UPDATED INFLATIONREDUCTION ACTMODELING USING THE
ENERGY POLICYSIMULATORMEGAN MAHAJAN, OLIVIA ASHMOORE, JEFFREY
RISSMAN, ROBBIE ORVIS, ANAND GOPAL
AUGUST 2022

This research note was updated on August 23, 2022 after final
passage of the IRA to incorporate modeling updates, add new
outputs and data, and add new appendices on our
methodologies.
EXECUTIVE SUMMARY
On August 16, 2022, President Biden signed the Inflation
Reduction Act (IRA) into law. The IRA’s $369 billion in fundingfor emissions-reducing climate and clean energy provisions
run the gamut from clean energy and electric vehicle (EV) tax
credits to large-scale investments in domestic clean
technology manufacturing to advancing environmental
justice. The IRA also requires auctions for oil and gas onfederal lands and waters prior to auctions for renewableenergy projects and requires completion of several 2022 leaseauctions that were previously canceled.
Energy Innovation Policy & Technology LLC® modeled the
IRA’s impact on emissions reductions, job creation, and publichealth, using our free and open-source U.S. Energy Policy
Simulator (EPS).1
Our updated modeling finds that the IRA is the mostsignificant federal climate and clean energy legislation in U.S.
history, and its provisions could cut greenhouse gas (GHG)
emissions 37 to 43 percent below 2005 levels. With additional
executive and state actions, the U.S. can realistically achieve
its nationally determined commitments (NDCs) under theParis Agreement.
www.energyinnovation.org
98 Battery Street, Suite 202
San Francisco, CA 94111
policy@energyinnovation.org
1

www.energyinnovation.org

Further, for every ton of emissions generated by IRA oil and gas provisions, at least 28 tons ofemissions are avoided by the other provisions.i
Under a business-as-usual (BAU) scenario (i.e., including all enacted federal and state policies todate) our modeling forecasts the U.S. would reduce emissions 25 percent compared to 2005
levels by 2030.

8000

Economy-Wide Greenhouse Gas Emissions

7000
BAU, 5,001(-25%)MMTCO2e

6000
5000

Low, 4,183(-37%)

4000

Moderate,
4,088(-39%)

3000

High, 3,809(-43%)

2000
1000
0
2005

2010

2015

2020

2025

2030

In other words, the IRA would enable the U.S. to close 49 to 71 percent of the emissions gap
between BAU and the NDC in 2030.
In absolute terms, U.S. emissions in 2030 are projected to be 2,500 million metric tons (MMT) to
2,800 million metric tons lower than 2005 levels. The IRA provisions could also generate enormous
public health and jobs benefits, preventing up to 4,500 premature deaths from air pollution in 2030
and creating up to 1.3 million jobs in 2030. Finally, the IRA could increase U.S. gross domestic
product (GDP) by 0.65 to 0.77 percent in 2030.

i This research is accessible under the CC BY license. Users are free to copy, distribute, transform, and build upon thematerial as long as they credit Energy Innovation Policy & Technology LLC® for the original creation and indicate ifchanges were made.

2

INTRODUCTION
The final IRA legislative text includes $369 billion in funding for climate and clean energy provisions.
These emissions-reducing provisions include clean energy and EV tax credits, large-scale domestic
clean technology manufacturing investments, and environmental justice measures. The IRA also
requires several auctions for oil and gas on federal lands and waters prior to auctions for renewableenergy projects and requires completion of several 2022 lease auctions that were previously
canceled.
To help understand its net effect, Energy Innovation® modeled climate and energy provisions of
the IRA using the U.S. EPS, an open-source and peer-reviewed climate policy model that estimatesclimate and energy policy impacts using publicly available data.
Our findings confirm that passing the IRA will reduce GHG emissions an estimated 820 to 1,200
MMTs of carbon dioxide equivalent (CO2e) in 2030 despite the oil and gas leasing requirements.
Those reductions would reduce U.S. emissions 37 to 43 percent below 2005 levels and makesignificant progress towards achieving the 2030 U.S. NDC of 50 to 52 percent below 2005 GHG
emissions.
The IRA could create up to 1.3 million new jobs in 2030 concentrated in the manufacturing,
construction, and service industries. Through greater clean energy deployment, the bill could avoid
up to 4,500 premature deaths and up to 119,000 asthma attacks annually by 2030.
While this analysis covers the vast majority of the IRA’s climate and energy provisions, including all
those that could significantly affect GHG emissions, it is not entirely comprehensive. Some
provisions or funding mechanisms were excluded from the modeling due to difficulty translating
certain spending categories or incentives into emissions reductions. These programs could likely
yield small additional GHG reductions beyond what we have modeled. They may also yield
important public health benefits that are not captured here.
RESULTS AND KEY FINDINGSThe results in this updated research note include policy scenarios updates reflecting final text of
the IRA, along with improvements to the methodologies and assumptions used in our earlier
research note.ii
Our modeling includes four core scenarios: A Business-as-Usual (BAU) Scenario that holds current
policy constant, along with Low, Moderate, and High Scenarios that make different assumptions
about the efficacy of certain provisions within the IRA, such as the share of projects or sales thatii The earlier version of the IRA modeling can be found here: https://energyinnovation.org/wp-

content/uploads/2022/08/Modeling-the-Inflation-Reduction-Act-with-the-US-Energy-Policy-Simulator_August.pdf

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qualify for bonus credits, leverage ratios for private sector dollars, and the evolution of supply
chains throughout the decade.
More information on data sources is available online at https://us.energypolicy.solutions/docs/. A
full description of our provision-by-provision methodology is included in Appendix A, including how
our assumptions varied across scenarios. A full description of our methodology for the oil and gas
leasing calculations is included in Appendix B.
Our model results are discussed below, including emissions projections, changes in clean electricity
and zero-emission vehicle (ZEV) deployment, and oil and gas supply changes, along with impacts
on public health, jobs, and the economy.
Greenhouse Gas Emissions

Our modeling shows the IRA could help reduce 2030 U.S. GHG emissions 37 to 43 percent below
2005 levels, while emissions would fall only 25 percent below 2005 levels under a BAU Scenario.
This means the IRA will enable the U.S. to close 49 to 71 percent of the emissions gap between
BAU and the U.S. NDC to reduce emissions 50 to 52 percent in 2030—representing a major down
payment on our Paris commitment.
2030 GHG Emissions(AR4 GWP-100 CO2e)

Percent Below 2005
Emissions in 2030

Business-as-usual

5,001

-25%

Low

4,183

-37%

Moderate

4,088

-39%

High

3,809

-43%

Scenario

Table 1: GHG Emissions Reductions

Figure 1 below presents emissions trajectories for each of the scenarios we modeled and highlights
the range between our Low and High scenarios.

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8000

Economy-Wide Greenhouse Gas Emissions

7000
BAU, 5,001(-25%)MMTCO2e

6000
5000

Low, 4,183(-37%)

4000

Moderate,
4,088(-39%)

3000

High, 3,809(-43%)

2000
1000
0
2005

2010

2015

2020

2025

2030

Figure 1: 2005-2030 GHG Emissions Trends by Scenario

Figure 2 and Figure 3 include projected sectoral GHG emissions and reductions by scenario in 2030.
As Figure 3 highlights, emissions reductions are most concentrated in the power sector, withsmaller contributions from other sectors. Transportation and building sector reductions are limited
because of the nature of the incentives and funding programs, along with the stock turnoverdynamics of those sectors, i.e., even with growth in the sales share of clean technology significant
emissions reductions take years to accrue.

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Figure 2: 2030 GHG Emissions by Sector

Figure 3: 2030 GHG Emissions Reductions by Sector and Scenario

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Clean Electricity

The IRA includes many incentives and significant funding to deploy clean power and reduce
emissions. Provisions include investment and production tax credits (which become technology
neutral in later years), a tax credit for existing nuclear power points, a new U.S. Department ofEnergy (DOE) loan program (section 1706), and funding for rural utilities, among others. The tax
credits also have bonus provisions that increase their value if certain project conditions are met,such as using unionized labor, meeting minimum domestic content requirements, and siting withincertain communities.
To model the impacts of the clean energy tax credit provisions for clean electricity, we partneredwith Energy Transitions AI, an external consultant group running the ReEDS capacity-expansion
model. We coupled the results of these modeling runs with estimated impacts of funding programs
to estimate the combined impact of the programs on clean electricity deployment. Table below
highlights our findings. In our BAU Scenario, clean electricity represents 49 percent of electricity
generation in 2030, corresponding to 413 gigawatts (GW) of cumulative renewable capacity. In our
IRA scenarios, the share of clean electricity ranges from 72 to 85 percent, corresponding to a rangeof cumulative solar and wind capacity of 795 GW to 1,053 GW.

Scenario

Share of Clean
Electricity Generation(2030)

Solar + Wind GWs(2030)

Business As Usual

49%

413

Low

72%

795

Moderate

75%

877

High

85%

1053

Table 2: 2030 Clean Electricity Shares and Cumulative Renewable Capacity

It is important to note these findings do not account for important barriers that could limit clean
electricity deployment. In particular, the modeling assumes that necessary transmission will bebuilt, interconnection delays are addressed, supply chains provide the necessary materials to
deploy these levels of clean electricity, and a sufficient workforce can supply the labor.
Each of these represents a potential barrier to scaling electricity deployment at the rates ourmodeling envisions. However, each barrier is being actively addressed by federal and statepolicymakers. The Federal Energy Regulatory Commission (FERC) is addressing transmission
planning and interconnection processes through several current rulemaking proceedings, likely to
be concluded in late 2022 or early 2023. Infrastructure Investment and Jobs Act (IIJA) of 2021
provisions could strengthen DOE authority to site and financially support transmission lines, andcould bolster manufacturing facilities and supply chains to support new transmission. President

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Biden has also invoked the Defense Production Act to ramp up domestic production of criticalmaterials and clean energy manufacturing to address supply chain concerns.
More work is needed to understand how much each barrier might constrain deployment as well as
the impact of current and future policy actions to address them.
Zero-Emission Vehicles

The IRA also includes new tax credits for personal and commercial clean vehicles. The commercial
clean vehicle tax credit provides an incentive of up to $7,500 for vehicles under 14,000 pounds,
and up to $40,000 for vehicles 14,000 pounds and over, depending on the vehicle cost andcomparative cost of a similar internal combustion engine vehicle.
The vehicle tax credit is much more complicated for personal vehicles, and includes the following
elements:
•

•

•
•

The credit is split into two pieces: a $3,750 credit for meeting increasingly stringent
domestic battery assembly requirements and a $3,750 credit for meeting increasingly
stringent critical minerals requirements.
The credit contains a manufacturer’s suggested retail price (MSRP) cap of $55,000 for cars
and $80,000 for all other vehicles, and all cars must be assembled in North America toqualify for the credit.
An additional adjusted gross income (AGI) cap limits the tax credit to individuals earning
less than $150,000 a year or households earning less than $300,000.
Restrictions on which vehicles qualify as clean begin in 2024, notably removing vehicles
that use materials from “entities of concern,” which includes Chinese companies, in thebattery and for any of the mineral sourcing or processing starting in 2025. It remains to be
seen how restrictive this language will be on limiting the ability of vehicle manufacturers,
but it could significantly limit qualifying vehicles, at least until the industry has time to findalternative sources of materials and establish the relevant supply chains. However, IRA
manufacturing incentives, especially when coupled with incentives in the IIJA and theChips and Science Act, create a very strong incentive to grow the necessary minerals
processing, battery, and semiconductor industries in the U.S.

Given the complexity of each requirement, our modeling of the personal vehicles evaluated a rangeof possibilities. In our Low Scenario, we assume no manufacturers qualify for the credits once new
restrictions on the “entities of concern” kicks in. In our High Scenario, we assume a gradually
increasing share of new vehicles qualify, such that by 2030 all new vehicles would qualify. Our
Moderate Scenario falls between the Low and High Scenarios. We also account for the MSRP cap,
AGI cap, the made in North America requirement, the ability of manufacturers to use batteries
assembled in North America, and their ability to source the critical minerals from qualifying regions.

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EI | MODELING THE INFLATION REDUCTION ACT USING THE ENERGY POLICY SIMULATORScenario

Passenger
Vehicle BEV
Sales Sharein 2030

Passenger
VehiclePHEV Sales
Share in
2030

Light/Medium
Truck BEV
Sales Share in
2030

Light/Medium
Truck PHEV
Sales Share in
2030

Bus BEV
Sales Sharein 2030

Heavy Truck
BEV Sales
Share in
2030

Business as
Usual

21%

8%

17%

4%

15%

10%

Low

22%

8%

36%

3%

20%

24%

Moderate

25%

9%

37%

3%

21%

25%

High

29%

10%

38%

3%

21%

27%

Table 3: Sales Shares of BEV and PHEVs in 2030 by Scenario

Scenario

Passenger
Vehicle BEV
Stock Sharein 2030

Passenger
VehiclePHEV Stock
Share in
2030

Light/Medium
Truck BEV
Stock Sharein 2030Light/Medium
Truck PHEV
Stock Sharein 2030Bus BEV
Stock Sharein 2030

Heavy
Truck BEV
Stock Sharein 2030

Business as Usual

9%

5%

7%

3%

5%

2%

Low

9%

4%

16%

3%

6%

5%

Moderate

10%

5%

16%

3%

6%

5%

High

11%

5%

16%

3%

6%

6%

Table 4: Stock Shares of BEV and PHEV in 2030 by Scenario

Our findings in Table 3 and Table 4 show changes in sales and stock in 2030 resulting from tax
credits and other provisions affecting vehicle sales, and highlight the large range of uncertainty forthe personal vehicle tax credits.
As is reflected in these tables, even higher sales shares drive a smaller change in the vehicle stockby 2030, which reflects limitations related to transportation sector stock turnover. Put anotherway, because only a fraction of the total stock of vehicles is replaced each year, it can take many
years to realize deep sectoral reductions, even with high shares of clean vehicle deployment. Thishighlights the importance of strong ZEV incentives in the next decade, as waiting runs the risk of
missing climate goals due to slow stock turnover. It is also worth noting that transportation
emissions reductions in 2035 or 2040 will be significantly greater than in 2030 given the stock
turnover dynamic.

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Oil and Natural Gas Supply and Emissions

Oil and Natural Gas Leasing Provisions
In oil and natural gas markets, demand drives prices, which in turn drive supply. Therefore, we
expect changes in demand for oil and natural gas to be the primary driver of U.S. productionchanges. Considering significant natural gas demand reductions from the IRA and moderatedecreases in petroleum product consumption, we would most likely see a decrease in productionof oil and gas, as is suggested by modeling from the Rhodium Group, not an increase.2
Nevertheless, we choose a potential worst-case scenario because oil and gas infrastructure has along life, and any production that might result from the IRA could continue to operate beyond
2030. We modeled upstream and downstream U.S., as well as rest-of-world emissions from theadditional oil and gas production on federal lands and waters which could result from the IRA
provisions, assuming those lands go into production.
Our methodology is as follows (see Appendix B for a full discussion of our methodology):
1) We developed two baseline cases of oil and gas lease auctions in the absence of the IRA.
In our Low Case, we assume a leasing ban through the end of the decade without the IRA.
In our High Case, we assume lease auctions continue based on the actions of the Biden
administration to date.
2) Next, we develop our IRA Case. This reinstates the cancelled 2022 lease auctions as
required under the IRA and assumes 60 million acres of offshore land and 2 million acresof onshore land offered at auction every year to the end of the decade.
3) To determine how much land is leased at auction, we used historical data covering multiple
administrations. The share of land that is leased at offshore auctions is very low on average,around 2 percent. For onshore auctions, approximately 30 percent of acreage offered isleased.
4) From there, we then developed production profiles using historical data:a. For offshore, we used Bureau of Ocean Energy Management data on the timelineof well completions for a given area of development. On average, an increasing
number of wells are drilled for the first 15 to 20 years, followed by a decreasing
number through years 30 to 35, resulting in a production profile of about 50
years.
b. For onshore, this data was not available, and we simply assumed land goes into
production at average production to area values once the land is leased at auction.
5) For offshore, we then applied production profiles to the wells that reflect the varying
amount of product produced over the lifetime of the well. For example, around 50 percent
of a well’s total product is produced in the first year after it is drilled, with diminishingoutput after.

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6) We then assumed that 30 percent of the new production on federal lands was offset bydecreases on private lands, based on data from Brian Prest at Resources for the Future. 37) Next, we developed price elasticities of supply using data from the U.S. Energy Information
Administration (EIA) and we estimated the percent change in the U.S. price of natural gas,
crude, and petroleum products using these values.
8) We fed the increased production and the changes in prices into the EPS, which captures
the emissions associated with production, processing, transmission, and distribution andthe subsequent change in downstream consumption and emissions from the priceimpacts.iii
9) Finally, we estimated the leakage of emissions internationally using values from Brian
Prest’s paper.
Our estimates assume that decreases in natural gas consumption as well as incremental supply canbe exported via liquified natural gas export terminals and international pipelines. Between our Low
and High Scenarios, U.S. natural gas demand decreases by roughly 18 to 27 percent relative to theBAU Scenario, equivalent to 6.2 to 9.3 trillion cubic feet (TCF) of natural gas. Incremental natural
gas domestic consumption from the oil and gas leasing provisions in 2030 totals 0.10 to 0.23 TCF.
In our BAU Scenario, based on EIA data, the U.S. exports about 9 TCF of natural gas, 5.4 TCF ofwhich is liquefied natural gas (LNG), in 2030. Based on the latest FERC data, under construction,
approved, and proposed LNG terminals total 19.4 TCF of capacity, though many of these projects
do not have an estimated completion date.4
Nevertheless, if a significant share of the under construction, approved, and proposed terminals
are completed by 2030, they could create sufficient capacity to export gas from reduced domestic
demand and incremental production. It is unclear whether sufficient demand for U.S. exported gas
exists to support this much export capacity, as well as the likelihood that all these facilities will becompleted by 2030, or completed at all.
Our revised approach to estimating lease auction impacts has several notable improvements on
our prior approach and related estimates. First, it correctly accounts for switching between federal
and non-federal lands, which was ignored in our earlier estimates. Second, it better estimates thetime profile of when extraction occurs from a given piece of land by looking at empirical data rather
than assuming all production starts in a single year. Finally, it correctly accounts for changes in U.S.
prices and consumption relative to international consumption and allows us to distinguish between
the two. For these reasons, the revised approach generates more accurate results.

iii See the Method section below for a discussion of methane global warming potential (GWP) used in the EPS

and how it affects our estimates.

11

EI | MODELING THE INFLATION REDUCTION ACT USING THE ENERGY POLICY SIMULATORThe findings are still conservative, as they do not account for potential decreases in domestic
demand for oil and gas resulting from the IRA that would likely reduce total U.S. production. The
approach also assumes that developers are able to obtain necessary drilling permits.
The updated approach generates estimates that are lower than, but of the same magnitude as, ourearlier estimates. As shown in Figure 4, we estimate the oil and gas lease provisions could add 17
to 29 MMT CO2e to global emissions, represented by the orange dots, the vast majority of which
occurs outside the U.S. In our Moderate Scenario, we actually find emissions decreases
domestically from changes in energy prices, which is why that scenario is lower than either the Low
or High Scenarios.

Incremental Domestic and International Emissions
Associated with Additional Oil and Gas Production
35
30

29

MMTCO2e

25

22

20

17

15
10
5
0
-5

Low

Moderate
U.S.

High

Rest of world

Figure 4: Potential Changes in Global GHG Emissions from Oil and Gas Leasing Provisions

The global increase in 2030 is relative to U.S. reductions of 820 to 1,200 MMT reductions in 2030.
In other words, based on the updated methodology, for every one ton of global emissions increases
caused by oil and gas leasing provisions, at least 28 tons of emissions are avoided by other IRA
provisions in the U.S. Thus, despite the potential for increased oil and gas extraction, the IRA
overwhelmingly reduces emissions.
While increased extraction could occur on public lands, the vast majority of it would occur offshore,
and would be associated with decreases in production on private lands, it is important to note that
increased extraction could lead to an increased pollution burden in communities where oil and gas
is processed and transported.

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Methane Emissions Reduction Program
The Methane Emissions Reduction Program (MERP) imposes a fee on oil and gas sector methane
emissions that rises to $60/ton CO2e for companies with facilities that exceed certain emissions
leakage rates. In the final legislation, the reporting threshold for facilities is 25,000 tons per year
and aligns with facilities required to report to the U.S. Environmental Protection Agency’s (EPA)
Greenhouse Gas Reporting Program (GHGRP). Similarly, emitting companies are allowed toaggregate emissions across their sites as opposed to having site-specific leakage requirements.
The combination of these requirements significantly reduces the program’s coverage relative toearlier iterations and the sector’s total methane emissions. For example, the latest U.S. GHG
inventory showed 212 MMT CO2e of methane emissions from the natural gas and oil supply sectors
in 2020, 5 but only 82 MMT CO2e of methane emissions were reported to the GHGRP, 6 meaning
only 39 percent of emitters are covered by the program. From there, the aggregation rules further
shrink the market size. Using data from M.J. Bradley and Associates, roughly 78 percent ofemissions that report to GHGRP are above the leakage thresholds. Finally, only a share of thoseemissions are abatable for under $60/ton CO 2e. Putting each of these together, we find the MERP
would reduce emissions by 29 MMT CO2e by 2030.
Improvements to this program could significantly increase its scope and emissions reductions.
Lowering the reporting threshold could increase the share of emissions covered by GHGRP and
therefore by the MERP. The IRA includes funding to assist the EPA and emitters with better leakmonitoring, which could also help improve the program because empirical measurements havetypically shown leakage rates significantly higher than what companies self-report, meaning morecompanies would fall under the program’s scope. Finally, the EPA is working towards final rules forexisting oil and gas producers, which could help cover facilities not covered by the IRA.
Carbon Capture, Utilization, and Storage

The IRA includes an expansion of the 45Q tax credit for carbon capture, utilization, and storage(CCUS) on top of the existing credit. Given the value of other IRA clean energy tax credits, ourmodeling does not find any power sector CCUS is deployed by 2030. However, is it possible thatcertain utilities will opt to install CCUS on existing plants, particularly if they are able to rate-basethe costs of doing so. However, even with this possibility, it is unlikely we will see significant
deployment of power sector CCUS by 2030.
To model industrial CCUS applications that result from 45Q we rely on Rhodium Group’s projectedcarbon capture capacity under various IRA scenarios and assign the CCUS growth to sectors in the
EPS.7 By 2030, our modeling finds an additional 17 to 19 MMT of capture potential in the industrial
sector, relative to 77 MMT of capture under the BAU Scenario. However, the Rhodium modelingfinds significant growth in carbon capture after 2030, and by 2035 the total installed industrial
carbon capture is significantly higher. Additionally, while the Rhodium modeling finds up to 7 MMT

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of direct air capture deployed by 2030, we do not see a market by 2030 for direct air capture (DAC)
given its costs (even with 45Q), and therefore do not include deployment of DAC.
Figure 5 shows estimated carbon capture in the manufacturing sector by industry. Based on thedata from Rhodium, growth in carbon capture is primarily concentrated in the chemicals andrefining industries (including hydrogen production) and natural gas processing.

Incremental Carbon Capture and Sequestration in
2030
25.0

MMTCO2e

20.0

15.0

18.3

17.4

7.0

6.1

19.1

7.8

10.0

5.0

Natural Gas Processing

Chemicals and Refineries
11.3

11.3

11.3

Low

Moderate

High-

Figure 5: 2030 Carbon Capture Amounts

Public Health and Climate Impacts

In addition to significantly reducing GHG emissions, the IRA could cut emissions that lead tonegative health outcomes, including particulates and precursor emissions like SOx and NOx. We
find that reduced air pollution in the modeled scenarios could avoid between 2,900 and 4,500
premature deaths in 2030, in addition to preventing 76,000 to 119,000 asthma attacks and 312,000
to 484,000 lost workdays.

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AvoidedPremature
Mortalities

Percent Change
in Deaths byRace - White

Percent Change
in Deaths byRace - Black

Percent Change
in Deaths byRace - Asian

Percent Change in
Deaths by Race –Other Race orMultiple Races

Low

2,900

-0.09%-0.11%-0.12%-0.17%

Moderate

3,200-0.10%-0.12%-0.13%-0.19%

High

4,500

-0.13%-0.17%-0.18%-0.27%

Scenario

Table 5: Annual Avoided Premature Deaths in 2030 by Scenario

As a percentage decrease, avoided deaths are concentrated in communities of color, which havehistorically experienced the most harm from air pollution. Disadvantaged communities are often
located in close proximity to polluting infrastructure and, on average, the bill’s provisions reduce
more negative health impacts in communities of color.

Scenario

AvoidedAsthmaAttacks

Avoided
Lost
Work
Days

AvoidedRespiratory
Symptoms
andBronchitis

AvoidedNonfatalHeart
Attacks

AvoidedHospital
Admissions

AvoidedRespiratory
ER Visits

AvoidedMinor
Restricted
Activity Days

Low

76,300312,200

115,100

3,300

1,500

1,400

1,821,700

Moderate

85,900350,700

129,200

3,700

1,700

1,600

2,046,300

High

118,600

484,600

178,900

5,100

2,300

2,200

2,825,900

Table 6: Avoided Health (Morbidity) Outcomes in 2030 by Scenario

Using the EPA’s Value of a Statistical Life, the monetized avoided health damages are $27 to $42
billion alone in 2030. Using the White House’s social cost of carbon estimates, the economic valueof avoided GHGs is valued at $51 to $74 billion in 2030.
Annual Monetized
Benefit from
Avoided Climate
Damages in 2030

Annual Monetized
Benefit from Avoided
Premature Mortality inYear 2030

Cumulative
Monetized Benefit
from Avoided Climate
Damages by 2030

Cumulative Monetized
Benefit from Avoided
Premature Mortality by
2030

Low

$51.1 billion$27.2 billion$211.3 billion$118.4 billion

Moderate$57.0 billion$30.5 billion$250.3 billion$138.9 billion

High$74.4 billion$42.4 billion$335.1 billion$199.8 billion

Scenario

Table 7: Monetized Avoided Climate and Health Damages by Scenario

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Cumulatively, the IRA results in climate benefits of $211 to $335 billion by 2030 and monetized
avoided health damages of $118 to $200 billion by 2030, for a total of $329 to $535 billion.
Jobs and GDP

The IRA earmarks billions in funding for climate and energy provisions, which could generatesignificant domestic job growth. Our modeling finds the provisions could create 1.2 million to 1.3
million net new jobs in 2030 relative to BAU. These new jobs are spread across the economy, but
focused in the service, manufacturing, trade, and construction sectors as shown in Figure 6.

Job Creation in 2030
1,600,000
1,400,000

1,200,000

Job Years

1,000,000

1,338,500
1,204,200

1,187,800

208,900

208,000

199,400

17,50011,30012,600267,100

226,200

249,100

800,000

48,400600,000

200,000-

75,900404,400

381,300

364,600

29,30036,10045,300285,000

253,700

261,000(22,400)
Low(21,400)
Moderate(4,600)High

400,000

Mining63,00048,60045,10037,100Trade

Services andProfessional
Other
Utilities
Manufacturing
Agriculture
Construction(200,000)
Figure 6: Net Annual Change in Jobs in 2030 by Scenario and Sector

These estimates are conservative because while they include impacts from the advanced
manufacturing tax credits and Defense Production Act funding, they do not include estimatedimpacts from the domestic content bonus credits for clean technology deployment. These bonus
credits are very likely to create significant demand for U.S. commodities and equipment that would
likely further increase job growth in manufacturing.

16

EI | MODELING THE INFLATION REDUCTION ACT USING THE ENERGY POLICY SIMULATORThe IRA includes bonus credits and other incentives aimed at increasing deployment of clean
energy technologies in energy communities, which includes communities with fossil fuelextraction, processing, and burning. The goal of these incentives is to promote job creation incommunities that have been are likely to be hardest hit by a transition away from fossil fuels. It is
important to note, however, that changes in total jobs ignores important regional and field specificconsiderations. For example, a coal mining job is not the same as a job installing solar panels, bothfrom a technical perspective but also considering differences in pay or benefits.
The growth in production and construction from the IRA is also associated with a significant
increase in GDP. We find the IRA could increase GDP by 0.65 to 0.77 percent in 2030.

Change in GDP (%)

1.0%

Percent Change in GDP

0.9%

High,
0.77%

0.8%
0.7%

Moderate,
0.65%

0.6%
0.5%

Low,
0.65%

0.4%

0.3%
0.2%
0.1%
0.0%
2020

2025

2030

Figure 7: Percent Change in Annual GDP by Scenario through 2030

Deployment of Capital and Spending on Energy

The IRA would significantly increase clean energy technology deployment and associated capitaloutlays. Our modeling finds the IRA could result in up to $180 billion a year in additional capital
equipment investment through 2030, as shown in Figure 8.
The shift to clean electricity, electrified technologies, and more efficient equipment results in largesavings on energy expenditures, which grow over time. By 2030, our modeling finds reductions inannual spending on energy of $79 to $85 billion. These savings persist even after capital equipment
spending returns to normal levels.

17

EI | MODELING THE INFLATION REDUCTION ACT USING THE ENERGY POLICY SIMULATOR

Billion 2020 Dollars

Total Change In Capital Expenditures
200
180
160
140
120
100
80
60
40
20
2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030
Low

Moderate

High

Figure 8: Annual Change in Capital Expenditures by Scenario

Total Change in Fuel Expenditures
Billion 2020 Dollars

20

(20)
(40)
(60)
(80)
(100)
2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030
Low

Moderate

High

Figure 9: Annual Change in Energy Expenditures by Scenario

These savings affect household energy spending. We find savings of $79 to 80 per household peryear by 2030 due to the IRA. These savings would grow in future years as stock turnover of building
equipment and vehicles would reduce spending on building fuels and transportation fuels.

18

EI | MODELING THE INFLATION REDUCTION ACT USING THE ENERGY POLICY SIMULATOR

Energy Savings per Household in 2030
$90
$80

$79

$80

$80

Low

Moderate

High

$70

2020 dollars

$60
$50
$40
$30
$20

$10
$-

Figure 10: Annual Household Energy Savings in 2030 by Scenario

METHOD
Energy Innovation used the U.S. EPS to estimate the net effects of IRA provisions on U.S. GHG
emissions through 2030. For this analysis all emissions are reported in AR4 GWP-100 values. Our
methane values are tied to the EPA’s inventory. 8
Many studies have shown the EPA’s inventory undercounts methane leakage and associatedmethane emissions. Methane is a potent GHG that has a 100-year global warming potential using
AR4 values 25 times that of CO2, and a 20-year global warming potential using AR4 values 84 times
that of CO2. These are important considerations when evaluating policy impacts and theirimportance for limiting global warming. In this instance, we chose to use the same factors as the
EPA to ensure comparability to the inventory, to other modeling studies, and to international
convention around emissions reporting and tracking. We nevertheless acknowledge that using
more updated values or assessing impacts using GWP20 values would change the estimatedreductions of emissions in CO2e.
For this analysis, Energy Innovation used a customized model built on EPS version 3.4.0.1 toaccurately model the IRA’s provisions, though these scenarios are not yet available online. Thisversion of the model is built on top of version 3.4.0.1, but includes customizations to be able to19

EI | MODELING THE INFLATION REDUCTION ACT USING THE ENERGY POLICY SIMULATOR

accurately model the provisions of the IRA. For example, we added multiple components to track
the government spending on various provisions.
Our BAU Scenario relies heavily on the EIA’s Annual Energy Outlook 2022 Low Economic Growth
Scenario for energy demand in buildings and industry, transportation service demand, and fuelprices. It is also adjusted to reflect the current high energy price situation due to the Russian
invasion of Ukraine and supply chain constraints. The 2022 Outlook’s Low Economic Growth
Scenario closely aligns with the latest projected GDP trajectory from the Congressional Budget
Office. Because the EPS calculates the impacts of policies relative to a single BAU case, the rangeof impacts in our Low, Moderate, and High Scenarios reflects uncertainty in policy efficacy andimplementation rather than uncertainty about a business-as-usual future (e.g., fuel and technology
prices, energy service demand).
To estimate IRA provision impacts, we carefully reviewed each section to develop a set of policy
assumptions for each provision. In many cases we developed a range of potential impacts to reflect
uncertainty around policy efficacy. For example, we varied the share of clean electricity projects
that qualified for bonus credits, with our Low Scenario reflecting more pessimistic assumptions andour High Scenario reflecting more optimistic assumptions.
A full, section-by-section description of our modeling methodology is included in Appendix A.
The list of provisions we modeled is included in Table 8 below:
Title I, Finance•

Section 13101, Extension and Modification of Credit for Electricity Produced from Certain Renewable
Resources•

Section 13102, Extension and Modification of Energy Credit•

Section 13103, Increase in Energy Credit for Solar and Wind Facilities Placed in Service Connection with
Low Income Communities

20•

Section 13104, Extension and Modification of Credit for Carbon Oxide Sequestration•

Section 13105, Zero-Emissions Nuclear Power Production Credit•

Section 13204, Clean Hydrogen•

Section 13301, Extensions, Increase, and Modifications of Nonbusiness Energy Property Credit•

Section 13302, Residential Clean Energy Credit•

Section 13303, Energy Efficient Commercial Buildings Deduction•

Section 13304, Extensions, Increase, and Modifications of New Energy Efficient Home Credit•

Section 13401, Clean Vehicle Credit•

Section 13403, Qualified Commercial Clean Vehicles•

Section 13404, Alternative Fuel Refueling Property Credit•

Section 13501, Extension of the Advanced Energy Project Credit•

Section 13502, Advanced Manufacturing Production Credit•

Section 13702, Clean Electricity Investment Credit

EI | MODELING THE INFLATION REDUCTION ACT USING THE ENERGY POLICY SIMULATOR

Title II, Agriculture•

Section 21001, Additional Agricultural Conservation Investments•

Section 21002, Conservation Technical Assistance•

Section 22001, Funding for Electric Loans for Renewable Energy•

Section 22002, Rural Energy for America Program•

Section 22004, USDA Assistance for Rural Electric Cooperatives•

Section 23002, Non-Federal Land Forest Restoration and Fuels Reduction Projects and Research•

Section 23003, State and Private Forestry Conservation Programs

Title III, Banking•

Section 30002, Improving Energy Efficiency of Water Efficiency or Climate Resilience of Affordable Housing

Title V, Energy and Natural Resources•

Section 50121, Home Energy Performance-Based, Whole-House Rebates•

Section 50122, High-Efficiency Electric Home Rebate Program•

Section 50131, Assistance for Latest and Zero Building Energy Code Adoption•

Section 50144, Energy Infrastructure Reinvestment Financing•

Section 50151, Transmission Facility Financing•

Section 50152, Grants to Facilitate the Siting of Interstate Electricity Transmission Lines•

Section 50161, Advanced Industrial Facilities Deployment Program•

Section 50263, Royalties on All Extracted Methane•

Section 50264, Lease Sales Under the 2017-2022 Outer Continental Shelf Leasing Program•

Section 50265, Ensuring Energy Security

Title VI, Environment and Public Works•

Section 60101, Clean Heavy-Duty Vehicles•

Section 60103, Greenhouse Gas Reduction Fund•

Section 60112, Environmental Product Declaration Assistance•

Section 60113, Methane Emissions Reduction Program•

Section 60116, Low-Embodied Carbon Labeling for Construction Materials•

Section 60502, Assistance for Federal Buildings•

Section 60503, Use of Low-Carbon Materials•

Section 60506, Low-Carbon Transportation Materials Grants

Title VII, Homeland Security and Government Affairs•

Section 70002, USPS Clean Fleets

Table 8: Provisions Included in Modeling

CONCLUSION

21

EI | MODELING THE INFLATION REDUCTION ACT USING THE ENERGY POLICY SIMULATORThe IRA could reduce emissions an estimated 37 to 43 percent below 2005 levels by 2030. In otherwords, the IRA could enable the U.S. to close 49 to 71 percent of the emissions gap between BAU
and the U.S. NDC in 2030. Realistic executive, state and local actions could lead the U.S. to achieve
its 2030 NDC commitment.
The bill’s provisions also greatly encourage domestic manufacturing of the clean energy
technologies that need to be deployed at a rapid rate across the economy, helping to onshore jobs.
Hence, the IRA’s climate benefits provide substantial economic and public health co-benefits,
generating up to 1.3 million jobs in 2030 and avoiding up to 4,500 deaths in 2030. Avoided deaths
and public health benefits disproportionately benefit the low-income communities of color thathave borne the brunt of fossil fuel pollution.
In summary, the IRA is the largest and most consequential U.S. climate legislation in history andsets the U.S. up to achieve deep emissions reductions by 2030 and beyond.

22

EI | MODELING THE INFLATION REDUCTION ACT USING THE ENERGY POLICY SIMULATORAPPENDIX A: SECTION-BY-SECTION MODELING METHODOLOGY
Section

Name

Methodology

Title I: Committee on Finance

13101

13102

Extension andFirst, we calculate the percentage of new plants that will
Modification of Credit for qualify for a) the prevailing wage and apprenticeshipElectricity Produced from requirements and b) the domestic content requirements.
Certain Renewable
For part a, we only calculate the share of plants that would
Resources
meet the apprenticeship requirement and assume all theseplants would also meet the prevailing wage requirement(varying assumptions on the share of qualifying plants
across scenarios based on data for the constructionindustry from American Clean Power’s Labor Supply
Report9). For part b, we calculate the domestic content
share for each power plant type. For onshore and offshorewind, we assume 100 percent of plants qualify for thebonus credit, based on an external analysis10 which lists
domestic content shares for various wind components atwell over the 55 percent domestic content requirement.
For solar, we use the cited domestic content values forcells, modules, and inverters to calculate a weighted
domestic content share, given the percentage of solar
capital costs by component from the JEDI model.11 For the
Low Scenario, we assume the share of domestic content for
Extension andsolar photovoltaics (PV) remains constant. For the High
Modification of Energy
Scenario, we assume domestic content can gradually
Creditincrease to meet the 55 percent requirement by 2026. For
the Moderate Scenario, we assume an average of the Low
and High Scenarios.
Next, we add in the energy community bonus, assumingthat 25 percent, 50 percent, and 75 percent of capacity
additions qualify in our Low, Moderate, and High Scenarios,
respectively. We then calculate what the total credit value
would be for each technology in each year for both the ITC
and the PTC. Here, we assume credits start in 2023 and run
at their full value through 2032. For the PTC values, we also
adjust the calculated credit by the present value over 10
years divided by the present value over the plant lifetime,
because the PTC is only available for the first 10 years of a

23

EI | MODELING THE INFLATION REDUCTION ACT USING THE ENERGY POLICY SIMULATOR

plant's lifetime. Finally, we apply a transferability multiplierof 10 percent, 7.5 percent, or 5 percent (in the Low,
Moderate, and High Scenarios, respectively). This value
reduces the credit value available to developers to accountfor the fact tax credits are transferable.
We take the incremental clean electricity share due to tax
credits from ReEDS runs that consider a tax credit value of$25. 12 We adjust the incremental share of clean electricity
based on our calculated value for tax credits, which
incorporates bonus multipliers and a transferability penalty.
This is done using a linear scaling factor, which we
determined was a reasonable approach based on priorcomparison of the Princeton REPEAT model electricity
outputs at different tax credit levels. We assume that thereported 2030 values from ReEDS are achieved in 2031, as
the ReEDS runs were completed in 2021 before the timelineof the tax credits was shifted forward one year.
We limit our analysis to onshore and offshore wind, solarPV, solar thermal, geothermal, municipal solid waste, andbattery storage. We do not model credits for qualifyinghydro or biogas plants. For solar PV, we calculate a levelized
cost of energy for both the ITC and PTC settings todetermine whether that resource elects the ITC or the PTC
in each year. Because the EPS does not track battery
storage as a power plant type, we rely on the external
ReEDS runs for the amount of incremental battery storage
added to the grid.

24

13103

Increase in Energy Credit We assume an additional 1.8 GW of distributed solar per
for Solar and Wind
year as part of qualified low-income residential building
Facilities Placed in Service projects, which is the annual cap specified in the bill text.
in Connection with LowIncome Communities

13104

We use Rhodium’s IRA analysis that evaluated extended
Extension and
45Q tax credits to model the potential in industry.13 We do
Modification of Credit for
not assume any electricity sector CCS under the 45Q tax
Carbon Oxide
credits given how cheap other clean electricity sources will
Sequestration
be with the clean electricity tax credits.

EI | MODELING THE INFLATION REDUCTION ACT USING THE ENERGY POLICY SIMULATORWe use the incremental additions in the “High emissions,”“Central,” and “Low emissions” cases as the inputs for ourLow, Moderate, and High Scenarios. We assume credits will
run at their full value through 2032. Because our BAU caseaccounts for currently planned projects through 2027 andnew plants will need time for permitting and construction,
we assume a 4-year delay before additional CCS capacity
begins to come online. Therefore, we phase in Rhodium’s
projections between 2027 and 2030. Because Rhodium
reports capture capacity rather than tons CO2 captured, we
also apply a calculated capacity factor for CCS equipment.

25

13105

The nuclear PTC runs through 2032, and we assume thecredits are sufficient to keep all existing nuclear without
planned retirement dates online through that time. To
Zero-Emission Nuclear
determine the weighted average credit value, we ran side
Power Production Credit
cases to determine that between $5.10 to $9.50 per MWh
was needed between 2024 and 2032, depending on the
scenario.

13204

Clean Hydrogen

We assume varying levels of displacement of gray hydrogenacross scenarios with electrolytic hydrogen. In the Low
scenario, we assume only offsite produced H2 is replaced,
which only affects part of ammonia and part of refineries. In
the Moderate Scenario, we assume all non-by product H2 isreplaced, covering ammonia and all non-by product refinery
demand. In the High Scenario, we assume iron and steel DRI
production moves to 30 percent hydrogen feedstock blend.
In all cases, the required clean electricity amount is added
to the power sector, which builds incremental capacity tomeet the new demand for green H2.

13301

We reference American Council for an Energy-Efficient
Economy (ACEEE) research on the number of heatincremental heat pumps that would be deployed in a
Extensions, Increase, andscenario with unconstrained rebates for heat pumps.14 We
Modifications oflinearly adjust that value by the ratio of the $2,000
Nonbusiness Energy
incentive cap for heat pumps in this section to ACEEE's
Property Credit (25C)
assumed incentive value. We then calculate the averagenatural gas consumption per unit using data from the EIA's
Annual Energy Outlook15 and apply these savings in the

EI | MODELING THE INFLATION REDUCTION ACT USING THE ENERGY POLICY SIMULATOR

model. Finally, we add the incremental electricity demand(calculated using the average efficiency of heat pumps).
13302

We directly implement ACEEE research on expected natural
Residential Clean Energy gas and electricity savings from this program.16 We also
Credit (25D)assume 1 GW of distributed solar is added per year basedon these credits, based on analysis from RMI.17

13303

Energy Efficient
Commercial Buildings
Deduction (179D)

13304

Extensions, Increase, and We directly implement ACEEE research on expected natural
Modifications of New
gas and electricity savings from this program.19
Energy Efficient Home
Credit (45L)

We directly implement ACEEE research on expected natural
gas and electricity savings from this program.18

We calculate a weighted average tax credit in each year
based on the fraction of vehicles that may be eligible for thetax credits and the estimated value of the credits for thosethat do qualify.

13401

Clean Vehicle Credit

The new clean vehicle tax credit is bifurcated into a $3,750
credit for US battery manufacturing and a $3,750 credit formeeting certain critical minerals thresholds. Additionally,
there is a new adjusted gross income cap of $150,000
individual/$300,000 household, MSRP caps of $55,000 forcars and $80,000 for all other vehicles, and a requirementthat final assembly occur in North America. Lastly, there is aprovision that disqualifies any vehicle using battery
components from entities of concern starting in 2024, or
minerals produced or processed by an entity of concern
starting in 2025. The credits are not direct pay, but they aretransferable, including to the dealer.
For the domestic battery component, based on projected
North American battery projects, we do not assume U.S.
battery manufacturing capacity is a constraint, which makes
the full credit available to vehicles that qualify as clean
vehicles.20
For the critical minerals component, we adjust the $3,750
bonus credit based on the share of vehicle sales that could
meet the requirements for critical minerals sourced

26

EI | MODELING THE INFLATION REDUCTION ACT USING THE ENERGY POLICY SIMULATOR

domestically or from nations with a free trade agreement.
We use data from the U.S. Geological Survey to calculate
the share of critical minerals demand that is currently
sourced from qualifying nations.21 In the Low Scenario, we
assume this remains constant, whereas the High Scenario
assumes the share gradually increases to 80 percent, as isrequired by the IRA for the full credit, by 2032. The
Moderate Scenario takes the average of the Low and High.
The two above pieces determine the total credit available
for vehicles that qualify for the credits. We then develop aweighted average credit for all EVs by adjusting the average
credit amount to exclude the percentage of vehicles that do
not satisfy the restrictions around materials from entities ofconcern. In the Low scenario, we assume no vehicles canmeet this requirement, i.e. the effective credit value is $0,
whereas in the High scenario we assume the fraction ofqualifying vehicles ramps up from 0 percent in 2024 to 100
percent in 2032. The Moderate Scenario takes the averageof the Low and High. This set of constraints are the mostimportant determinant of the average incentive available.
We also account for the share of electric vehicles with aretail price below the stated MSRP caps (we estimate this at
87 percent of vehicle sales) and for the share of all EV
buyers who would be eligible for the tax credit given theincome distribution of EV buyers, using publicly available
Census data and research from the Fuels Institute. 22

27

For commercial vehicle credits, we find that the credit caps
of $7,500 for vehicles under 14,000 pounds or $40,000 for
vehicles over 14,000 pounds apply in all years. We apply thecredit to all new sales of commercial trucks, using aweighted average credit value for our freight light-duty
vehicle (LDV) category which covers both light- andmedium-duty trucks. We also apply the credit to a fractionof buses, excluding buses purchased by the government.

13403

Qualified Commercial
Clean Vehicles

13404

We calculate an incremental number of chargers deployed
Alternative Fuel Refueling based on funding and the weighted average charger cost in
Property Credit
the EPS. We take estimated funding from the released Joint
Committee on Taxation scores23 and assume 80 percent of

EI | MODELING THE INFLATION REDUCTION ACT USING THE ENERGY POLICY SIMULATOR

the spending is directed toward public chargers. We do not
attempt to model the effects of private chargers. The
number of additional chargers is then fed into our model'scalculations for the shadow price used to represent
range/charging anxiety for passenger LDV owners, which ispartially determined by the ratio of charging infrastructure
to gasoline pumps. This adjustment helps to drop the
shadow price in response to additional infrastructure andincrease consumer adoption of EVs.
13501

Extension of theSee methodology for Section 13502.
Advanced Energy Project
CreditWe use the sector breakdowns from a Data for Progress
analysis.24 We leverage the tax credits into total increased
output of industries. Next, we use the model's 'buy inregion' policy to increase outputs of selected industries by
the correct totals. We assume the stimulus results inpermanent job creation, even after the tax credits expire.

13502

We also apply a credit of $35/kWh for battery cells and$10/kWh for assembly for onroad vehicle batteries. We use
several external sources to determine the average kWhAdvanced Manufacturing battery capacity for each vehicle type.25,26,27,28 We thenProduction Credit
apply a multiplier ranging from 0 to 25 percent to accountfor the fact that the credits paid to producers may not bepassed on to consumers, or if the pass-through amountwould likely be limited, based on conversations withindustry experts. We scale these multipliers in so that the
maximum value is reached in 2032.
Finally, we assume the $3 billion set aside for emissions
reductions is used for efficiency. See methodology for
Section 50161 for a full description of how we modeled
industrial efficiency spending.

13701

Clean Electricity
Production Credit

See methodology for Sections 13101-13102.

13702

Clean Electricity
Investment Credit

See methodology for Sections 13101-13102.

Title II: Committee on Agriculture, Nutrition, and Forestry

28

EI | MODELING THE INFLATION REDUCTION ACT USING THE ENERGY POLICY SIMULATOR

Additional Agricultural
Conservation
Investments

The EPS includes marginal abatement cost curves for
agricultural practices that specify emissions abatementlevels at different cost tiers. To model 21001, we computethe reductions using these curves such that the total spend
equals the funding in the IRA. This is done by adjusting themodel's “crop and rice measures,” “livestock measures,”and “improved soil measures” levers so that cumulative
spending matches the total funding in this section.

21002

Conservation Technical
AssistanceOur approach is to adjust the stringency of the model's“crop and rice measures,” “livestock measures,” and“improved soil measures” levers so that cumulative
spending matches the total funding in this Section. We
exclude funding for the emissions quantification program oradministrative costs.

22001

We combine Sections 22001 and 22002 (Forgivable loans
for Renewable Energy and the Rural Energy for America
Funding for Electric Loans Program). We take historical energy spend by the Ruralfor Renewable Energy
Utilities Service and apportion the new funding as in the(Sec. 317)
past.29 We allocate funding for energy efficiency tobuildings, and allocate all the remaining funding for clean
electricity sources to increase the share of clean electricity.

22002

Rural Energy for America See methodology for Section 22001.
Program

22004

We assume a $500/kW incentive is enough to retire all
majority owned co-op coal plants. We get data on co-op
ownership shares from EIA Form 860.30 We exclude
industrial CHP and non-CHP, because those facilities havedifferent economics and offtakers (available on request; file
USDA Assistance for Rural is large). Data on outstanding coal debt is taken from public
Electric Cooperatives
sources. We then estimate the cost based on the minimumof remaining coal debt or max of the policy setting and theremaining coal MW. For utilities missing data, we use thefull debt relief to be conservative. We allocate thereductions between 2023 and 2030. This results in roughly
20 GW of incremental coal retirements.

23001

National Forest System
Restoration and Fuels
Reduction Projects

21001

29

We sum forestry funding that aligns with the scope of the
EPS land use, land use change, and forestry (LULUCF)
sector, then assign it to either the model's “forest
management” or “afforestation and reforestation” levers.

EI | MODELING THE INFLATION REDUCTION ACT USING THE ENERGY POLICY SIMULATORWe then find the policy setting that matches total
government spend over the period of 2023-2031. For
Section 23001, we only include the protection of oldgrowth forests funding and exclude hazardous fuels
reduction and vegetation management, which are outside
the scope of the model.
23002

23003

Non-Federal Land Forest
Restoration and Fuels
Reduction Projects andResearch

We sum forestry funding that aligns with the scope of the
EPS LULUCF sector, then assign it to either the model's“forest management” or “afforestation and reforestation”
levers. We then find the policy setting that matches total
State and Private Forestry government spend over the period between 2023 andConservation Programs 2031. For Sections 23002 and 23003, we include all funding.

Title III: Committee on Banking, Housing, and Urban Affairs

30002

Improving Energy
Efficiency or Water
Efficiency or Climate
Resilience of Affordable
Housing

We directly implement ACEEE research on expected natural
gas and electricity savings from this program, scaling by theratio of actual funding to ACEEE's funding assumptions andadjusting so that total spend occurs across 2023-2031.31

Title V: Committee on Energy and Natural ResourcesHome Energy
Performance-Based,
Whole-House Rebates

We directly implement ACEEE research on expected natural
gas and electricity savings from this program, scaling by theratio of actual funding to ACEEE's funding assumptions andadjusting so that total spend occurs across 2023-2031.32

50122

High-Efficiency ElectricHome Rebate Program

We directly implement ACEEE research on expected natural
gas and electricity savings from this program, scaling by theratio of actual funding to ACEEE's funding assumptions andadjusting so that total spend occurs across the period
between 2023 and 2031.33

50131

We use a Pacific Northwest National Laboratory (PNNL)
report that evaluates the prospective impacts of nationalmodel building energy codes from 2010 through 2040. 34
The report identifies annual emissions reductions,
Assistance for Latest andelectricity, gas, and fuel oil savings possible by 2030. We
Zero Building Energy
assume funding can enable 25 percent, 50 percent, or 75
Code Adoption
percent of these savings in commercial and residentialbuildings in our Low, Moderate, and High Scenarios,
respectively. The PNNL report uses 2010 as a baseline. We
assume reported savings grow linearly between 2010 and

50121

30

EI | MODELING THE INFLATION REDUCTION ACT USING THE ENERGY POLICY SIMULATOR

2030, meaning that at year 12, 60 percent of the savings
have already been realized. Therefore, adjust total savings
to only account for 2023 to 2030.

31

50144

Energy Infrastructure
Reinvestment Financing

50151

Transmission Facility
Financing

50152

Grants to Facilitate theSiting of InterstateElectricity Transmission
Lines

The 1706 program provides allocates $5 billion to DOE for
up to $250 billion in guaranteed loans for reinvestment incommunities with retiring energy infrastructure, including
refinancing. Historically, the DOE’s Loan Program Office has
raised $20 billion in private capital for every $30 billion in
public loans.35 The potential investment is then about $417
billion. We assume this funding is used to replace retiring
fossil fuel assets with clean electricity and calculate theincremental clean share that would result from replacing
retiring fossil assets with clean electricity. We assume 25
percent, 50 percent, and 75 percent coverage in each of
our scenarios, to reflect varying ranges of market coverage,
friction in the system, and overlap with other tax incentives.
Though the program says loans must be made by 2026, weassume the build out of the clean electricity continues
through 2032, i.e. loans are made well in advance ofconstruction.
We use a report by Americans for a Clean Energy Grid andGrid Strategies LLC that reports the estimated impact andcosts of building 22 shovel ready transmission projects tofind an average cost per MW-mile.36 We then calculate
additional transmission based on funding levels and aleverage ratio of 2.
This program has a maximum government spend of 50
percent of total project costs and $6 billion in funding. In
the Low scenario, we assume 50 percent private/public. In
the Moderate we assume 40 percent public/60 percent
private. In the High scenario, we assume 30 percent public,
70 percent private. We also add in $3 billion from the 48C
program for industry using the same leverage ratios. We
then use the EPS to identify the incremental investment inenergy efficiency that these fundings levels correspond to.

50161

Advanced Industrial
Facilities Deployment
Program

50263

The methane royalty rate for production of natural gas isRoyalties on All Extracted extended to apply to all produced gas, including gas
Methaneconsumed onsite or vented, flared, or leaked. We apply thisin the model as an additional fuel tax on leaked methane.

EI | MODELING THE INFLATION REDUCTION ACT USING THE ENERGY POLICY SIMULATOR

50264

Lease Sales Under The
2017-2022 Outer
Continental Shelf Leasing Please see Appendix B for a full description of our
methodology.
Program

50265

Ensuring Energy Security

Title VI: Committee on Environment and Public Works

60101

Clean Heavy-Duty
Vehicles

We take total funding for Clean Heavy-Duty Vehicles andassign it to buses, using the model's EV subsidy lever to findthe incremental incentive needed to match total
government spend.
This section includes $27 billion in passthrough to the EPA
for non-profit institutions to assist in financing clean energy.
$7 billion of this is carved out for zero-emission
technologies in low-income and disadvantaged
communities, which we apply to distributed solar.

60103

32

The language targets funding at projects that have limited
financing options. Historically, investments by green banks(e.g. NY and CT) vary by project type, but are mostly
allocated to building efficiency/retrofits androoftop/community solar. Given the many other incentives
and programs in the IRA, we assume that the remaining $20
billion in this program would be directed primarily toGreenhouse Gas
buildings, where funding is more limited. This most closely
Reduction Fundfollows the model of the CT Green Bank, which has a heavy(Technology Accelerator) emphasis on C-PACE and multifamily. We use the Coalition
for Green Capital’s (CGC) estimate of leverage to estimate
the net impact of an initial capitalization at $20 billion.37
CGC estimates that 3.4 dollars of investment per one dollarof capitalization is possible, with revenue recycling every
seven or so years. We therefore assume a leverage ratio of
3.4 meaning $20 billion in initial capitalization could yield$68 billion in total capital investment by 2031. Because
there is separate carve out for grants for distributed solar
within the fund, we don't consider those projects here. We
assign 100 percent of the green bank investment tocommercial building retrofits, in line with previous
experience and missing areas of funding under the IRA. For
our scenarios, we use the guidance on the outlays

EI | MODELING THE INFLATION REDUCTION ACT USING THE ENERGY POLICY SIMULATOR

estimated by the Congressional Budget Office (CBO).38 The
Low scenario discounts the spending by the ratio CBO
estimates, the Moderate Scenario splits that and the total
funding available, and the High Scenario takes the fullamount on the table. Using the CBO score as guidance, we
assume the program takes five years to scale up.
The distributed solar calculations use the same approach ofadjusting by CBO estimates and a 3.4 leverage ratio above,
then deploy distributed solar based on the total funding
available and the average cost per watt.
We rely on research from BlueGreen Alliance reporting a
range of emissions outcomes and incremental costs for
cement and iron and steel as a result of these initiatives,
scaling the impacts by total funding available and market
coverage. For example, roughly 50 percent of concrete
consumption in the U.S. is for federal projects, but only 5
percent of iron and steel consumption is for federal
projects.39,40 Our estimates include ranges for the combined
impact from both procurement pilots and environmental
product declaration (EPD) programs. We do not include
spillover effects.

60112

Environmental ProductDeclaration AssistanceFor concrete, it is assumed that the primary way of lower
emissions is through different mixing ratios. For example,
existing EPDs suggest significant reductions are possible
through using less cement in ready-mixed concrete.
Because the concrete and cement sectors are the same in
the EPS, this is approximated as a reduction in energy
consumption and process emissions rather than a reductionin product demand. Some additional reductions areachieved through fuel switching (coal to gas) and cementclinker substitution in the cement sector.
For iron and steel, the primary pathway for compliance isthrough procurement of clean energy to supply electric arc
furnace – direct reduced iron (EAF-DRI) facilities. Beyond
that, there could be a switch from blast furnace—basic
oxygen furnace (BF-BOF) to EAF-DRI technology, but
without additional funding mechanisms, that is less likely.

33

EI | MODELING THE INFLATION REDUCTION ACT USING THE ENERGY POLICY SIMULATOR

In the Low and Moderate Scenarios, we assume reductions
are met with procurement of clean energy and in High we
add in technology shifting
Methane Emissions
60113(a)Reduction Program& (b)(Spending)Methane Emissions
60113(e) Reduction Program(Revenue)

60116

Only facilities that report via EPA's Greenhouse Gas
Reporting Program are subject to the methane fee. We use
EPA's FLIGHT tool to find these covered emissions,41 thenuse external analysis42 to develop an estimate of thepercentage of covered emissions that fall below thissection's leakage thresholds (we find 78 percent of covered
emissions are subject to the fee). This results in a total of 55
MMT methane emissions covered by the program.
We then use EPA's Non-CO2 Greenhouse Gas Emission
Projections & Mitigation report data 43 (scaled to align with
the EPA's latest Greenhouse Gas Inventory) 44 to apply allabatement potential at or below the fee amount of $60/ton
to the covered emissions, i.e. only a fraction of the 55 MMTof covered emissions are reduced.

Low-Embodied Carbon
See methodology for Section 60112.
Labeling for Construction
Materials
We take a PNNL study on efficiency potential in federalbuildings, which gives the average cost per square foot andkBTU per square foot for efficiency measures.45 This allows
us to determine the BTU savings from federal buildings
investments.

60502

Assistance for Federal
Buildings

60503

Use of Low-Carbon
Materials

60506

Low-Carbon
See methodology for Section 60112.
Transportation Materials
GrantsSee methodology for Section 60112.

Title VII: Committee on Homeland Security and Governmental Affairs

70002

34

USPS Clean Fleets

We take total funding for USPS Clean Fleets and assign it tofreight LDVs, using the model's EV subsidy lever to find theincremental incentive needed to match total government
spend.

EI | MODELING THE INFLATION REDUCTION ACT USING THE ENERGY POLICY SIMULATORAPPENDIX B: DETAILED OIL AND GAS LEASE PROVISION METHODOLOGY
To estimate the change in economy-wide GHG emissions from increased oil and gas lease auctions,
we estimated the difference in oil and gas production from these provisions. We then fed theseproduction changes into the EPS to forecast associated changes in emissions from extraction,
processing, transmission, and distribution. These changes include increased, incremental energy
use in the oil and gas sector and process emissions from the oil and gas sector. We developed priceelasticities from the EIA to estimate changes in fuel prices and to estimate change in energy
demand and emissions. Finally, we estimated international emissions changes using data from apaper by Brian Prest at Resources the Future.46 A detailed description of our approach is includedin this Appendix.
Reinstated and New Oil and Gas Lease Auction Provisions in the IRA

The IRA requires annual oil and gas lease auctions on federal land as a requirement for federal landleases for renewable energy. The IRA includes the following requirements:oReinstatement of the following lease auctions that were cancelled/expired: 257, 258,
259, 261
o Offshore and onshore renewable leasing tied to oil and gas lease auctions:o A new offshore wind lease cannot be issued unless, in the prior year, thegovernment held an offshore lease auction (called a “lease sale” in the IRA) for oil
and gas of at least 60 million acreso A new onshore lease for renewables cannot be issued unless, in the prior year
the government held an onshore lease auction for oil and gas for at least 2
million acres or 50 percent of the acreage with expressed interest
o For both onshore and offshore lease auctions, the auctions must result in at least
one lease issuance if there are any “acceptable bids”
Functionally, these provisions mean that in order to lease public land or waters for renewables
development, government must complete lease auctions of at least 60 million acres per year foroffshore and 2 million acres per year for onshore which result in the issuance of leases if there
are any acceptable bids.
Scenarios

We developed three scenarios to determine the incremental impact of expanded oil and gas drillingunder the proposed IRA above business-as-usual. These are coupled with two variations on
assumed international leakage.
•

35

Scenario 1: BAU Low Oil and Gas Development: Assumes in the BAU Scenario, 2022 rateof oil and gas leasing under the Biden administration continues through 2050. Assume no
impact on federal leasing for renewable energy production.

EI | MODELING THE INFLATION REDUCTION ACT USING THE ENERGY POLICY SIMULATOR•Scenario 2: BAU No Oil and Gas Development: Assumes there is no new federal leasing of
onshore and offshore land for oil and gas development.

•

Scenario 3: IRA Oil and Gas Auctions: Assumes four cancelled 2022 offshore leaseauctions are reinstated in 2022, BOEM’s 5-year plan is implemented through 2028,
incremental additional offshore acreage is offered to meet 60-million-acre program goal
between 2023 and 2050. Assume 2 million acres are offered for lease annually foronshore oil and gas development in 2022 through 2050.

•

International leakage: Uses upper and lower bound estimates of rest-of-world
incremental supply and consumption based on data from Brian Prest’s research at RFF. 47

Methodology

Our methodology starts with the acres offered at auction from our scenarios. Then we convert
these to estimated lease sales. To determine how much land is leased at auction, we used historical
data covering multiple administrations. Notably, the share of land that is leased at auction foroffshore auctions is very low, around two percent. For onshore auctions, approximately 30 percent
of acreage offered is leased.
After determining the amount of land that is leased at auction, we produce drilling profiles perunit land area. For offshore, we used BOEM data on the timeline of well completions for a given
area of development. Generally speaking, new drilled wells are spread out over about 30 years,
peaking about halfway through and following a fairly linear trajectory up to and after peaking. We
take the average of the Low and High Production Scenarios from the figure below. This results ina production profile of about 50 years.48

Figure 11: BOEM Well Drilling Profile for Offshore Leases.

36

EI | MODELING THE INFLATION REDUCTION ACT USING THE ENERGY POLICY SIMULATORFor onshore production we could not find data on drilling and production profiles, and we assume
land goes into production at average production to area values once the land is leased at auction.
Onshore production tends to be much smaller than offshore production.
We build on the drilling profiles for offshore land by then applying production profiles to the wells
that reflect the varying amount of product produced over the lifetime of the well. For example,
around 50 percent of a well’s total product is produced in the first year after it is drilled, withdiminishing output after as shown in Figure 12.

Percent of Total Product Produced

Offshore well production depletion curve
60.00%
50.00%
40.00%
30.00%
20.00%
10.00%
0.00%

year 0 year 1 year 2 year 3 year 4 year 5 year 6 year 7 year 8 year 9year 10

Figure 12: Offshore Well Production Profile

Data from the Prest paper concludes that about 30 percent of increased production on public lands
is offset by decreases on private land, so we reduce our estimated production values by 30 percent.
With production increases estimated, we then calculate the change in U.S. fuel prices that result
from the incremental production. To do this, we developed price elasticities of supply using datafrom the U.S. EIA’s Annual Energy Outlook 2022.
We input the increased production values and the estimated annual price changes into the EPS tosimulate changes in production, processing, transmission, and distribution emissions as well aschanges in consumption that result from lower prices. The resulting changes in emissions reflect
the total change in domestic emissions from increased oil and gas production and changes to
consumption from the incremental production.
Finally, we estimate rest-of-world emissions from the incremental supply using data from the Prestpaper. We assume production by permit using the 2017-2022 and 2023-2028 BOEM reports.49 For
future wells where production values are unknown, we use an average production value per permit
from the 2023-2028 report. 50

37

EI | MODELING THE INFLATION REDUCTION ACT USING THE ENERGY POLICY SIMULATOR

Findings

Based on the methodology above, we find U.S. production changes of 1.4 to 2.4 percent for crude
oil and 0.5 to 0.6 percent for natural gas in 2030.
These production changes result in price decreases of 1.02 to 1.72 percent for crude oil andpetroleum products and 1.72 to 2.41 percent for natural gas in 2030.
Rest-of-world emissions range from 14 to 36 MMT CO2e in 2030
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40

EI | MODELING THE INFLATION REDUCTION ACT USING THE ENERGY POLICY SIMULATOR