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:
    Nature Energy | Volume 8 | June 2023 | 597–609
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nature energy
https://doi.org/10.1038/s41560-023-01259-y
Article
Equitable low-carbon transition pathways
for California’s oil extraction
Ranjit Deshmukh
  1,2,3,12
, Paige Weber
  2,4,12
, Olivier Deschenes
  2,5,6,
Danae Hernandez-Cortes
  2,7,8, Tia Kordell
  1,2,9, Ruiwen Lee1,2,9,
Christopher Malloy
  2,5, Tracey Mangin
  1,2,9, Measrainsey Meng
  2,3,9,
Sandy Sum
  1,2, Vincent Thivierge
  1,2, Anagha Uppal2,10, David W. Lea11
& Kyle C. Meng
  1,2,5,6,12
Oil supply-side policies—setbacks, excise taxes and carbon taxes—are
increasingly considered for decarbonizing the transportation sector.
Understanding not only how such policies reduce oil extraction and
greenhouse gas (GHG) emissions but also which communities receive the
resulting health benefits and labour-market impacts is crucial for designing
effective and equitable decarbonization pathways. Here we combine
an empirical field-level oil-production model, an air pollution model
and an employment model to characterize spatially explicit 2020–2045
decarbonization scenarios from various policies applied to California, a
major oil producer with ambitious decarbonization goals. We find setbacks
generate the largest avoided mortality benefits from reduced air pollution
and the largest lost worker compensation, followed by excise and carbon
taxes. Setbacks also yield the highest share of health benefits and the lowest
share of lost worker compensation borne by disadvantaged communities.
However, currently proposed setbacks may fail to meet California’s GHG
targets, requiring either longer setbacks or additional supply-side policies.
Across many industrialized economies, climate policies are increas-
ingly focused on the transportation sector, which lags behind the
level and pace of decarbonization observed in other sectors. Indeed,
between 2010 and 2019, while non-transportation greenhouse gas
(GHG) emissions have fallen by 6% across Organisation for Eco-
nomic Co-operation and Development countries, GHG emissions
from transportation have risen by 6% (ref. 1). Today, the transporta-
tion sector is responsible for the largest share of GHG emissions
in the United States and the European Union at 28% and 24%,
respectively, and an even larger share in California (40%), the region
of focus in this study1,2.
To date, transportation climate-policy debates have primarily
focused on demand-side policies to reduce fossil fuel consumption,
such as fuel taxes, vehicle fuel-economy standards, low-carbon fuel
standards and electric vehicle subsidies3–9. In recent years, attention
has turned towards supply-side policies that directly reduce fossil fuel
production. These policies can take different forms. Some directly ban
extraction from specific oil fields, such as oil-well setbacks targeted at
Received: 9 August 2022
Accepted: 5 April 2023
Published online: 18 May 2023
 Check for updates
1Bren School of Environmental Science and Management, University of California Santa Barbara, Santa Barbara, CA, USA. 2Environmental Markets Lab
(emLab), University of California Santa Barbara, Santa Barbara, CA, USA. 3Environmental Studies Department, University of California Santa Barbara, Santa
Barbara, CA, USA. 4Department of Economics, University of North Carolina, Chapel Hill, NC, USA. 5Department of Economics, University of California Santa
Barbara, Santa Barbara, CA, USA. 6National Bureau of Economic Research, Cambridge, MA, USA. 7School for the Future of Innovation in Society, Arizona
State University, Tempe, AZ, USA. 8School of Sustainability, Arizona State University, Tempe, AZ, USA. 9Marine Science Institute, University of California
Santa Barbara, Santa Barbara, CA, USA. 10Department of Geography, University of California Santa Barbara, Santa Barbara, CA, USA. 11Department of Earth
Science, University of California Santa Barbara, Santa Barbara, CA, USA. 12These authors contributed equally: Ranjit Deshmukh, Paige Weber, Kyle Meng.
 e-mail: rdeshmukh@ucsb.edu; paigeweber@unc.edu; kmeng@bren.ucsb.edu

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healthcare facilities and playgrounds; (2) an excise tax on each barrel
of crude oil extracted and (3) a carbon tax on GHG emissions from oil
extraction. We find that a setback policy provides greater statewide
health benefits but also larger lost worker compensation compared
with a carbon or excise tax that achieves the same 2045 GHG emissions
target. In general, setback policies also have better equity outcomes
as disadvantaged communities accrue a larger share of health benefits
and a smaller share of loss in worker compensation. By contrast, a
carbon tax imposes the smallest statewide worker compensation loss
among the three policies. Finally, currently proposed setback distances
applied to only new wells will be unable to meet California’s decarboni-
zation goals. To do so requires setbacks with a distance greater than
1 mile, applied to both new and existing wells and/or combined with a
carbon or excise tax.
Crude oil production and GHG emissions
pathways
We develop spatially and temporally explicit pathways that reduce
California’s oil extraction in response to various supply-side interven-
tions—well setbacks, excise tax and carbon tax—between 2020 and
2045. Our approach has two components and is summarized in Fig. 1.
For all oil fields in California (Fig. 1a), we first construct an empirically
estimated model of crude oil-well entry (Fig. 1b), production and exit
at the oil-field level to project how various supply-side policies and
macroeconomic conditions affect oil production across California oil
fields out to 2045 (Methods and Supplementary Notes 8–11, 16 and 17).
In our second step, we insert field-level predictions of oil production
from our empirical model into: (1) an air pollution model, InMAP (Inter-
vention Model for Air Pollution)22, to characterize how air pollution
emissions from oil fields disperse across the state (Fig. 1c,d and Sup-
plementary Note 13) and (2) an employment input–output model,
IMPLAN (Impact Analysis for Planning)23,24, which uses fixed multipli-
ers to quantify local employment changes in the oil-extraction sector
(‘direct’), in sectors that provide inputs to oil extraction (‘indirect’)
and in sectors where these workers spend income (‘induced’) (Fig. 1e
and Supplementary Note 14). Together, these components provide an
empirically based analysis of how supply-side policies could alter not
just oil production across oil fields but also the spatial distribution of
health impacts from air pollution and employment across California.
For well setbacks, we consider three setback distances—1,000 feet,
2,500 feet and 1 mile—which encompass distances currently considered
in policy proposals25–28. To ensure policy comparability, we set excise
taxes as a percentage of oil price fixed across all years and carbon taxes
which increase at an annual rate of 7% to levels that result in the same
2045 statewide GHG emissions as our three setback-distance policies
(Supplementary Note 17). We further consider a fourth excise- and
carbon-tax level that achieves a 90% GHG emissions reduction by 2045
compared with 2019 levels, inline with California’s target for in-state
finished-fuel demand2.
Each combination of policy intervention—setbacks, excise tax
and carbon tax—and the 2045 annual GHG emissions target result in
a unique spatial and temporal pattern of oil production, benefits and
costs. We model these patterns across California for the 2020–2045
period, focusing on avoided mortality due to reduced PM2.5 emissions
and avoided global climate damages from reduced GHG emissions
on the benefits side and lost earnings from the oil-extraction sector
on the cost side. We analyse these policy scenarios using a common
benchmark projection of global oil prices out to 2045 (US Energy
Information Administration’s (EIA) reference oil-price projection29).
Sensitivity analysis results using higher and lower projected oil prices
are shown in the Supplementary Information.
California’s oil production peaked in 1985 and has been declining
since then30. Our projection of statewide oil production to 2045 under
a business-as-usual (BAU) scenario continues this trend (Fig. 2). In this
no-supply-side policy BAU scenario, oil production in 2045 decreases
fields located near where people live and work. Other policies reduce
extraction by targeting oil fields according to their extraction costs,
either on a per barrel basis as with an excise (or severance) tax or on
a per GHG-emissions basis as with a carbon tax. Thus, for the same
overall GHG emissions target, different supply-side policies can gener-
ate distinct aggregate and distributional consequences by reducing
production from different oil fields.
Two primary considerations arise when evaluating supply-side
policies. The first is the relative effectiveness of each policy type in
reducing oil production and associated GHG emissions, which to date,
has received limited empirical analysis10–12. The second pertains to the
ancillary benefits and costs of each policy and how they are distributed
across different communities. In particular, oil extraction tends to
be highly spatially concentrated in certain areas, employing a local
workforce and generating air pollution impacting nearby residents.
Depending on how oil extraction is spatially located in relation to
workers and households, different supply-side policies can have dif-
ferent aggregate and distributional consequences in terms of health
benefits and labour-market impacts. For example, for the same overall
GHG emissions target, a policy that phases out more labour-intensive
oil fields may have higher lost worker compensation than other poli-
cies. Likewise, a policy that bans oil fields near where disadvantaged
households reside may generate larger overall health benefits and
health equity gains. Quantifying such potential consequences is critical
for informing the design of supply-side policies. More broadly, there
is a need to understand if and how effectiveness in GHG emissions
reductions and distributional consequences trade off across different
oil supply-side policies.
Previous decarbonization studies employ either Integrated
Assessment Models, which are combined energy, economy and climate
models13,14, or macro energy-system models15–17 that model regional
energy systems. These models typically simulate or optimize energy
infrastructure investments and retirements to meet certain GHG
emissions-reduction targets by assuming that fossil fuel extraction
will be phased out and replaced by cleaner alternatives. Such models
typically do not explicitly consider how specific supply-side policies
(other than a carbon tax) can yield different decarbonization outcomes
for fossil fuel extraction. Furthermore, most energy or economic mod-
els lack the fine spatial resolution needed to examine the distributional
outcomes of alternative policies over time. For example, existing stud-
ies on the distributional and equity consequences of phasing fossil fuel
production including oil extraction use only the petroleum basin or
county level and not the oil-field and census-tract-level representation
for fuel production and air pollution exposure, respectively15,18, which
is critical to accurately estimate energy production, health effects and
equity outcomes of decarbonization pathways.
This paper examines the effectiveness and distributional con-
sequences of potential supply-side policies intended to phase out
oil extraction across California. As the world’s fifth-largest economy
and the United States’ seventh-largest oil-producing state, California
provides a unique setting to study supply-side policies. The state is cur-
rently implementing some of the world’s most ambitious climate poli-
cies with a statewide carbon-neutrality goal by 2045. This includes an
active debate over various supply-side policies to dramatically reduce
oil extraction, with an explicit interest in examining resulting labour
and health equity consequences and their distribution across the
state19–21.We improve upon previous studies by developing an empiri-
cally estimated model of crude oil-well entry (drilling), production and
exit (retirement) at the oil-field level along with an air pollution model
to quantify health effects at the census-tract level and an employment
input–output model to determine employment impacts at the county
level. We examine three supply-side policy interventions that have
been widely debated in California and elsewhere: (1) well setbacks
that require new oil wells to be located beyond a specified minimum
distance from sensitive sites such as occupied dwellings, schools,

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by 57% compared with 2019 levels. Associated GHG emissions decline
by 53%, which is well short of California’s decarbonization targets.
Supply-side policies lower statewide crude oil production but
with different temporal and spatial patterns (Fig. 2a and Supplemen-
tary Fig. 17). Setbacks applied to new wells, excise taxes applied per
unit of production and carbon taxes applied per tonne of GHG emis-
sions lead to continuous declines that outpace that of the BAU trajec-
tory, albeit with different pathways. In general, a setback and an excise
tax result in lower oil production in each year when compared with a
carbon tax that is calibrated to achieve the same 2045 GHG emissions
target. This is because a carbon tax on extraction emissions targets
oil fields with higher GHG emissions intensities, whereas a setback
targets oil fields in more populated areas and an excise tax targets
production declines among more costly oil fields. Supplementary
Fig. 1 shows that the relationship between production costs and emis-
sions intensities is not systematic. As a result, the fields that reduce
production under a carbon tax will be unique from the fields that
reduce production under an excise tax that achieves an equivalent
reduction in carbon emissions.
There is close correspondence between statewide oil production
and emissions pathways (Fig. 2b). As with oil production, setbacks,
excise taxes and carbon taxes induce a continuous decline. By con-
struction, because excise- and carbon-tax levels were calibrated to
result in the same 2045 GHG emissions as the corresponding setback
distances, the GHG emissions trajectories of setbacks, excise taxes and
carbon taxes are more closely aligned than oil-production trajectories.
Cumulative 2020–2045 GHG emissions reductions from carbon taxes
are consistently lower than setbacks and excise taxes for each 2045
GHG emissions target, irrespective of the oil-price projections (Fig. 2c
and Supplementary Figs. 24 and 25). However, excise taxes, depend-
ing on the tax level required to meet the GHG emissions target under
different oil prices, could have slightly lower or higher cumulative
GHG emissions compared to setbacks. When considering alternative
oil-price projections, annual GHG emissions reduction in 2045 for a
1 mile setback is substantially lower (33%) under EIA’s high oil-price
projection (Supplementary Fig. 24), while it nearly reaches the 90%
reduction target under EIA’s low oil-price projection (89% reduction)
(Supplementary Fig. 25).
Health, labour and avoided climate change
impacts
Reduced crude oil production from supply-side policies have associ-
ated health benefits, labour-market impacts and benefits from avoided
climate change damages. We estimate statewide health benefits from
cumulative avoided mortality resulting from lower air pollution levels,
costs from lost total labour compensation and benefits from avoided
climate change damages due to abated GHGs, priced at the social cost
of carbon31, both total (Fig. 3a–c) and per unit of cumulative avoided
GHG emissions over 2020–2045 for each scenario (Fig. 3d–f). The
costs and benefits are relative to the BAU scenario and estimated in
net-present-value terms, valued in 2019 US dollars (Supplementary
Notes 13–15).
33
34
35
36
37
122
121
120
119
118
PM2.5 concentration of
all oil-field emissions
0
1
2
3
4
1978
1990
2000
Year
2010
2020
Number of new oil wells (thousand)
Latitude (° N)
Latitude (° N)
Latitude (° N)
Latitude (° N)
Observed
Estimated
Observed and modelled
oil wells
Oil production (million barrels)
0
1
2
3
PM2.5 concentration from
Ventura cluster
0.00025
0.00125
PM2.5 (µg m
–3)
34
33
35
36
37
122
121
120
Longitude (° W)
Longitude (° W)
Longitude (° W)
Longitude (° W)
119
118
Oil fields and disadvantaged
communities
DAC
0
5
10
15
Oil production (million barrels)
34
33
35
36
37
122
121
120
119
118
34
35
c
a
b
d
e
119.5
119.0
118.5
Ventura
Fresno
Kern
Los Angeles
Monterey
Ventura
Population−weighted
PM2.5 (µg m
−3)
0
500
1,000
1,500
0
500
1,000
Million US$
Fresno
Los Angeles
Monterey
Ventura
Kern
Worker compensation from
all oil production
Fig. 1 | Summary of data and methods. a, Oil production in 2019 by field. Grey
shaded areas indicate census tracts with disadvantaged communities (DAC),
as defined by CalEnviroScreen. b, Observed and estimated historical oil-well
entry across California (Supplementary Note 9). c, Particulate matter (PM2.5)
concentration by census tract for a 1 tonne pulse of PM2.5 emissions from the
Ventura cluster. Points indicate location of 2019 oil production from oil fields
within the cluster. d, PM2.5 concentration by census tract associated with all
2019 oil production. e, Worker compensation by county associated with all
2019 oil production.

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We note that health benefits denominated in monetized avoided
mortality from air-quality improvements and lost worker compensa-
tion from oil extraction reported here do not provide a full account of
statewide benefits and costs under each supply-side policy. Reductions
in ambient air pollution can bring a wide range of health benefits,
including reduced morbidity, asthma attacks and other respiratory
diseases and lower hospital and medication expenses. For example,
reduced activity in the oil and gas extraction sectors may reduce
ground-level ozone concentrations, which may lead to additional
health benefits that are not accounted for in our study32. To the extent
that other ambient air pollutants such as ozone travel similarly to PM2.5,
the disadvantaged communities vs non-disadvantaged communities
contrasted in the estimated health benefits should be a reasonable
approximation of the full health benefits comparison despite focusing
only on primary and secondary PM2.5.
We focus on monetized avoided mortality alone to measure the
benefits of air-quality improvements because the previous literature
has shown that monetized avoided mortality is by far the largest ben-
efit33. Premature mortality is also the health end point for which there
is the most scientific consensus supporting the causal link between
air pollution (in particular PM2.5) and the end point33. There are also
potential benefits associated with non-health impacts through changes
in agricultural and labour productivity34,35. Likewise, we are unable to
account for the possible re-employment of oil-extraction workers that
may find employment in other sectors. Unfortunately, little is known
on re-employment rates and wages for former oil-extraction workers to
inform such calculations. Thus, our estimates represent lower bounds
of potential health benefits and upper bounds of potential employment
and worker compensation losses. Lastly, considerable uncertainty
exists in the value of the social cost of carbon, a key ingredient in how
avoided climate damages are calculated31. For these reasons, we present
our health, labour and avoided climate damage values separately in
Fig. 3, without attempting to conduct a full cost–benefit analysis. We
instead focus on the relative rankings of each benefit and cost across
the three supply-side policies examined.
Among policies, setbacks consistently achieve the greatest health
benefits, both in total and per unit of cumulative avoided GHG emis-
sions (Fig. 3a,d). This result validates the intent behind setbacks, a
BAU
BAU
BAU
2020
60
70
GHG emissions-reduction target (%, 2045 vs 2019)
80
90
Barrels (million)
Mt CO2e
0
0
40
80
120
a
c
b
160
Mt CO2e
150
175
200
250
225
275
5
10
15
2025
2030
2035
2040
2045
2020
2045 GHG emissions-reduction target
Policy
65% (= 2,500 foot setback)
72% (= 1 mile setback)
90%
Carbon tax
Excise tax
Setback (new wells)
Oil production
Cumulative GHG emissions
Year
Year
GHG emissions
2025
2030
2035
2040
2045
Fig. 2 | California crude oil production and associated GHG emissions
pathways. Annual California oil production and GHG emissions under BAU
and three supply-side policies—setbacks applied to new wells, excise tax on oil
production and carbon tax on emissions from oil extraction. Excise and carbon
taxes are calibrated to meet 62% (= 1,000 foot setback), 65% (= 2,500 foot
setback), 72% (= 1 mile setback) and 90% GHG emissions reduction by 2045
relative to 2020. a, Crude oil production. b, GHG emissions from crude oil
production. c, Cumulative 2020–2045 GHG emissions. Data for 62% GHG
emissions-reduction scenario (= 1,000 foot setback) not shown in a and b for
visual clarity. Setback distances are limited to 1 mile or below, and thus, a setback
that meets a 90% 2045 GHG emissions target is not modelled. Total number of oil
fields in the model is 263. CO2e = carbon dioxide equivalent.

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policy designed specifically for improving health outcomes by elimi-
nating oil extraction from fields that are situated near residences,
schools and other locations where people live and work. However, per
unit of cumulative avoided GHG emissions, longer-distance setbacks
yield smaller health benefits (Fig. 3d) because the marginal pollution
from avoided wells affects a smaller number of people.
For statewide worker compensation losses, the pattern flips
across supply-side policies. For a given 2045 GHG emissions target,
setbacks consistently generate slightly higher worker compensation
losses across the state than excise taxes, which exceed that for carbon
taxes (Fig. 3b). This is because setbacks experience a drop in produc-
tion larger than excise and carbon taxes designed to meet the same
2045 GHG emissions target, and they affect wells in counties that
have a higher employment intensity (jobs per barrel of oil produced).
Excise taxes lead to greater worker compensation loss because they
are less cost effective at targeting GHG emissions reductions com-
pared with carbon taxes, requiring a larger drop in oil production
and associated employment losses to meet the same GHG emissions
target. The ranking across policies is preserved when considering
worker compensation losses per unit of cumulative avoided GHG
emissions (Fig. 3e).
For avoided climate change damages, setbacks deliver slightly
greater cumulative benefits for each 2045 GHG emissions target com-
pared with excise and carbon taxes (Fig. 3c). These differences are
even smaller across policies on a per unit of cumulative avoided GHG
emissions basis (Fig. 3f).
The relative ranking for the health impacts from the three
supply-side policies remains the same under the EIA’s high and low
oil-price projections, although the average magnitude of these benefits
and costs are correspondingly higher or lower than the reference EIA
oil-price projection (Supplementary Figs. 26 and 27). Cumulative lost
worker compensation and avoided climate damages remain the lowest
for carbon taxes across high and low oil-price projections (Supplemen-
tary Figs. 26 and 27).
Drivers of health and labour outcomes across
policies
The ranking of health benefits and labour costs shown in Fig. 3 across
supply-side policies occurs because each policy targets different
aspects of crude oil production and thus the sequence and timing of
well entry, production and retirements across oil fields. To explore
this further, we sort oil fields according to the characteristic directly
targeted by each policy. Specifically, these characteristics, shown on
the x axis across the columns of Fig. 4, include an oil-field cluster’s: (1)
area share near sensitive sites, (2) per barrel cost of extraction per barrel
and (3) GHG emissions intensity per barrel. These characteristics are
directly affected by a setback, an excise tax and a carbon tax. Under each
policy, oil fields on the left of the x axis retire first, moving rightward
as stringency tightens. For example, for a particular setback distance
(2,500 feet in Fig. 4a,d), fields with a greater share of their area near
sensitive sites will experience greater reduction in oil production than
fields with areas less affected by the same setback. The latter fields that
GHG emissions-reduction target (%, 2045 vs 2019)
70
a
 Health: avoided mortality
b
Labour: lost worker compensation
c
 Climate: avoided damage
d
e
f
0
0.5
1.0
NPV (billions of US$)
NPV (millions of US$)
per avoided GHG Mt CO2e
1.5
2.0
–15
–10
–5
0
5
4
3
2
1
0
–150
–100
–50
0
0
10
20
40
30
50
0
10
20
40
30
50
80
90
70
80
90
70
80
90
70
80
90
70
80
90
70
80
90
Policy
Setback (new wells)
Excise tax
Carbon tax
Fig. 3 | Health, labour and climate impacts from California’s oil-production
pathways under different policies relative to BAU. a–c, Total health benefits
from avoided mortality (a), total lost worker compensation (b) and avoided
climate damages valued at the social cost of carbon over 2020–2045 (c) under
three supply-side policies—setbacks applied to new wells, excise tax on oil
production and carbon tax on emissions from oil extraction—relative to BAU
to meet four 2045 GHG emissions targets. d–f, Panels replicate a (d), b (e) and
c (f) but normalized by cumulative avoided GHG emissions over 2020–2045.
No setback distance equivalent to 90% 2045 GHG emissions target is applied.
Total number of oil fields in the model is 263. Net present values (NPV) are in
2019 US dollars, estimated using a discount rate of 3%.

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are farther from sensitive sites will be increasingly affected as setback
distances increase. Likewise, under a low excise tax, the oil fields that
initially phase out production are those with higher extraction costs.
As the excise tax increases, oil fields with lower extraction costs incre-
mentally phase out production. A similar pattern holds for carbon taxes
and their effect on oil fields with varying GHG intensities.
To understand how policies differ in terms of statewide health ben-
efits, the y axis in the top panels of Fig. 3 shows the number of affected
individuals per unit of pollution for each oil field. Because of the down-
ward relationship shown in Fig. 4a, shorter distance setbacks initially
affect oil fields that are upwind of more population-dense locations.
As setback distances increase, the marginal oil field that is phased out
is upwind of fewer people, explaining why the health benefit per unit of
cumulative avoided GHG emissions falls with more stringent setbacks
(Fig. 3d). By contrast, the relationships between population affected
by pollution and costs of extraction and GHG intensity of oil fields
are both upward sloping (Fig. 4b,c). This is reflected in the increas-
ing health benefits, in both total and per unit of cumulative avoided
GHG emissions, with increasing stringency of excise and carbon taxes
(Fig. 4a,d). In other words, as excise and carbon taxes increase, the
marginal oil field that exits production is upwind of more people.
To understand patterns in labour-market impacts, we explore cor-
relations between employment intensity in the oil-extraction sector at
the county level in total job losses per million barrels of oil produced
and the three oil-field characteristics (Fig. 4d–f). The employment
impacts reported in this study are driven by IMPLAN multipliers that
account for direct, indirect and induced jobs. As shown in Fig. 4, oil
fields that are more impacted by setbacks have a greater employment
intensity (jobs per million barrels), reflecting larger multipliers and
county population. For example, oil fields in Los Angeles County are
affected more by shorter setbacks because a larger population in the
county lives close to oil fields, but they also create more direct, indirect
and induced jobs based on IMPLAN’s data. The downward relationship
in Fig. 4d explains why employment loss per GHG emissions reduction
is the highest at shorter setback distances (Fig. 3d). Shorter setbacks
induce more labour-intensive oil fields to exit production first, followed
by less labour-intensive fields as setback distances increase. Again,
by contrast, Fig. 4e,f is upward sloping, indicating that with excise
and carbon taxes, less labour-intensive oil fields go out of production
first. This is consistent with statewide labour costs, in both the total
and per unit of cumulative avoided GHG emissions basis, increas-
ing (more negative) in Fig. 4b,e as excise- and carbon-tax stringency
increases. Higher excise and carbon taxes incrementally induce more
labour-intensive fields to go out of production.
County-level outcomes are similarly driven by county and oil-field
characteristics. Comparing California’s three highest oil-producing
counties in 2019, production in Los Angeles County has lower average
costs per barrel and lower average GHG emissions intensity compared
with Kern or Monterey counties (Supplementary Figs. 19 and 20) but
greater health impacts (mortality) and employment intensity per barrel
of oil production (Supplementary Figs. 21–23). Under a setback policy,
oil production in denser Los Angeles County is affected more than
Kern and Monterey counties (Supplementary Fig. 18), which results
in greater health benefits but also higher labour impacts compared
with the excise- and carbon-tax policies. Because the average cost
of oil production and GHG emissions intensities in oil fields in Kern
and Monterey counties are greater than Los Angeles County, both
the excise- and carbon-tax policies result in lower health benefits and
labour impacts compared to the setback policy.
Equity impacts of supply-side policies
To understand the equity impacts of supply-side policies, we exam-
ine how the statewide health and labour consequences of each decar-
bonization pathway are distributed spatially across the state. We use
200
400
600
800
1,000
1,200
Population afected by
pollution
0
0.2
0.4
0.6
0.8
1
a
–500
0
500
1,000
20
40
60
80
b
–500
0
500
1,000
20
40
60
80
c
–0.0005
0
0.0005
0.0010
Employment intensity
(jobs per million barrels)
0
0.2
0.4
0.6
0.8
1
Share of area afected by setback
d
–0.0005
0
0.0005
0.0010
18
22
26
30
34
38
Cost of extraction (US$ per barrel)
e
–0.0002
0
0.0002
0.0004
0.0006
0.0008
20
40
60
GHG intensity (kg CO2e per barrel)
f
Fig. 4 | Correlations between health and labour impacts with oil-field
characteristics. a–c, Correlation between statewide population affected by
a 1 tonne pulse of PM2.5 from an oil-field cluster on the y axis and that cluster’s
share of area affected by setback (at 2,500 feet) in blue (a); cost of extraction
(in US dollars per barrel) in red (b); and GHG intensity (in kg CO2e per barrel)
in orange (c) on x axes. d–f, Replicates a–c but with employment intensity (in
jobs per million barrels of oil produced) on the y axis at the county level. Total
number of oil fields in the model is 263. All oil-field characteristics shown here are
estimates from 2020. Data are presented as mean values ± 1.96 × standard errors
of measurement (SEM).

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California’s legal definition of whether a census tract is a ‘disadvantaged’
community (DAC) using CalEnviroScreen, a scoring system based on
multiple-pollution exposure and socioeconomic indicators developed
by the California Environmental Protection Agency36. For each policy
scenario, we estimate the share of the total statewide health benefits
and employment losses in oil extraction borne by communities living
in disadvantaged community census tracts (Fig. 5a,b).
The DAC’s share of health benefits is consistently larger under a
setback than under excise and carbon taxes for a given 2045 GHG emis-
sions target. This share is largest at lower setback distances or equiva-
lently less stringent 2045 GHG emissions targets and decreases as the
setback distance increases. For excise and carbon taxes, the DAC’s share
of benefits is relatively unaffected by the stringency of the 2045 GHG
emissions target. The lost worker compensation is largest for setbacks
at the statewide level. However, the share of total lost worker compen-
sation from workers in DACs is consistently lower under setbacks than
under excise and carbon taxes. Thus, for any given 2045 GHG emissions
target, a greater share of health benefits and a lower share of worker
compensation impacts are experienced by DACs under a setback than
under excise and carbon taxes. This result holds even under the EIA’s
high and low oil-price projections (Supplementary Figs. 28 and 29).
Setbacks applied to all versus only new wells
Although most existing and proposed setback policies apply to only
new wells, applying setbacks additionally to existing wells could be an
important policy instrument to further mitigate GHG emissions and
improve health outcomes of neighbouring communities that have
historically borne the burden of local pollution from oil extraction. To
understand the health, labour and equity consequences of setbacks
on all wells, we also model a setback policy that affects both new and
existing wells applied in 2020.
In comparison to setbacks on only new wells, applying setbacks to
all wells predictably results in greater oil-production declines and emis-
sions reductions. As discussed earlier, setbacks applied to only new
wells result in a continuous decline in oil production and GHG emissions
(Fig. 6). In contrast, setbacks applied to all wells induce an immediate
drop in statewide oil production and associated GHG emissions in 2020
as existing wells within the setback distance fall out of production.
This drop is then followed by a gradual decline thereafter that tracks
the BAU trajectory. Oil production and GHG emissions reductions
increase as setbacks get longer. Although a 1-mile setback, the largest
considered in this study, applied to all wells achieves a substantially
greater GHG emissions reduction (81%) by 2045 compared with the
same setback on new wells (72%), it still falls short of meeting the 90%
reduction target (Fig. 6b). However, the cumulative GHG emissions
reduction over 2020–2045 for the 1-mile setback applied to all wells is
on par with those of excise and carbon taxes that result in a 90% annual
GHG emissions reduction in 2045 (Fig. 2c).
Setbacks applied to all wells result in fewer premature deaths but
also greater total lost worker compensation compared with setbacks
on only new wells (Fig. 6). Setbacks on all wells have better equity out-
comes by accruing a greater share of avoided mortality benefits and
a lower share of lost worker compensation to disadvantaged commu-
nities. Thus, setbacks applied to all wells in general would yield more
pronounced health and labour-market consequences than setbacks
applied to just new wells.
Discussion and conclusions
By quantifying the trade-offs across different supply-side policies, we
find that for California, an oil-well-setback policy applied to new wells
provides greater health benefits compared to a carbon- or excise-tax
policy designed to achieve the same 2045 GHG emissions-reduction
target. A setback policy also produces equity gains as DACs accrue
greater health benefits and lower employment costs than other com-
munities under a setback compared to excise and carbon taxes.
Yet a setback policy imposes the largest statewide loss of worker
compensation among the three policies for the reference oil-price
projection. Moreover, on its own, a setback policy applied to new wells
achieves only a 72% GHG emissions reduction in 2045 compared with
2019 for a 1-mile setback, a distance larger than the maximum 3,200 feet
currently proposed in California28. GHG emissions reductions would
be even lower under higher global crude oil prices. While a setback
policy is generally advocated by stakeholders based on public health
concerns, it will need to either impose greater distances, be applied
to both new and existing wells or be combined with an appropriate
excise or carbon tax to meet California’s decarbonization goals (Sup-
plementary Figs. 30–35).
Whereas carbon taxes and excise taxes are both able to achieve
more aggressive annual GHG emissions reductions, that is, 90% GHG
emissions reduction by 2045 compared with 2019, the tax values
required to achieve 90% decarbonization are higher than those con-
sidered in current policies. The carbon tax required to drive a 90%
GHG emissions reduction by 2045 starts at US$250 t−1 CO2e in 2020
and increases to US$1,330 t−1 CO2e in 2045. This trajectory is nearly
four times higher than the allowance price ceiling under California’s
cap-and-trade system that starts at US$65 t−1 CO2e in 2021 and rises to
US$330 t−1 CO2e by 2045, assuming an annual real growth rate of 5%
and an inflation rate of 2% (ref. 37). Similarly, none of the excise taxes
currently in effect across 27 US states exceed 10% of the oil price38,
which is far lower than the 67% tax we find is required to achieve a
90% GHG emissions-reduction target by 2045 under EIA’s reference
oil-price projection.
Finally, our results indicate that combining a setback with a car-
bon tax could achieve the state’s GHG emissions target while yielding
greater statewide health benefits, lower statewide worker compensa-
tion losses and larger equity gains compared to having just a carbon
tax or excise tax alone. However, if the setbacks are applied to only new
wells, the carbon-tax trajectory would still need to be three times higher
than currently permitted under California’s cap-and-trade system
(Supplementary Fig. 16). For the two trajectories to be similar, setbacks
would need to be applied to both existing and new wells.
Although we examined only the impacts of PM2.5 on health out-
comes, oil extraction also emits other toxic pollutants, including ben-
zene, ethylbenzene and n-hexane, which are known to cause cancer and
other serious health effects39. Setbacks will not only reduce exposure
to PM2.5 pollution but will also decrease exposure to these other toxic
pollutants and thus could lead to larger health benefits as oil extraction
is phased out. To realize the health and climate benefits of setbacks
GHG emissions-reduction target (%, 2045 vs 2019)
DAC share
0.35
a
b
0.32
0.30
0.28
0.25
60
70
80
90
60
70
80
90
0.40
0.38
0.35
0.33
0.30
Carbon tax
Excise tax
Setback (new wells)
Policy
Health: avoided mortality
Labour: lost worker compensation
Fig. 5 | DACs’ share of health and labour impacts. a,b, Share of avoided
mortality benefits borne by individuals (a) and share of foregone oil-extraction
earnings borne by workers in DACs (b) under setbacks, excise tax and carbon tax
for different 2045 GHG-reduction targets.

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estimated in this study, setbacks will need to be applied to both exist-
ing and new wells, unlike most existing and proposed regulations that
apply setbacks to only new wells.
Two other supply-side policies that we do not examine in this study
include limiting producer subsidies14,40 and restricting development of
oil fields, either by compensating resource owners for not exploiting
their fuel resources, buying and retiring resource rights or limiting new
leases on government lands10,41. The former is similar to imposing an
excise tax on production, whereas the latter requires rules to prioritize
fields for constraining development, similar to a setback policy that is
considered in this study.
The effectiveness and equity trade-offs across various oil
supply-side policies must be ultimately considered in tandem with oil
demand-side policies, without which global GHG emissions reductions
may be limited when oil markets are global. For example, demand-side
policies from any jurisdiction alone may yield limited GHG emissions
reductions if other jurisdictions increase oil demand in response to
lower global oil prices11,42,43. Similarly, restricting only oil supply in a
Policy:
160
Barrels (million)
NPV (billions of US$)
DAC share
Mt CO2 e
120
80
40
0
2020
60
65
70
75
80
65
70
75
80
65
70
75
80
65
70
75
80
65
70
75
80
2025
2030
2035
2040
2045
BAU
BAU
0
0.30
0.31
0.32
0.33
0.34
0.35
1
2
3
275
250
225
200
175
150
–15
0.30
0.31
0.32
0.33
0.34
0.35
–10
–5
0
Setback (new wells)
Setback (all wells)
Setback distance:
2,500 feet
5,280 feet
1,000 feet
2,500 feet
5,280 feet
+
Cumulative GHG emissions
Oil production
a
b
c
d
e
f
Labour: lost worker compensation
GHG emissions-reduction target (%, 2045 vs 2019)
Year
GHG emissions-reduction target (%, 2045 vs 2019)
GHG emissions-reduction target (%, 2045 vs 2019)
Health: avoided mortality
DAC share labour: lost worker compensation
DAC share health: avoided mortality
Fig. 6 | Comparison between setback policies applied to new and all wells.
a–f, Three setback distances—1,000-foot setback, 2,500-foot setback and
1-mile setback—applied to new and all (new and existing) wells. Oil-production
pathways (a), cumulative GHG emissions over 2020–2045 (b), total health
benefits from avoided mortality (c), total lost worker compensation (d), share of
avoided mortality benefits borne by individuals in DACs (e) and share of foregone
oil-extraction earnings borne by workers in DACs (f) under the three setbacks.
Total number of oil fields in the model is 263. Net present values are in 2019
US dollars, estimated using a discount rate of 3%.

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single jurisdiction without efforts to limit oil demand in that jurisdic-
tion will result in an increase in oil exports from elsewhere, with some
amount of local GHG emissions reduction replaced by increased GHG
emissions elsewhere. By coordinating oil supply- and demand-side
policies, it is possible for a jurisdiction’s oil supply and demand curves
to jointly shift in a manner that leaves the global oil price unchanged
and avoid GHG leakage to other jurisdictions.
Additionally, demand and supply policies that simply reduce GHG
emissions from transportation fuels may have limited GHG emissions
reductions if there is not an economy-wide climate policy, such as
a carbon price, that ensures any energy source that replaces oil for
transportation, such as electricity, is not more carbon intensive. For
example, a transition from oil to electricity in transportation may have
limited climate benefits if the electricity is produced primarily by coal.
Future research should assess the resulting effectiveness and equity
consequences of having multiple complementary climate policies.
Such future analyses can take advantage of the methodological
approach developed in this paper. Across many settings and sectors,
stakeholders are asking decarbonization policies to take into account
not just their GHG emissions consequences but also how the local
costs and benefits of these policies are distributed spatially and across
different demographic groups. This paper provides a step forward
in that direction by combining an empirical-based, spatially explicit
energy production model with state-of-the-art air pollution transport
modelling to quantify health benefits at a fine spatial scale and an
employment model to quantify local labour-market consequences.
Our framework can be applied to other decarbonization policies at
various scales such as studying the distributional consequences of
decarbonizing other forms of fossil fuel extraction, electricity produc-
tion or manufacturing activity. More broadly, in many settings that
already exhibit socioeconomic inequities, there is an increasing need
to understand whether decarbonization policies themselves would
exacerbate or narrow such inequities. This study and its methodology
provides a path forward for such analyses.
Methods
Modelling framework
To estimate the health and labour consequences of supply-side policies,
we build an empirically validated model of oil production to estimate
field-level oil production and GHG emissions pathways under varying
policy scenarios. These estimates drive our projections of pollution
dispersion, mortality effects and local employment, which are used
to quantify health and labour impacts under different policy and GHG
emissions-target scenarios. We further examine the equity impacts of
these scenarios focusing on how health and labour impacts are distrib-
uted between disadvantaged and other communities. Throughout, we
use nominal prices in both the estimation and projection parts of the
analysis. When presenting health and labour impacts, we calculate net
present discounted values in 2019 US dollars after applying a discount
rate of 3% and an inflation rate of 2%.
Supply-side policies and oil-price forecasts
We model the impacts of three policies—setbacks, an excise tax and a
carbon tax—on California’s oil sector. A setback policy prohibits oil (and
gas) extraction within a specified distance from sensitive sites including
occupied dwellings, schools, healthcare facilities and playgrounds. We
model two setback scenarios: (1) setbacks that apply to new wells only
(main results) and (2) setbacks that apply to new and existing wells or
all wells. We model setbacks on new wells by proportionally reducing
field-level future new well entry based on the relative field area covered
by a given setback buffer. For existing wells, setbacks are implemented
in our model by removing those within the setback distance from future
production. We consider setback distances of 1,000 feet, 2,500 feet
and 1 mile. We assume only vertical drilling in the setback analysis.
Horizontal and directional drilling from pads outside of the setback
distance could access additional sub-surface oil resources within the
setback distance, reducing our estimates of the health and equity ben-
efits of setbacks, especially for shorter setback distances44. However,
the costs and extent of adoption of horizontal drilling are uncertain for
California and thus are not included in this study. The excise-tax policy
imposes a tax on each barrel of crude oil extracted. In our projection
period, we apply a constant tax rate to the oil price each year. This is
consistent with historical proposals for excise taxes on California oil
extraction45. The carbon-tax policy imposes a tax on the GHG emissions
from the oil-extraction site. We consider only direct GHG emissions,
excluding methane emissions due to a lack of reliable oil-field-specific
data. All carbon-tax trajectories increase at an annual rate of 7%, the
sum of a 5% real growth rate and 2% inflation rate per year (ref. 46). We
determine the excise-tax rates applied to the oil price and carbon taxes
that result in the following 2045 statewide GHG emissions targets using
an optimization function: (1) 2045 statewide GHG emissions associated
with the three setback distances (Supplementary Table 4) and (2) a 90%
reduction in statewide GHG emissions compared with 2019. The excise
and carbon taxes are shown in Supplementary Figs. 15 and 16 and are
inputs to the oil-extraction model and affect future well entry and exit.
Supplementary Note 17 provides more details.
For 2020–2045 macroeconomic conditions, we assume three
Brent spot crude oil nominal price trajectories (reference, low and
high) obtained from the EIA’s Annual Energy Outlook 2021 forecast
(Supplementary Fig. 13) (ref. 29). For scenarios that do not include
a carbon tax, we apply a baseline nominal carbon price equal to Cali-
fornia’s cap-and-trade allowance price floor (Supplementary Fig. 14).
Supplementary Note 16 provides more details.
Oil-production model
The model of oil production has three components: (1) well entry,
(2) annual production after entry and (3) well exit.
We model new well entry by estimating a Poisson model of well
entry using data on historical production from existing wells and fields,
costs and crude oil nominal prices. Specifically, we estimate annual new
well entry in an oil field as a function of oil prices, field-level capital and
operational expenditures (Supplementary Figs. 2–4) and field-level
depletion. Details are provided in Supplementary Note 9. This model is
estimated using well-entry data between 1977 and 2019 from California’s
Department of Conservation’s WellSTAR database47. Supplementary
Notes 1 and 3–5 provide more information on the input data. Capital
and operational expenditure data are from the subscription-based data
provider Rystad Energy (Supplementary Note 2). Model estimates are
provided in Supplementary Table 1.
After estimating the well-entry model, we predict annual well
entries for the 2020–2045 projection period using forecasted nominal
prices and prescribed policy conditions. Field-level operational costs
are modified each year based on the relevant carbon and excise tax. The
setback policy constrains projected new well entry in a given field by
reducing the number of predicted new wells by the percentage of field
area covered by a setback. Figure 1 and Supplementary Fig. 5 compare
the predicted and observed entry at the state level and for each top
field category, respectively.
To predict annual oil production after well entry, we estimate
oil-production decline curves at the field and vintage level for both
existing (that is, pre-2020 entry) and new wells (that is, wells that enter
during 2020–2045). Production from oil wells often follow a declin-
ing profile of production until the wells exit48,49. For existing wells, we
estimate the decline-curve parameters using historical oil-production
data (Supplementary Note 10) and apply them to the decline-curve
equations to estimate future annual production at the field-vintage
level. To predict future production from new wells, we extrapolate
historical parameters using a linear regression model to obtain val-
ues for the 2020–2045 forecast period. In each forecast year for each
field, we use the corresponding extrapolated decline parameters and

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decline-curve equations to determine field-vintage-level production
from the year the wells enter through the end of the projection period.
We repeat this process for all forecast years. Modelled production
decline curves and actual production for two fields are shown in Sup-
plementary Figs. 6 and 7.
Because most wells that idle for a long time stop producing alto-
gether50, we use historical data on wells that idled continuously for ten
years as a proxy for wells that stop producing and exit. We model well
exits as a function of the nominal oil price, nominal field-level opera-
tional costs and field-level depletion. We estimate the parameters of the
model using historical data from 1977 to 2019 and apply the parameters
to predict future well exit in the period 2020–2045, again modifying
field-level operational costs each year based on the relevant carbon and
excise taxes. Supplementary Note 11 provides details. Model estimates
are provided in Supplementary Table 1. Supplementary Figs. 8 and 9
compare the predicted and observed exit at the state level and for each
top field category, respectively.
To account for well exits and setbacks, we adjust the predicted
production from both existing and new vintages. We assume that each
well in a given field-vintage produces the same amount of oil. Each
year the exit model predicts the number of wells that exit from each
field. We then remove these wells in order of vintage, starting with the
oldest. For vintages that experience well exit, future production is
correspondingly decreased to account for the reduction in number of
wells in production. Similarly, for existing vintages we adjust predicted
production to account for wells prohibited from future production
due to setbacks by reducing production volumes proportionally by
the number of wells removed by the setback. Supplementary Note 8
provides more details about the oil-production model.
GHG emissions
We estimate GHG emissions associated with oil extraction using
field-specific GHG emissions factors. We first estimate historical GHG
emissions factors using the Oil Production Greenhouse Gas Emis-
sion Estimator (OPGEE) model v2.0 from the California Air Resources
Board51,52 (Supplementary Fig. 10 provides 2015 data). The OPGEE
model is an engineering-based life-cycle assessment tool for the meas-
urement of GHG emissions from the production, processing and trans-
port of crude oil. Using the OPGEE model and oil-extraction data from
the California Department of Conservation, we model field-level GHG
emissions for the years 2000, 2005, 2010, 2012, 2014, 2016 and 2018.
We consider only upstream emissions from exploration, drilling, crude
production, surface processing, maintenance operations, waste treat-
ment/disposal and other small sources (as modelled by OPGEE). To
obtain emissions factors for oil fields that were not modelled by OPGEE,
we apply the median emissions factors for the fields that were mod-
elled, separated by the use of steam injection (Supplementary Note 12
provides more information). To estimate the field-level GHG emis-
sions for the projection period (2020–2045), we average the historical
emissions factors for each year, again separated by fields based on the
use of steam injection. We then linearly regress the average emissions
factors and extrapolate over the projection period. Last, we apply the
percent change in emissions factor between each forecast year to the
field-level historical emissions factors from 2018 onwards to determine
field-level emissions factors for each forecast year. Supplementary
Note 12 provides more details.
Health impacts
We first estimate PM2.5 emissions from oil production for each oil-field
cluster (set of oil fields clustered by geographical proximity; Sup-
plementary Fig. 11) using average emissions factors obtained from
a nationwide US sample53 (Supplementary Table 2). Using average
PM2.5 emissions factors is a limitation of the study due to the lack
of field-specific PM2.5 emissions factors. In practice, actual emis-
sions factors are probably highly heterogeneous across oil fields.
Emissions-factor heterogeneity can arise from differences across PM2.5
emissions sources—which include on-site fossil fuel combustion from
processing plants, generators, pumps, compressors and drilling rigs,
flaring, gas venting, dust from heavy vehicles and secondary formation
from ambient conditions—and across well vintages and operators53,54.
Whether such heterogeneity is consequential for air-quality disparities
should be a subject of future research as field-level emissions data
become available.
Next, we model pollution dispersal using the Intervention Model
for Air Pollution (InMAP) to obtain PM2.5 concentration from oil pro-
duction at the census-tract level for each projection year55. InMAP is a
reduced-complexity dispersal model based on the Weather Research
and Forecasting model coupled with Chemistry (WRF-Chem) that mod-
els secondary PM2.5 concentrations developed by ref. 22. We followed the
methods of ref. 55 and ran InMAP individually for each cluster and pol-
lutant combination to obtain a source receptor matrix for all the extrac-
tion clusters. We then quantify the avoided mortality associated with
changes in ambient PM2.5 exposure at the census-tract level compared
with the BAU scenario56,57 using a mortality concentration-response
function adapted from ref. 58. This function estimates avoided mortal-
ity using population projections (Supplementary Fig. 12), a baseline
mortality rate from 2015, the percentage change in mortality associ-
ated with a 1 μg m−3 increase in PM2.5 exposure (0.0058 from ref. 59)
and our estimated changes in ambient concentrations of PM2.5.
Last, we estimate the monetized values of avoided mortality using a
US$9.4 million (in 2019 dollars) value obtained from ref. 60. All mortal-
ity benefits are then summed over the 2020–2045 projection period
and presented in net present value terms. Supplementary Notes 6
and 13 provide more details.
Labour impacts
We quantify changes in employment and worker compensation using
an economic input–output model from IMPLAN61,62. IMPLAN uses over
90 sources of employment data to construct measures of county-level
employment and compensation based on sector-specific revenue
inputs. Supplementary Table 3 summarizes the input specifications for
the labour analysis. Oil production and oil prices from the projected
pathways serve as the inputs to IMPLAN, which then computes result-
ing employment in full-time equivalent job years and total employee
compensation supported by the oil and gas industry for each county
with active oil and gas operations in the state. IMPLAN uses fixed multi-
pliers to quantify local employment changes in the oil-extraction sector
(‘direct’), in sectors that provide inputs to oil extraction (‘indirect’) and
in sectors where these workers spend income (‘induced’). Similar to
other input–output models, IMPLAN is based on a static framework
where the underlying multipliers are fixed and do not change with
the economic environment, which is a limitation of this model. This
implies, for example, that inflation, changes in labour productivity and
geographical or temporal shocks to labour markets, all of which could
be the result of some of the supply-side policies we consider, cannot
be incorporated in the labour-market impact analysis. Supplementary
Notes 7 and 14 provide more details.
Equity impacts
To quantify distributional impacts, we use California’s legal definition
of a ‘disadvantaged’ community (DAC) using CalEnviroScreen, a scor-
ing system based on multiple-pollution exposure and socioeconomic
indicators developed by the California Environmental Protection
Agency36. The following indicators are considered for the DAC defi-
nition: ozone concentration, PM2.5 concentration, diesel emissions,
pesticide use, toxic releases, traffic, drinking water quality, cleanup
sites, groundwater threats, hazardous waste facilities, impaired water
bodies, solid waste sites, asthma rate, cardiovascular disease rate, low
birth weight percent, educational attainment, housing burden, linguis-
tic isolation, poverty percent and percent unemployed. A census tract

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is considered disadvantaged if it has a CalEnviroScreen score above the
top 25th percentile (ref. 63). We calculate the DACs ratio of health and
labour impacts (that is, the share of impacts experienced by DACs) by
calculating the ratio of the impact experienced by DAC census tracts
to the total statewide impact. Supplementary Note 18 provides more
details. Supplementary Notes 19, 36 and 37 show the advantages of
finer spatial resolution analysis (census-tract level) and the errors that
may be introduced by a coarser analysis conducted at the county level,
especially in the ranking of equity outcomes.
Data availability
Data on assets and asset-level costs from Rystad Energy and employ-
ment and worker compensation data from IMPLAN are proprietary.
All other datasets are publicly available and were collected online
from California Department of Conservation, US Energy Information
Administration, International Energy Agency, California Air Resources
Board, California Office of Environmental Health Hazard Assessment,
California Department of Finance, the Environmental Benefits Mapping
and Analysis Program - Community Edition (BenMAP-CE), National His-
torical Geographic Information System, Congressional Budget Office,
InMAP and the US Census Bureau. All publicly available datasets are
available on Zenodo at https://doi.org/10.5281/zenodo.7742802 with
the exception of InMAP and BenMAP-CE data, which can be downloaded
directly from the software. The Zenodo repository includes raw input
data files that are not proprietary, intermediate data files to run the
models and final results files to create the figures. A detailed readme
file includes descriptions of all data used in the study. Source data are
provided with this paper.
Code availability
All code used to conduct the study is available at https://github.com/
emlab-ucsb/ca-transport-supply-decarb.
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Acknowledgements
We thank the state of California for supporting this work through the
Greenhouse Gas Reduction Fund. The state of California assumes
no liability for the contents or use of this study. The study does not
reflect the official views or policies of the state of California. We also
thank the California Environmental Protection Agency, California
State Transportation Agency, California Air Resources Board,
California Energy Commission, California Natural Resources Agency,
California Workforce Development Board, California Department of
Conservation, California Governor’s Office of Business and Economic
Development, California Office of Environmental Health Hazard
Assessment and Office of Planning and Research and the California
Governor’s Office of Planning and Research for providing support,
data and valuable feedback. We thank M. Clemence and E. O’Reilly for
managing and supporting the project.
Author contributions
R.D., P.W., K.C.M., O.D. and D.W.L. conceptualized the study and
acquired the funding. R.D., P.W., K.C.M., O.D., D.H.-C., R.L., C.M., T.M.,
M.M. and V.T. developed the methodology and software. R.D., P.W.,
K.C.M., O.D., D.H.-C., R.L., C.M., T.M., M.M., S.S., V.T. and A.U. conducted
the formal analysis. D.H.-C., R.L., C.M., T.M., M.M., S.S., V.T. and A.U.
curated the data. R.D., P.W., K.C.M., O.D., D.W.L., D.H.-C., T.K., R.L., C.M.,
T.M., M.M. and V.T. wrote and edited the paper. K.C.M., O.D., D.W.L., P.W.
and R.D. supervised the project.
Competing interests
The authors declare no competing interests.
Additional information
Supplementary information The online version contains supplementary
material available at https://doi.org/10.1038/s41560-023-01259-y.
Correspondence and requests for materials should be addressed to
Ranjit Deshmukh, Paige Weber or Kyle C. Meng.

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Peer review information Nature Energy thanks Peter Maniloff,
Erin Mayfield and the other, anonymous, reviewer(s) for their
contribution to the peer review of this work.
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2023

    Scientific Research Findings:

Answer: For a statewide 2045 GHG target, we find that setbacks applied to new oil wells generate the largest health benefits in terms of avoided mortality from reduced particulate matter air pollution, but also the largest lost worker compensation. This is followed by excise taxes and carbon taxes. Setbacks also have the most favourable equity outcomes by yielding the highest share of health benefits and the lowest share of lost worker compensation borne by disadvantaged communities. However, even a 1‑mile setback — the largest considered in this study and much larger than the 3,200 ft (975 m) currently proposed in California — may fail to meet California’s ambitious 90% GHG reduction target by 2045. Meeting this target will require combining setbacks applied to both existing and new oil wells with other supply‑side policies such as excise taxes and carbon taxes.