technique that precluded us from generating such estimates.

C A credible interval is a posterior probability interval used in
Bayesian statistics, which is similar to a confidence interval used in
frequentist statistics. Credible intervals not provided due to the fact
that the incidence estimates were derived through an interpolation
technique (see Appendix 6) that precluded us from generating such
estimates.

D All estimates rounded to two significant figures. As such, totals will
not sum across columns

E This table reflects full attainment in all locations of the U.S.
except two areas of California.  These two areas, which have high levels
of ozone, are not planning to meet the current standard until after
2020.  The estimates in the table reflect a progress point in 2020 or
"glidepath target" for the two California areas.

A Confidence intervals not provided due to the fact that the incidence
estimates were derived through an interpolation technique (see Appendix
6) that

Table 6-32: Illustrative Strategy to Attain 0.075 ppm: Estimated Annual
Monetary Value of Reductions in the Incidence of Mortality  Associated
with Exposure to Ozone (Millions of 1999$, Incremental to Current
Standard)

Model or AssumptionA	Reference	Eastern U.S.	Western U.S. Excluding
California	California	2020 National Benefits

Glidepath AttainmentE

	Arithmetic MeanB

(95% Credible Intervals)C

NMMAPS	  Bell et al. 2004	$1,400	$66	0	$1,400

Meta-Analysis	  Bell et al. 2005	$5,400	$270	0	$5,700

	  Levy et al. 2005	$6,700	$430	0	$7,100

	  Ito et al. 2005	$5,900	$290	0	$6,200

Assumption that association

is not causal	0	0	0	0

precluded us from generating such estimates.

B All estimates rounded to two significant figures. As such, totals will
not sum across columns

C This table reflects full attainment in all locations of the U.S.
except two areas of California.  These two areas, which have high levels
of ozone, are not planning to meet the current standard until after
2020.  The estimates in the table reflect a progress point in 2020 or
"glidepath target" for the two California areas.

Table 6-33: Illustrative Strategy to Attain 0.075 ppm in California:
Estimated Annual Valuation of Reductions in the Incidence of Premature
Mortality Associated with Ozone Exposure (Incremental to Current Ozone
Standard)

Model or AssumptionA	Reference	California GlidepathB	California
Incremental Post-2020 BenefitsC	California TotalD

NMMAPS	  Bell et al. 2004	0	$220	$220

Meta-Analysis	  Bell et al. 2005	0	$910	$910

	  Levy et al. 2005	0	$990	$990

	  Ito et al. 2005	0	$990	$990

Assumption that association

is not causal	0	0	0

A Does not represent equal weighting among models or between assumption
of causality vs. no causality (see text on page 63).

B This table reflects full attainment in all locations of the U.S.
except two areas of California.  These two areas, which have high levels
of ozone, are not planning to meet the current standard until after
2020.  The estimates in the table reflect a progress point in 2020 or
"glidepath target" for the two California areas.

C Certain mobile source programs including Tier-2 and Non-Road Diesel
are projected to generate NOx emission reductions in California between
2020 and 2030. The estimates in this column are the benefits of full
attainment with the alternate standard post-2020 with mobile source
emission reductions in the baseline, incremental to 2020 glidepath
attainment.

D This column sums the glidepath and incremental post-2020 benefits. The
estimates in this column do not include confidence intervals because
they were derived through a scaling technique described above.

E All estimates rounded to two significant figures. As such, totals will
not sum across columns

Table 6-34: Illustrative Strategy to Attain 0.075 ppm in California:
Estimated Annual Valuation of Reductions in the Incidence of Premature
Morbidity Associated with Ozone Exposure (Incremental to Current Ozone
Standard, 95% Confidence Intervals in Parentheses)

Morbidity Endpoint	California GlidepathA	California Incremental
Post-2020 BenefitsB	California TotalC

Hospital Admissions

(ages 0-1)	0	$2.4	$2.4

Hospital Admissions

(ages 65-99)	0	$4	$4

Emergency Department Visits, Asthma-RelatedA	0	$0.03	$0.03

School Absences	0	$8.7	$8.7

Worker Productivity	0	$9	$9

Minor Restricted Activity Days	0	$7.3	$7.3

A This table reflects full attainment in all locations of the U.S.
except two areas of California.  These two areas, which have high levels
of ozone, are not planning to meet the current standard until after
2020.  The estimates in the table reflect a progress point in 2020 or
"glidepath target" for the two California areas.

B Certain mobile source programs including Tier-2 and Non-Road Diesel
are projected to generate NOx emission reductions in California between
2020 and 2030. The estimates in this column are the benefits of full
attainment with the alternate standard post-2020 with mobile source
emission reductions in the baseline, incremental to 2020 glidepath
attainment.

C This column sums the glidepath and incremental post-2020 benefits. The
estimates in this column do not include confidence intervals because
they were derived through a scaling technique described below.

D All estimates rounded to two significant figures. As such, totals will
not sum across columns

Estimated reductions in ozone mortality incidence provided in Tables
6-5, 6-7, 6-11, 6-13, 6-17 and 6-19 represent the number of premature
deaths potentially avoided due to reductions in ozone exposure in 2020
using warm season functions from the recent ozone-mortality NMMAPS
analysis of 95 U.S. communities (Bell et al., 2004) and three
meta-analyses of the available published literature on ozone-mortality
effects (Bell et al., 2005; Ito et al., 2005; Levy et al., 2005).  These
same tables also include the possibility that there is not a causal
association between ozone and mortality, i.e., that the estimate for
premature mortality avoided could be zero. As noted above, for each
standard alternative we break out estimates between 2020 national
glidepath and California post-2020. Model uncertainty, including whether
or not the relationship is assumed to be causal, is a key source of
uncertainty.  Although multiple estimates are presented in these tables,
no attempt was made to quantify the likelihood of a causal relationship
between short-term ozone exposure and increased mortality or to weigh
the results of the various models.

The estimate of central tendency for premature mortality is expressed as
the arithmetic mean, with the assumption of a normal distribution, and
represents the central estimate of the number of premature deaths
avoided in association with the proposed standard based on each study.
Statistical uncertainty associated with the model estimate for each
study is characterized by the 95% credible interval around the mean
estimate (i.e., 2.5th and 97.5th percent interval).  Of the four
available studies, the NMMAPS study by Bell et al. (2004) is considered
to be the most representative for evaluating potential mortality-related
benefits associated with the proposed standard due to its extensive
coverage (examination of 95 large communities across the United States
over an extended period of time, from 1987 to 2000) and its specific
focus on the ozone-mortality relationship.  Annual estimates of lives
saved from this study are lower than those from the three meta-analyses,
possibly due to more stringent adjustment for meteorological factors
(Ito et al., 2005; Ostro et al., 2006), publication bias in the
meta-analyses (Bell et al., 2005; Ito et al., 2005) or other factors.
Clearly, the ozone-mortality reduction estimates are conditional on a
causal relationship.

The Ozone Criteria Document (U.S. EPA, 2006) and Staff Paper (U.S. EPA,
2007) concluded that the overall body of evidence is highly suggestive
that (short-term exposure to) ozone directly or indirectly contributes
to non-accidental cardiopulmonary-related mortality.  However, various
sources of uncertainty remain, including the possibility that there is
no causal relationship between ozone and mortality (i.e., zero effect).
For instance, because results of time-series studies implicate all of
the criteria air pollutants, and those who would be expected to be
potentially more susceptible to ozone exposure are likely to have lower
exposure to ozone due to the amount of time that they spend indoors,
CASAC stated that it seems unlikely that the observed associations
between short-term ozone concentrations and daily mortality are due
solely to ozone itself (i.e., ozone may be serving as a marker for other
agents that are contributing to the short-term exposure effects on
mortality).  Even so, CASAC concluded that the evidence was strong
enough to support a quantitative risk assessment of the relationship
between short-term exposure to ozone and premature mortality as part of
the Staff Paper.  EPA has asked the National Academy of Sciences for
their advice on how best to quantify the uncertainty about the
relationship between ambient ozone exposure and premature mortality
within the context of quantifying projected benefits of alternative
control strategies.

Using the NMMAPS study that was used as the basis for the risk analysis
presented in our Staff Paper, we estimate 280 avoided premature deaths
annually in 2020 from reducing ozone levels to meet a proposed standard
of 0.070 ppm, which, when added to the other projected ozone related
benefits, leads to an estimated total benefit of $1.8 billion/yr. Using
three studies that synthesize data across a large number of individual
studies, we estimate between 1,100 and 1,400 avoided premature deaths
annually in 2020, leading to total monetized benefits of between $7.2
and $8.9 billion/yr. Alternatively, if there is no causal relationship
between ozone and mortality, avoided premature deaths would be zero.
For a proposed standard of 0.075 ppm, using the NMMAPS ozone mortality
study, we estimate 200 premature deaths avoided and total monetized
benefits of $1.4 billion/yr.  Using the three synthesis studies, we
estimate premature deaths avoided for the less stringent standard to be
between 880 and 1,100, with total monetized ozone benefits to be between
$5.7 and $7.1 billion/yr.  Because EPA is taking comment on alternatives
as low as 0.065 ppm, we show that a more stringent standard of 0.065
ppm, using the NMMAPS ozone mortality study is estimated to result in
530 premature deaths avoided and total monetized benefits of $3.4
billion/yr.  Using the three synthesis studies, estimated premature
deaths avoided for the more stringent standard are between 2,100 and
2,400, with total monetized ozone benefits between $14 and $15
billion/yr.  Including premature mortality in our estimates had the
largest impact on the overall magnitude of benefits:  Premature
mortality benefits account for more than 95 percent of the total
benefits we can monetize.  We note that these estimates reflect EPA's
interim approach to characterizing the benefits of reducing premature
mortality associated with ozone exposure.   EPA has requested advice
from the NAS on how best to quantify uncertainty in the relationship
between ozone exposure and premature mortality in the context of
quantifying benefits associated with alternative ozone control
strategies.

6.5.3 PM2.5 Co-Benefits Resulting from Attainment of 0.070 ppm
incremental to 0.08 ppm

The summary of PM2.5 related co-benefits in the tables above represent
the benefits of partially attaining 0.070 ppm incremental to a partial
attainment of 0.08 ppm. Thus, these estimates overstate the benefits of
0.070 ppm partial attainment relative to the actual incremental benefits
of this scenario; this is due to the fact that the benefits estimates in
these tables include the benefits of NOx reductions that would be
required to attain a baseline of 0.08 ppm. Of greater analytical value
would be an estimate of the PM2.5 co-benefits associated with fully
attaining 0.070 ppm incremental to full attainment of the 0.08 ppm
standard.

To generate such an estimate, we calculated a new PM2.5 baseline that
established the PM2.5 air quality associated with full attainment of
0.08 ppm. To create such a baseline, EPA utilized benefit PM2.5 per-ton
estimates. These PM2.5 benefit per-ton estimates provide the total
monetized human health benefits (the sum of premature mortality and
premature morbidity) of reducing one ton of PM2.5 from a specified
source. EPA has used a similar technique in previous Regulatory Impact
Analyses. These estimates are based on the sum of the valuation of the
Pope (2002) estimates of mortality (3% discount rate, 1999$) and
valuation of the morbidity incidence. Readers interested in reviewing
the complete methodology for creating the benefit per-ton estimates used
in this analysis can consult the Technical Support Document accompanying
this RIA.

Estimating the PM2.5 benefits that represented the full attainment of
both 0.070 ppm incremental to full attainment of 0.08 ppm entailed the
following four steps:

Estimate the number of tons of NOx necessary to attain a baseline of
0.08 ppm. Chapter 3 described the method used to estimate the
extrapolated NOx emissions reductions necessary to attain a baseline of
0.08 ppm full attainment.

Calculate the benefits of attaining 0.08 ppm. To estimate the benefits
of fully attaining 0.080 ppm incremental to partial attainment of 0.080
ppm, the relevant benefit per ton is simply multiplied by the total
number of extrapolated NOx tons abated.

Calculate the benefits of partially attaining 0.070 ppm incremental to
full attainment of 0.08 ppm. Subtract the benefits of fully attaining
0.080 ppm incremental to the partial attainment of 0.080 ppm to create a
new estimate of incremental 0.070 ppm partial attainment.

Calculate the PM2.5 benefits of fully attaining 0.070 ppm. Multiplying
the estimate of the extrapolated NOx tons necessary to attain 0.070 ppm
fully (found in chapter 3) produces an estimate of the incremental
benefits of fully attaining 0.070 ppm incremental to partial attainment
of 0.070 ppm. By adding this incremental benefit estimate to the
benefits generated in step 3, we derived a total benefit estimate of
attaining 0.070 ppm incremental to 0.08 ppm.

The process for estimating the PM2.5 co-benefits of fully attaining
0.065 ppm and 0.075 ppm is identical to the steps above, with the
following exception; in step four we substituted the number of
extrapolated tons necessary to attain 0.065 ppm and 0.075 ppm,
respectively.  Table 5-21 below provides the inputs to the calculation
steps described above. In the example below we calculate total benefits
using the Pope et al. (2002) mortality estimate. However, in subsequent
tables we present benefits using Laden et al. (2006) as well as the
twelve expert functions described previously in this document. Note that
while our benefit per ton estimates are associated with broad source
categories (in this case, NOx Electrical Generating Units, Other NOx
point sources and Mobile NOx sources) the extrapolated tons were not.
For this reason we simply assumed that the total number of extrapolated
NOx tons were evenly distributed between these three source types.

Table 6-35: Estimated PM2.5 Co-Benefits Associated with Full Attainment
of 0.070 ppm incremental to 0.08 ppma

Calculation	Extrapolated NOx Tons	Benefit per ton estimate	Valuation of
PM2.5 Benefits

(Billions 1999$)

	Benefits of attaining 0.08 ppm partially and 0.070 ppm partially:b	---
---	$3.2B

	Benefits of attaining 0.08 ppm from a baseline of 0.08 ppm partial
attainment:	NOx EGU: 151,000	$3,400	$1.7B

	NOx Point: 151,000	$3,100

NOx Mobile: 151,000	$5,000

Benefits of attaining 0.070 ppm partially, incremental to attainment of
0.08 ppm	---	---	            = $3.2B - $1.7B

                                      =$1.5 B

	Benefits of attaining 0.070 ppm incremental to partial attainment of
0.070 ppm	NOx EGU: 420,000	$3,400	$4.8B

	NOx Point: 420,000	$3,100

NOx Mobile: 420,000	$5,000

Benefits of attaining 0.070 ppm incremetnal to attainment of 0.08 ppm

	           =$1.5B + 4.8B

                                      =$6.3B

	a Numbers have been rounded to two significant figures and therefore
summation may not match table estimates. PM2.5 benefit estimates do not
include confidence intervals because they are derived using benefit
per-ton estimates.

b From table 5-16 above

The procedure for calculating the PM2.5 benefits resulting from full
attainment of 0.075 ppm and 0.065 ppm is identical to this example, with
the exception of step 4; the PM2.5 benefits of attaining 0.065 ppm and
0.075 ppm incremental to partial attainment of 0.070 ppm are $9.7B and
$1.4B respectively. Thus, the total PM2.5 benefits of attaining 0.065
ppm and 0.075 ppm are $11B and $3B, respectively. The full attainment
PM2.5 benefits do not include confidence intervals. Because this full
attainment estimate was derived by summing the modeled PM2.5 benefits
and the benefits derived using the benefit per-ton metrics—and these
benefit per ton metrics do not include confidence intervals—the
resulting sum of total PM2.5 benefits do not include confidence
intervals.

6.5.4 Estimate of Full Attainment Benefits

Tables 6-36 through 6-41 below summarize the estimates of full
attainment and 2020 California glidepath attainment ozone benefits and
PM2.5 co-benefit estimate for each standard alternative. The
presentation of ozone benefits and PM2.5 co-benefits for each standard
alternative is broken into two tables. The first table presents the
national glidepath ozone benefits and PM2.5 co-benefits. The second
table presents California-only glidepath and post-2020 ozone benefits
and PM2.5 co-benefits. Tables 6-42 through 6-51 summarize the combined
ozone and PM2.5 co-benefits. The presentation of combined ozone and
PM2.5 co-benefit tables is broken into four components for each standard
alternative. The first table presents national glidepath benefits. The
second table presents the California-only glidepath benefits. The third
table presents the incremental benefits that accrue in California from
full attainment of the alternative standard after 2020. The last table
presents total California benefits—the sum of glidepath benefits and
post-2020 benefits.Table 6-36: Estimate of Total Annual Ozone and PM2.5
Benefits (95% Confidence Intervals, Millions of $1999) for the 0.065 ppm
Standard Alternative: National Glidepath Attainment

Ozone Mortality and Morbidity Benefits of Attaining 0.065 ppm

Standard Alternative and

Model or AssumptionA	Ozone Benefits, Arithmetic MeanB

NMMAPS 	Bell (2004)	$3,700

Meta-Analysis	Bell (2005)	$14,000

	Ito (2005)	$15,000

	Levy (2005)	$16,000

No Causality	$330

PM2.5 Mortality and Morbidity Benefits of Attaining 0.065 ppm

Mortality Impact Functions Derived from Epidemiology Literature

ACS StudyC	$10,000

Harvard Six-City StudyD	$22,000

Mortality Impact Functions Derived from Expert Elicitation

Expert A	$33,000

Expert B	$25,000

Expert C	$25,000

Expert D	$17,000

Expert E	$41,000

Expert F	$23,000

Expert G	$14,000

Expert H	$18,000

Expert I	$24,000

Expert J	$20,000

Expert K	$3,900

Expert L	$18,000

	 A Does not represent equal weighting among models or between
assumption of causality vs. no causality (see text on page 63).

B A credible interval is a posterior probability interval used in
Bayesian statistics, which is similar to a confidence interval used in
frequentist statistics. Credible intervals for ozone estimates and
confidence intervals for PM2.5 estimates not provided due to the fact
that the valuation estimates were derived through a scaling technique
(see above) that precluded us from generating such estimates.

C The estimate is based on the concentration-response (C-R) function
developed from the study of the American Cancer Society cohort reported
in Pope et al (2002), which has previously been reported as the primary
estimate in recent RIAs

D Based on Laden et al (2006) reporting of the extended Six-cities
study; to be reviewed by the EPA-SAB for advice on the appropriate
method for incorporating what has previously been a sensitivity
estimate.

E All estimates incremental to 2006 PM NAAQS RIA. Estimates derived
using benefit per ton estimates discounted at 3%.Estimates derived using
a 7% discount rate would be approximately 15% lower.

Table 6-37: Estimate of Total Annual Ozone and PM2.5 Benefits (95%
Confidence Intervals, Millions of $1999) for the 0.065 ppm Standard
Alternative: California Attainment

Ozone Mortality and Morbidity Benefits of Attaining 0.065 ppm

Standard Alternative and

Model or AssumptionA	Ozone Benefits, Arithmetic MeanB

	Glidepath	Incremental Post-2020 Benefits	Total

NMMAPS 	Bell (2004)	$61	 $690 	$750

Meta-Analysis	Bell (2005)	$230	 $2,600 	$2,800

	Ito (2005)	$210	 $2,800 	$3,000

	Levy (2005)	$240	 $2,700 	$3,000

No Causality	$6.8	$93	$100

PM2.5 Mortality and Morbidity Benefits of Attaining 0.065 ppm

Mortality Impact Functions Derived from Epidemiology Literature

	Glidepath	Incremental Post-2020 Benefits	Total

ACS StudyC	$190	$1,000	$1,200

Harvard Six-City StudyD	$410	$2,200	$2,600

Mortality Impact Functions Derived from Expert Elicitation

Expert A	$620	$3,300	$3,900

Expert B	$470	$2,500	$3,000

Expert C	$470	$2,500	$3,000

Expert D	$330	$1,700	$2,100

Expert E	$770	$4,100	$4,900

Expert F	$430	$2,300	$2,700

Expert G	$270	$1,500	$1,700

Expert H	$350	$1,800	$2,200

Expert I	$460	$2,500	$2,900

Expert J	$370	$2,000	$2,400

Expert K	$75	$400	$470

Expert L	$340	$1,800	$2,100

	 A Does not represent equal weighting among models or between
assumption of causality vs. no causality (see text on page 63).

B A credible interval is a posterior probability interval used in
Bayesian statistics, which is similar to a confidence interval used in
frequentist statistics. Credible intervals for ozone estimates and
confidence intervals for PM2.5 estimates not provided due to the fact
that the valuation estimates were derived through a scaling technique
(see above) that precluded us from generating such estimates.

C The estimate is based on the concentration-response (C-R) function
developed from the study of the American Cancer Society cohort reported
in Pope et al (2002), which has previously been reported as the primary
estimate in recent RIAs

D Based on Laden et al (2006) reporting of the extended Six-cities
study; to be reviewed by the EPA-SAB for advice on the appropriate
method for incorporating what has previously been a sensitivity
estimate.

E All estimates incremental to 2006 PM NAAQS RIA. Estimates derived
using benefit per ton estimates discounted at 3%.Estimates derived using
a 7% discount rate would be approximately 15% lower.

Table 6-38: Estimate of Total Annual Ozone and PM2.5 Benefits (95%
Confidence Intervals, Millions of $1999) for the 0.070 ppm Standard
Alternative: National Glidepath Attainment

Ozone Mortality and Morbidity Benefits of Attaining 0.070 ppm

Standard Alternative and

Model or AssumptionA	Ozone Benefits, Arithmetic MeanB

(95% Credible Intervals)C

NMMAPS	Bell (2004)	$2,000

($300--$4,400)

Meta-Analysis	Bell (2005)	$7,400

($1,200--$16,000)

	Ito (2005)	$8,000

($1,400--$16,000)

	Levy (2005)	$9,100

($1,600--$18,000)

No Causality	$190

($49--$400)

PM2.5 Mortality and Morbidity Benefits of Attaining 0.070 ppm

Mortality Impact Functions Derived from Epidemiology Literature

ACS StudyD	$5,400

Harvard Six-City StudyE	$12,000

Mortality Impact Functions Derived from Expert Elicitation

Expert A	$17,000

Expert B	$13,000

Expert C	$13,000

Expert D	$9,200

Expert E	$22,000

Expert F	$12,000

Expert G	$7,700

Expert H	$9,800

Expert I	$13,000

Expert J	$11,000

Expert K	$2,100

Expert L	$9,500

 A Does not represent equal weighting among models or between assumption
of causality vs. no causality (see text on page 63).

 B With the exception of the assumption of no causal relationship, the
arithmetic mean and 95% credible interval around the mean estimates of
the annual number  of lives saved are based on an assumption of a normal
distribution. Confidence intervals not available for PM2.5 valuation
estimates due to the fact that they were derived through a scaling
technique (see above) that precluded us from generating such estimates.

C A credible interval is a posterior probability interval used in
Bayesian statistics, which is similar to a confidence interval used in
frequentist statistics.

D The estimate is based on the concentration-response (C-R) function
developed from the study of the American Cancer Society cohort reported
in Pope et al (2002), which has previously been reported as the primary
estimate in recent RIAs

E Based on Laden et al (2006) reporting of the extended Six-cities
study; to be reviewed by the EPA-SAB for advice on the appropriate
method for incorporating what has previously been a sensitivity
estimate.

F All estimates incremental to 2006 PM NAAQS RIA. Estimates derived
using benefit per ton estimates discounted at 3%.Estimates derived using
a 7% discount rate would be approximately 15% lower.

Table 6-39: Estimate of Total Annual Ozone and PM2.5 Benefits (95%
Confidence Intervals, Millions of $1999) for the 0.070 ppm Standard
Alternative: California Attainment

Ozone Mortality and Morbidity Benefits of Attaining 0.070 ppm

Standard Alternative and

Model or AssumptionA	Ozone Benefits, Arithmetic MeanB

	Glidepath	Incremental Post-2020 Benefits	Total

NMMAPS 	Bell (2004)	$40

($7.2--$86)	$410	$450

Meta-Analysis	Bell (2005)	$150

($25--$310)	$1,500	$1,700

	Ito (2005)	$160

($29--$320)	$1,600	$1,800

	Levy (2005)	$140

($26--$270)	$1,700	$1,800

No Causality	$4.5

($2.3--$8.2)	$57	$61

PM2.5 Mortality and Morbidity Benefits of Attaining 0.070 ppm

Mortality Impact Functions Derived from Epidemiology Literature

	Glidepath	Incremental Post-2020 Benefits	Total

ACS StudyC	$77	$750	$830

Harvard Six-City StudyD	$160	$1,600	$1,800

Mortality Impact Functions Derived from Expert Elicitation

Expert A	$250	$2,400	$2,700

Expert B	$190	$1,900	$2,000

Expert C	$190	$1,800	$2,000

Expert D	$130	$1,300	$1,400

Expert E	$310	$3,000	$3,300

Expert F	$170	$1,700	$1,800

Expert G	$110	$1,100	$1,200

Expert H	$140	$1,400	$1,500

Expert I	$190	$1,800	$2,000

Expert J	$150	$1,500	$1,600

Expert K	$30	$290	$320

Expert L	$140	$1,300	$1,500

 A Does not represent equal weighting among models or between assumption
of causality vs. no causality (see text on page 63).

B A credible interval is a posterior probability interval used in
Bayesian statistics, which is similar to a confidence interval used in
frequentist statistics. Credible intervals for ozone estimates and
confidence intervals for PM2.5 estimates not provided due to the fact
that the valuation estimates were derived through a scaling technique
(see above) that precluded us from generating such estimates.

C The estimate is based on the concentration-response (C-R) function
developed from the study of the American Cancer Society cohort reported
in Pope et al (2002), which has previously been reported as the primary
estimate in recent RIAs

D Based on Laden et al (2006) reporting of the extended Six-cities
study; to be reviewed by the EPA-SAB for advice on the appropriate
method for incorporating what has previously been a sensitivity
estimate.

E All estimates incremental to 2006 PM NAAQS RIA. Estimates derived
using benefit per ton estimates discounted at 3%.Estimates derived using
a 7% discount rate would be approximately 15% lower.

Table 6-40: Estimate of Total Annual Ozone and PM2.5 Benefits (95%
Confidence Intervals, Millions of $1999) for the 0.075 ppm Standard
Alternative: National Glidepath Attainment

Ozone Mortality and Morbidity Benefits of Attaining 0.075 ppm

Standard Alternative and

Model or AssumptionA	Ozone Benefits, Arithmetic MeanB

NMMAPS	Bell (2004)	$1,600

Meta-Analysis	Bell (2005)	$5,900

	Ito (2005)	$6,400

	Levy (2005)	$7,300

No Causality	$150

PM2.5 Mortality and Morbidity Benefits of Attaining 0.075 ppm

Mortality Impact Functions Derived from Epidemiology Literature

ACS StudyC	$2,800

Harvard Six-City StudyD	$6,300

Mortality Impact Functions Derived from Expert Elicitation

Expert A	$9,000

Expert B	$6,900

Expert C	$6,800

Expert D	$4,700

Expert E	$11,000

Expert F	$6,200

Expert G	$4,000

Expert H	$5,000

Expert I	$6,700

Expert J	$5,400

Expert K	$1,100

Expert L	$4,900

	 A Does not represent equal weighting among models or between
assumption of causality vs. no causality (see text on page 63).

 B With the exception of the assumption of no causal relationship, the
arithmetic mean estimates of the annual number of lives saved are based
on an assumption of a normal distribution. Credible intervals for ozone
estimates and confidence intervals for PM2.5 estimates not provided due
to the fact that the valuation estimates were derived through a scaling
technique (see above) that precluded us from generating such estimates..

C The estimate is based on the concentration-response (C-R) function
developed from the study of the American Cancer Society cohort reported
in Pope et al (2002), which has previously been reported as the primary
estimate in recent RIAs

D Based on Laden et al (2006) reporting of the extended Six-cities
study; to be reviewed by the EPA-SAB for advice on the appropriate
method for incorporating what has previously been a sensitivity
estimate.

F All estimates incremental to 2006 PM NAAQS RIA. Estimates derived
using benefit per ton estimates discounted at 3%.Estimates derived using
a 7% discount rate would be approximately 15% lower.

Table 6-41: Estimate of Total Annual Ozone and PM2.5 Benefits (95%
Confidence Intervals, Millions of $1999) for the 0.075 ppm Standard
Alternative: California Attainment

Ozone Mortality and Morbidity Benefits of Attaining 0.075 ppm

Standard Alternative and

Model or AssumptionA	Ozone Benefits, Arithmetic MeanB

	Glidepath	Incremental Post-2020 Benefits	Total

NMMAPS 	Bell (2004)	0	$260	$260

Meta-Analysis	Bell (2005)	0	$940	$940

	Ito (2005)	0	$1,000	$1,000

	Levy (2005)	0	$1,000	$1,000

No Causality	0	$33	$33

PM2.5 Mortality and Morbidity Benefits of Attaining 0.075 ppm

Mortality Impact Functions Derived from Epidemiology Literature

	Glidepath	Incremental Post-2020 Benefits	Total

ACS StudyC	0	$210	$210

Harvard Six-City StudyD	0	$450	$450

Mortality Impact Functions Derived from Expert Elicitation

Expert A	0	$670	$670

Expert B	0	$510	$510

Expert C	0	$510	$510

Expert D	0	$350	$350

Expert E	0	$840	$840

Expert F	0	$460	$460

Expert G	0	$300	$300

Expert H	0	$380	$380

Expert I	0	$500	$500

Expert J	0	$410	$410

Expert K	0	$81	$81

Expert L	0	$370	$370

	 A Does not represent equal weighting among models or between
assumption of causality vs. no causality (see text on page 63).

B A credible interval is a posterior probability interval used in
Bayesian statistics, which is similar to a confidence interval used in
frequentist statistics. Credible intervals for ozone estimates and
confidence intervals for PM2.5 estimates not provided due to the fact
that the valuation estimates were derived through a scaling technique
(see above) that precluded us from generating such estimates.

C The estimate is based on the concentration-response (C-R) function
developed from the study of the American Cancer Society cohort reported
in Pope et al (2002), which has previously been reported as the primary
estimate in recent RIAs

D Based on Laden et al (2006) reporting of the extended Six-cities
study; to be reviewed by the EPA-SAB for advice on the appropriate
method for incorporating what has previously been a sensitivity
estimate.

E All estimates incremental to 2006 PM NAAQS RIA. Estimates derived
using benefit per ton estimates discounted at 3%.Estimates derived using
a 7% discount rate would be approximately 15% lower.

Table 6-42: Combined Estimate of Annual Ozone and PM2.5 Benefits (95%
Confidence Intervals, Millions of $1999) for the 0.065 ppm Alternative
Standard: National Glidepath Attainment

	Alternative Standard and Model or AssumptionA

	Bell (2004)	Bell (2005)	Ito (2005)	Levy (2005)	No Causality

Mortality Impact Functions Derived from Epidemiology Literature

ACS StudyB	$14,000	$24,000	$25,000	$26,000	$10,000

Harvard Six-City StudyC	$26,000	$36,000	$37,000	$38,000	$22,000

Mortality Impact Functions Derived from Expert Elicitation

Expert A	$36,000	$47,000	$48,000	$48,000	$33,000

Expert B	$29,000	$39,000	$40,000	$40,000	$25,000

Expert C	$28,000	$39,000	$40,000	$40,000	$25,000

Expert D	$21,000	$31,000	$32,000	$33,000	$18,000

Expert E	$45,000	$55,000	$56,000	$56,000	$41,000

Expert F	$26,000	$36,000	$38,000	$38,000	$23,000

Expert G	$18,000	$28,000	$30,000	$30,000	$15,000

Expert H	$22,000	$32,000	$34,000	$34,000	$19,000

Expert I	$28,000	$38,000	$40,000	$40,000	$25,000

Expert J	$23,000	$34,000	$35,000	$35,000	$20,000

Expert K	$7,700	$18,000	$19,000	$19,000	$4,300

Expert L	$22,000	$33,000	$30,000	$33,000	$18,000

	 A Does not represent equal weighting among models or between
assumption of causality vs. no causality (see text on page 63).

B The estimate is based on the concentration-response (C-R) function
developed from the study of the American Cancer Society cohort reported
in Pope et al (2002), which has previously been reported as the primary
estimate in recent RIAs

C Based on Laden et al (2006) reporting of the extended Six-cities
study; to be reviewed by the EPA-SAB for advice on the appropriate
method for incorporating what has previously been a sensitivity
estimate.

D All estimates incremental to 2006 PM NAAQS RIA. Confidence intervals
for PM2.5 estimates not provided due to the fact that the valuation
estimates were derived through a scaling technique (see above) that
precluded us from generating such estimates. Estimates derived using
benefit per ton estimates discounted at 3%.Estimates derived using a 7%
discount rate would be approximately 15% lower.

Table 6-43: Combined Estimate of Annual Ozone and PM2.5 Benefits (95%
Confidence Intervals, Millions of $1999) for the 0.065 ppm Alternative
Standard: California Glidepath Attainment

	Alternative Standard and Model or AssumptionA

	Bell (2004)	Bell (2005)	Ito (2005)	Levy (2005)	No Causality

Mortality Impact Functions Derived from Epidemiology Literature

ACS StudyB	$250	$420	$400	$430	$200

Harvard Six-City StudyC	$470	$640	$620	$650	$420

Mortality Impact Functions Derived from Expert Elicitation

Expert A	$680	$850	$830	$860	$630

Expert B	$530	$700	$690	$710	$480

Expert C	$530	$690	$680	$710	$470

Expert D	$390	$550	$540	$570	$330

Expert E	$830	$1,000	$980	$1,000	$780

Expert F	$490	$650	$640	$670	$430

Expert G	$330	$500	$490	$510	$280

Expert H	$410	$570	$560	$590	$350

Expert I	$520	$690	$670	$700	$470

Expert J	$430	$600	$590	$610	$3800

Expert K	$140	$300	$290	$320	$82

Expert L	$400	$570	$550	$580	$350

	 A Does not represent equal weighting among models or between
assumption of causality vs. no causality (see text on page 63).

B The estimate is based on the concentration-response (C-R) function
developed from the study of the American Cancer Society cohort reported
in Pope et al (2002), which has previously been reported as the primary
estimate in recent RIAs

C Based on Laden et al (2006) reporting of the extended Six-cities
study; to be reviewed by the EPA-SAB for advice on the appropriate
method for incorporating what has previously been a sensitivity
estimate.

D All estimates incremental to 2006 PM NAAQS RIA. Confidence intervals
for PM2.5 estimates not provided due to the fact that the valuation
estimates were derived through a scaling technique (see above) that
precluded us from generating such estimates. Estimates derived using
benefit per ton estimates discounted at 3%.Estimates derived using a 7%
discount rate would be approximately 15% lower.

Table 6-44: Combined Estimate of Annual Ozone and PM2.5 Benefits (95%
Confidence Intervals, Millions of $1999) for the 0.065 ppm Alternative
Standard: Incremental Benefits of California Post 2020 Attainment

	Alternative Standard and Model or AssumptionA

	Bell (2004)	Bell (2005)	Ito (2005)	Levy (2005)	No Causality

Mortality Impact Functions Derived from Epidemiology Literature

ACS StudyB	$1,700	$3,500	$3,700	$3,700	$1,100

Harvard Six-City StudyC	$2,800	$4,700	$4,900	$4,900	$2,300

Mortality Impact Functions Derived from Expert Elicitation

Expert A	$3,900	$5,800	$6,000	$6,000	$3,400

Expert B	$3,200	$5,000	$5,200	$5,200	$2,600

Expert C	$3,100	$5,000	$5,200	$5,200	$2,600

Expert D	$2,400	$4,200	$4,500	$4,400	$1,800

Expert E	$4,800	$6,600	$6,800	$6,800	$4,200

Expert F	$2,900	$4,800	$5,000	$4,900	$2,400

Expert G	$2,100	$3,900	$4,200	$4,100	$1,500

Expert H	$2,500	$4,300	$4,600	$4,500	$1,900

Expert I	$3,100	$4,900	$5,200	$5,100	$2,500

Expert J	$2,600	$4,500	$4,700	$4,700	$2,100

Expert K	$1,000	$2,900	$3,100	$3,100	$480

Expert L	$2,400	$4,300	$4,500	$4,500	$1,900

	 A Does not represent equal weighting among models or between
assumption of causality vs. no causality (see text on page 63).

B The estimate is based on the concentration-response (C-R) function
developed from the study of the American Cancer Society cohort reported
in Pope et al (2002), which has previously been reported as the primary
estimate in recent RIAs

C Based on Laden et al (2006) reporting of the extended Six-cities
study; to be reviewed by the EPA-SAB for advice on the appropriate
method for incorporating what has previously been a sensitivity
estimate.

D All estimates incremental to 2006 PM NAAQS RIA. Confidence intervals
for PM2.5 estimates not provided due to the fact that the valuation
estimates were derived through a scaling technique (see above) that
precluded us from generating such estimates. Estimates derived using
benefit per ton estimates discounted at 3%.Estimates derived using a 7%
discount rate would be approximately 15% lower.

Table 6-45: Combined Estimate of Annual Ozone and PM2.5 Benefits (95%
Confidence Intervals, Millions of $1999) for the 0.065 ppm Alternative
Standard: Total California Benefits of Post 2020 Attainment

	Alternative Standard and Model or AssumptionA

	Bell (2004)	Bell (2005)	Ito (2005)	Levy (2005)	No Causality

Mortality Impact Functions Derived from Epidemiology Literature

ACS StudyB	$1,900	$3,900	$4,100	$4,100	$1,300

Harvard Six-City StudyC	$3,300	$5,300	$5,500	$5,500	$2,700

Mortality Impact Functions Derived from Expert Elicitation

Expert A	$4,600	$6,600	$6,800	$6,800	$4,000

Expert B	$3,7000	$5,700	$5,900	$5,900	$3,100

Expert C	$3,600	$5,700	$5,900	$5,900	$3,100

Expert D	$2,800	$4,800	$5,000	$5,000	$2,200

Expert E	$5,600	$7,600	$7,800	$7,800	$5,000

Expert F	$3,400	$5,400	$5,600	$5,600	$2,800

Expert G	$2,400	$4,400	$4,700	$4,600	$1,800

Expert H	$2,900	$4,900	$5,100	$5,100	$2,300

Expert I	$3,600	$5,600	$5,800	$5,800	$3,000

Expert J	$3,100	$5,100	$5,300	$5,300	$2,500

Expert K	$1,200	$3,200	$3,400	$3,400	$570

Expert L	$2,800	$4,900	$5,100	$5,100	$2,200

	 A Does not represent equal weighting among models or between
assumption of causality vs. no causality (see text on page 63).

B The estimate is based on the concentration-response (C-R) function
developed from the study of the American Cancer Society cohort reported
in Pope et al (2002), which has previously been reported as the primary
estimate in recent RIAs

C Based on Laden et al (2006) reporting of the extended Six-cities
study; to be reviewed by the EPA-SAB for advice on the appropriate
method for incorporating what has previously been a sensitivity
estimate.

D All estimates incremental to 2006 PM NAAQS RIA. Confidence intervals
for PM2.5 estimates not provided due to the fact that the valuation
estimates were derived through a scaling technique (see above) that
precluded us from generating such estimates. Estimates derived using
benefit per ton estimates discounted at 3%.Estimates derived using a 7%
discount rate would be approximately 15% lower.

Table 6-46: Combined Estimate of Annual Ozone and PM2.5 Benefits (95%
Confidence Intervals, Millions of $1999) for the 0.070 ppm Alternative
Standard: National Glidepath Attainment

	Alternative Standard and Model or AssumptionA

	Bell (2004)	Bell (2005)	Ito (2005)	Levy (2005)	No Causality

Mortality Impact Functions Derived from Epidemiology Literature

ACS StudyB	$7,400	$13,000	$13,000	$14,000	$5,600

Harvard Six-City StudyC	$14,000	$19,000	$20,000	$21,000	$12,000

Mortality Impact Functions Derived from Expert Elicitation

Expert A	$19,000	$25,000	$25,000	$27,000	$18,000

Expert B	$15,000	$21,000	$21,000	$22,000	$14,000

Expert C	$15,000	$21,000	$21,000	$22,000	$13,000

Expert D	$11,000	$17,000	$17,000	$18,000	$9,300

Expert E	$24,000	$29,000	$30,000	$31,000	$22,000

Expert F	$14,000	$19,000	$20,000	$21,000	$12,000

Expert G	$9,700	$15,000	$16,000	$17,000	$7,900

Expert H	$12,000	$17,000	$18,000	$19,000	$9,900

Expert I	$15,000	$20,000	$21,000	$22,000	$13,000

Expert J	$13,000	$18,000	$19,000	$20,000	$11,000

Expert K	$4,100	$9,500	$10,000	$11,000	$2,300

Expert L	$12,000	$17,000	$18,000	$19,000	$9,700

	 A Does not represent equal weighting among models or between
assumption of causality vs. no causality (see text on page 63).

B The estimate is based on the concentration-response (C-R) function
developed from the study of the American Cancer Society cohort reported
in Pope et al (2002), which has previously been reported as the primary
estimate in recent RIAs

C Based on Laden et al (2006) reporting of the extended Six-cities
study; to be reviewed by the EPA-SAB for advice on the appropriate
method for incorporating what has previously been a sensitivity
estimate.

D All estimates incremental to 2006 PM NAAQS RIA. Confidence intervals
for PM2.5 estimates not provided due to the fact that the valuation
estimates were derived through a scaling technique (see above) that
precluded us from generating such estimates. Estimates derived using
benefit per ton estimates discounted at 3%.Estimates derived using a 7%
discount rate would be approximately 15% lower.

Table 6-47: Combined Estimate of Annual Ozone and PM2.5 Benefits (95%
Confidence Intervals, Millions of $1999) for the 0.070 ppm Alternative
Standard: California Glidepath Attainment

	Alternative Standard and Model or AssumptionA

	Bell (2004)	Bell (2005)	Ito (2005)	Levy (2005)	No Causality

Mortality Impact Functions Derived from Epidemiology Literature

ACS StudyB	$120	$220	$240	$210	$81

Harvard Six-City StudyC	$200	$310	$320	$300	$170

Mortality Impact Functions Derived from Expert Elicitation

Expert A	$290	$390	$410	$390	$250

Expert B	$230	$340	$350	$330	$190

Expert C	$230	$330	$350	$320	$190

Expert D	$170	$280	$290	$270	$140

Expert E	$350	$460	$470	$450	$310

Expert F	$210	$320	$330	$310	$180

Expert G	$150	$260	$270	$250	$110

Expert H	$180	$290	$300	$280	$140

Expert I	$220	$330	$340	$320	$190

Expert J	$190	$300	$310	$290	$150

Expert K	$69	$180	$190	$170	$34

Expert L	$180	$280	$290	$270	$140

	 A Does not represent equal weighting among models or between
assumption of causality vs. no causality (see text on page 63).

B The estimate is based on the concentration-response (C-R) function
developed from the study of the American Cancer Society cohort reported
in Pope et al (2002), which has previously been reported as the primary
estimate in recent RIAs

C Based on Laden et al (2006) reporting of the extended Six-cities
study; to be reviewed by the EPA-SAB for advice on the appropriate
method for incorporating what has previously been a sensitivity
estimate.

D All estimates incremental to 2006 PM NAAQS RIA. Confidence intervals
for PM2.5 estimates not provided due to the fact that the valuation
estimates were derived through a scaling technique (see above) that
precluded us from generating such estimates. Estimates derived using
benefit per ton estimates discounted at 3%.Estimates derived using a 7%
discount rate would be approximately 15% lower.

Table 6-48: Combined Estimate of Annual Ozone and PM2.5 Benefits (95%
Confidence Intervals, Millions of $1999) for the 0.070 ppm Alternative
Standard: Incremental Benefits of California Post 2020 Attainment

	Alternative Standard and Model or AssumptionA

	Bell (2004)	Bell (2005)	Ito (2005)	Levy (2005)	No Causality

Mortality Impact Functions Derived from Epidemiology Literature

ACS StudyB	$1,100	$2,200	$2,400	$2,400	$800

Harvard Six-City StudyC	$2,000	$3,100	$3,200	$3,300	$1,700

Mortality Impact Functions Derived from Expert Elicitation

Expert A	$2,800	$3,900	$4,000	$4,100	$2,500

Expert B	$2,200	$3,400	$3,500	$3,500	$1,900

Expert C	$2,200	$3,300	$3,400	$3,500	$1,900

Expert D	$1,700	$2,800	$2,900	$2,900	$1,300

Expert E	$3,400	$4,500	$4,600	$4,700	$3,100

Expert F	$2,100	$3,200	$3,300	$3,300	$1,700

Expert G	$1,500	$2,600	$2,700	$2,700	$1,100

Expert H	$1,800	$2,900	$3,000	$3,000	$1,400

Expert I	$2,200	$3,300	$3,400	$3,500	$1,900

Expert J	$1,900	$3,000	$3,100	$3,100	$1,500

Expert K	$680	$1,800	$1,900	$1,900	$350

Expert L	$1,700	$2,800	$2,900	$3,000	$1,400

	 A Does not represent equal weighting among models or between
assumption of causality vs. no causality (see text on page 63).

B The estimate is based on the concentration-response (C-R) function
developed from the study of the American Cancer Society cohort reported
in Pope et al (2002), which has previously been reported as the primary
estimate in recent RIAs

C Based on Laden et al (2006) reporting of the extended Six-cities
study; to be reviewed by the EPA-SAB for advice on the appropriate
method for incorporating what has previously been a sensitivity
estimate.

D All estimates incremental to 2006 PM NAAQS RIA. Confidence intervals
for PM2.5 estimates not provided due to the fact that the valuation
estimates were derived through a scaling technique (see above) that
precluded us from generating such estimates. Estimates derived using
benefit per ton estimates discounted at 3%.Estimates derived using a 7%
discount rate would be approximately 15% lower.

Table 6-49: Combined Estimate of Annual Ozone and PM2.5 Benefits (95%
Confidence Intervals, Millions of $1999) for the 0.070 ppm Alternative
Standard: California Post 2020 Attainment

	Alternative Standard and Model or AssumptionA

	Bell (2004)	Bell (2005)	Ito (2005)	Levy (2005)	No Causality

Mortality Impact Functions Derived from Epidemiology Literature

ACS StudyB	$1,300	$2,500	$2,600	$2,600	$890

Harvard Six-City StudyC	$2,200	$3,400	$3,500	$3,600	$1,800

Mortality Impact Functions Derived from Expert Elicitation

Expert A	$3,100	$4,300	$4,400	$4,500	$2,700

Expert B	$2,500	$3,700	$3,800	$3,800	$2,100

Expert C	$2,500	$3,700	$3,800	$3,800	$2,100

Expert D	$1,800	$3,000	$3,200	$3,200	$1,500

Expert E	$3,800	$5,000	$5,100	$5,100	$3,400

Expert F	$2,300	$3,500	$3,600	$3,600	$1,900

Expert G	$1,600	$2,800	$2,900	$3,000	$1,200

Expert H	$1,900	$3,100	$3,300	$3,300	$1,600

Expert I	$2,400	$3,600	$3,800	$3,800	$2,100

Expert J	$2,000	$3,300	$3,400	$3,400	$1,700

Expert K	$7500	$2,000	$2,100	$2,100	$380

Expert L	$1,900	$3,100	$3,200	$3,300	$1,500

	 A Does not represent equal weighting among models or between
assumption of causality vs. no causality (see text on page 63).

B The estimate is based on the concentration-response (C-R) function
developed from the study of the American Cancer Society cohort reported
in Pope et al (2002), which has previously been reported as the primary
estimate in recent RIAs

C Based on Laden et al (2006) reporting of the extended Six-cities
study; to be reviewed by the EPA-SAB for advice on the appropriate
method for incorporating what has previously been a sensitivity
estimate.

D All estimates incremental to 2006 PM NAAQS RIA. Confidence intervals
for PM2.5 estimates not provided due to the fact that the valuation
estimates were derived through a scaling technique (see above) that
precluded us from generating such estimates.  Estimates derived using
benefit per ton estimates discounted at 3%.Estimates derived using a 7%
discount rate would be approximately 15% lower.

Table 6-50: Combined Estimate of Annual Ozone and PM2.5 Benefits (95%
Confidence Intervals, Millions of $1999) for the 0.075 ppm Alternative
Standard: National Glidepath Attainment

	Alternative Standard and Model or AssumptionA

	Bell (2004)	Bell (2005)	Ito (2005)	Levy (2005)	No Causality

Mortality Impact Functions Derived from Epidemiology Literature

ACS StudyB	$4,400	$8,700	$9,300	$10,000	$2,900

Harvard Six-City StudyC	$7,900	$12,000	$13,000	$14,000	$6,500

Mortality Impact Functions Derived from Expert Elicitation

Expert A	$11,000	$15,000	$15,000	$16,000	$9,100

Expert B	$8,400	$13,000	$13,000	$14,000	$7,000

Expert C	$8,400	$13,000	$13,000	$14,000	$6,900

Expert D	$6,300	$11,000	$11,000	$12,000	$4,900

Expert E	$13,000	$17,000	$18,000	$19,000	$11,000

Expert F	$7,800	$12,000	$13,000	$14,000	$6,300

Expert G	$5,500	$9,900	$10,000	$11,000	$4,100

Expert H	$6,600	$11,000	$12,000	$12,000	$5,200

Expert I	$8,300	$13,000	$13,000	$14,000	$6,800

Expert J	$7,000	$11,000	$12,000	$13,000	$5,600

Expert K	$2,800	$7,100	$7,600	$8,500	$1,200

Expert L	$6,500	$11,000	$11,000	$12,000	$5,100

	 A Does not represent equal weighting among models or between
assumption of causality vs. no causality (see text on page 63).

 B The estimate is based on the concentration-response (C-R) function
developed from the study of the American Cancer Society cohort reported
in Pope et al (2002), which has previously been reported as the primary
estimate in recent RIAs

C Based on Laden et al (2006) reporting of the extended Six-cities
study; to be reviewed by the EPA-SAB for advice on the appropriate
method for incorporating what has previously been a sensitivity
estimate.

D All estimates incremental to 2006 PM NAAQS RIA. Confidence intervals
for PM2.5 estimates not provided due to the fact that the valuation
estimates were derived through a scaling technique (see above) that
precluded us from generating such estimates. Estimates derived using
benefit per ton estimates discounted at 3%.Estimates derived using a 7%
discount rate would be approximately 15% lower.

Table 6-51: Combined Estimate of Annual Ozone and PM2.5 Benefits (95%
Confidence Intervals, Millions of $1999) for the 0.075 ppm Alternative
Standard: California Post 2020 Attainment

	Alternative Standard and Model or AssumptionA

	Bell (2004)	Bell (2005)	Ito (2005)	Levy (2005)	No Causality

Mortality Impact Functions Derived from Epidemiology Literature

ACS StudyB	$470	$1,200	$1,200	$1,200	$240

Harvard Six-City StudyC	$700	$1,400	$1,500	$1,500	$480

Mortality Impact Functions Derived from Expert Elicitation

Expert A	$930	$1,600	$1,700	$1,700	$710

Expert B	$770	$1,500	$1,500	$1,500	$550

Expert C	$760	$1,500	$1,500	$1,500	$540

Expert D	$610	$1,300	$1,400	$1,400	$390

Expert E	$1,100	$1,800	$1,900	$1,900	$870

Expert F	$720	$1,400	$1,500	$1,500	$500

Expert G	$550	$1,200	$1,300	$1,300	$330

Expert H	$630	$1,300	$1,400	$1,400	$410

Expert I	$760	$1,500	$1,500	$1,500	$540

Expert J	$660	$1,400	$1,400	$1,400	$440

Expert K	$340	$1,000	$1,100	$1,100	$120

Expert L	$620	$1,300	$1,400	$1,400	$400

	 A Does not represent equal weighting among models or between
assumption of causality vs. no causality (see text on page 63).

B The estimate is based on the concentration-response (C-R) function
developed from the study of the American Cancer Society cohort reported
in Pope et al (2002), which has previously been reported as the primary
estimate in recent RIAs

C Based on Laden et al (2006) reporting of the extended Six-cities
study; to be reviewed by the EPA-SAB for advice on the appropriate
method for incorporating what has previously been a sensitivity
estimate.

D All estimates incremental to 2006 PM NAAQS RIA. Confidence intervals
for PM2.5 estimates not provided due to the fact that the valuation
estimates were derived through a scaling technique (see above) that
precluded us from generating such estimates. Estimates derived using
benefit per ton estimates discounted at 3%.Estimates derived using a 7%
discount rate would be approximately 15% lower.

6.5.5 Discussion of Results and Uncertainties

This analysis has estimated the health and welfare benefits of
reductions in ambient concentrations of ozone and particulate matter
resulting from a set of illustrative control strategies to reduce
emissions of ozone.  The results suggest there will be significant
additional health and welfare benefits arising from reducing emissions
from a variety of sources in and around projected nonattaining counties
in 2020.  While 2020 is the expected date that states would need to
demonstrate attainment with the revised standard, it is expected that
benefits (and costs) will begin occurring much earlier, as states begin
implementing control measures to show reasonable progress towards
attainment. Using the full range of benefits (including the results of
the expert elicitation), we estimate that total ozone and PM2.5 benefits
would be between and $2.7B and $37B annually for the 0.070 ppm
alternative when the emissions reductions from implementing the new
standard is fully realized provides additional evidence of the important
role that implementation of the standards plays in reducing the health
risks associated with exceeding the standard.

There are several important factors to consider when evaluating the
relative benefits of the attainment strategies for each of the
alternative ozone standards.

California accounts for a substantial share of the total benefits for
each of the evaluated standards.  Benefits are most uncertain for
California given the unique challenge of modeling attainment with the
standards due to the high levels of ozone, difficulties of modeling the
impacts of emissions controls on air quality, and the very large
proportion of California benefits that were derived through
extrapolation are very large relative to other areas of the U.S. for
each standard alternative. On the one hand, these California benefits
are likely to understate the actual benefits of attainment strategies,
because we applied an estimation approach that reduced concentrations
only at the specific violating monitors and not surrounding monitors
that did not violate the standards.  The magnitude of this underestimate
is unknown. On the other hand, it is possible that new technologies
might not meet the specifications, development timelines, or cost
estimates provided in this analysis, thereby increasing the uncertainty
in when and if such benefits would be truly achieved.

There are substantial uncertainties associated with the estimated
benefits of the 0.065 ppm and 0.075 ppm alternatives, which were derived
through extrapolation and interpolation, respectively. The great
majority of benefits estimated for the 0.065 ppm standard alternative
were derived through extrapolation. As noted above, these benefits are
likely to be more uncertain than the modeled benefits. The 0.075 ppm
benefits were derived through an interpolation technique (described in
Appendix 6) which scaled-down the benefits of the 0.070 ppm benefits
analysis. A key assumption in this approach is that the control strategy
to attain 0.075 ppm would share the same characteristics of the 0.070
ppm strategy—namely, regional emission controls on electrical
generating units and emission controls applied to counties within 200km
of projected non-attainment monitors. To the extent that states utilized
fewer regional emission controls, total benefits for the 0.075 ppm
strategy may be smaller.

There are a variety of uncertainties associated with the health impact
functions used in this modeling effort. These include: within study
variability, which is the precision with which a given study estimates
the relationship between air quality changes and health effects; across
study variation, which refers to the fact that different published
studies of the same pollutant/health effect relationship typically do
not report identical findings and in some instances the differences are
substantial.; the application of C-R functions nationwide, which does
not account for any relationship between region and health effect, to
the extent that such a relationship exists; extrapolation of impact
functions across population, in which we assumed that certain health
impact functions applied to age ranges broader than that considered in
the original epidemiological study; and, finally, there are various
uncertainties in the C-R function, including causality, the correlation
among multiple pollutants, the shape of the C-R function and the
relative toxicity of PM component species, and the lag between exposure
and the onset of the health effect.

There are a variety of uncertainties associated with the economic
valuation of the health endpoints estimated in this analysis.
Uncertainties specific to the valuation of premature mortality include
across study variation; the assumption that WTP for mortality risk
reduction is linear; assuming that voluntary and involuntary mortality
risk will be valued equally; assuming that premature mortality from air
pollution risk, which tend to involve longer periods of time, will be
valued the same as short catastrophic events; the possibility for
self-selection in avoiding risk, which may bias WTP estimates upward.

This analysis includes estimates of PM2.5 co-benefits that were derived
through benefit per-ton estimates derived from the Pope et. al (2002)
mortality estimate. These benefit per-ton estimates represent regional
averages. As such, they do not reflect any local variability in the
incremental PM2.5 benefits per ton of NOx abated. As discussed in the PM
NAAQS RIA (Table 5.5), there are a large number of uncertainties
associated with these PM benefits.

For the 0.070 ppm alternative, we estimate co-benefits from PM to be
between 20% and 99% of total benefits, depending on the PM2.5 and ozone
mortality functions used. In our calculation of PM2.5 co-benefits we
assume that states will pursue an ozone strategy that reduces NOx
emissions. As such, these estimates are strongly influenced by the
assumption that all PM components are equally toxic. We also acknowledge
that when implementing any new standard, states may elect to pursue a
different ozone strategy, which would in turn affect the level of PM2.5
co-benefits.

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.
 In addition, data limitations prevent an overall quantitative estimate
of the uncertainty associated with estimates of total economic benefits.
 If one is mindful of these limitations, the magnitude of the benefits
estimates presented here can be useful information in expanding the
understanding of the public health impacts of reducing ozone precursor
emissions.

There are certain unquantified effects not considered in this benefits
analysis due to lack of data, time and resources. These unquantified
endpoints include the direct effects of of ozone on vegetation, the
deposition of nitrogen to estuarine and coastal waters and agricultural
and forested land, and the changes in the level of exposure to
ultraviolet radiation from ground level ozone.

EPA will continue to evaluate new methods and models and select those
most appropriate for estimating the health benefits of reductions in air
pollution.  It is important to continue improving benefits transfer
methods in terms of transferring economic values and transferring
estimated impact functions.  The development of both better models of
current health outcomes and new models for additional health effects
such as asthma, high blood pressure, and adverse birth outcomes (such as
low birth weight) will be essential to future improvements in the
accuracy and reliability of benefits analyses (Guo et al., 1999  XE "Guo
et al., 1999"  ; Ibald-Mulli et al., 2001  XE "Ibald-Mulli et al., 2001"
 ).  Enhanced collaboration between air quality modelers,
epidemiologists, toxicologists, and economists should result in a more
tightly integrated analytical framework for measuring health benefits of
air pollution policies. Readers interested in a more extensive
discussion of the sources of uncertainty in human health benefits
analyses should consult the PM NAAQS RIA.

6.5.6 Summary of Total Benefits

Tables 6-52 presents the total number of estimated ozone and
PM2.5-related premature mortalities and morbidities avoided nationwide
in 2020. Table 6-53 presents these estimates for California, post 2020.

Table 6-52: Summary of Total Number of Annual Ozone and PM2.5-Related
Premature Mortalities and Premature Morbidity Avoided:

2020 National Benefits

Combined Estimate of Mortality

Standard Alternative and

Model or AssumptionA	Combined Range of Ozone Benefits and

 PM2.5 Co-Benefits

0.075 ppm 	0.070 ppm	0.065 ppm

NMMAPS 	Bell (2004)	390 to 2,100	650 to 4,000	1,200 to 7,600

Meta-Analysis	Bell (2005)	1,100 to 2,800	1,500 to 4,900	2,800 to 9,200

	Ito (2005)	1,200 to 2,900	1,600 to 5,000	9,400 to 3,100

	Levy (2005)	1,300 to 3,000	1,800 to 5,100	9,400 to 3,000

No Causality	190 to 1,900	370 to 4,000	690 to 7,000

	Combined Estimate of Morbidity

	Acute Myocardial Infarction	1,100	2,100	3,900

Hospital and ER Visits	30,000	55,000	100,000

Chronic Bronchitis	380	740	1,400

Acute Bronchitis	1,000	1,900	3,700

Asthma Exacerbation	7,600	15,000	28,000

Lower Respiratory Symptoms	8,300	16,000	30,000

Upper Respiratory Symptoms	6,100	12,000	22,000

School Loss Days	610,000	780,000	1,300,000

Work Loss Days	53,000	100,000	190,000

Minor Restricted Activity Days	2,000,000	2,700,000	4,700,000

Table 6-53: Summary of Total Number of Annual Ozone and PM2.5-Related
Premature Mortalities and Premature Morbidity Avoided: California Post
2020 Attainment

Combined Estimate of Mortality

Standard Alternative and

Model or AssumptionA	Combined Range of Ozone Benefits and

 PM2.5 Co-Benefits

0.075 ppm 	0.070 ppm	0.065 ppm

NMMAPS 	Bell (2004)	49 to 180	120 to 640	190 to 950

Meta-Analysis	Bell (2005)	160 to 290	310 to 830	500 to 1,300

	Ito (2005)	170 to 300	320 to 850	540 to 1,300

	Levy (2005)	170 to 300	330 to 850	530 to 1,300

No Causality	14 to 150	56 to 580	82 to 840

	Combined Estimate of Morbidity

	Acute Myocardial Infarction	80	320	460

Hospital and ER Visits	2,600	8,700	13,000

Chronic Bronchitis	28	110	170

Acute Bronchitis	75	300	440

Asthma Exacerbation	570	2,300	3,300

Lower Respiratory Symptoms	630	2,500	3,600

Upper Respiratory Symptoms	460	1,800	2,700

School Loss Days	120,000	210,000	340,000

Work Loss Days	3,900	16,000	23,000

Minor Restricted Activity Days	320,000	610,000	970,000

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 This is effectively 0.084 ppm due to current rounding conventions. When
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 The one exception relates to the use of updated health impact functions
for emergency department visits. These new functions are detailed
further in this chapter.

 The PM2.5 benefits presented below reflect the NOx emission reductions
from the ozone control strategy. Reductions from Ocean-Going Vessels
burning residual diesel fuel were included both East and West in the
baseline PM co-benefits, but not included in the ozone baseline for the
west.  See chapter 3 for more details of this rule and its application.

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 Expert elicitation is a formal, highly structured and well documented
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 Health impact functions measure the change in a health endpoint of
interest, such as hospital admissions, for a given change in ambient
ozone or PM concentration.

 Industrial Economics, Inc.  2006.  Expanded Expert Judgment Assessment
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 A credible interval is a posterior probability interval used in
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 Note that the valuation estimates for ozone benefits are not
discounted. Because these are short term benefits that occur the same
year in which the alternate standard is met, discounting is not
necessary.

 A credible interval is a posterior probability interval used in
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6- PAGE   2

6- PAGE   1

A The estimate is based on the concentration-response (C-R) function
developed from the study of the American Cancer Society cohort reported
in Pope et al (2002), which has previously been reported as the primary
estimate in recent RIAs

B Based on Laden et al (2006) reporting of the extended Six-cities
study; to be reviewed by the EPA-SAB for advice on the appropriate
method for incorporating what has previously been a sensitivity
estimate.

C All estimates rounded to two significant figures. As such, confidence
intervals may not be symmetrical and totals will not sum across columns.
All estimates incremental to 2006 PM NAAQS RIA. Estimates do not include
confidence intervals because they were derived through a scaling
technique described above.

A The estimate is based on the concentration-response (C-R) function
developed from the study of the American Cancer Society cohort reported
in Pope et al (2002), which has previously been reported as the primary
estimate in recent RIAs

B Based on Laden et al (2006) reporting of the extended Six-cities
study; to be reviewed by the EPA-SAB for advice on the appropriate
method for incorporating what has previously been a sensitivity
estimate.

C All estimates rounded to two significant figures. As such, confidence
intervals may not be symmetrical and totals will not sum across columns.
All estimates incremental to 2006 PM NAAQS RIA. Estimates do not include
confidence intervals because they were derived through a scaling
technique described above.

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All estimates incremental to 2006 PM NAAQS RIA. Estimates do not include
confidence intervals because they were derived through a scaling
technique described above.


[Federal Register Volume 82, Number 22 (Friday, February 3, 2017)]
[Rules and Regulations]
[Pages 9127-9128]
[FR Doc No: 2017-02309]

========================================================================
Rules and Regulations
                                                Federal Register
________________________________________________________________________

This section of the FEDERAL REGISTER contains regulatory documents
having general applicability and legal effect, most of which are keyed
to and codified in the Code of Federal Regulations, which is published
under 50 titles pursuant to 44 U.S.C. 1510.

The Code of Federal Regulations is sold by the Superintendent of Documents.
Prices of new books are listed in the first FEDERAL REGISTER issue of each
week.

========================================================================

Federal Register / Vol. 82, No. 22 / Friday, February 3, 2017 / Rules
and Regulations

DEPARTMENT OF ENERGY

Federal Energy Regulatory Commission

18 CFR Part 157

[Docket No. RM81-19-000]

Natural Gas Pipelines; Project Cost and Annual Limits

AGENCY: Federal Energy Regulatory Commission, Energy.

ACTION: Final rule.

-----------------------------------------------------------------------

SUMMARY: Pursuant to the authority delegated by the Commission's
regulations, the Director of the Office of Energy Projects (OEP)
computes and publishes the project cost and annual limits for natural
gas pipelines blanket construction certificates for each calendar year.

DATES: This final rule is effective February 3, 2017 and establishes
cost limits applicable from January 1, 2017 through December 31, 2017.

FOR FURTHER INFORMATION CONTACT: Marsha K. Palazzi, Chief, Certificates
Branch 2, Division of Pipeline Certificates,<PHONE_NUMBER>.

SUPPLEMENTARY INFORMATION: Section 157.208(d) of the Commission's
Regulations provides for project cost limits applicable to
construction, acquisition, operation and miscellaneous rearrangement of
facilities (Table I) authorized under the blanket certificate procedure
(Order No. 234, 19 FERC ] 61,216). Section 157.215(a) specifies the
calendar year dollar limit which may be expended on underground storage
testing and development (Table II) authorized under the blanket
certificate. Section 157.208(d) requires that the ``limits specified in
Tables I and II shall be adjusted each calendar year to reflect the
'GDP implicit price deflator' published by the Department of Commerce
for the previous calendar year.''
    Pursuant to Sec.  375.308(x)(1) of the Commission's Regulations,
the authority for the publication of such cost limits, as adjusted for
inflation, is delegated to the Director of the Office of Energy
Projects. The cost limits for calendar year 2017, as published in Table
I of Sec.  157.208(d) and Table II of 157.215(a), are hereby issued.

Effective Date

    This final rule is effective February 3, 2017. The provisions of 5
U.S.C. 804 regarding Congressional review of Final Rules does not apply
to the Final Rule because the rule concerns agency procedure and
practice and will not substantially affect the rights or obligations of
non-agency parties. The Final Rule merely updates amounts published in
the Code of Federal Regulations to reflect the Department of Commerce's
latest annual determination of the Gross Domestic Product (GDP)
implicit price deflator, a mathematical updating required by the
Commission's existing regulations.

List of Subjects in 18 CFR Part 157

    Administrative practice and procedure, Natural Gas, Reporting and
recordkeeping requirements.

Ann Miles,
Director, Office of Energy Projects.

    Accordingly, 18 CFR part 157 is amended as follows:

PART 157--[AMENDED]

0
1. The authority citation for part 157 is revised to read as follows:

    Authority: 15 U.S.C. 717-717w, 3301-3432; 42 U.S.C. 7101-7352.

0
2. Table I in Sec.  157.208(d) is revised to read as follows:

Sec.  157.208  Construction, acquisition, operation, replacement, and
miscellaneous rearrangement of facilities.

* * * * *
    (d) * * *

                                 Table I
------------------------------------------------------------------------
                                                       Limit
                                         -------------------------------
                  Year                      Auto. proj.    Prior notice
                                            cost limit      proj. cost
                                             (Col. 1)     limit (Col. 2)
------------------------------------------------------------------------
1982....................................      $4,200,000     $12,000,000
1983....................................       4,500,000      12,800,000
1984....................................       4,700,000      13,300,000
1985....................................       4,900,000      13,800,000
1986....................................       5,100,000      14,300,000
1987....................................       5,200,000      14,700,000
1988....................................       5,400,000      15,100,000
1989....................................       5,600,000      15,600,000
1990....................................       5,800,000      16,000,000
1991....................................       6,000,000      16,700,000
1992....................................       6,200,000      17,300,000
1993....................................       6,400,000      17,700,000
1994....................................       6,600,000      18,100,000
1995....................................       6,700,000      18,400,000
1996....................................       6,900,000      18,800,000
1997....................................       7,000,000      19,200,000
1998....................................       7,100,000      19,600,000
1999....................................       7,200,000      19,800,000
2000....................................       7,300,000      20,200,000
2001....................................       7,400,000      20,600,000
2002....................................       7,500,000      21,000,000
2003....................................       7,600,000      21,200,000
2004....................................       7,800,000      21,600,000
2005....................................       8,000,000      22,000,000
2006....................................       9,600,000      27,400,000
2007....................................       9,900,000      28,200,000
2008....................................      10,200,000      29,000,000
2009....................................      10,400,000      29,600,000
2010....................................      10,500,000      29,900,000
2011....................................      10,600,000      30,200,000
2012....................................      10,800,000      30,800,000
2013....................................      11,000,000      31,400,000
2014....................................      11,200,000      31,900,000
2015....................................      11,400,000      32,300,000
2016....................................      11,600,000      32,800,000
2017....................................      11,800,000      33,200,000
------------------------------------------------------------------------

* * * * *

0
3. Table II in Sec.  157.215(a)(5) is revised to read as follows:

Sec.  157.215  Underground storage testing and development.

    (a) * * *
    (5) * * *

                                Table II
------------------------------------------------------------------------
                          Year                                 Limit
------------------------------------------------------------------------
1982....................................................      $2,700,000
1983....................................................       2,900,000
1984....................................................       3,000,000
1985....................................................       3,100,000
1986....................................................       3,200,000
1987....................................................       3,300,000
1988....................................................       3,400,000
1989....................................................       3,500,000
1990....................................................       3,600,000
1991....................................................       3,800,000

1992....................................................       3,900,000
1993....................................................       4,000,000
1994....................................................       4,100,000
1995....................................................       4,200,000
1996....................................................       4,300,000
1997....................................................       4,400,000
1998....................................................       4,500,000
1999....................................................       4,550,000
2000....................................................       4,650,000
2001....................................................       4,750,000
2002....................................................       4,850,000
2003....................................................       4,900,000
2004....................................................       5,000,000
2005....................................................       5,100,000
2006....................................................       5,250,000
2007....................................................       5,400,000
2008....................................................       5,550,000
2009....................................................       5,600,000
2010....................................................       5,700,000
2011....................................................       5,750,000
2012....................................................       5,850,000
2013....................................................       6,000,000
2014....................................................       6,100,000
2015....................................................       6,200,000
2016....................................................       6,300,000
2017....................................................       6,400,000
------------------------------------------------------------------------

* * * * *
[FR Doc. 2017-02309 Filed 2-2-17; 8:45 am]
BILLING CODE 6717-01-P