EO12866MACT_NSPSUtilitiesMATS2060_AP52RIA20111104ES.doc

Executive Summary

This Regulatory Impact Analysis (RIA) presents the health and welfare
benefits, costs, and other impacts of the final Mercury and Air Toxics
Standards (MATS) in 2016.

ES.1	Key Findings

This rule will reduce emissions of Hazardous Air Pollutants (HAP)
including mercury from the electric power industry. As a co-benefit, the
emissions of certain PM2.5 precursors such as SO2 will also decline. EPA
estimates that this final rule will yield annual monetized benefits (in
2007$) of between $37 to $91 billion using a 3% discount rate and $33 to
$82 billion using a 7% discount rate. The great majority of the
estimates are attributable to co-benefits from 4,300 to 11,000 fewer
PM2.5-related premature mortalities.  The monetized benefits from
reductions in mercury emissions are expected to be $0.004 to $0.006
billion in 2016 using a 3% discount rate and $0.0005 to $0.001 billion
using a 7% discount rate.  The annual social costs, approximated by the
compliance costs, are $9.2 billion (2007$) and the annual monetized net
benefits are $28 to $81 billion using 3% discount rate or $24 to $72
billion using a 7% discount rate. The benefits outweigh costs by between
4 to 1 or 10 to 1 depending on the benefit estimate and discount rate
used. There are some costs and important benefits that EPA could not
monetize, such as those for the HAP being reduced by this final rule
other than mercury. Upon considering these limitations and
uncertainties, it remains clear that the benefits of the MATS are
substantial and far outweigh the costs. Employment impacts associated
with the final rule are estimated to be small.

The benefits and costs in 2016 of the final rule are in Table ES-1.  The
emission reductions from the electricity sector that are expected to
result from the rule are reported in Table ES-2.  

Table ES-1.	Summary of EPA’s Estimates of Annualizeda Benefits, Costs,
and Net Benefits of the Final MATS in 2016b (billions of 2007$)

Description	Estimate

(3% Discount Rate)	Estimate

(7% Discount Rate)

Costsc	$9.2	$9.2

Benefitsd,e,f	$37 to $91 + B	$33 to $82 + B

Net benefits (benefits-costs)g	$28 to $81 + B	$24 to $72 + B

a 	All estimates presented in this report represent annualized estimates
of the benefits and costs of the final MATS in 2016 rather than the net
present value of a stream of benefits and costs in these particular
years of analysis.

b	Estimates rounded to two significant figures and represent annualized
benefits and costs anticipated for the year 2016.

c Total social costs are approximated by the compliance costs ($9.2
billion) do not include monitoring and reporting costs.

d	Total benefits are composed primarily of monetized PM-related health
benefits. The reduction in premature fatalities each year accounts for
over 90% of total monetized benefits. Benefits in this table are
nationwide and are associated with directly emitted PM2.5 and SO2
reductions. The estimate of social benefits also includes CO2-related
benefits calculated using the social cost of carbon, discussed further
in chapter 5. 

e	Not all possible benefits or disbenefits are quantified and monetized
in this analysis. B is the sum of all unquantified benefits and
disbenefits. Data limitations prevented us from quantifying these
endpoints, and as such, these benefits are inherently more uncertain
than those benefits that we were able to quantify. Estimates here are
subject to uncertainties discussed further in the body of the document.
Potential benefit categories that have not been quantified and monetized
are listed in Table ES-4.

f	Mortality risk valuation assumes discounting over the SAB-recommended
20-year segmented lag structure. Results reflect the use of 3% and 7%
discount rates consistent with EPA and OMB guidelines for preparing
economic analyses (EPA, 2000; OMB, 2003).

g	Net benefits are rounded to two significant figures. Columnar totals
may not sum due to rounding

Table ES-2: 	Projected Electricity Generating Unit (EGU) Emissions of
SO2, NOX, Mercury, Hydrogen Chloride, PM, and CO2 with the Base Case and
with MATS, 2015 a,b

 	 	SO2

(million tons)	NOX

(million tons)	Mercury

(tons)	HCl

(thousand tons)	PM2.5

(thousand tons)	CO2

(million metric tonnes)

Base	All EGUs	3.4	1.9	28.7	48.7	277	2,230

	Coal > 25 MW	3.3	1.7	26.6	45.3	270	1,906

MATS	All EGUs	2.1	1.9	10.6	9.0	224	2,215

	Coal > 25 MW	1.9	1.7	8.4	5.5	215	1,881

a	Source: Integrated Planning Model run by EPA, 2011

b	The year 2016 is the compliance year for MATS, though as we explain in
later chapters, we use 2015 as a proxy for compliance in 2016 for IPM
emissions and costs due to availability of modeling impacts in that
year. 

ES.1.1	Health Benefits

The final MATS Rule is expected to yield significant health benefits by
reducing emissions not only of HAP such as mercury, but also significant
co-benefits by reducing to direct fine particles (PM2.5) and sulfur
dioxide, which contributes to the formation of PM2.5. 

Our analyses suggest this rule would yield benefits in 2016 of $37 to
$91 billion (based on a 3% discount rate) and $33 to $82 billion (based
on a 7% discount rate). This estimate reflects the economic value of a
range of avoided health outcomes including 510 fewer mercury-related IQ
points lost as well as avoided PM2.5-related impacts, including 4,300 to
11,000 premature deaths, 4,800 nonfatal heart attacks, 2,600
hospitalizations for respiratory and cardiovascular diseases, 550,000
lost work days and 3.2 million days when adults restrict normal
activities because of respiratory symptoms exacerbated by PM2.5. 

We also estimate substantial additional health improvements for children
from reductions in upper and lower respiratory illnesses, acute
bronchitis, and asthma attacks. See Table ES-2 for a list of the annual
reduction in health effects expected in 2016 and Table ES -3 for the
estimated value of those reductions.

We also include in our monetized benefits estimates the effect from the
reduction in CO2 emissions resulting from this rule. We calculate the
benefits associated with these emission reductions using the interagency
estimates of the social cost of carbon (SCC).

ES.1.2	Welfare Benefits

The term welfare benefits covers both environmental and societal
benefits of reducing pollution, such as reductions in damage to
ecosystems, improved visibility and improvements in recreational and
commercial fishing, agricultural yields, and forest productivity. EPA
did not quantify any of the important welfare benefits expected from the
final MATS, but these are discussed in detail in Chapter 5.

Table ES-2.	Estimated Reduction in Incidence of Adverse Health Effects
of the Mercury and Air Toxics Standards (95% confidence intervals)a,b

Impact	Eastern U.S.c	Western U.S.	Total

Mercury-Related Endpoints



	IQ Points Lost

	510.8

PM-Related Endpoints



	Premature death



	Pope et al. (2002)  XE "Pope et al. (2002)"   (age > 30)	4,100

(1,100 – 7,100)	130

(30 – 220)	4,300

(1,200 – 7,300)

Laden et al. (2006)  XE "Laden et al. (2006)"   (age > 25)	11,000

(4,900 – 16,000)	330

(140 – 510)	11,000

(5,000 – 17,000)

Infant (< 1 year)	19

(-22 – 60)	1

(-1 – 2)	20

(-22 – 62)

Chronic bronchitis	2,800

(90 – 5,400)	110

(-2 – 210)	2,900

(88 – 5,600)

Non-fatal heart attacks (age > 18)	4,700

(1,200 – 8,200)	120

(25 – 210)	4,800

(1,200 – 8,400)

Hospital admissions—respiratory (all ages)	820

(330 – 1,300)	17

(6 – 27)	840

(330 – 1,300)

Hospital admissions—cardiovascular (age > 18)	1,800

(1,200 – 2,200)	42

(28 – 51)	1,800

(1,300 – 2,200)

Emergency room visits for asthma (age < 18)	3,100

(1,600 – 4,500)	110

(52 – 160)	3,200

(1,600 – 4,700)

Acute bronchitis (age 8–12)	6,100

(-1,400 – 13,000)	250

(-71 – 570)	6,300

(-1,400 – 14,000)

Lower respiratory symptoms (age 7–14)	78,000

(30,000 – 130,000)	3,200

(1,100 – 5,200)	81,000

(31,000 – 130,000)

Upper respiratory symptoms (asthmatics age 9–18)	59,000

(11,000 – 110,000)	2,400

(360 – 4,500)	61,000

(11,000 – 110,000)

Asthma exacerbation (asthmatics 6–18)	130,000

(4,600 – 440,000)	5,300

(-10 – 18,000)	130,000

(4,500 – 450,000)

Lost work days (age 18–65)	530,000

(450,000 – 610,000)	21,000

(18,000 – 25,000)	550,000

(460,000 – 630,000)

Minor restricted-activity days (age 18–65)	3,100,000

(2,500,000 – 3,700,000)	120,000

(100,000 – 150,000)	3,200,000

(2,600,000 – 3,800,000)

a	Estimates rounded to two significant figures; column values will not
sum to total value.

b	The negative estimates for certain endpoints are the result of the
weak statistical power of the study used to calculate these health
impacts and do not suggest that increases in air pollution exposure
result in decreased health impacts.

c	Includes Texas and those states to the north and east.

Table ES-3.	Estimated Economic Value of Health and Welfare Benefits of
the Mercury and Air Toxics Standards (95% confidence intervals, billions
of 2007$)a

Impact	Pollutant	Eastern U.S.b	Western U.S.	Total

Avoided IQ loss associated with methylmercury exposure from self-caught
fish consumption among recreational anglers

3% discount rate	$0.004 – $0.006	Hg	$0.004  – $0.006

7% discount rate	$0.000005 – $0.000009	Hg	$0.000005  – $0.000009

Adult premature death (Pope et al., 2002  XE "Pope et al. 2002"   PM
mortality estimate)

3% discount rate	PM2.5	$33

($2.6 – $100)	$1.0

(<$0.01 – $3.2)	$34

($2.7 – $100)

7% discount rate	PM2.5	$30

($2.4 – $91)	$0.9

(<$0.01 – $2.8)	$31

($2.4 – $93)

Adult premature death (Laden et al., 2006  XE "Laden et al. 2006"   PM
mortality estimate)

	3% discount rate	PM2.5	$85

($7.5 – $250)	$2.6

($0.1 – $7.7)	$88

($7.6 – $250)

7% discount rate	PM2.5	$77

($6.7 – $220)	$2.4

($0.1 – $7.0)	$79

($6.8 – $230)

Infant premature death	PM2.5	$0.2

($-0.2 – $0.8)	<$0.01	$0.2

($-0.2 – $0.8)

Chronic Bronchitis	PM2.5	$1.3

($0.1 – $6.2)	$0.1

(<$0.01 – $0.2)	$1.4

($0.1 – $6.4)

Non-fatal heart attacks 

3% discount rate	PM2.5	$0.5

($0.1 – $1.3)	<$0.01	$0.5

($0.1 – $1.3)

7% discount rate	PM2.5	$0.4

($0.1 – $1.0)	<$0.01	$0.4

($0.1 – $1.0)

Hospital admissions—respiratory 	PM2.5	$0.01

(<$0.01 – $0.02)	<$0.01	$0.01

($0.01 – $0.02)

Hospital admissions—cardiovascular	PM2.5	$0.03

(<$0.01 – $0.05)	<$0.01	$0.03

(<$0.01 – $0.05)

Emergency room visits for asthma 	PM2.5	<$0.01	<$0.01	<$0.01

Acute bronchitis 	PM2.5	<$0.01	<$0.01	<$0.01

Lower respiratory symptoms 	PM2.5	<$0.01	<$0.01	<$0.01

Upper respiratory symptoms 	PM2.5	<$0.01	<$0.01	<$0.01

Asthma exacerbation 	PM2.5	<$0.01	<$0.01	<$0.01

Lost work days 	PM2.5	$0.1

($0.1 – $0.1)	<$0.01	$0.1

($0.1 – $0.1)

(continued)

Table ES-3.	Estimated Economic Value of Health and Welfare Benefits of
the Mercury and Air Toxics Standards (95% confidence intervals, billions
of 2007$)a (continued)

Impact	Pollutant	Eastern U.S.b	Western U.S.	Total

Minor restricted-activity days 	PM2.5	$0.2

($0.1 – $0.3)	<$0.01	$0.2

($0.1 – $0.3)

CO2-related benefits 

(3% discount rate)	CO2	$0.35

Monetized total Benefits (Pope et al., 2002  XE "Pope et al. 2002"  
PM2.5 mortality estimate)

	3% discount rate

$36+B

($2.8 – $110)	$1.1+B

(<$0.01 – $3.5)	$37+B

($3.2 – $110)

7% discount rate

$32+B

($2.5 – $99)	$1.0+B

(<$0.01 – $3.1)	$33+B

($2.9 – $100)

Monetized total Benefits (Laden et al., 2006  XE "Pope et al. 2002"  
PM2.5 mortality estimate)



3% discount rate

$88+B

($7.6 – $260)	$2.7+B

($0.1 – $8.1)	$91+B

($8.1 – $260)

7% discount rate

$79+B

($6.9 – $230)	$2.4+B

($0.1 – $7.3)	$82+B

($7.3 – $240)

a Economic value adjusted to 2007$ using GDP deflator. Estimates rounded
to two significant figures. The negative estimates for certain endpoints
are the result of the weak statistical power of the study used to
calculate these health impacts and do not suggest that increases in air
pollution exposure result in decreased health impacts. Confidence
intervals reflect random sampling error and not the additional
uncertainty associated with accounting for differences in air quality
baseline forecasts described in chapter 5. The net present value of
reduced CO2 emissions are calculated differently than other benefits.
The same discount rate used to discount the value of damages from future
emissions (SCC at 5, 3, 2.5 percent) is used to calculate net present
value of SCC for internal consistency. This table shows monetized CO2
co-benefits at discount rates at 3 and 7 percent that were calculated
using the global average SCC estimate at a 3% discount rate because the
interagency workgroup on this topic deemed this marginal value to be the
central value. In section 5.6 we also report CO2 co-benefits using
discount rates of 5 percent (average), 2.5 percent (average), and 3
percent (95th percentile).

b	Includes Texas and those states to the north and east.

Figure ES-1 summarizes an array of PM2.5-related monetized benefits
estimates based on alternative epidemiology and expert-derived
PM-mortality estimate.

Figure ES-2 summarizes the estimated net benefits for the final rule by
displaying all possible combinations of health and climate co-benefits
and costs. Each of the 14 bars in each graph represents a separate point
estimate of net benefits under a certain combination of cost and benefit
estimation methods. Because it is not a distribution, it is not possible
to infer the likelihood of any single net benefit estimate.

Figure ES-1. Economic Value of Estimated PM2.5-Related Health Benefits
According to Epidemiology or Expert-Derived PM Mortality Risk
Estimatea,b

a	Based on the modeled interim baseline, which is approximately
equivalent to the final baseline (see Appendix 5A)

b	Column total equals sum of PM2.5-related mortality and morbidity
benefits.

 

Figure ES-2. Net Benefits of the MATS Rule According to PM2.5
Epidemiology or Expert-Derived Mortality Risk Estimatea,b

a	Based on the modeled interim baseline, which is approximately
equivalent to the final baseline (see Appendix 5A)

b	Column total equals sum of PM2.5-related mortality and morbidity
benefits.

ES.2	Not All Benefits Quantified

EPA was unable to quantify or monetize all of the health and
environmental benefits associated with the final MATS Rule. EPA believes
these unquantified benefits are substantial, including the overall value
associated with HAP reductions, value of increased agricultural crop and
commercial forest yields, visibility improvements, and reductions in
nitrogen and acid deposition and the resulting changes in ecosystem
functions. Tables ES-4 and ES-5 provide a list of these benefits.

Table ES-4.	Human Health Effects of Pollutants Affected by the Mercury
and Air Toxics Standards

Benefits Category	Specific Effect	Effect Has Been Quantified	Effect Has
Been Monetized	More Informationa

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 5.4

	Infant mortality (age <1)			Section 5.4

Reduced incidence of morbidity from exposure to PM2.5	Non-fatal heart
attacks (age > 18)			Section 5.4

	Hospital admissions—respiratory (all ages)			Section 5.4

	Hospital admissions—cardiovascular (age >18)			Section 5.4

	Emergency room visits for asthma (<18)			Section 5.4

	Acute bronchitis (age 8–12)			Section 5.4

	Lower respiratory symptoms (age 7–14)			Section 5.4

	Upper respiratory symptoms (asthmatics age 9-11)			Section 5.4

	Asthma exacerbation (asthmatics age 6–18)			Section 5.4

	Lost work days (age 18-65)			Section 5.4

	Minor restricted-activity days (age 18–65)			Section 5.4

	Chronic Bronchitis (age >26)			Section 5.4

	Other cardiovascular effects (e.g., other ages)	—	—	PM ISAc

	Other respiratory effects (e.g., pulmonary function, non-asthma ER
visits, non-bronchitis chronic diseases, other ages and populations)	—
—	PM ISAc

	Reproductive and developmental effects (e.g., low birth weight,
pre-term births, etc)	—	—	PM ISAc, d

	Cancer, mutagenicity, and genotoxicity effects	—	—	PM ISAc, d

Reduced incidence of mortality from exposure to ozone	Premature
mortality based on short-term study estimates (all ages)	—	—	Ozone
CD, Draft Ozone ISAb

	Premature mortality based on long-term study estimates (age 30–99)
—	—	Ozone CD, Draft Ozone ISAb

Reduced incidence of morbidity from exposure to ozone	Hospital
admissions—respiratory causes (age > 65)	—	—	Ozone CD, Draft Ozone
ISAb

	Hospital admissions—respiratory causes (age <2)	—	—	Ozone CD,
Draft Ozone ISAb

	Emergency room visits for asthma (all ages)	—	—	Ozone CD, Draft
Ozone ISAb

	Minor restricted-activity days (age 18–65)	—	—	Ozone CD, Draft
Ozone ISAb

(continued)

Table ES-4.	Human Health Effects of Pollutants Affected by the Mercury
and Air Toxics Standards (continued)

Benefits Category	Specific Effect	Effect Has Been Quantified	Effect Has
Been Monetized	More Information

	School absence days (age 5–17)	—	—	Ozone CD, Draft Ozone ISAb

	Decreased outdoor worker productivity (age 18-65)	—	—	Ozone CD,
Draft Ozone ISAb

	Other respiratory effects (e.g., premature aging of lungs)	—	—
Ozone CD, Draft Ozone ISAc

	Cardiovascular and nervous system effects	—	—	Ozone CD, Draft Ozone
ISAd

	Reproductive and developmental effects	—	—	Ozone CD, Draft Ozone
ISAd

Reduced incidence of morbidity from exposure to NO2	Asthma hospital
admissions (all ages)	—	—	NO2 ISAb

	Chronic lung disease hospital admissions (age > 65)	—	—	NO2 ISAb

	Respiratory emergency department visits (all ages)	—	—	NO2 ISAb

	Asthma exacerbation (asthmatics age 4–18)	—	—	NO2 ISAb

	Acute respiratory symptoms (age 7–14)	—	—	NO2 ISAb

	Premature mortality	—	—	NO2 ISAc,d

	Other respiratory effects (e.g., airway hyperresponsiveness and
inflammation, lung function, other ages and populations)	—	—	NO2
ISAc,d

Reduced incidence of morbidity from exposure to SO2	Respiratory hospital
admissions (age > 65)	—	—	SO2 ISAb

	Asthma emergency room visits (all ages)	—	—	SO2 ISAb

	Asthma exacerbation (asthmatics age 4–12)	—	—	SO2 ISAb

	Acute respiratory symptoms (age 7–14)	—	—	SO2 ISAb

	Premature mortality	—	—	SO2 ISAc,d

	Other respiratory effects (e.g., airway hyperresponsiveness and
inflammation, lung function, other ages and populations)	—	—	SO2
ISAc,d

Reduced incidence of morbidity from exposure to methyl mercury (through
reduced mercury deposition as well as the role of sulfate in methylation
)	Neurologic effects—IQ loss			IRIS; NRC, 2000b

	Other neurologic effects (e.g., developmental delays, memory, behavior)
—	—	IRIS; NRC, 2000c

	Cardiovascular effects	—	—	IRIS; NRC, 2000c,d

	Genotoxic, immunologic, and other toxic effects	—	—	IRIS; NRC,
2000c,d

a	For a complete list of references see Chapter 5.

b	We assess these benefits qualitative due to time and resource
limitations for this analysis.

c	We assess these benefits qualitatively because we do not have
sufficient confidence in available data or methods.

d	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.

Table ES-5.	Environmental Effects of Pollutants Affected by the Mercury
and Air Toxics Standards

Benefits Category	Specific Effect	Effect Has Been Quantified	Effect Has
Been Monetized	More Informationa

Improved Environment

Reduced visibility impairment	Visibility in Class I areas in SE, SW, and
CA regions	—	—	PM ISAb

	Visibility in Class I areas in other regions	—	—	PM ISAb

	Visibility in residential areas	—	—	PM ISAb

Reduced climate effects	Global climate impacts from CO2 	—		Section
5.6

	Climate impacts from ozone and PM	—	—	Section 5.6

	Other climate impacts (e.g., other GHGs, other impacts) 	—	—	IPCCc

Reduced effects on materials	Household soiling	—	—	PM ISAc

	Materials damage (e.g., corrosion, increased wear)	—	—	PM ISAc

Reduced effects from PM deposition (metals and organics)	Effects on
Individual organisms and ecosystems	—	—	PM ISAc

Reduced vegetation and ecosystem effects from exposure to ozone	Visible
foliar injury on vegetation	—	—	Ozone CD, Draft Ozone ISAc

	Reduced vegetation growth and reproduction	—	—	Ozone CD, Draft
Ozone ISAb

	Yield and quality of commercial forest products and crops	—	—	Ozone
CD, Draft Ozone ISAb,d

	Damage to urban ornamental plants	—	—	Ozone CD, Draft Ozone ISAc

	Carbon sequestration in terrestrial ecosystems	—	—	Ozone CD, Draft
Ozone ISAc

	Recreational demand associated with forest aesthetics	—	—	Ozone CD,
Draft Ozone ISAc

	Other non-use effects	 	 	Ozone CD, Draft Ozone ISAc

	Ecosystem functions (e.g., water cycling, biogeochemical cycles, net
primary productivity, leaf-gas exchange, community composition)	—	—
Ozone CD, Draft Ozone ISAc

(continued)

Table ES-5.	Environmental Effects of Pollutants Affected by the Mercury
and Air Toxics Standards (continued)

Benefits Category	Specific Effect	Effect Has Been Quantified	Effect Has
Been Monetized	More Information

Reduced effects from acid deposition	Recreational fishing	—	—	NOx
SOx ISAb

	Tree mortality and decline	—	—	NOx SOx ISAc

	Commercial fishing and forestry effects	—	—	NOx SOx ISAc

	Recreational demand in terrestrial and aquatic ecosystems	—	—	NOx
SOx ISAc

	Other nonuse effects	 	 	NOx SOx ISAc

	Ecosystem functions (e.g., biogeochemical cycles)	—	—	NOx SOx ISAc

Reduced effects from nutrient enrichment	Species composition and
biodiversity in terrestrial and estuarine ecosystems	—	—	NOx SOx
ISAc

	Coastal eutrophication	—	—	NOx SOx ISAc

	Recreational demand in terrestrial and estuarine ecosystems	—	—	NOx
SOx ISAc

	Other non-use effects	 	 	NOx SOx ISAc

	Ecosystem functions (e.g., biogeochemical cycles, fire regulation)	—
—	NOx SOx ISAc

Reduced vegetation effects from ambient exposure to SO2 and NOx	Injury
to vegetation from SO2 exposure	—	—	NOx SOx ISAc

	Injury to vegetation from NOx exposure	—	—	NOx SOx ISAc

Reduced incidence of morbidity from exposure to methyl mercury (through
reduced mercury deposition as well as the role of sulfate in methylation
)	Effects on fish, birds, and mammals (e.g., reproductive effects)	—
—	Mercury Study RTCc,d

	Commercial, subsistence and recreational fishing	—	—	Mercury Study
RTCc

a	For a complete list of references see Chapter 5. 	

b	We assess these benefits qualitative due to time and resource
limitations for this analysis.

c	 We assess these benefits qualitatively because we do not have
sufficient confidence in available data or methods.

d 	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.

ES.3	Costs and Employment Impacts

The projected annual incremental private costs of the final MATS Rule to
the electric power industry are $9.2 billion in 2015. These costs
represent the total cost to the electricity-generating industry of
reducing HAP emissions to meet the emissions limits set out in the rule.
Estimates are in 2007 dollars. These costs of the rule are estimated
using the Integrated Planning Model (IPM).

There are several national changes in energy prices that result from the
final MATS Rule.  Retail electricity prices are projected to increase in
the contiguous US by an average of 3.0% in 2015 with the final MATS
Rule.  On a weighted average basis between 2015 and 2030, consumer
natural gas price anticipated to increase from 0.4% to 0.7% depending on
consumer class in response to the final MATS Rule.

There are several other types of energy impacts associated with the
final MATS Rule.  A small amount of coal-fired capacity, about 5.5 GW
(less than 2 percent of all coal-fired capacity and 0.5% of total
generation capacity in 2015), is projected to become uneconomic to
maintain by 2015.  These units are predominantly smaller and less
frequently-used generating units dispersed throughout the contiguous US.
 If current forecasts of either natural gas prices or electricity demand
were revised in the future to be higher, that would create a greater
incentive to keep these units operational.  Coal production for use in
the power sector is projected to decrease by less than 1 percent by
2015, and we expect slightly reduced coal demand in Appalachia and the
West with the final MATS Rule.

In addition to addressing the costs and benefits of the final MATS Rule,
EPA has estimated a portion of the employment impacts of this
rulemaking. We have estimated two types of impacts. One provides an
estimate of the employment impacts on the regulated industry over time.
The second covers the short-term employment impacts associated with the
construction of needed pollution control equipment until the compliance
date of the regulation. We expect that the rule’s impact on employment
will be small, but will (on net) result in an expected increase in
employment.

The approaches to estimate employment impacts use different analytical
techniques and are applied to different industries during different time
periods, and they use different units of analysis.  No overlapping
estimates are summed.  Estimates of employment changes per dollar of
expenditure on pollution control from Morgenstern et al. (2002) are used
to estimate the ongoing annual employment impacts for the regulated
entities (the electric power sector) as a result of this rule.  The
short term estimates for employment needed to design, construct, and
install the control equipment in the three year period before the
compliance date are also provided using an approach that estimates
employment impacts for the environmental protection sector based on
forecast changes from IPM on the number and scale of pollution controls
and labor intensities in relevant sectors.  Finally some of the other
types of employment impacts that will be ongoing are estimated using IPM
outputs and labor intensities, as reported in chapter 6, but not
included in this table because they omit some potentially important
categories.

In Table ES-6, we show the employment impacts of the MATS Rule as
estimated by the environmental protection sector approach and by the
Morgenstern approach.

Table ES-6.	Estimated Employment Impact Table

	Annual (Reoccurring)	One
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−14,000 to +30,000d	Not Applicable

a	These one-time impacts on employment are estimated in terms of
job-years.

b	This estimate is not statistically different from zero.

c	These annual or reoccurring employment impacts are estimated in terms
of production workers as defined by the US Census Bureau’s Annual
Survey of Manufacturers (ASM).

d	95% confidence interval

ES.4	Small Entity and Unfunded Mandates Impacts

After preparing an analysis of small entity impacts, EPA cannot certify
that this proposal will not have a no SISNOSE (significant economic
impacts on a substantial number of small entities).  Of the 83 small
entities affected, 49 are projected to have costs greater than 1 percent
of their revenues.  EPA’s decision to exclude units smaller than 25
Megawatt capacity (MW) as per the requirements of the Clean Air Act has
already significantly reduced the burden on small entities, and EPA
participated in a Small Business Regulatory Enforcement Fairness Act
(SBREFA) to examine ways to mitigate the impact of the proposed Toxics
Rule on affected small entities

EPA examined the potential economic impacts on state and
municipality-owned entities associated with this rulemaking based on
assumptions of how the affected states will implement control measures
to meet their emissions.  These impacts have been calculated to provide
additional understanding of the nature of potential impacts and
additional information.

According to EPA’s analysis, of the 96 government entities considered
in this, EPA projects that 51 government entities will have compliance
costs greater than 1 percent of base generation revenue in 2015, based
on our assumptions of how the affected states implement control measures
to meet their emissions budgets as set forth in this rulemaking.

Government entities projected to experience compliance costs in excess
of 1 percent of revenues may have some potential for significant impact
resulting from implementation of the Toxics Rule.

ES.5	Limitations and Uncertainties

Every analysis examining the potential benefits and costs of a change in
environmental protection requirements is limited to some extent by data
gaps, limitations in model capabilities (such as geographic coverage),
and variability or uncertainties in the underlying scientific and
economic studies used to configure the benefit and cost models. Despite
the uncertainties, we believe this benefit-cost analysis provides a
reasonable indication of the expected economic benefits and costs of the
final MATS Rule.

For this analysis, such uncertainties include possible errors in
measurement and projection for variables such as population growth and
baseline incidence rates; uncertainties associated with estimates of
future-year emissions inventories and air quality; variability in the
estimated relationships between changes in pollutant concentrations and
the resulting changes in health and welfare effects; and uncertainties
in exposure estimation.

Below is a summary of the key uncertainties of the analysis:

Costs

Compliance costs are used to approximate the social costs of this rule.
Social costs may be higher or lower than compliance costs and differ
because of preexisting distortions in the economy, and because certain
compliance costs may represent shifts in rents.

Analysis does not capture employment shifts as workers are retrained at
the same company or re-employed elsewhere in the economy.

We do not include the costs of certain relatively small permitting costs
associated with updating Title V permits or increases in monitoring
costs for affected units.

Technological innovation is not incorporated into these cost estimates. 
Thus, these cost estimates may be potentially higher than what may occur
in the future, all other things being the same.

Benefits

The mercury concentration estimates for the analysis come from several
different sources

The mercury concentration estimates used in the model were based on
simple temporal and spatial averages of reported fish tissue samples.
This approach assumes that the mercury samples are representative of
“local” conditions (i.e., within the same HUC 12) in similar
waterbodies (i.e., rivers or lakes).

State-level averages for fishing behavior of recreational anglers are
applied to each modeled census tract in the state; which does not
reflect within-state variation in these factors.

Application of state-level fertility rates to specific census tracts
(and specifically to women in angler households.

Applying the state-level individual level fishing participation rates to
approximate the household fishing rates conditions at a block level.

Populations are only included in the model if they are within a
reasonable distance of a waterbody with fish tissue MeHg samples. This
approach undercounts the exposed population (by roughly 40 to 45%) and
leads to underestimates of national aggregate baseline exposures and
risks and underestimates of the risk reductions and benefits resulting
from mercury emission reductions.

Assumption of 8 g/day fish consumption rate for the general population
in freshwater angler households.

The dose-response model used to estimate neurological effects on
children because of maternal mercury body burden has several important
uncertainties, including selection of IQ as a primary endpoint when
there may be other more sensitive endpoints, selection of the
blood-to-hair ratio for mercury, and the dose-response estimates from
the epidemiological literature. Control for confounding from the
potentially positive cognitive effects of fish consumption and, more
specifically, omega-3 fatty acids.

Valuation of IQ losses using a lost earning approach has several
uncertainties, including (1) there is a linear relationship between IQ
changes and net earnings losses, (2) the unit value applies to even very
small changes in IQ, and (3) the unit value will remain constant (in
real present value terms) for several years into the future. Each unit
value for IQ losses has two main sources of uncertainty (1). The
statistical error in the average percentage change in earnings as a
result of IQ changes and (2) estimates of average lifetime earnings and
costs of schooling. Most of the estimated PM-related benefits in this
rule accrue to populations exposed to higher levels of PM2.5. Of these
estimated PM-related mortalities avoided, about 30% occur among
populations initially exposed to annual mean PM2.5 level of 10 µg/m3
and about 80% occur among those initially exposed to annual mean PM2.5
level of 7.5 µg/m3 ; these are the lowest air quality levels considered
in the Laden et al. (2006) and Pope et al. (2002) studies, respectively.
This fact is important, because as we estimate PM-related mortality
among populations exposed to levels of PM2.5 that are successively
lower, our confidence in the results diminishes. However, our analysis
shows that a substantial portion of the impacts occur at higher
exposures.

There are uncertainties related to the health impact functions used in
the analysis. These include: within study variability; across study
variation; the application of concentration-response (C-R) functions
nationwide; extrapolation of impact functions across population; and
various uncertainties in the C-R function, including causality and
thresholds. Therefore, benefits may be under- or over-estimates.

Analysis is for 2016, and projecting key variables introduces
uncertainty. Inherent in any analysis of future regulatory programs are
uncertainties in projecting atmospheric conditions and source level
emissions, as well as population, health baselines, incomes, technology,
and other factors.

This analysis omits certain unquantified effects due to lack of data,
time and resources. These unquantified endpoints include other health
and ecosystem effects. EPA will continue to evaluate new methods and
models and select those most appropriate for estimating the benefits of
reductions in air pollution. Enhanced collaboration between air quality
modelers, epidemiologists, toxicologists, ecologists, and economists
should result in a more tightly integrated analytical framework for
measuring benefits of air pollution policies.

PM2.5 mortality benefits represent a substantial proportion of total
monetized benefits (over 90%), and these estimates have following key
assumptions and uncertainties.

The PM2.5 -related benefits of the alternative scenarios were derived
through a benefit per-ton approach, which does not fully reflect local
variability in population density, meteorology, exposure, baseline
health incidence rates, or other local factors that might lead to an
over-estimate or under-estimate of the actual benefits of this rule.

We assume that all fine particles, regardless of their chemical
composition, are equally potent in causing premature mortality. This is
an important assumption, because PM2.5 produced via transported
precursors emitted from EGUs may differ significantly from direct PM2.5
released from diesel engines and other industrial sources, but no clear
scientific grounds exist for supporting differential effects estimates
by particle type.

We assume that the health impact function for fine particles is linear
within the range of ambient concentrations under consideration. Thus,
the estimates include health benefits from reducing fine particles in
areas with varied concentrations of PM2.5, including both regions that
are in attainment with fine particle standard and those that do not meet
the standard down to the lowest modeled concentrations.

To characterize the uncertainty in the relationship between PM2.5 and
premature mortality, we include a set of twelve estimates based on
results of the expert elicitation study in addition to our core
estimates. Even these multiple characterizations omit the uncertainty in
air quality estimates, baseline incidence rates, populations exposed and
transferability of the effect estimate to diverse locations. As a
result, the reported confidence intervals and range of estimates give an
incomplete picture about the overall uncertainty in the PM2.5 estimates.
This information should be interpreted within the context of the larger
uncertainty surrounding the entire analysis.

ES.6	References

Laden, F., J. Schwartz, F.E. Speizer, and D.W. Dockery. 2006.
“Reduction in Fine Particulate Air Pollution and Mortality.”
American Journal of Respiratory and Critical Care Medicine 173:667-672.
Estimating the Public Health Benefits of Proposed Air Pollution
Regulations. Washington, DC: The National Academies Press.

Levy JI, Baxter LK, Schwartz J. 2009. Uncertainty and variability in
health-related damages from coal-fired power plants in the United
States. Risk Anal. doi: 10.1111/j.1539-6924.2009.01227.x [Online 9 Apr
2009]

Pope, C.A., III, R.T. Burnett, M.J. Thun, E.E. Calle, D. Krewski, K.
Ito, and G.D. Thurston. 2002. “Lung Cancer, Cardiopulmonary Mortality,
and Long-term Exposure to Fine Particulate Air Pollution.” Journal of
the American Medical Association 287:1132-1141.

U.S. Environmental Protection Agency (EPA). December 2010. Guidelines
for Preparing Economic Analyses. EPA 240-R-10-001.

U.S. Office of Management and Budget (OMB). 2003. Circular A-4 Guidance
to Federal Agencies on Preparation of Regulatory Analysis.

 

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 Docket ID EPA-HQ-OAR-2009-0472-114577, Technical Support Document:
Social Cost of Carbon for Regulatory Impact Analysis Under Executive
Order 12866, Interagency Working Group on Social Cost of Carbon, with
participation by Council of Economic Advisers, Council on Environmental
Quality, Department of Agriculture, Department of Commerce, Department
of Energy, Department of Transportation, Environmental Protection
Agency, National Economic Council, Office of Energy and Climate Change,
Office of Management and Budget, Office of Science and Technology
Policy, and Department of Treasury (February 2010). Also available at  
HYPERLINK "http://www.epa.gov/otaq/climate/regulations.htm" 
http://www.epa.gov/otaq/climate/regulations.htm 

 

 	The year 2016 is the compliance year for MATS, though as we explain in
later chapters, we use 2015 as a proxy for compliance in 2016 for IPM
emissions, costs and economic impact analysis due to availability of
modeling impacts in that year.

***E.O. 12866 Review–Draft–Do Not Cite, Quote, Or Release During
Review ***

ES-  PAGE  1 

