Question:
You are given the full text of a scientific research paper.

    Summarize the paper's key **research findings** in the style of a policy brief. Your response should:
    - Focus on the major empirical or model-based results
    - Present findings that are policy-relevant and supported by the study
    - Use concise, non-technical language with essential technical terms as needed
    - Avoid quoting directly or summarizing minor details

    Write a short, clear paragraph appropriate for the “Scientific Research Findings” section of a policy brief.

    Scientific Research Paper:
    Articles
https://doi.org/10.1038/s41558-021-01128-0
1School of International Affairs and Department of Civil and Environmental Engineering, Pennsylvania State University, University Park, PA, USA. 2Joint
Global Change Research Institute, Pacific Northwest National Laboratory, College Park, MD, USA. 3School of the Environment, Yale Program on Climate
Change Communication, Yale University, New Haven, CT, USA. 4Center for Global Sustainability, School of Public Policy, University of Maryland, College
Park, MD, USA. 5School of Global Policy and Strategy, University of California San Diego, La Jolla, CA, USA. 6Scripps Institution of Oceanography,
University of California San Diego, La Jolla, CA, USA. 7Mechanical and Aerospace Engineering, Jacobs School of Engineering, University of California San
Diego, La Jolla, CA, USA. 8The Brookings Institution, Washington, DC, USA. ✉e-mail: weipeng@psu.edu
A
s governments get serious about decarbonization, politi-
cal leaders in large and politically diverse countries need to
grapple with huge variations in political and administrative
feasibility within their countries. That heterogeneity in interests and
capabilities has led many federal governments to encourage or tol-
erate large internal variations in policy effort. Diverse studies have
pointed to the benefits of heterogeneous approaches for experimen-
tation and learning1–4. Yet these realities in climate politics have
not been well represented in leading modelling frameworks, which
typically assume nationally uniform policy efforts5–8. This gap in
modelling work also reflects the widely held assumption by poli-
cymakers that heterogeneous subnational policy efforts will be a lot
more costly than nationally uniform efforts9.
To assess the potential increase in cost from heterogeneous
subnational policy formation compared with theorized opti-
mal uniform nationwide policy, we study the case of the United
States. The United States is the world’s second largest emitter and
already displays one of the world’s largest variations in subna-
tional action. Bottom-up coalitions, such as the ‘America is All In’
initiative, have gathered thousands of signatories from political
leaders in cities, states, companies and universities that represent
a constituency of more than half the U.S. population10. More than
30 states have completed state-level climate action plans, or are
in the process of developing one11. Nearly 40 states have created
renewable portfolio standards or voluntary renewable energy
goals to facilitate low-carbon transition12. Meanwhile, some states
are making limited effort and are under no sustained public pres-
sure to strengthen it.
Here we focus on heterogeneity in the stringency of policy efforts
made by each state. For ease, we will represent those policy efforts
as state-varying prices on carbon, although in practice no enterprise
uses only simple price instruments—a variety of other mechanisms,
such as renewable portfolio standards, low-carbon fuel standards
and industrial policies are the norm13,14. Our approach, by design,
allows us to assess the long-term dynamics that arise when states
vary in their willingness to act and when the country, as a whole,
varies the national decarbonization targets it might pursue. We see
this long-term view of heterogeneity in action as a complement to
studies that have focused on much nearer-term policy heterogene-
ity and thus been able to look more granularly at specific policy
instruments15. (See Supplementary Note 2 for a comparison with
America’s Pledge study that examines nearer-term policies13.)
Methodologically, we employ a process-based integrated assess-
ment model (IAM): the Global Change Assessment Model with
state-level detail in the United States (GCAM-USA; Methods)16.
It includes detailed representation of sectoral and technology
options, as well as the interactions between the economic, energy
and land-use systems. These representations allow us to assess the
deployment trajectories of critical technologies in each state, the
competition between different technologies in various sectors and
the impacts of varying cost and policy assumptions on infrastruc-
ture investments across space and time. Our analysis hence goes
beyond prior studies based on simpler economic models17–19 by
identifying critical sectors, technologies and processes that deter-
mine the cost of heterogeneous policy efforts.
Scenario design
We examine 12 mitigation scenarios that vary across two dimensions:
	i.
National mitigation effort, measured by four targets of nation-
al total greenhouse gas (GHG) emissions for 2050 (for exam-
ple, 20%, 40%, 60% and 80% below 2005 levels; Supplementary
Fig. 1). We also include a 95% decarbonization target as a sen-
sitivity analysis, which is close to the net-zero emissions target
set by the Biden Administration (Supplementary Fig. 7).
The surprisingly inexpensive cost of state-driven
emission control strategies
Wei Peng   1 ✉, Gokul Iyer   2, Matthew Binsted   2, Jennifer Marlon   3, Leon Clarke4,
James A. Edmonds   2 and David G. Victor   5,6,7,8
Traditionally, analysis of the costs of cutting greenhouse gas emissions has assumed that governments would implement ideal-
ized, optimal policies such as uniform economy-wide carbon taxes. Yet actual policies in the real world, especially in large fed-
eral governments, are often highly heterogeneous and vary in political support and administrative capabilities within a country.
While the benefits of heterogeneous action have been discussed widely for experimentation and leadership, little is known
about its costs. Focusing on the United States, we represent plausible variation (by more than a factor of 3) in the stringency of
state-led climate policy in a process-based integrated assessment model (GCAM-USA). For a wide array of national decarbon-
ization targets, we find that the nationwide cost from heterogeneous subnational policies is only one-tenth higher than nation-
ally uniform policies. Such results hinge on two critical technologies (advanced biofuels and electricity) for which inter-state
trade ameliorates the economic efficiencies that might arise with heterogeneous action.
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	ii.	 Subnational policy approach, modelled as three degrees of
heterogeneity in the stringency of state-level climate policy. The
Uniform approach assumes a nationally uniform policy imple-
mentation. It is represented as a uniform price on carbon, mod-
elled by equalizing the marginal abatement cost (MAC) across
states in GCAM-USA. By contrast, the Hybrid and Heterogene-
ous approaches assume state heterogeneity in policy stringency,
which is represented as state-varying carbon prices and MACs.
The MAC implicitly measures the highest willingness to pay
by industries and households in each state to mitigate carbon
emissions. A higher MAC implies a higher price on carbon and
thus more stringent climate policy efforts.
We incorporate key political factors and processes in our sce-
nario design to bring it closer to the realities. Because the United
States is a democracy, we use public opinions to proxy for the het-
erogeneity in stringency of state policies. Indeed, there is a vast lit-
erature on the important role for public attitudes in shaping climate
policy (see Supplementary Note 1 as well as refs. 20–22). Under the
Heterogeneous approach, we model the widest heterogeneity in
policy stringency (by more than a factor of 3) across all the states.
Under the Hybrid approach, we temper that heterogeneity by first
overlaying a modest level of nationwide carbon policy that all states,
at minimum, must adopt. When looking at state-level policies,
a majoritarian 50% define who gets elected, and thus the median
voter matters; we hence allow a non-linear, steep rise in policy strin-
gency when support exceeds 50% (Figs. 1 and 2 and Methods). At
the federal level, the rules for adoption are stricter and, since 1975,
have required a 60% cloture threshold before the body can pass leg-
islation (rule 22 in ref. 23); we hence set the nationwide carbon policy
to be the 40th percentile of the stringency levels across all the states.
We are mindful that state and federal policies arise through much
more complex and nuanced processes; our purpose here is simply
to show a plausible method for quantifying degrees of heterogeneity
and their implications for mitigation cost (see Sensitivity analysis
section for alternative formulations for policy heterogeneity).
To make computation easier, we set the relative ratios of state-level
carbon prices based on public opinions, then let the model compute
the whole set of carbon price values to achieve the national mitiga-
tion targets (see Fig. 2 for more details).
Heterogeneity at state level
We categorize states into three groups, namely low-, medium-, and
high-supporting states, depending on the level of current public
support for climate policy (Fig. 1). With the Uniform approach,
the carbon price is uniform across the three groups of states, but
increases dramatically as the national mitigation efforts become
more stringent (solid lines in Fig.  3: US$74, US$210, US$670
and US$1,557 per ton CO2 for national targets of 20%, 40%, 60%
and 80% decarbonization, respectively). The substantial increase
in carbon price is a direct result of an increasing MAC, which
suggests that availability of low-cost mitigation options becomes
increasingly constrained to achieve more ambitious decarboniza-
tion goals.
Compared with the Uniform approach, the main effect of intro-
ducing heterogeneous subnational policies is to shift the burden of
emissions reductions from low- to medium- and high-supporting
states, while the country overall still achieves the same national
mitigation target. The effect of such a shift is driven by much lower
carbon prices in the low-supporting states and is greatest under the
Heterogeneous approach, since it displays the widest heterogeneity
in state-level effort.
Mitigation efforts by sector
By comparing scenarios having ambitious versus less ambitious
national mitigation effort (for example, the 80% and 40% decar-
bonization scenarios with the Uniform policy approach in Fig. 4),
we confirm the common finding in the literature that deep decar-
bonization generally requires decarbonizing the electricity sector
first (the sector with the lowest mitigation cost) then moves onto
‘harder-to-abate’ sectors such as industry, residential and transport
sectors24–26. This sectoral pattern remains robust under substantial
state heterogeneity in policy stringency, indicating that mitiga-
tion far beyond the electricity sector is necessary to achieve deep
decarbonization goals, irrespective of uniform or heterogeneous
approaches.
Introducing state heterogeneity affects the sectoral alloca-
tion of CO2 mitigation. At the national level, all three subnational
policy approaches achieve CO2 mitigation with similar sectoral
Ratio of the carbon price in each state to the carbon price in District of Columbia
0.3
0.4
0.5
0.6
0.7
0.8
0.85
0.9
1
Low support
Medium support High support
Percentage of adults who think their local officials should do more to address
global warming (2018)
45%
50%
55%
60%
65%
a
b
Fig. 1 | State-level variations in public support for climate policy and its
impact on carbon pricing under the Heterogeneous approach. a, State
heterogeneity in public support level for climate policy in 2018. We show the
percent adult population in each state who think their local officials should
do more to address global warming (data from ref. 49). b, State heterogeneity
in carbon prices under the Heterogeneous approach. Here we present the
ratio of the carbon price in each state (modelled as the marginal abatement
cost of carbon policies) to the carbon price in the District of Columbia, where
the support rate is the highest. We group the 50 states and the District of
Columbia into low-, medium- and high-supporting groups (indicated by red,
yellow and blue, respectively; each group includes 17 states), based on their
current climate policy support levels as shown in a. We assume the state-level
carbon price varies non-linearly with public support level and decreases
dramatically when the support level drops to below 50% according to the
medium voter theorem. This assumption leads to much lower carbon prices in
states with low support rate. More details are included in Fig. 2, Methods and
Supplementary Methods.
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contributions. At the subnational level, moving from the Uniform to
the Hybrid and Heterogeneous approach, the low-supporting states
reduce less CO2 from the electricity and refinery sectors, while
the medium- and high-supporting states reduce more from these
two sectors.
With a heterogeneous approach, mitigation in harder-to-abate
sectors is especially important in states with higher support rate.
For instance, to achieve a national mitigation effort of 80% decar-
bonization with a heterogeneous policy approach, the contribu-
tion of non-electricity sectors to total CO2 mitigation from 2015 to
2050 is only 48% in the low-supporting states, while it is 60% in
the medium- and high-supporting states (Fig. 4). This suggests that
decarbonizing the electricity sector is a key strategy for all the states,
and the major differences between states with low and high sup-
port levels occur outside the electricity sector, where mitigation is
more costly.
Implications for nationwide cost
The nationwide mitigation cost increases dramatically from mod-
erate to ambitious national mitigation efforts (Fig.  5). However,
more surprising is that the difference in total cost does not vary
much when the subnational policy approach is heterogeneous
as compared with uniformity across the states. Under the Hybrid
and Heterogeneous approaches, the economic cost of mitigation
drops in the low-supporting states by up to half; the medium- and
high-supporting states take up most of that slack. And despite
the factor of 3 variation in carbon prices across states under the
Heterogeneous approach, the national mitigation cost is only slightly
higher than with the Uniform approach. For a national mitigation
effort of 20%, 40%, 60% and 80% decarbonization, the nationwide
cost under the heterogeneous approach is only 14%, 9%, 4% and 5%
higher than the uniform approach, respectively.
This surprising result (that the overall costs do not rise much in spite
of huge heterogeneity across states) is largely driven by the flexibility
across states in terms of electricity trade and the location of
energy-intensive industries (for example, bio-refineries; see the
electricity and bioliquids production patterns in Supplementary
Fig.  3). In other words, despite the subnational heterogeneity in
policy stringency, energy markets are tightly coupled across states,
allowing much of the heterogeneity in policy to be arbitraged
through trade activities in the energy markets. Comparing the
Heterogeneous and Hybrid approach with the Uniform approach,
many states adjust the amount of electricity production, technology
choices and trading volume with neighbouring states. Nationally,
to achieve an 80% cut in GHG emissions, we find ~10% more
inter-grid electricity trade under the heterogeneous policy approach
than the uniform approach (see Extended Data Fig. 2 for net elec-
tricity trade across 15 grid regions; Supplementary Fig.  5 shows
a map of the grid regions). There is also a shift in the geographic
pattern of where critical mitigation technologies, such as bioen-
ergy with carbon capture and storage (BECCS), are being deployed
(Extended Data Fig. 3 and Supplementary Fig. 6). This is because,
with a heterogeneous approach, the mitigation efforts are shifted
from low- to high-supporting states, pushing the green states to
achieve deep cuts in their emissions by turning to negative emis-
sions technologies such as BECCS.
Our finding indicates that deep decarbonization is nonetheless
costly. The socioeconomic implications can be large and will vary
across states that have different levels of wealth, economic struc-
ture and carbon intensity (Extended Data Fig. 4). There is growing
attention on how various forms of justice and equity considerations
intersect with deep decarbonization, which is revealed not least
in current plans in the United States and Europe that frame deep
decarbonization as broad social changes.
260
Heterogeneous
Hybrid
Hybrid
Heterogeneous
Uniform
240
220
200
180
Ratio relative to
the highest carbon price
State-level carbon prices in 2050 (2015 US$ per ton CO2)
Public support level for climate policy
(Percentage of adults who think their local offcials should do
more to address global warming)
1.00
0.75
0.50
0.25
45%
50%
55%
60%
65%
160
140
120
100
80
60
WY
ND
MT
WV
IA
SD
VA
KY
NE
OK
AK
IN
KS
TN
AL
MN
AR
ID
NH
MO
LA
MS
TX
OH
MI
WA
SC
PA
CO
IL
NM
CT
ME
AZ
WI
NV
NC
UT
OR
GA
VT
MA
DE
RI
HI
NJ
MD
CA
FL
NY
DC
Fig. 2 | Model-computed state-level carbon prices in 2050 to achieve a national target of 40% decarbonization by 2050 relative to 2005 under three
subnational policy approaches. The carbon prices are modelled as the marginal abatement cost of carbon policies in GCAM-USA. The inset shows
different assumptions for how carbon price varies as a function of public support under the Hybrid and Heterogeneous approaches, respectively (more in
Methods and Supplementary Methods). Based on these assumptions, the GCAM-USA model then computes the whole set of state-level carbon prices to
achieve the national decarbonization target, as presented in the main figure.
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Sensitivity analyses
We test the sensitivity of the results to six alternative formulations for
policy heterogeneity (Fig. 6, Extended Data Fig. 5 and Supplementary
Methods), including: (1) assuming a linear relationship between pub-
lic support and policy stringency (‘Linear’), (2) increasing the state
heterogeneity in policy stringency by varying the state-level carbon
prices by a factor of 10 (‘+ range’), (3) and (4) assuming no effort and
hence zero carbon price in three or five lowest-supporting states (‘3
zero’ and ‘5 zero’), (5) using the public opinion results from a different
survey question on ‘Do you think your Governor should do more to
address global warming?’ (‘Gov’) and (6) using existing commitments
to climate action (instead of public opinion) to proxy for policy strin-
gency (‘AP’: America’s Pledge). Most of these alternative formulations
do not alter the core result that the heterogeneous policy approach is
only marginally more expensive. However, the cost of deep decarbon-
ization can increase significantly if a few states with the lowest sup-
port levels are not engaged in climate action at all (‘3 zero’ and ‘5 zero’
scenarios). For instance, to achieve 80% decarbonization nationally,
a zero effort in those locales drives costs for the rest of the country
up by 25–70%. At least some modest floor level of effort by all the
states is critical to avoid inter-state carbon leakage and a significant
cost escalation.
We also consider three technology constraints based on what prior
research has shown to be most pivotal in determining future mitiga-
tion costs (Fig. 6)27,28. For all three policy approaches, we find much
higher mitigation costs under: (a) limited electricity infrastructure
investment and production, (b) no investment in carbon capture
and storage (CCS) and (c) limited availability of biomass. The great-
est impacts on mitigation costs come from constraining CCS and
biomass because this restricts the role of BECCS and forces greater
reliance upon extremely expensive technologies outside the electric-
ity and refinery sectors (cf. Extended Data Fig. 6 with Fig. 4), such
as hydrogen use in transport and industrial sectors. Relaxing the bio-
mass constraint, by contrast, significantly lowers the mitigation costs
(Supplementary Figs.  11 and 12). Limiting electricity production
has a lesser impact on overall costs because, in the face of such con-
straints, reductions in energy demand through efficiency measures,
increases in natural gas use coupled with CCS, as well as more miti-
gation in the refinery sector through BECCS, can provide additional
decarbonization. Detailed discussions are included in Supplementary
Note 3. Although these technology constraints raise the total national
cost of mitigation, our main finding remains robust: a heteroge-
neous policy approach, relative to a uniform approach, is only slightly
more expensive.
1,500
National mitigation efforts
Subnational policy approaches
20% decarbonization
Uniform
Hybrid
Heterogeneous
High-supporting states
Low-supporting states
40% decarbonization
60% decarbonization
80% decarbonization
1,000
500
Average carbon price in 2050 (2015 US$ per ton CO2)
0
500
1,000
Reduction in energy-related CO2 emissions in 2050 relative to 2015
(million ton CO2)
1,500
Fig. 3 | Reduction in energy-related CO2 emissions and carbon prices in 2050 in low- and high-supporting states. The size of the dots represents four
levels of national mitigation effort: 20%, 40%, 60% and 80% decarbonization by 2050 relative to 2005. The solid, dotted and dashed lines represent
three subnational policy approaches: Uniform, Hybrid and Heterogeneous, respectively. Comparing the Hybrid and Heterogeneous approaches with the
Uniform approach, the lower carbon prices in the low-supporting states (modelled as lower marginal abatement cost) yield lesser CO2 reductions within
that category of states (that is, comparing dashed/dotted red lines with solid red lines), thus shifting more emissions reductions to the high-supporting
states (that is, comparing dashed/dotted blue lines with solid blue lines). The national average carbon price and national total CO2 emissions reduction are
presented in Supplementary Fig. 2.
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Discussion
U.S. policy analysts have famously celebrated subnational action
by states as federalist laboratories of democracy29. Unshackled
from central mandates, or where central governments are mired in
political gridlock, the logic of federalism globally emphasizes the
utility of local experiments and the practical reality that not every
40% D
Uni
64%
61%
60%
60%
44%
45%
52%
68%
67%
65%
43%
43%
40%
61%
60%
59%
39%
40%
40%
63%
62%
42%
43%
43%
0
a
b
c
d
–2,000
–4,000
Million ton CO2
0
0
0
–500
–1,000
–1,500
–500
–1,000
–1,000
–2,000
–1,500
Million ton CO2
Million ton CO2
Million ton CO2
Hyb
Het
Uni
Hyb
Het
Electricity
Transportation
Residential/commercial
Industry
Refinery
80% D
40% D
Uni Hyb
Het
Uni
Hyb
Het
80% D
40% D
Uni Hyb
Het
Uni
Hyb
Het
80% D
40% D
Uni Hyb
Het
Uni
Hyb
Het
80% D
Fig. 4 | Reduction in energy-related CO2 emissions. a–d, Reduction in energy-related CO2 emissions in 2050 relative to 2015 by sector at the national level
(a) and for low- (b), medium- (c) and high-supporting (d) states. The labels ‘40% D’ and ‘80% D’ represent two levels of national mitigation efforts, that
is, 40% and 80% decarbonization by 2050 relative to 2005. ‘Uni’, ‘Hyb’ and ‘Het’ represent three subnational policy approaches, that is, Uniform, Hybrid
and Heterogeneous. The white percentages represent the share of the electricity sector in all-sector CO2 reduction. Results for other levels of national
mitigation efforts are presented in Extended Data Fig. 1. Detailed energy technology choices for electricity generation, liquids production and end-use
sectors are reported in Supplementary Fig. 4.
Uniform
20% D
20%
Low
High
Medium
Low
Low
Low
High
High
High
Medium
Medium
Medium
40%
60%
80%
100%
0
40% D
60% D
National mitigation effort
80% D
0
1%
2%
3%
Mitigation cost in 2050 as a fraction of projected GDP
4%
5%
6%
Hybrid
Heterogeneous
Contribution of three groups of states
to national CO2 emissions in 2016
Uniform
Hybrid
Heterogeneous
Uniform
Hybrid
Heterogeneous
Uniform
Hybrid
Heterogeneous
Fig. 5 | Carbon mitigation cost in 2050 as a fraction of projected 2050 gross domestic product (GDP), by national mitigation effort (20–80%
decarbonization, indicated as 20–80% D) and by subnational policy approach (Uniform, Hybrid and Heterogeneous). Colours reflect the state
groupings (Fig. 1b), and the inset shows the contribution by low- (red), medium- (yellow) and high-supporting (blue) states to national total CO2
emissions in 2016 (ref. 50). See Extended Data Fig. 4 for state-by-state results.
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national subunit will have the same political preferences or admin-
istrative capabilities.
The question of heterogeneity is hardly new to climate policy
analysis, although over history most of this debate has played out
with regard to global politics, where it has been taken as axiom-
atic that jurisdiction-wide policies would achieve the greatest lever-
age on emissions and the lowest cost30,31. That assumption persists,
even as the Paris Agreement and other policy frameworks have
evolved to encourage high degrees of heterogeneity32–37. Where
these issues have been analysed closely, they appear to confirm the
costs of heterogeneity. Studies have found that heterogeneous action
across countries, driven by equity concerns38, delays in action39–41 or
variations in investment risks42, could increase the global mitigation
cost by as much as 40%28. (See Supplementary Note 4 for a fuller
literature review in the global context.)
Controlling pollution of warming gases may prove to be the most
elaborate and costly environmental policy undertaking yet, and the
analysis we present here suggests that the extra nationwide economic
cost of federalist variation in state-level policy can be very mod-
est—much smaller by an order of magnitude than variations in the
overall level of nationwide effort. For policymakers, this insight sug-
gests that federalist approaches could be more sustainable, because
higher costs are aligned with the states that are politically more will-
ing to bear them. Future research should aim to simulate or measure
1.0%
a
b
0.8%
10%
8%
6%
4%
2%
0
0.6%
0.4%
High
Med
Low
High
Med
Low
Mitigation cost as percentage of GDP
Mitigation cost as percentage of GDP
0.2%
0
Uni
Hyb
Het
Alternative formulations
for polilcy heterogeneity
Low electricity
infrastructure
40% decarbonization
80% decarbonization
No CCS
Low biomass
Uni
Hyb
Het
Uni
Hyb
Het
Uni
Hyb
Het
Het
(linear)
Het
(+range)
Het
(3 zero)
Het
(5 zero)
Het
(Gov)
Het
(AP)
Uni
Hyb
Het
Alternative formulations
for polilcy heterogeneity
Low electricity
infrastructure
No CCS
Low biomass
Uni
Hyb
Het
Uni
Hyb
Het
Uni
Hyb
Het
Het
(linear)
Het
(+range)
Het
(3 zero)
Het
(5 zero)
Het
(Gov)
Het
(AP)
Fig. 6 | Sensitivity analysis of carbon mitigation cost for two levels of national mitigation effort. a,b, Carbon mitigation cost in 2050 as a fraction of
projected 2050 GDP for 40% (a) and 80% (b) decarbonization, with state groups coloured as in Fig. 1. See Extended Data Fig. 5 and Supplementary
Figs. 8–10 for other national decarbonization levels. The first three bars on the left represent our main scenarios shown in Fig. 5. Alternative formulations of
policy heterogeneity include: ‘Linear’, assuming a linear relationship between public support and policy stringency; ‘+ range’, increasing state heterogeneity
by varying the state-level carbon prices by a factor of 10; ‘3 zero’ and ‘5 zero’, assuming no effort in three or five lowest-supporting states (that is, zero
carbon price); ‘Gov’, using the public opinion results from a different survey question on ‘Do you think your Governor should do more to address global
warming?’; and ‘AP’ (America’s Pledge), using existing commitments to climate action (instead of public opinion) to proxy for policy stringency. Technology
constraints include: ‘Low Electricity Infrastructure’, assuming reduced electricity infrastructure investment by constraining the national total electricity
production to be 60% of the level in the main scenario that uses a uniform approach to achieve 80% decarbonization nationally; ‘No CCS’, assuming no
investment in carbon capture and storage; and ‘Low Biomass’, assuming the national total biomass availability is half of the level in the main scenarios.
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the benefits of heterogeneous action—some agent-based modelling
has done this in other settings37—and compare them with the costs
of non-uniform action, such as using IAM-based cost assessments
that we demonstrate here.
Our study shows that the magnitude of mitigation costs is
affected by the availability of critical technologies (which in our case
include low-carbon electricity and BECCS) and the ability to trade
relevant energy products across state borders. Whether these tech-
nologies, especially untested ones such as BECCS, can be deployed
at the speed and scale needed for deep decarbonization depends
on a variety of factors, such as economic cost, land use constraints
and other sustainability considerations43,44. In addition, while our
model allows for a certain degree of flexibility for inter-state trade
of electricity and bioliquids, we often observe inflexibility of energy
investments and trade in the real world, due to physical and regu-
latory constraints on electricity transmission, biomass resources,
opposition to pipelines, etc.43–46. Future work should consider these
real-world constraints in modelling critical technologies at fine spa-
tial scale and should disentangle more precisely whether it is the
technology frontiers or the ability to trade across state borders that
drives the low cost of policy heterogeneity found in this study.
A central policy puzzle in heterogeneous systems is how policy
leaders—who are willing to bear higher costs for policy action—
can demonstrate effective mitigation strategies that make it easier
for other units to follow. For climate change, followership is par-
ticularly critical to effective policy, because the jurisdictions that are
willing to lead on climate policy account for just a tiny fraction of
global emissions47. In our analysis, followership is especially needed
in the medium-supporting states, given their large contribution to
national total emissions. The largest differences between leader and
follower units arise with so-called harder-to-abate sectors such as
industrial heating, buildings and transportation48. For policymak-
ers, this suggests that there is a very high premium on advances in
decarbonization of these sectors, because followership will be hard-
est in these domains. If leaders can, through testing and deployment
in their local markets, reduce abatement costs in these other sectors,
they could make followership much easier and increase total lever-
age on emissions. For analysts, the role of these sectors in follower
jurisdictions suggests that we need to analyse the real potential for
improved decarbonization performance in these sectors in greater
depth. Where leadership can plausibly reduce costs, the model of
heterogeneous policymaking can be particularly advantageous;
where not, it could lead to policy cul-de-sacs, where followers never
follow and world emissions remain stuck at high levels.
Online content
Any methods, additional references, Nature Research report-
ing summaries, source data, extended data, supplementary infor-
mation, acknowledgements, peer review information; details of
author contributions and competing interests; and statements of
data and code availability are available at https://doi.org/10.1038/
s41558-021-01128-0.
Received: 9 December 2020; Accepted: 23 July 2021;
Published online: 23 August 2021
References
	1.	 Ostrom, E. Beyond markets and states: polycentric governance of complex
economic systems. Am. Econ. Rev. 100, 641–672 (2010).
	2.	 De Búrca, G., Keohane, R. O. & Sabel, C. Global experimentalist governance.
Br. J. Political Sci. 44, 477–486 (2014).
	3.	 Rabe, B. G. Statehouse and Greenhouse (Brookings Institution Press, 2004).
	4.	 Sabel, C. & Victor, D. G. Governing global problems under uncertainty:
making bottom-up climate policy work. Clim. Change 144, 15–27 (2017).
	5.	 McCollum, D. L. et al. Energy investment needs for fulfilling the Paris
Agreement and achieving the Sustainable Development Goals. Nat. Energy 3,
589–599 (2018).
	6.	 Rogelj, J. et al. Paris Agreement climate proposals need a boost to keep
warming well below 2 °C. Nature 534, 631 (2016).
	7.	 Rogelj, J. et al. Scenarios towards limiting global mean temperature increase
below 1.5 °C. Nat. Clim. Change 8, 325–332 (2018).
	8.	 Fragkos, P. et al. Coupling national and global models to explore policy
impacts of NDCs. Energy Policy 118, 462–473 (2018).
	9.	 Lowrey, A. Are states really more efficient than the federal government?
The Atlantic (2 October 2017).
	10.	America is All In. https://www.americaisallin.com/
	11.	U.S. State Climate Action Plans. Center for Climate and Energy Solutions
https://www.c2es.org/document/climate-actionplans/ (2020).
	12.	State Renewable Portfolio Standards and Goals. National Conference of State
Legislatures https://www.ncsl.org/research/energy/
renewable-portfolio-standards.aspx (2020).
	13.	Fulfilling America’s Pledge: How States, Cities, and Businesses are Leading the
United States to a Low-Carbon Future (Bloomberg Philanthropies, Rocky
Mountain Institute and Center for Global Sustainability at the University of
Maryland, 2018).
	14.	Lempert, R. et al. Pathways to 2050: Alternative Pathways for Decarbonizing
the U.S. Economy. C2ES Climate Innovation 2050 https://www.c2es.org/
document/pathways-to-2050-scenarios-for-decarbonizing-the-u-s-economy
(2019).
	15.	Hultman, N. E. et al. Fusing subnational with national climate action is
central to decarbonization: the case of the United States. Nat. Commun. 11,
5255 (2020).
	16.	Calvin, K. et al. GCAM v5.1: representing the linkages between energy,
water, land, climate, and economic systems. Geosci. Model Dev. 12,
677–698 (2019).
	17.	D’Autume, A., Schubert, K. & Withagen, C. Should the carbon price be the
same in all countries? J. Public Econ. Theory 18, 709–725 (2016).
	18.	Böhringer, C. & Rutherford, T. F. Carbon taxes with exemptions in an open
economy: a general equilibrium analysis of the German tax initiative. J.
Environ. Econ. Manag. 32, 189–203 (1997).
	19.	Boeters, S. Optimally differentiated carbon prices for unilateral climate policy.
Energy Econ. 45, 304–312 (2014).
	20.	Page, B. I. & Shapiro, R. Y. Effects of public opinion on policy. Am. Political
Sci. Rev. 77, 175–190 (1983).
	21.	Burstein, P. The impact of public opinion on public policy: a review and an
agenda. Political Res. Q. 56, 29–40 (2003).
	22.	Bromley-Trujillo, R. & Poe, J. The importance of salience: public opinion and
state policy action on climate change. J. Public Policy https://doi.org/10.1017/
S0143814X18000375 (2018).
	23.	Rules of the Senate. U.S. Senate https://www.rules.senate.gov/
rules-of-the-senate
	24.	Fawcett, A. A., Clarke, L. E. & Weyant, J. P. Introduction to EMF 24. Energy
J. 35, https://doi.org/10.5547/01956574.35.SI1.1 (2014).
	25.	Williams, J. H. et al. Pathways to deep decarbonization in the United States.
The U.S. Report of the Deep Decarbonization Pathways project of the
Sustainable Development Solutions Network and the Institute for Sustainable
Development and International Relations (2014).
	26.	Iyer, G. et al. Measuring progress from nationally determined contributions
to mid-century strategies. Nat. Clim. Change 7, 871–874 (2017).
	27.	Clarke, L. et al. International climate policy architectures: overview of the
EMF 22 International Scenarios. Energy Econ. 31, S64–S81 (2009).
	28.	Clarke, L. et al. in Climate Change 2014: Mitigation of Climate Change. IPCC
Working Group III Contribution to AR5 (Cambridge Univ. Press, 2014).
	29.	Brandeis. New State Ice Co. v. Liebmann (1932).
	30.	United Nations Convention on Climate Change. FCCC/INFORMAL/84
GE.05-62220 (E) 200705 (United Nations, 1992).
	31.	Wigley, T. M. L., Richels, R. & Edmonds, J. A. Economic and environmental
choices in the stabilization of atmospheric CO2 concentrations. Nature 379,
240–243 (1996).
	32.	Keohane, R. O. & Victor, D. G. The regime complex for climate change.
Perspect. Politics 9, 7–23 (2011).
	33.	Keohane, R. O. & Victor, D. G. Cooperation and discord in global climate
policy. Nat. Clim. Change 6, 570 (2016).
	34.	Biermann, F., Pattberg, P., van Asselt, H. & Zelli, F. The fragmentation of
global governance architectures: a framework for analysis. Glob. Environ.
Politics 9, 14–40 (2009).
	35.	Ollivier-Mrejen, R., Michel, P. & Pham, M.-H. Chronicles of a Science
Diplomacy Initiative on Climate Change. Science and Diplomacy (2018).
	36.	Hale, T. ‘All hands on deck’: the Paris Agreement and nonstate climate action.
Glob. Environ. Politics 16, 12–22 (2016).
	37.	Hovi, J., Sprinz, D. F., Sælen, H. & Underdal, A. The club approach: a gateway
to effective climate co-operation? Br. J. Political Sci. 49, 1071–1096 (2019).
	38.	Bauer, N. et al. Quantification of an efficiency–sovereignty trade-off in
climate policy. Nature 588, 261–266 (2020).
	39.	Bosetti, V., Carraro, C., Sgobbi, A. & Tavoni, M. Delayed action and
uncertain stabilisation targets. How much will the delay cost? Clim. Change
96, 299–312 (2009).
Nature Climate Change | VOL 11 | September 2021 | 738–745 | www.nature.com/natureclimatechange
744

Articles
NATUrE CliMATE ChAnGE
	40.	Jakob, M., Luderer, G., Steckel, J., Tavoni, M. & Monjon, S. Time to act now?
Assessing the costs of delaying climate measures and benefits of early action.
Clim. Change 114, 79–99 (2012).
	41.	Schaeffer, M. et al. Mid- and long-term climate projections for fragmented
and delayed-action scenarios. Technol. Forecast. Soc. Change 90, 257–268
(2015).
	42.	Iyer, G. C. et al. Improved representation of investment decisions in
assessments of CO2 mitigation. Nat. Clim. Change 5, 436 (2015).
	43.	Fuss, S. et al. Negative emissions—Part 2: costs, potentials and side effects.
Environ. Res. Lett. 13, 063002 (2018).
	44.	Climate change and land: an IPCC special report on climate change,
desertification, land degradation, sustainable land management,
food security, and greenhouse gas fluxes in terrestrial ecosystems
(IPCC, 2019).
	45.	Sanchez, D. L., Johnson, N., McCoy, S. T., Turner, P. A. & Mach, K. J.
Near-term deployment of carbon capture and sequestration from
biorefineries in the United States. Proc. Natl Acad. Sci. USA 115,
4875 (2018).
	46.	Cochran, J., Denholm, P., Speer, B. & Miller, M. Grid Integration and the
Carrying Capacity of the U.S. Grid to Incorporate Variable Renewable Energy.
https://www.osti.gov/servlets/purl/1215010 (2015).
	47.	Victor, D. G. et al. Turning Paris into reality at the University of California.
Nat. Clim. Change 8, 183–185 (2018).
	48.	Mission Possible: Reaching Net-Zero Carbon Emissions from
Harder-to-Abate Sectors by Mid-Century. Energy Transitions Commission
http://www.energy-transitions.org/sites/default/files/ETC_MissionPossible_
FullReport.pdf (2018).
	49.	Howe, P. D., Mildenberger, M., Marlon, J. R. & Leiserowitz, A. Geographic
variation in opinions on climate change at state and local scales in the USA.
Nat. Clim. Change 5, 596 (2015).
	50.	U.S. Energy Information Administration. The State Energy Data System (SEDS).
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in
published maps and institutional affiliations.
© The Author(s), under exclusive licence to Springer Nature Limited 2021
Nature Climate Change | VOL 11 | September 2021 | 738–745 | www.nature.com/natureclimatechange
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Methods
GCAM-USA model. The GCAM is an open-source global integrated assessment
model (https://github.com/JGCRI/gcam-core/releases; for more information, see
ref. 16 and online documentation http://jgcri.github.io/gcam-doc/toc.html). GCAM
represents key interactions across the economic, energy, land and climate systems
in 32 geopolitical regions in the world. It is a market equilibrium model that solves
for the market prices and quantities of a large number of markets simultaneously.
It is dynamic recursive with myopic foresight (that is, the model solution in each
model period depends on the conditions in that period or periods before it).
In this study, we use GCAM-USA v5.1, which is a version of GCAM
with state-level detail in the United States26. Like GCAM, GCAM-USA is an
open-source model. Detailed documentation for the GCAM-USA model is
available online (http://jgcri.github.io/gcam-doc/gcam-usa.html). Here we
summarize key model features that are relevant for this study. The model results for
all main and supplementary scenarios are available from a public data repository51.
GCAM-USA divides the energy and economic systems of the United States into
50 states and Washington DC, with state-level representation of socioeconomics,
energy transformation (power generation and refining), carbon storage, renewable
resources (wind and solar), electricity markets (with the representation of
regional electricity grids) and consumer end-use energy demands (in buildings,
transportation and industrial sectors).
Economic growth, population changes and climate changes set the scale
for energy demands in buildings, transportation and industrial sectors. These
demands are supplied by a variety of fuels and technologies. GCAM-USA
includes technological detail in all sectors within the energy system. For example,
the model includes about 20 different power generation technologies, about 10
different building service types and building technologies that vary across fuel
inputs, and about 40 different transportation technologies that vary across modes,
vehicle class, vehicle size and fuel input. The model also tracks details about
capital stock vintages in capital intensive sectors such as power and refining along
with simple algorithms to retire existing stock based on natural lifetimes and
economic conditions. Nested logit structures are used to share out new investments
across technologies to meet demands. The logit structures create competition
between different fuels and technologies on the basis of relative costs52. It avoids
winner-take-all type of responses and helps capture heterogeneity in unmodelled
factors across various technology options.
To represent electricity trade, states are grouped into 15 electricity grid regions
to reflect electricity market and planning areas (Supplementary Fig. 5). Within
a grid region, we assume unconstrained trade and therefore common electricity
prices across these states. Trade between grid regions is calibrated to historical levels
to reflect existing economic conditions as well as implied physical transmission
capability. In future modelling periods, trade can change from calibrated levels as
relative regional electricity prices change. The model also includes flexibility in the
location of energy-intensive industries such as refineries on the basis of the relative
costs of production across states based on a non-linear logit equation53. For oil
refining, our scenarios assume that expansion takes place in the states that currently
engage in oil refining and that the relative competitiveness of those states remains
constant over time. For newer technologies such as biomass to liquids technologies,
we assume that the current distribution of production will remain largely static in the
coming years, which, in turn implies that biomass production will largely occur in
the same locations as today. Note that the model includes representation of negative
emissions technologies (such as BECCS) in both electricity and refining sectors.
In addition to a detailed representation of the energy system within the United
States, the model includes global representations of the agriculture and land-use
systems at the basin scale. These systems are all hard-coupled in code. For example,
biomass production is modelled in the agriculture and land-use component of the
model that creates a competition for land among various land uses such as biomass,
crop production, managed and unmanaged forests and livestock. Biomass produced
in the agriculture and land-use component is demanded in the energy system.
Likewise, fertilizers produced in the energy system are demanded by crops in the
agriculture and land-use system. GCAM-USA maintains representations of 31
geopolitical regions outside of the United States; hence, prices and changes occurring
within the United States are consistent with international and global conditions.
Scenario design. To design mid-century scenarios, we set varying levels of
national mitigation effort, targeting the national total GHG emissions in 2050
to be 20%, 40%, 60%, 80% and 95% below 2005 levels, respectively. The 20–80%
decarbonization results are presented in the main text, and 95% decarbonization
results are presented in Supplementary Fig. 7 as a sensitivity run to understand the
required energy system changes in line with a 1.5°C global climate stabilization
target and close to the Biden Administration’s net-zero emissions target. We
assume linear GHG mitigation pathways from 2015 to 2050 with 5-year interval
(see trajectories for GHG targets in Supplementary Fig. 1). Since GCAM-USA is
embedded within the global GCAM model and allows for interactions between
the United States and the rest of the world through global markets, to avoid
cross-country carbon leakage, we set decarbonization targets for other countries
based on ref. 53, which are consistent with the 2°C pathway.
We consider three subnational policy approaches to achieve the national
targets. Under the Uniform approach, the model solves a single MAC (and in turn
carbon price) nationally to meet the decarbonization target. The MAC is uniform
across states, which is determined by the marginal cost to mitigate the last unit of
CO2 emissions nationally. Under the Hybrid and Heterogeneous approaches, we
allow for heterogeneous MACs across states. We set the relative ratio of state-level
MACs based on the present-day public support level for climate policy, then let the
model solve the whole set of MACs for 51 states (Figs. 1b and 2 and Supplementary
Methods). Note that the MACs capture the effects similar to a carbon price. A
high MAC encourages the deployment of high-cost CO2 mitigation technologies
(such as renewable electricity and BECCS) as well as a reduction in overall fossil
energy use. As long as the importing activities can reduce energy production and
associated emissions within the state boundary, our approach would not further
require importing only low-carbon electricity or goods.
Under both the Hybrid and Heterogeneous approach, we assume a non-linear
relationship between the public support level and MAC (Figs. 1b and Fig. 2 and
Supplementary Methods). Under the Heterogeneous approach, we explore the
largest heterogeneity in MACs across all the states. Under the Hybrid approach,
we further consider a modest level of nationwide carbon policy, and allow states
to set their MAC only higher than this nationwide threshold. The threshold is set
at the 40th percentile to represent the 60% voting threshold of passing legislation
in the U.S. Senate. We also consider a variety of alternative formulations of policy
heterogeneity, discussed in detail in Supplementary Methods.
Calculation of mitigation costs. To calculate the mitigation cost, we construct
state-level MAC curves using the CO2 emissions and MACs from 20% to 95%
decarbonization target runs. The model considers state-varying and time-varying
MAC curves, driven by the variations in a wide range of factors such as existing
infrastructure, local availability of low-carbon resources and the evolving costs of
technologies over time. We then integrate the area under the MAC curves in each
state to calculate state-level mitigation cost, and add up the cost to the national
level. All monetary values in this paper are presented in 2015 US$.
Data availability
The datasets generated during and analysed in the current study are available from
a public repository (https://doi.org/10.5281/zenodo.5061357).
Code availability
The GCAM and GCAM-USA model are available for download from https://
github.com/JGCRI/gcam-core. Detailed model documentation is available online
at http://jgcri.github.io/gcam-doc/gcam-usa.html.
References
	51.	Peng, W. et al. Datasets for ‘The Surprisingly Inexpensive Cost of
State-Driven Emission Control Strategies’. Zenodo. https://doi.org/10.5281/
zenodo.5061357 (2021).
	52.	Clarke, J. F. & Edmonds, J. A. Modelling energy technologies in a competitive
market. Energy Econ. 15, 123–129 (1993).
	53.	Fawcett, A. A. et al. Can Paris pledges avert severe climate change? Science
350, 1168 (2015).
Acknowledgements
We thank B. Keohane, D. Tingley, L. Stokes, J. Jenkins, K. Fisher-Vanden and participants at
seminars at Penn State University (September 2019), Johns Hopkins University (September
2019) and Princeton University (November 2019) on related themes. W.P. received a
summer research stipend from Penn State School of International Affairs. G.I., M.B. and
J.A.E. received support from the Global Technology Strategy Program. D.G.V. draws
funding, in part, from the Electric Power Research Institute, a nonprofit R&D organization
focused on the electric power sector. D.G.V. is also supported partly by donations to the
Scripps Institutional Oceanography for research on emergency responses to climate change.
Author contributions
W.P., G.I. and D.G.V conceived and designed the study. W.P., G.I. and M.B performed the
model simulations with data input from J.M. W.P. analysed the data. W.P., G.I. and D.G.V
wrote the manuscript with important input from all authors.
Competing interests
D.G.V. is a consultant to the shareholder group Engine No. 1. The other authors declare
no competing interests.
Additional information
Extended data is available for this paper at https://doi.org/10.1038/s41558-021-01128-0.
Supplementary information The online version contains supplementary material
available at https://doi.org/10.1038/s41558-021-01128-0.
Correspondence and requests for materials should be addressed to W.P.
Peer review information Nature Climate Change thanks Aleh Cherp, Laurent Drouet and
the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Reprints and permissions information is available at www.nature.com/reprints.
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Extended Data Fig. 1 | Reduction in energy-related CO2 emissions for four levels of national mitigation efforts under two subnational policy
approaches. Here we show the reduction in CO2 emissions in 2050 relative to 2005. The first and second rows show the results under the uniform and
heterogeneous approach, respectively. Different colors of the bars show the mitigation in different economic sectors. The white numbers represent the
percent contribution of electricity sector to total CO2 mitigation. Low, Medium and High represents the low-, medium-, and high-supporting states,
respectively.
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Extended Data Fig. 2 | Net electricity trade in 2050 for 15 grid regions. a, ‘80% Uniform’: 80% national decarbonization with the uniform approach;
b, ‘80% Heterogeneous’: 80% national decarbonization with the heterogeneous approach; c, Changes in ‘80% Heterogeneous’ relative to ‘80%
Uniform’. For a) and b), the background colors represent the net electricity export from a grid region (orange) or the net import into a grid region (blue).
The electricity transmission patterns remain largely the same under these two subnational policy approaches. For c), the background colors represent
the absolute differences in net electricity export (that is, generation minus demand) between these two approaches. The black numbers show the
percent differences: the positive numbers indicate that a net exporting (importing) grid in “80% Uniform” further increases its export (import) in “80%
Heterogeneous”, while the negative numbers indicate that a net exporting (importing) grid in “80% Uniform” reduces its export (import) in “80%
Heterogeneous”. In other words, 13 out of the 15 grids increase their electricity trade with other grids under the Heterogeneous approach. The 15 electricity
grid regions are presented in Supplementary Fig. 5.
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Extended Data Fig. 3 | CO2 sequestration by bioenergy with carbon capture and storage (BECCS) technology in 2050. a, Total CO2 sequestration from
BECCS; b, CO2 sequestration from BECCS for bioliquids production; c, CO2 sequestration from BECCS for electricity production. 20%-80% represent the
levels of national mitigation effort. ‘U’ and ‘H’ represent Uniform and Heterogeneous policy approaches, respectively. Low, Medium and High represent
low-, medium-, and high-supporting states.
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Extended Data Fig. 4 | Variations in state-level carbon intensity and mitigation costs to achieve 80% decarbonization nationally. a, Carbon intensity
in 2015; b, Reduction in carbon intensity in 2050 relative to 2015, to achieve 80% national decarbonization with uniform or heterogeneous approach; c,
Mitigation cost in 2050 as a fraction of 2050 GDP, to achieve 80% national decarbonization with uniform or heterogeneous approach. All economic values
are presented in US$2015.
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Extended Data Fig. 5 | Carbon mitigation costs for four levels of national mitigation efforts under alternative formations of policy heterogeneity. Here
we show the carbon mitigation cost in 2050 as a fraction of projected 2050 GDP, by three groups of states (low, medium and high-supporting states).
‘Uni’ stands for the uniform approach. Het, Het (Gov), Het (LN), Het (+range), Het (3 zero), Het (5 zero) and Het (AP) represent different heterogeneous
approaches with detailed description in the Sensitivity Analysis section and Supplementary Methods. The inserted figure shows the contribution by low-,
medium-, and high-supporting states to national total CO2 emissions in 201650.
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Extended Data Fig. 6 | Reduction in energy-related CO2 emissions when carbon capture and storage (CCS) technology is not available. Here we show
the reduction in energy-related CO2 emissions in 2050 relative to 2015 for: a, National total; b, Low-supporting states; c, Medium-supporting states;
d, High-supporting states. Different colors of the bars represent different economic sectors. The white numbers represent the percent contribution of
the electricity sector to total CO2 mitigation. 40% U – 40% decarbonization with uniform approach; 40% H – 40% decarbonization with heterogeneous
approach; 80% U – 80% decarbonization with uniform approach; 80% H - 80% decarbonization with heterogeneous approach.
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    Scientific Research Findings:

Answer: As compared to an idealized nationally uniform policy, we find that varying the state-level policy stringency by a factor of three will increase the nationwide cost by only about 10%. Such results are robust under different national decarbonization targets, formulations for policy heterogeneity, and technology assumptions. The low cost hinges on two conditions. First is the availability of critical technologies (for example, low-carbon electricity and bioenergy with carbon capture and storage) and the ability to trade relevant energy products across state borders. Second is that there is at least some effort by every state. If a handful of states are not engaged at all, the leading states will need to adopt extremely expensive negative emissions technologies, which pushes up the nationwide cost. These two conditions could be difficult to meet in the real world given the technological, regulatory and political realities. Future work should consider potential constraints on technology adoption as well as trade and state politics.