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Technical Support Document
Estimating the Benefit per Ton of Reducing PM2.5
Precursors from 17 Sectors
U.S. Environmental Protection Agency
Office of Air and Radiation
Office of Air Quality Planning and Standards
Research Triangle Park, NC 27711
l
February 2018
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CONTACT INFORMATION
This document has been prepared by staff from the Office of Air Quality Planning
and Standards, U.S. Environmental Protection Agency. Questions related to this document
should be addressed to Neal Fann or Elizabeth Chan, U.S. Environmental Protection
Agency, Office of Air Quality Planning and Standards, Health and Environmental Impacts
Division, Risk and Benefits Group, Research Triangle Park, North Carolina 27711 (email:
fann.neal@epa.gov, chan.elizabeth@epa.gov).
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Background and Overview
In 2013, the Agency published a Technical Support Document (TSD) (U.S. EPA 2013)
describing an approach for estimating the average avoided human health impacts, and
monetized benefits related to emissions of PM2.5 and PM2.5 precursors including NOxand
SChfrom 17 sectors using the results of source apportionment photochemical modeling.
The Agency periodically updates the demographic and economic input parameters used to
quantify the incidence and dollar value of air pollution-related effects. In 2017, EPA
released a new version of its environmental Benefits Mapping and Analysis Program—
Community Edition (BenMAP-CE) tool that incorporated new demographic and economic
parameters; these are summarized below and described in greater detail in a
memorandum available here.
Using this new version of BenMAP-CE, we re-calculated the PM2.5 benefit per-ton
values (BPT). When calculating these new BPT values, we used the same emission and air
quality input parameters as was used in the 2013 TSD (U.S. EPA 2013) and a published
manuscript (Fann et al. 2012). Below we describe: our approach to calculating a BPT value;
the new demographic and economic datasets we incorporated into BenMAP-CE; and, the
limitations and uncertainties associated with application of these estimates. Finally, we
summarize the benefit per ton estimates for each of the 17 emission sectors. Readers
interested in learning more about the emissions and air quality input parameters may refer
to a separate TSD detailing the modeling or the two published manuscripts that detail the
photochemical modeling simulations (Fann et al. 2013, 2012; U.S. EPA 2011).
Approach to Calculating Benefit Per-Ton Values
The procedure for calculating benefit per ton coefficients follows three steps, shown
graphically in Figure 1:
1. Using source apportionment photochemical modeling, predict annual average
ambient concentrations of primary PM2.5, nitrate and sulfate attributable to each of
17 emission sectors across the Continental U.S.; see below for a summary of the
sectors modeled.
2. For each sector, estimate the health impacts, and the economic value of these
impacts, associated with the attributable ambient concentrations of primary PM2.5,
sulfate and nitrate PM2.5 using the environmental Benefits Mapping and Analysis
Program-Community Edition (BenMAP vl.3.71).1
1 In this stage we estimate the PM2.s-related impacts associated with changes in directly emitted PM2.5, nitrate
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3, For each sector, divide the PM2.5-related health impacts attributable to each type of
PM2.5, and the monetary value of these impacts, by the level of associated precursor
emissions. That is, primary PM2.5 benefits are divided by direct PM2.5 emissions,
sulfate benefits are divided by SO2 emissions, and nitrate benefits are divided by
NOxemissions.
> & Benefits and avoided impacts
; -— = Benefit ton
Scenario emissions
PM2 5 air quality foi a Human health impacts Benefit-per-ton calculation
given sector
Figure 1. Conceptual overview of the steps for calculating benefit per-ton estimates
Sectors Analyzed
The example above depicts the total PM2.5 contribution from the pulp and paper
sector, though we repeat this process for each of the 17 sectors, which include:
1. Locomotives and marine vessels2
2. Area sources
3. Cement kilns
4. Coke ovens
5. Electric arc furnaces
6. Electricity generating units
7. Ferroalloy facilities
8. Industrial point sources
9. Integrated iron and steel facilities
10. Iron and steel facilities
11. Non-road mobile sources
12. Ocean-going vessels
13. On-road mobile sources
14. Pulp and paper facilities
and sulfate separately, so that we may ultimately calculate the benefit per ton reduced of the corresponding
PM2.5 precursor, or directly emitted PM2.5, in step 3. When estimating these impacts we apply effect
coefficients that relate changes in total PiVh.s mass to the risk of adverse health outcomes; we do not apply
effect coefficients that are differentiated by PM2.5 specie.
2 The prior version of this TSD specified this sector as "Air, Locomotive and Marine Vessels." The Agency
subsequently learned that, due to an emissions processing error, this sector omits Aircraft emissions.
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15. Refineries
16. Residential wood combustion
17. Taconite mines
The "Area sources" and "Industrial point sources" categories are an agglomeration
of emission sectors that were not otherwise specified elsewhere. When selecting a benefit
per ton estimate for use with a sector not specifically modeled, it is necessary to determine
which composite sector is the best match with respect to the source characteristics that
would affect the level of benefits. These attributes include the proximity to receptor
populations, the geographic distribution of sources, and the release parameters of the
source (e.g., stack height).
Readers interested in a full discussion of the air quality modeling performed to
generate these benefit per ton estimates may consult "Air Quality Modeling Technical
Support Document: Source Sector Assessments" (U.S. EPA 2011). Ambient PM2.5
concentrations attributable to each sector were projected from the 2005 baseline to 2016
to represent growth and the application of controls. The starting point for the projections
was the 2005 v4.3 emissions platform (US EPA 2005). EGU emission estimates for 2016 are
from the Integrated Planning Model (IPM). The 2016 projection included emission
reductions related to the NOx State Implementation Plan Call (US EPA 1998), the Maximum
Achievable Control Technology (MACT) Standards for Industrial Boilers (US EPA 2011d)
and Reciprocating Internal Combustion Engines (US EPA 2010b), and the proposed
Transport Rule affecting emissions from Electricity Generating Units (US EPA 2010c).
Control and growth factors, including known plant shut-downs and economic growth in
some sectors, were applied to a subset of the 2005 industrial point sources and area
sources to create the 2016 projection. Other North American emissions are based on a
2006 Canadian inventory and 1999 Mexican inventory, which are not grown or controlled
when used as part of future year baseline inventories (US EPA 2011b; US EPA 2011c).
Global emissions are included in the modeling system through boundary condition inflow
to the 36 km CAMx simulation. The initial and boundary conditions for the 36 km CAMx
simulation are based on 3-hourly output from an annual 2005 GEOS-CHEM simulation
(standard version 7-04-11). Table 1 summarizes the total precursor emissions attributable
to each sector in 2016. Appendix B of this TSD includes plots of the PM2.5 levels attributed
to each of these sectors for which we estimated benefit per-ton metrics.
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Table 1. 2016 emissions by sector (tons per year)
Sector
voc
NOx
PM2.5a
SO2
NHs
Aircraft, locomotives and marine
vessels
43,547
1,342,849
35,604
9,087
940
Area sources
9,380,925
1,633,261
325,820
1,243,154
126,802
Cement kilns
3,059
130,536
1,106
48,737
679
Coke ovens
7,821
16,110
368
27,952
1,084
Electric arc furnaces
3,560
15,707
622
6,088
119
Electricity generating units
63,198
1,826,582
30,078
3,793,362
36,706
Ferroalloy facilities
150
3,412
201
4,580
510
Industrial point sources
1,259,745
1,263,276
67,614
877,620
140,948
Integrated iron and steel facilities
9,620
31,925
2,856
29,045
167
Iron and steel facilities
14,384
5,867
1,366
3,590
166
Non-road mobile sources
1,953,067
1,259,578
106,975
2,879
2,345
Ocean-going vessels
66,093
1,534,234
7,407
439,987
0
On-road mobile sources
2,357,108
4,239,971
118,986
26,786
82,094
Pulp and paper facilities
121,597
240,139
10,067
170,393
10,859
Refineries
111,391
118,206
7,379
132,337
3,556
Residential wood combustion
538,466
33,786
192,492
4,720
6,586
Taconite mines
606
41,350
884
8,823
4
a This value includes elemental and organic carbon, which were used for the benefit per ton
calculations.
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The photochemical modeling used here also produced estimates of ozone levels
attributable to each sector. However, the complex non-linear chemistry governing ozone
formation prevented us from developing a complementary array of ozone benefit per ton
values. This limitation notwithstanding, we anticipate that the ozone-related benefits
associated with reducing emissions of NOxand VOC for many of these sectors could be
substantial.
While most VOCs emitted are oxidized to carbon dioxide (CO2) rather than to PM, a
portion of VOC emission contributes to ambient PM2.5 levels as organic carbon aerosols (U.S.
EPA 2009). Therefore, reducing VOC emissions would reduce the level of PM2.5 formed in
the atmosphere, human exposure to PM2.5, and the incidence of PM2.5-related health effects.
However, we have not quantified VOC benefit per ton estimates in this analysis.
Uncertainties in both the origin and quantity of emissions contributing to secondary
organic aerosol on regional scales limit the quality of regional scale modeling of secondary
organic carbon. Modeling and monitoring the relative amount of organic particles that are
formed through secondary processes, versus primarily emitted organic particles, is highly
uncertain. While the relative contributions of different sources to regional sulfate and
nitrate can be quantified with certainty, the contributions from different sources to
secondary organic aerosol are less clear. Carbonaceous aerosol reflects a complex mixture
of hundreds to thousands of organic carbon compounds, many of which have not been
successfully quantified. Despite progress that has been made in understanding the origin,
properties, and key formation processes of SOA, it remains the least understood
component of PM2.5 (U.S. EPA 2004).
Below we provide an expanded discussion of each of the latter two steps to the
calculation—estimating health impacts and economic value of PM2.5 attributable to each
sector and calculating the benefit per ton coefficients. The discussion of these topics is not
intended to be exhaustive, and readers interested in learning more about our approach to
performing an air pollution health impact and benefits analysis may consult the PM NAAQS
RIA (US EPA 2012).
Estimating the number of PM2.5-related health impacts attributable to each sector
In this stage of the analysis we performed a Health Impact Assessment (HIA), which
quantifies the changes in the incidence of adverse health impacts resulting from changes in
human exposure to PM2.5 from each sector. HIAs are a well-established approach for
estimating the retrospective or prospective change in adverse health impacts expected to
result from population-level changes in exposure to pollutants (Hubbell et al. 2009b,
2009a). PC-based tools such as the environmental Benefits Mapping and Analysis Program
(BenMAP) can systematize health impact analyses by applying a database of key input
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parameters, including health impact functions and population projections (US EPA).
Analysts have applied the HIA approach to estimate human health impacts resulting from
hypothetical changes in pollutant levels(Davidson et al. 2007; Hubbell et al. 2004; Tagaris
et al. 2009).
The HIA approach used in this analysis involves three basic steps: (1) utilizing
CAMx-generated estimates of PM2.5 levels attributed to each sector; (2) determining the
subsequent change in population-level exposure; (3) calculating health impacts by applying
concentration-response relationships drawn from the epidemiological literature to this
change in population exposure (Hubbell et al. 2004).
This procedure is operationalized within BenMAP using a health impact function (Eq
1). We estimated the number of PM2.5-related total deaths and illnesses (y//) during each
year / (i=2016, 2020, 2025, 2030) among populations in each 12km by 12km air quality
model grid cell j (j=l,...,J where J is the total number of grids) as
yij = Ea yija
yija = mOija x[eP-cj-1) x Pi]aj Eq[l]
where /? is the risk coefficient for all-cause mortality for adults in association with PM2.5
exposure, moija is the baseline all-cause mortality or morbidity rate for populations aged a
in grid cell j in year / stratified in 10-year age bins, Cij is annual mean PM2.5 concentration
in grid cell j, and Pi]a is the number of individuals aged a in grid cell j in year / stratified into
5-year age bins.
Tools such as BenMAP can systematize the HIA calculation process, allowing users to
draw upon a library of existing air quality monitoring data, population data and health
impact functions.
Figure 2 provides a simplified overview of this approach, using PM2.5-related
premature mortality as an example, though the procedure is generally the same for other
health endpoints. This sequence of steps is performed for each of the 17 sectors for each
PM2.5 component (primary PM2.5, sulfate and nitrate). The PM2.5 health endpoints
quantified and the health impact functions applied in this analysis are consistent with the
PM NAAQS RIA (US EPA 2012). That RIA includes a detailed discussion of each of the data
inputs, analytical assumptions and sources of uncertainty. In the interest of brevity, we do
not repeat these here in detail. However, it is worth noting that we exclude the value of
several important non-health endpoints, including recreational and residential visibility,
climate-related impacts and ecological endpoints. Table 2 below summarizes the endpoints
quantified in this benefit per ton TSD.
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Baseline Air Quality Post-Policy Scenario Air Quality
Figure 2. Illustration of the BenMAP-CE Approach to Calculating Cases of Air
Pollution-Related Effects
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Table 2. Human health effects of PM2.5 quantified and not quantified in this analysis
More
Information in
Category
Effect
Quantified Monetized PM NAAQS RIA
Improved Human Health
Reduced incidence
of premature
mortality from
exposure to PM2.5
Adult premature mortality based on
cohort study estimates and expert
elicitation estimates (age >25 or age
>30)
Infant mortality (age <1)
~
~
~
v'
Section 5.6
Section 5.6
Reduced incidence
of morbidity from
exposure to PM2.5
Non-fatal heart attacks (age > 18)
Hospital admissions—respiratory (all
ages)
Hospital admissions—cardiovascular
(age >20)
Emergency room visits for asthma (all
ages)
Acute bronchitis (age 8-12)
Lower respiratory symptoms (age 7-14)
Upper respiratory symptoms
(asthmatics age 9-11)
Asthma exacerbation (asthmatics age 6-
18)
Lost work days (age 18-65)
Minor restricted-activity days (age 18-
65)
Chronic Bronchitis (age >26)
Emergency room visits for
cardiovascular effects (all ages)
Strokes and cerebrovascular disease
(age 50-79)
Other cardiovascular effects (e. g., other
ages)
Other respiratory effects (e.g.,
pulmonary function, non- a ER
visits, non-bronchitis chronic diseases,
other ages and populations)
Reproductive and developmental effects
(e.g., low birth weight, pre-term births,
etc)
Cancer, mutagenicity, and genotoxicity
effects
~
~
~
~
~
~
~
~
~
~
¦/
S
S
s
¦/
s
s
¦/
¦/
Section 5.6
Section 5.6
Section 5.6
Section 5.6
Section 5.6
Section 5.6
Section 5.6
Section 5.6
Section 5.6
Section 5.6
Section 5.6
Section 5.6
Section 5.6
PM ISA2
PM ISA2
PM ISA2.3
PM ISA2.3
1 We assess these benefits qualitatively due to time and resource limitations for this analysis. In the PM NAAQS
RIA, these benefits were quantified in a sensitivity analysis, but not in the core analysis.
2 We assess these benefits qualitatively because we do not have sufficient confidenc e in available data or
methods.
3 We assess these benefits qualitatively because current evidence is only suggestive of causality or there are other
significant concerns over the strength of the association.
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Estimating the economic value of health impacts attributable to each sector
After quantifying the number of adverse air pollution-attributable impacts, the next
step is to estimate the economic value of these events. The appropriate economic value for a
change in a health effect depends on whether the health effect is viewed ex ante (before the
effect has occurred) or ex post (after the effect has occurred). Reductions in ambient
concentrations of air pollution generally lower the risk of future adverse health effects by a
small amount for a large population. The appropriate economic measure is therefore ex
ante Willingness to Pay (WTP) for changes in risk. However, epidemiological studies
generally provide estimates of the relative risks of a particular health effect avoided due to
a reduction in air pollution. A convenient way to use this data in a consistent framework is
to convert probabilities to units of avoided statistical incidences. This measure is calculated
by dividing individual WTP for a risk reduction by the related observed change in risk. For
example, suppose a measure is able to reduce the risk of premature mortality from 2 in
10,000 to 1 in 10,000 (a reduction of 1 in 10,000). If individual WTP for this risk reduction
is $100, then the WTP for an avoided statistical premature mortality amounts to $1 million
($100/0.0001 change in risk). Using this approach, the size of the affected population is
automatically taken into account by the number of incidences predicted by epidemiological
studies applied to the relevant population. The same type of calculation can produce values
for statistical incidences of other health endpoints.
For some health effects, such as hospital admissions, WTP estimates are generally
not available. In these cases, we use the cost of treating or mitigating the effect as a primary
estimate. For example, for the valuation of hospital admissions we use the avoided medical
costs as an estimate of the value of avoiding the health effects causing the admission. These
cost of illness (COI) estimates generally (although not in every case) understate the true
value of reductions in risk of a health effect. They tend to reflect the direct expenditures
related to treatment but not the value of avoided pain and suffering from the health effect.
Avoided premature deaths account for 98% of monetized PM-related benefits. The
economics literature concerning the appropriate method for valuing reductions in
premature mortality risk is still developing. The adoption of a value for the projected
reduction in the risk of premature mortality is the subject of continuing discussion within
the economics and public policy analysis community. Following the advice of the SAB's
Environmental Economics Advisory Committee (SAB-EEAC), the EPA currently uses the
value of statistical life (VSL) approach in calculating estimates of mortality benefits, because
we believe this calculation provides the most reasonable single estimate of an individual's
willingness to trade off money for reductions in mortality risk (U.S. EPA Science Advisory
Board 2000). The VSL approach is a summary measure for the value of small changes in
mortality risk experienced by a large number of people.
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EPA continues work to update its guidance on valuing mortality risk reductions, and
the Agency consulted several times with the SAB-EEAC on the issue. Until updated
guidance is available, the Agency determined that a single, peer-reviewed estimate applied
consistently best reflects the SAB-EEAC advice it has received. Therefore, EPA has decided
to apply the VSL that was vetted and endorsed by the SAB in the Guidelines for Preparing
Economic Analyses (U.S. EPA 2000) while the Agency continues its efforts to update its
guidance on this issue.2 This approach calculates a mean value across VSL estimates
derived from 26 labor market and contingent valuation studies published between 1974
and 1991. The mean VSL across these studies is $6.3 million (2000$).3 We then adjust this
VSL to account for the currency year used for the analysis and to account for income
growth from 1990 to the analysis year. Table 3 shows the adjusted VSL estimates for
currency years 2000-2015 for the income growth years used in the source apportionment
benefit per ton calculations.
Table 3. Value of a Statistical Life Estimate Adjusted for Currency and Income Growth
Years
VSL with Income Growth to:
Currency Year
Base VSL
2016
2020
2026
2000
$6.3
$7.3
$7.4
$7.5
2001
$6.5
$7.5
$7.6
$7.7
2002
$6.6
$7.6
$7.7
$7.9
2003
$6.7
$7.8
$7.9
$8.0
2004
$6.9
$8.0
$8.1
$8.3
2005
$7.1
$8.2
$8.4
$8.5
2006
$7.4
$8.5
$8.6
$8.8
2007
$7.6
$8.7
$8.9
$9.1
2008
$7.9
$9.1
$9.2
$9.4
2009
$7.8
$9.0
$9.2
$9.4
2010
$8.0
$9.2
$9.3
$9.5
2011
$8.2
$9.5
$9.6
$9.8
2012
$8.4
$9.7
$9.8
$10.0
2013
$8.5
$9.8
$10.0
$10.2
2014
$8.7
$10.0
$10.1
$10.3
2015
$8.7
$10.0
$10.2
$10.4
2 In the updated Guidelines for Preparing Economic Analyses (US EPA 2010), EPA retained the VSL endorsed
by the SAB with the understanding that further updates to the mortality risk valuation guidance would be
forthcoming in the near future.
3 In 1990$, this VSLis $4.8 million.
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In valuing premature mortality, we discount the value of premature mortality
occurring in future years using rates of 3% and 7% (OMB 2003). We assume that there is a
"cessation" lag between changes in PM exposures and the total realization of changes in
health effects. Although the structure of the lag is uncertain, the EPA follows the advice of
the SAB-HES to assume a segmented lag structure characterized by 30% of mortality
reductions in the first year, 50% over years 2 to 5, and 20% over the years 6 to 20 after the
reduction in PM2.5 (U.S. EPA Science Advisory Board 2004). Changes in the cessation lag
assumptions do not change the total number of estimated deaths but rather the timing of
those deaths.
We express the economic value of the avoided impacts using constant year 2015
dollars, adjusted for growth in real income out to the analysis year using projections
provided by the Congressional Budget Office. However, these projections are only available
to 2026, so the 2030 estimates use income growth to 2026. Economic theory suggests that
WTP for most goods (such as environmental protection) will increase if real income
increases. Many of the valuation studies used in this analysis were conducted in the late
1980s and early 1990s. Because real income has grown since the studies were conducted,
people's willingness to pay for reductions in the risk of premature death and disease likely
has grown as well. We did not adjust cost of illness-based values because they are based on
current costs. For these two reasons, the cost of illness estimates may underestimate the
economic value of avoided health impacts in each analysis year. As with the selection of
health studies, the economic valuation estimates applied in this analysis are consistent with
those used in the PM NAAQS RIA.
Calculating the benefit per ton estimate
The final step is to divide the incidence of adverse health outcomes, and the
economic value of those outcomes, associated with the primary PM2.5, nitrate and sulfate
attributable to each sector by the sector emissions of directly emitted PM2.5, NOxand SO2.
The result is a suite of incidence per ton and $ benefit per ton estimates for each sector.
Below we summarize the total $ per ton estimates for each of the 17 sectors, with more
detailed health impacts per ton for each sector provided in Appendix A. The results for four
analysis years (2016, 2020, 2025 and 2030) are presented.
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Table 4. Data used for Benefit per Ton Estimates
Analysis
Year
Population Year
Mortality
Incidence Year
Income Growth
Year
Currency
Year
Emissions
Year
2016
2016
2015
2016
2020
2020
2020
2020
2015
2016
2025
2025
2025
2025
2030
2030
2030
2026
Demographic and Socioeconomic Input Parameters Updated in 2017
In 2017, the Agency updated four key input parameters in the BenMAP-CE tool:
1. Projected population. The program projects census-reported 2010 population counts to future
years using projected population counts from the Woods & Poole corporation. We procured
projections developed in the year 2015, which replaced projections last updated in 2012.
2. Baseline and projected death rates. We replaced the existing baseline cause-specific death rates
from the years 2004-2006 with rates from the years 2012-2014. We projected these cause-
specific rates to the year 2060 using life tables provided by the U.S. Census Bureau.
3. Baseline hospital admission rates. We replaced the baseline rates of hospital admissions and
emergency department visits procured from the Healthcare Cost and Utilization Program
(HCUP) for the year 2007 with rates for the year 2014.
4. Estimated changes in future income. We substituted projected data from the Congressional
Budget Office for the existing Standard and Poors data and projected personal income for each
year from 1990 to 2026.
The overall influence on the size of the estimated incidence and economic value of air quality changes
of these four changes is fairly modest; further information may be found in EPA (2017), linked here.
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Results
Table 5. Summary of the total dollar value (mortality and morbidity) per ton of directly emitted PM2.5 and PM2.5
precursor reduced by each of 17 sectors in 2016 (2015$, 3% discount rate)A
Krewski et al. (2009) mortality estimateB Lepeule et al. (2012) mortality estimateB
Sector
Directly emitted
PM2.5
SO2
NOx
Directly emitted
PM2.5
SO2
NOx
Aircraft, locomotives and
$260,000
$89,000
$7,800
$590,000
$200,000
$18,000
marine vessels
Area sources
$350,000
$54,000
$8,600
$800,000
$120,000
$19,000
Cement kilns
$390,000
$48,000
$6,300
$890,000
$110,000
$14,000
Coke ovens
$510,000
$58,000
$12,000
$1,200,000
$130,000
$27,000
Electric arc furnaces
$480,000
$89,000
$11,000
$1,100,000
$200,000
$25,000
Electricity generating units
$140,000
$40,000
$6,000
$330,000
$92,000
$14,000
Ferroalloy facilities
$320,000
$50,000
$5,100
$720,000
$110,000
$12,000
Industrial point sources
$540,000
$97,000
$15,000
$1,200,000
$220,000
$35,000
Integrated iron and steel
$560,000
$450,000
$18,000
$1,300,000
$1,000,000
$41,000
Iron and steel facilities
$340,000
$47,000
$7,400
$760,000
$110,000
$17,000
Non-road mobile sources
$290,000
$45,000
$7,000
$660,000
$100,000
$16,000
Ocean-going vessels
$48,000
$13,000
$2,000
$110,000
$29,000
$4,400
On-road mobile sources
$400,000
$21,000
$8,300
$900,000
$48,000
$19,000
Pulp and paper facilities
$170,000
$50,000
$4,200
$380,000
$120,000
$9,500
Refineries
$350,000
$73,000
$7,300
$790,000
$170,000
$17,000
Residential wood combustion
$400,000
$110,000
$15,000
$900,000
$250,000
$33,000
Taconite mines
$95,000
$38,000
$6,900
$220,000
$87,000
$16,000
A These values represent a national average $/ton of total emissions for each sector; the $/ton for a given location (e.g. state or county) may
be higher or lower than the value reported here. Estimates do not capture important differences in marginal $/ton that may exist due to
different combinations of reductions (i.e., all other sectors are held constant) or nonlinearities within a particular pollutant.
B Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5 mortality risk estimate
noted. Estimates rounded to two significant figures in this table, but all calculations are performed with the unrounded estimates.
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Table 6. Summary of the total dollar value (mortality and morbidity) per ton of directly emitted PM2.5 and PM2.5
precursor reduced by each of 17 sectors in 2016 (2015$, 7% discount rate)A
Krewski et al. (2009) mortality estimateB Lepeule et al. (2012) mortality estimateB
Sector
Directly emitted
PM2.5
SO2
NOx
Directly emitted
PM2.5
SO2
NOx
Aircraft, locomotives and
$240,000
$80,000
$7,000
$540,000
$180,000
$16,000
marine vessels
Area sources
$320,000
$48,000
$7,700
$720,000
$110,000
$18,000
Cement kilns
$350,000
$43,000
$5,700
$810,000
$99,000
$13,000
Coke ovens
$460,000
$52,000
$11,000
$1,000,000
$120,000
$25,000
Electric arc furnaces
$440,000
$81,000
$9,800
$990,000
$180,000
$22,000
Electricity generating units
$130,000
$36,000
$5,400
$300,000
$83,000
$12,000
Ferroalloy facilities
$290,000
$45,000
$4,600
$650,000
$100,000
$10,000
Industrial point sources
$490,000
$88,000
$14,000
$1,100,000
$200,000
$31,000
Integrated iron and steel
$500,000
$410,000
$16,000
$1,100,000
$930,000
$37,000
Iron and steel facilities
$300,000
$43,000
$6,700
$690,000
$97,000
$15,000
Non-road mobile sources
$260,000
$41,000
$6,300
$600,000
$93,000
$14,000
Ocean-going vessels
$44,000
$11,000
$1,800
$99,000
$26,000
$4,000
On-road mobile sources
$360,000
$19,000
$7,500
$810,000
$43,000
$17,000
Pulp and paper facilities
$150,000
$46,000
$3,800
$350,000
$100,000
$8,600
Refineries
$310,000
$66,000
$6,600
$710,000
$150,000
$15,000
Residential wood combustion
$360,000
$98,000
$13,000
$810,000
$220,000
$30,000
Taconite mines
$86,000
$34,000
$6,300
$200,000
$78,000
$14,000
A These values represent a national average $/ton of total emissions for each sector; the $/ton for a given location (e.g. state or county) may
be higher or lower than the value reported here. Estimates do not capture important differences in marginal $/ton that may exist due to
different combinations of reductions (i.e., all other sectors are held constant) or nonlinearities within a particular pollutant.
B Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5 mortality risk estimate
noted. Estimates rounded to two significant figures in this table, but all calculations are performed with the unrounded estimates.
15
-------
Table 7. Summary of the total dollar value (mortality and morbidity) per ton of directly emitted PM2.5 and PM2.5
precursor reduced by each of 17 sectors in 2020 (2015$, 3% discount rate)A
Krewski et al. (2009) mortality estimateB Lepeule et al. (2012) mortality estimateB
Sector
Directly emitted
PM2.5
SO2
NOx
Directly emitted
PM2.5
SO2
NOx
Aircraft, locomotives and
$280,000
$96,000
$8,100
$620,000
$220,000
$18,000
marine vessels
Area sources
$370,000
$56,000
$9,000
$840,000
$130,000
$20,000
Cement kilns
$420,000
$50,000
$6,500
$950,000
$110,000
$15,000
Coke ovens
$520,000
$60,000
$12,000
$1,200,000
$140,000
$28,000
Electric arc furnaces
$500,000
$93,000
$11,000
$1,100,000
$210,000
$26,000
Electricity generating units
$150,000
$42,000
$6,200
$350,000
$96,000
$14,000
Ferroalloy facilities
$330,000
$52,000
$5,200
$750,000
$120,000
$12,000
Industrial point sources
$560,000
$100,000
$16,000
$1,300,000
$230,000
$36,000
Integrated iron and steel
$580,000
$470,000
$19,000
$1,300,000
$1,100,000
$43,000
Iron and steel facilities
$360,000
$51,000
$7,800
$810,000
$120,000
$18,000
Non-road mobile sources
$310,000
$47,000
$7,300
$700,000
$110,000
$17,000
Ocean-going vessels
$52,000
$14,000
$2,100
$120,000
$31,000
$4,700
On-road mobile sources
$420,000
$23,000
$8,700
$950,000
$52,000
$20,000
Pulp and paper facilities
$180,000
$53,000
$4,400
$400,000
$120,000
$9,900
Refineries
$360,000
$77,000
$7,700
$830,000
$180,000
$17,000
Residential wood combustion
$420,000
$110,000
$15,000
$960,000
$260,000
$35,000
Taconite mines
$99,000
$40,000
$7,200
$230,000
$90,000
$16,000
A These values represent a national average $/ton of total emissions for each sector; the $/ton for a given location (e.g. state or county) may
be higher or lower than the value reported here. Estimates do not capture important differences in marginal $/ton that may exist due to
different combinations of reductions (i.e., all other sectors are held constant) or nonlinearities within a particular pollutant.
B Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5 mortality risk estimate
noted. Estimates rounded to two significant figures in this table, but all calculations are performed with the unrounded estimates.
16
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Table 8. Summary of the total dollar value (mortality and morbidity) per ton of directly emitted PM2.5 and PM2.5
precursor reduced by each of 17 sectors in 2020 (2015$, 7% discount rate)A
Krewski et al. (2009) mortality estimateB Lepeule et al. (2012) mortality estimateB
Sector
Directly emitted
PM2.5
SO2
NOx
Directly emitted
PM2.5
SO2
NOx
Aircraft, locomotives and
$250,000
$87,000
$7,300
$560,000
$200,000
$17,000
marine vessels
Area sources
$340,000
$51,000
$8,100
$760,000
$120,000
$18,000
Cement kilns
$380,000
$46,000
$5,900
$850,000
$100,000
$13,000
Coke ovens
$470,000
$54,000
$11,000
$1,100,000
$120,000
$25,000
Electric arc furnaces
$450,000
$84,000
$10,000
$1,000,000
$190,000
$23,000
Electricity generating units
$140,000
$38,000
$5,600
$310,000
$86,000
$13,000
Ferroalloy facilities
$300,000
$47,000
$4,700
$680,000
$110,000
$11,000
Industrial point sources
$500,000
$91,000
$14,000
$1,100,000
$210,000
$32,000
Integrated iron and steel
$520,000
$420,000
$17,000
$1,200,000
$960,000
$39,000
Iron and steel facilities
$320,000
$46,000
$7,000
$730,000
$100,000
$16,000
Non-road mobile sources
$280,000
$43,000
$6,600
$630,000
$97,000
$15,000
Ocean-going vessels
$47,000
$12,000
$1,900
$110,000
$28,000
$4,200
On-road mobile sources
$380,000
$21,000
$7,800
$850,000
$47,000
$18,000
Pulp and paper facilities
$160,000
$48,000
$3,900
$360,000
$110,000
$8,900
Refineries
$330,000
$70,000
$6,900
$750,000
$160,000
$16,000
Residential wood combustion
$380,000
$100,000
$14,000
$860,000
$230,000
$31,000
Taconite mines
$89,000
$36,000
$6,500
$200,000
$81,000
$15,000
A These values represent a national average $/ton of total emissions for each sector; the $/ton for a given location (e.g. state or county) may
be higher or lower than the value reported here. Estimates do not capture important differences in marginal $/ton that may exist due to
different combinations of reductions (i.e., all other sectors are held constant) or nonlinearities within a particular pollutant.
B Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5 mortality risk estimate
noted. Estimates rounded to two significant figures in this table, but all calculations are performed with the unrounded estimates.
17
-------
Table 9. Summary of the total dollar value (mortality and morbidity) per ton of directly emitted PM2.5 and PM2.5
precursor reduced by each of 17 sectors in 2025 (2015$, 3% discount rate)A
Krewski et al. (2009) mortality estimateB Lepeule et al. (2012) mortality estimateB
Sector
Directly emitted
PM2.5
SO2
NOx
Directly emitted
PM2.5
SO2
NOx
Aircraft, locomotives and
$300,000
$110,000
$8,800
$680,000
$240,000
$20,000
marine vessels
Area sources
$410,000
$61,000
$9,700
$920,000
$140,000
$22,000
Cement kilns
$460,000
$55,000
$7,100
$1,000,000
$120,000
$16,000
Coke ovens
$550,000
$65,000
$13,000
$1,300,000
$150,000
$30,000
Electric arc furnaces
$540,000
$100,000
$12,000
$1,200,000
$230,000
$27,000
Electricity generating units
$170,000
$46,000
$6,700
$370,000
$100,000
$15,000
Ferroalloy facilities
$350,000
$56,000
$5,600
$800,000
$130,000
$13,000
Industrial point sources
$590,000
$110,000
$17,000
$1,300,000
$240,000
$38,000
Integrated iron and steel
$620,000
$500,000
$20,000
$1,400,000
$1,100,000
$46,000
Iron and steel facilities
$390,000
$57,000
$8,400
$880,000
$130,000
$19,000
Non-road mobile sources
$330,000
$51,000
$7,900
$760,000
$120,000
$18,000
Ocean-going vessels
$57,000
$15,000
$2,300
$130,000
$34,000
$5,200
On-road mobile sources
$460,000
$25,000
$9,400
$1,000,000
$57,000
$21,000
Pulp and paper facilities
$190,000
$58,000
$4,700
$440,000
$130,000
$11,000
Refineries
$400,000
$85,000
$8,400
$900,000
$190,000
$19,000
Residential wood combustion
$460,000
$130,000
$17,000
$1,000,000
$280,000
$38,000
Taconite mines
$110,000
$43,000
$7,700
$240,000
$97,000
$17,000
A These values represent a national average $/ton of total emissions for each sector; the $/ton for a given location (e.g. state or county) may
be higher or lower than the value reported here. Estimates do not capture important differences in marginal $/ton that may exist due to
different combinations of reductions (i.e., all other sectors are held constant) or nonlinearities within a particular pollutant.
B Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5 mortality risk estimate
noted. Estimates rounded to two significant figures in this table, but all calculations are performed with the unrounded estimates.
18
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Table 10. Summary of the total dollar value (mortality and morbidity) per ton of directly emitted PM2.5 and PM2.5
precursor reduced by each of 17 sectors in 2025 (2015$, 7% discount rate)A
Krewski et al. (2009) mortality estimateB Lepeule et al. (2012) mortality estimateB
Sector
Directly emitted
PM2.5
SO2
NOx
Directly emitted
PM2.5
SO2
NOx
Aircraft, locomotives and
$270,000
$97,000
$8,000
$610,000
$220,000
$18,000
marine vessels
Area sources
$370,000
$55,000
$8,800
$830,000
$120,000
$20,000
Cement kilns
$410,000
$49,000
$6,400
$940,000
$110,000
$14,000
Coke ovens
$500,000
$58,000
$12,000
$1,100,000
$130,000
$27,000
Electric arc furnaces
$480,000
$90,000
$11,000
$1,100,000
$210,000
$25,000
Electricity generating units
$150,000
$41,000
$6,000
$340,000
$93,000
$14,000
Ferroalloy facilities
$320,000
$51,000
$5,100
$720,000
$120,000
$12,000
Industrial point sources
$540,000
$97,000
$15,000
$1,200,000
$220,000
$34,000
Integrated iron and steel
$560,000
$460,000
$18,000
$1,300,000
$1,000,000
$42,000
Iron and steel facilities
$350,000
$51,000
$7,600
$790,000
$120,000
$17,000
Non-road mobile sources
$300,000
$46,000
$7,100
$680,000
$100,000
$16,000
Ocean-going vessels
$51,000
$14,000
$2,100
$120,000
$30,000
$4,700
On-road mobile sources
$410,000
$23,000
$8,500
$930,000
$52,000
$19,000
Pulp and paper facilities
$170,000
$52,000
$4,200
$390,000
$120,000
$9,600
Refineries
$360,000
$76,000
$7,500
$810,000
$170,000
$17,000
Residential wood combustion
$420,000
$110,000
$15,000
$940,000
$260,000
$34,000
Taconite mines
$96,000
$38,000
$6,900
$220,000
$87,000
$16,000
A These values represent a national average $/ton of total emissions for each sector; the $/ton for a given location (e.g. state or county) may
be higher or lower than the value reported here. Estimates do not capture important differences in marginal $/ton that may exist due to
different combinations of reductions (i.e., all other sectors are held constant) or nonlinearities within a particular pollutant.
B Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5 mortality risk estimate
noted. Estimates rounded to two significant figures in this table, but all calculations are performed with the unrounded estimates.
19
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Table 11. Summary of the total dollar value (mortality and morbidity) per ton of directly emitted PM2.5 and PM2.5
precursor reduced by each of 17 sectors in 2030 (2015$, 3% discount rate)A
Krewski et al. (2009) mortality estimateB Lepeule et al. (2012) mortality estimateB
Sector
Directly emitted
PM2.5
SO2
NOx
Directly emitted
PM2.5
SO2
NOx
Aircraft, locomotives and
$330,000
$120,000
$9,600
$740,000
$270,000
$22,000
marine vessels
Area sources
$450,000
$67,000
$11,000
$1,000,000
$150,000
$24,000
Cement kilns
$510,000
$60,000
$7,700
$1,100,000
$130,000
$17,000
Coke ovens
$590,000
$70,000
$14,000
$1,300,000
$160,000
$32,000
Electric arc furnaces
$580,000
$110,000
$13,000
$1,300,000
$250,000
$29,000
Electricity generating units
$180,000
$49,000
$7,200
$410,000
$110,000
$16,000
Ferroalloy facilities
$380,000
$61,000
$6,000
$850,000
$140,000
$14,000
Industrial point sources
$630,000
$120,000
$18,000
$1,400,000
$260,000
$41,000
Integrated iron and steel
$670,000
$540,000
$22,000
$1,500,000
$1,200,000
$50,000
Iron and steel facilities
$430,000
$63,000
$9,200
$970,000
$140,000
$21,000
Non-road mobile sources
$370,000
$56,000
$8,500
$830,000
$130,000
$19,000
Ocean-going vessels
$63,000
$17,000
$2,600
$140,000
$38,000
$5,800
On-road mobile sources
$500,000
$28,000
$10,000
$1,100,000
$64,000
$23,000
Pulp and paper facilities
$210,000
$63,000
$5,100
$470,000
$140,000
$12,000
Refineries
$430,000
$93,000
$9,100
$980,000
$210,000
$21,000
Residential wood combustion
$510,000
$140,000
$18,000
$1,100,000
$310,000
$41,000
Taconite mines
$120,000
$46,000
$8,300
$260,000
$100,000
$19,000
A These values represent a national average $/ton of total emissions for each sector; the $/ton for a given location (e.g. state or county) may
be higher or lower than the value reported here. Estimates do not capture important differences in marginal $/ton that may exist due to
different combinations of reductions (i.e., all other sectors are held constant) or nonlinearities within a particular pollutant.
B Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5 mortality risk estimate
noted. Estimates rounded to two significant figures in this table, but all calculations are performed with the unrounded estimates.
20
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Table 12. Summary of the total dollar value (mortality and morbidity) per ton of directly emitted PM2.5 and PM2.5
precursor reduced by each of 17 sectors in 2030 (2015$, 7% discount rate)A
Krewski et al. (2009) mortality estimate8 Lepeule et al. (2012) mortality estimate8
Sector
Directly emitted
PM2.5
SO2
NOx
Directly emitted
PM2.5
SO2
NOx
Aircraft, locomotives and
$290,000
$110,000
$8,700
$660,000
$240,000
$20,000
marine vessels
Area sources
$400,000
$60,000
$9,500
$910,000
$140,000
$21,000
Cement kilns
$460,000
$54,000
$6,900
$1,000,000
$120,000
$16,000
Coke ovens
$530,000
$63,000
$13,000
$1,200,000
$140,000
$29,000
Electric arc furnaces
$520,000
$98,000
$12,000
$1,200,000
$220,000
$27,000
Electricity generating units
$160,000
$45,000
$6,500
$370,000
$100,000
$15,000
Ferroalloy facilities
$340,000
$55,000
$5,500
$770,000
$130,000
$12,000
Industrial point sources
$570,000
$100,000
$16,000
$1,300,000
$240,000
$37,000
Integrated iron and steel
$610,000
$490,000
$20,000
$1,400,000
$1,100,000
$45,000
Iron and steel facilities
$390,000
$57,000
$8,300
$870,000
$130,000
$19,000
Non-road mobile sources
$330,000
$50,000
$7,700
$750,000
$110,000
$17,000
Ocean-going vessels
$57,000
$15,000
$2,300
$130,000
$34,000
$5,200
On-road mobile sources
$450,000
$25,000
$9,200
$1,000,000
$57,000
$21,000
Pulp and paper facilities
$190,000
$57,000
$4,600
$430,000
$130,000
$10,000
Refineries
$390,000
$84,000
$8,200
$880,000
$190,000
$19,000
Residential wood combustion
$460,000
$120,000
$16,000
$1,000,000
$280,000
$37,000
Taconite mines
$100,000
$42,000
$7,500
$240,000
$94,000
$17,000
A These values represent a national average $/ton of total emissions for each sector; the $/ton for a given location (e.g. state or county) may
be higher or lower than the value reported here. Estimates do not capture important differences in marginal $/ton that may exist due to
different combinations of reductions (i.e., all other sectors are held constant) or nonlinearities within a particular pollutant.
B Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5 mortality risk estimate
noted. Estimates rounded to two significant figures in this table, but all calculations are performed with the unrounded estimates.
21
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Lowest Measured Air Quality Level Exposure Assessment
Assessments quantifying PM2.5 related health impacts generally find that cases of
avoided mortality represent the majority of the monetized benefits. For this reason, EPA
has historically performed a series of analyses that characterize the uncertainty associated
with the PM-mortality relationship and the economic value of reducing the risk of
premature death (Mansfield and Henrion 2009; Roman et al. 2008; US EPA 2012). Here we
focus on the level of uncertainty associated with the avoided premature deaths estimated
to occur due to air quality improvements below the lowest levels of PM2.5 observed in the
epidemiological studies used to quantify such risks.
In general, we are more confident in the magnitude of the risks we estimate from
simulated PM2.5 concentrations that coincide with the bulk of the observed PM
concentrations in the epidemiological studies that are used to estimate the benefits.
Likewise, we are less confident in the risk we estimate from simulated PM2.5 concentrations
that fall below the bulk of the observed data in these studies. Concentration benchmark
analyses (e.g., lowest measured level [LML] or one standard deviation below the mean of
the air quality data in the study) allow readers to determine the portion of population
exposed to annual mean PM2.5 levels at or above different concentrations, which provides
some insight into the level of uncertainty in the estimated PM2.5 mortality benefits. There
are uncertainties inherent in identifying any particular point at which our confidence in
reported associations becomes appreciably less, and the scientific evidence provides no
clear dividing line. However, the EPA does not view these concentration benchmarks as a
concentration threshold below which we would not quantify health benefits of air quality
improvements.4 Rather, the benefits estimates reported are the best available estimates
because they reflect the full range of air quality concentrations associated with the
emission reduction strategies and because the current body of scientific literature indicates
that a no-threshold model provides the best estimate of PM-related long-term mortality. In
other words, although we may have less confidence in the magnitude of the risk at
concentrations below these benchmarks, we still have high confidence that PM2.5 is causally
associated with risk at those lower air quality concentrations.
For a benefit per ton analysis, policy-specific air quality data is not available due to
time or resource limitations. For rules using benefit per ton estimates, we are unable to
estimate the percentage of premature mortality associated with that rule's emission
reductions at each PM2.5 level. However, we believe that it is still important to characterize
4 For a summary of the scientific review statements regarding the lack of a threshold in the PM2.s-mortality
relationship, see the Technical Support Document [TSD] entitled Summary of Expert Opinions on the Existence
of a Threshold in the Concentration-Response Function for PM2.s-related Mortality (US EPA 2010d).
22
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the distribution of exposure to baseline air quality levels as a representation of the starting
point for any marginal reductions in air pollution as a result of sector specific emissions
reductions. As a surrogate measure of mortality impacts, we provide the percentage of the
population exposed at each PM2.5 level in the baseline of the source apportionment
modeling used to calculate the benefit-per-ton estimates for this sector. It is important to
note that baseline exposure is only one parameter in the health impact function, along with
baseline incidence rates population, and change in air quality. In other words, the
percentage of the population exposed to air pollution below the LML is not the same as the
percentage of the population experiencing health impacts as a result of a specific emission
reduction policy. The most important aspect, which we are unable to quantify for rules
without rule-specific air quality modeling, is the shift in exposure associated with a specific
rule. Therefore, caution is warranted when interpreting the LML assessment for any
particular sector rule because these results are not consistent with results from rules that
had air quality modeling.
Table 13 provides the percentage of the population exposed above and below two
concentration benchmarks (i.e., LML and 1 standard deviation below the mean) in the
modeled baseline. Figure 3 shows a bar chart of the percentage of the population exposed
to various air quality levels in the baseline, and Figure 4 shows a cumulative distribution
function of the same data. Both figures identify the LML for each of the major cohort
studies.
Table 13. Population Exposure in the Baseline Above and Below Various
Concentration Benchmarks in the Underlying Epidemiology Studies3
Epidemiology Study
Below 1 Std. Dev.
Below AQ Mean
At or Above 1 Std. Dev.
Below AQ Mean
Below LML
At or Above LML
Krewski et al. (2009)
89%
11%
7%
93%
Lepeule etal. (2012)
N/A
N/A
23%
67%
a One standard deviation below the mean is equivalent to the middle of the range between the 10th and 25th
percentile. For Krewski, the LML is 5.8 ug/ m3 and one standard deviation below the mean is 11.0 ug/m\ For
Lepeule et al., the LML is 8 ug/ m3 and we do not have the data for one standard deviation below the mean. It is
important to emphasize that although we have lower levels of confidence in levels below the LML for each study,
the scientific evidence does not support the existence of a level below which health effects from e xposure to PM2.5
do not occur.
23
-------
0.3
Krewski et a I
(2009)
Lepeule et al.
(2012)
20
PM2 5 {|ig/m~)
Among the populations exposed to PM2.5 in the baseline:
93% are exposed to PM2.5 levels at or above the LML of the Krewski et al. (2009) study
67% are exposed to PM2.5 levels at or above the LML of the Lepeule et al. (2012) study
Figure 3. Percentage of Adult Population by Annual Mean PM2.5 Exposure in
Baseline
24
-------
100%
75%
O
0 50%
CT>
TO
0
> 25%
0%
1
1
1
1
1
1 y
1 /
1 /
1
1
1
1 I
1 /
1 f
1 /
1
1
1
1 /
/ 1
Krewski et al.
1 jl
/
/
1 /
1 /
1
1
1
- Lepeule et al.
(2009)
1 /
1/
/1
(2012)
1
1
1
/ 1
/ 1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
10
15
20
25
PM2_5 (fig/m )
Among the populations exposed to PM2.5 in the baseline:
93% are exposed to PM2.5 levels at or above the LML of the Krewski et al. (2009) study
67% are exposed to PM2.5 levels at or above the LML of the Lepeule et al. (2012) study
Figure 4. Cumulative Distribution of Adult Population by Annual Mean PM2.5
Exposure in the Baseline
Limitations and Uncertainties
This analysis includes many data sources as inputs, including emission inventories,
air quality data from models (with their associated parameters and inputs), population
data, health effect estimates from epidemiology studies, and economic data for monetizing
benefits. Each of these inputs may be uncertain and would affect the benefits estimate.
When the uncertainties from each stage of the analysis are compounded, small
uncertainties can have large effects on the total quantified benefits. This analysis does not
include the type of detailed uncertainty assessment found in the PM NAAQS RIA (EPA
2014; US EPA 2012). However, the results of the Monte Carlo analyses of the health and
welfare benefits presented in the PM RIAs can provide some evidence of the uncertainty
surrounding the benefits results presented in this analysis.
25
-------
In this analysis we assume that all fine particles, regardless of their chemical
composition, are equally potent in causing premature mortality. This is an important
26
-------
assumption, because PM2.5 produced via transported precursors emitted from EGUs may
differ significantly from direct PM2.5 released from other industrial sources. However, the
scientific evidence is not yet sufficient to allow differentiation of effect estimates by particle
type. We also assume that the health impact function for fine particles is linear down to the
lowest air quality levels modeled in this analysis. Thus, the estimates include health
benefits from reducing fine particles in areas with varied concentrations of PM2.5, including
regions that are in attainment with fine particle standard.
It is also important to note that the monetized benefit per ton estimates used here
reflect specific geographic patterns of emissions and specific air quality and benefits
modeling assumptions. Great care should be taken in applying these estimates to emission
reductions occurring in any specific location, as these are all based on national emission
reduction assumptions and therefore represent an average benefit per ton over the entire
United States. The benefit per ton for emission reductions in specific locations may be very
different from the estimates presented here. In addition, estimates do not capture
important differences in marginal benefit per ton that may exist due to different
combinations of reductions (i.e., all other sectors are held constant) or nonlinearities
within a particular pollutant (e.g., non-zero second derivatives with respect to emissions).
The maps in Appendix B provide an indication of the location of the facilities that were
modeled as well as the associated PM2.5 levels.
When using these benefit per ton estimates in analyses, care should be taken to not
overstate the accuracy of the total benefits estimates or estimates of avoided incidence. For
this reason, it is EPA practice to round total benefits estimates to two significant digits and
to round estimates of avoided incidence to the nearest whole number.
27
-------
Appendix A: Detailed Results for Each Sector
28
-------
2016 Analysis Year
29
-------
Table 1: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2016 from the cement kilns sector
(2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$6,300
$48,000
$390,000
Lepeule et al. (2012)
$14,000
$110,000
$890,000
7% Discount Rate
Krewski et al. (2009)
$5,700
$43,000
$350,000
Lepeule et al. (2012)
$13,000
$99,000
$810,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 2: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2016 from the cement kilns
sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.000680
Lepeule et al. (2012) 0.001500
Morbidity
Respiratory emergency room visits 0.000370
Acute bronchitis 0.000960
Lower respiratory symptoms 0.012000
Upper respiratory symptoms 0.017000
Minor Restricted Activity Days 0.510000
Work loss days 0.086000
Asthma exacerbation 0.020000
Cardiovascular hospital admissions 0.000160
Respiratory hospital admissions 0.000150
Non-fatal heart attacks (Peters) 0.000630
Non-fatal heart attacks (All others) 0.000068
0.005200
0.012000
0.002800
0.006700
0.086000
0.120000
3.700000
0.610000
0.140000
0.001200
0.001200
0.004900
0.000530
0.042000
0.097000
0.023000
0.063000
0.810000
1.200000
33.000000
5.500000
1.400000
0.009900
0.009000
0.041000
0.004400
30
-------
Table 3: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2016 from the pulp and paper facilities
sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$4,200
$50,000
$170,000
Lepeule et al. (2012)
$9,500
$120,000
$380,000
7% Discount Rate
Krewski et al. (2009)
$3,800
$46,000
$150,000
Lepeule et al. (2012)
$8,600
$100,000
$350,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 4: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2016 from the pulp and paper
facilities sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.000450
Lepeule et al. (2012) 0.001000
Morbidity
Respiratory emergency room visits 0.000230
Acute bronchitis 0.000580
Lower respiratory symptoms 0.007400
Upper respiratory symptoms 0.011000
Minor Restricted Activity Days 0.320000
Work loss days 0.053000
Asthma exacerbation 0.012000
Cardiovascular hospital admissions 0.000100
Respiratory hospital admissions 0.000095
Non-fatal heart attacks (Peters) 0.000410
Non-fatal heart attacks (All others) 0.000044
0.005500
0.013000
0.002700
0.006800
0.087000
0.120000
3.700000
0.620000
0.150000
0.001300
0.001200
0.005300
0.000570
0.018000
0.042000
0.008300
0.023000
0.290000
0.410000
12.000000
2.000000
0.480000
0.004400
0.004100
0.018000
0.001900
31
-------
Table 5: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2016 from the refineries sector (2015$)
Pollutant emitted
N0X
S02
Directly emitted
PM2.5
3% Discount Rate
Krewski et al. (2009)
$7,300
$73,000
$350,000
Lepeule et al. (2012)
$17,000
$170,000
$790,000
7% Discount Rate
Krewski et al. (2009)
$6,600
$66,000
$310,000
Lepeule et al. (2012)
$15,000
$150,000
$710,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 6: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2016 from the refineries sector
Pollutant emitted
Directly emitted
Health Endpoint N0X SO2 PM2.5
Premature mortality
Krewski et al. (2009) 0.000790
Lepeule et al. (2012) 0.001800
Morbidity
Respiratory emergency room visits 0.000420
Acute bronchitis 0.001200
Lower respiratory symptoms 0.016000
Upper respiratory symptoms 0.022000
Minor Restricted Activity Days 0.660000
Work loss days 0.110000
Asthma exacerbation 0.026000
Cardiovascular hospital admissions 0.000190
Respiratory hospital admissions 0.000180
Non-fatal heart attacks (Peters) 0.000750
Non-fatal heart attacks (All others) 0.000080
0.007900
0.018000
0.004400
0.012000
0.160000
0.220000
6.600000
1.100000
0.260000
0.001900
0.001800
0.007600
0.000820
0.037000
0.085000
0.022000
0.058000
0.730000
1.000000
31.000000
5.200000
1.200000
0.008800
0.008200
0.035000
0.003800
32
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Table 7: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2016 from the coke ovens sector (2015$)
Pollutant emitted
N0X
S02
Directly emitted
PM2.5
3% Discount Rate
Krewski et al. (2009)
$12,000
$58,000
$510,000
Lepeule et al. (2012)
$27,000
$130,000
$1,200,000
7% Discount Rate
Krewski et al. (2009)
$11,000
$52,000
$460,000
Lepeule et al. (2012)
$25,000
$120,000
$1,000,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 8: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2016 from the coke ovens sector
Pollutant emitted
Directly emitted
Health Endpoint N0X SO2 PM2.5
Premature mortality
Krewski et al. (2009) 0.001300
Lepeule et al. (2012) 0.003000
Morbidity
Respiratory emergency room visits 0.000680
Acute bronchitis 0.001600
Lower respiratory symptoms 0.020000
Upper respiratory symptoms 0.029000
Minor Restricted Activity Days 0.880000
Work loss days 0.150000
Asthma exacerbation 0.034000
Cardiovascular hospital admissions 0.000300
Respiratory hospital admissions 0.000280
Non-fatal heart attacks (Peters) 0.001200
Non-fatal heart attacks (All others) 0.000130
0.006300
0.014000
0.003000
0.007600
0.097000
0.140000
4.200000
0.700000
0.160000
0.001500
0.001400
0.006100
0.000660
0.055000
0.130000
0.025000
0.063000
0.800000
1.100000
35.000000
5.800000
1.300000
0.013000
0.012000
0.051000
0.005500
33
-------
Table 9: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2016 from the iron and steel facilities
sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$18,000
$450,000
$560,000
Lepeule et al. (2012)
$41,000
$1,000,000
$1,300,000
7% Discount Rate
Krewski et al. (2009)
$16,000
$410,000
$500,000
Lepeule et al. (2012)
$37,000
$930,000
$1,100,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 10: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2016 from the iron and steel
facilities sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.001900
Lepeule et al. (2012) 0.004400
Morbidity
Respiratory emergency room visits 0.001100
Acute bronchitis 0.003000
Lower respiratory symptoms 0.038000
Upper respiratory symptoms 0.054000
Minor Restricted Activity Days 1.600000
Work loss days 0.270000
Asthma exacerbation 0.064000
Cardiovascular hospital admissions 0.000470
Respiratory hospital admissions 0.000440
Non-fatal heart attacks (Peters) 0.001900
Non-fatal heart attacks (All others) 0.000200
0.049000
0.110000
0.024000
0.063000
0.800000
1.100000
35.000000
5.900000
1.300000
0.011000
0.011000
0.047000
0.005000
0.060000
0.140000
0.029000
0.082000
1.000000
1.500000
45.000000
7.500000
1.800000
0.014000
0.014000
0.059000
0.006400
34
-------
Table 11: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2016 from the integrated iron and steel
facilities sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$15,000
$97,000
$540,000
Lepeule et al. (2012)
$35,000
$220,000
$1,200,000
7% Discount Rate
Krewski et al. (2009)
$14,000
$88,000
$490,000
Lepeule et al. (2012)
$31,000
$200,000
$1,100,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 12: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2016 from the integrated iron
and steel facilities sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.001600
Lepeule et al. (2012) 0.003800
Morbidity
Respiratory emergency room visits 0.000830
Acute bronchitis 0.002100
Lower respiratory symptoms 0.026000
Upper respiratory symptoms 0.038000
Minor Restricted Activity Days 1.100000
Work loss days 0.190000
Asthma exacerbation 0.044000
Cardiovascular hospital admissions 0.000380
Respiratory hospital admissions 0.000360
Non-fatal heart attacks (Peters) 0.001500
Non-fatal heart attacks (All others) 0.000160
0.011000
0.024000
0.005500
0.013000
0.170000
0.240000
7.200000
1.200000
0.280000
0.002500
0.002500
0.010000
0.001100
0.059000
0.130000
0.028000
0.072000
0.910000
1.300000
39.000000
6.500000
1.500000
0.014000
0.013000
0.056000
0.006000
35
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Table 13: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2016 from the electric arc furnaces
sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$11,000
$89,000
$480,000
Lepeule et al. (2012)
$25,000
$200,000
$1,100,000
7% Discount Rate
Krewski et al. (2009)
$9,800
$81,000
$440,000
Lepeule et al. (2012)
$22,000
$180,000
$990,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 14: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2016 from the electric arc
furnaces sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.001200
Lepeule et al. (2012) 0.002700
Morbidity
Respiratory emergency room visits 0.000640
Acute bronchitis 0.001500
Lower respiratory symptoms 0.019000
Upper respiratory symptoms 0.028000
Minor Restricted Activity Days 0.820000
Work loss days 0.140000
Asthma exacerbation 0.033000
Cardiovascular hospital admissions 0.000270
Respiratory hospital admissions 0.000260
Non-fatal heart attacks (Peters) 0.001100
Non-fatal heart attacks (All others) 0.000120
0.009700
0.022000
0.004700
0.012000
0.150000
0.210000
6.400000
1.100000
0.250000
0.002300
0.002300
0.009800
0.001100
0.052000
0.120000
0.026000
0.063000
0.800000
1.100000
34.000000
5.700000
1.300000
0.013000
0.012000
0.054000
0.005900
36
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Table 15: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2016 from the taconite mines sector
(2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$6,900
$38,000
$95,000
Lepeule et al. (2012)
$16,000
$87,000
$220,000
7% Discount Rate
Krewski et al. (2009)
$6,300
$34,000
$86,000
Lepeule et al. (2012)
$14,000
$78,000
$200,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 16: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2016 from the taconite mines
sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.000750
Lepeule et al. (2012) 0.001700
Morbidity
Respiratory emergency room visits 0.000350
Acute bronchitis 0.000960
Lower respiratory symptoms 0.012000
Upper respiratory symptoms 0.017000
Minor Restricted Activity Days 0.530000
Work loss days 0.088000
Asthma exacerbation 0.020000
Cardiovascular hospital admissions 0.000160
Respiratory hospital admissions 0.000150
Non-fatal heart attacks (Peters) 0.000670
Non-fatal heart attacks (All others) 0.000072
0.004100
0.009400
0.001900
0.005100
0.065000
0.093000
2.800000
0.470000
0.110000
0.000920
0.000880
0.003800
0.000410
0.010000
0.024000
0.004300
0.012000
0.160000
0.220000
6.700000
1.100000
0.260000
0.002200
0.002100
0.009600
0.001000
37
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Table 17: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2016 from the ferroalloy facilities sector
(2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$5,100
$50,000
$320,000
Lepeule et al. (2012)
$12,000
$110,000
$720,000
7% Discount Rate
Krewski et al. (2009)
$4,600
$45,000
$290,000
Lepeule et al. (2012)
$10,000
$100,000
$650,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 18: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2016 from the ferroalloy
facilities sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.000550
Lepeule et al. (2012) 0.001300
Morbidity
Respiratory emergency room visits 0.000230
Acute bronchitis 0.000600
Lower respiratory symptoms 0.007700
Upper respiratory symptoms 0.011000
Minor Restricted Activity Days 0.340000
Work loss days 0.057000
Asthma exacerbation 0.013000
Cardiovascular hospital admissions 0.000120
Respiratory hospital admissions 0.000110
Non-fatal heart attacks (Peters) 0.000500
Non-fatal heart attacks (All others) 0.000054
0.005400
0.012000
0.002400
0.006300
0.081000
0.120000
3.500000
0.580000
0.140000
0.001300
0.001300
0.005500
0.000590
0.034000
0.079000
0.016000
0.040000
0.510000
0.730000
22.000000
3.700000
0.860000
0.008100
0.007900
0.035000
0.003800
38
-------
Table 19: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2016 from the residential wood
combustion sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$15,000
$110,000
$400,000
Lepeule et al. (2012)
$33,000
$250,000
$900,000
7% Discount Rate
Krewski et al. (2009)
$13,000
$98,000
$360,000
Lepeule et al. (2012)
$30,000
$220,000
$810,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 20: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2016 from the residential wood
combustion sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.001600
Lepeule et al. (2012) 0.003600
Morbidity
Respiratory emergency room visits 0.000850
Acute bronchitis 0.002300
Lower respiratory symptoms 0.029000
Upper respiratory symptoms 0.042000
Minor Restricted Activity Days 1.200000
Work loss days 0.210000
Asthma exacerbation 0.049000
Cardiovascular hospital admissions 0.000350
Respiratory hospital admissions 0.000330
Non-fatal heart attacks (Peters) 0.001400
Non-fatal heart attacks (All others) 0.000160
0.012000
0.027000
0.006000
0.016000
0.210000
0.300000
9.200000
1.500000
0.350000
0.002600
0.002400
0.011000
0.001100
0.043000
0.098000
0.022000
0.061000
0.770000
1.100000
34.000000
5.700000
1.300000
0.009600
0.008900
0.039000
0.004300
39
-------
Table 21: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2016 from the area sources sector
(2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$8,600
$54,000
$350,000
Lepeule et al. (2012)
$19,000
$120,000
$800,000
7% Discount Rate
Krewski et al. (2009)
$7,700
$48,000
$320,000
Lepeule et al. (2012)
$18,000
$110,000
$720,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 22: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2016 from the area sources
sector
Health Endpoint
N0X
Pollutant emitted
S02
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009)
Lepeule et al. (2012)
Morbidity
Respiratory emergency room visits
Acute bronchitis
Lower respiratory symptoms
Upper respiratory symptoms
Minor Restricted Activity Days
Work loss days
Asthma exacerbation
Cardiovascular hospital admissions
Respiratory hospital admissions
Non-fatal heart attacks (Peters)
Non-fatal heart attacks (All others)
0.000930
0.002100
0.000520
0.001400
0.017000
0.025000
0.720000
0.120000
0.029000
0.000210
0.000200
0.000860
0.000092
0.005800
0.013000
0.003400
0.007900
0.100000
0.150000
4.400000
0.740000
0.170000
0.001400
0.001300
0.005500
0.000600
0.038000
0.087000
0.022000
0.054000
0.690000
0.990000
30.000000
5.100000
1.200000
0.009100
0.008600
0.036000
0.003900
40
-------
Table 23: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2016 from the industrial point sources
sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$7,000
$45,000
$290,000
Lepeule et al. (2012)
$16,000
$100,000
$660,000
7% Discount Rate
Krewski et al. (2009)
$6,300
$41,000
$260,000
Lepeule et al. (2012)
$14,000
$93,000
$600,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 24: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2016 from the industrial point
sources sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.000760
Lepeule et al. (2012) 0.001700
Morbidity
Respiratory emergency room visits 0.000400
Acute bronchitis 0.001100
Lower respiratory symptoms 0.014000
Upper respiratory symptoms 0.020000
Minor Restricted Activity Days 0.570000
Work loss days 0.096000
Asthma exacerbation 0.023000
Cardiovascular hospital admissions 0.000170
Respiratory hospital admissions 0.000170
Non-fatal heart attacks (Peters) 0.000710
Non-fatal heart attacks (All others) 0.000076
0.004900
0.011000
0.002600
0.006400
0.082000
0.120000
3.500000
0.580000
0.140000
0.001200
0.001100
0.004700
0.000510
0.031000
0.072000
0.017000
0.044000
0.560000
0.800000
24.000000
4.000000
0.940000
0.007600
0.007200
0.031000
0.003300
41
-------
Table 25: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2016 from the aircraft, locomotives and
marine vessels sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$7,800
$89,000
$260,000
Lepeule et al. (2012)
$18,000
$200,000
$590,000
7% Discount Rate
Krewski et al. (2009)
$7,000
$80,000
$240,000
Lepeule et al. (2012)
$16,000
$180,000
$540,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 26: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2016 from the aircraft,
locomotives and marine vessels sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.000840
Lepeule et al. (2012) 0.001900
Morbidity
Respiratory emergency room visits 0.000430
Acute bronchitis 0.001200
Lower respiratory symptoms 0.016000
Upper respiratory symptoms 0.022000
Minor Restricted Activity Days 0.660000
Work loss days 0.110000
Asthma exacerbation 0.026000
Cardiovascular hospital admissions 0.000200
Respiratory hospital admissions 0.000190
Non-fatal heart attacks (Peters) 0.000800
Non-fatal heart attacks (All others) 0.000086
0.009600
0.022000
0.005200
0.017000
0.220000
0.310000
9.600000
1.600000
0.370000
0.002500
0.002200
0.009500
0.001000
0.028000
0.064000
0.016000
0.040000
0.520000
0.740000
23.000000
3.900000
0.870000
0.006800
0.006400
0.027000
0.002900
42
-------
Table 27: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2016 from the non-road mobile sources
sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$7,400
$47,000
$340,000
Lepeule et al. (2012)
$17,000
$110,000
$760,000
7% Discount Rate
Krewski et al. (2009)
$6,700
$43,000
$300,000
Lepeule et al. (2012)
$15,000
$97,000
$690,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 28: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2016 from the non-road mobile
sources sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.000800
Lepeule et al. (2012) 0.001800
Morbidity
Respiratory emergency room visits 0.000440
Acute bronchitis 0.001200
Lower respiratory symptoms 0.016000
Upper respiratory symptoms 0.022000
Minor Restricted Activity Days 0.650000
Work loss days 0.110000
Asthma exacerbation 0.026000
Cardiovascular hospital admissions 0.000190
Respiratory hospital admissions 0.000180
Non-fatal heart attacks (Peters) 0.000760
Non-fatal heart attacks (All others) 0.000082
0.005100
0.012000
0.002800
0.008700
0.110000
0.160000
4.300000
0.730000
0.180000
0.001100
0.001000
0.004500
0.000490
0.036000
0.083000
0.022000
0.053000
0.680000
0.970000
30.000000
5.000000
1.100000
0.008900
0.008300
0.035000
0.003800
43
-------
Table 29: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2016 from the on-road mobile sources
sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$8,300
$21,000
$400,000
Lepeule et al. (2012)
$19,000
$48,000
$900,000
7% Discount Rate
Krewski et al. (2009)
$7,500
$19,000
$360,000
Lepeule et al. (2012)
$17,000
$43,000
$810,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 30: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2016 from the on-road mobile
sources sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.000890
Lepeule et al. (2012) 0.002000
Morbidity
Respiratory emergency room visits 0.000490
Acute bronchitis 0.001300
Lower respiratory symptoms 0.016000
Upper respiratory symptoms 0.024000
Minor Restricted Activity Days 0.690000
Work loss days 0.120000
Asthma exacerbation 0.028000
Cardiovascular hospital admissions 0.000210
Respiratory hospital admissions 0.000200
Non-fatal heart attacks (Peters) 0.000840
Non-fatal heart attacks (All others) 0.000091
0.002300
0.005200
0.001200
0.003800
0.048000
0.069000
1.900000
0.330000
0.081000
0.000500
0.000480
0.002000
0.000220
0.043000
0.097000
0.025000
0.064000
0.810000
1.200000
35.000000
5.900000
1.400000
0.010000
0.009800
0.041000
0.004500
44
-------
Table 31: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2016 from the electricity generating
units sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$6,000
$40,000
$140,000
Lepeule et al. (2012)
$14,000
$92,000
$330,000
7% Discount Rate
Krewski et al. (2009)
$5,400
$36,000
$130,000
Lepeule et al. (2012)
$12,000
$83,000
$300,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 32: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2016 from the electricity
generating units sector
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009)
0.000650
0.004400
0.016000
Lepeule et al. (2012)
0.001500
0.010000
0.036000
Morbidity
Respiratory emergency room visits
0.000320
0.002200
0.008800
Acute bronchitis
0.000850
0.005400
0.021000
Lower respiratory symptoms
0.011000
0.070000
0.270000
Upper respiratory symptoms
0.016000
0.100000
0.390000
Minor Restricted Activity Days
0.450000
3.000000
12.000000
Work loss days
0.076000
0.500000
1.900000
Asthma exacerbation
0.018000
0.120000
0.450000
Cardiovascular hospital admissions
0.000150
0.001000
0.003700
Respiratory hospital admissions
0.000140
0.001000
0.003500
Non-fatal heart attacks (Peters)
0.000600
0.004200
0.015000
Non-fatal heart attacks (All others)
0.000064
0.000460
0.001600
45
-------
Table 33: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2016 from the ocean-going vessels sector
(2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$2,000
$13,000
$48,000
Lepeule et al. (2012)
$4,400
$29,000
$110,000
7% Discount Rate
Krewski et al. (2009)
$1,800
$11,000
$44,000
Lepeule et al. (2012)
$4,000
$26,000
$99,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 34: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2016 from the ocean-going
vessels sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.000210
Lepeule et al. (2012) 0.000480
Morbidity
Respiratory emergency room visits 0.000130
Acute bronchitis 0.000360
Lower respiratory symptoms 0.004600
Upper respiratory symptoms 0.006600
Minor Restricted Activity Days 0.200000
Work loss days 0.034000
Asthma exacerbation 0.007800
Cardiovascular hospital admissions 0.000054
Respiratory hospital admissions 0.000050
Non-fatal heart attacks (Peters) 0.000210
Non-fatal heart attacks (All others) 0.000023
0.001400
0.003100
0.000760
0.001900
0.024000
0.034000
1.100000
0.180000
0.040000
0.000340
0.000320
0.001300
0.000140
0.005200
0.012000
0.002900
0.007500
0.095000
0.140000
4.300000
0.720000
0.160000
0.001300
0.001200
0.005000
0.000540
46
-------
2020 Analysis Year
47
-------
Table 35: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2020 from the cement kilns sector
(2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$6,500
$50,000
$420,000
Lepeule et al. (2012)
$15,000
$110,000
$950,000
7% Discount Rate
Krewski et al. (2009)
$5,900
$46,000
$380,000
Lepeule et al. (2012)
$13,000
$100,000
$850,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 36: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2020 from the cement kilns
sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.000700
Lepeule et al. (2012) 0.001600
Morbidity
Respiratory emergency room visits 0.000380
Acute bronchitis 0.000960
Lower respiratory symptoms 0.012000
Upper respiratory symptoms 0.017000
Minor Restricted Activity Days 0.520000
Work loss days 0.088000
Asthma exacerbation 0.020000
Cardiovascular hospital admissions 0.000170
Respiratory hospital admissions 0.000160
Non-fatal heart attacks (Peters) 0.000670
Non-fatal heart attacks (All others) 0.000072
0.005400
0.012000
0.002800
0.006800
0.086000
0.120000
3.700000
0.620000
0.140000
0.001300
0.001300
0.005300
0.000570
0.044000
0.100000
0.023000
0.064000
0.810000
1.200000
34.000000
5.700000
1.400000
0.011000
0.009900
0.044000
0.004800
48
-------
Table 37: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2020 from the pulp and paper facilities
sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$4,400
$53,000
$180,000
Lepeule et al. (2012)
$9,900
$120,000
$400,000
7% Discount Rate
Krewski et al. (2009)
$3,900
$48,000
$160,000
Lepeule et al. (2012)
$8,900
$110,000
$360,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 38: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2020 from the pulp and paper
facilities sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.000460
Lepeule et al. (2012) 0.001100
Morbidity
Respiratory emergency room visits 0.000240
Acute bronchitis 0.000580
Lower respiratory symptoms 0.007400
Upper respiratory symptoms 0.011000
Minor Restricted Activity Days 0.320000
Work loss days 0.054000
Asthma exacerbation 0.012000
Cardiovascular hospital admissions 0.000110
Respiratory hospital admissions 0.000100
Non-fatal heart attacks (Peters) 0.000440
Non-fatal heart attacks (All others) 0.000047
0.005700
0.013000
0.002800
0.006900
0.088000
0.130000
3.800000
0.640000
0.150000
0.001400
0.001400
0.005700
0.000620
0.019000
0.043000
0.008600
0.023000
0.290000
0.420000
12.000000
2.100000
0.480000
0.004700
0.004500
0.019000
0.002100
49
-------
Table 39: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2020 from the refineries sector (2015$)
Pollutant emitted
N0X
S02
Directly emitted
PM2.5
3% Discount Rate
Krewski et al. (2009)
$7,700
$77,000
$360,000
Lepeule et al. (2012)
$17,000
$180,000
$830,000
7% Discount Rate
Krewski et al. (2009)
$6,900
$70,000
$330,000
Lepeule et al. (2012)
$16,000
$160,000
$750,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 40: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2020 from the refineries sector
Pollutant emitted
Directly emitted
Health Endpoint N0X SO2 PM2.5
Premature mortality
Krewski et al. (2009) 0.000820
Lepeule et al. (2012) 0.001900
Morbidity
Respiratory emergency room visits 0.000440
Acute bronchitis 0.001200
Lower respiratory symptoms 0.016000
Upper respiratory symptoms 0.023000
Minor Restricted Activity Days 0.660000
Work loss days 0.110000
Asthma exacerbation 0.026000
Cardiovascular hospital admissions 0.000200
Respiratory hospital admissions 0.000190
Non-fatal heart attacks (Peters) 0.000800
Non-fatal heart attacks (All others) 0.000087
0.008200
0.019000
0.004500
0.012000
0.160000
0.220000
6.700000
1.100000
0.260000
0.002100
0.002000
0.008200
0.000890
0.039000
0.088000
0.022000
0.059000
0.750000
1.100000
31.000000
5.300000
1.200000
0.009500
0.008900
0.038000
0.004100
50
-------
Table 41: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2020 from the coke ovens sector (2015$)
Pollutant emitted
N0X
S02
Directly emitted
PM2.5
3% Discount Rate
Krewski et al. (2009)
$12,000
$60,000
$520,000
Lepeule et al. (2012)
$28,000
$140,000
$1,200,000
7% Discount Rate
Krewski et al. (2009)
$11,000
$54,000
$470,000
Lepeule et al. (2012)
$25,000
$120,000
$1,100,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 42: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2020 from the coke ovens sector
Pollutant emitted
Directly emitted
Health Endpoint N0X SO2 PM2.5
Premature mortality
Krewski et al. (2009) 0.001300
Lepeule et al. (2012) 0.003000
Morbidity
Respiratory emergency room visits 0.000690
Acute bronchitis 0.001600
Lower respiratory symptoms 0.020000
Upper respiratory symptoms 0.028000
Minor Restricted Activity Days 0.870000
Work loss days 0.150000
Asthma exacerbation 0.033000
Cardiovascular hospital admissions 0.000310
Respiratory hospital admissions 0.000300
Non-fatal heart attacks (Peters) 0.001200
Non-fatal heart attacks (All others) 0.000130
0.006400
0.015000
0.003100
0.007600
0.096000
0.140000
4.200000
0.700000
0.160000
0.001600
0.001600
0.006500
0.000700
0.056000
0.130000
0.025000
0.062000
0.800000
1.100000
34.000000
5.800000
1.300000
0.013000
0.013000
0.054000
0.005800
51
-------
Table 43: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2020 from the iron and steel facilities
sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$19,000
$470,000
$580,000
Lepeule et al. (2012)
$43,000
$1,100,000
$1,300,000
7% Discount Rate
Krewski et al. (2009)
$17,000
$420,000
$520,000
Lepeule et al. (2012)
$39,000
$960,000
$1,200,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 44: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2020 from the iron and steel
facilities sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.002000
Lepeule et al. (2012) 0.004600
Morbidity
Respiratory emergency room visits 0.001100
Acute bronchitis 0.003000
Lower respiratory symptoms 0.038000
Upper respiratory symptoms 0.055000
Minor Restricted Activity Days 1.600000
Work loss days 0.270000
Asthma exacerbation 0.064000
Cardiovascular hospital admissions 0.000510
Respiratory hospital admissions 0.000480
Non-fatal heart attacks (Peters) 0.002000
Non-fatal heart attacks (All others) 0.000220
0.050000
0.110000
0.024000
0.063000
0.800000
1.100000
35.000000
5.900000
1.300000
0.012000
0.012000
0.050000
0.005400
0.062000
0.140000
0.030000
0.082000
1.000000
1.500000
45.000000
7.600000
1.800000
0.015000
0.015000
0.063000
0.006800
52
-------
Table 45: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2020 from the integrated iron and steel
facilities sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$16,000
$100,000
$560,000
Lepeule et al. (2012)
$36,000
$230,000
$1,300,000
7% Discount Rate
Krewski et al. (2009)
$14,000
$91,000
$500,000
Lepeule et al. (2012)
$32,000
$210,000
$1,100,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 46: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2020 from the integrated iron
and steel facilities sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.001700
Lepeule et al. (2012) 0.003800
Morbidity
Respiratory emergency room visits 0.000840
Acute bronchitis 0.002100
Lower respiratory symptoms 0.026000
Upper respiratory symptoms 0.037000
Minor Restricted Activity Days 1.100000
Work loss days 0.190000
Asthma exacerbation 0.044000
Cardiovascular hospital admissions 0.000400
Respiratory hospital admissions 0.000390
Non-fatal heart attacks (Peters) 0.001600
Non-fatal heart attacks (All others) 0.000170
0.011000
0.024000
0.005600
0.013000
0.170000
0.240000
7.100000
1.200000
0.280000
0.002700
0.002600
0.011000
0.001200
0.059000
0.140000
0.029000
0.071000
0.900000
1.300000
38.000000
6.500000
1.500000
0.015000
0.014000
0.059000
0.006300
53
-------
Table 47: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2020 from the electric arc furnaces
sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$11,000
$93,000
$500,000
Lepeule et al. (2012)
$26,000
$210,000
$1,100,000
7% Discount Rate
Krewski et al. (2009)
$10,000
$84,000
$450,000
Lepeule et al. (2012)
$23,000
$190,000
$1,000,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 48: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2020 from the electric arc
furnaces sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.001200
Lepeule et al. (2012) 0.002700
Morbidity
Respiratory emergency room visits 0.000650
Acute bronchitis 0.001500
Lower respiratory symptoms 0.019000
Upper respiratory symptoms 0.028000
Minor Restricted Activity Days 0.830000
Work loss days 0.140000
Asthma exacerbation 0.032000
Cardiovascular hospital admissions 0.000290
Respiratory hospital admissions 0.000280
Non-fatal heart attacks (Peters) 0.001200
Non-fatal heart attacks (All others) 0.000120
0.009900
0.023000
0.004800
0.012000
0.150000
0.210000
6.500000
1.100000
0.250000
0.002500
0.002400
0.010000
0.001100
0.053000
0.120000
0.026000
0.063000
0.800000
1.100000
34.000000
5.800000
1.300000
0.013000
0.013000
0.057000
0.006200
54
-------
Table 49: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2020 from the taconite mines sector
(2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$7,200
$40,000
$99,000
Lepeule et al. (2012)
$16,000
$90,000
$230,000
7% Discount Rate
Krewski et al. (2009)
$6,500
$36,000
$89,000
Lepeule et al. (2012)
$15,000
$81,000
$200,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 50: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2020 from the taconite mines
sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.000770
Lepeule et al. (2012) 0.001800
Morbidity
Respiratory emergency room visits 0.000360
Acute bronchitis 0.000950
Lower respiratory symptoms 0.012000
Upper respiratory symptoms 0.017000
Minor Restricted Activity Days 0.520000
Work loss days 0.088000
Asthma exacerbation 0.020000
Cardiovascular hospital admissions 0.000170
Respiratory hospital admissions 0.000160
Non-fatal heart attacks (Peters) 0.000710
Non-fatal heart attacks (All others) 0.000076
0.004200
0.009600
0.002000
0.005100
0.065000
0.092000
2.800000
0.470000
0.110000
0.000990
0.000950
0.004100
0.000440
0.011000
0.024000
0.004400
0.012000
0.160000
0.220000
6.700000
1.100000
0.260000
0.002400
0.002300
0.010000
0.001100
55
-------
Table 51: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2020 from the ferroalloy facilities sector
(2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$5,200
$52,000
$330,000
Lepeule et al. (2012)
$12,000
$120,000
$750,000
7% Discount Rate
Krewski et al. (2009)
$4,700
$47,000
$300,000
Lepeule et al. (2012)
$11,000
$110,000
$680,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 52: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2020 from the ferroalloy
facilities sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.000560
Lepeule et al. (2012) 0.001300
Morbidity
Respiratory emergency room visits 0.000230
Acute bronchitis 0.000600
Lower respiratory symptoms 0.007700
Upper respiratory symptoms 0.011000
Minor Restricted Activity Days 0.340000
Work loss days 0.058000
Asthma exacerbation 0.013000
Cardiovascular hospital admissions 0.000130
Respiratory hospital admissions 0.000120
Non-fatal heart attacks (Peters) 0.000530
Non-fatal heart attacks (All others) 0.000058
0.005600
0.013000
0.002500
0.006400
0.081000
0.120000
3.500000
0.590000
0.140000
0.001400
0.001400
0.005900
0.000630
0.035000
0.080000
0.016000
0.040000
0.510000
0.730000
22.000000
3.700000
0.860000
0.008600
0.008500
0.037000
0.004000
56
-------
Table 53: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2020 from the residential wood
combustion sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$15,000
$110,000
$420,000
Lepeule et al. (2012)
$35,000
$260,000
$960,000
7% Discount Rate
Krewski et al. (2009)
$14,000
$100,000
$380,000
Lepeule et al. (2012)
$31,000
$230,000
$860,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 54: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2020 from the residential wood
combustion sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.001600
Lepeule et al. (2012) 0.003700
Morbidity
Respiratory emergency room visits 0.000870
Acute bronchitis 0.002300
Lower respiratory symptoms 0.029000
Upper respiratory symptoms 0.042000
Minor Restricted Activity Days 1.200000
Work loss days 0.210000
Asthma exacerbation 0.049000
Cardiovascular hospital admissions 0.000380
Respiratory hospital admissions 0.000350
Non-fatal heart attacks (Peters) 0.001600
Non-fatal heart attacks (All others) 0.000170
0.012000
0.028000
0.006200
0.017000
0.210000
0.300000
9.300000
1.600000
0.350000
0.002800
0.002600
0.012000
0.001200
0.045000
0.100000
0.023000
0.061000
0.780000
1.100000
34.000000
5.800000
1.300000
0.010000
0.009700
0.043000
0.004600
57
-------
Table 55: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2020 from the area sources sector
(2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$9,000
$56,000
$370,000
Lepeule et al. (2012)
$20,000
$130,000
$840,000
7% Discount Rate
Krewski et al. (2009)
$8,100
$51,000
$340,000
Lepeule et al. (2012)
$18,000
$120,000
$760,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 56: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2020 from the area sources
sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009)
0.000950
0.006000
0.040000
Lepeule et al. (2012)
0.002200
0.014000
0.090000
Morbidity
Respiratory emergency room visits
0.000530
0.003500
0.023000
Acute bronchitis
0.001400
0.008000
0.054000
Lower respiratory symptoms
0.017000
0.100000
0.700000
Upper respiratory symptoms
0.025000
0.150000
1.000000
Minor Restricted Activity Days
0.730000
4.500000
30.000000
Work loss days
0.120000
0.760000
5.200000
Asthma exacerbation
0.029000
0.170000
1.200000
Cardiovascular hospital admissions
0.000230
0.001500
0.009800
Respiratory hospital admissions
0.000220
0.001500
0.009400
Non-fatal heart attacks (Peters)
0.000920
0.006000
0.039000
Non-fatal heart attacks (All others)
0.000099
0.000650
0.004200
58
-------
Table 57: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2020 from the industrial point sources
sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$7,300
$47,000
$310,000
Lepeule et al. (2012)
$17,000
$110,000
$700,000
7% Discount Rate
Krewski et al. (2009)
$6,600
$43,000
$280,000
Lepeule et al. (2012)
$15,000
$97,000
$630,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 58: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2020 from the industrial point
sources sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.000780
Lepeule et al. (2012) 0.001800
Morbidity
Respiratory emergency room visits 0.000410
Acute bronchitis 0.001100
Lower respiratory symptoms 0.014000
Upper respiratory symptoms 0.020000
Minor Restricted Activity Days 0.570000
Work loss days 0.097000
Asthma exacerbation 0.023000
Cardiovascular hospital admissions 0.000190
Respiratory hospital admissions 0.000180
Non-fatal heart attacks (Peters) 0.000750
Non-fatal heart attacks (All others) 0.000081
0.005000
0.011000
0.002700
0.006400
0.082000
0.120000
3.500000
0.590000
0.140000
0.001300
0.001200
0.005100
0.000550
0.033000
0.074000
0.017000
0.044000
0.560000
0.810000
24.000000
4.100000
0.940000
0.008200
0.007900
0.033000
0.003600
59
-------
Table 59: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2020 from the aircraft, locomotives and
marine vessels sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$8,100
$96,000
$280,000
Lepeule et al. (2012)
$18,000
$220,000
$620,000
7% Discount Rate
Krewski et al. (2009)
$7,300
$87,000
$250,000
Lepeule et al. (2012)
$17,000
$200,000
$560,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 60: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2020 from the aircraft,
locomotives and marine vessels sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.000860
Lepeule et al. (2012) 0.002000
Morbidity
Respiratory emergency room visits 0.000450
Acute bronchitis 0.001200
Lower respiratory symptoms 0.016000
Upper respiratory symptoms 0.022000
Minor Restricted Activity Days 0.670000
Work loss days 0.110000
Asthma exacerbation 0.026000
Cardiovascular hospital admissions 0.000210
Respiratory hospital admissions 0.000200
Non-fatal heart attacks (Peters) 0.000860
Non-fatal heart attacks (All others) 0.000092
0.010000
0.023000
0.005400
0.018000
0.220000
0.320000
9.800000
1.700000
0.370000
0.002700
0.002500
0.010000
0.001100
0.029000
0.067000
0.016000
0.041000
0.520000
0.750000
23.000000
3.900000
0.880000
0.007300
0.007000
0.029000
0.003100
60
-------
Table 61: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2020 from the non-road mobile sources
sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$7,800
$51,000
$360,000
Lepeule et al. (2012)
$18,000
$120,000
$810,000
7% Discount Rate
Krewski et al. (2009)
$7,000
$46,000
$320,000
Lepeule et al. (2012)
$16,000
$100,000
$730,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 62: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2020 from the non-road mobile
sources sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.000820
Lepeule et al. (2012) 0.001900
Morbidity
Respiratory emergency room visits 0.000450
Acute bronchitis 0.001200
Lower respiratory symptoms 0.016000
Upper respiratory symptoms 0.022000
Minor Restricted Activity Days 0.660000
Work loss days 0.110000
Asthma exacerbation 0.026000
Cardiovascular hospital admissions 0.000200
Respiratory hospital admissions 0.000190
Non-fatal heart attacks (Peters) 0.000820
Non-fatal heart attacks (All others) 0.000088
0.005400
0.012000
0.003000
0.008800
0.110000
0.160000
4.500000
0.760000
0.190000
0.001200
0.001100
0.005000
0.000530
0.038000
0.086000
0.023000
0.054000
0.690000
0.980000
30.000000
5.100000
1.200000
0.009600
0.009000
0.038000
0.004100
61
-------
Table 63: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2020 from the on-road mobile sources
sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$8,700
$23,000
$420,000
Lepeule et al. (2012)
$20,000
$52,000
$950,000
7% Discount Rate
Krewski et al. (2009)
$7,800
$21,000
$380,000
Lepeule et al. (2012)
$18,000
$47,000
$850,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 64: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2020 from the on-road mobile
sources sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.000920
Lepeule et al. (2012) 0.002100
Morbidity
Respiratory emergency room visits 0.000500
Acute bronchitis 0.001300
Lower respiratory symptoms 0.016000
Upper respiratory symptoms 0.024000
Minor Restricted Activity Days 0.700000
Work loss days 0.120000
Asthma exacerbation 0.028000
Cardiovascular hospital admissions 0.000220
Respiratory hospital admissions 0.000210
Non-fatal heart attacks (Peters) 0.000900
Non-fatal heart attacks (All others) 0.000097
0.002400
0.005500
0.001300
0.003900
0.049000
0.070000
2.000000
0.340000
0.082000
0.000550
0.000530
0.002200
0.000240
0.044000
0.100000
0.026000
0.064000
0.820000
1.200000
36.000000
6.100000
1.400000
0.011000
0.011000
0.045000
0.004800
62
-------
Table 65: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2020 from the electricity generating
units sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$6,200
$42,000
$150,000
Lepeule et al. (2012)
$14,000
$96,000
$350,000
7% Discount Rate
Krewski et al. (2009)
$5,600
$38,000
$140,000
Lepeule et al. (2012)
$13,000
$86,000
$310,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 66: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2020 from the electricity
generating units sector
Pollutant emitted
Directly emitted
Health Endpoint N0X SO2 PM2.5
Premature mortality
Krewski et al. (2009) 0.000660 0.004500 0.016000
Lepeuleetal. (2012) 0.001500 0.010000 0.037000
Morbidity
Respiratory emergency room visits 0.000320 0.002200 0.009100
Acute bronchitis 0.000850 0.005500 0.021000
Lower respiratory symptoms 0.011000 0.070000 0.270000
Upper respiratory symptoms 0.016000 0.100000 0.390000
Minor Restricted Activity Days 0.460000 3.000000 12.000000
Work loss days 0.077000 0.510000 2.000000
Asthma exacerbation 0.018000 0.120000 0.460000
Cardiovascular hospital admissions 0.000160 0.001100 0.004000
Respiratory hospital admissions 0.000150 0.001100 0.003800
Non-fatal heart attacks (Peters) 0.000630 0.004500 0.016000
Non-fatal heart attacks (All others) 0.000068 0.000490 0.001700
63
-------
Table 67: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2020 from the ocean-going vessels sector
(2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$2,100
$14,000
$52,000
Lepeule et al. (2012)
$4,700
$31,000
$120,000
7% Discount Rate
Krewski et al. (2009)
$1,900
$12,000
$47,000
Lepeule et al. (2012)
$4,200
$28,000
$110,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 68: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2020 from the ocean-going
vessels sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.000220
Lepeule et al. (2012) 0.000500
Morbidity
Respiratory emergency room visits 0.000130
Acute bronchitis 0.000370
Lower respiratory symptoms 0.004700
Upper respiratory symptoms 0.006700
Minor Restricted Activity Days 0.210000
Work loss days 0.035000
Asthma exacerbation 0.007800
Cardiovascular hospital admissions 0.000059
Respiratory hospital admissions 0.000054
Non-fatal heart attacks (Peters) 0.000230
Non-fatal heart attacks (All others) 0.000025
0.001400
0.003300
0.000790
0.001900
0.024000
0.035000
1.100000
0.190000
0.041000
0.000370
0.000350
0.001400
0.000150
0.005500
0.012000
0.003000
0.007600
0.097000
0.140000
4.300000
0.740000
0.160000
0.001400
0.001300
0.005400
0.000580
64
-------
2025 Analysis Year
65
-------
Table 69: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2025 from the cement kilns sector
(2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$7,100
$55,000
$460,000
Lepeule et al. (2012)
$16,000
$120,000
$1,000,000
7% Discount Rate
Krewski et al. (2009)
$6,400
$49,000
$410,000
Lepeule et al. (2012)
$14,000
$110,000
$940,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 70: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2025 from the cement kilns
sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.000740
Lepeule et al. (2012) 0.001700
Morbidity
Respiratory emergency room visits 0.000400
Acute bronchitis 0.001000
Lower respiratory symptoms 0.013000
Upper respiratory symptoms 0.018000
Minor Restricted Activity Days 0.520000
Work loss days 0.089000
Asthma exacerbation 0.021000
Cardiovascular hospital admissions 0.000180
Respiratory hospital admissions 0.000180
Non-fatal heart attacks (Peters) 0.000730
Non-fatal heart attacks (All others) 0.000079
0.005700
0.013000
0.002900
0.007100
0.090000
0.130000
3.700000
0.640000
0.150000
0.001500
0.001400
0.005800
0.000620
0.048000
0.110000
0.025000
0.067000
0.850000
1.200000
35.000000
5.900000
1.400000
0.012000
0.011000
0.049000
0.005300
66
-------
Table 71: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2025 from the pulp and paper facilities
sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$4,700
$58,000
$190,000
Lepeule et al. (2012)
$11,000
$130,000
$440,000
7% Discount Rate
Krewski et al. (2009)
$4,200
$52,000
$170,000
Lepeule et al. (2012)
$9,600
$120,000
$390,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 72: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2025 from the pulp and paper
facilities sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.000490
Lepeule et al. (2012) 0.001100
Morbidity
Respiratory emergency room visits 0.000240
Acute bronchitis 0.000610
Lower respiratory symptoms 0.007800
Upper respiratory symptoms 0.011000
Minor Restricted Activity Days 0.320000
Work loss days 0.054000
Asthma exacerbation 0.013000
Cardiovascular hospital admissions 0.000120
Respiratory hospital admissions 0.000110
Non-fatal heart attacks (Peters) 0.000480
Non-fatal heart attacks (All others) 0.000052
0.006000
0.014000
0.002900
0.007200
0.092000
0.130000
3.800000
0.650000
0.150000
0.001600
0.001500
0.006300
0.000670
0.020000
0.046000
0.009000
0.024000
0.310000
0.430000
12.000000
2.100000
0.510000
0.005200
0.005000
0.021000
0.002300
67
-------
Table 73: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2025 from the refineries sector (2015$)
Pollutant emitted
N0X
S02
Directly emitted
PM2.5
3% Discount Rate
Krewski et al. (2009)
$8,400
$85,000
$400,000
Lepeule et al. (2012)
$19,000
$190,000
$900,000
7% Discount Rate
Krewski et al. (2009)
$7,500
$76,000
$360,000
Lepeule et al. (2012)
$17,000
$170,000
$810,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 74: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2025 from the refineries sector
Pollutant emitted
Directly emitted
Health Endpoint N0X SO2 PM2.5
Premature mortality
Krewski et al. (2009) 0.000870
Lepeule et al. (2012) 0.002000
Morbidity
Respiratory emergency room visits 0.000450
Acute bronchitis 0.001300
Lower respiratory symptoms 0.016000
Upper respiratory symptoms 0.023000
Minor Restricted Activity Days 0.670000
Work loss days 0.110000
Asthma exacerbation 0.027000
Cardiovascular hospital admissions 0.000220
Respiratory hospital admissions 0.000210
Non-fatal heart attacks (Peters) 0.000880
Non-fatal heart attacks (All others) 0.000095
0.008800
0.020000
0.004700
0.013000
0.160000
0.230000
6.800000
1.200000
0.280000
0.002300
0.002200
0.009100
0.000990
0.041000
0.094000
0.023000
0.061000
0.780000
1.100000
32.000000
5.400000
1.300000
0.010000
0.010000
0.041000
0.004500
68
-------
Table 75: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2025 from the coke ovens sector (2015$)
Pollutant emitted
N0X
S02
Directly emitted
PM2.5
3% Discount Rate
Krewski et al. (2009)
$13,000
$65,000
$550,000
Lepeule et al. (2012)
$30,000
$150,000
$1,300,000
7% Discount Rate
Krewski et al. (2009)
$12,000
$58,000
$500,000
Lepeule et al. (2012)
$27,000
$130,000
$1,100,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 76: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2025 from the coke ovens sector
Pollutant emitted
Directly emitted
Health Endpoint N0X SO2 PM2.5
Premature mortality
Krewski et al. (2009) 0.001400
Lepeule et al. (2012) 0.003100
Morbidity
Respiratory emergency room visits 0.000700
Acute bronchitis 0.001600
Lower respiratory symptoms 0.021000
Upper respiratory symptoms 0.029000
Minor Restricted Activity Days 0.860000
Work loss days 0.150000
Asthma exacerbation 0.035000
Cardiovascular hospital admissions 0.000340
Respiratory hospital admissions 0.000330
Non-fatal heart attacks (Peters) 0.001300
Non-fatal heart attacks (All others) 0.000140
0.006700
0.015000
0.003200
0.007900
0.100000
0.140000
4.200000
0.710000
0.170000
0.001700
0.001700
0.007000
0.000750
0.058000
0.130000
0.025000
0.065000
0.820000
1.200000
34.000000
5.700000
1.400000
0.014000
0.014000
0.057000
0.006100
69
-------
Table 77: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2025 from the iron and steel facilities
sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$20,000
$500,000
$620,000
Lepeule et al. (2012)
$46,000
$1,100,000
$1,400,000
7% Discount Rate
Krewski et al. (2009)
$18,000
$460,000
$560,000
Lepeule et al. (2012)
$42,000
$1,000,000
$1,300,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 78: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2025 from the iron and steel
facilities sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.002100
Lepeule et al. (2012) 0.004900
Morbidity
Respiratory emergency room visits 0.001100
Acute bronchitis 0.003100
Lower respiratory symptoms 0.040000
Upper respiratory symptoms 0.056000
Minor Restricted Activity Days 1.600000
Work loss days 0.280000
Asthma exacerbation 0.066000
Cardiovascular hospital admissions 0.000560
Respiratory hospital admissions 0.000530
Non-fatal heart attacks (Peters) 0.002200
Non-fatal heart attacks (All others) 0.000240
0.053000
0.120000
0.025000
0.066000
0.840000
1.200000
35.000000
5.900000
1.400000
0.013000
0.013000
0.054000
0.005800
0.065000
0.150000
0.031000
0.086000
1.100000
1.600000
45.000000
7.700000
1.800000
0.017000
0.016000
0.069000
0.007400
70
-------
Table 79: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2025 from the integrated iron and steel
facilities sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$17,000
$110,000
$590,000
Lepeule et al. (2012)
$38,000
$240,000
$1,300,000
7% Discount Rate
Krewski et al. (2009)
$15,000
$97,000
$540,000
Lepeule et al. (2012)
$34,000
$220,000
$1,200,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 80: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2025 from the integrated iron
and steel facilities sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.001800
Lepeule et al. (2012) 0.004000
Morbidity
Respiratory emergency room visits 0.000860
Acute bronchitis 0.002100
Lower respiratory symptoms 0.027000
Upper respiratory symptoms 0.038000
Minor Restricted Activity Days 1.100000
Work loss days 0.190000
Asthma exacerbation 0.045000
Cardiovascular hospital admissions 0.000440
Respiratory hospital admissions 0.000420
Non-fatal heart attacks (Peters) 0.001700
Non-fatal heart attacks (All others) 0.000190
0.011000
0.026000
0.005700
0.014000
0.170000
0.250000
7.100000
1.200000
0.290000
0.002900
0.002900
0.012000
0.001200
0.062000
0.140000
0.029000
0.073000
0.930000
1.300000
38.000000
6.400000
1.600000
0.016000
0.015000
0.063000
0.006800
71
-------
Table 81: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2025 from the electric arc furnaces
sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$12,000
$100,000
$540,000
Lepeule et al. (2012)
$27,000
$230,000
$1,200,000
7% Discount Rate
Krewski et al. (2009)
$11,000
$90,000
$480,000
Lepeule et al. (2012)
$25,000
$210,000
$1,100,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 82: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2025 from the electric arc
furnaces sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.001300
Lepeule et al. (2012) 0.002900
Morbidity
Respiratory emergency room visits 0.000670
Acute bronchitis 0.001600
Lower respiratory symptoms 0.020000
Upper respiratory symptoms 0.029000
Minor Restricted Activity Days 0.820000
Work loss days 0.140000
Asthma exacerbation 0.034000
Cardiovascular hospital admissions 0.000310
Respiratory hospital admissions 0.000300
Non-fatal heart attacks (Peters) 0.001200
Non-fatal heart attacks (All others) 0.000130
0.010000
0.024000
0.005000
0.012000
0.160000
0.220000
6.500000
1.100000
0.260000
0.002700
0.002700
0.011000
0.001200
0.056000
0.130000
0.027000
0.066000
0.830000
1.200000
34.000000
5.800000
1.400000
0.015000
0.014000
0.062000
0.006600
72
-------
Table 83: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2025 from the taconite mines sector
(2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$7,700
$43,000
$110,000
Lepeule et al. (2012)
$17,000
$97,000
$240,000
7% Discount Rate
Krewski et al. (2009)
$6,900
$38,000
$96,000
Lepeule et al. (2012)
$16,000
$87,000
$220,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 84: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2025 from the taconite mines
sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.000800
Lepeule et al. (2012) 0.001800
Morbidity
Respiratory emergency room visits 0.000370
Acute bronchitis 0.001000
Lower respiratory symptoms 0.013000
Upper respiratory symptoms 0.018000
Minor Restricted Activity Days 0.520000
Work loss days 0.088000
Asthma exacerbation 0.021000
Cardiovascular hospital admissions 0.000190
Respiratory hospital admissions 0.000180
Non-fatal heart attacks (Peters) 0.000770
Non-fatal heart attacks (All others) 0.000082
0.004500
0.010000
0.002000
0.005300
0.067000
0.096000
2.800000
0.470000
0.110000
0.001100
0.001000
0.004400
0.000480
0.011000
0.025000
0.004600
0.013000
0.160000
0.230000
6.700000
1.100000
0.270000
0.002600
0.002500
0.011000
0.001200
73
-------
Table 85: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2025 from the ferroalloy facilities sector
(2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$5,600
$56,000
$350,000
Lepeule et al. (2012)
$13,000
$130,000
$800,000
7% Discount Rate
Krewski et al. (2009)
$5,100
$51,000
$320,000
Lepeule et al. (2012)
$12,000
$120,000
$720,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 86: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2025 from the ferroalloy
facilities sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.000590
Lepeule et al. (2012) 0.001300
Morbidity
Respiratory emergency room visits 0.000240
Acute bronchitis 0.000630
Lower respiratory symptoms 0.008000
Upper respiratory symptoms 0.011000
Minor Restricted Activity Days 0.340000
Work loss days 0.058000
Asthma exacerbation 0.013000
Cardiovascular hospital admissions 0.000140
Respiratory hospital admissions 0.000140
Non-fatal heart attacks (Peters) 0.000580
Non-fatal heart attacks (All others) 0.000062
0.005900
0.013000
0.002600
0.006700
0.085000
0.120000
3.500000
0.600000
0.140000
0.001500
0.001500
0.006400
0.000690
0.037000
0.084000
0.017000
0.042000
0.540000
0.760000
22.000000
3.700000
0.900000
0.009400
0.009400
0.040000
0.004300
74
-------
Table 87: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2025 from the residential wood
combustion sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$17,000
$130,000
$460,000
Lepeule et al. (2012)
$38,000
$280,000
$1,000,000
7% Discount Rate
Krewski et al. (2009)
$15,000
$110,000
$420,000
Lepeule et al. (2012)
$34,000
$260,000
$940,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 88: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2025 from the residential wood
combustion sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.001700
Lepeule et al. (2012) 0.004000
Morbidity
Respiratory emergency room visits 0.000900
Acute bronchitis 0.002400
Lower respiratory symptoms 0.031000
Upper respiratory symptoms 0.044000
Minor Restricted Activity Days 1.300000
Work loss days 0.210000
Asthma exacerbation 0.051000
Cardiovascular hospital admissions 0.000420
Respiratory hospital admissions 0.000390
Non-fatal heart attacks (Peters) 0.001700
Non-fatal heart attacks (All others) 0.000180
0.013000
0.030000
0.006500
0.017000
0.220000
0.310000
9.500000
1.600000
0.370000
0.003100
0.002900
0.013000
0.001400
0.048000
0.110000
0.024000
0.064000
0.820000
1.200000
35.000000
5.900000
1.400000
0.012000
0.011000
0.047000
0.005100
75
-------
Table 89: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2025 from the area sources sector
(2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$9,700
$61,000
$410,000
Lepeule et al. (2012)
$22,000
$140,000
$920,000
7% Discount Rate
Krewski et al. (2009)
$8,800
$55,000
$370,000
Lepeule et al. (2012)
$20,000
$120,000
$830,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 90: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2025 from the area sources
sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.001000
Lepeule et al. (2012) 0.002300
Morbidity
Respiratory emergency room visits 0.000550
Acute bronchitis 0.001400
Lower respiratory symptoms 0.018000
Upper respiratory symptoms 0.026000
Minor Restricted Activity Days 0.730000
Work loss days 0.120000
Asthma exacerbation 0.030000
Cardiovascular hospital admissions 0.000250
Respiratory hospital admissions 0.000240
Non-fatal heart attacks (Peters) 0.001000
Non-fatal heart attacks (All others) 0.000110
0.006400
0.015000
0.003700
0.008400
0.110000
0.150000
4.500000
0.770000
0.180000
0.001700
0.001600
0.006500
0.000710
0.043000
0.096000
0.024000
0.057000
0.730000
1.000000
31.000000
5.300000
1.200000
0.011000
0.011000
0.043000
0.004700
76
-------
Table 91: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2025 from the industrial point sources
sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$7,900
$51,000
$330,000
Lepeule et al. (2012)
$18,000
$120,000
$760,000
7% Discount Rate
Krewski et al. (2009)
$7,100
$46,000
$300,000
Lepeule et al. (2012)
$16,000
$100,000
$680,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 92: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2025 from the industrial point
sources sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.000820
Lepeule et al. (2012) 0.001900
Morbidity
Respiratory emergency room visits 0.000420
Acute bronchitis 0.001100
Lower respiratory symptoms 0.014000
Upper respiratory symptoms 0.020000
Minor Restricted Activity Days 0.580000
Work loss days 0.098000
Asthma exacerbation 0.024000
Cardiovascular hospital admissions 0.000200
Respiratory hospital admissions 0.000200
Non-fatal heart attacks (Peters) 0.000820
Non-fatal heart attacks (All others) 0.000088
0.005400
0.012000
0.002800
0.006800
0.086000
0.120000
3.600000
0.610000
0.140000
0.001400
0.001400
0.005500
0.000600
0.035000
0.079000
0.018000
0.047000
0.590000
0.840000
25.000000
4.200000
0.990000
0.009100
0.008800
0.036000
0.003900
77
-------
Table 93: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2025 from the aircraft, locomotives and
marine vessels sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$8,800
$110,000
$300,000
Lepeule et al. (2012)
$20,000
$240,000
$680,000
7% Discount Rate
Krewski et al. (2009)
$8,000
$97,000
$270,000
Lepeule et al. (2012)
$18,000
$220,000
$610,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 94: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2025 from the aircraft,
locomotives and marine vessels sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009)
0.000920
0.011000
0.031000
Lepeule et al. (2012)
0.002100
0.025000
0.071000
Morbidity
Respiratory emergency room visits
0.000460
0.005700
0.017000
Acute bronchitis
0.001300
0.018000
0.043000
Lower respiratory symptoms
0.016000
0.230000
0.550000
Upper respiratory symptoms
0.023000
0.330000
0.780000
Minor Restricted Activity Days
0.670000
10.000000
23.000000
Work loss days
0.110000
1.700000
4.000000
Asthma exacerbation
0.027000
0.390000
0.920000
Cardiovascular hospital admissions
0.000230
0.003100
0.008100
Respiratory hospital admissions
0.000230
0.002800
0.007800
Non-fatal heart attacks (Peters)
0.000940
0.012000
0.032000
Non-fatal heart attacks (All others)
0.000100
0.001300
0.003400
78
-------
Table 95: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2025 from the non-road mobile sources
sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$8,400
$57,000
$390,000
Lepeule et al. (2012)
$19,000
$130,000
$880,000
7% Discount Rate
Krewski et al. (2009)
$7,600
$51,000
$350,000
Lepeule et al. (2012)
$17,000
$120,000
$790,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 96: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2025 from the non-road mobile
sources sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.000880
Lepeule et al. (2012) 0.002000
Morbidity
Respiratory emergency room visits 0.000470
Acute bronchitis 0.001300
Lower respiratory symptoms 0.016000
Upper respiratory symptoms 0.023000
Minor Restricted Activity Days 0.670000
Work loss days 0.110000
Asthma exacerbation 0.027000
Cardiovascular hospital admissions 0.000220
Respiratory hospital admissions 0.000210
Non-fatal heart attacks (Peters) 0.000900
Non-fatal heart attacks (All others) 0.000097
0.005900
0.013000
0.003200
0.009300
0.120000
0.170000
4.700000
0.800000
0.200000
0.001300
0.001300
0.005600
0.000600
0.041000
0.092000
0.024000
0.057000
0.720000
1.000000
31.000000
5.300000
1.200000
0.011000
0.010000
0.041000
0.004500
79
-------
Table 97: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2025 from the on-road mobile sources
sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$9,400
$25,000
$460,000
Lepeule et al. (2012)
$21,000
$57,000
$1,000,000
7% Discount Rate
Krewski et al. (2009)
$8,500
$23,000
$410,000
Lepeule et al. (2012)
$19,000
$52,000
$930,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 98: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2025 from the on-road mobile
sources sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.000980
Lepeule et al. (2012) 0.002200
Morbidity
Respiratory emergency room visits 0.000520
Acute bronchitis 0.001300
Lower respiratory symptoms 0.017000
Upper respiratory symptoms 0.025000
Minor Restricted Activity Days 0.700000
Work loss days 0.120000
Asthma exacerbation 0.029000
Cardiovascular hospital admissions 0.000250
Respiratory hospital admissions 0.000240
Non-fatal heart attacks (Peters) 0.000980
Non-fatal heart attacks (All others) 0.000110
0.002600
0.006000
0.001400
0.004100
0.052000
0.074000
2.100000
0.350000
0.087000
0.000620
0.000600
0.002500
0.000270
0.048000
0.110000
0.027000
0.067000
0.860000
1.200000
36.000000
6.200000
1.400000
0.012000
0.012000
0.049000
0.005300
80
-------
Table 99: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2025 from the electricity generating
units sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$6,700
$46,000
$170,000
Lepeule et al. (2012)
$15,000
$100,000
$370,000
7% Discount Rate
Krewski et al. (2009)
$6,000
$41,000
$150,000
Lepeule et al. (2012)
$14,000
$93,000
$340,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 100: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2025 from the electricity
generating units sector
Pollutant emitted
Directly emitted
Health Endpoint N0X SO2 PM2.5
Premature mortality
Krewski et al. (2009) 0.000700 0.004800 0.017000
Lepeuleetal. (2012) 0.001600 0.011000 0.039000
Morbidity
Respiratory emergency room visits 0.000330 0.002300 0.009400
Acute bronchitis 0.000890 0.005700 0.022000
Lower respiratory symptoms 0.011000 0.073000 0.290000
Upper respiratory symptoms 0.016000 0.100000 0.410000
Minor Restricted Activity Days 0.460000 3.000000 12.000000
Work loss days 0.077000 0.520000 2.000000
Asthma exacerbation 0.019000 0.120000 0.480000
Cardiovascular hospital admissions 0.000170 0.001200 0.004400
Respiratory hospital admissions 0.000170 0.001200 0.004300
Non-fatal heart attacks (Peters) 0.000680 0.004900 0.018000
Non-fatal heart attacks (All others) 0.000074 0.000540 0.001900
81
-------
Table 101: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2025 from the ocean-going vessels sector
(2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$2,300
$15,000
$57,000
Lepeule et al. (2012)
$5,200
$34,000
$130,000
7% Discount Rate
Krewski et al. (2009)
$2,100
$14,000
$51,000
Lepeule et al. (2012)
$4,700
$30,000
$120,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 102: Incidence of avoided mortalities and morbidities per ton
emitted PM2.5 and PM2.5 precursors reduced in 2025 from the ocean-
vessels sector
Pollutant emitted
Health Endpoint
N0X
S02
of directly
going
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.000240
Lepeule et al. (2012) 0.000540
Morbidity
Respiratory emergency room visits 0.000140
Acute bronchitis 0.000380
Lower respiratory symptoms 0.004900
Upper respiratory symptoms 0.007000
Minor Restricted Activity Days 0.210000
Work loss days 0.036000
Asthma exacerbation 0.008200
Cardiovascular hospital admissions 0.000066
Respiratory hospital admissions 0.000062
Non-fatal heart attacks (Peters) 0.000260
Non-fatal heart attacks (All others) 0.000028
0.001600
0.003500
0.000840
0.002000
0.026000
0.037000
1.100000
0.190000
0.043000
0.000420
0.000400
0.001600
0.000170
0.005900
0.013000
0.003200
0.008000
0.100000
0.140000
4.400000
0.750000
0.170000
0.001500
0.001400
0.006000
0.000650
82
-------
2030 Analysis Year
83
-------
Table 103: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2030 from the cement kilns sector
(2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$7,700
$60,000
$510,000
Lepeule et al. (2012)
$17,000
$130,000
$1,100,000
7% Discount Rate
Krewski et al. (2009)
$6,900
$54,000
$460,000
Lepeule et al. (2012)
$16,000
$120,000
$1,000,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 104: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2030 from the cement kilns
sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.000780
Lepeule et al. (2012) 0.001800
Morbidity
Respiratory emergency room visits 0.000410
Acute bronchitis 0.001100
Lower respiratory symptoms 0.014000
Upper respiratory symptoms 0.020000
Minor Restricted Activity Days 0.530000
Work loss days 0.090000
Asthma exacerbation 0.023000
Cardiovascular hospital admissions 0.000200
Respiratory hospital admissions 0.000200
Non-fatal heart attacks (Peters) 0.000800
Non-fatal heart attacks (All others) 0.000086
0.006100
0.014000
0.003100
0.007700
0.098000
0.140000
3.800000
0.650000
0.160000
0.001600
0.001500
0.006300
0.000680
0.052000
0.120000
0.026000
0.074000
0.940000
1.300000
36.000000
6.100000
1.500000
0.013000
0.013000
0.055000
0.005900
84
-------
Table 105: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2030 from the pulp and paper facilities
sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$5,100
$63,000
$210,000
Lepeule et al. (2012)
$12,000
$140,000
$470,000
7% Discount Rate
Krewski et al. (2009)
$4,600
$57,000
$190,000
Lepeule et al. (2012)
$10,000
$130,000
$430,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 106: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2030 from the pulp and paper
facilities sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.000520
Lepeule et al. (2012) 0.001200
Morbidity
Respiratory emergency room visits 0.000250
Acute bronchitis 0.000660
Lower respiratory symptoms 0.008400
Upper respiratory symptoms 0.012000
Minor Restricted Activity Days 0.320000
Work loss days 0.055000
Asthma exacerbation 0.014000
Cardiovascular hospital admissions 0.000130
Respiratory hospital admissions 0.000120
Non-fatal heart attacks (Peters) 0.000520
Non-fatal heart attacks (All others) 0.000056
0.006500
0.015000
0.003000
0.007800
0.100000
0.140000
3.900000
0.670000
0.160000
0.001700
0.001700
0.006800
0.000730
0.021000
0.049000
0.009300
0.026000
0.330000
0.470000
13.000000
2.200000
0.540000
0.005700
0.005500
0.023000
0.002500
85
-------
Table 107: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2030 from the refineries sector (2015$)
Pollutant emitted
N0X
S02
Directly emitted
PM2.5
3% Discount Rate
Krewski et al. (2009)
$9,100
$93,000
$430,000
Lepeule et al. (2012)
$21,000
$210,000
$980,000
7% Discount Rate
Krewski et al. (2009)
$8,200
$84,000
$390,000
Lepeule et al. (2012)
$19,000
$190,000
$880,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 108: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2030 from the refineries sector
Pollutant emitted
Directly emitted
Health Endpoint N0X SO2 PM2.5
Premature mortality
Krewski et al. (2009) 0.000940
Lepeule et al. (2012) 0.002100
Morbidity
Respiratory emergency room visits 0.000470
Acute bronchitis 0.001400
Lower respiratory symptoms 0.018000
Upper respiratory symptoms 0.025000
Minor Restricted Activity Days 0.680000
Work loss days 0.120000
Asthma exacerbation 0.029000
Cardiovascular hospital admissions 0.000250
Respiratory hospital admissions 0.000240
Non-fatal heart attacks (Peters) 0.000970
Non-fatal heart attacks (All others) 0.000100
0.009500
0.022000
0.004900
0.014000
0.180000
0.250000
7.000000
1.200000
0.290000
0.002600
0.002500
0.010000
0.001100
0.044000
0.100000
0.024000
0.066000
0.840000
1.200000
33.000000
5.600000
1.400000
0.012000
0.011000
0.045000
0.004900
86
-------
Table 109: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2030 from the coke ovens sector (2015$)
Pollutant emitted
N0X
S02
Directly emitted
PM2.5
3% Discount Rate
Krewski et al. (2009)
$14,000
$70,000
$590,000
Lepeule et al. (2012)
$32,000
$160,000
$1,300,000
7% Discount Rate
Krewski et al. (2009)
$13,000
$63,000
$530,000
Lepeule et al. (2012)
$29,000
$140,000
$1,200,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 110: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2030 from the coke ovens sector
Pollutant emitted
Directly emitted
Health Endpoint N0X SO2 PM2.5
Premature mortality
Krewski et al. (2009) 0.001400
Lepeule et al. (2012) 0.003300
Morbidity
Respiratory emergency room visits 0.000710
Acute bronchitis 0.001700
Lower respiratory symptoms 0.022000
Upper respiratory symptoms 0.031000
Minor Restricted Activity Days 0.860000
Work loss days 0.150000
Asthma exacerbation 0.036000
Cardiovascular hospital admissions 0.000360
Respiratory hospital admissions 0.000360
Non-fatal heart attacks (Peters) 0.001400
Non-fatal heart attacks (All others) 0.000150
0.007100
0.016000
0.003300
0.008400
0.110000
0.150000
4.200000
0.710000
0.180000
0.001900
0.001900
0.007500
0.000810
0.061000
0.140000
0.026000
0.068000
0.870000
1.200000
34.000000
5.700000
1.400000
0.015000
0.015000
0.060000
0.006500
87
-------
Table 111: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2030 from the iron and steel facilities
sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$22,000
$540,000
$670,000
Lepeule et al. (2012)
$50,000
$1,200,000
$1,500,000
7% Discount Rate
Krewski et al. (2009)
$20,000
$490,000
$610,000
Lepeule et al. (2012)
$45,000
$1,100,000
$1,400,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 112: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2030 from the iron and steel
facilities sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.002300
Lepeule et al. (2012) 0.005200
Morbidity
Respiratory emergency room visits 0.001200
Acute bronchitis 0.003300
Lower respiratory symptoms 0.042000
Upper respiratory symptoms 0.061000
Minor Restricted Activity Days 1.600000
Work loss days 0.280000
Asthma exacerbation 0.070000
Cardiovascular hospital admissions 0.000610
Respiratory hospital admissions 0.000590
Non-fatal heart attacks (Peters) 0.002400
Non-fatal heart attacks (All others) 0.000260
0.056000
0.130000
0.026000
0.070000
0.900000
1.300000
35.000000
6.000000
1.500000
0.014000
0.014000
0.058000
0.006200
0.069000
0.160000
0.032000
0.092000
1.200000
1.700000
46.000000
7.800000
1.900000
0.018000
0.018000
0.074000
0.008000
88
-------
Table 113: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2030 from the integrated iron and steel
facilities sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$18,000
$120,000
$630,000
Lepeule et al. (2012)
$41,000
$260,000
$1,400,000
7% Discount Rate
Krewski et al. (2009)
$16,000
$100,000
$570,000
Lepeule et al. (2012)
$37,000
$240,000
$1,300,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 114: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2030 from the integrated iron
and steel facilities sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.001900
Lepeule et al. (2012) 0.004200
Morbidity
Respiratory emergency room visits 0.000880
Acute bronchitis 0.002300
Lower respiratory symptoms 0.029000
Upper respiratory symptoms 0.041000
Minor Restricted Activity Days 1.100000
Work loss days 0.190000
Asthma exacerbation 0.047000
Cardiovascular hospital admissions 0.000470
Respiratory hospital admissions 0.000460
Non-fatal heart attacks (Peters) 0.001900
Non-fatal heart attacks (All others) 0.000200
0.012000
0.027000
0.005800
0.014000
0.180000
0.260000
7.100000
1.200000
0.300000
0.003100
0.003100
0.012000
0.001300
0.065000
0.150000
0.029000
0.077000
0.980000
1.400000
38.000000
6.400000
1.600000
0.017000
0.017000
0.066000
0.007200
89
-------
Table 115: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2030 from the electric arc furnaces
sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$13,000
$110,000
$580,000
Lepeule et al. (2012)
$29,000
$250,000
$1,300,000
7% Discount Rate
Krewski et al. (2009)
$12,000
$98,000
$520,000
Lepeule et al. (2012)
$27,000
$220,000
$1,200,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 116: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2030 from the electric arc
furnaces sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.001300
Lepeule et al. (2012) 0.003000
Morbidity
Respiratory emergency room visits 0.000690
Acute bronchitis 0.001700
Lower respiratory symptoms 0.022000
Upper respiratory symptoms 0.031000
Minor Restricted Activity Days 0.830000
Work loss days 0.140000
Asthma exacerbation 0.036000
Cardiovascular hospital admissions 0.000340
Respiratory hospital admissions 0.000330
Non-fatal heart attacks (Peters) 0.001300
Non-fatal heart attacks (All others) 0.000140
0.011000
0.025000
0.005200
0.013000
0.170000
0.240000
6.600000
1.100000
0.280000
0.002900
0.002900
0.012000
0.001300
0.059000
0.130000
0.028000
0.070000
0.900000
1.300000
35.000000
5.900000
1.500000
0.016000
0.016000
0.066000
0.007100
90
-------
Table 117: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2030 from the taconite mines sector
(2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$8,300
$46,000
$120,000
Lepeule et al. (2012)
$19,000
$100,000
$260,000
7% Discount Rate
Krewski et al. (2009)
$7,500
$42,000
$100,000
Lepeule et al. (2012)
$17,000
$94,000
$240,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 118: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2030 from the taconite mines
sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.000850
Lepeule et al. (2012) 0.001900
Morbidity
Respiratory emergency room visits 0.000380
Acute bronchitis 0.001100
Lower respiratory symptoms 0.014000
Upper respiratory symptoms 0.019000
Minor Restricted Activity Days 0.520000
Work loss days 0.088000
Asthma exacerbation 0.022000
Cardiovascular hospital admissions 0.000200
Respiratory hospital admissions 0.000190
Non-fatal heart attacks (Peters) 0.000820
Non-fatal heart attacks (All others) 0.000089
0.004700
0.011000
0.002100
0.005700
0.072000
0.100000
2.800000
0.480000
0.120000
0.001200
0.001200
0.004800
0.000520
0.012000
0.027000
0.004700
0.014000
0.180000
0.250000
6.700000
1.100000
0.290000
0.002800
0.002800
0.012000
0.001300
91
-------
Table 119: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2030 from the ferroalloy facilities sector
(2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$6,000
$61,000
$380,000
Lepeule et al. (2012)
$14,000
$140,000
$850,000
7% Discount Rate
Krewski et al. (2009)
$5,500
$55,000
$340,000
Lepeule et al. (2012)
$12,000
$130,000
$770,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 120: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2030 from the ferroalloy
facilities sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.000620
Lepeule et al. (2012) 0.001400
Morbidity
Respiratory emergency room visits 0.000250
Acute bronchitis 0.000680
Lower respiratory symptoms 0.008600
Upper respiratory symptoms 0.012000
Minor Restricted Activity Days 0.340000
Work loss days 0.058000
Asthma exacerbation 0.014000
Cardiovascular hospital admissions 0.000150
Respiratory hospital admissions 0.000150
Non-fatal heart attacks (Peters) 0.000620
Non-fatal heart attacks (All others) 0.000067
0.006300
0.014000
0.002700
0.007200
0.092000
0.130000
3.600000
0.610000
0.150000
0.001700
0.001700
0.006900
0.000740
0.039000
0.088000
0.017000
0.045000
0.580000
0.820000
22.000000
3.800000
0.950000
0.010000
0.010000
0.043000
0.004600
92
-------
Table 121: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2030 from the residential wood
combustion sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$18,000
$140,000
$510,000
Lepeule et al. (2012)
$41,000
$310,000
$1,100,000
7% Discount Rate
Krewski et al. (2009)
$16,000
$120,000
$460,000
Lepeule et al. (2012)
$37,000
$280,000
$1,000,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 122: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2030 from the residential wood
combustion sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.001900
Lepeule et al. (2012) 0.004200
Morbidity
Respiratory emergency room visits 0.000930
Acute bronchitis 0.002600
Lower respiratory symptoms 0.033000
Upper respiratory symptoms 0.047000
Minor Restricted Activity Days 1.300000
Work loss days 0.220000
Asthma exacerbation 0.054000
Cardiovascular hospital admissions 0.000450
Respiratory hospital admissions 0.000430
Non-fatal heart attacks (Peters) 0.001800
Non-fatal heart attacks (All others) 0.000200
0.014000
0.032000
0.006800
0.019000
0.240000
0.340000
9.700000
1.600000
0.400000
0.003400
0.003200
0.014000
0.001500
0.052000
0.120000
0.025000
0.070000
0.890000
1.300000
35.000000
6.000000
1.500000
0.013000
0.012000
0.051000
0.005600
93
-------
Table 123: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2030 from the area sources sector
(2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$11,000
$67,000
$450,000
Lepeule et al. (2012)
$24,000
$150,000
$1,000,000
7% Discount Rate
Krewski et al. (2009)
$9,500
$60,000
$400,000
Lepeule et al. (2012)
$21,000
$140,000
$910,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 124: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2030 from the area sources
sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.001100
Lepeule et al. (2012) 0.002400
Morbidity
Respiratory emergency room visits 0.000570
Acute bronchitis 0.001500
Lower respiratory symptoms 0.020000
Upper respiratory symptoms 0.028000
Minor Restricted Activity Days 0.740000
Work loss days 0.130000
Asthma exacerbation 0.032000
Cardiovascular hospital admissions 0.000270
Respiratory hospital admissions 0.000270
Non-fatal heart attacks (Peters) 0.001100
Non-fatal heart attacks (All others) 0.000120
0.006800
0.015000
0.003800
0.009000
0.120000
0.170000
4.600000
0.790000
0.190000
0.001800
0.001800
0.007100
0.000770
0.046000
0.100000
0.025000
0.062000
0.790000
1.100000
32.000000
5.400000
1.300000
0.012000
0.012000
0.047000
0.005100
94
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Table 125: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2030 from the industrial point sources
sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$8,500
$56,000
$370,000
Lepeule et al. (2012)
$19,000
$130,000
$830,000
7% Discount Rate
Krewski et al. (2009)
$7,700
$50,000
$330,000
Lepeule et al. (2012)
$17,000
$110,000
$750,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 126: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2030 from the industrial point
sources sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.000880
Lepeule et al. (2012) 0.002000
Morbidity
Respiratory emergency room visits 0.000430
Acute bronchitis 0.001200
Lower respiratory symptoms 0.015000
Upper respiratory symptoms 0.022000
Minor Restricted Activity Days 0.580000
Work loss days 0.099000
Asthma exacerbation 0.025000
Cardiovascular hospital admissions 0.000220
Respiratory hospital admissions 0.000220
Non-fatal heart attacks (Peters) 0.000890
Non-fatal heart attacks (All others) 0.000096
0.005700
0.013000
0.002900
0.007300
0.093000
0.130000
3.600000
0.620000
0.150000
0.001500
0.001500
0.006000
0.000650
0.037000
0.085000
0.019000
0.050000
0.640000
0.920000
25.000000
4.300000
1.100000
0.010000
0.009800
0.040000
0.004300
95
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Table 127: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2030 from the aircraft, locomotives and
marine vessels sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$9,600
$120,000
$330,000
Lepeule et al. (2012)
$22,000
$270,000
$740,000
7% Discount Rate
Krewski et al. (2009)
$8,700
$110,000
$290,000
Lepeule et al. (2012)
$20,000
$240,000
$660,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 128: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2030 from the aircraft,
locomotives and marine vessels sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.000980
Lepeule et al. (2012) 0.002200
Morbidity
Respiratory emergency room visits 0.000480
Acute bronchitis 0.001400
Lower respiratory symptoms 0.018000
Upper respiratory symptoms 0.025000
Minor Restricted Activity Days 0.680000
Work loss days 0.120000
Asthma exacerbation 0.029000
Cardiovascular hospital admissions 0.000260
Respiratory hospital admissions 0.000250
Non-fatal heart attacks (Peters) 0.001000
Non-fatal heart attacks (All others) 0.000110
0.012000
0.028000
0.006000
0.020000
0.250000
0.360000
10.000000
1.700000
0.410000
0.003500
0.003200
0.013000
0.001400
0.033000
0.076000
0.018000
0.046000
0.590000
0.840000
24.000000
4.100000
0.980000
0.008900
0.008600
0.035000
0.003800
96
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Table 129: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2030 from the non-road mobile sources
sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$9,200
$63,000
$430,000
Lepeule et al. (2012)
$21,000
$140,000
$970,000
7% Discount Rate
Krewski et al. (2009)
$8,300
$57,000
$390,000
Lepeule et al. (2012)
$19,000
$130,000
$870,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 130: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2030 from the non-road mobile
sources sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.000940
Lepeule et al. (2012) 0.002100
Morbidity
Respiratory emergency room visits 0.000480
Acute bronchitis 0.001400
Lower respiratory symptoms 0.018000
Upper respiratory symptoms 0.025000
Minor Restricted Activity Days 0.680000
Work loss days 0.120000
Asthma exacerbation 0.029000
Cardiovascular hospital admissions 0.000250
Respiratory hospital admissions 0.000240
Non-fatal heart attacks (Peters) 0.000980
Non-fatal heart attacks (All others) 0.000110
0.006500
0.015000
0.003400
0.010000
0.130000
0.190000
4.900000
0.840000
0.210000
0.001500
0.001500
0.006200
0.000670
0.044000
0.099000
0.025000
0.061000
0.780000
1.100000
32.000000
5.400000
1.300000
0.012000
0.011000
0.045000
0.004900
97
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Table 131: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2030 from the on-road mobile sources
sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$10,000
$28,000
$500,000
Lepeule et al. (2012)
$23,000
$64,000
$1,100,000
7% Discount Rate
Krewski et al. (2009)
$9,200
$25,000
$450,000
Lepeule et al. (2012)
$21,000
$57,000
$1,000,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 132: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2030 from the on-road mobile
sources sector
Health Endpoint
N0X
Pollutant emitted
SO2
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.001000
Lepeule et al. (2012) 0.002400
Morbidity
Respiratory emergency room visits 0.000530
Acute bronchitis 0.001400
Lower respiratory symptoms 0.018000
Upper respiratory symptoms 0.026000
Minor Restricted Activity Days 0.710000
Work loss days 0.120000
Asthma exacerbation 0.031000
Cardiovascular hospital admissions 0.000270
Respiratory hospital admissions 0.000260
Non-fatal heart attacks (Peters) 0.001100
Non-fatal heart attacks (All others) 0.000110
0.002900
0.006500
0.001500
0.004500
0.057000
0.082000
2.100000
0.370000
0.094000
0.000700
0.000680
0.002800
0.000300
0.051000
0.120000
0.028000
0.073000
0.930000
1.300000
37.000000
6.300000
1.500000
0.014000
0.013000
0.054000
0.005800
98
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Table 133: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2030 from the electricity generating
units sector (2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$7,200
$49,000
$180,000
Lepeule et al. (2012)
$16,000
$110,000
$410,000
7% Discount Rate
Krewski et al. (2009)
$6,500
$45,000
$160,000
Lepeule et al. (2012)
$15,000
$100,000
$370,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 134: Incidence of avoided mortalities and morbidities per ton of directly
emitted PM2.5 and PM2.5 precursors reduced in 2030 from the electricity
generating units sector
Pollutant emitted
Directly emitted
Health Endpoint N0X SO2 PM2.5
Premature mortality
Krewski et al. (2009) 0.000740 0.005100 0.018000
Lepeuleetal. (2012) 0.001700 0.011000 0.042000
Morbidity
Respiratory emergency room visits 0.000340 0.002400 0.009800
Acute bronchitis 0.000960 0.006200 0.024000
Lower respiratory symptoms 0.012000 0.079000 0.310000
Upper respiratory symptoms 0.017000 0.110000 0.440000
Minor Restricted Activity Days 0.460000 3.100000 12.000000
Work loss days 0.078000 0.530000 2.100000
Asthma exacerbation 0.020000 0.130000 0.510000
Cardiovascular hospital admissions 0.000180 0.001400 0.004800
Respiratory hospital admissions 0.000180 0.001300 0.004700
Non-fatal heart attacks (Peters) 0.000740 0.005300 0.019000
Non-fatal heart attacks (All others) 0.000079 0.000580 0.002100
99
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Table 135: Dollar value (mortality and morbidity) per ton of directly emitted
PM2.5 and PM2.5 precursors reduced in 2030 from the ocean-going vessels sector
(2015$)
Pollutant emitted
Directly emitted
Mortality risk estimateA N0X SO2 PM2.5
3% Discount Rate
Krewski et al. (2009)
$2,600
$17,000
$63,000
Lepeule et al. (2012)
$5,800
$38,000
$140,000
7% Discount Rate
Krewski et al. (2009)
$2,300
$15,000
$57,000
Lepeule et al. (2012)
$5,200
$34,000
$130,000
A Value represents sum of the value of avoided morbidity impacts and mortality impacts quantified using the PM2.5
mortality risk estimate noted. Estimates are rounded to two significant digits in this table, but all calculations are
performed with the unrounded estimates.
Table 136: Incidence of avoided mortalities and morbidities per ton
emitted PM2.5 and PM2.5 precursors reduced in 2030 from the ocean-
vessels sector
Pollutant emitted
Health Endpoint
N0X
S02
of directly
going
Directly emitted
PM2.5
Premature mortality
Krewski et al. (2009) 0.000260
Lepeule et al. (2012) 0.000590
Morbidity
Respiratory emergency room visits 0.000140
Acute bronchitis 0.000410
Lower respiratory symptoms 0.005200
Upper respiratory symptoms 0.007500
Minor Restricted Activity Days 0.210000
Work loss days 0.036000
Asthma exacerbation 0.008600
Cardiovascular hospital admissions 0.000074
Respiratory hospital admissions 0.000070
Non-fatal heart attacks (Peters) 0.000280
Non-fatal heart attacks (All others) 0.000031
0.001700
0.003900
0.000880
0.002200
0.028000
0.040000
1.200000
0.200000
0.046000
0.000470
0.000450
0.001800
0.000190
0.006400
0.015000
0.003300
0.008600
0.110000
0.160000
4.500000
0.770000
0.180000
0.001700
0.001600
0.006600
0.000710
100
-------
Appendix B: Modeled annual mean PM2.5 levels
attributable to sectors in 2016
101
-------
100
-------
101
Electricity generating units
Industrial point sources
-------
Non-road mobile sources
< 0.020
0.021
0.050
0.051
0.100
0.101
0.250
0.251
0.500
0.501
0.750
0.751
1.000
1.001
2.000
2.001
5.000
>5.000
Iron and steel facilities
Sl/
< 0.020
m 0.021 - o.oso
m o.o5i -o.ioo
¦ 0.101 -0.250
0.251 -0.500
0.501-0.750
0.751 - 1.000
m 1.001 -2.000
¦ 2.001 - 5.000
¦ > 5.000
Ocean-going vessels
102
-------
On-road mobile sources
Pulp and paper facilities
Refineries
< 0.020
0.021
0.050
¦
0.051
0.100
mm
0.101
0.250
mm
0.251
0.500
0.501
0.750
^m
0.751
1.000
¦
1.001
2.000
¦¦
2.001
5.000
103
-------
104
-------
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105
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