1

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

January 2013
2

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 Charles Fulcher, 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, fulcher.charles@epa.gov). 
3

Overview

This Technical Support Document (TSD) describes an approach for estimating the

average avoided human health impacts, and monetized benefits related to emissions of 

PM2.5 and PM2.5 precursors including NOx and SO2 from 17 sectors using the results of 

source apportionment photochemical modeling. We focus in particular on the aspects of 

our approach that represent a change from the benefit per ton calculation methodology

described in Fann, Fulcher and Hubbell (2009) and subsequently applied in several EPA 

RIAs. We also describe the ways in which these new estimates can improve our 

characterization of the PM2.5-related health benefits from the sectors that were modeled, as 

well as limitations and uncertainties associated with application of these estimates. We 

summarize the benefit per ton estimates for each of the 17 emission sectors. These sourceapportionment based benefit per ton estimates are also discussed in Fann, Baker and 

Fulcher (2012).

Summary of Calculations

The procedure for calculating benefit per ton coefficients follows three steps, shown 

graphically in Figure 1:

1. Use source apportionment photochemical modeling to predict 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 (BenMAP v4.0.66)1.

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 

NOx emissions.

 1 In this stage we estimate the PM2.5-related impacts associated with changes in directly emitted PM2.5, nitrate 

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 PM2.5 mass to the risk of adverse health outcomes; we do not apply 

effect coefficients that are differentiated by PM2.5 specie. 
4

Figure 1. Conceptual overview of the steps for calculating benefit per-ton estimates

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. Aircraft, locomotives and marine vessels

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

15. Refineries

16. Residential wood combustion

17. Taconite mines

The “Area sources” and “Industrial point sources” categories are agglomerations of 

sectors that were not modeled separately. 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” (US EPA 2011a). Ambient PM2.5
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.

Table 1. 2016 emissions by sector (tons per year)

Sector VOC NOx PM2.5a SO2 NH3

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.
6

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 NOx and VOC for many of these sectors could be 

substantial. 

Finally, it is important to note that 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 (US EPA 2009). Therefore, reducing these emissions 

would reduce PM2.5 formation, 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 (Federal Register; 40CFR Parts 51, 72, 75, and 96 

Rule to Reduce Interstate Transport of Fine Particulate Matter and Ozone (Interstate Air 

Quality Rule); Proposed Rule. January 30, 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 (Levy et al. 2009). PC-based 
7

tools such as the environmental Benefits Mapping and Analysis Program (BenMAP) can 

systematize health impact analyses by applying a database of key input parameters, 

including health impact functions and population projections(Abt Associates Inc. 2012). 

Analysts have applied the HIA approach to estimate human health impacts resulting from 

hypothetical changes in pollutant levels (Hubbell et al. 2004; Davidson et al. 2007; 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. 2009). This procedure is operationalized 

within BenMAP using a health impact function. 

A typical health impact function looks as follows:

∆y = yo ∙ �eβ∙∆x − 1� ∙ Pop

where y0 is the baseline incidence rate for the health endpoint being quantified (for 

example, a health impact function quantifying changes in mortality would use the baseline, 

or background, mortality rate for the given population of interest); Pop is the population 

affected by the change in air quality, whose size and distribution we have projected to the 

analysis year; ∆x is the change in air quality; and β is the effect coefficient drawn from the 

epidemiological study. 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 1 below summarizes the endpoints 

quantified in this benefit per ton TSD.
8

Figure 2. Illustration of BenMAP Approach
9

Table 2. Human health effects of PM2.5 quantified and not quantified in this analysis

Category Specific Effect

Effect Has 

Been 

Quantified

Effect Has 

Been 

Monetized

More 

Information in 

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)

  Section 5.6

Infant mortality (age <1)   Section 5.6

Reduced incidence of 

morbidity from 

exposure to PM2.5

Non-fatal heart attacks (age > 18)   Section 5.6

Hospital admissions—respiratory (all 

ages)

  Section 5.6

Hospital admissions—cardiov ascular 

(age >20)   Section 5.6

Emergency room visits for asthma (all 

ages)

  Section 5.6

Acute bronchitis (age 8-12)   Section 5.6

Lower respiratory symptoms (age 7-14)   Section 5.6

Upper respiratory symptoms 

(asthmatics age 9-11)   Section 5.6

Asthma exacerbation (asthmatics age 6-

18)

  Section 5.6

Lost work days (age 18-65)   Section 5.6

Minor restricted-activity days (age 18-

65)

  Section 5.6

Chronic Bronchitis (age >26) --1 --1 Section 5.6

Emergency room visits for 

cardiovascular effects (all ages) --1 --1 Section 5.6

Strokes and cerebrovascular disease 

(age 50-79) --1 --1 Section 5.6

Other cardiovascular effects (e.g., other 

ages) -- -- PM ISA2

Other respiratory effects (e.g., 

pulmonary function, non-asthma ER 

visits, non-bronchitis chronic diseases, 

other ages and populations)

-- -- PM ISA2

Reproductive and developmental effects 

(e.g., low birth weight, pre-term births, 

etc)

-- -- PM ISA2,3

Cancer, mutagenicity, and genotoxicity 

effects -- -- 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 confidence 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.
10

Estimating the economic value of health impacts attributable to each sector

After quantifying the change in adverse health impacts, the next step is to estimate 

the economic value of these avoided impacts. 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 (US EPA-SAB 

2000). The VSL approach is a summary measure for the value of small changes in mortality 

risk experienced by a large number of people.
11

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 (US 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 2 shows the adjusted VSL estimates for 

currency years 2000-2012 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 Estimate 2016 2020 2024a

2000 $6.3 $7.3 $7.6 $7.8

2001 $6.5 $7.5 $7.8 $8.0

2002 $6.6 $7.7 $7.9 $8.1

2003 $6.7 $7.8 $8.1 $8.3

2004 $6.9 $8.0 $8.3 $8.5

2005 $7.1 $8.3 $8.6 $8.8

2006 $7.4 $8.6 $8.9 $9.1

2007 $7.6 $8.8 $9.1 $9.4

2008 $7.9 $9.2 $9.5 $9.7

2009 $7.8 $9.1 $9.4 $9.7

2010 $8.0 $9.3 $9.6 $9.8

2011 $8.2 $9.6 $9.9 $10.1

2012 $8.4 $9.8 $10.1 $10.4

a Income growth projections are only available to 2024, so both the 2025 and 2030 estimates use 

income growth to 2024 and are therefore likely underestimates.

 

2 In the updated Guidelines for Preparing Economic Analyses (US EPA 2010a), EPA retained the VSL endorsed 

by the SAB with the understanding that further updates to the mortality risk valuation guidance woul d be 

forthcoming in the near future.

3 In 1990$, this VSL is $4.8 million.
12

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 (US EPA-SAB 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 2010

dollars, adjusted for growth in real income out to the analysis year using projections 

provided by Standard and Poor’s. However, these projections are only available to 2024, so 

both the 2025 and 2030 estimates use income growth to 2024. Economic theory argues 

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, NOx and 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. 

Table 4. Data used for Benefit per Ton Estimates

Analysis 

Year Popul ation Year

Mortality 

Incidence Year

Income Growth 

Year Currency Year Emissions Year

2016 2016 2015 2016

2020 2020 2020 2020 2010 2016

2025 2025 2025 2024

2025 2030 2030 2024
13

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 (2010$, 3% discount rate)A

Krewski et al. (2009) mortality estimateB Lepeule et al. (2012) m ortality estimateB

Sector

Directly emitted 

PM2.5 SO2 NOx

Directly emitted 

PM2.5 SO2 NOx

Aircraft, locomotives and marine 

vessels $240,000 $85,000 $6,900 $530,000 $190,000 $16,000

Area sources $320,000 $48,000 $7,500 $710,000 $110,000 $17,000

Cement kilns $350,000 $42,000 $5,500 $790,000 $95,000 $12,000

Coke ovens $450,000 $50,000 $10,000 $1,000,000 $110,000 $24,000

Electric arc furnaces $420,000 $78,000 $9,500 $950,000 $180,000 $21,000

Electricity generating units $130,000 $35,000 $5,200 $290,000 $78,000 $12,000

Ferroalloy facilities $270,000 $43,000 $4,300 $620,000 $98,000 $9,700

Industrial point sources $260,000 $39,000 $6,100 $580,000 $89,000 $14,000

Integrated iron and steel facilities $480,000 $85,000 $13,000 $1,100,000 $190,000 $30,000

Iron and steel facilities $490,000 $400,000 $16,000 $1,100,000 $900,000 $36,000

Non-road mobile sources $300,000 $43,000 $6,600 $690,000 $97,000 $15,000

Ocean-going vessels $45,000 $12,000 $1,800 $100,000 $26,000 $4,200

On-road mobile sources $360,000 $19,000 $7,300 $810,000 $43,000 $17,000

Pulp and paper facilities $150,000 $44,000 $3,600 $330,000 $100,000 $8,200

Refineries $310,000 $66,000 $6,500 $710,000 $150,000 $15,000

Residential wood combustion $360,000 $97,000 $13,000 $810,000 $220,000 $29,000

Taconite mines $81,000 $33,000 $5,900 $180,000 $74,000 $13,000

A Reported estimates are average $/ton across the full range of emissions for each sector and do not reflect heterogeneity across locations. Estimates

also 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 particul ar pollutant (e.g., non-zero second derivatives with respect to emissions).

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.
14

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 (2010$, 7% discount rate) A

Krewski et al. (2009) mortality estimateB Lepeule et al. (2012) m ortality estimateB

Sector

Directly emitted 

PM2.5 SO2 NOx

Directly emitted 

PM2.5 SO2 NOx

Aircraft, locomotives and marine 

vessels $210,000 $77,000 $6,200 $480,000 $170,000 $14,000

Area sources $280,000 $43,000 $6,800 $640,000 $97,000 $15,000

Cement kilns $320,000 $38,000 $4,900 $710,000 $86,000 $11,000

Coke ovens $400,000 $45,000 $9,400 $910,000 $100,000 $21,000

Electric arc furnaces $380,000 $70,000 $8,500 $860,000 $160,000 $19,000

Electricity generating units $120,000 $31,000 $4,600 $260,000 $71,000 $10,000

Ferroalloy facilities $250,000 $39,000 $3,900 $560,000 $88,000 $8,700

Industrial point sources $230,000 $36,000 $5,500 $520,000 $80,000 $12,000

Integrated iron and steel facilities $430,000 $77,000 $12,000 $980,000 $170,000 $27,000

Iron and steel facilities $450,000 $360,000 $15,000 $1,000,000 $810,000 $33,000

Non-road mobile sources $270,000 $38,000 $5,900 $620,000 $87,000 $13,000

Ocean-going vessels $40,000 $11,000 $1,700 $91,000 $24,000 $3,800

On-road mobile sources $320,000 $17,000 $6,600 $730,000 $39,000 $15,000

Pulp and paper facilities $130,000 $40,000 $3,300 $300,000 $90,000 $7,400

Refineries $280,000 $60,000 $5,900 $640,000 $130,000 $13,000

Residential wood combustion $320,000 $88,000 $12,000 $730,000 $200,000 $26,000

Taconite mines $73,000 $30,000 $5,300 $170,000 $67,000 $12,000

A Reported estimates are average $/ton across the full range of emissions for each sector and do not reflect heterogeneity across locations. Estimates 

also 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 particul ar pollutant (e.g., non-zero second derivatives with respect to emissions).

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 (2010$, 3% discount rate) A

Krewski et al. (2009) mortality estimateB Lepeule et al. (2012) m ortality estimateB

Sector

Directly emitted 

PM2.5 SO2 NOx

Directly emitted 

PM2.5 SO2 NOx

Aircraft, locomotives and marine 

vessels $250,000 $93,000 $7,300 $570,000 $210,000 $16,000

Area sources $340,000 $51,000 $8,000 $760,000 $110,000 $18,000

Cement kilns $380,000 $45,000 $5,800 $850,000 $100,000 $13,000

Coke ovens $470,000 $53,000 $11,000 $1,100,000 $120,000 $24,000

Electric arc furnaces $440,000 $82,000 $9,900 $1,000,000 $190,000 $22,000

Electricity generating units $140,000 $37,000 $5,400 $310,000 $83,000 $12,000

Ferroalloy facilities $290,000 $46,000 $4,500 $650,000 $100,000 $10,000

Industrial point sources $270,000 $42,000 $6,500 $620,000 $94,000 $15,000

Integrated iron and steel facilities $500,000 $89,000 $14,000 $1,100,000 $200,000 $31,000

Iron and steel facilities $520,000 $420,000 $17,000 $1,200,000 $940,000 $39,000

Non-road mobile sources $320,000 $46,000 $7,000 $730,000 $100,000 $16,000

Ocean-going vessels $48,000 $13,000 $2,000 $110,000 $29,000 $4,500

On-road mobile sources $380,000 $21,000 $7,700 $860,000 $47,000 $17,000

Pulp and paper facilities $160,000 $47,000 $3,800 $350,000 $110,000 $8,600

Refineries $330,000 $71,000 $7,000 $750,000 $160,000 $16,000

Residential wood combustion $380,000 $100,000 $14,000 $860,000 $230,000 $31,000

Taconite mines $86,000 $34,000 $6,200 $190,000 $78,000 $14,000

A Reported estimates are average $/ton across the full range of emissions for each sector and do not reflect heterogeneity across locations. Estimates

also 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 particul ar pollutant (e.g., non-zero second derivatives with respect to emissions).

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

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 (2010$, 7% discount rate) A

Krewski et al. (2009) mortality estimateB Lepeule et al. (2012) m ortality estimateB

Sector

Directly emitted 

PM2.5 SO2 NOx

Directly emitted 

PM2.5 SO2 NOx

Aircraft, locomotives and marine 

vessels $230,000 $84,000 $6,600 $510,000 $190,000 $15,000

Area sources $300,000 $46,000 $7,200 $680,000 $100,000 $16,000

Cement kilns $340,000 $40,000 $5,200 $770,000 $91,000 $12,000

Coke ovens $420,000 $48,000 $9,700 $950,000 $110,000 $22,000

Electric arc furnaces $400,000 $74,000 $8,900 $900,000 $170,000 $20,000

Electricity generating units $120,000 $33,000 $4,900 $280,000 $75,000 $11,000

Ferroalloy facilities $260,000 $41,000 $4,000 $580,000 $93,000 $9,100

Industrial point sources $250,000 $38,000 $5,800 $560,000 $85,000 $13,000

Integrated iron and steel facilities $450,000 $81,000 $12,000 $1,000,000 $180,000 $28,000

Iron and steel facilities $470,000 $380,000 $15,000 $1,100,000 $850,000 $35,000

Non-road mobile sources $290,000 $42,000 $6,300 $660,000 $94,000 $14,000

Ocean-going vessels $43,000 $11,000 $1,800 $98,000 $26,000 $4,100

On-road mobile sources $350,000 $19,000 $7,000 $780,000 $42,000 $16,000

Pulp and paper facilities $140,000 $42,000 $3,400 $320,000 $96,000 $7,800

Refineries $300,000 $64,000 $6,300 $680,000 $140,000 $14,000

Residential wood combustion $350,000 $94,000 $12,000 $780,000 $210,000 $28,000

Taconite mines $77,000 $31,000 $5,600 $170,000 $70,000 $13,000

A Reported estimates are average $/ton across the full range of emissions for each sector and do not reflect heterogeneity across locations. Estimates

also 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 particul ar pollutant (e.g., non-zero second derivatives with respect to emissions).

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 (2010$, 3% discount rate) A

Krewski et al. (2009) mortality estimateB Lepeule et al. (2012) m ortality estimateB

Sector

Directly emitted 

PM2.5 SO2 NOx

Directly emitted 

PM2.5 SO2 NOx

Aircraft, locomotives and marine 

vessels $280,000 $110,000 $8,000 $620,000 $240,000 $18,000

Area sources $370,000 $56,000 $8,700 $840,000 $130,000 $20,000

Cement kilns $420,000 $49,000 $6,300 $950,000 $110,000 $14,000

Coke ovens $500,000 $57,000 $12,000 $1,100,000 $130,000 $26,000

Electric arc furnaces $480,000 $89,000 $11,000 $1,100,000 $200,000 $24,000

Electricity generating units $150,000 $40,000 $5,800 $340,000 $90,000 $13,000

Ferroalloy facilities $310,000 $50,000 $4,800 $700,000 $110,000 $11,000

Industrial point sources $300,000 $46,000 $7,000 $680,000 $100,000 $16,000

Integrated iron and steel facilities $540,000 $96,000 $15,000 $1,200,000 $220,000 $34,000

Iron and steel facilities $570,000 $450,000 $19,000 $1,300,000 $1,000,000 $42,000

Non-road mobile sources $360,000 $52,000 $7,700 $810,000 $120,000 $17,000

Ocean-going vessels $53,000 $14,000 $2,300 $120,000 $32,000 $5,100

On-road mobile sources $420,000 $23,000 $8,400 $950,000 $52,000 $19,000

Pulp and paper facilities $170,000 $51,000 $4,200 $380,000 $120,000 $9,400

Refineries $370,000 $79,000 $7,700 $830,000 $180,000 $17,000

Residential wood combustion $420,000 $120,000 $15,000 $950,000 $260,000 $34,000

Taconite mines $93,000 $37,000 $6,600 $210,000 $84,000 $15,000

A Reported estimates are average $/ton across the full range of emissions for each sector and do not reflect heterogeneity across locations. Estimates 

also 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 particul ar pollutant (e.g., non-zero second derivatives with respect to emissions).

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

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 (2010$, 7% discount rate) A

Krewski et al. (2009) mortality estimateB Lepeule et al. (2012) m ortality estimateB

Sector

Directly emitted 

PM2.5 SO2 NOx

Directly emitted 

PM2.5 SO2 NOx

Aircraft, locomotives and marine 

vessels $250,000 $96,000 $7,200 $560,000 $220,000 $16,000

Area sources $330,000 $50,000 $7,900 $750,000 $110,000 $18,000

Cement kilns $380,000 $44,000 $5,700 $850,000 $99,000 $13,000

Coke ovens $450,000 $51,000 $10,000 $1,000,000 $120,000 $24,000

Electric arc furnaces $430,000 $80,000 $9,600 $970,000 $180,000 $22,000

Electricity generating units $130,000 $36,000 $5,200 $300,000 $82,000 $12,000

Ferroalloy facilities $280,000 $45,000 $4,400 $630,000 $100,000 $9,800

Industrial point sources $270,000 $41,000 $6,300 $620,000 $93,000 $14,000

Integrated iron and steel facilities $480,000 $87,000 $13,000 $1,100,000 $200,000 $30,000

Iron and steel facilities $510,000 $410,000 $17,000 $1,200,000 $920,000 $38,000

Non-road mobile sources $320,000 $47,000 $7,000 $730,000 $110,000 $16,000

Ocean-going vessels $48,000 $13,000 $2,000 $110,000 $29,000 $4,600

On-road mobile sources $380,000 $21,000 $7,600 $860,000 $47,000 $17,000

Pulp and paper facilities $150,000 $46,000 $3,700 $350,000 $100,000 $8,500

Refineries $330,000 $71,000 $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 $84,000 $34,000 $6,000 $190,000 $76,000 $14,000

A Reported estimates are average $/ton across the full range of emissions for each sector and do not reflect heterogeneity across locations. Estimates

also 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 particul ar pollutant (e.g., non-zero second derivatives with respect to emissions).

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

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 (2010$, 3% discount rate) A

Krewski et al. (2009) mortality estimateB Lepeule et al. (2012) m ortality estimateB

Sector

Directly emitted 

PM2.5 SO2 NOx

Directly emitted 

PM2.5 SO2 NOx

Aircraft, locomotives and marine 

vessels $300,000 $120,000 $8,700 $680,000 $270,000 $20,000

Area sources $400,000 $60,000 $9,400 $910,000 $140,000 $21,000

Cement kilns $460,000 $52,000 $6,800 $1,000,000 $120,000 $15,000

Coke ovens $530,000 $61,000 $12,000 $1,200,000 $140,000 $28,000

Electric arc furnaces $510,000 $95,000 $11,000 $1,200,000 $220,000 $26,000

Electricity generating units $160,000 $43,000 $6,200 $360,000 $97,000 $14,000

Ferroalloy facilities $330,000 $53,000 $5,100 $740,000 $120,000 $12,000

Industrial point sources $330,000 $49,000 $7,600 $740,000 $110,000 $17,000

Integrated iron and steel facilities $570,000 $100,000 $16,000 $1,300,000 $230,000 $36,000

Iron and steel facilities $610,000 $480,000 $20,000 $1,400,000 $1,100,000 $46,000

Non-road mobile sources $390,000 $57,000 $8,400 $880,000 $130,000 $19,000

Ocean-going vessels $58,000 $16,000 $2,500 $130,000 $35,000 $5,600

On-road mobile sources $460,000 $26,000 $9,100 $1,000,000 $58,000 $21,000

Pulp and paper facilities $180,000 $55,000 $4,500 $410,000 $130,000 $10,000

Refineries $400,000 $86,000 $8,300 $900,000 $190,000 $19,000

Residential wood combustion $460,000 $130,000 $16,000 $1,000,000 $280,000 $37,000

Taconite mines $100,000 $40,000 $7,100 $220,000 $90,000 $16,000

A Reported estimates are average $/ton across the full range of emissions for each sector and do not reflect heterogeneity across locations. Estimates

also 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 particul ar pollutant (e.g., non-zero second derivatives with respect to emissions).

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

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 (2010$, 7% discount rate)A

Krewski et al. (2009) mortality estimateB Lepeule et al. (2012) m ortality estimateB

Sector

Directly emitted 

PM2.5 SO2 NOx

Directly emitted 

PM2.5 SO2 NOx

Aircraft, locomotives and marine 

vessels $270,000 $110,000 $7,800 $610,000 $240,000 $18,000

Area sources $360,000 $54,000 $8,500 $820,000 $120,000 $19,000

Cement kilns $410,000 $47,000 $6,100 $930,000 $110,000 $14,000

Coke ovens $480,000 $55,000 $11,000 $1,100,000 $120,000 $25,000

Electric arc furnaces $460,000 $86,000 $10,000 $1,000,000 $190,000 $23,000

Electricity generating units $140,000 $39,000 $5,600 $330,000 $87,000 $13,000

Ferroalloy facilities $290,000 $48,000 $4,600 $670,000 $110,000 $10,000

Industrial point sources $300,000 $44,000 $6,800 $670,000 $100,000 $15,000

Integrated iron and steel facilities $510,000 $92,000 $14,000 $1,200,000 $210,000 $32,000

Iron and steel facilities $550,000 $440,000 $18,000 $1,200,000 $980,000 $41,000

Non-road mobile sources $350,000 $52,000 $7,600 $790,000 $120,000 $17,000

Ocean-going vessels $53,000 $14,000 $2,300 $120,000 $32,000 $5,100

On-road mobile sources $410,000 $23,000 $8,200 $930,000 $52,000 $19,000

Pulp and paper facilities $170,000 $50,000 $4,000 $370,000 $110,000 $9,100

Refineries $360,000 $77,000 $7,500 $810,000 $170,000 $17,000

Residential wood combustion $420,000 $110,000 $15,000 $940,000 $250,000 $33,000

Taconite mines $90,000 $36,000 $6,400 $200,000 $81,000 $14,000

A Reported estimates are average $/ton across the full range of emissions for each sector and do not reflect heterogeneity across locations. Estimates 

also 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 particul ar pollutant (e.g., non-zero second derivatives with respect to emissions).

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

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 et al. 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 PM2.5-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 PM2.5-related Mortality (US EPA 2010d).
22

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 12 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 Studiesa

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 et al. (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 μg/m3 and one standard deviation below the mean is 11.0 μg/m3

. For 

Lepeule et al., the LML is 8 μg/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 exposure to PM2.5

do not occur.
23

Among the populations exposed to PM2.5 in the baseline:

93% are exposed to PM2.5 levels at or above the LML of the Kr ewski 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 the 

Baseline

0%

5%

10%

15%

20%

25%

<1 1-2 2-3 3-4 4-5 5-6 6-7 7-8 8-9 9-10 10-11 11-12 12-13 13-14 14-15 15-16 16-17 17-18 18-19 19-20

Percentage of Population Exposed

Baseline Annual Mean PM2.5 Level (μg/m3)

 

LML of Lepeule et al. 

(2012) study

LML of Krewski et 

al. (2009) study
24

Among the populations exposed to PM2.5 in the baseline:

93% are exposed to PM2.5 levels at or above the LML of the Kr ewski 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

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 (US EPA 

2012; US EPA 2006). 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.

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 

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Cumulative percentage of population exposed

Baseline Annual Mean PM2.5 Level (μg/m3)

 

LML of Krewski et 

al. (2009) study

LML of Lepeule et 

al. (2012) study
25

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. 
26

Appendix A

Detailed Results for Each Sector
27

2016 Analysis Year
28

Table 14. 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 (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $6,900 $85,000 $240,000 

Lepeule et al. (2012) $16,000 $190,000 $530,000 

7% Discount Rate

Krewski et al. (2009) $6,200 $77,000 $210,000 

Lepeule et al. (2012) $14,000 $170,000 $480,000 

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 15. Incidence per ton of avoided mortalities and morbidities from the 

Petroleum Refineries sector for directly emitted PM2.5 and PM2.5 precursors reduced 

in 2016

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000800 0.009900 0.027000

Lepeule et al. (2012) 0.001800 0.023000 0.062000

Morbidity

Respiratory emergency room visits 0.000440 0.005000 0.015000

Acute bronchitis 0.001300 0.018000 0.042000

Lower respiratory symptoms 0.017000 0.230000 0.540000

Upper respiratory symptoms 0.024000 0.320000 0.770000

Minor Restricted Activity Days 0.660000 9.600000 23.000000

Work loss days 0.110000 1.600000 3.800000

Asthma exacerbation 0.024000 0.340000 0.800000

Cardiovascular hospital admissions 0.000270 0.002900 0.009000

Respiratory hospital admissions 0.000220 0.002300 0.007300

Non-fatal heart attacks (Peters) 0.000870 0.009700 0.029000

Non-fatal heart attacks (All others) 0.000093 0.001000 0.003100
29

Table 16. Dollar value (mortality and morbidity) per ton of directly emitted PM2.5 

and PM2.5 precursors reduced in 2016 from the area sources sector (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $7,500 $48,000 $320,000 

Lepeule et al. (2012) $17,000 $110,000 $710,000 

7% Discount Rate

Krewski et al. (2009) $6,800 $43,000 $280,000 

Lepeule et al. (2012) $15,000 $97,000 $640,000 

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 17. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000880 0.005600 0.037000

Lepeule et al. (2012) 0.002000 0.013000 0.083000

Morbidity

Respiratory emergency room visits 0.000510 0.003200 0.021000

Acute bronchitis 0.001400 0.008400 0.057000

Lower respiratory symptoms 0.018000 0.110000 0.730000

Upper respiratory symptoms 0.026000 0.150000 1.000000

Minor Restricted Activity Days 0.720000 4.400000 30.000000

Work loss days 0.120000 0.740000 5.100000

Asthma exacerbation 0.027000 0.380000 2.600000

Cardiovascular hospital admissions 0.000290 0.001900 0.012000

Respiratory hospital admissions 0.000240 0.001500 0.009900

Non-fatal heart attacks (Peters) 0.000950 0.006000 0.039000

Non-fatal heart attacks (All others) 0.000100 0.000650 0.004200
30

Table 18. Dollar value (mortality and morbidity) per ton of directly emitted PM2.5 

and PM2.5 precursors reduced in 2016 from the cement kilns sector (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $5,500 $42,000 $350,000 

Lepeule et al. (2012) $12,000 $95,000 $790,000 

7% Discount Rate

Krewski et al. (2009) $4,900 $38,000 $320,000 

Lepeule et al. (2012) $11,000 $86,000 $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 19. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000640 0.004900 0.041000

Lepeule et al. (2012) 0.001400 0.011000 0.093000

Morbidity

Respiratory emergency room visits 0.000370 0.002600 0.021000

Acute bronchitis 0.001000 0.007200 0.068000

Lower respiratory symptoms 0.013000 0.092000 0.860000

Upper respiratory symptoms 0.018000 0.130000 1.200000

Minor Restricted Activity Days 0.510000 3.700000 33.000000

Work loss days 0.086000 0.620000 5.600000

Asthma exacerbation 0.019000 0.130000 1.300000

Cardiovascular hospital admissions 0.000220 0.001700 0.013000

Respiratory hospital admissions 0.000170 0.001300 0.010000

Non-fatal heart attacks (Peters) 0.000690 0.005300 0.043000

Non-fatal heart attacks (All others) 0.000075 0.000570 0.004700
31

Table 20. Dollar value (mortality and morbidity) per ton of directly emitted PM2.5 

and PM2.5 precursors reduced in 2016 from the coke ovens sector (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $10,000 $50,000 $450,000 

Lepeule et al. (2012) $24,000 $110,000 $1,000,000 

7% Discount Rate

Krewski et al. (2009) $9,400 $45,000 $400,000 

Lepeule et al. (2012) $21,000 $100,000 $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 21. 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

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.001200 0.005900 0.052000

Lepeule et al. (2012) 0.002700 0.013000 0.120000

Morbidity

Respiratory emergency room visits 0.000730 0.003100 0.026000

Acute bronchitis 0.001700 0.008100 0.067000

Lower respiratory symptoms 0.021000 0.100000 0.850000

Upper respiratory symptoms 0.031000 0.150000 1.200000

Minor Restricted Activity Days 0.880000 4.200000 35.000000

Work loss days 0.150000 0.700000 5.800000

Asthma exacerbation 0.031000 0.150000 1.200000

Cardiovascular hospital admissions 0.000440 0.002100 0.018000

Respiratory hospital admissions 0.000350 0.001700 0.015000

Non-fatal heart attacks (Peters) 0.001400 0.006600 0.057000

Non-fatal heart attacks (All others) 0.000150 0.000710 0.006200
32

Table 22. 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 (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $9,500 $78,000 $420,000 

Lepeule et al. (2012) $21,000 $180,000 $950,000 

7% Discount Rate

Krewski et al. (2009) $8,500 $70,000 $380,000 

Lepeule et al. (2012) $19,000 $160,000 $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 23. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.001100 0.009100 0.049000

Lepeule et al. (2012) 0.002500 0.021000 0.110000

Morbidity

Respiratory emergency room visits 0.000660 0.004500 0.024000

Acute bronchitis 0.001600 0.013000 0.067000

Lower respiratory symptoms 0.021000 0.160000 0.850000

Upper respiratory symptoms 0.030000 0.230000 1.200000

Minor Restricted Activity Days 0.830000 6.500000 35.000000

Work loss days 0.140000 1.100000 5.800000

Asthma exacerbation 0.030000 0.240000 1.300000

Cardiovascular hospital admissions 0.000390 0.003000 0.016000

Respiratory hospital admissions 0.000310 0.002400 0.013000

Non-fatal heart attacks (Peters) 0.001200 0.009900 0.053000

Non-fatal heart attacks (All others) 0.000130 0.001100 0.005700
33

Table 24. 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 

(2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $5,200 $35,000 $130,000 

Lepeule et al. (2012) $12,000 $78,000 $290,000 

7% Discount Rate

Krewski et al. (2009) $4,600 $31,000 $120,000 

Lepeule et al. (2012) $10,000 $71,000 $260,000 

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 25. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000600 0.004100 0.015000

Lepeule et al. (2012) 0.001400 0.009200 0.034000

Morbidity

Respiratory emergency room visits 0.000330 0.002100 0.008300

Acute bronchitis 0.000910 0.005800 0.023000

Lower respiratory symptoms 0.012000 0.074000 0.290000

Upper respiratory symptoms 0.017000 0.110000 0.410000

Minor Restricted Activity Days 0.460000 3.000000 12.000000

Work loss days 0.077000 0.500000 1.900000

Asthma exacerbation 0.017000 0.260000 0.420000

Cardiovascular hospital admissions 0.000210 0.001400 0.005100

Respiratory hospital admissions 0.000170 0.001100 0.004100

Non-fatal heart attacks (Peters) 0.000670 0.004400 0.016000

Non-fatal heart attacks (All others) 0.000072 0.000480 0.001700
34

Table 26. Dollar value (mortality and morbidity) per ton of directly emitted PM2.5 

and PM2.5 precursors reduced in 2016 from the ferroalloy facilities sector (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $4,300 $43,000 $270,000 

Lepeule et al. (2012) $9,700 $98,000 $620,000 

7% Discount Rate

Krewski et al. (2009) $3,900 $39,000 $250,000 

Lepeule et al. (2012) $8,700 $88,000 $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 27. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000500 0.005000 0.032000

Lepeule et al. (2012) 0.001100 0.011000 0.072000

Morbidity

Respiratory emergency room visits 0.000230 0.002400 0.015000

Acute bronchitis 0.000650 0.006800 0.043000

Lower respiratory symptoms 0.008300 0.087000 0.550000

Upper respiratory symptoms 0.012000 0.120000 0.780000

Minor Restricted Activity Days 0.340000 3.500000 22.000000

Work loss days 0.058000 0.590000 3.700000

Asthma exacerbation 0.012000 0.130000 0.810000

Cardiovascular hospital admissions 0.000170 0.001700 0.011000

Respiratory hospital admissions 0.000130 0.001400 0.009000

Non-fatal heart attacks (Peters) 0.000550 0.005600 0.035000

Non-fatal heart attacks (All others) 0.000059 0.000600 0.003800
35

Table 28. 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 

(2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $6,100 $39,000 $260,000 

Lepeule et al. (2012) $14,000 $89,000 $580,000 

7% Discount Rate

Krewski et al. (2009) $5,500 $36,000 $230,000 

Lepeule et al. (2012) $12,000 $80,000 $520,000 

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 29. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000710 0.004600 0.030000

Lepeule et al. (2012) 0.001600 0.010000 0.068000

Morbidity

Respiratory emergency room visits 0.000400 0.002500 0.016000

Acute bronchitis 0.001100 0.006800 0.046000

Lower respiratory symptoms 0.014000 0.087000 0.590000

Upper respiratory symptoms 0.021000 0.120000 0.850000

Minor Restricted Activity Days 0.570000 3.500000 24.000000

Work loss days 0.096000 0.590000 4.000000

Asthma exacerbation 0.021000 0.130000 0.870000

Cardiovascular hospital admissions 0.000240 0.001600 0.009900

Respiratory hospital admissions 0.000190 0.001300 0.008000

Non-fatal heart attacks (Peters) 0.000780 0.005000 0.032000

Non-fatal heart attacks (All others) 0.000084 0.000540 0.003400
36

Table 30. 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 (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $13,000 $85,000 $480,000 

Lepeule et al. (2012) $30,000 $190,000 $1,100,000 

7% Discount Rate

Krewski et al. (2009) $12,000 $77,000 $430,000 

Lepeule et al. (2012) $27,000 $170,000 $980,000 

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 31. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.001500 0.010000 0.056000

Lepeule et al. (2012) 0.003500 0.023000 0.130000

Morbidity

Respiratory emergency room visits 0.000910 0.005700 0.031000

Acute bronchitis 0.002200 0.014000 0.076000

Lower respiratory symptoms 0.028000 0.180000 0.970000

Upper respiratory symptoms 0.040000 0.250000 1.400000

Minor Restricted Activity Days 1.100000 7.200000 39.000000

Work loss days 0.190000 1.200000 6.600000

Asthma exacerbation 0.041000 0.260000 1.400000

Cardiovascular hospital admissions 0.000570 0.003600 0.020000

Respiratory hospital admissions 0.000450 0.002900 0.016000

Non-fatal heart attacks (Peters) 0.001800 0.011000 0.064000

Non-fatal heart attacks (All others) 0.000190 0.001200 0.006900
37

Table 32. 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 

(2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $16,000 $400,000 $490,000 

Lepeule et al. (2012) $36,000 $900,000 $1,100,000 

7% Discount Rate

Krewski et al. (2009) $15,000 $360,000 $450,000 

Lepeule et al. (2012) $33,000 $810,000 $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 33. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.001900 0.046000 0.058000

Lepeule et al. (2012) 0.004200 0.110000 0.130000

Morbidity

Respiratory emergency room visits 0.001000 0.024000 0.029000

Acute bronchitis 0.003100 0.067000 0.087000

Lower respiratory symptoms 0.040000 0.850000 1.100000

Upper respiratory symptoms 0.057000 1.200000 1.600000

Minor Restricted Activity Days 1.600000 35.000000 45.000000

Work loss days 0.270000 5.900000 7.600000

Asthma exacerbation 0.059000 1.300000 1.600000

Cardiovascular hospital admissions 0.000620 0.015000 0.019000

Respiratory hospital admissions 0.000500 0.012000 0.015000

Non-fatal heart attacks (Peters) 0.002000 0.049000 0.061000

Non-fatal heart attacks (All others) 0.000210 0.005300 0.006500
38

Table 34. 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 

(2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $6,600 $43,000 $300,000 

Lepeule et al. (2012) $15,000 $97,000 $690,000 

7% Discount Rate

Krewski et al. (2009) $5,900 $38,000 $270,000 

Lepeule et al. (2012) $13,000 $87,000 $620,000 

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 35. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000770 0.005000 0.035000

Lepeule et al. (2012) 0.001700 0.011000 0.080000

Morbidity

Respiratory emergency room visits 0.000430 0.002600 0.021000

Acute bronchitis 0.001300 0.009100 0.056000

Lower respiratory symptoms 0.016000 0.120000 0.720000

Upper respiratory symptoms 0.023000 0.160000 1.000000

Minor Restricted Activity Days 0.650000 4.300000 30.000000

Work loss days 0.110000 0.730000 5.000000

Asthma exacerbation 0.024000 0.170000 1.100000

Cardiovascular hospital admissions 0.000250 0.001400 0.012000

Respiratory hospital admissions 0.000200 0.001200 0.009500

Non-fatal heart attacks (Peters) 0.000820 0.005000 0.038000

Non-fatal heart attacks (All others) 0.000089 0.000530 0.004100
39

Table 36. 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 (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $1,800 $12,000 $45,000 

Lepeule et al. (2012) $4,200 $26,000 $100,000 

7% Discount Rate

Krewski et al. (2009) $1,700 $11,000 $40,000 

Lepeule et al. (2012) $3,800 $24,000 $91,000 

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 37. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000210 0.001400 0.005200

Lepeule et al. (2012) 0.000490 0.003100 0.012000

Morbidity

Respiratory emergency room visits 0.000120 0.000680 0.002600

Acute bronchitis 0.000380 0.002000 0.007800

Lower respiratory symptoms 0.004800 0.025000 0.099000

Upper respiratory symptoms 0.006800 0.036000 0.140000

Minor Restricted Activity Days 0.200000 1.100000 4.200000

Work loss days 0.034000 0.180000 0.720000

Asthma exacerbation 0.007100 0.037000 0.150000

Cardiovascular hospital admissions 0.000067 0.000440 0.001700

Respiratory hospital admissions 0.000054 0.000350 0.001300

Non-fatal heart attacks (Peters) 0.000220 0.001400 0.005500

Non-fatal heart attacks (All others) 0.000024 0.000160 0.000590
40

Table 38. 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 

(2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $7,300 $19,000 $360,000 

Lepeule et al. (2012) $17,000 $43,000 $810,000 

7% Discount Rate

Krewski et al. (2009) $6,600 $17,000 $320,000 

Lepeule et al. (2012) $15,000 $39,000 $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 39. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000850 0.002200 0.042000

Lepeule et al. (2012) 0.001900 0.005000 0.094000

Morbidity

Respiratory emergency room visits 0.000490 0.001100 0.024000

Acute bronchitis 0.001400 0.004000 0.067000

Lower respiratory symptoms 0.017000 0.051000 0.850000

Upper respiratory symptoms 0.025000 0.072000 1.200000

Minor Restricted Activity Days 0.690000 1.900000 35.000000

Work loss days 0.120000 0.320000 5.900000

Asthma exacerbation 0.061000 0.074000 3.000000

Cardiovascular hospital admissions 0.000290 0.000660 0.014000

Respiratory hospital admissions 0.000230 0.000530 0.011000

Non-fatal heart attacks (Peters) 0.000930 0.002200 0.044000

Non-fatal heart attacks (All others) 0.000100 0.000240 0.004800
41

Table 40. 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 

(2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted

PM2.5

3% Discount Rate

Krewski et al. (2009) $3,600 $44,000 $150,000 

Lepeule et al. (2012) $8,200 $100,000 $330,000 

7% Discount Rate

Krewski et al. (2009) $3,300 $40,000 $130,000 

Lepeule et al. (2012) $7,400 $90,000 $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 41. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000420 0.005100 0.017000

Lepeule et al. (2012) 0.000960 0.012000 0.038000

Morbidity

Respiratory emergency room visits 0.000230 0.002500 0.007800

Acute bronchitis 0.000630 0.007300 0.024000

Lower respiratory symptoms 0.008000 0.093000 0.310000

Upper respiratory symptoms 0.011000 0.130000 0.440000

Minor Restricted Activity Days 0.320000 3.800000 12.000000

Work loss days 0.054000 0.630000 2.100000

Asthma exacerbation 0.012000 0.140000 0.450000

Cardiovascular hospital admissions 0.000140 0.001700 0.005500

Respiratory hospital admissions 0.000110 0.001400 0.004400

Non-fatal heart attacks (Peters) 0.000460 0.005500 0.018000

Non-fatal heart attacks (All others) 0.000050 0.000600 0.001900
42

Table 42. Dollar value (mortality and morbidity) per ton of directly emitted PM2.5 

and PM2.5 precursors reduced in 2016 from the refineries sector (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $6,500 $66,000 $310,000 

Lepeule et al. (2012) $15,000 $150,000 $710,000 

7% Discount Rate

Krewski et al. (2009) $5,900 $60,000 $280,000 

Lepeule et al. (2012) $13,000 $130,000 $640,000 

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 43. 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

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000760 0.007700 0.036000

Lepeule et al. (2012) 0.001700 0.017000 0.083000

Morbidity

Respiratory emergency room visits 0.000420 0.004100 0.019000

Acute bronchitis 0.001300 0.013000 0.060000

Lower respiratory symptoms 0.016000 0.160000 0.760000

Upper respiratory symptoms 0.023000 0.230000 1.100000

Minor Restricted Activity Days 0.660000 6.600000 31.000000

Work loss days 0.110000 1.100000 5.200000

Asthma exacerbation 0.024000 0.240000 1.100000

Cardiovascular hospital admissions 0.000250 0.002500 0.012000

Respiratory hospital admissions 0.000200 0.002000 0.009700

Non-fatal heart attacks (Peters) 0.000810 0.008000 0.037000

Non-fatal heart attacks (All others) 0.000087 0.000860 0.004000
43

Table 44. 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 

(2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $13,000 $97,000 $360,000 

Lepeule et al. (2012) $29,000 $220,000 $810,000 

7% Discount Rate

Krewski et al. (2009) $12,000 $88,000 $320,000 

Lepeule et al. (2012) $26,000 $200,000 $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 45. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.001500 0.011000 0.042000

Lepeule et al. (2012) 0.003400 0.026000 0.094000

Morbidity

Respiratory emergency room visits 0.000830 0.005700 0.021000

Acute bronchitis 0.002400 0.017000 0.064000

Lower respiratory symptoms 0.031000 0.220000 0.820000

Upper respiratory symptoms 0.044000 0.320000 1.200000

Minor Restricted Activity Days 1.200000 9.200000 34.000000

Work loss days 0.210000 1.500000 5.700000

Asthma exacerbation 0.045000 0.330000 2.900000

Cardiovascular hospital admissions 0.000470 0.003400 0.013000

Respiratory hospital admissions 0.000380 0.002800 0.010000

Non-fatal heart attacks (Peters) 0.001600 0.012000 0.043000

Non-fatal heart attacks (All others) 0.000170 0.001300 0.004700
44

Table 46. Dollar value (mortality and morbidity) per ton of directly emitted PM2.5 

and PM2.5 precursors reduced in 2016 from the taconite mines sector (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $5,900 $33,000 $81,000 

Lepeule et al. (2012) $13,000 $74,000 $180,000 

7% Discount Rate

Krewski et al. (2009) $5,300 $30,000 $73,000 

Lepeule et al. (2012) $12,000 $67,000 $170,000 

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 47. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000690 0.003800 0.009500

Lepeule et al. (2012) 0.001600 0.008700 0.022000

Morbidity

Respiratory emergency room visits 0.000370 0.001900 0.004200

Acute bronchitis 0.001000 0.005500 0.013000

Lower respiratory symptoms 0.013000 0.070000 0.170000

Upper respiratory symptoms 0.019000 0.099000 0.240000

Minor Restricted Activity Days 0.530000 2.800000 6.700000

Work loss days 0.089000 0.470000 1.100000

Asthma exacerbation 0.019000 0.100000 0.240000

Cardiovascular hospital admissions 0.000230 0.001300 0.003000

Respiratory hospital admissions 0.000190 0.001000 0.002400

Non-fatal heart attacks (Peters) 0.000750 0.004200 0.009800

Non-fatal heart attacks (All others) 0.000081 0.000460 0.001100
45

2020 Analysis Year
46

Table 48. 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 (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $7,300 $93,000 $250,000 

Lepeule et al. (2012) $16,000 $210,000 $570,000 

7% Discount Rate

Krewski et al. (2009) $6,600 $84,000 $230,000 

Lepeule et al. (2012) $15,000 $190,000 $510,000 

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 49. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000820 0.011000 0.028000

Lepeule et al. (2012) 0.001900 0.024000 0.064000

Morbidity

Respiratory emergency room visits 0.000450 0.005100 0.015000

Acute bronchitis 0.001300 0.018000 0.044000

Lower respiratory symptoms 0.017000 0.230000 0.560000

Upper respiratory symptoms 0.024000 0.330000 0.800000

Minor Restricted Activity Days 0.670000 9.900000 23.000000

Work loss days 0.110000 1.700000 3.900000

Asthma exacerbation 0.025000 0.350000 0.830000

Cardiovascular hospital admissions 0.000280 0.003100 0.009700

Respiratory hospital admissions 0.000230 0.002600 0.007900

Non-fatal heart attacks (Peters) 0.000930 0.011000 0.031000

Non-fatal heart attacks (All others) 0.000100 0.001100 0.003300
47

Table 50. Dollar value (mortality and morbidity) per ton of directly emitted PM2.5 

and PM2.5 precursors reduced in 2020 from the area sources sector (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $8,000 $51,000 $340,000 

Lepeule et al. (2012) $18,000 $110,000 $760,000 

7% Discount Rate

Krewski et al. (2009) $7,200 $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 51. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000900 0.005700 0.038000

Lepeule et al. (2012) 0.002000 0.013000 0.086000

Morbidity

Respiratory emergency room visits 0.000520 0.003300 0.021000

Acute bronchitis 0.001500 0.008700 0.059000

Lower respiratory symptoms 0.019000 0.110000 0.760000

Upper respiratory symptoms 0.027000 0.160000 1.100000

Minor Restricted Activity Days 0.730000 4.500000 31.000000

Work loss days 0.120000 0.760000 5.200000

Asthma exacerbation 0.028000 0.390000 2.700000

Cardiovascular hospital admissions 0.000310 0.002000 0.013000

Respiratory hospital admissions 0.000250 0.001700 0.011000

Non-fatal heart attacks (Peters) 0.001000 0.006400 0.042000

Non-fatal heart attacks (All others) 0.000110 0.000700 0.004500
48

Table 52. Dollar value (mortality and morbidity) per ton of directly emitted PM2.5 

and PM2.5 precursors reduced in 2020 from the cement kilns sector (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $5,800 $45,000 $380,000 

Lepeule et al. (2012) $13,000 $100,000 $850,000 

7% Discount Rate

Krewski et al. (2009) $5,200 $40,000 $340,000 

Lepeule et al. (2012) $12,000 $91,000 $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 53. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000650 0.005000 0.042000

Lepeule et al. (2012) 0.001500 0.011000 0.096000

Morbidity

Respiratory emergency room visits 0.000380 0.002700 0.022000

Acute bronchitis 0.001000 0.007400 0.070000

Lower respiratory symptoms 0.013000 0.095000 0.890000

Upper respiratory symptoms 0.019000 0.140000 1.300000

Minor Restricted Activity Days 0.520000 3.700000 34.000000

Work loss days 0.088000 0.630000 5.800000

Asthma exacerbation 0.020000 0.140000 1.300000

Cardiovascular hospital admissions 0.000230 0.001800 0.014000

Respiratory hospital admissions 0.000190 0.001400 0.011000

Non-fatal heart attacks (Peters) 0.000740 0.005700 0.047000

Non-fatal heart attacks (All others) 0.000080 0.000620 0.005100
49

Table 54. Dollar value (mortality and morbidity) per ton of directly emitted PM2.5 

and PM2.5 precursors reduced in 2020 from the coke ovens sector (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $11,000 $53,000 $470,000 

Lepeule et al. (2012) $24,000 $120,000 $1,100,000 

7% Discount Rate

Krewski et al. (2009) $9,700 $48,000 $420,000 

Lepeule et al. (2012) $22,000 $110,000 $950,000 

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 55. 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

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.001200 0.006000 0.053000

Lepeule et al. (2012) 0.002800 0.014000 0.120000

Morbidity

Respiratory emergency room visits 0.000740 0.003200 0.027000

Acute bronchitis 0.001700 0.008300 0.068000

Lower respiratory symptoms 0.022000 0.110000 0.860000

Upper respiratory symptoms 0.031000 0.150000 1.200000

Minor Restricted Activity Days 0.870000 4.200000 35.000000

Work loss days 0.150000 0.710000 5.800000

Asthma exacerbation 0.032000 0.160000 1.300000

Cardiovascular hospital admissions 0.000460 0.002200 0.019000

Respiratory hospital admissions 0.000370 0.001800 0.015000

Non-fatal heart attacks (Peters) 0.001400 0.007000 0.060000

Non-fatal heart attacks (All others) 0.000160 0.000760 0.006500
50

Table 56. 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 (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $9,900 $82,000 $440,000 

Lepeule et al. (2012) $22,000 $190,000 $1,000,000 

7% Discount Rate

Krewski et al. (2009) $8,900 $74,000 $400,000 

Lepeule et al. (2012) $20,000 $170,000 $900,000 

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 57. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.001100 0.009300 0.050000

Lepeule et al. (2012) 0.002500 0.021000 0.110000

Morbidity

Respiratory emergency room visits 0.000680 0.004600 0.025000

Acute bronchitis 0.001700 0.013000 0.069000

Lower respiratory symptoms 0.021000 0.170000 0.880000

Upper respiratory symptoms 0.030000 0.240000 1.300000

Minor Restricted Activity Days 0.830000 6.500000 35.000000

Work loss days 0.140000 1.100000 5.800000

Asthma exacerbation 0.031000 0.240000 1.300000

Cardiovascular hospital admissions 0.000410 0.003200 0.017000

Respiratory hospital admissions 0.000330 0.002600 0.014000

Non-fatal heart attacks (Peters) 0.001300 0.011000 0.056000

Non-fatal heart attacks (All others) 0.000140 0.001100 0.006000
51

Table 58. 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 

(2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $5,400 $37,000 $140,000 

Lepeule et al. (2012) $12,000 $83,000 $310,000 

7% Discount Rate

Krewski et al. (2009) $4,900 $33,000 $120,000 

Lepeule et al. (2012) $11,000 $75,000 $280,000 

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 59. 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

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000610 0.004200 0.015000

Lepeule et al. (2012) 0.001400 0.009400 0.035000

Morbidity

Respiratory emergency room visits 0.000340 0.002200 0.008600

Acute bronchitis 0.000930 0.006000 0.023000

Lower respiratory symptoms 0.012000 0.077000 0.300000

Upper respiratory symptoms 0.017000 0.110000 0.420000

Minor Restricted Activity Days 0.460000 3.000000 12.000000

Work loss days 0.077000 0.510000 2.000000

Asthma exacerbation 0.018000 0.270000 0.440000

Cardiovascular hospital admissions 0.000220 0.001500 0.005500

Respiratory hospital admissions 0.000180 0.001200 0.004400

Non-fatal heart attacks (Peters) 0.000710 0.004700 0.017000

Non-fatal heart attacks (All others) 0.000077 0.000520 0.001900
52

Table 60. Dollar value (mortality and morbidity) per ton of directly emitted PM2.5 

and PM2.5 precursors reduced in 2020 from the ferroalloy facilities sector (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $4,500 $46,000 $290,000 

Lepeule et al. (2012) $10,000 $100,000 $650,000 

7% Discount Rate

Krewski et al. (2009) $4,000 $41,000 $260,000 

Lepeule et al. (2012) $9,100 $93,000 $580,000 

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 61. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000510 0.005200 0.032000

Lepeule et al. (2012) 0.001100 0.012000 0.073000

Morbidity

Respiratory emergency room visits 0.000230 0.002400 0.015000

Acute bronchitis 0.000670 0.007000 0.044000

Lower respiratory symptoms 0.008500 0.090000 0.570000

Upper respiratory symptoms 0.012000 0.130000 0.810000

Minor Restricted Activity Days 0.350000 3.500000 22.000000

Work loss days 0.058000 0.600000 3.700000

Asthma exacerbation 0.013000 0.130000 0.840000

Cardiovascular hospital admissions 0.000180 0.001800 0.011000

Respiratory hospital admissions 0.000140 0.001500 0.009700

Non-fatal heart attacks (Peters) 0.000580 0.006000 0.037000

Non-fatal heart attacks (All others) 0.000062 0.000640 0.004000
53

Table 62. 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 

(2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $6,500 $42,000 $270,000 

Lepeule et al. (2012) $15,000 $94,000 $620,000 

7% Discount Rate

Krewski et al. (2009) $5,800 $38,000 $250,000 

Lepeule et al. (2012) $13,000 $85,000 $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 63. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000730 0.004700 0.031000

Lepeule et al. (2012) 0.001700 0.011000 0.070000

Morbidity

Respiratory emergency room visits 0.000410 0.002500 0.016000

Acute bronchitis 0.001200 0.007100 0.048000

Lower respiratory symptoms 0.015000 0.090000 0.610000

Upper respiratory symptoms 0.021000 0.130000 0.880000

Minor Restricted Activity Days 0.580000 3.500000 24.000000

Work loss days 0.097000 0.600000 4.100000

Asthma exacerbation 0.022000 0.130000 0.910000

Cardiovascular hospital admissions 0.000260 0.001700 0.011000

Respiratory hospital admissions 0.000210 0.001400 0.008700

Non-fatal heart attacks (Peters) 0.000830 0.005400 0.034000

Non-fatal heart attacks (All others) 0.000090 0.000580 0.003700
54

Table 64. 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 (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $14,000 $89,000 $500,000 

Lepeule et al. (2012) $31,000 $200,000 $1,100,000 

7% Discount Rate

Krewski et al. (2009) $12,000 $81,000 $450,000 

Lepeule et al. (2012) $28,000 $180,000 $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 65. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.001600 0.010000 0.057000

Lepeule et al. (2012) 0.003500 0.023000 0.130000

Morbidity

Respiratory emergency room visits 0.000920 0.005700 0.031000

Acute bronchitis 0.002200 0.014000 0.077000

Lower respiratory symptoms 0.029000 0.180000 0.980000

Upper respiratory symptoms 0.041000 0.260000 1.400000

Minor Restricted Activity Days 1.100000 7.200000 39.000000

Work loss days 0.190000 1.200000 6.500000

Asthma exacerbation 0.042000 0.270000 1.500000

Cardiovascular hospital admissions 0.000600 0.003800 0.022000

Respiratory hospital admissions 0.000480 0.003100 0.018000

Non-fatal heart attacks (Peters) 0.001900 0.012000 0.068000

Non-fatal heart attacks (All others) 0.000200 0.001300 0.007300
55

Table 66. 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 

(2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $17,000 $420,000 $520,000 

Lepeule et al. (2012) $39,000 $940,000 $1,200,000 

7% Discount Rate

Krewski et al. (2009) $15,000 $380,000 $470,000 

Lepeule et al. (2012) $35,000 $850,000 $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 67. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.001900 0.047000 0.059000

Lepeule et al. (2012) 0.004400 0.110000 0.130000

Morbidity

Respiratory emergency room visits 0.001100 0.025000 0.030000

Acute bronchitis 0.003200 0.069000 0.089000

Lower respiratory symptoms 0.041000 0.880000 1.100000

Upper respiratory symptoms 0.058000 1.300000 1.600000

Minor Restricted Activity Days 1.600000 35.000000 45.000000

Work loss days 0.270000 5.900000 7.700000

Asthma exacerbation 0.060000 1.300000 1.700000

Cardiovascular hospital admissions 0.000670 0.016000 0.020000

Respiratory hospital admissions 0.000540 0.013000 0.016000

Non-fatal heart attacks (Peters) 0.002100 0.052000 0.065000

Non-fatal heart attacks (All others) 0.000230 0.005600 0.007000
56

Table 68. 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 

(2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $7,000 $46,000 $320,000 

Lepeule et al. (2012) $16,000 $100,000 $730,000 

7% Discount Rate

Krewski et al. (2009) $6,300 $42,000 $290,000 

Lepeule et al. (2012) $14,000 $94,000 $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 69. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000790 0.005200 0.037000

Lepeule et al. (2012) 0.001800 0.012000 0.083000

Morbidity

Respiratory emergency room visits 0.000450 0.002700 0.021000

Acute bronchitis 0.001300 0.009500 0.058000

Lower respiratory symptoms 0.017000 0.120000 0.740000

Upper respiratory symptoms 0.024000 0.170000 1.100000

Minor Restricted Activity Days 0.660000 4.500000 30.000000

Work loss days 0.110000 0.760000 5.100000

Asthma exacerbation 0.025000 0.180000 1.100000

Cardiovascular hospital admissions 0.000270 0.001600 0.013000

Respiratory hospital admissions 0.000220 0.001300 0.010000

Non-fatal heart attacks (Peters) 0.000880 0.005400 0.041000

Non-fatal heart attacks (All others) 0.000095 0.000590 0.004400
57

Table 70. 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 (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $2,000 $13,000 $48,000 

Lepeule et al. (2012) $4,500 $29,000 $110,000 

7% Discount Rate

Krewski et al. (2009) $1,800 $11,000 $43,000 

Lepeule et al. (2012) $4,100 $26,000 $98,000 

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 71. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000230 0.001400 0.005400

Lepeule et al. (2012) 0.000510 0.003200 0.012000

Morbidity

Respiratory emergency room visits 0.000120 0.000700 0.002700

Acute bronchitis 0.000390 0.002100 0.008100

Lower respiratory symptoms 0.004900 0.026000 0.100000

Upper respiratory symptoms 0.007100 0.037000 0.150000

Minor Restricted Activity Days 0.210000 1.100000 4.300000

Work loss days 0.035000 0.190000 0.730000

Asthma exacerbation 0.007300 0.039000 0.150000

Cardiovascular hospital admissions 0.000072 0.000480 0.001800

Respiratory hospital admissions 0.000059 0.000380 0.001500

Non-fatal heart attacks (Peters) 0.000240 0.001600 0.006000

Non-fatal heart attacks (All others) 0.000026 0.000170 0.000640
58

Table 72. 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 

(2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $7,700 $21,000 $380,000 

Lepeule et al. (2012) $17,000 $47,000 $860,000 

7% Discount Rate

Krewski et al. (2009) $7,000 $19,000 $350,000 

Lepeule et al. (2012) $16,000 $42,000 $780,000 

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 73. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000870 0.002300 0.043000

Lepeule et al. (2012) 0.002000 0.005300 0.098000

Morbidity

Respiratory emergency room visits 0.000500 0.001200 0.025000

Acute bronchitis 0.001400 0.004100 0.069000

Lower respiratory symptoms 0.018000 0.053000 0.880000

Upper respiratory symptoms 0.026000 0.075000 1.300000

Minor Restricted Activity Days 0.700000 2.000000 36.000000

Work loss days 0.120000 0.340000 6.100000

Asthma exacerbation 0.063000 0.078000 3.100000

Cardiovascular hospital admissions 0.000310 0.000720 0.015000

Respiratory hospital admissions 0.000250 0.000580 0.012000

Non-fatal heart attacks (Peters) 0.000990 0.002400 0.048000

Non-fatal heart attacks (All others) 0.000110 0.000260 0.005200
59

Table 74. 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 

(2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $3,800 $47,000 $160,000 

Lepeule et al. (2012) $8,600 $110,000 $350,000 

7% Discount Rate

Krewski et al. (2009) $3,400 $42,000 $140,000 

Lepeule et al. (2012) $7,800 $96,000 $320,000 

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 75. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000430 0.005300 0.018000

Lepeule et al. (2012) 0.000980 0.012000 0.040000

Morbidity

Respiratory emergency room visits 0.000240 0.002600 0.008000

Acute bronchitis 0.000640 0.007600 0.025000

Lower respiratory symptoms 0.008200 0.097000 0.320000

Upper respiratory symptoms 0.012000 0.140000 0.460000

Minor Restricted Activity Days 0.320000 3.800000 12.000000

Work loss days 0.054000 0.640000 2.100000

Asthma exacerbation 0.012000 0.140000 0.480000

Cardiovascular hospital admissions 0.000150 0.001900 0.005900

Respiratory hospital admissions 0.000120 0.001500 0.004800

Non-fatal heart attacks (Peters) 0.000490 0.006000 0.019000

Non-fatal heart attacks (All others) 0.000053 0.000640 0.002100
60

Table 76. Dollar value (mortality and morbidity) per ton of directly emitted PM2.5 

and PM2.5 precursors reduced in 2020 from the refineries sector (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $7,000 $71,000 $330,000 

Lepeule et al. (2012) $16,000 $160,000 $750,000 

7% Discount Rate

Krewski et al. (2009) $6,300 $64,000 $300,000 

Lepeule et al. (2012) $14,000 $140,000 $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 77. 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

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000790 0.008000 0.038000

Lepeule et al. (2012) 0.001800 0.018000 0.085000

Morbidity

Respiratory emergency room visits 0.000430 0.004200 0.020000

Acute bronchitis 0.001300 0.013000 0.062000

Lower respiratory symptoms 0.017000 0.170000 0.790000

Upper respiratory symptoms 0.024000 0.240000 1.100000

Minor Restricted Activity Days 0.660000 6.700000 31.000000

Work loss days 0.110000 1.100000 5.300000

Asthma exacerbation 0.025000 0.250000 1.200000

Cardiovascular hospital admissions 0.000270 0.002700 0.013000

Respiratory hospital admissions 0.000220 0.002200 0.011000

Non-fatal heart attacks (Peters) 0.000870 0.008600 0.040000

Non-fatal heart attacks (All others) 0.000093 0.000930 0.004300
61

Table 78. 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 

(2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $14,000 $100,000 $380,000 

Lepeule et al. (2012) $31,000 $230,000 $860,000 

7% Discount Rate

Krewski et al. (2009) $12,000 $94,000 $350,000 

Lepeule et al. (2012) $28,000 $210,000 $780,000 

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 79. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.001600 0.012000 0.043000

Lepeule et al. (2012) 0.003500 0.027000 0.098000

Morbidity

Respiratory emergency room visits 0.000850 0.005900 0.022000

Acute bronchitis 0.002500 0.018000 0.067000

Lower respiratory symptoms 0.032000 0.230000 0.850000

Upper respiratory symptoms 0.045000 0.330000 1.200000

Minor Restricted Activity Days 1.200000 9.400000 34.000000

Work loss days 0.210000 1.600000 5.800000

Asthma exacerbation 0.047000 0.340000 3.000000

Cardiovascular hospital admissions 0.000510 0.003700 0.014000

Respiratory hospital admissions 0.000410 0.003000 0.011000

Non-fatal heart attacks (Peters) 0.001700 0.013000 0.047000

Non-fatal heart attacks (All others) 0.000190 0.001400 0.005100
62

Table 80. Dollar value (mortality and morbidity) per ton of directly emitted PM2.5 

and PM2.5 precursors reduced in 2020 from the taconite mines sector (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $6,200 $34,000 $86,000 

Lepeule et al. (2012) $14,000 $78,000 $190,000 

7% Discount Rate

Krewski et al. (2009) $5,600 $31,000 $77,000 

Lepeule et al. (2012) $13,000 $70,000 $170,000 

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 81. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000700 0.003900 0.009700

Lepeule et al. (2012) 0.001600 0.008800 0.022000

Morbidity

Respiratory emergency room visits 0.000380 0.002000 0.004300

Acute bronchitis 0.001100 0.005600 0.014000

Lower respiratory symptoms 0.013000 0.071000 0.170000

Upper respiratory symptoms 0.019000 0.100000 0.250000

Minor Restricted Activity Days 0.530000 2.800000 6.700000

Work loss days 0.089000 0.470000 1.100000

Asthma exacerbation 0.020000 0.110000 0.250000

Cardiovascular hospital admissions 0.000250 0.001400 0.003200

Respiratory hospital admissions 0.000200 0.001100 0.002600

Non-fatal heart attacks (Peters) 0.000800 0.004500 0.010000

Non-fatal heart attacks (All others) 0.000086 0.000490 0.001100
63

2025 Analysis Year
64

Table 82. 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 (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $8,000 $110,000 $280,000 

Lepeule et al. (2012) $18,000 $240,000 $620,000 

7% Discount Rate

Krewski et al. (2009) $7,200 $96,000 $250,000 

Lepeule et al. (2012) $16,000 $220,000 $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 83. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000880 0.012000 0.030000

Lepeule et al. (2012) 0.002000 0.027000 0.069000

Morbidity

Respiratory emergency room visits 0.000460 0.005400 0.016000

Acute bronchitis 0.001400 0.019000 0.046000

Lower respiratory symptoms 0.018000 0.250000 0.590000

Upper respiratory symptoms 0.025000 0.350000 0.840000

Minor Restricted Activity Days 0.680000 10.000000 23.000000

Work loss days 0.110000 1.700000 4.000000

Asthma exacerbation 0.026000 0.360000 0.870000

Cardiovascular hospital admissions 0.000310 0.003600 0.011000

Respiratory hospital admissions 0.000260 0.003000 0.008900

Non-fatal heart attacks (Peters) 0.001000 0.012000 0.034000

Non-fatal heart attacks (All others) 0.000110 0.001300 0.003700
65

Table 84. Dollar value (mortality and morbidity) per ton of directly emitted PM2.5 

and PM2.5 precursors reduced in 2025 from the area sources sector (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $8,700 $56,000 $370,000 

Lepeule et al. (2012) $20,000 $130,000 $840,000 

7% Discount Rate

Krewski et al. (2009) $7,900 $50,000 $330,000 

Lepeule et al. (2012) $18,000 $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 85. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000960 0.006100 0.041000

Lepeule et al. (2012) 0.002200 0.014000 0.092000

Morbidity

Respiratory emergency room visits 0.000540 0.003500 0.022000

Acute bronchitis 0.001500 0.009100 0.062000

Lower respiratory symptoms 0.019000 0.120000 0.790000

Upper respiratory symptoms 0.028000 0.170000 1.100000

Minor Restricted Activity Days 0.740000 4.600000 31.000000

Work loss days 0.120000 0.780000 5.300000

Asthma exacerbation 0.029000 0.410000 2.800000

Cardiovascular hospital admissions 0.000340 0.002200 0.015000

Respiratory hospital admissions 0.000280 0.001800 0.012000

Non-fatal heart attacks (Peters) 0.001100 0.007100 0.046000

Non-fatal heart attacks (All others) 0.000120 0.000770 0.005000
66

Table 86. Dollar value (mortality and morbidity) per ton of directly emitted PM2.5 

and PM2.5 precursors reduced in 2025 from the cement kilns sector (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $6,300 $49,000 $420,000 

Lepeule et al. (2012) $14,000 $110,000 $950,000 

7% Discount Rate

Krewski et al. (2009) $5,700 $44,000 $380,000 

Lepeule et al. (2012) $13,000 $99,000 $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 87. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000700 0.005400 0.046000

Lepeule et al. (2012) 0.001600 0.012000 0.100000

Morbidity

Respiratory emergency room visits 0.000390 0.002800 0.023000

Acute bronchitis 0.001100 0.007700 0.074000

Lower respiratory symptoms 0.014000 0.099000 0.940000

Upper respiratory symptoms 0.020000 0.140000 1.300000

Minor Restricted Activity Days 0.530000 3.800000 35.000000

Work loss days 0.089000 0.640000 6.000000

Asthma exacerbation 0.020000 0.150000 1.400000

Cardiovascular hospital admissions 0.000250 0.002000 0.016000

Respiratory hospital admissions 0.000210 0.001600 0.013000

Non-fatal heart attacks (Peters) 0.000810 0.006300 0.052000

Non-fatal heart attacks (All others) 0.000087 0.000680 0.005600
67

Table 88. Dollar value (mortality and morbidity) per ton of directly emitted PM2.5 

and PM2.5 precursors reduced in 2025 from the coke ovens sector (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $12,000 $57,000 $500,000 

Lepeule et al. (2012) $26,000 $130,000 $1,100,000 

7% Discount Rate

Krewski et al. (2009) $10,000 $51,000 $450,000 

Lepeule et al. (2012) $24,000 $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 89. 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

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.001300 0.006300 0.055000

Lepeule et al. (2012) 0.002900 0.014000 0.120000

Morbidity

Respiratory emergency room visits 0.000750 0.003300 0.027000

Acute bronchitis 0.001800 0.008600 0.069000

Lower respiratory symptoms 0.022000 0.110000 0.890000

Upper respiratory symptoms 0.032000 0.160000 1.300000

Minor Restricted Activity Days 0.870000 4.200000 34.000000

Work loss days 0.150000 0.710000 5.800000

Asthma exacerbation 0.033000 0.160000 1.300000

Cardiovascular hospital admissions 0.000500 0.002400 0.021000

Respiratory hospital admissions 0.000410 0.002000 0.017000

Non-fatal heart attacks (Peters) 0.001600 0.007600 0.065000

Non-fatal heart attacks (All others) 0.000170 0.000820 0.007000
68

Table 90. 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 (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $11,000 $89,000 $480,000 

Lepeule et al. (2012) $24,000 $200,000 $1,100,000 

7% Discount Rate

Krewski et al. (2009) $9,600 $80,000 $430,000 

Lepeule et al. (2012) $22,000 $180,000 $970,000 

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 91. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.001200 0.009800 0.053000

Lepeule et al. (2012) 0.002700 0.022000 0.120000

Morbidity

Respiratory emergency room visits 0.000690 0.004800 0.025000

Acute bronchitis 0.001700 0.013000 0.072000

Lower respiratory symptoms 0.022000 0.170000 0.910000

Upper respiratory symptoms 0.031000 0.250000 1.300000

Minor Restricted Activity Days 0.830000 6.600000 35.000000

Work loss days 0.140000 1.100000 5.900000

Asthma exacerbation 0.032000 0.250000 1.400000

Cardiovascular hospital admissions 0.000450 0.003500 0.019000

Respiratory hospital admissions 0.000360 0.002900 0.015000

Non-fatal heart attacks (Peters) 0.001400 0.011000 0.061000

Non-fatal heart attacks (All others) 0.000150 0.001200 0.006500
69

Table 92. 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 

(2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $5,800 $40,000 $150,000 

Lepeule et al. (2012) $13,000 $90,000 $340,000 

7% Discount Rate

Krewski et al. (2009) $5,200 $36,000 $130,000 

Lepeule et al. (2012) $12,000 $82,000 $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 93. 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

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000640 0.004400 0.016000

Lepeule et al. (2012) 0.001400 0.010000 0.037000

Morbidity

Respiratory emergency room visits 0.000350 0.002300 0.008900

Acute bronchitis 0.000960 0.006300 0.024000

Lower respiratory symptoms 0.012000 0.080000 0.310000

Upper respiratory symptoms 0.018000 0.120000 0.440000

Minor Restricted Activity Days 0.460000 3.100000 12.000000

Work loss days 0.078000 0.520000 2.000000

Asthma exacerbation 0.018000 0.280000 0.460000

Cardiovascular hospital admissions 0.000240 0.001700 0.006000

Respiratory hospital admissions 0.000200 0.001400 0.004900

Non-fatal heart attacks (Peters) 0.000770 0.005200 0.019000

Non-fatal heart attacks (All others) 0.000083 0.000570 0.002100
70

Table 94. Dollar value (mortality and morbidity) per ton of directly emitted PM2.5 

and PM2.5 precursors reduced in 2025 from the ferroalloy facilities sector (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $4,800 $50,000 $310,000 

Lepeule et al. (2012) $11,000 $110,000 $700,000 

7% Discount Rate

Krewski et al. (2009) $4,400 $45,000 $280,000 

Lepeule et al. (2012) $9,800 $100,000 $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 95. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000530 0.005500 0.034000

Lepeule et al. (2012) 0.001200 0.012000 0.077000

Morbidity

Respiratory emergency room visits 0.000240 0.002500 0.015000

Acute bronchitis 0.000690 0.007300 0.046000

Lower respiratory symptoms 0.008700 0.093000 0.580000

Upper respiratory symptoms 0.012000 0.130000 0.840000

Minor Restricted Activity Days 0.350000 3.600000 22.000000

Work loss days 0.058000 0.610000 3.700000

Asthma exacerbation 0.013000 0.140000 0.860000

Cardiovascular hospital admissions 0.000200 0.002000 0.012000

Respiratory hospital admissions 0.000160 0.001700 0.011000

Non-fatal heart attacks (Peters) 0.000630 0.006500 0.041000

Non-fatal heart attacks (All others) 0.000067 0.000700 0.004400
71

Table 96. 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 

(2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $7,000 $46,000 $300,000 

Lepeule et al. (2012) $16,000 $100,000 $680,000 

7% Discount Rate

Krewski et al. (2009) $6,300 $41,000 $270,000 

Lepeule et al. (2012) $14,000 $93,000 $620,000 

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 97. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000770 0.005000 0.033000

Lepeule et al. (2012) 0.001800 0.011000 0.075000

Morbidity

Respiratory emergency room visits 0.000420 0.002600 0.017000

Acute bronchitis 0.001200 0.007400 0.050000

Lower respiratory symptoms 0.015000 0.094000 0.640000

Upper respiratory symptoms 0.022000 0.130000 0.920000

Minor Restricted Activity Days 0.580000 3.600000 25.000000

Work loss days 0.098000 0.610000 4.200000

Asthma exacerbation 0.023000 0.140000 0.950000

Cardiovascular hospital admissions 0.000280 0.001900 0.012000

Respiratory hospital admissions 0.000230 0.001500 0.009800

Non-fatal heart attacks (Peters) 0.000910 0.005900 0.038000

Non-fatal heart attacks (All others) 0.000098 0.000640 0.004100
72

Table 98. 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 (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $15,000 $96,000 $540,000 

Lepeule et al. (2012) $34,000 $220,000 $1,200,000 

7% Discount Rate

Krewski et al. (2009) $13,000 $87,000 $480,000 

Lepeule et al. (2012) $30,000 $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 99. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.001600 0.011000 0.059000

Lepeule et al. (2012) 0.003700 0.024000 0.130000

Morbidity

Respiratory emergency room visits 0.000930 0.005900 0.032000

Acute bronchitis 0.002300 0.015000 0.079000

Lower respiratory symptoms 0.029000 0.190000 1.000000

Upper respiratory symptoms 0.042000 0.270000 1.400000

Minor Restricted Activity Days 1.100000 7.200000 38.000000

Work loss days 0.190000 1.200000 6.500000

Asthma exacerbation 0.043000 0.280000 1.500000

Cardiovascular hospital admissions 0.000650 0.004100 0.023000

Respiratory hospital admissions 0.000530 0.003400 0.019000

Non-fatal heart attacks (Peters) 0.002000 0.013000 0.073000

Non-fatal heart attacks (All others) 0.000220 0.001400 0.007800
73

Table 100. 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 

(2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $19,000 $450,000 $570,000 

Lepeule et al. (2012) $42,000 $1,000,000 $1,300,000 

7% Discount Rate

Krewski et al. (2009) $17,000 $410,000 $510,000 

Lepeule et al. (2012) $38,000 $920,000 $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 101. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.002100 0.050000 0.063000

Lepeule et al. (2012) 0.004700 0.110000 0.140000

Morbidity

Respiratory emergency room visits 0.001100 0.025000 0.031000

Acute bronchitis 0.003300 0.071000 0.093000

Lower respiratory symptoms 0.042000 0.910000 1.200000

Upper respiratory symptoms 0.060000 1.300000 1.700000

Minor Restricted Activity Days 1.600000 36.000000 46.000000

Work loss days 0.280000 6.000000 7.800000

Asthma exacerbation 0.062000 1.300000 1.800000

Cardiovascular hospital admissions 0.000740 0.018000 0.022000

Respiratory hospital admissions 0.000610 0.015000 0.018000

Non-fatal heart attacks (Peters) 0.002400 0.057000 0.071000

Non-fatal heart attacks (All others) 0.000250 0.006100 0.007600
74

Table 102. 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 

(2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $7,700 $52,000 $360,000 

Lepeule et al. (2012) $17,000 $120,000 $810,000 

7% Discount Rate

Krewski et al. (2009) $7,000 $47,000 $320,000 

Lepeule et al. (2012) $16,000 $110,000 $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 103. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000850 0.005700 0.040000

Lepeule et al. (2012) 0.001900 0.013000 0.089000

Morbidity

Respiratory emergency room visits 0.000460 0.002800 0.022000

Acute bronchitis 0.001400 0.010000 0.061000

Lower respiratory symptoms 0.018000 0.130000 0.780000

Upper respiratory symptoms 0.025000 0.180000 1.100000

Minor Restricted Activity Days 0.670000 4.700000 31.000000

Work loss days 0.110000 0.800000 5.300000

Asthma exacerbation 0.026000 0.190000 1.200000

Cardiovascular hospital admissions 0.000300 0.001800 0.014000

Respiratory hospital admissions 0.000240 0.001500 0.012000

Non-fatal heart attacks (Peters) 0.000980 0.006100 0.045000

Non-fatal heart attacks (All others) 0.000110 0.000660 0.004900
75

Table 104. 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 (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $2,300 $14,000 $53,000 

Lepeule et al. (2012) $5,100 $32,000 $120,000 

7% Discount Rate

Krewski et al. (2009) $2,000 $13,000 $48,000 

Lepeule et al. (2012) $4,600 $29,000 $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 105. Incidence of avoided mortalities and morbidities per ton of directly 

emitted PM2.5 and PM2.5 precursors reduced in 2025 from the ocean-going vessels 

sector

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000250 0.001600 0.005900

Lepeule et al. (2012) 0.000560 0.003500 0.013000

Morbidity

Respiratory emergency room visits 0.000130 0.000740 0.002800

Acute bronchitis 0.000410 0.002200 0.008500

Lower respiratory symptoms 0.005200 0.028000 0.110000

Upper respiratory symptoms 0.007400 0.040000 0.150000

Minor Restricted Activity Days 0.210000 1.100000 4.400000

Work loss days 0.036000 0.190000 0.750000

Asthma exacerbation 0.007600 0.041000 0.160000

Cardiovascular hospital admissions 0.000081 0.000540 0.002000

Respiratory hospital admissions 0.000067 0.000430 0.001600

Non-fatal heart attacks (Peters) 0.000270 0.001800 0.006600

Non-fatal heart attacks (All others) 0.000029 0.000190 0.000720
76

Table 106. 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 

(2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $8,400 $23,000 $420,000 

Lepeule et al. (2012) $19,000 $52,000 $950,000 

7% Discount Rate

Krewski et al. (2009) $7,600 $21,000 $380,000 

Lepeule et al. (2012) $17,000 $47,000 $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 107. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000930 0.002600 0.047000

Lepeule et al. (2012) 0.002100 0.005800 0.110000

Morbidity

Respiratory emergency room visits 0.000510 0.001200 0.026000

Acute bronchitis 0.001400 0.004400 0.072000

Lower respiratory symptoms 0.018000 0.056000 0.920000

Upper respiratory symptoms 0.027000 0.080000 1.300000

Minor Restricted Activity Days 0.710000 2.100000 37.000000

Work loss days 0.120000 0.350000 6.200000

Asthma exacerbation 0.065000 0.082000 3.300000

Cardiovascular hospital admissions 0.000340 0.000810 0.017000

Respiratory hospital admissions 0.000280 0.000660 0.014000

Non-fatal heart attacks (Peters) 0.001100 0.002700 0.053000

Non-fatal heart attacks (All others) 0.000120 0.000290 0.005700
77

Table 108. 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 

(2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $4,200 $51,000 $170,000 

Lepeule et al. (2012) $9,400 $120,000 $380,000 

7% Discount Rate

Krewski et al. (2009) $3,700 $46,000 $150,000 

Lepeule et al. (2012) $8,500 $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 109. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000460 0.005700 0.019000

Lepeule et al. (2012) 0.001000 0.013000 0.042000

Morbidity

Respiratory emergency room visits 0.000240 0.002700 0.008400

Acute bronchitis 0.000670 0.008000 0.027000

Lower respiratory symptoms 0.008500 0.100000 0.340000

Upper respiratory symptoms 0.012000 0.150000 0.480000

Minor Restricted Activity Days 0.330000 3.900000 13.000000

Work loss days 0.055000 0.660000 2.100000

Asthma exacerbation 0.013000 0.150000 0.500000

Cardiovascular hospital admissions 0.000170 0.002000 0.006500

Respiratory hospital admissions 0.000130 0.001700 0.005300

Non-fatal heart attacks (Peters) 0.000540 0.006600 0.021000

Non-fatal heart attacks (All others) 0.000058 0.000710 0.002300
78

Table 110. Dollar value (mortality and morbidity) per ton of directly emitted PM2.5 

and PM2.5 precursors reduced in 2025 from the refineries sector (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $7,700 $79,000 $370,000 

Lepeule et al. (2012) $17,000 $180,000 $830,000 

7% Discount Rate

Krewski et al. (2009) $6,900 $71,000 $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 111. 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

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000850 0.008600 0.040000

Lepeule et al. (2012) 0.001900 0.020000 0.091000

Morbidity

Respiratory emergency room visits 0.000440 0.004300 0.020000

Acute bronchitis 0.001400 0.014000 0.065000

Lower respiratory symptoms 0.018000 0.180000 0.820000

Upper respiratory symptoms 0.025000 0.250000 1.200000

Minor Restricted Activity Days 0.670000 6.800000 32.000000

Work loss days 0.110000 1.200000 5.300000

Asthma exacerbation 0.026000 0.260000 1.200000

Cardiovascular hospital admissions 0.000290 0.003000 0.014000

Respiratory hospital admissions 0.000240 0.002500 0.012000

Non-fatal heart attacks (Peters) 0.000960 0.009600 0.044000

Non-fatal heart attacks (All others) 0.000100 0.001000 0.004800
79

Table 112. 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 

(2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $15,000 $120,000 $420,000 

Lepeule et al. (2012) $34,000 $260,000 $950,000 

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 113. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.001700 0.013000 0.047000

Lepeule et al. (2012) 0.003800 0.029000 0.110000

Morbidity

Respiratory emergency room visits 0.000880 0.006200 0.023000

Acute bronchitis 0.002600 0.019000 0.070000

Lower respiratory symptoms 0.033000 0.240000 0.890000

Upper respiratory symptoms 0.047000 0.340000 1.300000

Minor Restricted Activity Days 1.300000 9.600000 35.000000

Work loss days 0.210000 1.600000 5.900000

Asthma exacerbation 0.049000 0.360000 3.100000

Cardiovascular hospital admissions 0.000560 0.004100 0.015000

Respiratory hospital admissions 0.000460 0.003400 0.013000

Non-fatal heart attacks (Peters) 0.001900 0.014000 0.052000

Non-fatal heart attacks (All others) 0.000200 0.001500 0.005700
80

Table 114. Dollar value (mortality and morbidity) per ton of directly emitted PM2.5 

and PM2.5 precursors reduced in 2025 from the taconite mines sector (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $6,600 $37,000 $93,000 

Lepeule et al. (2012) $15,000 $84,000 $210,000 

7% Discount Rate

Krewski et al. (2009) $6,000 $34,000 $84,000 

Lepeule et al. (2012) $14,000 $76,000 $190,000 

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 115. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000730 0.004100 0.010000

Lepeule et al. (2012) 0.001700 0.009300 0.023000

Morbidity

Respiratory emergency room visits 0.000380 0.002000 0.004500

Acute bronchitis 0.001100 0.005800 0.014000

Lower respiratory symptoms 0.014000 0.074000 0.180000

Upper respiratory symptoms 0.020000 0.110000 0.250000

Minor Restricted Activity Days 0.530000 2.800000 6.700000

Work loss days 0.089000 0.480000 1.100000

Asthma exacerbation 0.020000 0.110000 0.260000

Cardiovascular hospital admissions 0.000270 0.001500 0.003500

Respiratory hospital admissions 0.000220 0.001200 0.002800

Non-fatal heart attacks (Peters) 0.000870 0.004900 0.011000

Non-fatal heart attacks (All others) 0.000093 0.000530 0.001200
81

2030 Analysis Year
82

Table 116. 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 (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $8,700 $120,000 $300,000 

Lepeule et al. (2012) $20,000 $270,000 $680,000 

7% Discount Rate

Krewski et al. (2009) $7,800 $110,000 $270,000 

Lepeule et al. (2012) $18,000 $240,000 $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 117. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000960 0.013000 0.033000

Lepeule et al. (2012) 0.002200 0.030000 0.075000

Morbidity

Respiratory emergency room visits 0.000480 0.005700 0.016000

Acute bronchitis 0.001400 0.020000 0.047000

Lower respiratory symptoms 0.018000 0.260000 0.600000

Upper respiratory symptoms 0.026000 0.370000 0.860000

Minor Restricted Activity Days 0.690000 10.000000 24.000000

Work loss days 0.120000 1.700000 4.000000

Asthma exacerbation 0.027000 0.380000 0.900000

Cardiovascular hospital admissions 0.000340 0.004100 0.012000

Respiratory hospital admissions 0.000290 0.003500 0.009900

Non-fatal heart attacks (Peters) 0.001100 0.014000 0.038000

Non-fatal heart attacks (All others) 0.000120 0.001500 0.004000
83

Table 118. Dollar value (mortality and morbidity) per ton of directly emitted PM2.5 

and PM2.5 precursors reduced in 2030 from the area sources sector (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $9,400 $60,000 $400,000 

Lepeule et al. (2012) $21,000 $140,000 $910,000 

7% Discount Rate

Krewski et al. (2009) $8,500 $54,000 $360,000 

Lepeule et al. (2012) $19,000 $120,000 $820,000 

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 119. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.001000 0.006600 0.044000

Lepeule et al. (2012) 0.002300 0.015000 0.100000

Morbidity

Respiratory emergency room visits 0.000560 0.003600 0.023000

Acute bronchitis 0.001600 0.009400 0.064000

Lower respiratory symptoms 0.020000 0.120000 0.820000

Upper respiratory symptoms 0.029000 0.170000 1.200000

Minor Restricted Activity Days 0.750000 4.700000 32.000000

Work loss days 0.130000 0.790000 5.500000

Asthma exacerbation 0.030000 0.420000 2.900000

Cardiovascular hospital admissions 0.000380 0.002500 0.016000

Respiratory hospital admissions 0.000310 0.002000 0.013000

Non-fatal heart attacks (Peters) 0.001200 0.007800 0.051000

Non-fatal heart attacks (All others) 0.000130 0.000850 0.005600
84

Table 120. Dollar value (mortality and morbidity) per ton of directly emitted PM2.5 

and PM2.5 precursors reduced in 2030 from the cement kilns sector (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $6,800 $52,000 $460,000 

Lepeule et al. (2012) $15,000 $120,000 $1,000,000 

7% Discount Rate

Krewski et al. (2009) $6,100 $47,000 $410,000 

Lepeule et al. (2012) $14,000 $110,000 $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 121. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000750 0.005800 0.051000

Lepeule et al. (2012) 0.001700 0.013000 0.110000

Morbidity

Respiratory emergency room visits 0.000400 0.002900 0.024000

Acute bronchitis 0.001100 0.008000 0.077000

Lower respiratory symptoms 0.014000 0.100000 0.980000

Upper respiratory symptoms 0.020000 0.150000 1.400000

Minor Restricted Activity Days 0.540000 3.900000 36.000000

Work loss days 0.091000 0.660000 6.200000

Asthma exacerbation 0.021000 0.150000 1.400000

Cardiovascular hospital admissions 0.000280 0.002100 0.018000

Respiratory hospital admissions 0.000230 0.001800 0.014000

Non-fatal heart attacks (Peters) 0.000890 0.006900 0.058000

Non-fatal heart attacks (All others) 0.000096 0.000740 0.006300
85

Table 122. Dollar value (mortality and morbidity) per ton of directly emitted PM2.5 

and PM2.5 precursors reduced in 2030 from the coke ovens sector (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $12,000 $61,000 $530,000 

Lepeule et al. (2012) $28,000 $140,000 $1,200,000 

7% Discount Rate

Krewski et al. (2009) $11,000 $55,000 $480,000 

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 123. 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

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.001400 0.006700 0.058000

Lepeule et al. (2012) 0.003100 0.015000 0.130000

Morbidity

Respiratory emergency room visits 0.000760 0.003400 0.027000

Acute bronchitis 0.001800 0.008800 0.070000

Lower respiratory symptoms 0.023000 0.110000 0.890000

Upper respiratory symptoms 0.032000 0.160000 1.300000

Minor Restricted Activity Days 0.870000 4.300000 34.000000

Work loss days 0.150000 0.720000 5.800000

Asthma exacerbation 0.034000 0.170000 1.300000

Cardiovascular hospital admissions 0.000530 0.002600 0.022000

Respiratory hospital admissions 0.000440 0.002100 0.018000

Non-fatal heart attacks (Peters) 0.001700 0.008300 0.070000

Non-fatal heart attacks (All others) 0.000180 0.000890 0.007500
86

Table 124. 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 (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $11,000 $95,000 $510,000 

Lepeule et al. (2012) $26,000 $220,000 $1,200,000 

7% Discount Rate

Krewski et al. (2009) $10,000 $86,000 $460,000 

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 125. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.001200 0.011000 0.056000

Lepeule et al. (2012) 0.002800 0.024000 0.130000

Morbidity

Respiratory emergency room visits 0.000710 0.005000 0.026000

Acute bronchitis 0.001800 0.014000 0.073000

Lower respiratory symptoms 0.022000 0.180000 0.940000

Upper respiratory symptoms 0.032000 0.250000 1.300000

Minor Restricted Activity Days 0.840000 6.800000 36.000000

Work loss days 0.140000 1.100000 6.000000

Asthma exacerbation 0.033000 0.260000 1.400000

Cardiovascular hospital admissions 0.000480 0.003800 0.020000

Respiratory hospital admissions 0.000400 0.003200 0.017000

Non-fatal heart attacks (Peters) 0.001500 0.012000 0.066000

Non-fatal heart attacks (All others) 0.000160 0.001300 0.007100
87

Table 126. 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 

(2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $6,200 $43,000 $160,000 

Lepeule et al. (2012) $14,000 $97,000 $360,000 

7% Discount Rate

Krewski et al. (2009) $5,600 $39,000 $140,000 

Lepeule et al. (2012) $13,000 $87,000 $330,000 

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 127. 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

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000680 0.004800 0.018000

Lepeule et al. (2012) 0.001500 0.011000 0.040000

Morbidity

Respiratory emergency room visits 0.000350 0.002300 0.009200

Acute bronchitis 0.000980 0.006500 0.025000

Lower respiratory symptoms 0.013000 0.083000 0.320000

Upper respiratory symptoms 0.018000 0.120000 0.460000

Minor Restricted Activity Days 0.470000 3.200000 12.000000

Work loss days 0.079000 0.540000 2.100000

Asthma exacerbation 0.019000 0.290000 0.480000

Cardiovascular hospital admissions 0.000260 0.001800 0.006600

Respiratory hospital admissions 0.000220 0.001500 0.005500

Non-fatal heart attacks (Peters) 0.000830 0.005700 0.021000

Non-fatal heart attacks (All others) 0.000090 0.000620 0.002300
88

Table 128. Dollar value (mortality and morbidity) per ton of directly emitted PM2.5 

and PM2.5 precursors reduced in 2030 from the ferroalloy facilities sector (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $5,100 $53,000 $330,000 

Lepeule et al. (2012) $12,000 $120,000 $740,000 

7% Discount Rate

Krewski et al. (2009) $4,600 $48,000 $290,000 

Lepeule et al. (2012) $10,000 $110,000 $670,000 

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 129. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000570 0.005900 0.036000

Lepeule et al. (2012) 0.001300 0.013000 0.082000

Morbidity

Respiratory emergency room visits 0.000240 0.002600 0.016000

Acute bronchitis 0.000700 0.007500 0.047000

Lower respiratory symptoms 0.008900 0.096000 0.590000

Upper respiratory symptoms 0.013000 0.140000 0.850000

Minor Restricted Activity Days 0.350000 3.700000 23.000000

Work loss days 0.059000 0.620000 3.800000

Asthma exacerbation 0.013000 0.140000 0.880000

Cardiovascular hospital admissions 0.000210 0.002200 0.013000

Respiratory hospital admissions 0.000170 0.001800 0.012000

Non-fatal heart attacks (Peters) 0.000680 0.007100 0.044000

Non-fatal heart attacks (All others) 0.000073 0.000760 0.004700
89

Table 130. 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 

(2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $7,600 $49,000 $330,000 

Lepeule et al. (2012) $17,000 $110,000 $740,000 

7% Discount Rate

Krewski et al. (2009) $6,800 $44,000 $300,000 

Lepeule et al. (2012) $15,000 $100,000 $670,000 

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 131. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000830 0.005400 0.036000

Lepeule et al. (2012) 0.001900 0.012000 0.082000

Morbidity

Respiratory emergency room visits 0.000430 0.002700 0.018000

Acute bronchitis 0.001200 0.007600 0.052000

Lower respiratory symptoms 0.016000 0.097000 0.670000

Upper respiratory symptoms 0.023000 0.140000 0.950000

Minor Restricted Activity Days 0.590000 3.700000 26.000000

Work loss days 0.100000 0.630000 4.300000

Asthma exacerbation 0.023000 0.140000 0.990000

Cardiovascular hospital admissions 0.000310 0.002000 0.013000

Respiratory hospital admissions 0.000260 0.001700 0.011000

Non-fatal heart attacks (Peters) 0.001000 0.006400 0.042000

Non-fatal heart attacks (All others) 0.000110 0.000700 0.004500
90

Table 132. 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 (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $16,000 $100,000 $570,000 

Lepeule et al. (2012) $36,000 $230,000 $1,300,000 

7% Discount Rate

Krewski et al. (2009) $14,000 $92,000 $510,000 

Lepeule et al. (2012) $32,000 $210,000 $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 133. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.001700 0.011000 0.063000

Lepeule et al. (2012) 0.003900 0.026000 0.140000

Morbidity

Respiratory emergency room visits 0.000950 0.006000 0.032000

Acute bronchitis 0.002300 0.015000 0.079000

Lower respiratory symptoms 0.030000 0.190000 1.000000

Upper respiratory symptoms 0.042000 0.270000 1.400000

Minor Restricted Activity Days 1.100000 7.200000 38.000000

Work loss days 0.190000 1.200000 6.500000

Asthma exacerbation 0.044000 0.280000 1.500000

Cardiovascular hospital admissions 0.000700 0.004500 0.025000

Respiratory hospital admissions 0.000570 0.003700 0.021000

Non-fatal heart attacks (Peters) 0.002200 0.014000 0.078000

Non-fatal heart attacks (All others) 0.000240 0.001500 0.008500
91

Table 134. 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 

(2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $20,000 $480,000 $610,000 

Lepeule et al. (2012) $46,000 $1,100,000 $1,400,000 

7% Discount Rate

Krewski et al. (2009) $18,000 $440,000 $550,000 

Lepeule et al. (2012) $41,000 $980,000 $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 135. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.002200 0.053000 0.068000

Lepeule et al. (2012) 0.005100 0.120000 0.150000

Morbidity

Respiratory emergency room visits 0.001100 0.026000 0.032000

Acute bronchitis 0.003400 0.073000 0.095000

Lower respiratory symptoms 0.043000 0.930000 1.200000

Upper respiratory symptoms 0.062000 1.300000 1.700000

Minor Restricted Activity Days 1.700000 36.000000 47.000000

Work loss days 0.280000 6.100000 7.900000

Asthma exacerbation 0.064000 1.400000 1.800000

Cardiovascular hospital admissions 0.000810 0.019000 0.024000

Respiratory hospital admissions 0.000680 0.016000 0.020000

Non-fatal heart attacks (Peters) 0.002600 0.062000 0.078000

Non-fatal heart attacks (All others) 0.000280 0.006700 0.008400
92

Table 136. 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 

(2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

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 $52,000 $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 137. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000930 0.006300 0.043000

Lepeule et al. (2012) 0.002100 0.014000 0.097000

Morbidity

Respiratory emergency room visits 0.000480 0.003000 0.023000

Acute bronchitis 0.001400 0.010000 0.063000

Lower respiratory symptoms 0.018000 0.130000 0.810000

Upper respiratory symptoms 0.026000 0.190000 1.200000

Minor Restricted Activity Days 0.690000 4.900000 32.000000

Work loss days 0.120000 0.830000 5.400000

Asthma exacerbation 0.027000 0.200000 1.200000

Cardiovascular hospital admissions 0.000330 0.002000 0.016000

Respiratory hospital admissions 0.000270 0.001700 0.013000

Non-fatal heart attacks (Peters) 0.001100 0.006900 0.050000

Non-fatal heart attacks (All others) 0.000120 0.000740 0.005400
93

Table 138. 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 (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $2,500 $16,000 $58,000 

Lepeule et al. (2012) $5,600 $35,000 $130,000 

7% Discount Rate

Krewski et al. (2009) $2,300 $14,000 $53,000 

Lepeule et al. (2012) $5,100 $32,000 $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 139. Incidence of avoided mortalities and morbidities per ton of directly 

emitted PM2.5 and PM2.5 precursors reduced in 2030 from the ocean-going vessels 

sector

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000280 0.001700 0.006400

Lepeule et al. (2012) 0.000620 0.003900 0.015000

Morbidity

Respiratory emergency room visits 0.000130 0.000780 0.002900

Acute bronchitis 0.000420 0.002300 0.008800

Lower respiratory symptoms 0.005300 0.029000 0.110000

Upper respiratory symptoms 0.007600 0.041000 0.160000

Minor Restricted Activity Days 0.210000 1.200000 4.500000

Work loss days 0.036000 0.200000 0.760000

Asthma exacerbation 0.007900 0.043000 0.170000

Cardiovascular hospital admissions 0.000092 0.000600 0.002200

Respiratory hospital admissions 0.000077 0.000490 0.001800

Non-fatal heart attacks (Peters) 0.000300 0.002000 0.007400

Non-fatal heart attacks (All others) 0.000033 0.000210 0.000800
94

Table 140. 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 

(2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $9,100 $26,000 $460,000 

Lepeule et al. (2012) $21,000 $58,000 $1,000,000 

7% Discount Rate

Krewski et al. (2009) $8,200 $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 141. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.001000 0.002800 0.051000

Lepeule et al. (2012) 0.002300 0.006400 0.110000

Morbidity

Respiratory emergency room visits 0.000530 0.001300 0.026000

Acute bronchitis 0.001500 0.004600 0.075000

Lower respiratory symptoms 0.019000 0.058000 0.950000

Upper respiratory symptoms 0.027000 0.083000 1.400000

Minor Restricted Activity Days 0.720000 2.100000 37.000000

Work loss days 0.120000 0.360000 6.400000

Asthma exacerbation 0.067000 0.086000 3.400000

Cardiovascular hospital admissions 0.000370 0.000910 0.018000

Respiratory hospital admissions 0.000300 0.000750 0.015000

Non-fatal heart attacks (Peters) 0.001200 0.003100 0.059000

Non-fatal heart attacks (All others) 0.000130 0.000330 0.006400
95

Table 142. 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 

(2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $4,500 $55,000 $180,000 

Lepeule et al. (2012) $10,000 $130,000 $410,000 

7% Discount Rate

Krewski et al. (2009) $4,000 $50,000 $170,000 

Lepeule et al. (2012) $9,100 $110,000 $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 143. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000490 0.006100 0.020000

Lepeule et al. (2012) 0.001100 0.014000 0.046000

Morbidity

Respiratory emergency room visits 0.000250 0.002900 0.008700

Acute bronchitis 0.000680 0.008200 0.027000

Lower respiratory symptoms 0.008700 0.100000 0.350000

Upper respiratory symptoms 0.012000 0.150000 0.500000

Minor Restricted Activity Days 0.330000 4.000000 13.000000

Work loss days 0.056000 0.680000 2.200000

Asthma exacerbation 0.013000 0.160000 0.520000

Cardiovascular hospital admissions 0.000180 0.002200 0.007100

Respiratory hospital admissions 0.000150 0.001800 0.005900

Non-fatal heart attacks (Peters) 0.000590 0.007200 0.023000

Non-fatal heart attacks (All others) 0.000063 0.000770 0.002500
96

Table 144. Dollar value (mortality and morbidity) per ton of directly emitted PM2.5 

and PM2.5 precursors reduced in 2030 from the refineries sector (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $8,300 $86,000 $400,000 

Lepeule et al. (2012) $19,000 $190,000 $900,000 

7% Discount Rate

Krewski et al. (2009) $7,500 $77,000 $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 145. 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

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000920 0.009500 0.044000

Lepeule et al. (2012) 0.002100 0.021000 0.099000

Morbidity

Respiratory emergency room visits 0.000460 0.004500 0.021000

Acute bronchitis 0.001400 0.014000 0.066000

Lower respiratory symptoms 0.018000 0.180000 0.850000

Upper respiratory symptoms 0.026000 0.260000 1.200000

Minor Restricted Activity Days 0.680000 7.000000 32.000000

Work loss days 0.120000 1.200000 5.400000

Asthma exacerbation 0.027000 0.270000 1.300000

Cardiovascular hospital admissions 0.000330 0.003300 0.016000

Respiratory hospital admissions 0.000270 0.002800 0.013000

Non-fatal heart attacks (Peters) 0.001100 0.011000 0.049000

Non-fatal heart attacks (All others) 0.000110 0.001200 0.005300
97

Table 146. 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 

(2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $16,000 $130,000 $460,000 

Lepeule et al. (2012) $37,000 $280,000 $1,000,000 

7% Discount Rate

Krewski et al. (2009) $15,000 $110,000 $420,000 

Lepeule et al. (2012) $33,000 $250,000 $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 147. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.001800 0.014000 0.051000

Lepeule et al. (2012) 0.004100 0.031000 0.110000

Morbidity

Respiratory emergency room visits 0.000900 0.006400 0.024000

Acute bronchitis 0.002700 0.020000 0.072000

Lower respiratory symptoms 0.034000 0.250000 0.920000

Upper respiratory symptoms 0.049000 0.360000 1.300000

Minor Restricted Activity Days 1.300000 9.800000 36.000000

Work loss days 0.220000 1.700000 6.100000

Asthma exacerbation 0.050000 0.370000 3.300000

Cardiovascular hospital admissions 0.000610 0.004500 0.017000

Respiratory hospital admissions 0.000510 0.003800 0.014000

Non-fatal heart attacks (Peters) 0.002100 0.016000 0.057000

Non-fatal heart attacks (All others) 0.000220 0.001700 0.006300
98

Table 148. Dollar value (mortality and morbidity) per ton of directly emitted PM2.5 

and PM2.5 precursors reduced in 2030 from the taconite mines sector (2010$)

Pollutant emitted

Mortality risk estimateA NOx SO2

Directly emitted 

PM2.5

3% Discount Rate

Krewski et al. (2009) $7,100 $40,000 $100,000 

Lepeule et al. (2012) $16,000 $90,000 $220,000 

7% Discount Rate

Krewski et al. (2009) $6,400 $36,000 $90,000 

Lepeule et al. (2012) $14,000 $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 149. 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

Pollutant emitted

Health Endpoint NOx SO2

Directly emitted 

PM2.5

Premature mortality

Krewski et al. (2009) 0.000780 0.004400 0.011000

Lepeule et al. (2012) 0.001800 0.010000 0.025000

Morbidity

Respiratory emergency room visits 0.000390 0.002100 0.004600

Acute bronchitis 0.001100 0.005900 0.014000

Lower respiratory symptoms 0.014000 0.076000 0.180000

Upper respiratory symptoms 0.020000 0.110000 0.260000

Minor Restricted Activity Days 0.530000 2.900000 6.800000

Work loss days 0.090000 0.490000 1.100000

Asthma exacerbation 0.021000 0.110000 0.270000

Cardiovascular hospital admissions 0.000290 0.001600 0.003800

Respiratory hospital admissions 0.000240 0.001400 0.003100

Non-fatal heart attacks (Peters) 0.000940 0.005400 0.012000

Non-fatal heart attacks (All others) 0.000100 0.000580 0.001300
99

Appendix B

Modeled annual mean PM2.5 levels attributable to 

sectors in 2016
100
101
102
103
104
105

References

Abt Associates Inc., 2012. BenMAP User’s Manual Appendices, Prepared for U.S. 

Environmental Protection Agency Office of Air Quality Planning and Standards. 

Research Triangle Park, NC. Available at: 

http://www.epa.gov/air/benmap/models/BenMAPAppendicesOct2012.pdf.

Davidson, K. et al., 2007. Analysis of PM2.5 using the Environmental Benefits Mapping and 

Analysis Program (BenMAP). Journal of Toxicology and Environmental Health. Part A, 

70(3-4), pp.332–46.

Fann, N., Baker, K.R. & Fulcher, C.M., 2012. Characterizing the PM2.5-related health benefits 

of emission reductions for 17 industrial, area and mobile emission sectors across the 

U.S. Environment international, 49, pp.141–51. Available at: 

http://www.ncbi.nlm.nih.gov/pubmed/23022875 [Accessed January 14, 2013].

Fann, N., Fulcher, C.M. & Hubbell, B.J., 2009. The influence of location, source, and emission 

type in estimates of the human health benefits of reducing a ton of air pollution. Air 

Quality, Atmosphere, & Health, 2(3), pp.169–176.

Hubbell, B.J. et al., 2004. Health-Related Benefits of Attaining the 8-Hr Ozone Standard. 

Environmental Health Perspectives, 113(1), pp.73–82.

Hubbell, B.J., Fann, N. & Levy, J.I., 2009. Methodological considerations in developing localscale health impact assessments: balancing national, regional, and local data. Air 

Quality, Atmosphere & Health, 2(2), pp.99–110.

Levy, J.I., Baxter, L.K. & Schwartz, J., 2009. Uncertainty and Variability in Health-Related 

Damages from Coal-Fired Power Plants in the United States. Risk Analysis, 29(7), 

pp.1000–1014.

Mansfield, C., Sinha, P. & Henrion, M., 2009. Influence Analysis in Support of Characterizing 

Uncertainty in Human Health Benefits Analysis Influence Analysis in Support of 

Characterizing Uncertainty in Human Health Benefits Analysis: Final Report, Prepared 

for U.S. EPA, Office of Air Quality Planning and Standards. Research Triangle Park, NC. 

Available at: 

http://www.epa.gov/ttn/ecas/regdata/Benefits/influence_analysis_final_report_psg.p

df.

Office of Management and Budget (OMB), 2003. Circular A-4: Regulatory Analysis, 

Washington, DC. Available at: http://www.whitehouse.gov/omb/circulars/a004/a4.html.

Roman, H.A. et al., 2008. Expert judgment assessment of the mortality impact of changes in 

ambient fine particulate matter in the U.S. Environmental Science & Technology, 42(7), 

pp.2268–74.
106

Tagaris, E. et al., 2009. Potential impact of climate change on air pollution-related human 

health effects. Environmental Science & Technology, 43(13), pp.4979–88.

US EPA, 2005. 2005 National Emissions Inventory Data & Documentation, Available at: 

www.epa.gov/ttnchie1/net/2005inventory.html.

US EPA, 2011a. Air Quality Modeling Technical Support Document: Source Sector 

Assessments, Research Triangle Park, NC. Available at: 

http://www.epa.gov/scram001/reports/EPA454_R11_006.pdf.

US EPA, 2000. Guidelines for Preparing Economic Analyses, EPA 240-R-00-003. National 

Center for Environmental Economics, Office of Policy Economics and Innovation. 

Washington, DC. Available at: 

http://yosemite.epa.gov/ee/epa/eed.nsf/webpages/Guidelines.html/$file/cover.pdf.

US EPA, 2010a. Guidelines for Preparing Economic Analyses, EPA 240-R-10-001. National 

Center for Environmental Economics, Office of Policy Economics and Innovation. 

Washington, DC. Available at: http://yosemite.epa.gov/ee/epa/eerm.nsf/vwAN/EE0568-50.pdf/$file/EE-0568- 50.pdf.

US EPA, 2009. Integrated Science Assessment for Particulate Matter (Final Report), EPA-600-

R-08-139F. National Center for Environmental Assessment – RTP Division. Research 

Triangle Park, NC. Available at: 

http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=216546.

US EPA, 2011b. North American Emissions Inventories — Canada, Available at: 

http://www.epa.gov/ttnchie1/net/canada.html.

US EPA, 2011c. North American Emissions Inventories — Mexico, Available at: 

http://www.epa.gov/ttnchie1/net/mexico.html.

US EPA, 2010b. Regulatory Impact Analysis (RIA) for existing stationary Spark Ignition (SI) 

RICE NESHAP, EPA-452/R-10-010. Research Triangle Park, NC. Available at: 

http://www.epa.gov/ttn/ecas/regdata/RIAs/riceriafinal.pdf.

US EPA, 2012. Regulatory Impact Analysis for the Final Revisions to the National Ambient Air 

Quality Standards for Particulate Matter, Research Triangle Park, NC. Available at: 

http://www.epa.gov/pm/2012/finalria.pdf.

US EPA, 1998. Regulatory impact analysis for the NOx SIP call, FIP, and Section 126 petitions, 

EPA-452/R-98-003. Available at: http://www.epa.gov/ttn/oarpg/otag/sipriav2.zip.

US EPA, 2010c. Regulatory impact analysis for the proposed federal transport rule, EPA-HQOAR-2009-0491. Research Triangle Park, NC. Available at: 

http://www.epa.gov/ttn/ecas/regdata/RIAs/proposaltrria_final.pdf.
107

US EPA, 2006. Regulatory Impact Analysis, 2006 National Ambient Air Quality Standards for 

Particulate Matter, Chapter 5, Research Triangle Park, NC. Available at: 

http://www.epa.gov/ttn/ecas/regdata/RIAs/Chapter 5--Benefits.pdf.

US EPA, 2011d. Regulatory impact analysis: national emissions standards for hazardous air 

pollutants for industrial, commercial, and institutional boilers and process heaters, 

Research Triangle Park, NC. Available at: 

http://www.epa.gov/ttn/ecas/regdata/RIAs/boilersriafinal110221_psg.pdf.

US EPA, 2010d. Technical Support Document: Summary of Expert Opinions on the Existence 

of a Threshold in the Concentration-Response Function for PM2.5-related Mortality, 

Research Triangle Park, NC. Available at: 

http://www.epa.gov/ttn/ecas/regdata/Benefits/thresholdstsd.pdf.

US EPA-SAB, 2004. Advisory Council on Clean Air Compliance Analysis Response to Agency 

Request on Cessation Lag, EPA-COUNCIL-LTR-05-001. Available at: 

http://yosemite.epa.gov/sab/sabproduct.nsf/0/39F44B098DB49F3C8525717000529

3E0/$File/council_ltr_05_001.pdf.

US EPA-SAB, 2000. An SAB Report on EPA’s White Paper Valuing the Benefits of Fatal Cancer 

Risk Reduction., EPA-SAB-EEAC-00-013. Available at: 

http://yosemite.epa.gov/sab\SABPRODUCT.NSF/41334524148BCCD6852571A7005

16498/$File/eeacf013.pdf.