy policies for replacing
conventional combustible and nuclear fuels. Several such policies are proposed herein for each energy sector.
a
Atmosphere/Energy Program, Dept. of Civil and Env. Engineering,
Stanford University, USA. E-mail: jacobson@stanford.edu; Fax: +1-650-723-7058;
Tel: +1-650-723-6836
b
Institute of Transportation Studies, U.C. Berkeley, USA
† Electronic supplementary information (ESI) available. See DOI: 10.1039/c5ee01283j
This journal is © The Royal Society of Chemistry 2015
1. Introduction
This paper presents a consistent set of roadmaps to convert
each of the 50 U.S. states’ all-purpose (electricity, transportation,
Energy Environ. Sci., 2015, 8, 2093–2117 | 2093
Paper
heating/cooling, and industry) energy infrastructures to ones
powered 100% by wind, water, and sunlight (WWS). Existing energy
plans in many states address the need to reduce greenhouse gas
emissions and air pollution, keep energy prices low, and foster job
creation. However, in most if not all states these goals are limited to
partial emission reductions by 2050 (see, for example,1 for a review
of California roadmaps), and no set of consistently-developed
roadmaps exist for every U.S. state. By contrast, the roadmaps here
provide a consistent set of pathways to eliminate 100% of presentday greenhouse gas and air pollutant emissions from energy by
2050 in all 50 sates while growing the number of jobs and
stabilizing energy prices. A separate study2 provides a grid
integration analysis to examine the ability of the intermittent
energy produced from the state plans here, in combination, to
match time-varying electric and thermal loads when combined
with storage and demand response.
The methods used here to create each state roadmap are
broadly similar to those recently developed for New York,3
California,4 and the world as a whole.5–7 Such methods are
applied here to make detailed, original, state-by-state estimates of
(1) Future energy demand (load) in the electricity, transportation, heating/cooling, and industrial sectors in both a
business-as-usual (BAU) case and a WWS case;
(2) The numbers of WWS generators needed to meet the
estimated load in each sector in the WWS case;
(3) Footprint and spacing areas needed for WWS generators;
(4) Rooftop areas and solar photovoltaic (PV) installation
potentials over residential and commercial/government buildings and associated carports, garages, parking lots, and parking
structures;
(5) The levelized cost of energy today and in 2050 in the BAU
and WWS cases;
(6) Reductions in air-pollution mortality and associated
health costs today based on pollution data from all monitoring
stations in each state and in 2050, accounting for future reductions in emissions in the BAU versus WWS cases;
(7) Avoided global-warming costs today and in 2050 in the
BAU versus WWS cases; and
(8) Numbers of jobs produced and lost and the resulting
revenue changes between the BAU and WWS cases.
This paper further provides a transition timeline, energy
efficiency measures, and potential policy measures to implement
the plans. In sum, whereas, many studies focus on changing
energy sources in one energy sector, such as electricity, this study
integrates changes among all energy sectors: electricity, transportation, heating/cooling, and industry. It further provides rigorous
and detailed and consistent estimates of 2050 state-by-state air
pollution damage, climate damage, energy cost, solar rooftop
potential, and job production and loss not previously available.
2. WWS technologies
This study assumes all energy sectors are electrified by 2050. The
WWS energy technologies chosen to provide electricity include
wind, concentrated solar power (CSP), geothermal, solar PV,
2094 | Energy Environ. Sci., 2015, 8, 2093–2117
Energy & Environmental Science
tidal, wave, and hydroelectric power. These generators are existing
technologies that were found to reduce health and climate
impacts the most among multiple technologies while minimizing
land and water use and other impacts.8
The technologies selected for ground transportation, which
will be entirely electrified, include battery electric vehicles (BEVs)
and hydrogen fuel cell (HFC) vehicles, where the hydrogen is
produced by electrolysis. BEVs with fast charging or battery
swapping will dominate long-distance, light-duty transportation;
Battery electric-HFC hybrids will dominate heavy-duty transportation and long-distance shipping; batteries will power
short-distance shipping (e.g., ferries); and electrolytic cryogenic
hydrogen, with batteries for idling, taxiing, and internal power,
will power aircraft.
Air heating and cooling will be electrified and powered by
electric heat pumps (ground-, air-, or water-source) and some
electric-resistance heating. Water will be heated by heat pumps
with electric resistance elements and/or solar hot water preheating. Cook stoves will have either an electric induction or
resistance-heating element.
High-temperature industrial processes will be powered by
electric arc furnaces, induction furnaces, dielectric heaters, and
resistance heaters and some combusted electrolytic hydrogen.
HFCs will be used only for transportation, not for electric
power generation due to the inefficiency of that application
for HFCs. Although electrolytic hydrogen for transportation is
less efficient and more costly than is electricity for BEVs, some
segments of transportation (e.g., long-distance ships and freight)
may benefit from HFCs.
The roadmaps presented here include energy efficiency
measures but not nuclear power, coal with carbon capture, liquid
or solid biofuels, or natural gas, as previously discussed.3,6
Biofuels, for example, are not included because their combustion produces air pollution at rates on the same order as fossil
fuels and their lifecycle carbon emissions are highly uncertain
but definitely larger than those of WWS technologies. Several
biofuels also have water and land requirements much larger
than those of WWS technologies. Since photosynthesis is 1%
efficient whereas solar PV, for example, is B20% efficient, the
same land used for PV produces B20 times more energy than
does using the land for biofuels.
This study first calculates the installed capacity and number
of generators of each type needed in each state to potentially
meet the state’s annual power demand (assuming state-specific
average-annual capacity factors) in 2050 after all sectors have
been electrified, without considering sub-annual (e.g., daily
or hourly) load balancing. The calculations assume only that
existing hydroelectric from outside of a state continues to come
from outside. The study then provides the additional number of
generators needed by state to ensure that hourly power demand
across all states does not suffer loss of load, based on results
from ref. 2. As such, while the study bases each state’s installed
capacity on the state’s annual demand, it allows interstate
transmission of power as needed to ensure that supply and
demand balance every hour in every state. We also roughly
estimate the additional cost of transmission lines needed for
This journal is © The Royal Society of Chemistry 2015
Energy & Environmental Science
this hourly balancing. Note that if we relax our assumption that
each state’s capacity match its annual demand, and instead
allow states with especially good solar or wind resources to have
enough capacity to supply larger regions, then the average
levelized cost of electricity will be lower than we estimate because
of the higher average capacity factors in states with the best WWS
resources.
3. Changes in U.S. power load upon
conversion to WWS
Table 1 summarizes the state-by-state end-use load calculated
by sector in 2050 if conventional fuel use continues along BAU
or ‘‘conventional energy’’ trajectory. It also shows the estimated
new load upon a conversion to a 100% WWS infrastructure
(with zero fossil fuels, biofuels, or nuclear fuels). The table is
derived from a spreadsheet analysis of annually averaged enduse load data.9 All end uses that feasibly can be electrified are
assumed to use WWS power directly, and remaining end uses
(some heating, high-temperature industrial processes, and some
transportation) are assumed to use WWS power indirectly in the
form of electrolytic hydrogen (hydrogen produced by splitting
water with WWS electricity). End-use power excludes losses
incurred during production and transmission of the power.
With these roadmaps, electricity generation increases, but
the use of oil and gas for transportation and heating/cooling
decreases to zero. Further, the increase in electricity use due to
electrifying all sectors is much less than the decrease in energy
in the gas, liquid, and solid fuels that the electricity replaces,
because of the high energy-to-work conversion efficiency of
electricity used for heating and electric motors. As a result,
end use load decreases significantly with WWS energy systems
in all 50 states (Table 1).
In 2010, U.S. all-purpose, end-use load was B2.37 TW
(terawatts, or trillion watts). Of this, 0.43 TW (18.1%) was
electric power load. If the U.S. follows the business-as-usual
(BAU) trajectory of the current energy infrastructure, which
involves growing load and modest shifts in the power sector
away from coal to renewables and natural gas, all-purpose enduse load is expected to grow to 2.62 TW in 2050 (Table 1).
A conversion to WWS by 2050 is calculated here to reduce U.S.
end-use load and the power required to meet that load by
B39.3% (Table 1). About 6.9 percentage points of this reduction
is due to modest additional energy-conservation measures
(Table 1, last column) and another relatively small portion is
due to the fact that conversion to WWS reduces the need for
energy use in petroleum refining. The remaining and major
reason for the reduction is that the use of electricity for heating
and electric motors is more efficient than is fuel combustion for
the same applications.6 Also, the use of WWS electricity to
produce hydrogen for fuel cell vehicles, while less efficient than
the use of WWS electricity to run BEVs, is more efficient and
cleaner than is burning liquid fossil fuels for vehicles.6,10
Combusting electrolytic hydrogen is slightly less efficient
but cleaner than is combusting fossil fuels for direct heating,
This journal is © The Royal Society of Chemistry 2015
Paper
and this is accounted for in Table 1. In Table 1, B11.48% of all
2050 WWS electricity (47.8% of transportation load, and 5.72%
of industrial load) will be used to produce, store, and use
hydrogen, for long distance and heavy transportation and some
high-temperature industrial processes.
The percent decrease in load upon conversion to WWS in
Table 1 is greater in some states (e.g., Hawaii, California, Florida,
New Jersey, New Hampshire, and Vermont) than in others
(e.g. Minnesota, Iowa, and Nebraska). The reason is that the
transportation-energy share of the total in the states with the
large reductions is greater than in those with the small reductions, and efficiency gains from electrifying transportation
are much greater than are efficiency gains from electrifying
other sectors.
4. Numbers of electric power
generators needed and land-use
implications
Table 2 summarizes the number of WWS power plants or
devices needed to power each U.S. state in 2050 for all purposes
assuming end use power requirements in Table 1, the percent
mix of end-use power generation in Table 3, and electrical
transmission, distribution, and array losses. The specific mix
of generators presented for each state in Table 3 is just one set
of options.
Rooftop PV in Table 2 is divided into residential (5 kW
systems on average) and commercial/government (100 kW systems
on average). Rooftop PV can be placed on existing rooftops or on
elevated canopies above parking lots, highways, and structures
without taking up additional undeveloped land. Table 4 summarizes projected 2050 rooftop areas by state usable for solar
PV on residential and commercial/government buildings,
carports, garages, parking structures, and parking lot canopies.
The rooftop areas in Table 4 are used to calculate potential
rooftop generation, which in turn limits the penetration of
residential and commercial/government PV in Table 3. Utilityscale PV power plants are sized, on average, relatively small
(50 MW) to allow them to be placed optimally in available
locations. While utility-scale PV can operate in any state
because it can take advantage of both direct and diffuse solar
radiation, CSP is assumed to be viable only in states with
sufficient direct solar radiation. While some states listed in
Table 3, such as states in the upper Midwest, are assumed to
install CSP although they have marginal average solar insolation,
such states have regions with greater than average insolation,
and the value of CSP storage is sufficiently high to suggest a
small penetration of CSP in those states.
Onshore wind is assumed to be viable primarily in states with
good wind resources (Section 5.1). Offshore wind is assumed to
be viable offshore of any state with either ocean or Great Lakes
coastline (Section 5.1). Wind and solar are the only two sources
of electric power with sufficient resource to power the whole
U.S. independently on their own. Averaged over the U.S., wind
(B50.0%) and solar (45.2%) are the largest generators of
Energy Environ. Sci., 2015, 8, 2093–2117 | 2095
Paper
Energy & Environmental Science
Table 1 1st row of each state: estimated 2050 total end-use load (GW) and percent of total load by sector if conventional fossil-fuel, nuclear, and biofuel
use continue from today to 2050 under a business-as-usual (BAU) trajectory. 2nd row of each state: estimated 2050 total end-use load (GW) and percent of
total load by sector if 100% of BAU end-use all-purpose delivered load in 2050 is instead provided by WWS. The estimate in the ‘‘% change’’ column for each
state is the percent reduction in total 2050 BAU load due to switching to WWS, including (second-to-last column) the effects of assumed policy-based
improvements in end-use efficiency, inherent reductions in energy use due to electrification, and the elimination of energy use for the upstream production
of fuels (e.g., petroleum refining). The number in the last column is the reduction due only to assumed, policy-driven end-use energy efficiency measuresa
State
Scenario
Alabama
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
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
New Mexico
2050 total end-use
load (GW)
53.9
35.3
24.0
14.5
38.0
21.9
31.6
20.3
229.3
127.8
46.5
27.9
19.2
11.4
5.9
3.5
107.2
61.2
79.4
47.2
7.4
3.8
15.0
9.5
93.5
57.9
64.4
40.4
42.7
30.6
30.1
18.8
46.5
28.5
147.7
92.7
13.5
9.1
34.9
20.1
35.8
21.4
64.8
39.9
48.8
31.5
33.9
21.0
42.8
25.5
12.3
7.4
21.9
15.5
18.5
11.0
7.1
3.9
57.5
32.9
21.6
12.8
2096 | Energy Environ. Sci., 2015, 8, 2093–2117
Residential
% of total
Commercial
% of total
Industrial
% of total
Transport
% of total
11.3
13.5
4.9
5.6
20.7
28.7
14.8
18.2
13.2
16.9
18.2
23.0
24.1
29.0
19.5
24.2
19.5
26.9
16.7
20.6
7.1
10.3
17.5
21.8
16.9
20.2
12.4
15.0
10.0
10.9
14.0
17.5
11.9
14.6
4.9
6.2
12.1
13.3
20.9
25.9
24.9
29.1
19.3
22.9
14.8
17.7
10.5
13.1
20.9
27.8
15.5
19.8
12.2
13.6
20.3
26.7
20.9
27.4
17.7
22.7
12.9
16.9
9.3
11.2
7.8
10.9
18.9
25.4
13.0
16.5
14.6
22.2
14.2
18.5
22.6
30.6
23.2
30.6
18.2
24.7
14.3
18.7
13.6
22.1
12.9
15.9
17.2
21.4
11.5
14.1
10.4
11.5
12.1
15.5
10.0
12.8
3.8
4.8
11.4
13.4
25.9
34.8
20.4
27.9
19.5
24.5
14.5
17.9
9.5
12.1
16.9
22.6
15.4
19.8
12.3
13.9
17.0
22.2
19.0
26.9
23.3
33.9
13.6
17.9
51.2
60.4
56.4
66.2
15.5
19.0
38.8
47.4
26.9
34.3
34.6
39.2
14.7
17.5
23.4
27.2
16.9
22.4
30.7
39.9
22.1
32.6
36.0
42.9
36.7
42.3
50.6
57.5
57.7
67.3
44.8
49.9
47.2
55.6
73.4
78.3
49.6
60.1
14.1
16.6
17.8
22.4
28.2
33.8
41.1
48.9
44.1
53.7
23.6
28.7
34.8
39.3
50.4
60.5
23.4
29.2
17.9
21.7
17.0
19.6
40.3
45.3
28.2
14.9
30.9
17.2
44.9
27.0
33.4
17.8
45.3
26.6
33.0
19.3
38.6
22.8
33.9
18.0
45.4
25.9
38.2
20.8
57.2
35.0
33.6
19.5
29.1
16.2
25.6
13.5
21.9
10.3
29.1
17.1
31.0
17.0
18.0
10.7
27.0
13.2
39.1
22.7
36.9
20.6
33.0
18.7
29.6
15.5
35.8
21.0
38.6
21.0
34.3
21.1
25.1
12.1
39.3
21.8
42.3
24.0
42.0
23.7
33.2
19.9
% change in end-use
power with WWS
Overall
Effic. only
34.4
4.5
39.8
3.0
42.2
10.5
35.5
4.5
44.3
7.1
40.1
9.1
40.7
9.6
41.1
10.5
42.9
9.8
40.6
8.3
49.5
6.6
37.0
7.8
38.1
8.1
37.2
6.6
28.3
2.0
37.5
7.0
38.8
7.6
37.2
3.4
32.7
2.1
42.3
11.4
40.3
8.8
38.4
9.4
35.4
4.0
38.0
6.3
40.4
7.3
39.5
8.2
29.3
0.4
40.6
9.2
44.2
8.7
42.8
7.1
41.0
8.8
This journal is © The Royal Society of Chemistry 2015
Energy & Environmental Science
Table 1
Paper
(continued)
State
Scenario
2050 total end-use
load (GW)
Residential
% of total
Commercial
% of total
Industrial
% of total
Transport
% of total
New York
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
BAU
WWS
86.3
54.9
62.7
37.9
14.3
9.0
87.0
53.5
47.3
29.1
27.3
16.3
94.0
59.1
5.5
3.2
39.7
24.2
10.6
7.5
52.8
32.2
376.6
225.3
23.2
13.8
3.7
2.1
60.3
35.1
52.8
31.7
21.7
13.0
41.9
26.8
18.1
11.2
2621.4
1591.0
23.0
26.5
19.8
24.8
7.3
9.1
16.2
19.8
13.1
16.7
15.4
18.9
15.4
18.5
24.2
28.9
15.1
19.0
10.6
11.8
15.6
19.6
8.4
11.2
17.8
22.8
25.1
31.8
18.0
22.7
14.3
17.7
14.3
17.0
15.7
18.3
6.0
7.4
14.3
17.8
30.1
39.0
18.9
24.2
8.7
11.0
16.4
20.5
11.4
15.0
15.6
21.9
14.1
18.3
21.1
28.9
13.0
16.6
11.1
12.5
13.5
17.4
8.0
10.8
16.6
21.8
16.3
22.4
20.3
27.1
15.2
21.3
12.3
15.9
17.2
20.7
8.3
10.4
14.1
18.6
15.0
16.6
25.8
32.1
59.0
64.4
37.6
43.6
41.1
47.0
26.5
34.6
39.5
44.1
19.9
21.7
36.3
45.8
50.4
61.9
36.5
44.5
56.9
62.7
28.7
33.0
19.2
24.3
23.1
28.5
30.2
38.7
40.6
45.3
39.6
47.3
56.2
61.2
38.5
45.0
31.8
17.9
35.5
18.9
24.9
15.5
29.8
16.1
34.4
21.3
42.6
24.6
31.0
19.2
34.9
20.5
35.6
18.6
28.0
13.9
34.3
18.4
26.7
15.3
36.8
22.4
39.4
21.5
38.6
21.7
40.4
22.4
32.7
21.7
27.4
13.8
29.5
20.9
33.1
18.6
North Carolina
North Dakota
Ohio
Oklahoma
Oregon
Pennsylvania
Rhode Island
South Carolina
South Dakota
Tennessee
Texas
Utah
Vermont
Virginia
Washington
West Virginia
Wisconsin
Wyoming
United States
% change in end-use
power with WWS
Overall
Effic. only
36.4
7.8
39.5
9.8
36.9
4.6
38.5
8.2
38.5
6.9
40.4
8.5
37.2
7.3
41.5
10.7
39.1
7.8
29.1
1.8
39.1
7.3
40.2
4.8
40.6
9.1
42.7
8.6
41.8
10.2
39.9
7.4
39.9
12.3
36.0
6.4
38.3
8.5
39.3
6.9
a
BAU values are extrapolations from the U.S. Energy Information Administration (EIA) projections for the year 2040. WWS values are estimated
with respect to BAU values accounting for the effect of electrification of end-uses on energy requirements and the effects of additional energyefficiency measures. See the ESI and ref. 9 for details.
annually averaged end-use electric power under these plans.
The ratio of wind to solar end-use power is 1.1 : 1.
Under the roadmaps, the 2050 installed capacity of hydroelectric, averaged over the U.S., is assumed to be virtually the
same as in 2010, except for a small growth in Alaska. However,
existing dams in most states are assumed to run more efficiently for producing peaking power, thus the capacity factor of
dams is assumed to increase (Section 5.4). Geothermal, wave,
and tidal energy expansions are limited in each state by their
potentials (Sections 5.3, 5.5 and 5.6, respectively).
Table 2 lists installed capacities beyond those needed to
match annually averaged power demand for CSP with storage
and for solar thermal. These additional capacities are derived in
the separate grid integration study2 and are needed to produce
peaking power, to account for additional loads due to losses in
and out of storage, and to ensure reliability of the grid, as
described and quantified in that paper.
This journal is © The Royal Society of Chemistry 2015
Fig. 1 shows the additional footprint and spacing areas required
from Table 2 to replace the entire U.S. all-purpose energy infrastructure with WWS by 2050. Footprint area is the physical area on
the ground needed for each energy device. Spacing area is the area
between some devices, such as wind, tidal, and wave turbines,
needed to minimize interference of the wake of one turbine with
downwind turbines.
Table 2 indicates that the total new land footprint required for
the plans, averaged over the U.S. is B0.42% of U.S. land area,
mostly for solar PV power plants (rooftop solar does not take up
new land). This does not account for the decrease in footprint from
eliminating the current energy infrastructure, which includes the
footprint for mining, transporting, and refining fossil fuels and
uranium and for growing, transporting, and refining biofuels.
The only spacing over land needed for the WWS system is
between onshore wind turbines and this requires B1.6% of
U.S. land. The footprint associated with this spacing is trivial,
Energy Environ. Sci., 2015, 8, 2093–2117 | 2097
Paper
Energy & Environmental Science
Table 2 Number, capacity, footprint area, and spacing area of WWS power plants or devices needed to provide total annually-averaged end-use allpurpose load over all 50 states plus additional power needed to provide peaking and storage services, as derived in ref. 2. The numbers account for shortand moderate-distance transmission, distribution, forced and unforced maintenance, and array losses. Ref. 9 derives individual tables for each state
Energy technology
Rated power
one plant or
device (MW)
Annual power
Onshore wind
Offshore wind
Wave device
Geothermal plant
Hydroelectric plantc
Tidal turbine
Res. roof PV
Com/gov roof PVd
Solar PV plantd
Utility CSP plant
5
5
0.75
100
1300
1
0.005
0.1
50
100
Total
Peaking/storage
Additional CSPe
Solar thermale
Name-plate
capacity of
existing plus
new plants or
devices (MW)
Percent
name-plate
capacity
already
installed
2013
30.92
19.08
0.37
1.25
3.01
0.14
3.98
3.24
30.73
7.30
1 701 000
780 900
27 040
23 250
91 650
8823
379 500
276 500
2 326 000
227 300
3.59
0.00
0.00
10.35
95.87
0.00
0.94
0.64
0.08
0.00
100.00
5 841 000
2.71
4.38
7.21
136 400
469 000
0.00
0.00
6 447 000
2.46
Percent of
2050 allpurpose load
met by plant/
devicea
100
50
Total all
Total new land f
Number of
new plants or
devices needed
for U.S.
Percent of
U.S. land
area for footprint of new
plants/
devicesb
Percent of
U.S. land
area for
spacing of
new plants/
devices
328 000
156 200
36 050
208
3
8823
75 190 000
2 747 000
46 480
2273
0.00004
0.00002
0.00021
0.00078
0.02077
0.00003
0.03070
0.02243
0.18973
0.12313
1.5912
0.7578
0.0098
0.0000
0.0000
0.0004
0.0000
0.0000
0.0000
0.0000
0.388
2.359
0.07388
0.00731
0.0000
0.0000
0.469
0.416
2.359
1.591
1364
9380
The national total number of each device is the sum among all states. The number of devices in each state is the end use load in 2050 in each state
(Table 1) multiplied by the fraction of load satisfied by each source in each state (Table 3) and divided by the annual power output from each device. The
annual output equals the rated power (this table; same for all states) multiplied by the state-specific annual capacity factor of the device and accounting
for transmission, distribution, maintenance-time, and array losses. The capacity factor is determined for each device in each state in ref. 9. The state-bystate capacity factors for onshore wind turbines in 2050, accounting for transmission, distribution, maintenance-time, and array losses, are calculated
from actual 2013 state installed capacity11 and power output12 with an assumed increase in capacity factor between 2013 and 2050 due to turbine
efficiency improvements and a decrease due to diminishing quality of sites after the best are taken. The 2050 U.S. mean onshore wind capacity factor
calculated in this manner (after transmission, distribution, maintenance-time, and array losses) is 29.0%. The highest state onshore wind capacity factor
in 2050 is estimated to be 40.0%, for Oklahoma; the lowest, 17.0%, for Alabama, Kentucky, Mississippi, and Tennessee. Offshore wind turbines are
assumed to be placed in locations with hub-height wind speeds of 8.5 m s 1 or higher,13 which corresponds to a capacity factor before transmission,
distribution, maintenance, and array losses of B42.5% for the same turbine and 39.0%, in the U.S. average after losses. Short- and moderate distance
transmission, distribution, and maintenance-time losses for offshore wind and all other energy sources treated here, except rooftop PV, are assumed to
be 5–10%. Rooftop PV losses are assumed to be 1–2%. Wind array losses due to competition among turbines for the same energy are an additional
8.5%.2 The plans assume 38 (30–45)% of onshore wind and solar and 20 (15–25)% of offshore wind is subject to long-distance transmission with line
lengths of 875 (750–1000) km and 75 (50–100) km, respectively. Line losses are 4 (3–5)% per 1000 km plus 1.5 (1.3–1.8)% of power in the station
equipment. Footprint and spacing areas are calculated from the spreadsheets in ref. 9. Footprint is the area on the top surface of soil covered by an
energy technology, thus does not include underground structures. a Total end-use power demand in 2050 with 100% WWS is estimated from Table 1.
b
Total land area for each state is given in ref. 9. U.S. land area is 9 161 924 km2. c The average capacity factor for hydro is assumed to increase from its
current value to 52.5% (see text). For hydro already installed capacity is based on data for 2010. d The solar PV panels used for this calculation are Sun
Power E20 panels. The capacity factors used for residential and commercial/government rooftop solar production estimates are given in ref. 9 for each
state. For utility solar PV plants, nominal spacing between panels is included in the plant footprint area. The capacity factors assumed for utility PV are
given in ref. 9. e The installed capacities for peaking power/storage are derived in the separate grid integration study.2 Additional CSP is CSP plus
storage beyond that needed for annual power generation to firm the grid across all states. Additional solar thermal is used for soil heat storage.
Other types of storage are also used in ref. 2. f The footprint area requiring new land is equal to the footprint area for new onshore wind,
geothermal, hydroelectric, and utility solar PV. Offshore wind, wave, and tidal are in water, and so do not require new land. The footprint area for
rooftop solar PV does not entail new land because the rooftops already exist and are not used for other purposes (that might be displaced by rooftop
PV). Only onshore wind entails new land for spacing area. The other energy sources either are in water or on rooftops, or do not use additional land
for spacing. Note that the spacing area for onshore wind can be used for multiple purposes, such as open space, agriculture, grazing, etc.
and the spacing area can be used for multiple purposes, such as
agricultural land, grazing land, and open space. Landowners
can thus derive income, not only from the wind turbines on the
land, but also from farming around the turbines.
5. Resource availability
This section evaluates whether the United States has sufficient
wind, solar, geothermal, and hydroelectric resources to supply
the country’s all-purpose energy in 2050.
2098 | Energy Environ. Sci., 2015, 8, 2093–2117
5.1.
Wind
Fig. 2 shows three-dimensional computer model estimates,
derived for this study, of the U.S. annually averaged capacity
factor of wind turbines if they are installed onshore and offshore. The calculations are performed assuming a REpower
5 MW turbine with a 126 m diameter rotor (the same turbine
assumed for the roadmaps). Results are obtained for a hub
height of 100 m above the topographical surface. Spacing areas
of 4 7 rotor diameters are used for onshore turbines and
5 10 diameters for offshore turbines.
This journal is © The Royal Society of Chemistry 2015
Energy & Environmental Science
Paper
Table 3 Percent of annually-averaged 2050 U.S. state all-purpose end-use load in a WWS world from Table 1 proposed here to be met by the given
electric power generator. Power generation by each resource in each state is limited by resource availability, as discussed in Section 5. All rows add
up to 100%
State
Onshore wind
Offshore wind
Wave
Geothermal
Hydro-electric
Tidal
Res PV
Comm/gov PV
Utility PV
CSP
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
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
United States
5.00
50.00
18.91
43.00
25.00
55.00
5.00
5.00
5.00
5.00
12.00
35.00
60.00
50.00
68.00
70.00
8.45
0.65
35.00
5.00
13.00
40.00
60.00
5.00
60.00
35.00
65.00
10.00
40.00
10.00
50.00
10.00
5.00
55.00
45.00
65.00
32.50
20.00
10.00
5.00
61.00
8.00
50.00
40.00
25.00
10.00
35.00
30.00
45.00
65.00
30.92
10.00
20.00
0.00
0.00
10.00
0.00
45.00
65.00
14.93
35.00
16.00
0.00
5.00
0.00
0.00
0.00
0.00
60.00
35.00
60.00
55.00
31.00
19.00
10.00
0.00
0.00
0.00
0.00
20.00
55.50
0.00
40.00
50.00
0.00
10.00
0.00
15.00
3.00
63.00
50.00
0.00
0.00
13.90
0.00
0.00
50.00
13.00
0.00
30.00
0.00
19.08
0.08
1.00
0.00
0.00
0.50
0.00
1.00
1.00
1.00
0.30
1.00
0.00
0.00
0.00
0.00
0.00
0.00
0.40
1.00
1.00
1.00
1.00
0.00
1.00
0.00
0.00
0.00
0.00
1.00
0.80
0.00
0.80
0.75
0.00
0.00
0.00
1.00
1.00
1.00
1.00
0.00
0.00
0.10
0.00
0.00
0.50
0.50
0.00
0.00
0.00
0.37
0.00
7.00
2.00
0.00
5.00
3.00
0.00
0.00
0.00
0.00
30.00
15.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
9.00
0.00
30.00
0.00
0.00
10.00
0.00
0.00
0.00
0.00
0.00
5.00
0.00
0.00
0.00
0.00
0.00
0.50
8.00
0.00
0.00
0.65
0.00
0.00
1.00
1.25
4.84
14.96
6.49
3.44
4.48
1.24
0.56
0.00
0.05
2.27
0.33
14.96
0.03
0.08
0.25
0.01
1.51
0.11
5.79
1.53
1.42
0.69
3.61
0.00
1.15
19.15
0.94
5.02
6.48
0.01
0.35
6.54
2.69
2.95
0.10
1.54
27.25
0.74
0.05
2.90
11.10
4.26
0.16
1.03
64.35
1.29
35.42
1.14
0.96
1.43
3.01
0.01
1.00
0.00
0.00
0.50
0.00
0.00
0.50
0.04
0.08
1.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
1.00
0.03
0.06
0.00
0.00
1.00
0.00
0.00
0.00
0.00
0.50
0.10
0.00
0.10
0.03
0.00
0.00
0.00
0.05
0.85
0.08
0.30
0.00
0.00
0.00
0.00
0.00
0.05
0.30
1.00
0.00
0.00
0.14
3.50
0.23
1.30
4.40
7.50
4.20
4.00
5.00
11.2
5.50
14.0
4.00
2.85
2.45
1.50
3.20
3.20
1.30
5.40
5.40
3.90
3.50
2.50
2.40
5.10
2.80
2.20
12.0
4.50
3.54
5.50
3.60
6.00
1.00
3.20
3.20
4.00
3.30
4.40
4.00
1.70
3.50
3.00
4.00
4.20
4.20
2.90
2.50
3.30
1.10
3.98
2.20
0.15
9.30
3.50
5.50
4.00
3.35
3.85
7.80
4.30
9.00
3.20
2.90
2.20
1.50
3.00
2.10
1.20
1.80
4.80
3.30
3.20
3.00
1.60
4.40
2.10
2.00
8.00
3.30
2.80
3.80
3.20
4.00
1.00
3.00
2.80
2.20
2.35
3.70
2.80
1.80
2.20
2.50
4.00
2.80
3.50
1.50
1.70
2.90
0.70
3.24
64.38
5.66
32.00
35.66
26.52
17.56
41.09
19.65
49.98
42.55
9.67
17.84
26.22
42.77
25.75
13.79
79.74
31.34
15.01
22.24
22.32
18.61
9.89
74.00
24.35
21.95
19.86
19.23
24.22
27.25
14.35
35.76
26.53
35.05
35.70
17.46
8.00
68.76
17.78
27.70
14.40
75.04
15.84
27.97
3.65
25.46
10.73
61.66
15.84
20.77
30.73
10.00
0.00
30.00
10.00
15.00
15.00
0.00
0.00
10.00
5.00
7.00
10.00
3.00
2.50
3.00
10.00
5.00
5.00
0.00
0.00
0.00
2.00
2.00
5.00
5.00
10.00
10.00
15.75
0.00
0.00
16.00
0.00
5.00
5.00
3.00
10.00
5.00
0.00
0.00
6.30
10.00
7.00
14.00
15.00
0.00
5.00
0.00
2.00
2.00
10.00
7.30
Results suggest a U.S. mean onshore capacity factor of B30.5%
and offshore of B37.3% before transmission, distribution,
maintenance-time, and array losses (Fig. 2). Locations of strong
onshore wind resources include the Great Plains, northern
parts of the northeast, and many areas in the west. Weak wind
regimes include the southeast and the westernmost part of the
west coast continent. Strong offshore wind resources occur off
the east coast north of South Carolina and the Great Lakes. Very
good offshore wind resources also occur offshore the west coast
and offshore the southeast and gulf coasts. Table 2 indicates that
the 2050 clean-energy plans require B1.6% of U.S. onshore land
and 0.76% of U.S. onshore-equivalent land area sited offshore
This journal is © The Royal Society of Chemistry 2015
for wind-turbine spacing to power 50.0% of all-purpose annuallyaveraged 2050 U.S. energy. The mean capacity factor before
transmission, distribution, maintenance-time, and array losses
used to derive the number of onshore wind turbines needed in
Table 2 is B35% and for offshore turbines is 42.5% (Table 2,
footnote). Fig. 2 suggests that much more land and ocean areas
with these respective capacity factors or higher are available
than are needed for the roadmaps.
5.2.
Solar
World solar power resources are known to be large.16 Here, such
resources are estimated (Fig. 3) for the U.S. using a 3-D climate
Energy Environ. Sci., 2015, 8, 2093–2117 | 2099
Paper
Energy & Environmental Science
Table 4 Rooftop areas suitable for PV panels, potential capacity of suitable rooftop areas, and proposed installed capacity for both residential and
commercial/government buildings, by state. See ref. 9 for detailed calculations
Residential rooftop PV
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
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
United States
Rooftop area
suitable for
PVs in 2012
(km2)
Commercial/government rooftop PV
Proposed
Potential capacity installed capaof suitable area in city in 2050
2050 (MWdc-peak) (MWdc-peak)
Percent of
potential
capacity
installed
Rooftop area
suitable for
PVs in 2012
(km2)
Proposed
Potential capacity installed capaof suitable area in city in 2050
2050 (MWdc-peak) (MWdc-peak)
Percent of
potential
capacity
installed
59.7
7.0
7.1
36.7
336.1
48.8
32.2
10.9
229.1
108.9
12.7
16.2
116.3
65.6
31.2
32.1
52.7
54.2
32.2
60.5
58.6
105.0
52.9
35.5
72.9
11.6
20.5
29.4
13.9
10 130
760
3520
7090
83 150
11 190
4640
1940
85 950
25 760
3260
4030
17 220
10 500
4430
5220
8270
9910
4740
11 550
8560
14 970
9280
4950
12 260
1880
3140
15 120
2480
7409
414
1379
5217
48 412
6684
3301
1182
33 873
15 431
2291
2318
11 537
6652
3165
3804
6076
6582
3340
7102
6053
10 142
5564
3653
8270
1391
2228
6451
1287
73
54
39
74
58
60
71
61
39
60
70
58
67
63
71
73
73
66
70
61
71
68
60
74
67
74
71
43
52
35.4
4.2
46.9
27.0
220.6
40.6
25.1
7.3
148.4
76.9
7.5
12.2
110.6
54.8
29.4
28.1
32.3
44.6
9.4
49.0
46.4
89.0
54.6
22.6
58.0
8.2
18.0
18.8
9.3
6150
460
23 210
5330
55 330
9440
3690
1320
55 750
18 450
1950
3070
16 770
8960
4260
4680
5200
8350
1410
9530
6930
12 980
9740
3230
9980
1350
2830
9600
1680
4175
242
8841
3720
31 826
5706
2478
816
21 147
10 815
1320
1663
10 524
5354
2837
3197
3575
5447
998
5659
4591
8312
5985
2183
6396
936
1816
3855
846
68
53
38
70
58
60
67
62
38
59
68
54
63
60
67
68
69
65
71
59
66
64
61
68
64
69
64
40
50
83.1
24.7
165.2
119.2
12 730
5070
20 140
28 340
8345
3674
14 545
14 084
66
72
72
50
60.7
15.7
135.0
74.6
9520
3300
16 940
17 950
5917
2276
11 590
8417
62
69
68
47
7.2
117.0
46.2
43.5
136.4
9.9
58.4
940
16 960
8150
8590
18 870
1460
9220
639
11 623
5544
4431
13 757
1015
6057
68
69
68
52
73
70
66
6.8
101.0
34.8
21.6
87.9
7.8
36.8
920
15 000
6270
4330
12 410
1180
5950
573
9768
4349
2185
8782
765
3801
62
65
69
50
71
65
64
8.5
76.6
268.9
23.1
7.5
88.1
73.6
24.3
59.5
6.3
3197.6
1290
12 020
78 190
6360
1110
17 400
14 050
3140
9310
1050
660 290
857
7246
36 792
3160
672
9825
6774
2273
6236
754
379 513
66
60
47
50
61
56
48
72
67
72
57
8.3
45.9
216.9
20.9
4.5
65.8
37.2
16.1
48.3
4.5
2386
1280
7370
63 550
5810
680
13 190
7180
2140
7710
760
505 070
813
4083
27 485
2833
402
7339
3141
1386
4912
430
276 508
64
55
43
49
59
56
44
65
64
57
55
model that treats radiative transfer accounting for sun angles,
day/night, and clouds. The best solar resources in the U.S. are
broadly in the Southwest, followed by the Southeast, the Northwest,
then the Northeast. The land area in 2050 required for non-rooftop
solar under the plan here is equivalent to B0.394% of U.S. land
area, which is a small percentage of the area of strong solar
resources available (Fig. 3).
2100 | Energy Environ. Sci., 2015, 8, 2093–2117
The estimates of potential generation by solar rooftop PV shown
in Tables 2 and 3 are based on state-by-state calculations of available
roof areas and PV power potentials on residential, commercial, and
governmental buildings, garages, carports, parking lots, and parking
structures. Commercial and governmental buildings include all
non-residential buildings except manufacturing, industrial, and
military buildings. (Commercial buildings do include schools.)
This journal is © The Royal Society of Chemistry 2015
Energy & Environmental Science
Paper
Fig. 1 Spacing and footprint areas required from Table 2 for annual power load, beyond existing 2013 resources, to repower the U.S. state-by-state for
all purposes in 2050. The dots do not indicate the actual location of energy farms. For wind, the small dot in the middle is footprint on the ground or
water (not to scale) and the green or blue is space between turbines that can be used for multiple purposes. For others, footprint and spacing areas are
mostly the same (except tidal and wave, where only spacing is shown). For rooftop PV, the dot represents the rooftop area needed.
Fig. 2 Modeled 2006 annually averaged capacity factor for 5 MW REpower wind turbines (126 m diameter rotor) at 100 m hub height above the
topographical surface in the contiguous United States ignoring competition among wind turbines for the same kinetic energy and before transmission,
distribution, and maintenance-time losses. The model used is GATOR-GCMOM,14,15 which is nested for one year from the global to regional scale with
resolution on the regional scale of 0.61 W–E 0.51 S–N.
Ref. 4 (Supplemental Information) and ref. 9 document
how rooftop areas and generation potential are calculated for
California for four situations: residential-warm, residential-cool,
commercial/government-warm, and commercial/government-cool.
This method is applied here to calculate potential rooftop
PV generation in each state, accounting for housing units and
This journal is © The Royal Society of Chemistry 2015
building areas, available solar insolation, degradation of solar
panels over time, technology improvements over time, and DC
to AC power conversion losses.
Each state’s potential installed capacity of rooftop PV in
2050 equals the potential alternating-current (AC) generation
from rooftop PV in 2050 in the state divided by the PV capacity
Energy Environ. Sci., 2015, 8, 2093–2117 | 2101
Paper
Energy & Environmental Science
Fig. 3 Modeled 2013 annual downward direct plus diffuse solar radiation at the surface (kW h per m2 per day) available to photovoltaics in the contiguous
United States. The model used is GATOR-GCMOM,14,15 which simulates clouds, aerosols gases, weather, radiation fields, and variations in surface albedo
over time. The model is nested from the global to regional scale with resolution on the regional scale 0.61 W–E 0.51 S–N.
factor in 2050. This calculation is performed here for each state
under the four situations mentioned above: residential and
commercial/government rooftop PV systems, in warm and cool
climate zones.
Based on the analysis, we estimate that, in 2050, residential
rooftop areas (including garages and carports) could support
660 GWdc-peak of installed power. The plans here propose to
install B57% of this potential. In 2050, commercial/government
rooftop areas (including parking lots and parking structures)
could support 505 GWdc-peak of installed power. The state plans
here propose to cover B55% of installable power.
5.3.
Geothermal
The U.S. has significant traditional geothermal resources (volcanos,
geysers, and hot springs) as well as heat stored in the ground
due to heat conduction from the interior of the Earth and solar
radiation absorbed by the ground. In terms of traditional
geothermal, the U.S. has an identified resource of 9.057 GW
deliverable power distributed over 13 states, undiscovered resources
of 30.033 GW deliverable power, and enhanced recovery resources
of 517.8 GW deliverable power.17 As of April 2013, 3.386 GW of
geothermal capacity had been installed in the U.S. and another
5.15–5.523 GW was under development.18
States with identified geothermal resources (and the percent
of resource available in each state) include Colorado (0.33%),
Hawaii (2.0%), Idaho (3.68%), Montana (0.65%), Nevada (15.36%),
New Mexico (1.88%), Oregon (5.96%), Utah (2.03%), Washington
State (0.25%), Wyoming (0.43%), Alaska (7.47%), Arizona (0.29%),
and California (59.67%).17 All states have the ability to extract
2102 | Energy Environ. Sci., 2015, 8, 2093–2117
heat from the ground for heat pumps. This extracted energy
would not be used to generate electricity, but rather would be used
directly for heating, thereby reducing electric power demand for
heating, although electricity would still be needed to run heat
pumps. This electricity use for heat pumps is accounted for in the
numbers for Table 1.
The roadmaps here propose 19.8 GW of delivered existing
plus new electric power from geothermal in 2050, which is less
than the sum of identified and undiscovered resources and
much less than the enhanced recovery resources. The proposed
electric power from geothermal is limited to the 13 states with
known resources plus Texas, where recent studies show several
potential sites for geothermal. If resources in other states prove
to be cost-effective, these roadmaps can be updated to include
geothermal in those states.
5.4.
Hydroelectric
In 2010, conventional (small and large) hydroelectric power
provided 29.7 GW (260 203 GW h per year) of U.S. electric power,
or 6.3% of the U.S. electric power supply.19 The installed conventional hydroelectric capacity was 78.825 GW,19 giving the capacity
factor of conventional hydro as 37.7% in 2010. Fig. 4 shows the
installed conventional hydroelectric by state in 2010.
In addition, 23 U.S. states receive an estimated 5.103 GW of
delivered hydroelectric power from Canada. Assuming a capacity
factor of 56.47%, Canadian hydro currently provides B9.036 GW
worth of installed capacity to the U.S. This is included as part
of existing hydro capacity in this study to give a total existing
(year-2010) capacity in the U.S. in Table 2 of 87.86 GW.
This journal is © The Royal Society of Chemistry 2015
Energy & Environmental Science
Paper
Fig. 4 Installed conventional hydroelectric by U.S. state in 2010.19
Under the plan proposed here, conventional hydro would
supply 3.01% of U.S. total end-use all-purpose power demand
(Table 2), or 47.84 GW of delivered power in 2050. In 2010, U.S.
plus Canadian delivered 34.8 GW of hydropower, only 13.0 GW
less than that needed in 2050. This additional power will be
supplied by adding three new dams in Alaska with a total
capacity of 3.8 GW (Table 2) and increasing the capacity factor
on existing dams from a Canada-plus-US average of B39% to
52.5%. Increasing the capacity factor is feasible because existing
dams currently provide much less than their maximum capacity,
primarily due to an oversupply of energy available from fossil
fuel sources, resulting in less demand for hydroelectricity. In
some cases, hydroelectricity is not used to its full extent in
deference to other priorities affecting water use.
Whereas, we believe modestly increasing hydroelectric capacity factors is possible, if it is not, additional hydroelectric
capacity can be obtained by powering presently non-powered
dams. In addition to the 2500-plus dams that provide the
78.8 GW of installed conventional power and 22.2 GW of installed
pumped-storage hydroelectric power, the U.S. has over 80 000 dams
that are not powered at present. Although only a small fraction
of these dams can feasibly be powered, ref. 20 estimates that
the potential amounts to 12 GW of capacity in the contiguous
48 states. Two-thirds of this comes from just 100 dams, but
potential exists in every state. Over 80% of the top 100 dams
with the most new-powering capacity are navigation locks on
the Ohio, Mississippi, Alabama, and Arkansas Rivers and their
tributaries. Illinois, Kentucky, and Arkansas each have over 1 GW
This journal is © The Royal Society of Chemistry 2015
of potential. Alabama, Louisiana, Pennsylvania, and Texas each
have 0.5–1 GW of potential. Because the costs and environmental
impacts of such dams have already been incurred, adding
electricity generation to these dams is less expensive and faster
than building a new dam with hydroelectric capacity.
In addition, ref. 21 estimates that the U.S. has an additional
low-power and small-hydroelectric potential of 30–100 GW
of delivered power – far more than the 11.3 GW of additional
generation proposed here. The states with the most additional
low- and small-hydroelectric potential are Alaska, Washington
State, California, Idaho, Oregon, and Montana. However, 33 states
can more than double their small hydroelectric potential and
41 can increase it by more than 50%.
5.5.
Tidal
Tidal (or ocean current) is proposed to contribute about 0.14%
of U.S. total power in 2050 (Table 2). The U.S. currently has the
potential to generate 50.8 GW (445 TW h per year) of delivered
power from tidal streams.22 States with the greatest potential
offshore tidal power include Alaska (47.4 GW), Washington
State (683 MW), Maine (675 MW), South Carolina (388 MW),
New York (280 MW), Georgia (219 MW), California (204 MW),
New Jersey (192 MW), Florida (166 MW), Delaware (165 MW),
Virginia (133 MW), Massachusetts (66 MW), North Carolina
(66 MW), Oregon (48 MW), Maryland (35 MW), Rhode Island
(16 MW), Alabama (7 MW), Texas (6 MW), Louisiana (2 MW).
The available power in Maine, for example, is distributed over
15 tidal streams. The present state plans call for extracting
Energy Environ. Sci., 2015, 8, 2093–2117 | 2103
Paper
Energy & Environmental Science
B2.2 GW of delivered power, which would require an installed
capacity of B8.82 GW of tidal turbines.
5.6.
Wave
Wave power is proposed to contribute 0.37%, or about 5.85 GW,
of the U.S. total end-use power demand in 2050 (Table 2). The
U.S. has a recoverable delivered power potential (after accounting
for array losses) of 135.8 GW (1190 TW h) along its continental
shelf edge.23 This includes 28.5 GW of recoverable power along
the West Coast, 18.3 GW along the East Coast, 6.8 GW along the
Gulf of Mexico, 70.8 GW along Alaska’s coast, 9.1 GW along
Hawaii’s coast, and 2.3 GW along Puerto Rico’s coast. Thus, all
states border the oceans have wave power potential. The available supply is B23 times the delivered power proposed under
this plan.
6. Matching electric power supply with
demand
Ref. 2 develops and applies a grid integration model to determine the quantities and costs of additional storage devices and
generators needed to ensure that the 100% WWS system developed here for the U.S. can match load without loss every 30 s for
six years (2050–2055) while accounting for the variability and
uncertainty in WWS resources. Wind and solar time-series are
derived from 3-D global model simulations that account for
extreme events, competition among wind turbines for kinetic
energy, and the feedback of extracted solar radiation to roof and
surface temperatures.
Solutions to the grid integration problem are obtained by
prioritizing storage for excess heat (in soil and water) and
electricity (in ice, water, phase-change material tied to CSP, pumped
hydro, and hydrogen); using hydroelectric only as a last resort; and
using demand response to shave periods of excess demand over
supply. No batteries (except in electric vehicles), biomass, nuclear
power, or natural gas are needed. Frequency regulation of the grid
can be provided by ramping up/down hydroelectric, stored CSP or
pumped hydro; ramping down other WWS generators and storing
the electricity in heat, cold, or hydrogen instead of curtailing; and
using demand response.
The study is able to derive multiple low-cost stable solutions
with the number of generators across the U.S. listed in Table 2
here, except that that study applies to the continental U.S., so
excludes data for Alaska and Hawaii. Numerous low-cost solutions
are found, suggesting that maintaining grid reliability upon 100%
conversion to WWS is economically feasible and not a barrier to
the conversion.
7. Costs of electric power generation
In this section, current and future full social costs (including
capital, land, operating, maintenance, storage, fuel, transmission, and externality costs) of WWS electric power generators
versus non-WWS conventional fuel generators are estimated.
These costs do not include the costs of storage necessary to keep
2104 | Energy Environ. Sci., 2015, 8, 2093–2117
the grid stable, which are quantified in ref. 2. The estimates here
are based on current cost data and trend projections for individual generator types and do not account for interactions among
energy generators and major end uses (e.g., wind and solar
power in combination with heat pumps and electric vehicles24).
The estimates are only a rough approximation of costs in a future
optimized renewable energy system.
Table 5 presents 2013 and 2050 U.S. averaged estimates of fully
annualized levelized business costs of electric power generation
for conventional fuels and WWS technologies. Whereas, several
studies have calculated levelized costs of present-day renewable
energy,25,26 few have estimated such costs in the future. The
methodology used here for determining 2050 levelized costs is
described in the ESI.† Table 5 indicates that the 2013 business
costs of hydroelectric, onshore wind, utility-scale solar, and solar
thermal for heat are already similar to or less than the costs of
natural gas combined cycle. Residential and commercial rooftop
PV, offshore wind, tidal, and wave are more expensive. However,
residential rooftop PV costs are given as if PV is purchased for an
individual household. A common business model today is where
multiple households contract together with a solar provider,
thereby decreasing the average cost.
By 2050, however, the costs of all WWS technologies are expected
to drop, most significantly for offshore wind, tidal, wave, rooftop PV,
CSP, and utility PV, whereas conventional fuel costs are expected to
rise. Because WWS technologies have zero fuel costs, the drop in
their costs over time is due primarily to technology improvements.
In addition, WWS costs are expected to decline due to less expensive
manufacturing and streamlined project deployment from increased
economies of scale. Conventional fuels, on the other hand, face
rising costs over time due to higher labor and transport costs for
mining, transporting, and processing fuels continuously over the
lifetime of fossil-fuel plants.
The 2050 U.S. air pollution cost (Table 7) plus global climate
cost (Table 8) per unit total U.S. energy produced by the conventional fuel sector in 2050 (Table 1) corresponds to a mean 2050
externality cost (in 2013 dollars) due to conventional fuels
of B$0.17 (0.085–0.41) per kWh. Such costs arise due to air
pollution morbidity and mortality and global warming damage
(e.g. coastline losses, fishery losses, heat stress mortality, increased
drought and wildfires, and increased severe weather) caused by
conventional fuels. When externality costs are added to the business costs of conventional fuels, all WWS technologies cost less
than conventional technologies in 2050.
Table 6 provides the mean value of the 2013 and 2050
levelized costs of energy (LCOEs) for conventional fuels and
the mean value of the LCOE of WWS fuels in 2050 by state. The
table also gives the 2050 energy, health, and global climate cost
savings per person. The electric power cost of WWS in 2050 is not
directly comparable with the BAU electric power cost, because
the latter does not integrate transportation, heating/cooling,
or industry energy costs. Conventional vehicle fuel costs, for
example, are a factor of 4–5 higher than those of electric
vehicles, yet the cost of BAU electricity cost in 2050 does not
include the transportation cost, whereas the WWS electricity
cost does. Nevertheless, based on the comparison, WWS energy in
This journal is © The Royal Society of Chemistry 2015
Energy & Environmental Science
Paper
Table 5 Approximate fully annualized, unsubsidized 2013 and 2050 U.S.-averaged costs of delivered electricity, including generation, short- and longdistance transmission, distribution, and storage, but not including external costs, for conventional fuels and WWS power (2013 U.S. $ per kWh-delivered)a
Technology year 2013
Technology year 2050
Technology
LCHB
HCLB
Average
LCHB
HCLB
Average
Advanced pulverized coal
Advanced pulverized coal w/CC
IGCC coal
IGCC coal w/CC
Diesel generator (for steam turb.)
Gas combustion turbine
Combined cycle conventional
Combined cycle advanced
Combined cycle advanced w/CC
Fuel cell (using natural gas)
Microturbine (using natural gas)
Nuclear, APWR
Nuclear, SMR
Distributed gen. (using natural gas)
Municipal solid waste
Biomass direct
Geothermal
Hydropower
On-shore wind
Off-shore wind
CSP no storage
CSP with storage
PV utility crystalline tracking
PV utility crystalline fixed
PV utility thin-film tracking
PV utility thin-film fixed
PV commercial rooftop
PV residential rooftop
Wave power
Tidal power
Solar thermal for heat ($ per kWh-th)
0.083
0.116
0.094
0.144
0.187
0.191
0.082
n.a.
n.a.
0.122
0.123
0.082
0.095
n.a.
0.204
0.132
0.087
0.063
0.076
0.111
0.131
0.081
0.073
0.078
0.073
0.077
0.098
0.130
0.276
0.147
0.057
0.113
0.179
0.132
0.249
0.255
0.429
0.097
n.a.
n.a.
0.200
0.149
0.143
0.141
n.a.
0.280
0.181
0.139
0.096
0.108
0.216
0.225
0.131
0.107
0.118
0.104
0.118
0.164
0.225
0.661
0.335
0.070
0.098
0.148
0.113
0.197
0.221
0.310
0.090
n.a.
n.a.
0.161
0.136
0.112
0.118
n.a.
0.242
0.156
0.113
0.080
0.092
0.164
0.178
0.106
0.090
0.098
0.089
0.098
0.131
0.177
0.468
0.241
0.064
0.079
0.101
0.084
0.098
0.250
0.193
0.105
0.096
0.112
0.133
0.152
0.073
0.080
0.254
0.180
0.105
0.081
0.055
0.064
0.093
0.091
0.061
0.061
0.063
0.061
0.062
0.072
0.080
0.156
0.084
0.051
0.107
0.151
0.115
0.146
0.389
0.404
0.137
0.119
0.143
0.206
0.194
0.121
0.114
0.424
0.228
0.133
0.131
0.093
0.101
0.185
0.174
0.111
0.091
0.098
0.090
0.098
0.122
0.146
0.407
0.200
0.074
0.093
0.126
0.100
0.122
0.319
0.299
0.121
0.108
0.128
0.170
0.173
0.097
0.097
0.339
0.204
0.119
0.106
0.074
0.082
0.139
0.132
0.086
0.076
0.080
0.075
0.080
0.097
0.113
0.282
0.142
0.063
a
LCHB = low cost, high benefits case; HCLB = high cost, low benefits case. The methodology for determining costs is given in the ESI. For the year
2050 100% WWS scenario, costs are shown for WWS technologies; for the year 2050 BAU case, costs of WWS are slightly different. The costs assume
$0.0115 (0.11–0.12) per kWh for standard (but not extra-long-distance) transmission for all technologies except rooftop solar PV (to which no
transmission cost is assigned) and $0.0257 (0.025–0.0264) per kWh for distribution for all technologies. Transmission and distribution losses are
accounted for. CC = carbon capture; IGCC = integrated gasification combined cycle; AWPR = advanced pressurized-water reactor; SMR = small
modular reactor; PV = photovoltaics. CSP w/storage assumes a maximum charge to discharge rate (storage size to generator size ratio) of 2.62 : 1.
Solar thermal for heat assumes $3600–$4000 per 3.716 m2 collector and 0.7 kW-th per m2 maximum power.2
2050 will save the average U.S. consumer $260 (190–320) per year
in energy costs ($2013 dollars). In addition, WWS will save $1500
(210–6000) per year in health costs, and $8300 (4700–17 600) per
year in global climate costs. The total up-front capital cost of the
2050 WWS system is B$13.4 trillion (B$2.08 mil. per MW).
8. Air pollution and global warming
damage costs eliminated by WWS
Conversion to a 100% WWS energy infrastructure in the U.S. will
eliminate energy-related air pollution mortality and morbidity and
the associated health costs, and it will eliminate energy-related
climate change costs to the world while causing variable climate
impacts on individual states. This section discusses these topics.
8.A.
Air pollution cost reductions due to WWS
The benefits of reducing air pollution mortality and its costs in
each U.S. state can be quantified with a top-down approach and
a bottom-up approach.
This journal is © The Royal Society of Chemistry 2015
The top-down approach. The premature human mortality rate
in the U.S. due to cardiovascular disease, respiratory disease,
and complications from asthma due to air pollution has been
estimated conservatively by several sources to be at least
50 000–100 000 per year. In ref. 27, the U.S. air pollution
mortality rate is estimated at about 3% of all deaths. The allcause death rate in the U.S. is about 833 deaths per 100 000
people and the U.S. population in 2012 was 313.9 million. This
suggests a present-day air pollution mortality rate in the U.S. of
B78 000 per year. Similarly, from ref. 15, the U.S. premature
mortality rate due to ozone and particulate matter is calculated
with a three-dimensional air pollution-weather model to be
50 000–100 000 per year. These results are consistent with those
of ref. 28, who estimated 80 000 to 137 000 premature mortalities
per year due to all anthropogenic air pollution in the U.S. in
1990, when air pollution levels were higher than today.
Bottom-up approach. This approach involves combining
measured countywide or regional concentrations of particulate
matter (PM2.5) and ozone (O3) with a relative risk as a function
of concentration and with population by county. From these
Energy Environ. Sci., 2015, 8, 2093–2117 | 2105
(a) 2013 average
LCOE conventional fuels
(b per kWh)
11.4
15.1
11.2
11.2
12.5
9.9
12.5
12.0
12.7
11.4
22.7
9.4
10.1
10.6
9.4
9.6
10.1
11.2
12.5
12.0
12.5
10.6
9.4
11.2
10.1
9.4
9.4
9.4
12.5
12.0
11.2
14.5
11.1
9.4
10.6
10.5
9.4
12.0
12.5
11.1
9.4
10.1
10.7
9.4
12.5
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
New Mexico
New York
North Carolina
North Dakota
Ohio
Oklahoma
Oregon
Pennsylvania
Rhode Island
South Carolina
South Dakota
Tennessee
Texas
Utah
Vermont
10.7
15.5
10.3
10.8
10.7
9.9
11.0
11.1
11.6
10.7
30.3
9.0
9.8
10.4
9.3
9.4
9.6
10.8
11.0
11.1
11.0
10.8
9.3
10.8
9.8
9.0
9.3
9.0
11.0
11.1
10.3
12.6
10.5
9.3
10.4
10.5
9.0
11.1
11.0
10.5
9.3
9.6
10.7
9.0
11.0
(b) 2050 average
LCOE conventional fuels
(b per kWh)
8.7
11.1
8.7
8.2
9.7
8.5
11.9
12.8
9.1
10.1
11.9
9.0
9.4
9.3
8.4
8.3
8.7
11.5
11.4
12.5
12.7
11.4
9.8
9.5
8.5
9.0
8.3
9.4
10.8
12.4
9.2
13.4
11.1
8.4
9.6
8.1
10.0
9.8
12.8
11.1
8.1
8.6
8.7
8.9
8.7
(c) 2050 average
LCOE of WWS
(b per kWh)
693
483
250
731
161
312
114
65
319
293
1785
188
231
436
392
349
516
242
143
72
26
157
98
531
368
260
382
98
144
57
437
112
131
483
369
655
33
341
48
193
372
338
384
127
336
(d) 2050 average
electricity cost savings per person per
year ($ per person
per year)
1464
886
1852
1132
2503
1033
1475
2361
1099
1568
1028
1051
1790
1922
1270
962
1492
1250
739
1725
1148
1280
963
1357
1377
1021
973
1628
967
1272
1230
1168
1322
598
1834
1189
894
1746
1144
1511
719
1620
1267
1640
726
(e) 2050 average air
quality damage savings per person per
year due to WWS ($
per person per year)
1808
1042
958
1585
494
165
215
1218
1905
1045
2176
349
18
129
903
1130
919
3019
1713
556
460
468
299
1975
1190
564
1366
589
880
675
523
112
741
482
55
1778
719
28
766
1560
653
1119
1456
93
1392
(f) 2050 average climate cost savings to
state per person per
year due to WWS ($
per person per year)
15 046
25 692
4266
12 855
4731
7957
5359
10 045
3789
7198
8762
4228
9736
16 770
17 063
13 972
19 346
30 706
8029
5390
5192
9495
8074
12 125
11 418
19 245
15 420
4110
5621
6174
18 095
4508
5170
47 504
12 065
15 855
4305
10 799
6094
8396
9972
7576
10 273
8405
4933
(g) 2050 average climate cost savings to
world per person
per year due to
WWS ($ per person
per year)
17 203
27 060
6368
14 717
7395
9303
6948
12 470
5207
9059
11 575
5468
11 757
19 128
18 726
15 283
21 354
32 197
8912
7187
6365
10 932
9134
14 013
13 162
20 526
16 775
5836
6732
7504
19 762
5789
6623
48 584
14 268
17 699
5232
12 886
7286
10 100
11 063
9534
11 923
10 173
5995
(h) 2050 average
energy + air quality
damage + world climate cost savings
due to WWS ($ per
person per year)
Table 6 Mean values of the levelized cost of energy (LCOE) for conventional fuels in 2013 and 2050 and for WWS fuels in 2050. The LCOEs do not include externality costs. The 2013 and 2050 values
are used to calculate energy cost savings per person per year in each state (see footnotes). Health and climate cost savings per person per year are derived from data in Section 8. All costs are in 2013
dollars. Low-cost and high-cost results can be found in the ‘‘Expanded cost results by state’’ tab in ref. 9a
Paper
Energy & Environmental Science
2106 | Energy Environ. Sci., 2015, 8, 2093–2117
This journal is © The Royal Society of Chemistry 2015
(a) The 2013 LCOE cost for conventional fuels in each state combines the estimated distribution of conventional and WWS generators in 2013 with 2013 mean LCOEs for each generator from
Table 5. Costs include all-distance transmission, pipelines, and distribution, but they exclude externalities. (b) Same as (a), but for a 2050 BAU case (ESI) and 2050 LCOEs for each generator from
Table 5. (c) The 2050 LCOE of WWS in the state combines the 2050 distribution of WWS generators from Table 3 with the 2050 mean LCOEs for each WWS generator from Table 5. The LCOE
accounts for all-distance transmission and distribution and storage (footnotes to Tables 2 and 5). (d) The total cost of electricity use in the electricity sector in the BAU (the product of electricity
use and the LCOE) less the total cost in the electricity sector in the WWS scenario and less the annualized cost of the assumed efficiency improvements in the electricity sector in the WWS
scenario. See ESI and ref. 9, for details. (e) Total cost of air pollution per year in the state from Table 7 divided by the 2050 population of the state. (f) Total climate cost per year in the state due to
U.S. emissions (Table 8) divided by the 2050 population of the state. (g) Total climate cost per year to the world due to state’s emissions (Table 8) divided by the 2050 population of the state. (h)
The sum of columns (d), (e), and (g).
Virginia
Washington
West Virginia
Wisconsin
Wyoming
United States
Paper
a
6898
5229
40 873
10 779
77 783
10 019
5501
4195
38911
9264
75 614
8265
676
635
172
548
612
661
1255
949
1259
1197
787
1491
142
85
703
318
1382
263
11.2
9.4
9.2
10.6
8.3
9.78
11.1
9.4
10.6
10.1
9.9
11.11
State
10.5
9.0
10.4
11.3
9.9
10.55
(c) 2050 average
LCOE of WWS
(b per kWh)
(a) 2013 average
LCOE conventional fuels
(b per kWh)
Table 6
(continued)
(b) 2050 average
LCOE conventional fuels
(b per kWh)
(d) 2050 average
electricity cost savings per person per
year ($ per person
per year)
(e) 2050 average air
quality damage savings per person per
year due to WWS ($
per person per year)
(f) 2050 average climate cost savings to
state per person per
year due to WWS ($
per person per year)
(g) 2050 average climate cost savings to
world per person
per year due to
WWS ($ per person
per year)
(h) 2050 average
energy + air quality
damage + world climate cost savings
due to WWS ($ per
person per year)
Energy & Environmental Science
This journal is © The Royal Society of Chemistry 2015
three pieces of information, low, medium, and high estimates
of mortality due to PM2.5 and O3 pollution are calculated with a
health-effects equation.15
Table 7 shows the resulting estimates of premature mortality for
each state in the U.S. due to the sum of PM2.5 and O3, as calculated
with 2010–2012 air quality data. The mean values for the U.S. for
PM2.5 are B48 000 premature mortalities per year, with a range of
12 000–95 000 per year and for O3 are B14 000 premature mortalities per year, with a range of 7000–21 000 per year. Thus, overall,
the bottom-up approach gives B62 000 (19 000–115 000) premature
mortalities per year for PM2.5 plus O3. The top-down estimate
(50 000–100 000), from ref. 15, is within the bottom-up range.
Mortality and non-mortality costs of air pollution. The total
damage cost of air pollution from fossil fuel and biofuel combustion and evaporative emissions is the sum of mortality costs,
morbidity costs, and non-health costs such as lost visibility and
agricultural output. We estimate this total damage cost of air
pollution in each state S in a target year Y as the product of an
estimate of the number of premature deaths due to air pollution
and the total cost of air pollution per death. The total cost of air
pollution premature death is equal to the value of a statistical life
multiplied by the ratio of the value of total mortality-plus-nonmortality impacts to mortality impacts. The number of premature deaths in the base year is as described in the footnote to
Table 7. The number of deaths in 2050 is estimated by scaling
the base-year number by factors that account for changes in
population, exposure, and air pollution. The method is fully
documented in the ESI† and ref. 9.
Given this information, the total social cost due to air pollution
mortality, morbidity, lost productivity, and visibility degradation
in the U.S. in 2050 is conservatively estimated from the B45 800
(11 600–104 000) premature mortalities per year to be $600
(85–2400) bil. per year using $13.1 (7.3–23.0) million per mortality
in 2050. Eliminating these costs in 2050 represents a savings
equivalent to B3.6 (0.5–14.3)% of the 2014 U.S. gross domestic
product of $16.8 trillion. The U.S.-averaged payback time of the
cost of installing all WWS generators in Table 2 due to the avoided
air pollution costs alone is 20 (5–140) years.
8.B. Global-warming damage costs eliminated by 100% WWS
in each state
This section provides estimates of two kinds of climate change
costs due to greenhouse gas (GHG) emissions from energy use
(Table 8). GHG emissions are defined here to include emissions
of carbon dioxide, other greenhouse gases, and air pollution
particles that cause global warming, converted to equivalent carbon
dioxide. A 100% WWS system in each state would eliminate such
damages. The two kinds of costs calculated are
(1) The cost of climate change impacts to the world and U.S.
attributable to emissions of GHGs from each of the 50 states, and
(2) The cost of climate-change impacts borne by each state
due to U.S. GHG emissions.
Costs due to climate change include coastal flood and real
estate damage costs, energy-sector costs, health costs due to heat
stress and heat stroke, influenza and malaria costs, famine costs,
ocean acidification costs, increased drought and wildfire costs,
Energy Environ. Sci., 2015, 8, 2093–2117 | 2107
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Energy & Environmental Science
Table 7 Avoided air pollution PM2.5 plus O3 premature mortalities by state in 2010–2012 and 2050 and mean avoided costs (in 2013 dollars) from
mortalities and morbidities in 2050a
State
2012 population
2010–2012
low avoided
mortalities
per year
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
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
United States
4 822 023
731 449
6 553 255
2 949 131
38 041 430
5 187 582
3 590 347
917 092
19 317 568
9 919 945
1 392 313
1 595 728
12 875 255
6 537 334
3 074 186
2 885 905
4 380 415
4 601 893
1 329 192
5 884 563
6 646 144
9 883 360
5 379 139
2 984 926
6 021 988
1 005 141
1 855 525
2 758 931
1 320 718
8 864 590
2 085 538
19 570 261
9 752 073
699 628
11 544 225
3 814 820
3 899 353
12 763 536
1 050 292
4 723 723
833 354
6 456 243
26 059 203
2 855 287
626 011
8 185 867
6 897 012
1 855 413
5 726 398
576 412
313 281 717
291
23
517
126
3825
262
235
61
818
632
51
73
942
523
164
121
280
236
43
436
328
565
205
167
361
37
74
212
54
467
117
901
543
18
911
186
132
921
53
288
26
432
1294
209
20
436
242
101
294
23
19 273
2010–2012
mean
avoided mortalities per
year
2010–2012
high avoided
mortalities
per year
2050 mean
avoided mortalities per
year
2050 mean
avoided cost
($mil. per
year)
954
84
1518
448
12 528
699
729
198
2681
2043
192
219
3150
1704
540
377
887
780
136
1350
1033
1744
692
553
1123
139
245
567
171
1528
353
3137
1672
57
2920
606
453
3065
166
948
81
1380
4217
598
62
1352
839
327
934
62
62 241
1784
155
2729
859
23 194
1215
1338
367
5018
3799
374
395
5909
3170
1010
695
1638
1462
250
2475
1906
3192
1305
1036
2065
266
460
986
317
2854
640
5963
3065
105
5403
1131
849
5730
307
1774
150
2558
7869
1060
115
2483
1592
610
1727
108
115 461
596
71
1911
301
9778
568
393
132
3118
1585
121
185
1811
1037
272
220
542
465
71
966
628
927
475
320
700
81
142
632
119
946
184
1708
1485
29
1551
412
403
1649
87
663
45
1047
4142
598
36
1051
832
147
544
32
45 754
7799
922
24 988
3937
127 868
7428
5142
1723
40 770
20 733
1584
2420
23 678
13 562
3552
2878
7089
6075
927
12 630
8206
12 129
6213
4186
9156
1054
1863
8261
1557
12 373
2409
22 342
19 417
385
20 279
5383
5265
21 563
1131
8667
595
13 688
54 161
7821
473
13 740
10 887
1920
7109
417
598 356
a
Premature mortality due to ozone exposure is estimated on the basis of the 8 h maximum ozone each day over the period 2010–2012.29 Relative risks and the
ozone-health-risk equation are as in ref. 15. The low ambient concentration threshold for ozone premature mortality is assumed to be 35 ppbv (ref. 15, and
reference therein). Mortality due to PM2.5 exposure is estimated on the basis of daily-averaged PM2.5 over the period 2010–201229 and the relative risks30 for
long-term health impacts of PM2.5 are applied to all ages as in ref. 31 rather than to those over 30 years old as in ref. 30. The threshold for PM2.5 is zero but
concentrations below 8 mg m 3 are down-weighted as in ref. 15. For each county in each state, mortality rates are averaged over the three-year period for each
station to determine the station with the maximum average mortality rate. Daily air quality data from that station are then used with the 2012 county
population and the relative risk in the health effects equation to determine the premature mortality in the county. For the PM2.5 calculations, data are not
available for 25% of the population and for the ozone calculations data are not available for 26% of the population. For these populations, mortality rates are
set equal to the minimum county value for a given state, as determined per the method specified above. In cases where 2012 data are unavailable, data from
2013 are used instead. PM2.5 and ozone concentrations shown in the table above reflect the three-year average concentrations at the representative station(s)
within each county. Since mortality rates are first calculated for each monitoring site in a county and then averaged over each station in the county, these
average concentrations cannot directly be used to reproduce each county’s mortality rate. In cases where n/a is shown, data within that county are not available
(and the minimum county mortality rate within the state is used in these cases, as specified above). 2050 estimates of avoided mortality are derived from
2010–2012 estimates as detailed in the ESI. The cost of avoided mortalities plus associated morbidities is determined as described in the text.
2108 | Energy Environ. Sci., 2015, 8, 2093–2117
This journal is © The Royal Society of Chemistry 2015
Energy & Environmental Science
severe weather costs, and increased air pollution health costs.
These costs are partly offset by fewer extreme cold events and
associated reductions in illnesses and mortalities and gains in
agriculture in some regions. Net costs due to global-warmingrelevant emissions are embodied in the social cost of carbon
dioxide. The range of the 2050 social cost of carbon from recent
papers is $500 (282–1063) per metric tonne-CO2e in 2013 dollars
(ESI†). This range is used to derive the costs in Table 8. State costs
due to their own air pollution also take into account a study of the
state-by-state damage versus benefits of climate change (ESI†).
Table 8 indicates that, in some, primarily northern cold states,
climate change due to total U.S. emissions may contribute to
fewer extreme cold events and improved agriculture; however, the
sum of all states’ emissions cause a net positive damage to the
U.S. as a whole (with total damage caused by all states’ emissions
in 2050 of $265 bil. per year in 2013 dollars) and to the world
(with total damage to the world caused by all states’ emissions of
$3.3 (1.9–7.1) tril. per year). Thus, the global climate cost savings
per person in the U.S. due to reducing all U.S. climate-relevant
emissions through a 100% WWS system is B$8300 (4700–17 600)
per person per year (in 2013 dollars) (Table 6).
9. Impacts of WWS on jobs and
earnings in the electric power sector
This section provides estimates of the jobs and total earnings
created by implementing WWS-based electricity and the jobs and
earnings lost in the displaced fossil-fuel electricity and petroleum
industries. The analysis does not include the potential job and
revenue gains in other affected industries such as the manufacturing of electric vehicles, fuel cells or electricity storage because
of the additional complexity required and greater uncertainty as to
where those jobs will be located.
9.A.
JEDI job creation analysis
Changes in jobs and total earnings are estimated here first with
the Jobs and Economic Development Impact (JEDI) models.33
These are economic input–output models programmed by default
for local and state levels. They incorporate three levels of impacts:
(1) project development and onsite labor impacts; (2) local
revenue and supply chain impacts; and (3) induced impacts. Jobs
and revenue are reported for two phases of development: (1) the
construction period and (2) operating years.
Scenarios for wind and solar powered electricity generation
are run assuming that the WWS electricity sector is fully developed by 2050. Existing capacities are excluded from the calculations. As construction period jobs are temporary in nature, JEDI
models report job creation in this stage as full-time equivalents
(FTE, equal to 2080 hours of work per year). This analysis
assumes that each year from 2010 to 2050 1/40th of the WWS
infrastructure is built.
The JEDI models are economic input–output models that
have several uncertainties.34 To evaluate the robustness of the
models, we compared results with calculations derived from a
compilation of 15 different renewable energy job creation models.35
This journal is © The Royal Society of Chemistry 2015
Paper
Table 8 Percent of 2010 world CO2 emissions by state,32 mean estimate
of avoided (+) or increased ( 1) 2050 climate change cost in each state
due to converting the U.S. as a whole to 100% WWS for all purposes, and
low, medium, and high estimates of avoided 2050 global climate-change
costs due to converting to 100% WWS for all purposes in each state
individually. All costs are in 2013 dollars
2010
State
2050
2050 avoided global
climate cost ($2013 bil.
per year)
Medium
avoided state
Percent of climate costs
world CO2 ($2013 bil.
emissions per year)
Low
Alabama
0.39
Alaska
0.12
Arizona
0.28
Arkansas
0.20
California
1.04
Colorado
0.28
Connecticut
0.10
Delaware
0.04
Florida
0.68
Georgia
0.46
Hawaii
0.06
Idaho
0.05
Illinois
0.68
Indiana
0.62
Iowa
0.25
Kansas
0.22
Kentucky
0.45
Louisiana
0.67
Maine
0.05
Maryland
0.19
Massachusetts
0.20
Michigan
0.47
Minnesota
0.28
Mississippi
0.18
Missouri
0.40
Montana
0.10
Nebraska
0.16
Nevada
0.10
New Hampshire 0.05
New Jersey
0.33
New Mexico
0.17
New York
0.48
North Carolina
0.37
North Dakota
0.16
Ohio
0.70
Oklahoma
0.32
Oregon
0.11
Pennsylvania
0.74
Rhode Island
0.03
South Carolina
0.23
South Dakota
0.04
Tennessee
0.31
Texas
1.98
Utah
0.19
Vermont
0.02
Virginia
0.29
Washington
0.21
West Virginia
0.29
Wisconsin
0.29
Wyoming
0.19
United States
16.2
9.63
1.09
12.92
5.51
25.24
1.19
0.75
0.89
70.63
13.82
3.35
0.80
0.24
0.91
2.53
3.38
4.37
14.68
2.15
4.07
3.29
4.44
1.93
6.09
7.91
0.58
2.62
2.99
1.42
6.57
1.02
2.15
10.89
0.31
0.61
8.06
4.24
0.35
0.76
8.95
0.54
9.46
62.26
0.45
0.91
7.40
7.28
0.26
3.26
0.32
265.3
Medium High
170.6
80.1
57.0
26.8
122.5
57.6
95.2
44.7
514.4 241.7
121.8
57.2
39.8
18.7
15.6
7.3
299.0 140.5
202.6
95.2
28.7
13.5
20.7
9.7
274.1 128.8
251.9 118.3
101.6
47.7
89.0
41.8
195.7
91.9
317.8 149.3
21.4
10.1
84.0
39.5
79.0
37.1
191.5
89.9
110.9
52.1
79.6
37.4
161.6
75.9
42.3
19.9
62.9
29.5
44.4
20.9
19.3
9.0
127.8
60.0
75.5
35.4
183.5
86.2
161.7
76.0
65.2
30.6
284.0 133.4
152.9
71.8
53.9
25.3
283.8 133.3
12.8
6.0
102.5
48.1
17.6
8.2
136.3
64.0
935.0 439.3
85.3
40.1
6.8
3.2
128.2
60.2
102.4
48.1
126.4
59.4
117.1
55.0
85.1
40.0
7058.7 3316.1
45.2
15.1
32.4
25.2
136.2
32.3
10.5
4.1
79.2
53.7
7.6
5.5
72.6
66.7
26.9
23.6
51.8
84.2
5.7
22.2
20.9
50.7
29.4
21.1
42.8
11.2
16.7
11.8
5.1
33.8
20.0
48.6
42.8
17.3
75.2
40.5
14.3
75.2
3.4
27.1
4.6
36.1
247.6
22.6
1.8
34.0
27.1
33.5
31.0
22.5
1869.4
These included input/output models such as JEDI and bottom-up
analytical models. Table 9 suggests that the JEDI models estimate
the number of 40-year operation jobs as 2.0 million across
Energy Environ. Sci., 2015, 8, 2093–2117 | 2109
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Energy & Environmental Science
the U.S. due to WWS. This estimate falls within the range of
0.9–4.8 million jobs derived from the aggregation of models
shown in Table 10.
of studies have estimated that efficiency measures can reduce
energy use in non-transportation sectors by up to 30%.50–54
9.B.
11. Timeline for implementing the
roadmaps
Job loss analysis
Table 11 provides estimates of the number of U.S. jobs that may
be lost in the oil, gas, and uranium extraction and production
industries; petroleum refining industry; coal, gas, and nuclear
power plant operation industries; fuel transportation industry,
and other fuel-related industries upon a shift to WWS.
Although the petroleum industry will lose jobs upon the
elimination of extraction of crude oil in the U.S., jobs in the
production of non-fuel petroleum commodities such as lubricants,
asphalt, petrochemical feedstocks, and petroleum coke will remain.
The number of these jobs is estimated as follows: currently, 195 000
people work in oil and gas production alone across the U.S.48
Assuming 50% of these workers are in oil production, 97 500 jobs
exist in the U.S. oil production industry. Petroleum refineries
employ another 73 900 workers (Table 11). Nationally, the nonfuel output from oil refineries is B10% of refinery output.49 We
thus assume that only 10% (B17 000) of petroleum production
and refining jobs will remain upon conversion to WWS. We
assume another 33 000 jobs will remain for transporting this
petroleum for a total of 50 000 jobs remaining. These jobs are
assigned to states with current oil refining based on the current
capacity of refining. This study does not address the economics
of the remaining petroleum industry.
In sum, the shift to WWS may result in the displacement
of B3.86 million jobs in current fossil- and nuclear-related
industries in the U.S. At $69 930 per year per job – close to the
average for the WWS jobs – the corresponding loss in revenues
is B$270 billion.
9.C.
Jobs analysis summary
The JEDI models predict the creation of B3.9 million 40-year
construction jobs and B2.0 million 40-year operation and
maintenance jobs for the WWS generators proposed. The shift
to WWS will simultaneously result in the loss of B3.9 million in
the current fossil-based electricity generation, petroleum refining,
and uranium production industries in the U.S. Thus, a net of
B2.0 million 40-year jobs will be created in the U.S. The direct
and indirect earnings from WWS amount to $223 bil. per year
during the construction stage and $132 bil. per year for operation. The annual earnings lost from fossil-fuel industries total
B$270 bil. per year giving a net gain in annual earnings of
B$85 bil. per year.
10. Energy efficiency
The proposed state plans will continue and enhance existing
efforts to improve energy efficiency in residential, commercial,
institutional, and government buildings, thereby reducing energy
demand in each state. Current state energy policies promote
building efficiency through appliance standards, regulations, tax
incentives, education, and renewable energy portfolios. A number
2110 | Energy Environ. Sci., 2015, 8, 2093–2117
Fig. 5 shows a proposed timeline for the implementation of the
roadmaps presented here. The plans call for 80–85% conversion to WWS by 2030 and 100% by 2050. For such a transition
to occur, conversions need to occur rapidly for technologies as
follows:
Power plants: by 2020, no more construction of new coal,
nuclear, natural gas, or biomass fired power plants; all new
power plants built are WWS. This is feasible because few power
plants are built every year, and most relevant WWS electric
power generator technologies are already cost competitive. We
do not believe a technical or economic barrier exists to ramping
up production of WWS technologies, as history suggests that
rapid ramp-ups of production can occur given strong enough
political will. For example during World War II, aircraft production increased from nearly zero to 330 000 over five years.
Heating, drying, and cooking in the residential and commercial sectors: by 2020, all new devices and machines are powered
by electricity. This is feasible because the electric versions of all
of these products are already available, and all sectors can use
electricity without any adaptation (the devices can just be
plugged in).
Large-scale waterborne freight transport: by 2020–2025, all
new ships are electrified and/or use electrolytic hydrogen, all
new port operations are electrified, and port retro-electrification
is well underway. This should be feasible for relatively large
ships and ports because large ports are centralized and few ships
are built each year. Policies may be needed to incentivize the
early retirement of ships that do not naturally retire before 2050.
Rail and bus transport: by 2025, all new trains and buses are
electrified. This sector will take a bit longer to convert to WWS
because we also need to make changes to the supporting energydelivery infrastructure, and this is somewhat decentralized
across the U.S. However, relatively few producers of buses and
trains exist, and the supporting energy infrastructure is concentrated in major cities.
Off-road transport, small-scale marine: by 2025 to 2030, all
new production is electrified. If these vehicles can all be battery
powered, conversion will be simplified because electricity is
everywhere. The potential slowdown in converting these sectors
may be social.
Heavy-duty truck transport: by 2025 to 2030, all new vehicles
are electrified or use electrolytic hydrogen. It may take 10–15 years
for manufacturers to completely retool and for enough of the
supporting energy-delivery infrastructure to be in place.
Light-duty on-road transport: by 2025–2030, all new vehicles
are electrified. It takes time for manufacturers to retool, but more
importantly, it will take several years to get the energy-delivery
infrastructure in place, because it will need to be everywhere by
2030 when no more ICEV are made.
This journal is © The Royal Society of Chemistry 2015
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
New Mexico
New York
North Carolina
North Dakota
Ohio
Oklahoma
Oregon
Pennsylvania
Rhode Island
South Carolina
South Dakota
Tennessee
Texas
Utah
Vermont
Virginia
State
130 925
14 662
49 200
53 887
315 982
49 417
40 487
8286
222 082
146 597
8239
16 877
132 687
119 791
57 914
29 065
142 163
174 500
17 771
51 557
53 490
89 250
46 025
100 778
60 791
13 833
26 533
27 457
10 402
86 049
20 885
174 775
99 676
21 744
151 668
46 516
21 564
279 540
7473
58 473
10 244
148 143
312 979
29 857
2496
89 362
40-year construction
jobs
49 650
15 099
18 536
20 481
142 153
21 119
21 662
6458
90 727
73 419
4239
6707
59 709
47 951
25 106
13 346
47 719
143 400
13 381
35 893
37 950
58 810
29 767
40 659
23 469
5642
12 006
9140
5697
58 606
9663
94 644
63 199
8574
66 117
20 350
14 235
107 584
5775
40 345
4714
49 950
191 331
11 987
1005
57 779
40-year
operation
jobs
57 095
24 423
63 825
38 570
413 097
76 576
34 194
8922
173 635
95 086
13 599
14 746
138 722
71 464
29 899
42 836
62 687
134 860
12 446
54 286
64 380
99 191
56 345
39 126
59 914
16 202
23 343
27 589
13 662
90 836
41 674
187 203
94 223
26 690
123 109
95 445
36 020
158 788
9892
48 132
8028
63 345
571 429
37 942
6455
83 707
Job losses in
current
energy
industry
123 480
5339
3911
35 798
45 039
6040
27 955
5822
139 175
124 929
1120
8837
53 675
96 277
53 121
425
127 195
183 040
18 706
33 164
27 060
48 869
19 447
102 310
24 345
3273
15 196
9008
2437
53 819
11 126
82 216
68 652
3628
94 677
28 579
221
228 337
3356
50 687
6930
134 748
67 119
3902
2953
63 434
40-year net construction plus
operation jobs created minus jobs lost
7.28
0.87
2.92
3.04
18.12
2.89
2.25
0.48
12.41
8.24
0.47
0.97
7.46
6.64
3.25
1.70
7.78
10.18
1.02
2.94
3.05
5.12
2.67
5.54
3.41
0.79
1.54
1.56
0.58
4.88
1.23
9.75
5.70
1.21
8.47
2.69
1.26
15.24
0.43
3.37
0.60
8.14
18.73
1.72
0.14
5.14
Earnings from new
40-year construction
jobs ($bil 2013 per
year)
3.11
1.10
1.23
1.36
9.51
1.48
1.40
0.43
5.76
4.74
0.29
0.47
4.16
3.26
1.76
0.96
2.95
9.51
0.92
2.38
2.55
4.10
2.14
2.56
1.60
0.39
0.85
0.60
0.39
3.90
0.70
6.19
4.16
0.57
4.46
1.43
1.00
6.83
0.39
2.67
0.33
3.09
13.52
0.82
0.07
3.83
Earnings from new
40-year operation
jobs ($bil 2013 per
year)
6.40
0.26
0.31
1.70
1.26
0.98
1.27
0.28
6.03
6.33
0.19
0.40
1.93
4.90
2.92
0.34
6.35
10.26
1.07
1.52
1.10
2.28
0.87
5.37
0.82
0.05
0.75
0.24
0.02
2.43
0.98
2.85
3.28
0.08
4.32
2.55
0.26
10.97
0.12
2.68
0.37
6.80
7.71
0.11
0.24
3.11
Net earnings from
new construct-ion
plus operation jobs
minus jobs lost ($bil
2013 per year)
Table 9 Estimated 40-year construction jobs, 40-year operation jobs, construction plus operation jobs minus jobs lost, annual earnings corresponding to construction and operation jobs produced,
and net earnings from construction plus operation jobs produced minus jobs lost, by state, due to converting to WWS. Earnings are in 2013 dollars per year
Energy & Environmental Science
This journal is © The Royal Society of Chemistry 2015
Paper
Energy Environ. Sci., 2015, 8, 2093–2117 | 2111
24 927
20 295
33 200
7731
1 971 907
38 226
53 944
51 458
15 806
3 931 527
State
Washington
West Virginia
Wisconsin
Wyoming
United States
2112 | Energy Environ. Sci., 2015, 8, 2093–2117
40-year jobs are number of full-time equivalent (FTE) 1-year (2080 hours of work per year) jobs for 40 years.Earnings are in the form of wages, services, and supply-chain impacts. During the
construction period, they are the earnings during all construction. For the operation period, they are the annual earnings.
1.75
1.30
2.32
0.56
131.9
2.17
2.95
2.96
0.92
222.9
40-year
operation
jobs
40-year construction
jobs
67 603
53 862
54 168
40 009
3 859 275
4449
20 377
30 490
16 472
2 044 158
Earnings from new
40-year operation
jobs ($bil 2013 per
year)
Earnings from new
40-year construction
jobs ($bil 2013 per
year)
40-year net construction plus
operation jobs created minus jobs lost
Job losses in
current
energy
industry
(continued)
Table 9
0.81
0.49
1.50
1.32
85
Energy & Environmental Science
Net earnings from
new construct-ion
plus operation jobs
minus jobs lost ($bil
2013 per year)
Paper
Table 10 Estimated number of permanent operations, maintenance, and
fuel processing jobs per installed MW of proposed new energy technology
plants (Table 2)
Jobs per installed Number of
MW
permanent jobs
Energy technology Installed MW Low
High
Low
Onshore wind
1 639 819
Offshore wind
780 921
Wave device
27 036
Geothermal plant
20 845
Hydroelectric plant
3789
Tidal turbine
8823
Residential roof PV 375 963
Com/gov roof PV
274 733
Solar PV plant
2 323 800
CSP plant
363 640
Solar thermal
469 008
0.40
0.40
0.40
1.78
1.14
0.40
1.00
1.00
1.00
1.00
1.00
229 575 655 927
109 329 312 368
3785
10 814
34 811
37 103
4319
4319
1235
3529
45 116 375 963
32 968 274 733
278 856 2 323 800
80 001 363 640
56 281 469 008
Total
6 288 375
0.14
0.14
0.14
1.67
1.14
0.14
0.12
0.12
0.12
0.22
0.12
High
876 275 4 831 206
Table 11 U.S. job loss upon eliminating energy generation and use from
the fossil fuel and nuclear sectors
Energy sector
Number of jobs lost
Oil and gas extraction/production
Petroleum refining
Coal/gas power plant operation
Coal mining
Uranium extraction/production
Nuclear power plant operation
Coal and oil transportation
Other
Less petroleum jobs retained
806 300a
73 900b
259 400c
89 700d
1160e
58 870f
2 448 300g
171 500h
50 000i
Total
a
3 859 000
b
Ref. 36. Workers employed in U.S. refineries from ref. 37. State
values are estimated by multiplying the U.S. total by the fraction of U.S.
barrels of crude oil distilled in each state from ref. 38. c Includes coal
plant operators, gas plant operators, compressor and gas pumping
station operators, pump system operators, refinery operators, stationary
engineers and boiler operators, and service unit operators for oil, gas,
and mining. Coal data from ref. 39. All other data from ref. 40. d Ref. 41.
e
Sum U.S. uranium mining employment across 12 U.S. states that mine
uranium from ref. 42. State values are estimated by multiplying the total
by the state population divided by the total population of the 12 states.
f
Ref. 43. g Multiply the total number of direct U.S. jobs in transportation (11 000 000) from ref. 44 by the ratio (0.287 in 2007) of weight of oil
and coal shipped in the U.S. relative to the total weight of commodities
shipped from ref. 45 and by the fraction of transportation jobs that are
relevant to oil and coal transportation (0.78) from ref. 46 and by the
fraction of the U.S. population in each state. h Other includes accountants, auditors, administrative assistants, chemical engineers, geoscientists, industrial engineers, mechanical engineers, petroleum attorneys,
petroleum engineers, and service station attendants associated with oil
and gas.47 i See text for discussion of jobs retained.
Short-haul aircraft: by 2035, all new small, short-range planes
are battery- or electrolytic-hydrogen powered. Changing the design
and manufacture of airplanes and the design and operation of
airports are the main limiting factors to a more rapid transition.
Long-haul aircraft: by 2040, all remaining new aircraft are
electrolytic cryogenic hydrogen (ref. 6, Section A.2.7) with electric
power for idling, taxiing, and internal power. The limiting factors
to a faster transition are the time and social changes required for
the redesign of aircraft and the design and operation of airports.
This journal is © The Royal Society of Chemistry 2015
Energy & Environmental Science
Paper
Fig. 5 Time-dependent change in U.S. end-use power demand for all purposes (electricity, transportation, heating/cooling, and industry) and its supply
by conventional fuels and WWS generators based on the state roadmaps proposed here. Total power demand decreases upon conversion to WWS due to
the efficiency of electricity over combustion and end-use energy efficiency measures. The percentages on the horizontal date axis are the percent
conversion to WWS that has occurred by that year. The percentages next to each WWS source are the final estimated penetration of the source. The
100% demarcation in 2050 indicates that 100% of all-purpose power is provided by WWS technologies by 2050, and the power demand by that time has
decreased. Karl Burkart, personal communication.
This section discusses short-term policy options to aid conversion to WWS at the state level. Within each section, the policy
options listed are listed roughly in order of proposed priority.
Incentivize conversion from natural gas water and air heaters
to heat pumps (air and ground-source) and rooftop solar thermal
hot water pre-heaters. Incentivize more use of efficient lighting in
buildings and on city streets.
Promote, though municipal financing, incentives, and rebates,
energy efficiency measures in buildings. Efficiency measures
include, but are not limited to, using LED lighting; optimized
air conditioning systems; evaporative cooling; ductless air conditioning; water-cooled heat exchangers; night ventilation cooling;
heat-pump water heaters; improved data center design; improved
air flow management; advanced lighting controls; combined
space and water heaters; variable refrigerant flow; improved wall,
floor, ceiling, and pipe insulation; sealing leaks in windows,
doors, and fireplaces; converting to double-paned windows;
using more passive solar heating; monitoring building energy
use to determine wasteful processes; and performing an energy
audit to discover energy waste.
Revise building codes as new technologies become available.
Incentivize landlords’ investment in efficiency. Allow owners
of multi-family buildings to take a property tax exemption for
energy efficiency improvements made in their buildings that
provide benefits to their tenants.
Introduce a Public Benefit Funds (PBF) program for energy
efficiency. Fund the program with a non-bypassable charge
on consumers’ electricity bills for distribution services. These
funds generate capital that sponsor energy efficiency programs,
and research and development related to clean energy technologies and training.
12.1.
12.2.
During the transition, conventional fuels will be needed along
with existing WWS technologies to produce the remaining WWS
infrastructure. The use of such fuels …
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