&EPA
United State
EirviroiiwiU Protection
Agnncy
Health Risk and Exposure Assessment
for Ozone
Second External Review Draft
Chapter 7, 8 and 9 Appendices
-------
DISCLAIMER
This draft document has been prepared by staff from the Risk and Benefits Group, Health
and Environmental Impacts Division, Office of Air Quality Planning and Standards, U.S.
Environmental Protection Agency. Any findings and conclusions are those of the authors and do
not necessarily reflect the views of the Agency. This draft document is being circulated to
facilitate discussion with the Clean Air Scientific Advisory Committee to inform the EPA's
consideration of the ozone National Ambient Air Quality Standards.
This information is distributed for the purposes of pre-dissemination peer review under
applicable information quality guidelines. It has not been formally disseminated by EPA. It
does not represent and should not be construed to represent any Agency determination or policy.
Questions related to this preliminary draft document should be addressed to Dr. Bryan
Hubbell, U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards,
C539-07, Research Triangle Park, North Carolina 27711 (email: hubbell.bryan@epa.gov).
-------
EPA-452/P-14-004e
February 2014
Health Risk and Exposure Assessment for Ozone
Second External Review Draft
Chapter 7, 8 and 9 Appendices
U.S. Environmental Protection Agency
Office of Air and Radiation
Office of Air Quality Planning and Standards
Health and Environmental Impacts Division
Risk and Benefits Group
Research Triangle Park, North Carolina 27711
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Appendix 7A. Detailed Information on Effect Estimates, Baseline Incidence and Demographic Data Used in the Epidemiological-Based Risk Assessment
Endpoint
Core Risk - short-term e
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Core Risk - long-term ei
Mortality, Respiratory
Mortality, Respiratory
Mortality, Respiratory
Mortality, Respiratory
Mortality, Respiratory
Mortality, Respiratory
Mortality, Respiratory
Mortality, Respiratory
Mortality, Respiratory
Mortality, Respiratory
Mortality, Respiratory
Mortality, Respiratory
Core Risk - short-term e
HA, All Respiratory
HA, All Respiratory
HA, Asthma
HA, Asthma
HA, Chronic Lung
Disease
HA, All Respiratory
HA, Chronic Lung
Disease (less Asthma)
Study
posu re -related all-can
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
posure-related respirat
Jerrett etal., 2009
Jerrett etal., 2010
Jerrett etal., 2011
Jerrett etal., 2012
Jerrett etal., 2013
Jerrett etal., 2014
Jerrett etal., 2015
Jerrett etal., 2016
Jerrett etal., 2017
Jerrett etal., 2018
Jerrett etal., 2019
Jerrett etal., 2020
posure-related morbid
Katsouyanni et al.,
2009
Katsouyanni et al.,
2009
Silvermanand Ito,
2010
Silvermanand Ito,
2010
Lin etal. (a), 2008
Linn etal., 2000
2006
Urban study area
e mortality
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
ory mortality
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
LosAngeles,CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
ity
Detroit, Ml
Detroit, Ml
New York, NY
New York, NY
New York, NY
Los Angeles, CA
Atlanta, GA
Study area
template
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
Study information (C-R function)
„
DSHourMax
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
Seasonal-avg DlhrMax
Seasonal-avg DlhrMax
Seasonal-avg DlhrMax
Seasonal-avg DlhrMax
Seasonal-avg DlhrMax
Seasonal-avg DlhrMax
Seasonal-avg DlhrMax
Seasonal-avg DlhrMax
Seasonal-avg DlhrMax
Seasonal-avg DlhrMax
Seasonal-avg DlhrMax
Seasonal-avg DlhrMax
DIHourMax
DIHourMax
DSHourMax
DSHourMax
DIHourMax
D24HourMean
DSHourMean
Risk assessment
modeling period
March-October
April-October
April-September
April-October
March-
September
April-September
January-
December
January-
December
April-October
April-October
January-
December
April-October
April-September
April-September
April-September
April-September
April-September
April-September
April-September
April-September
April-September
April-September
April-September
April-September
June-August
June-August
April-October
April-October
April-October
June-August
June-August
Age range
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
30-99
30-99
30-99
30-99
30-99
30-99
30-99
30-99
30-99
30-99
30-99
30-99
65-99
65-99
6-18
6-18
0-17
30-99
65-99
Lag
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
average of lag 0
average of lag 0
and lagl
average of lag 0
and lagl
average of lag 0
and lagl
Lag2d
LagOd
distributed lagO
Id
Additional study
details
penalized splines
natural splines
PM2.5
Statistical
Model
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
logistic
Effect
estimate
(Beta)
0.00029536
0.000515048
0.000681639
0.000596249
0.000351818
0.001045932
0.000162925
0.000273722
0.001092475
0.000624582
0.000569111
0.000544366
0.003922071
0.003922071
0.003922071
0.003922071
0.003922071
0.003922071
0.003922071
0.003922071
0.003922071
0.003922071
0.003922071
0.003922071
0.00056
0.00054
0.007906969
0.005555347
0.00076087
0.0006
0.00054
SE (effect
estimate)3
0.000291921
0.000329964
0.000342908
0.000314904
0.000356513
0.000311744
0.000207509
0.000157143
0.000207428
0.000284572
0.00031446
0.000342796
0.001324866
0.001324866
0.001324866
0.001324866
0.001324866
0.001324866
0.001324866
0.001324866
0.001324866
0.001324866
0.001324866
0.001324866
0.000352041
0.000357143
0.0037862
0.003692645
0.000163043
0.0007
0.00019898
Baseline incidence11
2007
24,086
22,709
29,168
17,651
9,977
21,796
35,544
121,194
67,939
38,076
30,170
17,256
3,803
3,970
6,466
2,947
2,287
4,094
3,317
12,443
10,779
6,747
3,814
3,143
8,291
1,463
1,463
3,706
32,087
2,646
2009
24,565
22,630
28,606
17,246
10,128
21,387
36,135
121,736
66,898
37,426
30,336
16,888
3,893
3,952
6,328
2,873
2,324
4,007
3,370
12,529
10,600
6,620
3,835
3,072
8,519
1,453
1,453
3,667
33,749
2,SS3
Population
2007
5,798,520
5,362,979
7,469,168
3,419,753
3,585,323
5,703,138
6,145,152
21,225,780
16,024,400
7,813,329
4,675,398
3,344,163
3,283,262
3,195,786
4,562,351
2,105,949
2,055,105
3,382,306
3,359,712
11,723,570
9,670,019
4,647,403
2,695,086
1,998,779
687,389
2,804,642
2,804,642
3,823,944
11,723,570
505,741
2009
5,991,005
5,437,691
7,553,629
3,404,546
3,714,085
5,620,925
6,437,742
21,587,310
16,202,260
7,904,328
4,770,990
3,369,708
3,419,286
3,255,696
4,631,833
2,107,957
2,137,319
3,373,240
3,529,238
12,038,790
9,817,407
4,726,359
2,765,834
2,028,727
713,374
2,787,619
2,787,619
3,786,262
12,038,790
554,624
-------
Endpoint
HA, Chronic Lung
Disease (less Asthma)
HA, Chronic Lung
Disease (less Asthma)
HA, Chronic Lung
Disease (less Asthma)
HA, Chronic Lung
Disease (less Asthma)
HA, Chronic Lung
Disease (less Asthma)
HA, Chronic Lung
Disease (less Asthma)
HA, Chronic Lung
Disease (less Asthma)
HA, Chronic Lung
Disease (less Asthma)
HA, Chronic Lung
Disease (less Asthma)
HA, Chronic Lung
Disease (less Asthma)
HA, Chronic Lung
Disease (less Asthma)
Emergency Room Visits,
Respiratory
Emergency Room Visits,
Respiratory
Emergency Room Visits,
Respiratory
Emergency Room Visits,
Respiratory
Emergency Room Visits,
Respiratory
Emergency Room Visits,
Respiratory
Emergency Room Visits,
Respiratory
Emergency Room Visits,
Respiratory
Emergency Room Visits,
Asthma
Emergency Room Visits,
Asthma
Emergency Room Visits,
Asthma
Emergency Room Visits,
Asthma
Emergency Room Visits,
Asthma
Asthma Exacerbation,
Chest Tightness
Asthma Exacerbation,
Chest Tightness
Asthma Exacerbation,
Chest Tightness
Asthma Exacerbation,
Chest Tightness
Study
2006
2006
2006
2006
2006
2006
2006
2006
2006
2006
2006
Strickland et al., 2010
Strickland et al., 2010
Tolbertetal., 2007
Tolbertetal., 2007
Tolbertetal., 2007
Tolbertetal., 2007
Tolbertetal., 2007
Darrowetal., 2011
Itoetal., 2007
Itoetal., 2007
Itoetal., 2007
Itoetal., 2007
Itoetal., 2007
Gentetal., 2003
Gentetal., 2003
Gentetal., 2003
Gentetal., 2003
Urban study area
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Atlanta, GA
Atlanta, GA
Atlanta, GA
Atlanta, GA
Atlanta, GA
Atlanta, GA
Atlanta, GA
Atlanta, GA
New York, NY
New York, NY
New York, NY
New York, NY
New York, NY
Boston, MA
Boston, MA
Boston, MA
Boston, MA
Study area
template
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
Atlanta, GA
Atlanta, GA
Atlanta, GA
Atlanta, GA
Atlanta, GA
Atlanta, GA
Atlanta, GA
Atlanta, GA
New York, NY
New York, NY
New York, NY
New York, NY
New York, NY
Boston, MA
Boston, MA
Boston, MA
Boston, MA
Study information (C-R function)
„
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DIHourMax
DSHourMax
DIHourMax
DIHourMax
Risk assessment
modeling period
June-August
June-August
June-August
June-August
June-August
June-August
June-August
June-August
June-August
June-August
June-August
March-October
(8)
March-October
(8)
March-October
(8)
March-October
(8)
March-October
(8)
March-October
(8)
March-October
(8)
March-October
(8)
April-October (7)
April-October (7)
April-October (7)
April-October (7)
April-October (7)
April-September
(6)
April-September
(6)
April-September
(6)
April-September
(6)
Age range
65-99
65-99
65-99
65-99
65-99
65-99
65-99
65-99
65-99
65-99
65-99
5-17
5-17
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-12
0-12
0-12
0-12
Lag
distributed lagO
Id
distributed lagO
Id
distributed lagO
Id
distributed lagO
Id
distributed lagO
Id
distributed lagO
Id
distributed lagO
Id
distributed lagO
Id
distributed lagO
Id
distributed lagO
Id
distributed lagO
Id
distributed lagO
7d
average of lags
0-2
average of lags
0-2
average of lags
0-2
average of lags
0-2
average of lags
0-2
average of lags
0-2
Lag Id
average of lag 0
and lagl
average of lag 0
and lagl
average of lag 0
and lagl
average of lag 0
and lagl
average of lag 0
and lagl
Lag Id
Lag Id
Lag Id
Lag Id
Additional study
details
CO
NO2
PM10
PM10, NO2
PM2.5
NO2
CO
SO2
PM2.5
PM2.5
Statistical
Model
logistic
logistic
logistic
logistic
logistic
logistic
logistic
logistic
logistic
logistic
logistic
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
logistic
logistic
logistic
logistic
Effect
estimate
(Beta)
0.00054
0.00054
0.00054
0.00054
0.00054
0.00054
0.00054
0.00054
0.00054
0.00054
0.00054
0.004786368
0.002699013
0.001286007
0.0011408
0.001028713
0.000803233
0.000774925
0.000685212
0.005213389
0.00397574
0.003233689
0.005543699
0.004114984
0.00076087
0.005703579
0.007705248
0.007013137
SE (effect
estimate)3
0.00019898
0.00019898
0.00019898
0.00019898
0.00019898
0.00019898
0.00019898
0.00019898
0.00019898
0.00019898
0.00019898
0.000760164
0.00064564
0.000206235
0.000228328
0.000250581
0.000266964
0.000267224
0.000138467
0.00090866
0.000978924
0.00093586
0.000893945
0.000922644
0.002000215
0.002021676
0.002266587
0.002273393
Baseline incidence11
2007
2,958
4,502
2,569
923
3,643
3,238
6,741
7,850
5,173
1,385
2,048
38,242
38,242
140,690
140,690
140,690
140,690
140,690
140,690
45,290
45,290
45,290
45,290
45,290
235,224
294,030
235,224
294,030
2009
3,086
4,618
987
3,740
3,452
7,165
8,058
5,315
1,475
2,099
39,464
39,464
145,038
145,038
145,038
145,038
145,038
145,038
45,547
45,547
45,547
45,547
45,547
233,053
291,316
233,053
291,316
Population
2007
621,817
975,770
337,427
687,389
536,446
2,183,030
2,052,957
1,023,602
536,631
442,691
1,105,830
1,105,830
5,798,520
5,798,520
5,798,520
5,798,520
5,798,520
5,798,520
16,024,400
16,024,400
16,024,400
16,024,400
16,024,400
1,189,925
1,189,925
1,189,925
1,189,925
2009
654,073
1,009,556
365,450
713,374
576,473
2,301,532
2,120,805
1,059,325
569,298
456,212
1,141,180
1,141,180
5,991,005
5,991,005
5,991,005
5,991,005
5,991,005
5,991,005
16,202,260
16,202,260
16,202,260
16,202,260
16,202,260
1,177,644
1,177,644
1,177,644
1,177,644
-------
Endpoint
Asthma Exacerbation,
Shortness of Breath
Asthma Exacerbation,
Shortness of Breath
Asthma Exacerbation,
Wheeze
Sensitivity Analysis - she
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Study
Gentetal., 2003
Gentetal., 2003
Gentetal., 2003
it-term exposure-relat
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Urban study area
Boston, MA
Boston, MA
Boston, MA
ed all-cause mortal!
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Study area
template
Boston, MA
Boston, MA
Boston, MA
V
Epi study
based
Epi study
based
Epi study
based
Epi study
based
Epi study
based
Epi study
based
Epi study
based
Epi study
based
Epi study
based
Epi study
based
Epi study
based
Epi study
based
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
Study information (C-R function)
„
DIHourMax
DSHourMax
DIHourMax
DSHourMax
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMax
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMax
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
Risk assessment
modeling period
April-September
(6)
April-September
(6)
April-September
(6)
March-October
April-October
April-September
April-October
March-
September
April-September
January-
December
January-
December
April-October
April-October
January-
December
April-October
March-October
April-October
April-September
April-October
March-
September
April-September
January-
December
January-
December
April-October
April-October
January-
December
April-October
March-October
April-October
April-September
April-October
March-
September
April-September
January-
December
Age range
0-12
0-12
0-12
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
Lag
Lag Id
Lag Id
LagOd
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
Additional study
details
PM2.5
Regional Bayes-
based
Regional Bayes-
based
Regional Bayes-
based
Regional Bayes-
based
Regional Bayes-
based
Regional Bayes-
based
Regional Bayes-
based
Regional Bayes-
based
Regional Bayes-
based
Regional Bayes-
based
Regional Bayes-
based
Regional Bayes-
based
PM10
PM10
PM10
PM10
PM10
PM10
PM10
Statistical
Model
logistic
logistic
logistic
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
Effect
estimate
(Beta)
0.003977017
0.005247285
0.006002092
0.00029536
0.000515048
0.000681639
0.000596249
0.000351818
0.001045932
0.000162925
0.000273722
0.001092475
0.000624582
0.000569111
0.000544366
0.000260274
0.000939893
0.000882699
0.000678936
0.0000293
0.000715864
0.000422972
0.000198781
0.001122295
0.001025996
0.000107022
0.000675448
0.000118303
0.000472682
0.000159064
0.000462588
-0.0000383
0.000286042
0.000631017
SE (effect
estimate)3
0.001794699
0.002180837
0.002022527
0.000291921
0.000329964
0.000342908
0.000314904
0.000356513
0.000311744
0.000207509
0.000157143
0.000207428
0.000284572
0.00031446
0.000342796
0.000235902
0.000282919
0.000300367
0.000263728
0.000350178
0.000262244
0.000182484
0.000150979
0.000180774
0.000239469
0.000323012
0.00028
0.000545629
0.000530993
0.000575152
0.000433506
0.000526263
0.000406606
0.000362269
Baseline incidence11
2007
235,224
235,224
548,857
SA
for 2 009
SA
for 2 009
SA
for 2 009
2009
233,053
233,053
543,790
16,524
11,341
14,399
15,402
9,093
19,846
29,179
92,186
50,341
27,057
29,479
11,625
24,565
22,630
28,606
17,246
10,128
21,387
36,135
121,736
66,898
37,426
30,336
16,888
24,565
22,630
28,606
17,246
10,128
21,387
36,135
Population
2007
1,189,925
1,189,925
1,189,925
SA completed
for 2 009
SA completed
for 2 009
SA completed
for 2 009
2009
1,177,644
1,177,644
1,177,644
4,462,663
1,953,317
3,609,318
2,786,348
2,737,299
4,377,305
5,769,285
16,403,420
13,239,830
4,737,330
4,341,150
1,855,249
5,991,005
5,437,691
7,553,629
3,404,546
3,714,085
5,620,925
6,437,742
21,587,310
16,202,260
7,904,328
4,770,990
3,369,708
5,991,005
5,437,691
7,553,629
3,404,546
3,714,085
5,620,925
6,437,742
-------
Endpoint
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Mortality, All Cause
Sensitivity Analysis - Ion
Mortality, Respiratory
Mortality, Respiratory
Mortality, Respiratory
Mortality, Respiratory
Mortality, Respiratory
Mortality, Respiratory
Mortality, Respiratory
Mortality, Respiratory
Mortality, Respiratory
Mortality, Respiratory
Mortality, Respiratory
Mortality, Respiratory
Study
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Smith etal., 2009
Zanobettiand
Schwartz fb), 2008
Zanobettiand
Schwartz fb), 2008
Schwartz fb), 2008
Schwartz fb), 2008
Zanobettiand
Schwartz fb), 2008
Zanobettiand
Schwartz fb), 2008
Schwartz fb), 2008
Schwartz fb), 2008
Zanobettiand
Schwartz fb), 2008
Zanobettiand
Schwartz fb), 2008
Schwartz fb), 2008
Schwartz fb), 2008
g-term exposure- relate
Jerrett etal., 2009
Jerrett etal., 2010
Jerrett etal., 2011
Jerrett etal., 2012
Jerrett etal., 2013
Jerrett etal., 2014
Jerrett etal., 2015
Jerrett etal., 2016
Jerrett etal., 2017
Jerrett etal., 2018
Jerrett etal., 2019
Jerrett etal., 2020
Urban study area
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
d respiratory morta
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
LosAngeles,CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Study area
template
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
ty
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
Study information (C-R function)
„
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
Seasonal-avg DlhrMax
Seasonal-avg DlhrMax
Seasonal-avg DlhrMax
Seasonal-avg DlhrMax
Seasonal-avg DlhrMax
Seasonal-avg DlhrMax
Seasonal-avg DlhrMax
Seasonal-avg DlhrMax
Seasonal-avg DlhrMax
Seasonal-avg DlhrMax
Seasonal-avg DlhrMax
Seasonal-avg DlhrMax
Risk assessment
modeling period
January-
December
April-October
April-October
January-
December
April-October
June-August
June-August
June-August
June-August
June-August
June-August
June-August
June-August
June-August
June-August
June-August
June-August
April-September
April-September
April-September
April-September
April-September
April-September
April-September
April-September
April-September
April-September
April-September
April-September
Age range
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
30-99
30-99
30-99
30-99
30-99
30-99
30-99
30-99
30-99
30-99
30-99
30-99
Lag
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
6d
distributed lagO
3d
distributed lagO
3d
distributed lagO
3d
distributed lagO
3d
distributed lagO
3d
distributed lagO
3d
distributed lagO
3d
distributed lagO
3d
distributed lagO
3d
distributed lagO
3d
distributed lagO
3d
distributed lagO
3d
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
Additional study
details
PM10
PM10
PM10
PM10
PM10
Reginoal
Reginoal
Reginoal
Reginoal
Reginoal
Reginoal
Reginoal
Reginoal
Reginoal
Reginoal
Reginoal
Reginoal
Statistical
Model
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
Effect
estimate
(Beta)
0.0000524
0.000440658
0.000544544
0.000280547
0.000360175
0.00029536
0.000515048
0.000681639
0.000596249
0.000351818
0.001045932
0.000162925
0.000273722
0.001092475
0.000624582
0.000569111
0.000544366
0.003192937
0.003853068
0.003853068
0.004604295
0.003117797
0.004604295
0.003192937
0.002767363
0.003853068
0.003853068
0.004604295
SE (effect
estimate)3
0.000347345
0.000390403
0.000518628
0.000543375
0.000581296
0.000288562
0.00031402
0.000328429
0.000354552
0.000408829
0.000344122
0.000262836
0.000213402
0.000235676
0.000314555
0.000388525
0.000333395
0.0027397
0.0027397
0.0027397
0.0027397
0.0027397
0.0027397
0.0027397
0.0027397
0.0027397
0.0027397
0.0027397
Baseline incidence11
2007
SA
for 2 009
3,803
3,970
6,466
2,947
2,287
4,094
3,317
12,443
10,779
6,747
3,143
2009
121,736
66,898
37,426
30,336
16,888
10,119
10,408
15,160
7,808
4,953
11,430
10,132
32,840
30,192
17,137
8,295
7,837
3,893
3,952
6,328
2,873
2,324
4,007
3,370
12,529
10,600
6,620
3,072
Population
2007
SA completed
for 2 009
3,283,262
3,195,786
4,562,351
2,105,949
2,055,105
3,382,306
3,359,712
11,723,570
9,670,019
4,647,403
1,998,779
2009
21,587,310
16,202,260
7,904,328
4,770,990
3,369,708
5,991,005
5,437,691
7,553,629
3,404,546
3,714,085
5,620,925
6,437,742
21,587,310
16,202,260
7,904,328
4,770,990
3,369,708
3,419,286
3,255,696
4,631,833
2,107,957
2,137,319
3,373,240
3,529,238
12,038,790
9,817,407
4,726,359
2,028,727
a-all Beta distributions assumed to be normal
b-Gent et al., 2003 also usese the following prevalence rates: 0.028 (wheeze), 0.015 (shortness of breath), 0.012 (chest tightness) (from study
-------
Appendix 7-B - Detailed Summary of Core Risk Estimates
Table 7B-1 Core Short-Term Ozone-Attributable Mortality (2007) (incidence, percent of
baseline mortality, incidence per 100,000) (Smith et al., 2009)
Study Area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
NewYork, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Air Quality Scenario
Absolute Ozone-Attributable Incidence
Base
300
(-430-1000)
470
(-260-1200)
360
(-510-1200)
430
(-41-890)
87
(-290-440)
660
(32-1300)
640
(120-1100)
1100
(-450-2600)
3000
(1800-4100)
1300
(290-2300)
380
(-400-1100)
460
(-110-1000)
75ppb
270
(-370 - 890)
440
(-250 - 1100)
350
(-500 - 1200)
430
(-41-890)
86
(-280 - 440)
660
(32-1300)
680
(130-1200)
1300
(-530 - 3000)
2800
(1700-3900)
1200
(270-2200)
370
(-390 - 1100)
430
(-110-950)
70ppb
260
(-360-850)
430
(-240 - 1100)
350
(-490-1200)
420
(-40 - 860)
84
(-280-430)
630
(31-1200)
680
(130-1200)
1200
(-510-2900)
2700
(1600-3700)
1200
(260-2100)
360
(-380-1100)
410
(-100-910)
65ppb
250
(-340-820)
420
(-230-1000)
330
(-470-1100)
400
(-38-830)
82
(-270-420)
610
(30 - 1200)
670
(120-1200)
1200
(-490-2800)
2200
(1300-3100)
1200
(260-2000)
350
(-380-1100)
390
(-98-870)
60ppb
230
(-330-780)
400
(-220-1000)
320
(-460-1100)
370
(-35-760)
79
(-260-400)
590
(29-1100)
660
(120-1200)
1100
(-460-2600)
2200
(1300-3100)
1100
(250-2000)
340
(-370-1000)
370
(-93-820)
Change in Ozone-Attributable Incidence
Base-75
37
(-51-120)
23
(-12-57)
6
(-8-19)
0
(0--1)
1
(-3-4)
3
(0-5)
-46
(-8 --83)
-180
(77- -450)
150
(90-210)
64
(14-110)
11
(-12-33)
28
(-7-62)
75-70
12
(-16-39)
13
(-7-33)
7
(-10-24)
14
(-1-28)
2
(-6-10)
23
(1-44)
5
(1-9)
43
(-18-100)
130
(80-190)
35
(8-62)
7
(-7-20)
18
(-5-41)
75-65
21
(-30-72)
27
(-15-68)
20
(-28-67)
32
(-3-67)
4
(-14-23)
42
(2 - 81)
11
(2-20)
87
(-36-210)
640
(380-890)
76
(17-140)
13
(-13-39)
39
(-10-86)
75-60
34
(-47-110)
45
(-25-110)
32
(-45-110)
64
(-6-130)
8
(-25-40)
69
(3 - 130)
24
(4-43)
160
(-66-380)
NA
NA
120
(25-210)
23
(-24-70)
60
(-15-130)
Study Area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
NewYork, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Air Quality Scenario
Percent of Baseline Incidence Attributable to Ozone
Base
1.2
2.0
1.2
2.4
0.8
3.0
1.8
0.9
4.3
3.4
1.2
2.6
75ppb
1.1
1.9
1.2
2.4
0.8
3.0
1.9
1.0
4.1
3.2
1.2
2.5
70ppb
1.0
1.9
1.2
2.4
0.8
2.9
1.9
1.0
3.9
3.2
1.2
2.4
65ppb
1.0
1.8
1.1
2.3
0.8
2.8
1.9
1.0
3.2
3.0
1.2
2.3
60ppb
1.0
1.7
1.1
2.1
0.8
2.7
1.9
0.9
3.2
2.9
1.1
2.1
Change in O,-Attributable Risk
Base-75
12
5
2
0
1
0
-7
-17
5
5
3
6
75-70
4
3
2
3
2
3
1
3
5
3
2
4
75-65
8
6
5
7
5
6
2
7
22
6
3
9
75-60
12
10
9
14
9
10
3
13
NA
9
6
14
Study Area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
NewYork, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Air Quality Scenario
Ozone-Attributable Deaths per 100,000 Change in Ozone-Attributable Deaths per 100,000
Base
5.17
8.76
4.82
12.57
2.43
11.57
10.41
5.18
18.72
16.64
8.13
13.76
75ppb
4.66
8.20
4.69
12.57
2.40
11.57
11.07
6.12
17.47
15.36
7.91
12.86
70ppb
4.48
8.02
4.69
12.28
2.34
11.05
11.07
5.65
16.85
15.36
7.70
12.26
65ppb
4.31
7.83
4.42
11.70
2.29
10.70
10.90
5.65
13.73
15.36
7.49
11.66
60ppb
3.97
7.46
4.28
10.82
2.20
10.35
10.74
5.18
13.73
14.08
7.27
11.06
Base-75
0.64
0.43
0.08
-0.01
0.02
0.05
-0.75
-0.85
0.94
0.82
0.24
0.84
75-70
0.21
0.24
0.10
0.41
0.05
0.40
0.08
0.20
0.81
0.45
0.14
0.54
75-65
0.36
0.50
0.27
0.94
0.12
0.74
0.18
0.41
3.99
0.97
0.28
1.17
75-60
0.59
0.84
0.43
1.87
0.21
1.21
0.39
0.75
NA
1.54
0.49
1.79
NA: for NYC, the model-based adjustment methodology was unable to estimate ozone distributions which would meet the lower
alternative standard level of 60 ppb.
7B-1
-------
Table 7B-2 Core Short-Term Ozone-Attributable Mortality (2009) (incidence, percent of
baseline mortality, incidence per 100,000) (Smith et al., 2009)
Study Area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
AirQuality Scenario
Absolute Ozone-Attributable Incidence
Base
250
(-340-820)
410
(-230-1000)
320
(-450-1100)
400
(-38-820)
83
(-270-420)
580
(28-1100)
640
(120-1200)
1100
(-470-2700)
2600
(1500-3600)
1100
(240-1900)
380
(-400-1100)
380
(-96-850)
75ppb
240
(-340-800)
400
(-220-1000)
320
(-450-1100)
400
(-38-830)
83
(-270-420)
580
(28-1100)
700
(130-1200)
1300
(-540-3100)
2600
(1600-3700)
1100
(240 - 2000)
370
(-390-1100)
380
(-96-840)
70ppb
230
(-320-770)
400
(-220-990)
320
(-450-1100)
390
(-37-800)
83
(-270-420)
600
(29-1200)
700
(130-1300)
1200
(-520-3000)
2600
(1500-3600)
1100
(240-1900)
360
(-380-1100)
370
(-94-830)
65ppb
230
(-310-750)
390
(-210-970)
310
(-450-1100)
370
(-36-770)
81
(-270-410)
590
(28 - 1100)
690
(130-1200)
1200
(-500-2900)
2200
(1300-3100)
1100
(230-1900)
360
(-380-1100)
360
(-91-800)
eoppb
220
(-300-730)
380
(-210-940)
310
(-430-1000)
350
(-34-730)
76
(-250-390)
560
(27-1100)
680
(130-1200)
1100
(-470-2700)
2200
(1300-3100)
1000
(230-1800)
350
(-370-1000)
350
(-87-770)
Change in Ozone-Attributable Incidence
Base-75
5
(-6-15)
6
(-3-15)
-2
(3 --8)
-5
(0--10)
0
(1--2)
NA
NA
-55
(-10 --99)
-160
(68- -400)
-77
(-46- -110)
-6
(-1--10)
10
(-11-31)
1
(0-3)
75-70
9
(-12-28)
7
(-4-19)
-1
(2 --4)
12
(-1-24)
0
(-1-2)
-21
(-1--41)
-1
(0--1)
41
(-17-100)
84
(50 - 120)
19
(4 - 34)
6
(-7-19)
8
(-2-18)
75-65
16
(-22-54)
17
(-10-44)
5
(-7-17)
29
(-3-60)
2
(-6-10)
-6
(0--12)
4
(1-7)
89
(-37-210)
440
(260-610)
44
(10-78)
12
(-13-38)
21
(-5-46)
75-60
23
(-32-77)
28
(-15-71)
14
(-19-47)
49
(-5-100)
7
(-23-37)
15
(1-30)
14
(3-26)
160
(-68-390)
NA
NA
69
(15-120)
21
(-22-64)
37
(-9-83)
Study Area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
AirQuality Scenario
Percent of Baseline Incidence Attributable to Ozone
Base
1.0
1.8
1.1
2.3
0.8
2.7
1.8
0.9
3.8
2.9
1.2
2.3
75ppb
1.0
1.8
1.1
2.3
0.8
2.7
1.9
1.1
3.9
3.0
1.2
2.3
70ppb
0.9
1.7
1.1
2.3
0.8
2.8
1.9
1.0
3.8
2.9
1.2
2.2
65ppb
0.9
1.7
1.1
2.2
0.8
2.7
1.9
1.0
3.3
2.8
1.2
2.1
eoppb
0.9
1.7
1.1
2.0
0.7
2.6
1.9
0.9
3.3
2.8
1.1
2.0
Change in O3-Attributable Risk
Base-75
2
1
-1
-1
0
0
-8
-15
-3
-1
3
0
75-70
3
2
0
3
0
-4
0
3
3
2
2
2
75-65
7
4
2
7
2
-1
0
7
16
4
3
5
75-60
9
7
4
12
8
3
2
13
NA
6
6
9
Study Area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
AirQuality Scenario
Ozone-Attributable Deaths per 100,000 Change n Ozone-Attributable Deaths per 100,000
Base
4.17
7.54
4.24
11.75
2.23
10.32
9.94
5.10
16.05
13.92
7.96
11.28
75ppb
4.01
7.36
4.24
11.75
2.23
10.32
10.87
6.02
16.05
13.92
7.76
11.28
70ppb
3.84
7.36
4.24
11.46
2.23
10.67
10.87
5.56
16.05
13.92
7.55
10.98
65ppb
3.84
7.17
4.10
10.87
2.18
10.50
10.72
5.56
13.58
13.92
7.55
10.68
eoppb
3.67
6.99
4.10
10.28
2.05
9.96
10.56
5.10
13.58
12.65
7.34
10.39
Base-75
0.08
0.11
-0.03
-0.14
-0.01
NA
-0.85
-0.74
-0.48
-0.07
0.21
0.04
75-70
0.14
0.14
-0.01
0.35
0.01
-0.37
-0.01
0.19
0.52
0.24
0.13
0.24
75-65
0.27
0.31
0.07
0.85
0.05
-0.11
0.06
0.41
2.72
0.56
0.25
0.62
75-60
0.38
0.51
0.19
1.44
0.19
0.27
0.22
0.74
NA
0.87
0.44
1.10
NA: for NYC, the model-based adjustment methodology was unable to estimate ozone distributions which would meet the lower
alternative standard level of 60 ppb.
7B-2
-------
Figure 7B-1 Core Short-Term Ozone-Attributable Mortality (2007) (heat map tables
absolute ozone-attributable incidence) (Smith et al., 2009)
Recent conditions
Study area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Daily Shr Max Ozone Level (ppb)
0-5
0
0
0
0
0
0
0
0
0
0
0
0
5-10
0
0
0
0
0
0
2
0
0
0
0
0
10-15
0
0
0
^~
0
1
8
6
0
2
0
1
15-20
2
2
1
0
0
23
23
41
7
4
2
20-25
3
7
9
0
7
48
55
81
21
17
3
25-30
5
19
17
23
0
29
69
63
147
53
23
11
30-35
13
18
47
45
3
40
87
115
295
85
38
21
35-40
16
48
42
48
5
61
83
97
478
94
56
42
40-45
20
39
62
73
7
96
72
159
284
159
44
60
45-50
29
55
38
55
9
121
57
140
389
131
47
41
50-55
41
58
30
53
13
63
60
135
266
151
46
72
55-60
57
56
31
40
18
39
33
131
199
158
44
59
60-65
35
35
25
37
17
51
30
59
193
94
23
40
65-70
36
65
18
25
8
25
32
33
231
126
17
31
70-75
24
38
10
10
4
37
31
26
178
116
12
28
>75
23
25
29
11
2
86
4
29
171
103
6
44
Total
304
465
358
431
87
657
638
1,070
2,953
1,299
378
457
Current Standard (75)
Alternative Standard 70
Alternative Standard 65
Alternative Standard 60
Study area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Daily Shr Max Ozone Level (ppb)
0-5
0
0
0
0
0
0
0
0
0
0
0
0
5-10
0
0
0
0
0
0
0
0
0
0
0
0
10-15
0
0
0
0
0
0
0
0
0
0
0
0
15-20
0
1
0
1
0
0
0
0
0
2
0
1
20-25
3
1
4
5
0
2
17
0
21
0
3
25-30
5
11
20
14
0
7
49
0
98
34
18
7
30-35
18
22
45
40
1
42
126
0
297
62
53
18
35-40
24
43
50
65
5
72
146
17
544
156
98
65
40-45
41
84
58
89
6
123
148
340
741
213
67
66
45-50
52
71
57
81
13
147
95
445
475
236
65
76
50-55
63
69
35
43
17
75
50
388
364
209
40
74
55-60
38
73
20
40
23
52
49
44
233
165
20
47
60-65
15
44
30
31
15
56
3
13
39
101
5
29
65-70
6
12
9
12
4
20
0
5
0
42
2
29
70-75
3
9
13
10
2
43
0
0
0
9
0
12
>75
0
3
11
0
0
17
0
0
0
10
0
~^~
Total
267
443
353
431
86
655
683
1,253
2,812
1,238
367
430
Study area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Daily Shr Max Ozone Level (ppb)
0-5
0
0
0
0
0
0
0
0
0
0
0
0
5-10
0
0
0
0
0
0
0
0
0
0
0
0
10-15
0
0
0
0
0
0
0
0
0
0
0
0
15-20
0
1
0
1
0
0
0
0
0
0
0
1
20-25
2
1
4
^Z
0
9
0
13
3
0
2
25-30
9
11
19
0
6
49
0
136
31
15
8
30-35
19
14
48
0
42
128
0
341
61
55
24
35-40
27
54
60
5
83
166
28
652
180
106
76
40-45
52
95
55
7
152
164
399
z»n
273
79
76
45-50
64
86
55
76
16
143
96
603
519
225
69
84
50-55
52
84
37
39
26
63
54
164
195
216
21
58
55-60
20
51
28
34
23
69
13
8
17
121
14
42
60-65
7
22
14
23
6
29
0
9
0
77
0
30
65-70
3
9
12
6
3
30
0
0
0
8
2
12
70-75
0
3
6
0
0
16
0
0
0
9
0
0
>75
0
0
7
0
0
0
0
0
0
0
0
0
Total
255
430
346
418
84
633
678
1,211
2,684
1,204
361
412
Study area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Daily Shr Max Ozone Level (ppb)
0-5
0
0
0
0
0
0
0
0
0
0
0
0
5-10
0
0
0
0
0
0
0
0
0
0
0
0
10-15
0
0
0
0
0
0
0
0
0
0
0
0
15-20
0
1
0
0
0
0
0
0
0
0
0
0
20-25
2
1
2
3
0
0
5
0
37
3
0
3
25-30
10
10
19
18
0
4
42
0
604
32
11
8
30-35
24
22
53
55
~~T~
42
141
0
618
61
65
36
35-40
28
65
63
92
3
94
183
105
920
194
114
77
40-45
65
99
65
104
10
183
176
519
13
308
93
85
45-50
66
85
54
67
20
121
81
479
0
266
50
93
50-55
37
83
37
36
31
71
45
48
0
201
17
47
55-60
9
37
20
18
14
47
0
12
0
85
4
35
60-65
4
11
11
6
3
37
0
4
0
8
2
8
65-70
0
3
6
0
0
15
0
0
0
8
0
0
70-75
0
0
3
0
0
0
0
0
0
0
0
0
>75
0
0
0
0
0
0
0
0
0
0
0
0
Total
246
417
333
400
82
615
672
1,167
2,193
1,165
355
393
Study area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Daily Shr Max Ozone Level (ppb)
0-5
0
0
0
0
0
0
0
0
0
0
0
5-10
0
0
0
0
0
0
0
0
0
0
0
10-15
0
0
0
0
0
0
0
0
0
0
0
15-20
0
1
0
0
0
0
0
0
0
0
0
20-25
2
1
1
4
0
0
0
0
3
0
3
25-30
13
10
21
24
0
2
33
0
28
9
10
30-35
25
23
68
82
1
49
160
12
82
74
56
35-40
49
87
51
106
3
134
40-45
64
108
93
112
13
176
227 179
375 | 439
NA
218
134
91
355
88
114
45-50
58
108
45
24
31
128
57
251
295
29
57
50-55
19
48
21
17
27
59
5
19
131
9
36
55-60
3
13
12
0
4
39
0
0
7
1
5
60-65
0
0
5
0
0
0
0
0
8
0
0
65-70
0
0
3
0
0
0
0
0
0
0
0
70-75
0
0
0
0
0
0
0
0
0
0
0
>75
0
0
0
0
0
0
0
0
0
0
0
Total
233
399
321
369
79
588
659
1,095
1,126
344
371
NA: for NYC, the model-based adjustment methodology was unable to estimate ozone distributions which would meet the lower
alternative standard level of 60 ppb.
7B-3
-------
Figure 7B-2 Core Short-Term Ozone-Attributable Mortality (2007) (heat map tables
change in absolute ozone-attributable incidence) (Smith et al., 2009)
Note: negative values are risk increases, positive values are risk reductions
Decrease recent conditions to 75
Study are a
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Daily Shr Max Ozone Level (ppb)
0-5
0
0
0
0
0
0
0
0
0
0
0
0
5-10
0
0
0
0
0
0
-2
0
0
0
0
0
10-15
0
0
0
0
0
-1
-7
-12
0
-1
0
-1
15-20
-1
0
0
-1
0
0
-13
-30
-16
-3
-2
0
20-25
0
-2
-1
-1
0
-2
-17
-46
-27
-4
-5
-1
25-30
0
-3
-1
-3
0
-5
-17
-37
-27
-12
-4
-1
30-35
0
-3
-1
-4
0
-5
-12
-43
-37
-12
-3
-1
35-40
0
-3
-1
-2
0
-5
-7
-24
-22
-7
-1
0
40-45
1
0
0
-1
0
-3
-1
-24
6
-1
2
2
45-50
2
3
0
2
0
1
3
-8
38
4
4
3
50-55
5
4
1
2
0
1
6
2
34
13
5
5
55-60
8
5
2
2
0
2
4
11
34
16
6
5
60-65
6
4
1
2
1
4
5
8
33
12
4
4
65-70
6
8
2
2
0
2
5
6
48
19
3
3
70-75
>75
5
4
3
1
0
11
1
7
43
20
1
6
Total
37
23
6
0
1
3
-46
-184
150
64
11
28
Change in risk
Inc.
-2
-12
-7
-15
-2
-24
-76
-225
-148
-46
-16
-5
Dec.
39
35
13
14
3
27
31
41
298
110
27
33
Decrease 75 to 70
Study are a
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Daily Shr Max Ozone Level (ppb)
0-5
0
0
0
0
0
0
0
0
0
0
0
0
5-10
0
0
0
0
0
0
0
0
0
0
0
0
10-15
0
0
0
0
0
0
0
0
0
0
0
0
15-20
0
0
0
0
0
0
0
0
0
0
0
0
20-25
0
0
0
0
0
0
-1
0
-1
0
0
0
25-30
0
0
0
0
0
0
-1
0
-2
-1
-1
0
30-35
0
0
0
0
0
-1
-2
0
0
0
-1
0
35-40
1
0
0
0
0
0
0
0
12
0
1
1
40-45
1
1
1
2
0
2
2
6
27
3
2
2
45-50
2
2
1
3
0
5
2
16
32
7
2
3
50-55
3
3
1
2
0
3
2
17
35
8
2
4
55-60
2
3
1
2
1
3
2
2
25
9
1
3
60-65
1
2
1
2
1
4
0
1
5
6
0
2
65-70
0
1
0
1
0
2
0
0
0
3
0
2
70-75
0
1
1
1
0
3
0
0
0
1
0
1
>75
0
0
1
0
0
1
0
0
0
1
0
0
Total
12
1 4
Change in risk
Inc.
0
-1
-1
-2
0
-2
-4
0
-11
-3
-1
0
Dec.
12
14
8
15
2
24
9
43
146
38
8
19
Decrease 75 to 65
Study are a
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Daily Shr Max Ozone Level (ppb)
0-5
0
0
0
0
0
0
0
0
0
0
0
0
5-10
0
0
0
0
0
0
0
0
0
0
0
0
10-15
0
0
0
0
0
0
0
0
0
0
0
0
15-20
0
0
0
0
0
0
0
0
0
0
0
0
20-25
0
0
0
0
0
0
-2
0
-1
0
0
0
25-30
0
0
-1
0
0
0
-3
0
2
-1
-1
0
30-35
1
0
0
0
0
-1
-3
0
24
-1
-1
0
35-40
1
0
1
2
0
1
0
0
85
0
2
3
40-45
3
9
45-50
4
4
3
7
0
8
5
33
136
15
4
7
50-55
6
5
3
5
1
6
4
35
136
17
3
8
55-60
0
8
60-65
2
5
3
4
1
7
0
1
19
12
0
4
65-70
1
1
1
2
0
3
0
1
0
6
0
4
70-75
1
1
2
2
0
6
0
0
0
1
0
2
>75
0
0
2
0
0
3
0
0
0
2
0
1
Total
21
27
20
32
4
42
11
87
640
76
13
39
Change in risk
Inc.
0
-2
-2
-3
-1
-3
-9
0
-6
-5
-3
-1
Dec.
22
28
22
34
5
45
20
87
646
81
15
39
Decrease 75 to 60
Study are a
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Daily Shr Max Ozone Level (ppb)
0-5
0
0
0
0
0
0
0
0
5-10
0
0
0
0
0
0
0
0
10-15
0
0
0
0
0
0
0
0
15-20
0
0
0
0
0
0
0
0
20-25
0
0
0
-1
0
0
-3
0
25-30
0
0
-1
0
0
0
-5
0
30-35
1
0
1
0
0
-1
-4
0
35-40
2
1
2
5
0
2
2
2
40-45
4
5
4
12
0
8
8
41
45-50
50-55
9
9
5
10
2
10
7
48
55-60
6
11
3
10
3
9
8
6
60-65
3
8
5
8
2
11
1
2
65-70
1
2
2
4
1
5
0
1
70-75
1
2
3
3
0
9
0
0
>75
0
1
2
0
0
4
0
0
Total
34
45
32
64
8
69
24
159
Change in risk
Inc.
0
-2
-2
-3
-1
-4
-13
0
Dec.
34
47
34
67
8
73
37
159
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
-2
-2
0
-1
-2
0
1
4
5
11
6
7
26
5
12
27
3
9
17
1
6
8
0
7
2
0
3
2
0
1
116
23
60
-7
-4
-1
123
27
61
NA: for NYC, the model-based adjustment methodology was unable to estimate ozone distributions which would meet the lower
alternative standard level of 60 ppb.
7B-4
-------
Figure 7B-3 Core Short-Term Ozone-Attributable Mortality (2009) (heat map tables
absolute ozone-attributable incidence) (Smith et al., 2009)
Recent conditions
Study area
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Houston, TX
Los Angeles, CA
New York, NY
Sacramento, CA
St. Louis, MO
Daily 8hr Max Ozone Level (ppb)
0
0
0
0
0
0
0
0
0
0
0
0
1
1
0
0
2
1
0
0
— —
6
4
4
2
1
6
0
20
19
SI
6
11
11
13
0
39
38
144
15
23
33
27
2
79
66
217
27
19
30-35
39
37
32
2
94
113
281
37
26
35-40
40
56
51
3
99
84
325
35
57
40-45
39
50
78
11
70
102
^^
49
45
45-50
56
54
56
16
65
182
320
49
69
50-55
79
43
56
20
62
167
323
43
75
55-60
65
10
39
19
~^T~
125
210
30
48
60-65
30
3
11
8
24
112
134
23
21
65-70
14
6
24
1
17
68
102
33
11
70-75
9
9
3
1
7
20
21
20
0
>75
0
3
0
0
8
18
0
6
0
Total
409
317
397
S3
642
1,122
2,569
377
384
Current Standard (75)
Alternative Standard 70
Alternative Standard 65
Alternative Standard 60
Study area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Daily 8hr Max Ozone Level (ppb)
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1
0
0
0
0
0
0
0
1
2
1
0
0
0
6
0
6
2
0
6
8
3
11
5
0
28
0
36
16
2
7
16
13
25
25
1
51
0
215
51
23
17
30-35
IS
41
45
46
2
122
2
427
159
64
29
35-40
33
71
57
68
4
123
17
356
126
69
54
40-45
49
64
50
75
9
114
281
632
219
73
52
45-50
44
92
53
81
17
90
328
469
175
56
77
50-55
29
64
48
57
22
~i4~
496
274
198
42
66
55-60
30
45
7
28
20
36
152
175
97
33
53
60-65
9
11
3
11
6
27
9
56
68
6
13
65-70
2
0
6
6
2
7
0
0
0
0
8
70-75
0
0
9
0
1
4
0
0
0
0
0
>75
0
0
3
0
0
4
0
0
0
0
0
Total
241
404
319
401
S3
695
1,285
2,645
1,112
367
383
Study area
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Daily 8hr Max Ozone Level (ppb)
0-5
0
0
0
0
0
0
0
0
0
0
0
5-10
0
0
0
0
0
0
0
0
0
0
0
10-15
0
0
0
0
0
0
0
0
0
0
0
15-20
0
1
0
0
0
3
0
0
0
0
4
20-25
3
2
2
0
12
24
0
37
17
1
9
25-30
14
30
25
0
13
45
0
177
45
15
14
30-35
39
39
56
2
42
124
2
478
147
76
34
35-40
77
65
76
4
73
145
40
532
172
80
63
40-45
83
60
86
10
104
116
331
739
206
79
72
45-50
89
57
79
17
175
113
502
379
243
47
72
50-55
72
43
49
30
84
81
308
224
172
50
64
55-60
20
5
8
16
64
25
61
0
84
13
31
60-65
0
0
8
3
9
12
0
0
7
0
10
65-70
0
9
0
1
19
3
0
0
0
0
0
70-75
0
9
0
0
5
4
0
0
0
0
0
>75
0
0
0
0
0
0
0
0
0
0
0
Total
397
320
390
S3
600
696
1,244
2,566
1,094
361
375
Study area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Daily 8hr Max Ozone Level (ppb)
0-5
0
0
0
0
0
0
0
0
0
0
0
0
5-10
0
0
0
0
0
0
0
0
0
0
0
0
10-15
0
0
0
0
0
0
0
0
0
0
0
0
15-20
1
0
0
0
0
0
0
0
0
0
0
1
20-25
9
1
1
1
0
11
11
0
38
15
0
12
25-30
13
12
30
24
0
10
44
0
462
42
14
12
30-35
33
43
47
SO
39
137
2
731
138
81
41
35-40
52
86
64
S3
87
164
91
942
232
98
76
40-45
63
108
70
91
142
137
402
50
261
76
86
45-50
25
75
57
70
174
127
532
0
232
42
64
50-55
28
57
25
16
66
48
161
0
115
41
56
55-60
1
5
2
8
8
33
14
8
0
34
3
14
60-65
0
0
8
0
1
18
6
0
0
0
0
0
65-70
0
0
9
0
0
5
3
0
0
0
0
0
70-75
0
0
0
0
0
0
0
0
0
0
0
0
>75
0
0
0
0
0
0
0
0
0
0
0
0
Total
225
387
314
373
81
586
692
1,197
2,224
1,070
355
362
Study area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Daily 8hr Max Ozone Level (ppb)
0-5
0
0
0
0
0
0
0
0
0
0
0
5-10
0
0
0
0
0
0
0
0
0
0
0
10-15
0
0
0
0
0
0
0
0
0
0
0
15-20
0
0
0
0
0
0
0
0
0
0
0
20-25
9
1
1
1
0
5
5
0
6
0
13
25-30
14
10
32
28
0
16
38
0
31
9
13
30-35
42
53
60
108
0
39
134
7
148
86
58
35-40
56
105
65
82
7
121
208
332
290
119
93
40-45
57
108
78
93
17
164
181
361
NA
298
71
79
45-50
30
73
45
34
43
156
92
404
191
55
71
50-55
10
27
9
7
7
46
20
18
82
6
19
55-60
0
0
7
0
0
13
3
0
0
0
0
60-65
0
0
8
0
0
4
0
0
0
0
0
65-70
0
0
0
0
0
0
0
0
0
0
0
70-75
0
0
0
0
0
0
0
0
0
0
0
>75
0
0
0
0
0
0
0
0
0
0
0
Total
218
376
306
353
76
565
681
1,123
1,046
347
346
NA: for NYC, the model-based adjustment methodology was unable to estimate ozone distributions which would meet the lower
alternative standard level of 60 ppb.
7B-5
-------
Figure 7B-4 Core Short-Term Ozone-Attributable Mortality (2009) (heat map tables
change in absolute ozone-attributable incidence) (Smith et al., 2009)
Note: negative values are risk increases, positive values are risk reductions
Decrease recent conditions to 75
Study are a
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
St. Louis, MO
Daily Shr Max Ozone Level (ppb)
0-5
0
0
0
0
0
0
0
0
0
0
0
5-10
0
0
0
0
0
0
-1
-4
0
0
0
10-15
0
-1
0
0
0
0
-5
-14
-2
-3
0
15-20
-1
-1
0
-3
0
0
-8
-25
-30
-5
0
20-25
0
-3
0
-3
0
0
-10
-32
-41
-8
0
25-30
-1
-4
-1
-4
0
0
-14
-38
-37
-12
-1
30-35
0
-4
-1
-3
0
0
-12
-43
-24
-9
0
35-40
0
-1
-1
-1
0
0
-9
-22
-16
-6
0
40-45
1
0
0
0
0
0
-3
-16
-3
2
0
45-50
1
3
0
1
0
0
-1
-13
9
4
1
50-55
2
6
0
3
0
0
1
2
21
7
1
55-60
1
5
0
2
0
0
2
8
17
12
1
60-65
1
3
0
1
0
0
1
12
14
7
0
65-70
1
2
0
2
0
0
1
11
12
4
0
70-75
0
1
0
0
0
0
1
4
3
1
0
>75
0
0
0
0
0
0
1
5
0
0
0
Total
4
6
-2
-5
0
0
-55
-165
-77
-6
1
Change in risk
Inc.
-3
-18
-3
-17
-1
0
-62
-208
-172
-49
-2
Dec.
7
24
1
12
0
0
8
43
95
43
3
Decrease 75 to 70
Study are a
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Daily Shr Max Ozone Level (ppb)
0-5
0
0
0
0
0
0
0
0
0
0
0
0
5-10
0
0
0
0
0
0
0
0
0
0
0
0
10-15
0
0
0
0
0
-1
0
0
0
0
0
0
15-20
0
0
0
0
0
-3
-1
0
-1
0
0
-1
20-25
0
0
-1
0
0
-2
-2
0
-3
-1
0
-1
25-30
0
0
-1
-1
0
-6
-3
0
-14
-2
-1
-1
30-35
0
-1
-1
0
0
-5
-3
0
-8
-2
-1
0
35-40
1
0
0
1
0
-5
-1
0
8
-1
1
1
40-45
2
1
0
2
0
-5
1
4
22
5
2
1
45-50
3
3
1
3
0
-2
2
11
31
5
2
3
50-55
2
2
1
3
0
0
3
20
22
8
2
3
55-60
2
2
0
2
1
2
2
6
19
5
2
3
60-65
1
1
0
1
0
2
2
0
6
4
0
1
65-70
0
0
0
0
0
0
0
0
0
0
0
1
70-75
0
0
0
0
0
2
0
0
0
0
0
0
>75
0
0
0
0
0
1
0
0
0
0
0
0
Total
8
7
-1
12
0
-21
-1
41
84
19
6
8
Change in risk
Inc.
-2
-2
-6
-2
-1
-29
-10
0
-38
-9
-2
-4
Dec.
1 1
8
12
Decrease 75 to 65
Study are a
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Daily Shr Max Ozone Level (ppb)
0-5
0
0
0
0
0
0
0
0
0
0
0
0
5-10
0
0
0
0
0
0
0
0
0
0
0
0
10-15
0
0
0
0
0
-1
0
0
0
0
0
-1
15-20
0
0
0
0
0
-2
0
-1
-1
0
-2
20-25
-1
0
-1
-1
0
-4
0
-5
-2
0
-1
25-30
-1
-1
-1
-1
0
-5
0
~TT~
-4
-2
-1
30-35
0
-1
-1
0
0
-5
0
16
-4
-1
0
35-40
1
0
0
4
0
-1
0
52
-1
2
2
40-45
3
3
1
5
0
2
10
10
3
3
45-50
5
6
2
8
0
3
4
120
11
4
6
50-55
3
5
3
7
1
6
81
17
3
6
55-60
3
0
60-65
2
1
0
2
1
5
3
21
8
1
2
65-70
0
0
0
1
0
0
1
0
0
0
0
1
70-75
0
0
1
0
0
3
1
0
0
0
0
0
>75
0
0
0
0
0
1
1
0
0
0
0
0
Total
16
89
437
44
12
21
Change in risk
Inc.
-3
-3
-6
-3
-1
-27
-18
0
-43
-15
-4
-5
Dec.
19
21
11
32
3
21
21
89
479
59
16
26
Decrease 75 to 60
Study are a
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Daily Shr Max Ozone Level (ppb)
0-5
0
0
0
0
0
0
0
0
5-10
0
0
0
0
0
0
0
0
10-15
-1
0
0
0
0
-1
0
0
15-20
0
0
0
0
0
-4
-2
0
20-25
-1
-1
-2
-1
0
-2
-7
0
25-30
-1
-1
-1
-1
0
-7
0
30-35
0
-1
-1
1
0
-7
0
35-40
2
1
2
7
0
-2
0
2
40-45
5
5
2
9
0
2
5
32
45-50
6
10
5
13
1
10
8
44
50-55
5
8
5
11
2
4
11
63
55-60
5
6
1
6
3
8
6
22
60-65
2
2
1
2
1
8
5
1
65-70
0
0
1
1
0
0
1
0
70-75
0
0
2
0
0
4
1
0
>75
0
0
1
0
0
2
1
0
Total
23
28
14
49
7
15
14
164
Change in risk
Inc.
-3
-4
-6
-3
-1
-26
-25
0
Dec.
26
32
20
53
8
41
40
164
NA
0
0
0
0
0
0
0
0
-1
-1
0
-2
-3
-1
-1
-6
-3
-2
-4
-1
0
0
3
3
16
6
5
17
6
10
25
5
9
14
5
9
11
1
3
0
0
2
0
0
0
0
0
0
69
21
37
-20
-6
-6
88
27
43
NA: for NYC, the model-based adjustment methodology was unable to estimate ozone distributions which would meet the lower
alternative standard level of 60 ppb.
7B-6
-------
Table 7B-3 Core Short-Term Ozone-Attributable Morbidity - Hospital Admissions (2007
and 2009)
Endpoint/Study Area/Descriptor
Ai r Qual ity See nario
Absolute Ozone-Attributable Incidence
Base
75ppb
70ppb
65ppb
eoppb
Change in Ozone-Attributable Incidence
Base-75
75-70
75-65
75-60
2007 Simulation Year
HA (respiratory); Detroit (Katsouyanni etal., 2009)
Ihr max, penalized splines
Ihr max, natural splines
250
240
230
230
220
210
210
200
200
190
18
17
13
12
23
22
37
36
HA (respiratory); NYC (Silverman and Ito, 2010; Lin etal., 2008)
HA Chronic Lung Disease (Lin)
HA Asthma (Silverman)
HA Asthma, PM2.5 (Silverman)
130
450
340
120
420
310
120
400
290
95
330
240
95
330
240
12
50
36
6.7
28
20
29
120
84
29
120
84
HA (respiratory); LA (Linn etal., 2000)
Ihr max penalized splines
610
790
770
750
730
-180
19
38
60
HA (COPD less asthma); all 12 study areas (Medina-Ramon, etal., 2006)
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
79
83
100
62
27
91
65
190
190
140
39
57
67
77
100
61
27
90
68
180
180
130
34
53
64
74
99
58
26
87
67
180
170
130
33
50
61
71
95
56
25
85
66
170
130
120
32
48
57
67
92
50
24
81
64
160
130
120
30
45
12
7
3
1
1
1
-2
3
19
12
5
5
4
3
2
2
1
3
1
8
11
4
1
3
6
6
6
5
2
6
2
16
50
10
2
5
10
9
10
10
3
9
4
25
NA
15
4
8
2009 Simulation Year
HA (respiratory); Detroit (Katsouyanni etal., 2009)
Ihr max, penalized splines
Ihr max, natural splines
220
210
220
210
210
210
200
200
190
190
0
0
3.6
3.4
13
12
25
24
HA (respiratory); NYC (Silverman and Ito, 2010; Lin etal., 2008)
HA Chronic Lung Disease (Lin)
HA Asthma (Silverman)
HA Asthma, PM2.5 (Silverman)
120
410
310
120
410
300
110
390
290
97
340
250
97
340
250
0.045
8.1
5.8
5.1
24
17
21
96
68
21
96
68
HA (respiratory); LA (Linn etal., 2000)
Ihr max penalized splines
640
830
820
800
770
-190
18
39
62
HA (COPD less asthma); all 12 study areas (Medina-Ramon, etal., 2006)
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
65
74
92
58
27
81
71
200
170
120
41
51
64
71
92
58
27
81
74
190
170
120
36
50
61
69
92
56
26
85
74
190
160
120
35
49
58
67
91
53
25
83
73
180
140
110
34
47
56
65
89
50
24
80
71
170
140
110
32
44
2
3
-1
0
0
0
-4
5
0
2
5
0
3
2
0
2
0
-3
1
8
7
2
1
2
5
4
1
5
1
-2
2
16
35
6
3
4
8
6
4
8
3
1
4
26
NA
9
4
6
NA: for NYC, the model-based adjustment methodology was unable to estimate ozone distributions which would meet the lower
alternative standard level of 60 ppb.
7B-7
-------
Table 7B-4 Core Short-Term Ozone-Attributable Morbidity - Emergency Room Visits
(2007 and 2009)
Endpoint/Study Area/Descriptor
Air Quality Scenario
Absolute Ozone-Attributable Incidence
Base
75ppb
70ppb
esppb
eoppb
Change in Ozone-Attributable Incidence
Base-75
75-70
75-65
75-60
2007 Simulation Year
ER Visits (repiratory); Atlanta (Strickland etal., 2007)
Distributed lagO-7 days
Average day lag 0-2
8,500
5,100
7,500
4,500
7,200
4,200
6,900
4,100
6,600
3,900
1,300
750
410
230
740
420
1,200
670
ER-visits (respiratory); Atlanta (Tolbert et al., 2007, Darrowetal., 2011)
Tolbert
Tolbert-CO
Tolbert-N02
Tolbert-PMlO
Tolbert-PMlO, N02
Darrow
9,200
8,200
7,400
5,800
5,600
5,000
8,100
7,200
6,500
5,100
4,900
4,400
7,800
6,900
6,300
4,900
4,700
4,200
7,500
6,700
6,000
4,700
4,600
4,000
7,100
6,300
5,700
4,500
4,300
3,800
1,100
1,000
920
720
690
610
360
320
290
230
220
190
670
590
530
420
400
360
1,100
940
840
660
640
560
ER-visits (asthma); NYC (Ito et al, 2007)
single pollutant model
PM2.5
N02
CO
S02
9,600
7,600
6,300
10,000
7,800
9,000
7,100
5,800
9,500
7,300
8,600
6,700
5,600
9,100
6,900
7,100
5,500
4,500
7,500
5,700
NA
780
610
500
830
630
530
410
330
570
420
2,300
1,800
1,500
2,500
1,900
NA
2009 Simulation Year
ER Visits (repiratory); Atlanta (Strickland etal., 2007)
Distributed Iag0-7days
Average day lag 0-2
6,900
4,100
6,800
4,000
6,600
3,900
6,400
3,700
6,200
3,600
170
98
310
170
570
320
800
460
ER-visits (respiratory); Atlanta (Tolbert et al., 2007, Darrow etal., 2011)
Tolbert (single pollutant
Tolbert-CO
Tolbert-N02
Tolbert-PMlO
Tolbert-PMlO, N02
Darrow (single pollutant
7,500
6,700
6,100
4,800
4,600
4,100
7,400
6,600
6,000
4,700
4,500
4,000
7,200
6,400
5,800
4,500
4,400
3,900
6,900
6,200
5,600
4,400
4,200
3,700
6,700
6,000
5,400
4,200
4,100
3,600
140
120
110
88
85
75
270
240
210
170
160
140
500
450
400
310
300
270
720
640
580
450
430
380
ER-visits (asthma); NYC (Ito et al, 2007)
single pollutant model
PM2.5
N02
CO
S02
8,700
6,800
5,600
9,200
7,000
8,800
6,900
5,700
9,300
7,100
8,500
6,600
5,500
9,000
6,800
7,300
5,700
4,700
7,700
5,900
NA
-72
-53
-42
-77
-55
400
310
250
430
320
1,800
1,400
1,100
1,900
1,400
NA
NA: for NYC, the model-based adjustment methodology was unable to estimate ozone distributions which would meet the lower
alternative standard level of 60 ppb.
7B-8
-------
Table 7B-5 Core Short-Term Ozone-Attributable Morbidity - Asthma Exacerbations
(2007 and 2009)
Endpoint/Study Area/Descriptor
Air Quality Scenario
Absolute Ozone-Attributable Incidence
Base
75ppb
70ppb
65ppb
eoppb
Change in Ozone-Attributable Incidence
Base-75
75-70
75-65
75-60
2007 Simulation Year
Asthma exacerbation (wheeze); Boston (Gent et al., 2003, 2004)
Chest Tightness
Shortness of Breath
Chest Tightness (Ihr max)
Shortness of Breath (Ihr max)
Chest Tightness (PM2.5)
Chest Tightness (PM2.5)
Wheeze (PM2.5)
70,000
50,000
51,000
59,000
71,000
66,000
130,000
69,000
49,000
51,000
59,000
69,000
64,000
130,000
67,000
48,000
50,000
58,000
68,000
63,000
130,000
65,000
46,000
48,000
56,000
66,000
60,000
120,000
63,000
44,000
47,000
54,000
63,000
58,000
120,000
2,500
1,600
900
1,000
2,500
2,300
4,500
2,100
1,400
1,200
1,300
2,100
1,900
3,800
5,600
3,700
3,200
3,600
5,600
5,100
10,000
8,600
5,700
5,000
5,800
8,700
8,000
16,000
2009 Simulation Year
Asthma exacerbation (wheeze); Boston (Gent et al., 2003, 2004)
Chest Tightness
Shortness of Breath
Chest Tightness (Ihr max)
Shortness of Breath (Ihr max)
Chest Tightness (PM2.5)
Chest Tightness (PM2.5)
Wheeze (PM2.5)
63,000
45,000
46,000
54,000
64,000
59,000
120,000
63,000
45,000
47,000
54,000
64,000
59,000
120,000
63,000
44,000
47,000
54,000
64,000
59,000
120,000
62,000
43,000
46,000
53,000
63,000
58,000
120,000
60,000
42,000
45,000
52,000
61,000
56,000
110,000
-150
-100
-360
-420
-160
-140
-280
490
330
-180
-210
500
450
900
2,400
1,600
790
910
2,400
2,200
4,300
4,800
3,200
2,200
2,500
4,800
4,400
8,700
7B-9
-------
Table 7B-6 Core Long-Term Ozone-Attributable Respiratory Mortality (2007) (incidence,
percent of baseline mortality, incidence per 100,000) (Jerrett et al., 2009)
Study Area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
AirQuality Scenario
Absolute Ozone-Attributable Incidence
Base
840
(300-1300)
820
(300-1300)
1,200
(410-1800)
540
(190-850)
500
(180-770)
790
(280-1200)
560
(200-880)
2,600
(960-4100)
2,100
(750-3200)
1,400
(500-2100)
790
(290-1200)
640
(230-1000)
75ppb
710
(260-1100)
750
(270-1200)
1,100
(400-1800)
530
(190-820)
480
(170-740)
760
(270-1200)
550
(190-860)
2,600
(930-4000)
1,800
(660-2900)
1,300
(450-1900)
680
(250-1100)
600
(210-930)
70ppb
680
(240-1100)
720
(260-1100)
1,100
(390-1700)
500
(180-790)
470
(170-720)
730
(260-1100)
540
(190-850)
2,500
(890-3800)
1,700
(620-2700)
1,200
(430-1900)
660
(240-1000)
570
(200-890)
65ppb
650
(230-1000)
700
(250-1100)
1,000
(370-1600)
480
(170-750)
450
(160-700)
710
(250-1100)
530
(190-830)
2,400
(850-3700)
1,400
(500-2200)
1,200
(410-1800)
630
(230-1000)
540
(190-840)
eoppb
610
(220-960)
660
(240-1000)
1,000
(350-1600)
440
(160-690)
430
(150-670)
680
(240-1100)
520
(180-820)
2,200
(800-3500)
1,400
(500-2200)
1,100
(390-1700)
600
(210-940)
510
(180-800)
Change in Ozone-Attributable Incidence
Base-75
150
(51-250)
78
(27-130)
41
(14-69)
21
(7-34)
23
(8-39)
30
(10-50)
22
(7-36)
95
(32-160)
280
(96-470)
170
(57-270)
130
(44-210)
60
(20-99)
75-70
43
(15-71)
33
(11-55)
35
(12-58)
26
(9-43)
19
(6-31)
35
(12-59)
9.5
(3-16)
140
(46-230)
120
(41-200)
56
(19-93)
31
(10-51)
34
(230-1000)
75-65
78
(26-130)
67
(23-110)
93
(32-150)
56
(19-93)
39
(13-64)
63
(21-100)
19
(6-31)
260
(89-430)
480
(160-790)
120
(40-190)
60
(20-98)
69
(23-110)
75-60
120
(41-200)
110
(37-180)
140
(49-240)
100
(35 - 170)
64
(22-100)
99
(33 - 160)
32
(11-53)
410
(140-670)
NA
NA
170
(59-290)
100
(34-170)
100
(35-170)
Study Area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
AirQuality Scenario
Percent of Baseline Incidence Attributable to Ozone
Base
21.7
20.3
17.7
18.2
21.5
19.0
16.8
21.0
19.0
20.3
20.4
20.2
75ppb
18.6
18.7
17.2
17.6
20.8
18.4
16.3
20.4
16.9
18.4
17.7
18.7
70ppb
17.7
18.1
16.7
16.9
20.1
17.7
16.1
19.6
15.9
17.7
17.1
17.9
65ppb
16.9
17.4
16.0
16.1
19.4
17.1
15.8
18.7
13.0
16.9
16.5
16.9
eoppb
15.9
16.5
15.3
14.7
18.5
16.4
15.5
17.8
13.0
16.2
15.6
16.0
Change in O3-Attributable Risk
Base-75
14
8
3
3
4
3
3
3
11
10
13
7
75-70
5
4
3
4
3
4
1
4
6
4
4
5
75-65
9
8
7
9
7
7
3
9
24
8
7
10
75-60
15
12
11
17
11
11
5
13
NA
12
13
15
Study Area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
AirQuality Scenario
Ozone-Attributable Deaths per 100,000 Change in Ozone-Attributable Deaths per 100,000
Base
25.47
25.52
25.33
25.77
24.29
23.24
16.80
22.58
21.41
29.87
29.29
32.23
75ppb
21.75
23.53
24.58
24.96
23.39
22.51
16.26
21.94
18.98
26.95
25.39
29.80
70ppb
20.67
22.68
23.94
23.94
22.66
21.65
16.02
21.01
17.92
25.96
24.44
28.41
65ppb
19.78
21.81
22.86
22.72
21.86
20.97
15.80
20.12
14.65
24.85
23.55
26.94
eoppb
18.66
20.68
21.90
20.83
20.87
20.08
15.46
19.11
14.65
23.81
22.23
25.43
Base-75
4.58
2.46
0.91
0.98
1.14
0.90
0.64
0.81
2.92
3.59
4.75
3.01
75-70
1.31
1.04
0.77
1.23
0.91
1.05
0.28
1.16
1.26
1.21
1.15
1.69
75-65
2.38
2.09
2.05
2.67
1.90
1.86
0.55
2.25
4.98
2.54
2.21
3.45
75-60
3.69
3.42
3.17
4.85
3.10
2.92
0.94
3.46
NA
3.76
3.75
5.21
NA: for NYC, the model-based adjustment methodology was unable to estimate ozone distributions which would meet the lower
alternative standard level of 60 ppb.
7B-10
-------
Table 7B-7 Core Long-Term Ozone-Attributable Respiratory Mortality (2009) (incidence,
percent of baseline mortality, incidence per 100,000) (Jerrett et al., 2009)
Study Area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Air Quality Scenario
Absolute Ozone-Attributable Incidence
Base
730
(260-1100)
770
(280-1200)
1,100
(380 - 1700)
520
(190-820)
500
(180-770)
720
(260-1100)
600
(220-940)
2,800
(1000-4400)
1,900
(690 - 3000)
1,300
(450 - 2000)
850
(310-1300)
580
(210-910)
75ppb
700
(250-1100)
730
(260-1100)
1,100
(380 - 1700)
510
(180-800)
490
(180-770)
720
(260-1100)
610
(220-950)
2,800
(1000-4300)
1,900
(670 - 2900)
1,200
(430 - 1900)
730
(260-1100)
580
(210-900)
70ppb
670
(240-1000)
710
(250-1100)
1,100
(380 - 1700)
490
(170-770)
490
(180-750)
730
(260-1100)
600
(210-930)
2,600
(960 - 4100)
1,800
(630 - 2800)
1,200
(420 - 1800)
700
(250-1100)
560
(200-870)
65ppb
640
(230-1000)
680
(240-1100)
1,000
(370-1600)
470
(170-730)
470
(170-730)
710
(250-1100)
580
(210-910)
2,500
(910-3900)
1,500
(540-2400)
1,100
(400-1800)
680
(240-1100)
530
(190-840)
eoppb
610
(220-970)
660
(230-1000)
1,000
(350-1600)
440
(160-690)
440
(160-680)
680
(240-1100)
560
(200-890)
2,400
(860-3700)
1,500
(540-2400)
1,100
(390-1700)
640
(230-1000)
510
(180-800)
Change in Ozone-Attributable Incidence
Base-75
33
(11-55)
50
(17-83)
-2.1
(-1--4)
16
(5-26)
0.77
(0-1)
NA
NA
-4.9
(-2 --8)
110
(37 - 180)
57
(19-94)
56
(19-93)
150
(50 - 240)
7.3
(3-12)
75-70
41
(14-68)
25
(8-41)
6.8
(2-11)
24
(8-41)
9.0
(3-15)
-8.9
(-3 --15)
14
(5-23)
130
(45 - 220)
110
(37 - 180)
44
(15-73)
34
(12-57)
24
(210-910)
75-65
76
(26-120)
54
(18-90)
42
(14-69)
54
(18-89)
28
(10-47)
18
(6-30)
30
(10-49)
280
(94 - 460)
390
(130-630)
94
(32-160)
66
(22-110)
53
(18-87)
75-60
100
(36 - 170)
84
(28-140)
85
(29-140)
84
(29-140)
70
(24-120)
51
(17-85)
49
(17-82)
430
(150-710)
NA
NA
140
(47 - 230)
110
(36 - 170)
86
(29-140)
Study Area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Air Quality Scenario
Percent of Baseline Incidence Attributable to Ozone
Base
17.6
18.4
15.9
17.2
20.0
17.0
16.8
21.4
17.1
17.8
20.9
17.9
75ppb
17.0
17.4
15.9
16.8
20.0
17.0
16.9
20.7
16.7
17.2
18.0
17.7
70ppb
16.1
16.9
15.9
16.1
19.7
17.1
16.6
19.9
15.9
16.7
17.3
17.1
65ppb
15.4
16.3
15.4
15.3
19.1
16.6
16.2
19.0
13.7
16.1
16.6
16.4
eoppb
14.8
15.7
14.9
14.4
17.7
16.0
15.8
18.1
13.7
15.5
15.8
15.5
Change in O3-Attributable Risk
Base-75
4
5
0
2
0
NA
-1
3
2
4
14
1
75-70
5
3
1
4
1
-1
2
4
5
3
4
4
75-65
9
6
3
9
5
2
4
8
18
7
8
8
75-60
13
10
7
15
12
6
7
13
NA
10
12
13
Study Area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Air Quality Scenario
Ozone-Attributable Deaths per 100,000 Change in Ozone-Attributable Deaths per 100,000
Base
21.33
23.68
23.02
24.89
23.17
21.39
17.07
23.62
19.57
26.50
30.74
28.78
75ppb
20.53
22.40
23.06
24.26
23.14
21.39
17.18
22.89
19.09
25.51
26.44
28.49
70ppb
19.53
21.77
22.93
23.29
22.81
21.61
16.86
22.00
18.15
24.74
25.42
27.49
65ppb
18.66
21.01
22.30
22.10
22.08
20.95
16.48
21.03
15.71
23.84
24.46
26.32
eoppb
17.92
20.23
21.49
20.85
20.44
20.12
16.01
19.97
15.71
23.05
23.24
24.91
Base-75
0.97
1.55
-0.04
0.76
0.04
NA
-0.14
0.92
0.58
1.19
5.26
0.36
75-70
1.20
0.76
0.15
1.16
0.42
-0.26
0.39
1.11
1.11
0.94
1.24
1.20
75-65
2.21
1.67
0.90
2.56
1.32
0.54
0.84
2.31
3.92
1.99
2.37
2.60
75-60
3.07
2.58
1.84
4.00
3.30
1.52
1.40
3.58
NA
2.93
3.81
4.24
NA: for NYC, the model-based adjustment methodology was unable to estimate ozone distributions which would meet the lower
alternative standard level of 60 ppb.
7B-11
-------
Appendix 7-C - Detailed Sensitivity Analysis Results
Table 7C-1 Sensitivity Analysis - STMortality: Smaller Smith et al, 2009-based study area
(2009) (incidence, percent of baseline mortality, incidence per 100,000) - compare with
Core Results in Table 7B-2
Study Area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
AirQuality Scenar o
Absolute Ozone- Attributable Incidence
Base
170
(-240-560)
190
(-100-470)
160
(-220-520)
340
(-33-710)
73
(-240-370)
530
(26-1000)
510
(96-920)
850
(-360-2000)
1800
(1100-2600)
720
(160-1300)
370
(-390-1100)
250
(-62-550)
75ppb
170
(-240-570)
200
(-110-500)
160
(-230-530)
360
(-34 - 740)
74
(-240-380)
530
(26-1000)
570
(110-1000)
990
(-420 - 2400)
2100
(1300-2900)
770
(170-1400)
360
(-390-1100)
250
(-64-560)
70ppb
170
(-230-560)
200
(-110-500)
170
(-240 - 560)
350
(-34-730)
75
(-240-380)
550
(27-1100)
570
(110-1000)
960
(-400 - 2300)
2100
(1300-2900)
770
(170-1400)
360
(-380-1100)
270
(-67-590)
65ppb
160
(-230-550)
200
(-110-490)
170
(-240-550)
340
(-32-700)
74
(-240-380)
540
(26-1000)
570
(110-1000)
920
(-380-2200)
1900
(1100-2600)
760
(170-1300)
350
(-370-1100)
270
(-68-600)
eoppb
160
(-220-530)
190
(-110-480)
160
(-230-550)
320
(-31 - 670)
70
(-230-360)
530
(26-1000)
560
(100-1000)
860
(-360 - 2100)
1900
(1100-2600)
750
(170-1300)
340
(-360-1000)
270
(-67-590)
Change in Ozone-Attributable Incidence
Base-75
-2
(2 --6)
-11
(6 --29)
-4
(5 --13)
-17
(2 --35)
-1
(3 --4)
NA
NA
-54
(-10 --98)
-140
(57- -330)
-260
(-160- -370)
-53
(-11 --94)
3
(-3-8)
-6
(1--13)
75-70
2
(-3-7)
2
(-1-4)
-7
(10 --25)
8
(-1-16)
-1
(3 --5)
-28
(-1--54)
-3
(-1--5)
34
(-14-82)
7
(4-10)
2
(0-4)
6
(-6-18)
-15
(4 --33)
75-65
6
(-9-21)
5
(-2-11)
-6
(9 --22)
20
(-2-42)
0
(0--1)
-17
(-1--33)
-1
(0--2)
73
(-30-180)
210
(130-300)
9
(2-16)
12
(-12-36)
-18
(5 --41)
75-60
11
(-15-35)
8
(-4-20)
-4
(6 --14)
37
(-4-77)
4
(-12-19)
0
(0-1)
5
(1-9)
130
(-55 - 320)
NA
NA
18
(4-32)
21
(-22 - 63)
-15
(4 --34)
Study Area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
AirQuality Scenar o
Percent of Baseline Incidence Attributable to Ozone
Base
1.0
1.7
1.1
2.2
0.8
2.6
1.8
0.9
3.7
2.6
1.2
2.1
75ppb
1.0
1.7
1.1
2.3
0.8
2.6
1.9
1.1
4.2
2.8
1.2
2.2
70ppb
1.0
1.7
1.1
2.3
0.8
2.8
1.9
1.0
4.1
2.8
1.2
2.3
65ppb
1.0
1.7
1.1
2.2
0.8
2.7
1.9
1.0
3.8
2.8
1.2
2.3
eoppb
1.0
1.7
1.1
2.1
0.8
2.6
1.9
0.9
3.8
2.8
1.2
2.3
Change in O3- Attributable Risk
Base-75
-1
-6
-2
-5
-1
NA
-10
-16
-14
-7
1
-2
75-70
1
1
-4
2
-1
-5
-1
3
0
0
2
-6
75-65
4
2
-4
5
0
-3
0
7
10
1
3
-7
75-60
6
4
-2
10
5
0
1
13
NA
2
6
-6
Study Area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
AirQuality Scenar o
Ozone-Attributable Deaths per 100,000 Change in Ozone-Attributable Deaths per 100,000
Base
3.81
9.73
4.43
12.20
2.67
12.11
8.84
5.18
13.60
15.20
8.52
13.48
75ppb
3.81
10.24
4.43
12.92
2.70
12.11
9.88
6.04
15.86
16.25
8.29
13.48
70ppb
3.81
10.24
4.71
12.56
2.74
12.56
9.88
5.85
15.86
16.25
8.29
14.55
65ppb
3.59
10.24
4.71
12.20
2.70
12.34
9.88
5.61
14.35
16.04
8.06
14.55
eoppb
3.59
9.73
4.43
11.48
2.56
12.11
9.71
5.24
14.35
15.83
7.83
14.55
Base-75
-0.04
-0.56
-0.11
-0.61
-0.03
NA
-0.94
-0.85
-1.96
-1.12
0.06
-0.32
75-70
0.05
0.08
-0.20
0.27
-0.04
-0.64
-0.05
0.21
0.05
0.04
0.14
-0.81
75-65
0.14
0.23
-0.18
0.72
0.00
-0.39
-0.02
0.45
1.59
0.19
0.28
-0.97
75-60
0.25
0.41
-0.11
1.33
0.13
0.01
0.08
0.79
NA
0.38
0.48
-0.81
NA: for NYC, the model-based adjustment methodology was unable to estimate ozone distributions which would meet the lower
alternative standard level of 60 ppb.
7C-1
-------
Table 7C-1 Sensitivity Analysis - STMortality: Smaller Smith et al, 2009-based study area
(2009) (heat maps for just meeting existing standard and risk reductions from just
meeting alternative standards) (see Key at bottom of figure)
Current Standard (75)
Study are a
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Daily Shr Max Ozone Level (ppb)
0-5
0
0
0
0
0
0
0
0
0
0
0
0
5-10
— —
0
0
0
0
0
0
0
0
0
0
0
10-15
0
0
0
0
0
2
i
0
0
0
0
2
15-20
2
0
0
0
0
10
6
0
9
3
0
3
20-25
5
2
4
5
0
13
22
0
22
20
4
7
25-30
11
8
13
24
17
37
0
170
70
21
13
30-35
15
25
24
38
49
93
2
231
87
58
25
35-40
18
31
28
65
68
104
9
280
137
73
31
40-45
21
35
27
58
9
106
95
189
318
106
59
37
45-50
29
40
29
72
13
116
69
224
450
123
57
54
50-55
22
32
15
44
19
51
68
378
267
122
31
35
55-60
19
18
6
36
16
39
34
168
186
71
36
28
60-65
14
7
5
15
6
26
20
20
86
22
16
11
65-70
7
2
3
3
2
19
11
0
77
0
6
2
70-75
3
0
2
0
0
0
0
6
2
4
>75
4
0
2
0
0
6
±
0
0
0
3
Total
170
200
160
360
74
526
567
989
2,096
769
364
254
Decrease 75 to 70
Study are a
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Daily Shr Max Ozone Level (ppb)
0-5
0
0
0
0
0
0
0
0
0
0
0
0
5-10
0
0
0
0
0
0
0
0
0
0
0
0
10-15
0
0
0
0
0
-1
0
0
0
0
0
-1
15-20
0
0
0
0
0
-3
-1
0
-2
-1
0
-1
20-25
0
0
-1
0
0
-4
-2
0
-3
-2
0
-1
25-30
-1
0
-1
-1
0
-3
-2
0
-20
-4
-1
-2
30-35
-1
-1
-1
-1
0
-6
-3
0
-14
-2
-1
-3
35-40
0
0
-2
0
0
-6
-1
0
-4
-1
1
-2
40-45
0
0
-1
1
0
-6
0
3
-1
1
1
-2
45-50
1
1
-1
3
0
-3
1
7
10
3
2
-2
50-55
1
1
0
2
0
0
2
16
13
3
1
-1
55-60
0
60-65
1
0
0
1
0
0
65-70
0
0
0
0
0
1
1
0
8
0
0
0
70-75
0
0
0
0
0
0
0
0
0
0
0
0
>75
0
0
0
0
0
0
0
0
0
0
0
0
Total
- 8
-
Change in risk
Inc.
-3
-2
-8
-3
-2
-32
-10
0
-59
-12
-3
-15
Dec.
5
4
0
10
1
4
7
34
66
14
9
0
Decrease 75 to 65
Study are a
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Daily Shr Max Ozone Level (ppb)
0-5
0
0
0
0
0
0
0
0
0
0
0
5-10
0
0
0
0
0
0
0
0
0
0
0
10-15
0
0
0
0
0
0
0
0
0
0
-2
15-20
-1
0
0
0
0
-2
0
-4
-1
0
-1
20-25
-1
0
-1
-1
0
-3
0
-5
-4
-1
-2
25-30
-1
-1
-2
-2
0
-4
0
-38
-8
-2
-3
30-35
-1
-1
-2
-1
0
-6
0
-15
-4
-1
-4
35-40
0
-1
-2
2
0
-2
0
12
-1
2
-3
40-45
1
1
-1
3
0
1
6
3
3
-3
45-50
2
2
-1
6
0
3
16
7
4
-1
50-55
2
2
0
5
0
4
33
8
2
0
55-60
2
1
0
5
1
3
16
54
6
3
1
60-65
2
1
0
2
0
2
2
27
2
2
0
65-70
1
0
0
0
0
1
0
28
0
1
0
70-75
0
0
0
0
0
0
0
0
1
0
0
>75
1
0
0
0
0
1
0
0
0
0
0
Total
6
4
-6
20
0
-1
73
214
9
12
-18
Change in risk
Inc.
-4
-4
-8
-4
-2
-18
0
-87
-21
-5
-20
Dec.
10
8
3 0
Decrease 75 to 60
Study are a
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Daily Shr Max Ozone Level (ppb)
0-5
0
0
0
0
0
0
0
0
0
0
0
5-10
0
0
0
0
0
0
0
0
0
0
-1
10-15
0
0
0
0
0
-2
0
0
0
0
-2
15-20
-1
0
0
0
0
-5
-2
0
-2
0
-2
20-25
-1
-1
-1
-1
0
-6
-5
0
-5
-1
-3
25-30
-1
-1
-2
-2
0
-4
-6
0
-11
-3
-4
30-35
-1
-2
-2
0
0
-6
-8
0
-5
-2
-5
35-40
0
-1
-2
4
0
-4
-2
1
0
3
-3
40-45
1
2
0
5
0
-1
3
22
5
4
-2
45-50
3
3
0
11
0
6
5
32
NA
10
6
0
50-55
3
3
1
8
1
5
8
49
12
4
1
55-60
3
2
1
8
2
5
5
25
10
6
2
60-65
65-70
1
0
0
1
0
3
2
0
0
1
0
70-75
1
0
0
0
0
1
1
0
1
0
1
>75
1
0
0
0
0
1
2
0
0
0
1
Total
11
8
-4
37
4
0
5
133
18
21
-15
Change in risk
Inc.
-4
-5
-8
-4
-2
-32
-26
0
-28
-7
-22
Dec.
15
13
4
41
6
33
31
133
46
28
6
NA: for NYC, the model-based adjustment methodology was unable to estimate ozone distributions which would meet the lower
alternative standard level of 60 ppb.
Key: For current standard (75) which is an absolute risk metric, color gradient ranges from blue (smallest ozone-
related mortality count) to red (highest ozone-related mortality count). For Decrease results, color gradient ranges
from red (increase in risk - negative cell values) to blue (reduction in risk - positive cell values).
7C-2
-------
Table 7C-2 Sensitivity Analysis - ST Mortality: Alternate method for simulating standards
(2009) (incidence, percent of baseline mortality, incidence per 100,000) - compare with
Core Results in Table 7B-2
Study Area
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
Air Quality Scenario
Absolute Ozone-Attributable Incidence
Base
83
(-270 - 420)
580
(28 - 1100)
640
(120-1200)
1100
(-470 - 2700)
2600
(1500-3600)
1100
(240 - 1900)
380
(-400 - 1100)
75ppb
84
(-280-430)
580
(28 - 1100)
680
(130-1200)
1200
(-480 - 2800)
2600
(1500-3600)
1100
(240 - 1900)
360
(-390 - 1100)
Study Area
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
70ppb
84
(-280 - 430)
590
(29 - 1100)
680
(130-1200)
1100
(-470 - 2700)
2600
(1500-3500)
1100
(240 - 1900)
360
(-380 - 1100)
65ppb
82
(-270 - 420)
580
(28 - 1100)
680
(130-1200)
1100
(-460 - 2600)
2300
(1400-3200)
1000
(230 - 1800)
350
(-370 - 1000)
eoppb
77
(-250 - 390)
550
(27-1100)
660
(120-1200)
1100
(-450-2600)
NA
NA
1000
(220 - 1800)
340
(-360-1000)
Change in Ozone-Attributable Incidence
Base-75
-1
(5 --8)
0
0
-37
(-7 - -67)
-31
(13 --76)
-2
(-1--3)
12
(3 - 22)
15
(-16-44)
75-70
0
(1--D
-12
(-1--23)
-2
(0--3)
25
(-10 - 60)
21
(12-29)
21
(5-38)
7
(-8-22)
75-65
2
(-5 - 8)
5
(0-9)
2
(0-3)
53
(-22 - 130)
250
(150-350)
47
(10-83)
14
(-14 - 42)
75-60
7
(-23-37)
30
(1-58)
20
(4 - 37)
80
(-33 - 190)
NA
NA
79
(17-140)
22
(-24-68)
Air Quality Scenario
Percent of Baseline Incidence Attributable to Ozone
Base
0.8
2.70
1.77
0.9
3.8
2.95
1.23
75ppb
0.8
2.70
1.87
0.9
3.8
2.91
1.19
70ppb
0.8
2.75
1.88
0.9
3.8
2.86
1.16
65ppb
0.8
2.68
1.87
0.9
3.5
2.80
1.14
eoppb
0.7
2.56
1.82
0.9
NA
2.71
1.11
Change in O3-Attributable Risk
Base-75
-2
0.00
-0.10
-3
0
0.03
0.05
75-70
0
-0.05
0.00
2
1
0.06
0.02
75-65
2
0.02
0.01
5
9
0.12
0.05
75-60
8
0.14
0.06
7
NA
0.21
0.07
Study Area
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
Air Quality Scenario
Ozone-Attributable Deaths per 100,000
Base
2.23
10.32
9.94
5.10
16.05
13.92
7.96
75ppb
2.26
10.32
10.56
5.56
16.05
13.92
7.55
70ppb
2.26
10.50
10.56
5.10
16.05
13.92
7.55
65ppb
2.21
10.32
10.56
5.10
14.20
12.65
7.34
eoppb
2.07
9.78
10.25
5.10
NA
12.65
7.13
Change in Ozone-Attributable Deaths per 100,000
Base-75
-0.04
NA
-0.57
-0.14
-0.01
0.15
0.31
75-70
0.00
-0.21
-0.03
0.12
0.13
0.27
0.15
75-65
0.04
0.08
0.03
0.25
1.54
0.59
0.29
75-60
0.19
0.53
0.31
0.37
NA
1.00
0.46
NA: for NYC, the model-based adjustment methodology was unable to estimate ozone distributions which would meet the lower
alternative standard level of 60 ppb.
7C-3
-------
Table 7C-3 Sensitivity Analysis - STMortality: Regional Bayes Adjustment (2009)
(incidence, percent of baseline mortality, incidence per 100,000) - compare with Core
Results in Table 7B-2)
Study Are a
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Air Quality Scenario
Absolute Ozone-Attributable Incidence
Base
260
(-210 - 730)
910
(380 - 1400)
980
(330-1600)
470
(110-830)
15
(-330 - 350)
640
(180-1100)
540
(84 - 1000)
1000
(-510 - 2500)
2800
(2000 - 3700)
1600
(860-2300)
130
(-670 - 920)
480
(90-860)
75ppb
260
(-210 - 710)
900
(370-1400)
990
(330-1600)
480
(120-840)
15
(-340 - 350)
640
(180-1100)
590
(91 - 1100)
1200
(-580-2900)
2900
(2000 - 3800)
1600
(870 - 2300)
130
(-650 - 890)
480
(90 - 850)
70ppb
250
(-200 - 690)
880
(360 - 1400)
990
(330 - 1600)
470
(110-810)
15
(-340 - 350)
670
(190-1100)
590
(91 - 1100)
1100
(-560-2800)
2800
(2000 - 3700)
1600
(850 - 2300)
130
(-640 - 880)
470
(88 - 840)
65ppb
240
(-190 - 670)
860
(350 - 1300)
980
(330 - 1600)
450
(110-780)
14
(-330 - 340)
650
(180-1100)
590
(90 - 1100)
1100
(-540 - 2700)
2500
(1700-3200)
1500
(840 - 2200)
130
(-630-860)
450
(85 - 810)
eoppb
240
(-190-650)
830
(340 - 1300)
950
(320 - 1600)
420
(100-740)
13
(-310-320)
630
(180-1100)
580
(89 - 1100)
1000
(-510 - 2500)
NA
NA
1500
(820 - 2200)
120
(-620-840)
430
(81 - 770)
Change in Ozone-Attributable ncidence
Base-75
5
(-4-13)
13
(5-20)
-7
(-2 --12)
-6
(-1--10)
0
(1--2)
NA
NA
-46
(-7 --85)
-150
(74 - -370)
-86
(-58- -110)
-8
(-4 --12)
4
(-18-25)
2
(0-3)
75-70
9
(-7-25)
17
(7-26)
-3
(-1--6)
14
(3-25)
0
(-1-1)
-24
(-7 --41)
-1
(0--1)
38
(-19 - 94)
93
(63 - 120)
27
(15-40)
2
(-11-15)
10
(2-19)
75-65
17
(-14 - 48)
39
(16-62)
16
(5-26)
35
(8-61)
0
(-8-9)
-7
(-2 --12)
3
(0-6)
81
(-40 - 200)
480
(330 - 640)
63
(34-92)
4
(-22-30)
26
(5-47)
75-60
25
(-19-69)
63
(26 - 100)
43
(14-72)
59
(14-100)
1
(-28-30)
17
(5-29)
12
(2-22)
150
(-74 - 370)
NA
NA
98
(53 - 140)
8
(-37-52)
46
(9-83)
Study Are a
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Air Quality Scenario
Percent of Baseline Incidence Attributable to Ozone
Base
1.1
4.0
3.4
2.7
0.1
3.0
1.5
0.8
4.2
4.2
0.4
2.8
75ppb
1.1
3.9
3.5
2.8
0.1
3.0
1.6
1.0
4.4
4.2
0.4
2.8
70ppb
1.0
3.9
3.5
2.7
0.1
3.1
1.6
0.9
4.2
4.2
0.4
2.8
65ppb
1.0
3.8
3.4
2.6
0.1
3.0
1.6
0.9
3.7
4.1
0.4
2.7
eoppb
1.0
3.7
3.3
2.4
0.1
2.9
1.6
0.8
NA
4.0
0.4
2.6
Change in Oj-Attributable Risk
Base-75
2
1
-1
-1
0
NA
-8
-15
-3
-1
2
0
75-70
3
2
0
3
0
-4
0
3
3
2
2
2
75-65
7
4
1
7
2
-1
0
7
16
4
3
5
75-60
9
7
4
12
7
3
2
13
NA
6
6
9
Study Are a
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Air Quality Scenario
Ozone-Attributable Deaths per 100,000
Base
4.34
16.74
12.97
13.81
0.40
11.39
8.39
4.63
17.28
20.24
2.72
14.24
75ppb
4.34
16.55
13.11
14.10
0.40
11.39
9.16
5.56
17.90
20.24
2.72
14.24
70ppb
4.17
16.18
13.11
13.81
0.40
11.92
9.16
5.10
17.28
20.24
2.72
13.95
65ppb
4.01
15.82
12.97
13.22
0.38
11.56
9.16
5.10
15.43
18.98
2.72
13.35
eoppb
4.01
15.26
12.58
12.34
0.35
11.21
9.01
4.63
NA
18.98
2.52
12.76
Chani
Base-75
0.08
0.24
-0.09
-0.17
0.00
NA
-0.71
-0.69
-0.53
-0.10
0.08
0.05
e in Ozone-Attributable Deaths per 100,000
75-70
0.15
0.31
-0.04
0.41
0.00
-0.43
-0.01
0.18
0.57
0.34
0.05
0.30
75-65
0.28
0.72
0.21
1.03
0.01
-0.12
0.05
0.38
2.96
0.80
0.09
0.77
75-60
0.42
1.16
0.57
1.73
0.03
0.30
0.19
0.69
NA
1.24
0.16
1.37
NA: for NYC, the model-based adjustment methodology was unable to estimate ozone distributions which would meet the lower
alternative standard level of 60 ppb.
7C-4
-------
Table 7C-4 Sensitivity Analysis - STMortality: Copollutant model (PMw) (2009) (incidence,
percent of baseline mortality, incidence per 100,000) - compare with Core Results in
Table 7B-2)
Study Area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Air Quality Scenario
Absolute Ozone-Attributable Incidence
Base
120
-1000 - 1200)
460
(-570 - 1400)
180
-1100 - 1400)
330
(-280 - 900)
-19
(-550 - 480)
260
(-470 - 960)
810
(-100 - 1700)
270
(-3300 - 3700)
1100
(-850 - 3000)
850
(-760 - 2400)
350
(-1000 - 1600)
260
(-570 - 1000)
75ppb
120
(-980 - 1200)
450
(-560-1400)
180
(-1100 - 1400)
330
(-280 - 920)
-19
(-550 - 490)
260
(-470 - 960)
880
(-110 - 1800)
310
(-3800 - 4300)
1200
(-880 - 3100)
850
(-760 - 2400)
340
(-980 - 1600)
260
(-570 - 1000)
70ppb
110
(-940 - 1100)
450
(-550 - 1400)
180
(-1100 - 1400)
320
(-270 - 890)
-19
(-550 - 480)
270
(-490 - 1000)
880
(-110 - 1800)
300
(-3700 - 4100)
1100
(-850 - 3000)
840
(-750 - 2300)
340
(-960 - 1600)
250
(-560 - 1000)
65ppb
110
(-910 - 1100)
440
(-540 - 1400)
180
(-1100 - 1400)
310
(-260 - 850)
-19
(-540 - 470)
260
(-480 - 980)
870
(-110 - 1800)
290
(-3500 - 4000)
980
(-730 - 2600)
820
(-730 - 2300)
330
(-950 - 1600)
240
(-540 - 990)
eoppb
110
(-880 - 1100)
420
(-520 - 1300)
170
-1100 - 1400)
290
(-250 - 810)
-18
(-510 - 450)
250
(-460 - 940)
860
(-110-1800)
270
(-3300 - 3700)
NA
NA
800
(-710 - 2200)
320
(-920 - 1500)
230
(-510 - 940)
Change in Ozone-Attributable Incidence
Base-75
2
(-18-22)
7
(-8-20)
-1
(8 --10)
-4
(3 --11)
0
(2 --2)
NA
NA
-69
(9- -150)
-39
(470 - -560)
-33
(25 --92)
-4
(4 --13)
10
(-28-45)
1
(-2-4)
75-70
4
(-34 - 42)
8
(-10-27)
-1
(4 --5)
10
(-8-27)
0
(-2-2)
-9
(17 --36)
-1
(0--2)
10
(-120 - 140)
36
(-27-99)
15
(-13-42)
6
(-16-28)
6
(-12-23)
75-65
8
(-64 - 78)
20
(-24-62)
3
(-18-23)
24
(-20 - 67)
0
(-13-12)
-3
(5 --10)
5
(-1-10)
21
(-260 - 300)
190
(-140 - 520)
34
(-29 - 96)
12
(-32-55)
14
(-30-57)
75-60
11
(-91-110)
32
(-39 - 100)
8
(-48-63)
40
(-34 - 110)
-2
(-46 - 42)
7
(-12-26)
18
(-2-38)
39
(-470 - 550)
NA
NA
52
(-46 - 150)
20
(-56-94)
25
(-54 - 100)
Study Area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Air Quality Scenario
Percent of Baseline Incidence Attributable to Ozone
Base
0.46
2.00
0.60
1.86
-0.23
1.19
2.22
0.21
1.68
2.23
1.12
1.48
75ppb
0.45
1.98
0.60
1.89
-0.23
1.19
2.41
0.24
1.73
2.25
1.10
1.48
70ppb
0.44
1.94
0.60
1.83
-0.23
1.24
2.41
0.23
1.67
2.21
1.08
1.45
65ppb
0.42
1.90
0.59
1.76
-0.22
1.21
2.40
0.22
1.45
2.16
1.06
1.40
eoppb
0.41
1.84
0.58
1.66
-0.21
1.16
2.36
0.21
NA
2.11
1.04
1.34
Change in O3-Attributable Risk
Base-75
0.01
0.03
0.00
-0.02
0.00
NA
-0.19
-0.03
-0.05
-0.01
0.03
0.01
75-70
0.02
0.04
0.00
0.06
0.00
-0.04
0.00
0.01
0.05
0.04
0.02
0.03
75-65
0.03
0.09
0.01
0.14
0.00
-0.01
0.01
0.02
0.28
0.09
0.04
0.08
75-60
0.04
0.14
0.03
0.23
-0.02
0.03
0.05
0.03
NA
0.14
0.06
0.14
Study Area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Air Quality Scenario
Ozone-Attributable Deaths per 100,000
Base
2.00
8.46
2.38
9.69
-0.51
4.63
12.58
1.25
6.79
10.75
7.34
7.72
75ppb
2.00
8.28
2.38
9.69
-0.51
4.63
13.67
1.44
7.41
10.75
7.13
7.72
70ppb
1.84
8.28
2.38
9.40
-0.51
4.80
13.67
1.39
6.79
10.63
7.13
7.42
65ppb
1.84
8.09
2.38
9.11
-0.51
4.63
13.51
1.34
6.05
10.37
6.92
7.12
eoppb
1.84
7.72
2.25
8.52
-0.48
4.45
13.36
1.25
NA
10.12
6.71
6.83
Change in Ozone-Attributable Deaths per 100,000
Base-75
0.04
0.12
-0.02
-0.12
0.00
NA
-1.07
-0.18
-0.20
-0.05
0.20
0.03
75-70
0.07
0.15
-0.01
0.28
0.00
-0.17
-0.01
0.05
0.22
0.19
0.12
0.16
75-65
0.13
0.37
0.04
0.70
-0.01
-0.05
0.07
0.10
1.17
0.43
0.25
0.42
75-60
0.18
0.59
0.10
1.17
-0.04
0.12
0.28
0.18
NA
0.66
0.42
0.74
NA: for NYC, the model-based adjustment methodology was unable to estimate ozone distributions which would meet the lower
alternative standard level of 60 ppb.
7C-5
-------
Table 7C-5 Sensitivity Analysis - STMortality: Alternate risk model (Zanobetti and
Schwartz, 2008) (2009) (incidence, percent of baseline mortality, incidence per 100,000)
- compare with Core Results in Table 7B-2)
Study Area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Air Quality Scenario
Absolute Ozone-Attributable Incidence
Base
140
(-130-400)
260
(-52-560)
380
(21-730)
190
(-33-410)
91
(-120-290)
470
(170-770)
61
(-130-250)
460
(-250-1100)
1300
(790-1900)
490
(5-950)
240
(-85-560)
190
(-39-410)
75ppb
130
(-120-380)
230
(-47-510)
380
(21-730)
180
(-32-390)
91
(-120-290)
470
(170-770)
65
(-140-270)
450
(-240-1100)
1300
(740-1800)
450
(5-890)
210
(-73-480)
190
(-39-410)
70ppb
120
(-110-350)
230
(-45-490)
370
(20 - 710)
180
(-30-380)
88
(-120-280)
480
(170-780)
65
(-140-270)
430
(-230-1100)
1200
(680-1700)
440
(5-860)
200
(-70-470)
180
(-37-390)
65ppb
110
(-110-330)
220
(-43 - 470)
360
(20-690)
170
(-28 - 350)
85
(-110-270)
470
(170-760)
64
(-140-260)
400
(-220-1000)
910
(530-1300)
420
(5-830)
190
(-68 - 450)
170
(-35 - 370)
60ppb
110
(-100-310)
210
(-41 - 450)
350
(19-670)
150
(-26-330)
76
(-99-240)
450
(160-730)
62
(-140-260)
380
(-200 - 960)
NA
NA
400
(4-790)
180
(-64-430)
160
(-33-350)
Change in Ozone-Attributable Incidence
Base-75
8
(-7-22)
26
(-5-56)
1
(0-3)
9
(-1-18)
1
(-1-2)
NA
NA
-4
(9 --17)
11
(-6-26)
84
(48-120)
32
(0-64)
35
(-12-81)
3
(-1-6)
75-70
10
(-9-29)
9
(-2-19)
10
(1-19)
8
(-1-18)
3
(-4-9)
-8
(-3 --12)
0
(0-1)
21
(-11-54)
96
(55 - 140)
16
(0 - 32)
8
(-3-20)
10
(-2-21)
75-65
17
(-16-49)
19
(-4-41)
20
(1-39)
20
(-3-43)
6
(-8-21)
7
(2-11)
1
(-2-4)
46
(-24 - 110)
370
(210-520)
35
(0-69)
16
(-6-38)
19
(-4 - 42)
75-60
23
(-21-67)
29
(-6-63)
33
(2-64)
33
(-6-70)
15
(-20 - 49)
27
(10-45)
3
(-6-12)
67
(-36-170)
NA
NA
52
(1-100)
26
(-9-62)
30
(-6-65)
Study Area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Air Quality Scenario
Percent of Baseline Incidence Attributable to Ozone
Base
1.4
2.5
2.5
2.5
1.8
4.1
0.6
1.4
4.5
2.8
2.9
2.4
75ppb
1.3
2.2
2.5
2.4
1.8
4.1
0.6
1.4
4.2
2.6
2.5
2.4
70ppb
1.2
2.2
2.4
2.3
1.8
4.2
0.6
1.3
3.9
2.5
2.4
2.3
65ppb
1.1
2.1
2.4
2.1
1.7
4.1
0.6
1.2
3.0
2.4
2.3
2.2
60ppb
1.1
2.0
2.3
1.9
1.5
3.9
0.6
1.2
NA
2.3
2.2
2.0
Change in O3-Attributable Risk
Base-75
5
10
0
4
1
NA
-7
2
6
6
14
1
75-70
7
4
2
4
3
-2
0
5
7
3
4
5
75-65
13
8
5
10
7
1
2
10
28
7
7
10
75-60
17
12
8
17
16
5
4
15
NA
11
12
15
Study Area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
NewYork, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Air Quality Scenario
Ozone-Attributable Deaths per 100,000
Base
2.34
4.78
5.03
5.58
2.45
8.36
0.95
2.13
8.02
6.20
5.03
5.64
75ppb
2.17
4.23
5.03
5.29
2.45
8.36
1.01
2.08
8.02
5.69
4.40
5.64
70ppb
2.00
4.23
4.90
5.29
2.37
8.54
1.01
1.99
7.41
5.57
4.19
5.34
65ppb
1.84
4.05
4.77
4.99
2.29
8.36
0.99
1.85
5.62
5.31
3.98
5.04
60ppb
1.84
3.86
4.63
4.41
2.05
8.01
0.96
1.76
NA
5.06
3.77
4.75
Change in Ozone-Attributable Deaths per 100,000
Base-75
0.13
0.48
0.02
0.25
0.01
NA
-0.07
0.05
0.52
0.40
0.73
0.08
75-70
0.17
0.16
0.13
0.25
0.08
-0.13
0.00
0.10
0.59
0.20
0.18
0.28
75-65
0.28
0.35
0.26
0.59
0.17
0.12
0.02
0.21
2.28
0.44
0.34
0.56
75-60
0.38
0.53
0.44
0.97
0.40
0.48
0.05
0.31
NA
0.66
0.54
0.89
NA: for NYC, the model-based adjustment methodology was unable to estimate ozone distributions which would meet the lower
alternative standard level of 60 ppb.
7C-6
-------
Table 7C-6 Sensitivity Analysis - LTMortality: Alternate risk model (regional effect
estiamtes) (2009) (incidence, percent of baseline mortality, incidence per 100,000)
compare with Core Results in Table 7B-7)
Study Area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Air Quality Scenario
Absolute Ozone-Attributable Incidence
Base
1,684
(870-2277)
-214
(-2241-1145)
-290
(-2952-1601)
0
(-1592-1021)
665
(-40-1158)
0
(-2176-1406)
1,402
(720-1907)
751
(-3983 - 4116)
-528
(-5446 - 2871)
-346
(-3604 - 1866)
1,139
(-70-1971)
0
(-1796-1130)
75ppb
1,632
(838-2217)
-201
(-2078-1088)
-291
(-2959-1604)
0
(-1538-998)
664
(-40-1157)
0
(0-0)
1,410
(724-1916)
1,452
(-7652 - 7999)
-513
(-5268-2805)
-331
(-3423 - 1801)
988
(-59 - 1750)
0
(-1770-1120)
70ppb
1,565
(799 - 2140)
-194
(-2000-1059)
-289
(-2938-1596)
0
(-1456-963)
655
(-40-1144)
0
(-2207-1418)
1,388
(711-1891)
695
(-3637-3856)
-485
(-4928-2676)
-320
(-3284-1750)
951
(-56-1695)
0
(-1687-1085)
65ppb
1,507
(764-2071)
-187
(-1906-1024)
-280
(-2832-1554)
0
(-1358-919)
635
(-38-1115)
0
(-2115-1380)
1,362
(696-1861)
662
(-3434-3696)
-413
(-4090-2334)
-307
(-3128-1690)
917
(-54-1643)
0
(-1590-1044)
eoppb
1,455
(734 - 2010)
-179
(-1814-989)
-269
(-2700-1501)
0
(-1259-872)
590
(-35 - 1048)
0
(-2004-1331)
1,329
(676-1822)
626
(-3220-3522)
NA
NA
-296
(-2991-1637)
873
(-51 - 1575)
0
(-1478-995)
Change in Ozone-Attributable Incidence
Base-75
90
(41 - 139)
-12
(-107-80)
1
(4 --3)
0
(-35 - 35)
1
(0-2)
0
(0-0)
-13
(-6 --21)
27
(-120-171)
-14
(-119-90)
-14
(-119-89)
204
(-11-406)
0
(-16-16)
75-70
111
(50-171)
-6
(-52-39)
-2
(-14-11)
0
(-55-53)
13
(-1-26)
0
(0-0)
37
(17-58)
65
(-292-416)
-27
(-232-173)
-11
(-93-70)
48
(-2-98)
0
(-54-53)
75-65
204
(92-312)
-13
(-116-86)
-10
(-87 - 66)
0
(-122-117)
40
(-2-81)
0
(0-0)
81
(36-124)
136
(-615 - 862)
-96
(-849 - 605)
-23
(-201-149)
92
(-5-187)
0
(-119-114)
75-60
281
(128-428)
-21
(-181-132)
-21
(-182-135)
0
(-194-181)
99
(-5 - 198)
0
(0-0)
134
(61 - 206)
211
(-964-1329)
NA
NA
-34
(-298-218)
148
(-8-297)
0
(-197-185)
Study Area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Air Quality Scenario
Percent of Baseline Incidence Attributable to Ozone
Base
42.5
-7.6
-6.2
0.0
27.4
0.0
40.9
4.6
-6.8
-7.3
28.4
0.0
75ppb
41.2
-7.0
-6.2
0.0
27.4
0.0
41.1
8.9
-6.6
-6.9
24.8
0.0
70ppb
39.6
-6.7
-6.1
0.0
27.0
0.0
40.5
4.3
-6.2
-6.6
23.9
0.0
65ppb
38.1
-6.4
-5.9
0.0
26.2
0.0
39.8
4.2
-5.0
-6.3
23.1
0.0
eoppb
36.8
-6.1
-5.6
0.0
24.4
0.0
38.8
4.0
NA
-6.0
22.0
0.0
Change in O3-Attributable Risk
Base-75
3.1
7.7
-0.2
0.0
0.1
0.0
-0.5
-95.3
3.5
5.3
12.8
0.0
75-70
4.0
4.0
0.7
0.0
1.3
0.0
1.5
51.5
6.8
4.3
3.6
0.0
75-65
7.6
8.8
4.5
0.0
4.2
0.0
3.4
53.2
23.6
9.2
6.9
0.0
75-60
10.6
13.4
9.3
0.0
10.7
0.0
5.7
55.2
NA
13.4
11.2
0.0
Study Area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Air Quality Scenario
Ozone-Attributable Deaths per 100,000
Base
49.25
-6.56
-6.27
0.00
31.10
0.00
39.74
6.24
-5.38
-7.32
41.19
0.00
75ppb
47.72
-6.16
-6.28
0.00
31.06
0.00
39.96
6.03
-5.23
-7.01
35.71
0.00
70ppb
45.77
-5.97
-6.25
0.00
30.63
0.00
39.34
5.78
-4.94
-6.77
34.39
0.00
65ppb
44.06
-5.73
-6.05
0.00
29.71
0.00
38.59
5.50
-4.21
-6.50
33.17
0.00
eoppb
42.57
-5.50
-5.81
0.00
27.61
0.00
37.66
5.20
NA
-6.26
31.57
0.00
Change in Ozone-Attributable Deaths per 100,000
Base-75
2.64
-0.38
0.01
0.00
0.05
0.00
-0.38
0.22
-0.14
-0.29
7.38
0.00
75-70
3.26
-0.19
-0.04
0.00
0.59
0.00
1.05
0.27
-0.27
-0.23
1.75
0.00
75-65
5.97
-0.41
-0.22
0.00
1.87
0.00
2.29
0.56
-0.98
-0.49
3.34
0.00
75-60
8.23
-0.64
-0.45
0.00
4.63
0.00
3.80
0.88
NA
-0.72
5.36
0.00
NA: for NYC, the model-based adjustment methodology was unable to estimate ozone distributions which would meet the lower
alternative standard level of 60 ppb.
7C-7
-------
Table 7C-7 Sensitivity Analysis —LTMortality: Alternate risk model (ozone-only effect
estimate) (2009) (incidence, percent of baseline mortality, incidence per 100,000) -
compare with Core Results in Table 7B-7)
Study Area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Air Quality Scenario
Absolute Ozone-Attributable Incidence
Base
200
(61-330)
220
(65-350)
300
(89-490)
150
(44-240)
140
(42-230)
200
(60-330)
170
(50-280)
800
(240-1300)
540
(160-880)
350
(100-570)
240
(72-390)
160
(49-270)
75ppb
200
(58-320)
200
(61-330)
300
(89 - 490)
140
(43 - 230)
140
(42 - 230)
200
(60-330)
170
(50-280)
780
(230-1300)
520
(160-860)
340
(100-550)
200
(61-330)
160
(48-260)
70ppb
190
(55 - 310)
200
(59 - 320)
300
(88-490)
140
(41 - 220)
140
(41 - 220)
200
(61-330)
170
(49 - 270)
740
(220-1200)
500
(150-820)
330
(97 - 540)
200
(59 - 320)
160
(46-250)
65ppb
180
(53-290)
190
(57-310)
290
(86-470)
130
(39-210)
130
(40-220)
200
(59-320)
160
(48-270)
710
(210-1200)
430
(130-710)
310
(94-520)
190
(56-310)
150
(44-240)
eoppb
170
(50-280)
180
(55-300)
280
(82-460)
120
(36-200)
120
(37 - 200)
190
(56-310)
160
(47 - 260)
670
(200-1100)
NA
NA
300
(90-500)
180
(53 - 290)
140
(42 - 230)
Change in Ozone-Attributable Incidence
Base -75
9.0
(3-15)
14
(4-23)
-0.57
(0--1)
4.3
(1-7)
0.21
(0-0)
NA
NA
-1.3
(0--2)
30
(9-51)
15
(4-26)
15
(4-26)
40
(11-67)
2.0
(1-3)
75-70
11
(3-19)
6.7
(2-11)
1.8
(1-3)
6.7
(2-11)
2.4
(1-4)
-2.4
(-1--4)
3.7
(1-6)
36
(10-62)
30
(9-51)
12
(3-21)
9.3
(3-16)
6.6
(49-270)
75-65
21
(6-35)
15
(4-25)
11
(3-19)
15
(4-25)
7.7
(2-13)
4.9
(1-8)
8.0
(2-14)
76
(22-130)
110
(30-180)
26
(7-44)
18
(5-30)
14
(4-24)
75-60
29
(8-49)
23
(7-39)
23
(7-40)
23
(7-39)
19
(6-33)
14
(4-24)
13
(4-23)
120
(34-200)
NA
NA
38
(11-64)
29
(8-49)
23
(7-40)
Study Area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Air Quality Scenario
Percent of Baseline Incidence Attributable to Ozone
Base
12.4
12.9
11.1
12.1
14.1
11.9
11.8
15.1
12.0
12.5
14.7
12.6
75ppb
11.9
12.2
11.1
11.8
14.1
11.9
11.9
14.6
11.7
12.0
12.6
12.4
70ppb
11.3
11.8
11.1
11.3
13.9
12.0
11.6
14.0
11.1
11.7
12.1
12.0
65ppb
10.8
11.4
10.8
10.7
13.4
11.6
11.4
13.4
9.6
11.2
11.6
11.5
eoppb
10.3
11.0
10.4
10.1
12.4
11.2
11.0
12.7
NA
10.9
11.1
10.8
Change in O3-Attributable Risk
Base -75
4
6
0
3
0
NA
-1
3
3
4
14
1
75-70
5
3
1
4
2
-1
2
4
5
3
4
4
75-65
10
7
3
10
5
2
4
9
19
7
8
8
75-60
14
10
7
15
12
6
7
14
NA
10
13
13
Study Area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Air Quality Scenario
Ozone-Attributable Deaths per 100,000
Base
5.95
6.63
6.42
6.96
6.51
5.97
4.76
6.66
5.47
7.42
8.65
8.05
75ppb
5.72
6.26
6.43
6.78
6.50
5.97
4.79
6.44
5.33
7.13
7.40
7.96
70ppb
5.43
6.08
6.40
6.50
6.40
6.04
4.70
6.19
5.06
6.91
7.10
7.68
65ppb
5.19
5.86
6.22
6.16
6.19
5.84
4.59
5.90
4.36
6.65
6.83
7.34
eoppb
4.97
5.64
5.99
5.80
5.71
5.61
4.45
5.59
NA
6.42
6.48
6.94
Change in Ozone-Attributable Deaths per 100,000
Base -75
0.26
0.42
-0.01
0.21
0.01
0.00
-0.04
0.25
0.16
0.32
1.44
0.10
75-70
0.32
0.21
0.04
0.32
0.11
-0.07
0.10
0.30
0.30
0.25
0.34
0.33
75-65
0.60
0.45
0.24
0.70
0.36
0.15
0.23
0.63
1.07
0.54
0.65
0.71
75-60
0.83
0.70
0.50
1.09
0.90
0.41
0.38
0.98
NA
0.80
1.04
1.15
NA: for NYC, the model-based adjustment methodology was unable to estimate ozone distributions which would meet the lower
alternative standard level of 60 ppb.
7C-8
-------
APPENDIX 8-A.
ESTIMATES
CITY-SPECIFIC OZONE-MORTALITY EFFECT
Table 8-A-l. Smith et al. (2009) city-specific and regional non-accidental mortality effect
estimates for 8-hr daily maximum ozone, using April-October (many just May-September)
ozone observations from 1987-2000, based on 98 U.S. urban communities.
Location
Akron, OH
Albuquerque, NM
Arlington, VA
Atlanta, GA
Austin, TX
Bakersfield, CA
Baltimore, MD
Baton Rouge, LA
Biddeford, ME
Birmingham, AL
Boston, MA
Buffalo, NY
Cedar Rapids, IA
Charlotte, NC
Chicago, IL
Cincinnati, OH
Cleveland, OH
Colorado Springs, CO
Columbus, GA
Columbus, OH
Corpus Christi, TX
Coventry, RI
Dallas/Ft Worth, TX
Dayton, OH
Denver, CO
Des Moines, IA
Detroit, MI
El Paso, TX
Evansville
Ft Wayne, IN
National prior
Beta
0.000305
0.000292
0.000341
0.000256
0.000309
0.000342
0.000313
0.000383
0.000321
0.000212
0.000156
0.000349
0.000338
0.000236
0.000498
0.000513
0.000488
0.000389
0.000405
0.000309
0.000375
0.000251
0.000538
0.000314
0.000182
0.000188
0.000439
0.000173
0.000275
0.000319
Std
0.000332
0.000349
0.000353
0.000283
0.000313
0.00033
0.000322
0.00031
0.000349
0.000318
0.000343
0.000324
0.000338
0.000328
0.000247
0.000329
0.000308
0.000347
0.000321
0.000323
0.000322
0.000335
0.000238
0.000334
0.000345
0.000342
0.000299
0.000347
0.000326
0.00034
Regional prior
Beta
0.000502
-5E-05
0.00091
0.000222
-1.6E-05
4.41E-05
0.000863
0.000281
0.000897
0.000197
0.000803
0.00052
-0.00017
0.000208
0.000568
0.000597
0.00058
0.000257
0.000289
0.000501
8.6E-06
0.000847
0.000392
0.000507
0.000163
-0.00024
0.000554
-9.7E-05
0.000486
0.000512
Std
0.000279
0.000351
0.000297
0.000229
0.000326
0.000282
0.000286
0.000244
0.000297
0.00025
0.00031
0.000274
0.000482
0.000254
0.000224
0.000277
0.000264
0.000377
0.000249
0.000274
0.000335
0.000297
0.000213
0.00028
0.000372
0.00048
0.000259
0.000347
0.000277
0.000283
-------
Fresno, CA
Grand Rapids, MI
Greensboro, NC
Honolulu, HI
Houston, TX
Huntsville, AL
Indianapolis, IN
Industrial Midwest
Jackson, MS
Jacksonville, FL
Jersey City, NJ
Johnston, PA
Kansas City, KS
Kansas City, MO
Kingston, NY
Knoxville, TN
Lafayette, LA
Lake Charles, LA
Las Vegas, NV
Lexington, KY
Lincoln, NE
Little Rock, AR
Los Angeles, CA
Louisville, KY
Madison, WI
Memphis, TN
Miami, FL
Milwaukee, WI
Mobile, AL
Modesto, CA
Muskegon, MI
Nashville, TN
National Average
New Orleans, LA
New York, NY
Newark, NJ
North East
North West
Oakland, CA
Oklahoma City, OK
Omaha, NE
0.000188
0.000377
0.000291
0.000451
0.000403
0.000548
0.000246
N/A
0.000269
0.000201
0.000117
0.000329
0.000146
0.000395
0.000452
0.000471
0.000236
0.000263
0.00014
0.000172
0.000426
0.000217
0.000148
0.000351
0.000456
0.000391
0.000233
0.00029
0.000359
0.000322
0.000305
0.000347
0.000322
0.000252
0.000917
0.000549
N/A
N/A
0.000214
0.000358
0.000377
0.000334
0.000335
0.000346
0.000358
0.000215
0.000357
0.000331
N/A
0.000327
0.000322
0.000336
0.000334
0.000339
0.000321
0.000342
0.000339
0.000315
0.000312
0.000348
0.000345
0.000349
0.000339
0.000165
0.000322
0.000355
0.000312
0.000277
0.000315
0.000323
0.000341
0.000346
0.000329
8.42E-05
0.000321
0.00023
0.000333
N/A
N/A
0.000334
0.000317
0.000345
-2.6E-05
0.000537
0.000231
6.17E-05
0.00032
0.000349
0.000474
0.000521
0.000223
0.000192
0.000769
0.000884
-0.00025
-0.00013
0.000944
0.000316
0.000209
0.000222
-0.00011
0.000443
0.000941
0.000198
5.24E-05
0.000521
0.000577
0.000284
0.000211
0.000488
0.000266
0.000227
0.000508
0.00026
N/A
0.000216
0.001055
0.000972
0.000908
0.000224
0.000179
4.62E-06
0.000917
0.000283
0.00028
0.000262
0.000236
0.000189
0.000271
0.00028
0.00018
0.000253
0.000252
0.000314
0.00029
0.000473
0.000467
0.000287
0.00026
0.000247
0.000245
0.000346
0.00029
0.000292
0.000261
0.000161
0.000273
0.000292
0.000245
0.000226
0.00027
0.00025
0.000372
0.000287
0.000253
N/A
0.00025
0.000195
0.000276
0.000192
0.000308
0.000366
0.000331
0.000292
-------
Orlando, FL
Philadelphia, PA
Phoenix, AZ
Pittsburgh, PA
Portland, OR
Providence, RI
Raleigh, NC
Riverside, CA
Rochester, NY
Sacramento, CA
Salt Lake City, UT
San Antonio, TX
San Bernardino, CA
San Diego, CA
San Jose, CA
Santa Ana/ Anaheim, CA
Seattle, WA
Shreveport, LA
South East
South West
Southern California
Spokane, WA
St. Louis, MO
St Petersburg, FL
Stockton, CA
Syracuse, NY
Tacoma, WA
Tampa, FL
Toledo, OH
Tucson, AZ
Tulsa, OK
Upper Midwest
Washington, DC
Wichita, KS
Worcester, MA
-3.3E-05
0.000574
0.00034
0.000155
0.00037
0.000418
0.000271
0.000206
0.000406
0.000306
0.000296
7.15E-05
0.00034
0.000118
0.000351
0.0002
0.000283
0.000366
N/A
N/A
N/A
0.000327
0.000476
0.000147
0.00036
0.00053
0.00036
0.000223
0.000414
0.000333
0.000382
N/A
0.000239
0.000249
0.000467
0.000358
0.000296
0.000301
0.000306
0.000335
0.000333
0.000337
0.000295
0.000339
0.000313
0.000345
0.000307
0.000283
0.000289
0.000323
0.000279
0.000325
0.00032
N/A
N/A
N/A
0.000353
0.000336
0.000288
0.000343
0.000357
0.000342
0.000299
0.000333
0.000334
0.000325
N/A
0.000321
0.000345
0.000337
7.91E-05
0.000948
7.84E-06
0.000412
0.00025
0.000922
0.000223
2.3E-06
0.000923
0.000225
0.000215
-0.00012
7.61E-05
-3.6E-05
0.000244
8.65E-06
0.000212
0.00027
0.000242
-4.4E-05
1.73E-05
0.000227
0.000581
0.000166
0.000244
0.000985
0.000245
0.000204
0.000553
-2.1E-05
0.000277
-0.0002
0.000823
-0.00022
0.000946
0.000286
0.000253
0.00032
0.000272
0.000369
0.000284
0.000258
0.000257
0.000287
0.000351
0.000375
0.000313
0.000254
0.000252
0.00036
0.000246
0.00036
0.000248
0.000135
0.000273
0.000189
0.000381
0.000281
0.000235
0.000374
0.000292
0.000373
0.000239
0.000279
0.000342
0.000251
0.000445
0.000294
0.000486
0.000283
-------
Table 8-A-2. Zanobetti and Schwartz (2008) city-specific all-cause mortality effect
estimates for June-August 8-hr daily mean (10am-6pm) ozone from 1989-2000, using a 0-3
day lag, based on 48 U.S. cities.
Location
All cities (48)
Albuquerque, NM
Atlanta, GA
Austin, TX
Baltimore, MD
Birmingham, AL
Boston, MA
Boulder, CO
Broward, FL
Canton, OH
Charlotte, NC
Chicago, IL
Cincinnati, OH
Cleveland, OH
Colorado Springs, CO
Columbus, OH
Dallas, TX
Denver, CO
Detroit, MI
Greensboro, NC
Honolulu, HI
Houston, TX
Jersey city, NJ
Kansas City, KS
Los Angeles, CA
Miami, FL
Milwaukee, WI
Nashville, TN
New Haven, CT
New Orleans, LA
New York, NY
Oklahoma City, OK
Orlando, FL
Philadelphia, PA
Phoenix, AZ
Pittsburgh, PA
Provo/Orem, UT
Beta
0.00053
0.000528
0.000295
0.00045
0.000515
0.000293
0.000682
0.000602
0.000593
0.000489
0.000571
0.000479
0.000509
0.000596
0.000497
0.000739
0.000578
0.000352
0.001046
0.000478
0.000486
0.000163
0.000354
0.000922
0.000274
0.000607
0.000659
0.00046
0.000647
0.000218
0.001092
0.00062
0.000487
0.000625
0.00071
0.00028
0.000527
Std
0.000125
0.000416
0.000289
0.000393
0.000314
0.000356
0.000328
0.000419
0.000382
0.000401
0.000381
0.000299
0.000361
0.000355
0.000418
0.000368
0.000317
0.000409
0.000344
0.000397
0.00042
0.000263
0.00038
0.000387
0.000213
0.000373
0.000382
0.000383
0.000364
0.000375
0.000236
0.00038
0.000377
0.000315
0.000374
0.000328
0.00042
-------
Sacramento, CA
Salt Lake City, UT
San Diego, CA
San Francisco, CA
Seattle, WA
Spokane, WA
St. Louis, MO
Tampa, FL
Terra Haute, IN
Tulsa, OK
Washington, DC
Youngstown, OH
0.000569
0.000478
0.000448
0.000566
0.000491
0.00059
0.000544
0.000123
0.000659
0.000871
9.56E-05
0.000448
0.000389
0.000407
0.000373
0.000416
0.00038
0.000415
0.000333
0.000366
0.00042
0.000391
0.00036
0.000394
-------
APPENDIX 8-B. Supplement to the Representativeness Analysis of the
12 Urban Study Areas
Following the analysis discussed in Section 8.2, this appendix provides graphical comparisons of
the empirical distributions of components of the risk function, and additional variables that have
been identified as potentially influencing the risk associated with ozone exposures. In each
graph, the blue line represents the cumulative distribution function (CDF) for the complete set of
data available for the variable. In some cases, this many encompass all counties in the U.S.,
while in others it may be based on a subset of the U.S., usually for large urban areas. The black
squares at the bottom of each graph represent the specific value of the variable for one of the
case study locations, with the line showing where that value intersect the CDF of the nationwide
data.
Elements of the Risk Equation
Comparison of Urban Case Study Area with U.S. Distribution (3143 U.S.
Counties) - Population
Urban case study
areas are all above
the 90th percentile of
county populations
100
1000
10000 100000
Population, 2008
1000000
10000000
•All Counties CDF
Case Study Counties
Figure A.I Comparison of distributions for key elements of the risk equation: Total
population
-------
Comparison of Urban Case Study Area with U.S. Distribution (3141 U.S.
Counties) - Percent Younger than 15 Years Old
% Younger than 15 Years Old, 2005
•All Counties CDF
Case Study Counties
Figure A.2 Comparison of distributions for key elements of the risk equation: Percent of
population younger than 15 years old
-------
Comparison of Urban Case Study Area with U.S. Distribution (3141 U.S.
Counties) - Percent 65 Years and Older
Urban case study
counties are all below
the 60th percentile of
county % of population
65 years and older
Figure A.3
11 13 15 17 19
% 65 Years and Older, 2005
21 23 25 27
•All Counties CDF
Case Study Counties
Comparison of distributions for key elements of the risk equation: Percent of
population 65 and older
-------
Comparison of Urban Case Study Area with U.S. Distribution (3141 U.S.
Counties) - Percent 85 Years and Older
100%
90%
80%
S 70%
X
§ 60%
o
^ 50%
^ 40%
* 30%
20%
10%
0% -
<
^
H
^
1— 1
/
/
• 1
A
/
H
/
II
f
1 — •
/
»1
/
H
/
1— 1
/
III
0.5
Urban case study
areas are all below
the 75th percentile
of % of population
85 years and older
Figure A.4
1.5 2 2.5 3 3.5
% 85 Years and Older, 2005
4.5
5.5
•All Counties CDF
Case Study Counties
Comparison of distributions for key elements of the risk equation: Percent of
population 85 and older
-------
100%
90%
80%
| 70%
o 60%
u
"S 50%
o
'E 40%
o
J 30%
'o
^ 20%
10%
Comparison of Urban Case Study Area with U.S. Distribution (671 U.S.
Counties with Ozone Monitors) -
Seasonal Mean 8-hr Daily Max Ozone
30 40 50 60 70
Seasonal Mean 8-hr Daily Max Ozone Concentration, Average 2006-2008
(ppb)
•All Counties CDF
Case Study Counties
Figure A.5
Comparison of distributions for key elements of the risk equation: Seasonal
mean 8-hr daily maximum ozone concentration
-------
Comparison of Urban Case Study Area with U.S. Distribution (725 U.S.
Counties with Ozone Monitors) -
4th High 8-hr Daily Maximum Ozone
40
Figure A.6
50 60 70 80 90 100
4th High 8-hr Daily Maximum Ozone, 2007 (ppb)
110
•All Counties CDF
Case Study Counties
Comparison of distributions for key elements of the risk equation: 4 highest
8-hr daily maximum ozone concentration
-------
Comparison of Urban Case Study Area with U.S. Distribution (671 U.S.
Counties with Ozone Monitors) -
Seasonal Mean 1-hr Daily Max Ozone
1/1
Q)
C
3
O
u
1
o
'E
o
•s
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
^
x
r
Illl
V
40 50 60 70 80
Seasonal Mean 1-hr Daily Max Ozone Concentration, Average 2006-2008
(ppb)
•All Counties CDF
Case Study Counties
Figure A.7 Comparison of distributions for key elements of the risk equation: Seasonal
mean 1-hr daily maximum ozone concentration
-------
Comparison of Urban Case Study Area with U.S. Distribution (671 U.S.
Counties with Ozone Monitors) -
Seasonal Mean Ozone
20
30 40 50
Seasonal Mean Ozone Concentration, Average 2006-2008 (ppb)
60
•All Counties CDF
Case Study Counties
Figure A.8 Comparison of distributions for key elements of the risk equation: Seasonal
mean ozone concentration
-------
Comparison of Urban Case Study Area with U.S. Distribution (3137 U.S.
Counties) - All Cause Mortality
Urban case
study areas are
all below the
85th percentile
of county all
cause mortality
500
600 700 800 900 1000 1100 1200 1300 1400
All Cause Mortality per 100,000 Population, 1999-2005
1500
•All Counties CDF
Case Study Counties
Figure A.9 Comparison of distributions for key elements of the risk equation: Baseline
all-cause mortality
-------
Comparison of Urban Case Study Area with U.S. Distribution (3135 U.S.
Counties) - Non Accidental Mortality
300
Urban case study
counties are all
below the 80th
percentile of non
accidental
mortality
500 700 900 1100 1300
Non Accidental Mortality per 100,000 Population, 1999-2005
1500
•All Counties CDF
Case Study Counties
Figure A.10 Comparison of distributions for key elements of the risk equation: Baseline
non-accidental mortality
10
-------
Comparison of Urban Case Study Area with U.S. Distribution (3110 U.S.
Counties) - Cardiovascular Mortality
100
200 300 400 500
Cardiovascular Mortality per 100,000 Population, 1999-2005
600
•All Counties CDF
Case Study Counties
Figure A.ll Comparison of distributions for key elements of the risk equation: Baseline
cardiovascular mortality
11
-------
Comparison of Urban Case Study Area with U.S. Distribution (2993 U.S.
Counties) - Respiratory Mortality
Urban case study
counties are all below
the 50th percentile of
respiratory mortality
40 60 80 100 120 140
Respiratory Mortality per 100,000 Population, 1999-2005
•All Counties CDF
Case Study Counties
160
Figure A. 12
Comparison of distributions for key elements of the risk equation: Baseline
respiratory mortality
12
-------
Comparison of Urban Case Study Area with U.S. Distribution (95
NMMAPS Cities) -
Non Accidental Mortality Risk ((J)
.0002
0.0004 0.0006 0.0008 0.001
Non Accidental Mortality Risk Coefficient ((J)
0.0012
•All Cities CDF
Case Study Cities
Figure A.13 Comparison of distributions for key elements of the risk equation: Non-
accidental mortality risk coefficient from Bell et al. (2004)
13
-------
1/1
_QJ
JM
U
I
O
2.
N
t
rc
J
s
•o
c
ro
c
^
o
c
TO
M
"4-
o
s?
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
O.OC
Comparison of Urban Case Study Area with U.S. Distribution (48 Z&S
Cities) - All Cause Mortality Risk (p)
0.0004 0.0006 0.0008 0.001
All Cause Mortality Risk Coefficient ((J)
0.0012
All cities
•All Cities CDF
Case Study Cities
Figure A.14 Comparison of distributions for key elements of the risk equation: All-cause
mortality risk coefficient from Zanobetti and Schwartz (2008)
14
-------
Comparison of Urban Case Study Area with U.S. Distribution (48 Z&S
Cities) - Cardiovascular Mortality Risk Coefficient ((J)
.0002
0.0005 0.0008 0.0011 0.0014
Cardiovascular Mortality Risk Coefficient ((J)
0.0017
All Cities
•All Cities CDF
Case Study Cities
Figure A.15 Comparison of distributions for key elements of the risk equation:
Cardiovascular mortality risk coefficient from Zanobetti and Schwartz
(2008)
15
-------
Comparison of Urban Case Study Area with U.S. Distribution (48 Z&S
Cities) - Respiratory Mortality Risk ((J)
1/1
0)
u
co"
8
DL
N
ro
u
to
£
(0
s
^
o
£
(D
M
'o
*
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
O.OC
0.0005 0.0007 0.0009
Respiratory Mortality Risk Coefficient
0.0011
0.0013
All Cities
•All Cities CDF
Case Study Cities
Figure A.16 Comparison of distributions for key elements of the risk equation:
Respiratory mortality risk coefficient from Zanobetti and Schwartz (2008)
16
-------
Variables Expected to Influence the Relative Risk from Ozone
Demographic Variables
Comparison of Urban Case Study Area with U.S. Distribution (3143 U.S.
Counties) - Population Density
10 100 1000 10000
Population Per Square Mile, 2008
100000
1000000
•All Counties CDF
Case Study Counties
Figure A.17 Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Population density
17
-------
100%
90%
80%
I 70%
c
o 60%
3 50%
"S 40%
S?
30%
20%
10%
0%
Comparison of Urban Case Study Area with U.S. Distribution (3141 U.S.
Counties) - Median Age
32 34
38
40 42 44 46
Median Age, 2005
48 50
52 54
•All Counties CDF
Case Study Counties
Figure A.18 Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Median age
18
-------
100%
90%
80%
.2 70%
c
g 60%
u
"j 50%
D
^ 40%
S?
30% -
20%
10%
0%
Comparison of Urban Case Study Area with U.S. Distribution (3141 U.S.
Counties) -
Percent Less than High School Education
10
15 20 25 30 35 40 45 50
% Less than High School Education, 2000
55 60 65
•All Counties CDF
Case Study Counties
Figure A.19 Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Percent less than high school education
19
-------
Comparison of Urban Case Study Area with U.S. Distribution (3141 U.S.
Counties) - Unemployment rate
6 8
Unemployment rate, 2005
10
12
•All Counties CDF
Case Study Counties
Figure A.20 Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Unemployment rate
20
-------
100%
90%
80%
-------
Comparison of Urban Case Study Area with U.S. Distribution (3141 U.S.
Counties) - Urbanicity
4 5
Urbanicity, 2003
•All Counties CDF
Case Study Counties
Figure A.22 Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Urbanicity
22
-------
Comparison of Urban Case Study Area with U.S. Distribution (76 Cities)
Air Conditioning Prevalence
10
20
Urban study areas
are all below the
90th percentile of
percent of
residences with no
air conditioning
30 40 50 60 70
No air conditioning, 2004 (%)
80
•All Cities CDF
Case Study Cities
90
100
Figure A.23 Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Air conditioning prevalence
23
-------
Comparison of Urban Case Study Area with U.S. Distribution (366 U.S.
Cities) - Public Transportation Use
5 10 15 20 25 30
% Commuting by Public Transportation, 2010
35
40
•All Counties CDF
Case Study Counties
Figure A.24
Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Percent commuting by public transportation
24
-------
Health Conditions
Comparison of Urban Case Study Area with U.S. Distribution (184 BFRSS
Cities) -
Acute Myocardial Infarction
234567
Acute Myocardial Infarction Prevalence, 2007 (%)
•All Counties CDF
Case Study Counties
Figure A.25 Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Acute myocardial infarction prevalence
25
-------
Comparison of Urban Case Study Area with U.S. Distribution (184 BFRSS
Cities) - Diabetes
8 9 10 11
Diabetes Prevalence, 2007 (%)
12
•All Counties CDF
Case Study Counties
13
14
Figure A.26 Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Diabetes prevalence
26
-------
Comparison of Urban Case Study Area with U.S. Distribution (184 BFRSS
Cities) - Stroke
1.5
2.5 3 3.5
Stroke Prevalence, 2007 (%)
•All Counties CDF
Case Study Counties
4.5
Figure A.27 Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Stroke prevalence
27
-------
8 60%
Comparison of Urban Case Study Area with U.S. Distribution (184 BFRSS
Cities) - Coronary Heart Disease
45678
Coronary Heart Disease Prevalence, 2007 (%)
10
•All Counties CDF
Case Study Counties
Figure A.28 Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Coronary heart disease prevalence
28
-------
Comparison of Urban Case Study Area with U.S. Distribution (182 BFRSS
Cities) - Obesity
15
20 25 30
Obesity Prevalence, 2007 (%)
35
40
•All Counties CDF
Case Study Counties
Figure A.29 Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Obesity prevalence
29
-------
Comparison of Urban Case Study Area with U.S. Distribution (183 BFRSS
Cities)- Vigorous Activity 20min
15
20 25 30 35
Vigorous Activity 20 minutes per day, 2007 (%)
40
•All Counties CDF
Case Study Counties
Figure A.30 Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Vigorous activity at least 20 minutes per day
30
-------
1/1
Q)
U
'o
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0% -
Comparison of Urban Case Study Area with U.S. Distribution (182 BFRSS
Cities) - Moderate Activity SOmin or Vigorous Activity 20min
35 40 45 50 55 60 65
Moderate Activity 30 minutes per day or Vigorous Activity 20 minutes per
day, 2007 (%)
•All Counties CDF
Case Study Counties
Figure A.31
Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Moderate activity at least 30 minutes per day or
vigorous activity at least 20 minutes per day
31
-------
Comparison of Urban Case Study Area with U.S. Distribution (184 BFRSS
Cities) - Asthma Prevalence
.0)
§ 50%
8 10
Asthma Prevaldence, 2007(%)
12
14
•All Counties CDF
Case Study Counties
Figure A.32 Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Asthma prevalence
32
-------
Comparison of Urban Case Study Area with U.S. Distribution (184 BFRSS
Cities) - Ever Smoked
10
15
20 25
Ever Smoked, 2007(%)
30
35
•All Counties CDF
Case Study Counties
Figure A.33 Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Smoking prevalence
33
-------
Air Quality and Climate Variables
Comparison of Urban Case Study Area with U.S. Distribution (617
U.S.Counties with PM2 5 Monitors) - Annual Average PM2 5
10 12 14 16 18 20
Annual Average PM2 5, 2007 (u,g/m3)
22
•All Counties CDF
Case Study Counties
24
Figure A.34
Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Annual average PMi.s concentration
34
-------
Comparison of Urban Case Study Area with U.S. Distribution (617 U.S.
Counties with PM2 5 Monitors) -
98th Percentile PM,
10
20 30 40 50 60
98th Percentile PM2 5, 2007 (u.g/m3)
•All Counties CDF
Case Study Counties
70
80
Figure A.35 Comparison of distributions for selected variables expected to influence the
»th
relative risk from ozone: 98 percentile PMi.5 concentration
35
-------
Comparison of Urban Case Study Area with U.S. Distribution (204 U.S.
Counties in MCAPS Database) -
Percent Days with PM2 5 Exceeding 35 u.g/m3
5 10 15
% days with PM2 5 exceeding 35 u,g/m3,1999-2002
•All Counties CDF
Case Study Counties
20
Figure A.36 Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Percent of days with PMi.5 exceeding 35 ug/m3
36
-------
1/1
Q)
C
3
O
u
'o
*
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
X
Comparison of Urban Case Study Area with U.S. Distribution (202 U.S.
Counties in MCAPS Database) - Average Temperature
40
50 60
Average Temperature ( F)
70
80
•All Counties CDF
Case Study Counties
Figure A.37 Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Average temperature
37
-------
Comparison of Urban Case Study Area with U.S. Distribution (All U.S.
Counties) - July Temperature
66
68
70 72 74 76 78 80
Mean Temperature for July, 1941-1970 ( F)
82
84
86
•All Counties CDF
Case Study Counties
Figure A.38 Comparison of distributions for selected variables expected to influence the
relative risk from ozone: July temperature
38
-------
Comparison of Urban Case Study Area with U.S. Distribution (All U.S.
Counties) - July Humidity
20
30 40 50 60
Relative Humidity for July, 1941-1970
70
80
•All Counties CDF
Case Study Counties
Figure A.39 Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Relative humidity
39
-------
8-C. National Representativeness of Ozone Response to
Emissions Changes
Table of Contents
1. Ambient Trends Over a Period of Nationally Decreasing NOx emissions 9
1.1 Nationwide maps showing absolute changes in ozone between 2001-2003 and 2008-20109
1.2 THIRTEEN-YEAR OZONE TRENDS ACROSS THE COUNTRY AND IN CASE-
STUDY AREAS 17
2. Modeled Ozone Changes in Response to Across the Board Emissions Reductions 34
2.1 Maps of ratios of mean ozone from 2007 CMAQ simulations including emissions
reductions to mean ozone from 2007 base CMAQ simulations 34
2.2 Modeled ozone response paired with population 44
TABLE OF FIGURES
FIGURE 1: CHANGE IN STH PERCENTILE JUNE-AUGUST SUMMER SEASON DAILY S-HOUR MAXIMUM OZONE
CONCENTRATIONS BETWEEN 2001-2003 AND 2008-2010 10
FIGURE 2: CHANGE IN 25TH PERCENTILE JUNE-AUGUST SUMMER SEASON DAILY S-HOUR MAXIMUM OZONE
CONCENTRATIONS BETWEEN 2001-2003 AND 2008-2010 10
FIGURE 3: CHANGE IN 50TH PERCENTILE JUNE-AUGUST SUMMER SEASON DAILY S-HOUR MAXIMUM OZONE
CONCENTRATIONS BETWEEN 2001-2003 AND 2008-2010 11
FIGURE 4: CHANGE IN 75TH PERCENTILE JUNE-AUGUST SUMMER SEASON DAILY S-HOUR MAXIMUM OZONE
CONCENTRATIONS BETWEEN 2001-2003 AND 2008-2010 11
FIGURE 5: CHANGE IN 95TH PERCENTILE JUNE-AUGUST SUMMER SEASON DAILY S-HOUR MAXIMUM OZONE
CONCENTRATIONS BETWEEN 2001-2003 AND 2008-2010 12
FIGURE 6: CHANGE IN STH PERCENTILE APRIL-OCTOBER SUMMER SEASON DAILY S-HOUR MAXIMUM OZONE
CONCENTRATIONS BETWEEN 2001-2003 AND 2008-2010 12
FIGURE 7: CHANGE IN 25TH PERCENTILE APRIL-OCTOBER SUMMER SEASON DAILY S-HOUR MAXIMUM OZONE
CONCENTRATIONS BETWEEN 2001-2003 AND 2008-2010 13
FIGURE 8: CHANGE IN 50TH PERCENTILE APRIL-OCTOBER SUMMER SEASON DAILY S-HOUR MAXIMUM OZONE
CONCENTRATIONS BETWEEN 2001-2003 AND 2008-2010 13
FIGURE 9: CHANGE IN 75TH PERCENTILE APRIL-OCTOBER SUMMER SEASON DAILY S-HOUR MAXIMUM OZONE
CONCENTRATIONS BETWEEN 2001-2003 AND 2008-2010 14
FIGURE 10: CHANGE IN 95TH PERCENTILE APRIL-OCTOBER SUMMER SEASON DAILY S-HOUR MAXIMUM OZONE
CONCENTRATIONS BETWEEN 2001-2003 AND 2008-2010 14
FIGURE 11: CHANGE IN STH PERCENTILE ANNUAL DAILY S-HOUR MAXIMUM OZONE CONCENTRATIONS BETWEEN 2001 -
2003 AND 2008-2010 15
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FIGURE 12: CHANGE IN 25TH PERCENTILE ANNUAL DAILY S-HOUR MAXIMUM OZONE CONCENTRATIONS BETWEEN
2001-2003 AND 2008-2010 15
FIGURE 13: CHANGE IN 50TH PERCENTILE ANNUAL DAILY S-HOUR MAXIMUM OZONE CONCENTRATIONS BETWEEN
2001-2003 AND 2008-2010 16
FIGURE 14: CHANGE IN 75TH PERCENTILE ANNUAL DAILY S-HOUR MAXIMUM OZONE CONCENTRATIONS BETWEEN
2001-2003 AND 2008-2010 16
FIGURE 15: CHANGE IN 95TH PERCENTILE ANNUAL DAILY S-HOUR MAXIMUM OZONE CONCENTRATIONS BETWEEN
2001-2003 AND 2008-2010 17
FIGURE 16: ANNUAL MEDIANS OF O3 CONCENTRATIONS AT EACH MONITOR BASED ON DIFFERENT SUBSETS OF
MONTHS 18
FIGURE 17: PROCEDURE FOR CREATING THE DISPLAY OF O3 DISTRIBUTIONS SHOWN IN FIGURE 18 19
FIGURE 18: KDEs OF GROUPS OF MONITORS' ANNUAL O3 CONCENTRATIONS FOR DIFFERENT SUBSETS OF MONTHS,
SHOWN ON A LINEAR COLOR SCALE. THE MODES AND MEDIANS OF THESE CONCENTRATIONS ACROSS THE YEAR
AND MONITORS FOR EACH GROUP ARE SHOWN IN THE OVERLAYING LINES 20
FIGURE 19: MAP OF OZONE TRENDS AT SPECIFIC MONITOR LOCATIONS IN THE ATLANTA AREA. ALL UPWARD AND
DOWNWARD FACING TRIANGLES REPRESENT STATISTICALLY SIGNIFICANT TRENDS FROM 1998-2001 (P<0.05),
CIRCLES REPRESENT LOCATIONS WITH NO SIGNIFICANT TRENDS. THE PINK STAR INDICATES THE SITE WITH THE
HIGHEST DESIGN VALUES IN 2011. LEFT PANEL SHOWS TRENDS IN MAY-SEPTEMBER 4™ HIGHEST 8-HOUR DAILY
MAXIMUM OZONE VALUES, CENTER PANEL SHOWS TRENDS IN MAY-SEPTEMBER MEAN 8-HOUR DAILY
MAXIMUM, AND LEFT PANEL SHOWS TRENDS IN MAY-SEPTEMBER MEDIAN 8-HOUR DAILY MAXIMUM OZONE
VALUES 21
FIGURE 20: MAP OF OZONE TRENDS AT SPECIFIC MONITOR LOCATIONS IN THE BALTIMORE/WASHINGTON D.C. AREA.
ALL UPWARD AND DOWNWARD FACING TRIANGLES REPRESENT STATISTICALLY SIGNIFICANT TRENDS FROM
1998-2001 (PO.05), CIRCLES REPRESENT LOCATIONS WITH NO SIGNIFICANT TRENDS. THE PINK STAR INDICATES
THE SITE WITH THE HIGHEST DESIGN VALUES IN 2011. LEFT PANEL SHOWS TRENDS IN MAY-SEPTEMBER 4™
HIGHEST 8-HOUR DAILY MAXIMUM OZONE VALUES, CENTER PANEL SHOWS TRENDS IN MAY-SEPTEMBER MEAN
8-HOUR DAILY MAXIMUM, AND LEFT PANEL SHOWS TRENDS IN MAY-SEPTEMBER MEDIAN 8-HOUR DAILY
MAXIMUM OZONE VALUES 22
FIGURE 21: MAP OF OZONE TRENDS AT SPECIFIC MONITOR LOCATIONS IN THE BOSTON AREA. ALL UPWARD AND
DOWNWARD FACING TRIANGLES REPRESENT STATISTICALLY SIGNIFICANT TRENDS FROM 1998-2001 (P<0.05),
CIRCLES REPRESENT LOCATIONS WITH NO SIGNIFICANT TRENDS. THE PINK STAR INDICATES THE SITE WITH THE
HIGHEST DESIGN VALUES IN 2011. LEFT PANEL SHOWS TRENDS IN MAY-SEPTEMBER 4™ HIGHEST 8-HOUR DAILY
MAXIMUM OZONE VALUES, CENTER PANEL SHOWS TRENDS IN MAY-SEPTEMBER MEAN 8-HOUR DAILY
MAXIMUM, AND LEFT PANEL SHOWS TRENDS IN MAY-SEPTEMBER MEDIAN 8-HOUR DAILY MAXIMUM OZONE
VALUES 23
FIGURE 22: MAP OF OZONE TRENDS AT SPECIFIC MONITOR LOCATIONS IN THE CLEVELAND AREA. ALL UPWARD AND
DOWNWARD FACING TRIANGLES REPRESENT STATISTICALLY SIGNIFICANT TRENDS FROM 1998-2001 (P<0.05),
CIRCLES REPRESENT LOCATIONS WITH NO SIGNIFICANT TRENDS. THE PINK STAR INDICATES THE SITE WITH THE
HIGHEST DESIGN VALUES IN 2011. LEFT PANEL SHOWS TRENDS IN MAY-SEPTEMBER 4™ HIGHEST 8-HOUR DAILY
MAXIMUM OZONE VALUES, CENTER PANEL SHOWS TRENDS IN MAY-SEPTEMBER MEAN 8-HOUR DAILY
MAXIMUM, AND LEFT PANEL SHOWS TRENDS IN MAY-SEPTEMBER MEDIAN 8-HOUR DAILY MAXIMUM OZONE
VALUES 24
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FIGURE 23: MAP OF OZONE TRENDS AT SPECIFIC MONITOR LOCATIONS IN THE DALLAS AREA. ALL UPWARD AND
DOWNWARD FACING TRIANGLES REPRESENT STATISTICALLY SIGNIFICANT TRENDS FROM 1998-2001 (P<0.05),
CIRCLES REPRESENT LOCATIONS WITH NO SIGNIFICANT TRENDS. THE PINK STAR INDICATES THE SITE WITH THE
HIGHEST DESIGN VALUES IN 2011. LEFT PANEL SHOWS TRENDS IN MAY-SEPTEMBER 4™ HIGHEST 8-HOUR DAILY
MAXIMUM OZONE VALUES, CENTER PANEL SHOWS TRENDS IN MAY-SEPTEMBER MEAN 8-HOUR DAILY
MAXIMUM, AND LEFT PANEL SHOWS TRENDS IN MAY-SEPTEMBER MEDIAN 8-HOUR DAILY MAXIMUM OZONE
VALUES 24
FIGURE 24: MAP OF OZONE TRENDS AT SPECIFIC MONITOR LOCATIONS IN THE DENVER AREA. ALL UPWARD AND
DOWNWARD FACING TRIANGLES REPRESENT STATISTICALLY SIGNIFICANT TRENDS FROM 1998-2001 (P<0.05),
CIRCLES REPRESENT LOCATIONS WITH NO SIGNIFICANT TRENDS. THE PINK STAR INDICATES THE SITE WITH THE
HIGHEST DESIGN VALUES IN 2011. LEFT PANEL SHOWS TRENDS IN MAY-SEPTEMBER 4™ HIGHEST 8-HOUR DAILY
MAXIMUM OZONE VALUES, CENTER PANEL SHOWS TRENDS IN MAY-SEPTEMBER MEAN 8-HOUR DAILY
MAXIMUM, AND LEFT PANEL SHOWS TRENDS IN MAY-SEPTEMBER MEDIAN 8-HOUR DAILY MAXIMUM OZONE
VALUES 25
FIGURE 25: MAP OF OZONE TRENDS AT SPECIFIC MONITOR LOCATIONS IN THE DETROIT AREA. ALL UPWARD AND
DOWNWARD FACING TRIANGLES REPRESENT STATISTICALLY SIGNIFICANT TRENDS FROM 1998-2001 (P<0.05),
CIRCLES REPRESENT LOCATIONS WITH NO SIGNIFICANT TRENDS. THE PINK STAR INDICATES THE SITE WITH THE
HIGHEST DESIGN VALUES IN 2011. LEFT PANEL SHOWS TRENDS IN MAY-SEPTEMBER 4™ HIGHEST 8-HOUR DAILY
MAXIMUM OZONE VALUES, CENTER PANEL SHOWS TRENDS IN MAY-SEPTEMBER MEAN 8-HOUR DAILY
MAXIMUM, AND LEFT PANEL SHOWS TRENDS IN MAY-SEPTEMBER MEDIAN 8-HOUR DAILY MAXIMUM OZONE
VALUES 26
FIGURE 26: MAP OF OZONE TRENDS AT SPECIFIC MONITOR LOCATIONS IN THE HOUSTON AREA. ALL UPWARD AND
DOWNWARD FACING TRIANGLES REPRESENT STATISTICALLY SIGNIFICANT TRENDS FROM 1998-2001 (P<0.05),
CIRCLES REPRESENT LOCATIONS WITH NO SIGNIFICANT TRENDS. THE PINK STAR INDICATES THE SITE WITH THE
HIGHEST DESIGN VALUES IN 2011. LEFT PANEL SHOWS TRENDS IN MAY-SEPTEMBER 4™ HIGHEST 8-HOUR DAILY
MAXIMUM OZONE VALUES, CENTER PANEL SHOWS TRENDS IN MAY-SEPTEMBER MEAN 8-HOUR DAILY
MAXIMUM, AND LEFT PANEL SHOWS TRENDS IN MAY-SEPTEMBER MEDIAN 8-HOUR DAILY MAXIMUM OZONE
VALUES 26
FIGURE 27: MAP OF OZONE TRENDS AT SPECIFIC MONITOR LOCATIONS IN THE Los ANGELES AREA. ALL UPWARD AND
DOWNWARD FACING TRIANGLES REPRESENT STATISTICALLY SIGNIFICANT TRENDS FROM 1998-2001 (P<0.05),
CIRCLES REPRESENT LOCATIONS WITH NO SIGNIFICANT TRENDS. THE PINK STAR INDICATES THE SITE WITH THE
HIGHEST DESIGN VALUES IN 2011. LEFT PANEL SHOWS TRENDS IN MAY-SEPTEMBER 4™ HIGHEST 8-HOUR DAILY
MAXIMUM OZONE VALUES, CENTER PANEL SHOWS TRENDS IN MAY-SEPTEMBER MEAN 8-HOUR DAILY
MAXIMUM, AND LEFT PANEL SHOWS TRENDS IN MAY-SEPTEMBER MEDIAN 8-HOUR DAILY MAXIMUM OZONE
VALUES 27
FIGURE 28: MAP OF OZONE TRENDS AT SPECIFIC MONITOR LOCATIONS IN THE PHILADELPHIA AREA. ALL UPWARD
AND DOWNWARD FACING TRIANGLES REPRESENT STATISTICALLY SIGNIFICANT TRENDS FROM 1998-2001
(PO.05), CIRCLES REPRESENT LOCATIONS WITH NO SIGNIFICANT TRENDS. THE PINK STAR INDICATES THE SITE
WITH THE HIGHEST DESIGN VALUES IN 2011. LEFT PANEL SHOWS TRENDS IN MAY-SEPTEMBER 4™ HIGHEST 8-
HOUR DAILY MAXIMUM OZONE VALUES, CENTER PANEL SHOWS TRENDS IN MAY-SEPTEMBER MEAN 8-HOUR
DAILY MAXIMUM, AND LEFT PANEL SHOWS TRENDS IN MAY-SEPTEMBER MEDIAN 8-HOUR DAILY MAXIMUM
OZONE VALUES 27
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FIGURE 29: MAP OF OZONE TRENDS AT SPECIFIC MONITOR LOCATIONS IN THE SACRAMENTO AREA. ALL UPWARD AND
DOWNWARD FACING TRIANGLES REPRESENT STATISTICALLY SIGNIFICANT TRENDS FROM 1998-2001 (P<0.05),
CIRCLES REPRESENT LOCATIONS WITH NO SIGNIFICANT TRENDS. THE PINK STAR INDICATES THE SITE WITH THE
HIGHEST DESIGN VALUES IN 2011. LEFT PANEL SHOWS TRENDS IN MAY-SEPTEMBER 4™ HIGHEST 8-HOUR DAILY
MAXIMUM OZONE VALUES, CENTER PANEL SHOWS TRENDS IN MAY-SEPTEMBER MEAN 8-HOUR DAILY
MAXIMUM, AND LEFT PANEL SHOWS TRENDS IN MAY-SEPTEMBER MEDIAN 8-HOUR DAILY MAXIMUM OZONE
VALUES 28
FIGURE 30: MAP OF OZONE TRENDS AT SPECIFIC MONITOR LOCATIONS IN THE SAINT Louis AREA. ALL UPWARD AND
DOWNWARD FACING TRIANGLES REPRESENT STATISTICALLY SIGNIFICANT TRENDS FROM 1998-2001 (P<0.05),
CIRCLES REPRESENT LOCATIONS WITH NO SIGNIFICANT TRENDS. THE PINK STAR INDICATES THE SITE WITH THE
HIGHEST DESIGN VALUES IN 2011. LEFT PANEL SHOWS TRENDS IN MAY-SEPTEMBER 4™ HIGHEST 8-HOUR DAILY
MAXIMUM OZONE VALUES, CENTER PANEL SHOWS TRENDS IN MAY-SEPTEMBER MEAN 8-HOUR DAILY
MAXIMUM, AND LEFT PANEL SHOWS TRENDS IN MAY-SEPTEMBER MEDIAN 8-HOUR DAILY MAXIMUM OZONE
VALUES 28
FIGURE 31: MAPS OF NOX AND VOC EMISSIONS BY SOURCE SECTOR FOR 2002, 2005, 2008, AND 2011 30
FIGURE 32: MAP OF NINE NOAA CLIMATE REGIONS THAT WERE USED TO AGGREGATE EMISSIONS AND AMBIENT
OZONE TRENDS. DOTS SHOW LOCATIONS OF OZONE MONITORS 31
FIGURE 33: PLOTS OF NOx AND VOC EMISSIONS TRENDS BY SOURCE SECTOR. EMISSIONS ARE AGGREGATED BY
NOAA CLIMATE REGION AND BY URBAN, RURAL, AND SUBURB AN LOCATION 32
FIGURE 34: DISTRIBUTIONS OF LOW POPULATION DENSITY (RURAL) MONITORS' O3 CONCENTRATIONS FOR DIFFERENT
SUBSETS OF MONTHS OVER A 13-YEAR PERIOD. FROM TOP TO BOTTOM IN EACH RIBBON PLOT, THE BLUE AND
WHITE LINES INDICATE THE SPATIAL MEAN OF THE 95™, 75™, 50™, 25™, AND 5™ PERCENTILES FOR EACH
MONITOR FOR EVERY YEAR FROM 1998-2011. TREND ARE SHOWN FOR 8 OF 9 NOAA CLIMATE REGIONS (THE
WEST NORTH CENTRAL REGION DID NOT CONTAIN ANY CASE-STUDY AREAS) 33
FIGURE 35: DISTRIBUTIONS OF HIGH POPULATION DENSITY MONITORS' O3 CONCENTRATIONS FOR DIFFERENT SUBSETS
OF MONTHS OVER A 13-YEAR PERIOD. FROM TOP TO BOTTOM IN EACH RIBBON PLOT, THE BLUE AND WHITE
LINES INDICATE THE SPATIAL MEAN OF THE 95™, 75™, 50™, 25™, AND 5™ PERCENTILES FOR EACH MONITOR FOR
EVERY YEAR FROM 1998-2011. TREND ARE SHOWN FOR EACH OF 8 OF 9 NOAA CLIMATE REGIONS (THE WEST
NORTH CENTRAL REGION DID NOT CONTAIN ANY CASE-STUDY AREAS) 34
FIGURE 36: RATIO OF JANUARY MONTHLY AVERAGE OZONE CONCENTRATIONS IN BRUTE FORCE 50% NOx EMISSIONS
REDUCTION CMAQ SIMULATION TO JANUARY MONTHLY AVERAGE OZONE CONCENTRATION IN THE 2007 BASE
CMAQ SIMULATION 35
FIGURE 37: RATIO OF JANUARY MONTHLY AVERAGE OZONE CONCENTRATIONS IN BRUTE FORCE 50% NOx AND VOC
EMISSIONS REDUCTION CMAQ SIMULATION TO JANUARY MONTHLY AVERAGE OZONE CONCENTRATION IN THE
2007 BASE CMAQ SIMULATION 36
FIGURE 38: RATIO OF JANUARY MONTHLY AVERAGE OZONE CONCENTRATIONS IN BRUTE FORCE 50% NOx AND VOC
EMISSIONS REDUCTION CMAQ SIMULATION TO JANUARY MONTHLY AVERAGE OZONE CONCENTRATION IN THE
2007 BASE CMAQ SIMULATION 36
FIGURE 39: RATIO OF JANUARY MONTHLY AVERAGE OZONE CONCENTRATIONS IN BRUTE FORCE 90% NOx AND
EMISSIONS REDUCTION CMAQ SIMULATION TO JANUARY MONTHLY AVERAGE OZONE CONCENTRATION IN THE
2007 BASE CMAQ SIMULATION 37
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FIGURE 40: RATIO OF APRIL-OCTOBER SEASONAL AVERAGE OZONE CONCENTRATIONS IN BRUTE FORCE 50% NOx
EMISSIONS REDUCTION CMAQ SIMULATION TO APRIL-OCTOBER SEASONAL AVERAGE OZONE CONCENTRATION
IN THE 2007 BASE CMAQ SIMULATION 37
FIGURE 41: RATIO OF APRIL-OCTOBER SEASONAL AVERAGE OZONE CONCENTRATIONS IN BRUTE FORCE 50% NOx
AND VOC EMISSIONS REDUCTION CMAQ SIMULATION TO APRIL-OCTOBER SEASONAL AVERAGE OZONE
CONCENTRATION IN THE 2007 BASE CMAQ SIMULATION 38
FIGURE 42: RATIO OF APRIL-OCTOBER SEASONAL AVERAGE OZONE CONCENTRATIONS IN BRUTE FORCE 90% NOx
EMISSIONS REDUCTION CMAQ SIMULATION TO APRIL-OCTOBER SEASONAL AVERAGE OZONE CONCENTRATION
IN THE 2007 BASE CMAQ SIMULATION 38
FIGURE 43: RATIO OF APRIL-OCTOBER SEASONAL AVERAGE OZONE CONCENTRATIONS IN BRUTE FORCE 90% NOx
AND VOC EMISSIONS REDUCTION CMAQ SIMULATION TO APRIL-OCTOBER SEASONAL AVERAGE OZONE
CONCENTRATION IN THE 2007 BASE CMAQ SIMULATION 39
FIGURE 44: RATIO OF MAY-SEPTEMBER SEASONAL AVERAGE OZONE CONCENTRATIONS IN BRUTE FORCE 50% NOx
EMISSIONS REDUCTION CMAQ SIMULATION TO MAY-SEPTEMBER SEASONAL AVERAGE OZONE CONCENTRATION
IN THE 2007 BASE CMAQ SIMULATION 39
FIGURE 45: RATIO OF MAY-SEPTEMBER SEASONAL AVERAGE OZONE CONCENTRATIONS IN BRUTE FORCE 50% NOx
AND VOC EMISSIONS REDUCTION CMAQ SIMULATION TO MAY-SEPTEMBER SEASONAL AVERAGE OZONE
CONCENTRATION IN THE 2007 BASE CMAQ SIMULATION 40
FIGURE 46: RATIO OF MAY-SEPTEMBER SEASONAL AVERAGE OZONE CONCENTRATIONS IN BRUTE FORCE 90% NOx
EMISSIONS REDUCTION CMAQ SIMULATION TO MAY-SEPTEMBER SEASONAL AVERAGE OZONE CONCENTRATION
IN THE 2007 BASE CMAQ SIMULATION 41
FIGURE 47: RATIO OF MAY-SEPTEMBER SEASONAL AVERAGE OZONE CONCENTRATIONS IN BRUTE FORCE 90% NOx
AND VOC EMISSIONS REDUCTION CMAQ SIMULATION TO MAY-SEPTEMBER SEASONAL AVERAGE OZONE
CONCENTRATION IN THE 2007 BASE CMAQ SIMULATION 41
FIGURE 48: DENSITY SCATTER PLOT COMPARING MODELED MONTHLY MEAN OZONE IN THE 2007 BASE CMAQ
SIMULATION TO MODELED MONTHLY MEAN OZONE IN THE EMISSIONS REDUCTION CMAQ SIMULATIONS.
COLORS DEPICT THE NUMBER OF POINTS OCCURRING AT ANY LOCATION ON THE SCATTER PLOT 42
FIGURE 49: DENSITY SCATTER PLOT COMPARING MODELED MONTHLY MEAN OZONE IN THE 2007 BASE CMAQ
SIMULATION TO THE RELATIVE CHANGE IN MONTHLY MEAN OZONE FROM THE EMISSIONS REDUCTION CMAQ
SIMULATIONS. RELATIVE CHANGE IS SHOWN AS THE RATIO OF OZONE IN THE EMISSIONS REDUCTION
SIMULATION TO OZONE IN THE 2007 BASE SIMULATION. COLORS DEPICT THE NUMBER OF PEOPLE LIVING IN
AREAS THAT FALL AT ANY LOCATION ON THE SCATTER PLOT 43
FIGURE 50: P POPULATIONS LIVING IN LOCATIONS WITH VARIOUS RANGES OF RATIOS OF MONTHLY MEAN OZONE IN
THE NOX REDUCTION SIMULATIONS TO MONTHLY MEAN OZONE IN THE 2007 BASE CMAQ SIMULATION. EIGHT
DIFFERENT MONTHLY RATIOS ARE SHOWN IN EACH PANEL (JANUARY, APRIL-OCTOBER). PANELS SPLIT
POPULATION BY 9 CLIMATE REGIONS, URBAN CASE STUDY AREA VS NON-URBAN CASE STUDY AREA, URBAN
VERSUS NON-URBAN AND 50% NOX REDUCTION SCENARIO VS 90% NOX REDUCTION SCENARIO 45
FIGURE 51: POPULATIONS LIVING IN LOCATIONS WITH VARIOUS RANGES OF RATIOS OF MONTHLY MEAN OZONE IN THE
COMBINED NOX AND VOC REDUCTION SIMULATIONS TO MONTHLY MEAN OZONE IN THE 2007 BASE CMAQ
SIMULATION. EIGHT DIFFERENT MONTHLY RATIOS ARE SHOWN IN EACH PANEL (JANUARY, APRIL-OCTOBER).
PANELS SPLIT POPULATION BY 9 CLIMATE REGIONS, URBAN CASE STUDY AREA vs NON-URBAN CASE STUDY
AREA, URBAN VERSUS NON-URBAN AND 50% NOX/VOC REDUCTION SCENARIO VS 90% NOX/VOC REDUCTION
SCENARIO 46
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FIGURE 52: PERCENT OF POPULATION LIVING IN LOCATIONS WITH VARIOUS RANGES OF RATIOS OF MONTHLY MEAN
OZONE IN THE FOUR EMISSIONS REDUCTION SIMULATIONS TO MONTHLY MEAN OZONE IN THE 2007 BASE CMAQ
SIMULATION. EIGHT DIFFERENT MONTHLY RATIOS ARE SHOWN IN EACH PANEL (JANUARY, APRIL-OCTOBER).
PANELS SPLIT POPULATION BY 15 URBAN CASE-STUDY AREAS AND BY FOUR EMISSIONS REDUCTION
SIMULATIONS: FROM TOP TO BOTTOM, 50% NOx REDUCTION, 90% NOx REDUCTION, 50% NOx AND VOC
REDUCTION, 90% NOX AND VOC REDUCTION 47
FIGURE 53: HISTOGRAMS OF US POPULATION LIVING IN LOCATIONS WITH INCREASING AND DECREASING MEAN
OZONE. VALUES ON THE X-AXIS REPRESENT THE RATIO OF MEAN OZONE IN THE 50% NOx cur CMAQ
SIMULATION TO THE MEAN OZONE IN THE 2007 BASE CMAQ SIMULATION. THE PERCENTAGES OF THE US
POPULATION LIVING IN AREAS THAT HAVE RATIOS LESS THAN 0.95, FROM 0.95 TO 1.05 AND GREATER THAN 1.05
ARE SHOWN ON THE Y-AXIS. LEFT PLOTS SHOW POPULATION NUMBERS IN LOCATIONS NOT INCLUDED IN ONE OF
THE URBAN CASE STUDY AREAS WHILE RIGHT PLOTS SHOW POPULATION NUMBERS IN LOCATIONS INCLUDED IN
ONE OF THE URBAN CASE STUDY AREAS. TOP PLOTS SHOW RATIOS OF JANUARY MONTHLY MEAN OZONE,
MIDDLE PLOTS SHOW RATIOS OF SEASON MEAN JUNE-AUGUST OZONE, AND BOTTOM PLOTS SHOW RATIOS OF
SEASONAL MEAN APRIL-OCTOBER OZONE 48
FIGURE 54: HISTOGRAMS OF US POPULATION LIVING IN LOCATIONS WITH INCREASING AND DECREASING MEAN
OZONE. VALUES ON THE X-AXIS REPRESENT THE RATIO OF MEAN OZONE IN THE 50% NOx AND VOC CUT
CMAQ SIMULATION TO THE MEAN OZONE IN THE 2007 BASE CMAQ SIMULATION. THE PERCENTAGES OF THE
US POPULATION LIVING IN AREAS THAT HAVE RATIOS LESS THAN 0.95, FROM 0.95 TO 1.05 AND GREATER THAN
1.05 ARE SHOWN ON THE Y-AXIS. LEFT PLOTS SHOW POPULATION NUMBERS IN LOCATIONS NOT INCLUDED IN
ONE OF THE URBAN CASE STUDY AREAS WHILE RIGHT PLOTS SHOW POPULATION NUMBERS IN LOCATIONS
INCLUDED IN ONE OF THE URBAN CASE STUDY AREAS. TOP PLOTS SHOW RATIOS OF JANUARY MONTHLY MEAN
OZONE, MIDDLE PLOTS SHOW RATIOS OF SEASON MEAN JUNE-AUGUST OZONE, AND BOTTOM PLOTS SHOW
RATIOS OF SEASONAL MEAN APRIL-OCTOBER OZONE 49
FIGURE 55: HISTOGRAMS OF US POPULATION LIVING IN LOCATIONS WITH INCREASING AND DECREASING MEAN
OZONE. VALUES ON THE X-AXIS REPRESENT THE RATIO OF MEAN OZONE IN THE 90% NOx cur CMAQ
SIMULATION TO THE MEAN OZONE IN THE 2007 BASE CMAQ SIMULATION. THE PERCENTAGES OF THE US
POPULATION LIVING IN AREAS THAT HAVE RATIOS LESS THAN 0.95, FROM 0.95 TO 1.05 AND GREATER THAN 1.05
ARE SHOWN ON THE Y-AXIS. LEFT PLOTS SHOW POPULATION NUMBERS IN LOCATIONS NOT INCLUDED IN ONE OF
THE URBAN CASE STUDY AREAS WHILE RIGHT PLOTS SHOW POPULATION NUMBERS IN LOCATIONS INCLUDED IN
ONE OF THE URBAN CASE STUDY AREAS. TOP PLOTS SHOW RATIOS OF JANUARY MONTHLY MEAN OZONE,
MIDDLE PLOTS SHOW RATIOS OF SEASON MEAN JUNE-AUGUST OZONE, AND BOTTOM PLOTS SHOW RATIOS OF
SEASONAL MEAN APRIL-OCTOBER OZONE 50
FIGURE 56: HISTOGRAMS OF US POPULATION LIVING IN LOCATIONS WITH INCREASING AND DECREASING MEAN
OZONE. VALUES ON THE X-AXIS REPRESENT THE RATIO OF MEAN OZONE IN THE 90% NOx AND VOC CUT
CMAQ SIMULATION TO THE MEAN OZONE IN THE 2007 BASE CMAQ SIMULATION. THE PERCENTAGES OF THE
US POPULATION LIVING IN AREAS THAT HAVE RATIOS LESS THAN 0.95, FROM 0.95 TO 1.05 AND GREATER THAN
1.05 ARE SHOWN ON THE Y-AXIS. LEFT PLOTS SHOW POPULATION NUMBERS IN LOCATIONS NOT INCLUDED IN
ONE OF THE URBAN CASE STUDY AREAS WHILE RIGHT PLOTS SHOW POPULATION NUMBERS IN LOCATIONS
INCLUDED IN ONE OF THE URBAN CASE STUDY AREAS. TOP PLOTS SHOW RATIOS OF JANUARY MONTHLY MEAN
OZONE, MIDDLE PLOTS SHOW RATIOS OF SEASON MEAN JUNE-AUGUST OZONE, AND BOTTOM PLOTS SHOW
RATIOS OF SEASONAL MEAN APRIL-OCTOBER OZONE 51
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FIGURE 57: HISTOGRAMS OF US POPULATION LIVING IN LOCATIONS WITH INCREASING AND DECREASING MEAN
OZONE. VALUES ON THE X-AXIS REPRESENT THE ABSOLUTE (PPB) CHANGE OF MEAN OZONE FROM THE 2007
BASE CMAQ SIMULATION TO THE 50% NOX CUT CMAQ SIMULATION TO THE MEAN OZONE IN THE 2007 BASE
CMAQ SIMULATION. THE PERCENTAGES OF THE US POPULATION LIVING IN AREAS THAT HAVE CHANGES LESS
THAN -1 PPB, BETWEEN -1 AND +1 PPB AND GREATER THAN +1 PPB ARE SHOWN ON THE Y-AXIS. LEFT PLOTS
SHOW POPULATION NUMBERS IN LOCATIONS NOT INCLUDED IN ONE OF THE CASE STUDY AREAS WHILE RIGHT
PLOTS SHOW POPULATION NUMBERS IN LOCATIONS INCLUDED IN ONE OF THE CASE STUDY AREAS. TOP PLOTS
SHOW RATIOS OF JANUARY MONTHLY MEAN OZONE, MIDDLE PLOTS SHOW RATIOS OF SEASON MEAN JUNE-
AUGUST OZONE, AND BOTTOM PLOTS SHOW RATIOS OF SEASONAL MEAN APRIL-OCTOBER OZONE 52
FIGURE 58: HISTOGRAMS OF US POPULATION LIVING IN LOCATIONS WITH INCREASING AND DECREASING MEAN
OZONE. VALUES ON THE X-AXIS REPRESENT THE ABSOLUTE (PPB) CHANGE OF MEAN OZONE FROM THE 2007
BASE CMAQ SIMULATION TO THE 50% NOX AND VOC CUT CMAQ SIMULATION TO THE MEAN OZONE IN THE
2007 BASE CMAQ SIMULATION. THE PERCENTAGES OF THE US POPULATION LIVING IN AREAS THAT HAVE
CHANGES LESS THAN -1 PPB, BETWEEN -1 AND +1 PPB AND GREATER THAN +1 PPB ARE SHOWN ON THE Y-AXIS.
LEFT PLOTS SHOW POPULATION NUMBERS IN LOCATIONS NOT INCLUDED IN ONE OF THE CASE STUDY AREAS
WHILE RIGHT PLOTS SHOW POPULATION NUMBERS IN LOCATIONS INCLUDED IN ONE OF THE CASE STUDY AREAS.
TOP PLOTS SHOW RATIOS OF JANUARY MONTHLY MEAN OZONE, MIDDLE PLOTS SHOW RATIOS OF SEASON MEAN
JUNE-AUGUST OZONE, AND BOTTOM PLOTS SHOW RATIOS OF SEASONAL MEAN APRIL-OCTOBER OZONE 53
FIGURE 59: HISTOGRAMS OF US POPULATION LIVING IN LOCATIONS WITH INCREASING AND DECREASING MEAN
OZONE. VALUES ON THE X-AXIS REPRESENT THE ABSOLUTE (PPB) CHANGE OF MEAN OZONE FROM THE 2007
BASE CMAQ SIMULATION TO THE 90% NOX CUT CMAQ SIMULATION TO THE MEAN OZONE IN THE 2007 BASE
CMAQ SIMULATION. THE PERCENTAGES OF THE US POPULATION LIVING IN AREAS THAT HAVE CHANGES LESS
THAN -1 PPB, BETWEEN -1 AND +1 PPB AND GREATER THAN +1 PPB ARE SHOWN ON THE Y-AXIS. LEFT PLOTS
SHOW POPULATION NUMBERS IN LOCATIONS NOT INCLUDED IN ONE OF THE CASE STUDY AREAS WHILE RIGHT
PLOTS SHOW POPULATION NUMBERS IN LOCATIONS INCLUDED IN ONE OF THE CASE STUDY AREAS. TOP PLOTS
SHOW RATIOS OF JANUARY MONTHLY MEAN OZONE, MIDDLE PLOTS SHOW RATIOS OF SEASON MEAN JUNE-
AUGUST OZONE, AND BOTTOM PLOTS SHOW RATIOS OF SEASONAL MEAN APRIL-OCTOBER OZONE 54
FIGURE 60: HISTOGRAMS OF US POPULATION LIVING IN LOCATIONS WITH INCREASING AND DECREASING MEAN
OZONE. VALUES ON THE X-AXIS REPRESENT THE ABSOLUTE (PPB) CHANGE OF MEAN OZONE FROM THE 2007
BASE CMAQ SIMULATION TO THE 90% NOX AND VOC CUT CMAQ SIMULATION TO THE MEAN OZONE IN THE
2007 BASE CMAQ SIMULATION. THE PERCENTAGES OF THE US POPULATION LIVING IN AREAS THAT HAVE
CHANGES LESS THAN -1 PPB, BETWEEN -1 AND +1 PPB AND GREATER THAN +1 PPB ARE SHOWN ON THE Y-AXIS.
LEFT PLOTS SHOW POPULATION NUMBERS IN LOCATIONS NOT INCLUDED IN ONE OF THE CASE STUDY AREAS
WHILE RIGHT PLOTS SHOW POPULATION NUMBERS IN LOCATIONS INCLUDED IN ONE OF THE CASE STUDY AREAS.
TOP PLOTS SHOW RATIOS OF JANUARY MONTHLY MEAN OZONE, MIDDLE PLOTS SHOW RATIOS OF SEASON MEAN
JUNE-AUGUST OZONE, AND BOTTOM PLOTS SHOW RATIOS OF SEASONAL MEAN APRIL-OCTOBER OZONE 55
-------
Table of Tables
TABLE 1: PERCENTAGE OF US POPULATION LIVING IN LOCATIONS WITH INCREASING AND DECREASING MEAN OZONE
FOR THE 50% NOX REDUCTION AND 90% NOX REDUCTIONS CMAQ SIMULATIONS BROKEN DOWN BY
DIFFERENT SEASONAL AND MONTHLY TIME PERIODS 56
TABLE 2: PERCENTAGE OF US POPULATION LIVING IN LOCATIONS WITH INCREASING AND DECREASING APRIL-
OCTOBER SEASONAL MEAN OZONE IN THE 50% NOX REDUCTION AND 90% NOX REDUCTIONS CMAQ
SIMULATIONS BROKEN DOWN BY HIGH AND LOW-MID POPULATION DENSITY AREAS 57
TABLE 3: PERCENTAGE OF US POPULATION LIVING IN LOCATIONS WITH INCREASING AND DECREASING APRIL-
OCTOBER SEASONAL MEAN OZONE IN THE 50% NOX REDUCTION AND 90% NOX REDUCTION CMAQ
SIMULATIONS BROKEN DOWN BY 15 CASE STUDY AREAS 58
-------
This appendix provides additional plots and information to support the analysis provided
in section 8.2.3 of the main text of the health REA.
1. AMBIENT TRENDS OVER A PERIOD OF NATIONALLY
DECREASING NOX EMISSIONS
1.1 NATIONWIDE MAPS SHOWING ABSOLUTE CHANGES IN OZONE BETWEEN
2001-2003 AND 2008-2010
In Chapter 8 we provided maps of US ozone monitors showing absolute changes in ozone
percentiles between a 3-year period before many of the nationwide NOx reductions took place
(2001-2003) and a period after many of these reductions took place (2008-2010). Here we
provide a full set of maps which includes not only the behavior of the 50th and 95th percentiles
but also 5*, 25 , and 75* percentiles for three different groupings of months: short summer
season (June-August), longer warm season (April-October), and all year. These plots further
support the general trends that were noted in chapter 8: ozone increases occurred more in cooler
months than warmer months, ozone increases occurred more at the lower end of the distribution
that the upper end of the distribution, and ozone increases were more likely to occur in urban
core area than at locations further from the city centers. The plots of 95* percentile ozone
changes show that high ozone days have decreased across the country at all times of year. The
June-August plots show that mid-range ozone has also decreased at most locations during the
warmest time of year when ozone levels are highest.
-------
Change in June -August 5th Percentile Daily Maximum 8-hour Ozone Concentration from 2001 - 2003 to 2008 - 2010
Increase 10+ ppb
Increase 5 ppb
No Change
Decrease 5 ppb
Decrease 10+ppb
Figure 1: Change in 5th percentile June-August summer season daily 8-hour maximum
ozone concentrations between 2001-2003 and 2008-2010.
Change in June - August 25th Percentile Daily Maximum 8-hour Ozone Concentration from 2001 - 2003 to 2008 - 2010
Increase 10+ ppb
Increase 5 ppb
No Change
Decrease 5 ppb
Decrease 10+ppb
Figure 2: Change in 25th percentile June-August summer season daily 8-hour maximum
ozone concentrations between 2001-2003 and 2008-2010.
-------
Change in June - August Median Daily Maximum 8-hour Ozone Concentration from 2001 - 2003 to 2008 - 2010
Increase 10+ ppb
4 Increase 5 ppb
0 No Change
» Decrease 5 ppb
T Decrease 10+ppb
Figure 3: Change in 50th percentile June-August summer season daily 8-hour maximum
ozone concentrations between 2001-2003 and 2008-2010.
Change in June - August 75th Percentile Daily Maximum 8-hour Ozone Concentration from 2001 - 2003 to 2008 - 2010
,.?r
Increase 10+ppb
Increase 5 ppb
No Change
Decrease 5 ppb
Decrease 10+ppb
Figure 4: Change in 75th percentile June-August summer season daily 8-hour maximum
ozone concentrations between 2001-2003 and 2008-2010.
-------
Change in June -August 95th Percentile Daily Maximum 8-hour Ozone Concentration from 2001 - 2003 to 2008 - 2010
Increase 10+ ppb
4 Increase 5 ppb
0 No Change
» Decrease 5 ppb
T Decrease 10+ppb
Figure 5: Change in 95th percentile June-August summer season daily 8-hour maximum
ozone concentrations between 2001-2003 and 2008-2010.
Change in April - October 5th Percentile Daily Maximum 8-hour Ozone Concentration from 2001 - 2003 to 2008 - 2010
Increase 10+ ppb
Increase 5 ppb
No Change
Decrease 5 ppb
Decrease 10+ppb
Figure 6: Change in 5th percentile April-October summer season daily 8-hour maximum
ozone concentrations between 2001-2003 and 2008-2010.
-------
Change in April - October 25th Percentile Daily Maximum 8-hour Ozone Concentration from 2001 - 2003 to 2008 - 2010
Increase 10+ ppb
Increase 5 ppb
No Change
Decrease 5 ppb
Decrease 10+ppb
Figure 7: Change in 25th percentile April-October summer season daily 8-hour maximum
ozone concentrations between 2001-2003 and 2008-2010.
Change in April - October Median Daily Maximum 8-hour Ozone Concentration from 2001 - 2003 to 2008 - 2010
Increase 10+ppb
Increase 5 ppb
No Change
Decrease 5 ppb
Decrease 10+ppb
Figure 8: Change in 50th percentile April-October summer season daily 8-hour maximum
ozone concentrations between 2001-2003 and 2008-2010.
-------
Change in April - October 75th Percentile Daily Maximum 8-hour Ozone Concentration from 2001 - 2003 to 2008 - 2010
Increase 10+ ppb
Increase 5 ppb
No Change
Decrease 5 ppb
Decrease 10+ppb
Figure 9: Change in 75th percentile April-October summer season daily 8-hour maximum
ozone concentrations between 2001-2003 and 2008-2010.
Change in April - October 95th Percentile Daily Maximum 8-hour Ozone Concentration from 2001 - 2003 to 2008 - 2010
Increase 10+ppb
Increase 5 ppb
No Change
Decrease 5 ppb
Decrease 10+ppb
Figure 10: Change in 95th percentile April-October summer season daily 8-hour maximum
ozone concentrations between 2001-2003 and 2008-2010.
-------
Change in January - December 5th Percentile Daily Maximum 8-hour Ozone Concentration from 2001 - 2003 to 2008 - 2010
Increase 10+ ppb
*• i * Increase 5 ppb
No Change
Decrease 5 ppb
Decrease 10+ppb
Figure 11: Change in 5th percentile annual daily 8-hour maximum ozone concentrations
between 2001-2003 and 2008-2010.
Change in January - December 25th Percentile Daily Maximum 8-hour Ozone Concentration from 2001 - 2003 to 2008 - 2010
Increase 10+ppb
Increase 5 ppb
No Change
Decrease 5 ppb
Decrease 10+ppb
Figure 12: Change in 25th percentile annual daily 8-hour maximum ozone concentrations
between 2001-2003 and 2008-2010.
-------
Change in January - December Median Daily Maximum 8-hour Ozone Concentration from 2001 - 2003 to 2008 - 2010
Increase 10+ppb
Increase 5 ppb
No Change
Decrease 5 ppb
Decrease 10+ppb
Figure 13: Change in 50th percentile annual daily 8-hour maximum ozone concentrations
between 2001-2003 and 2008-2010.
Change in January - December 75th Percentile Daily Maximum 8-hour Ozone Concentration from 2001 - 2003 to 2008 - 2010
Increase 10+ ppb
Increase 5 ppb
No Change
Decrease 5 ppb
Decrease 10+ppb
Figure 14: Change in 75th percentile annual daily 8-hour maximum ozone concentrations
between 2001-2003 and 2008-2010.
-------
Change in January - December 95th Percentile Daily Maximum 8-hour Ozone Concentration from 2001 - 2003 to 2008 - 2010
Increase 10+ppb
Increase 5 ppb
No Change
Decrease 5 ppb
Decrease 10+ppb
Figure 15: Change in 95th percentile annual daily 8-hour maximum ozone concentrations
between 2001-2003 and 2008-2010.
1.2 THIRTEEN-YEAR OZONE TRENDS ACROSS THE COUNTRY AND IN CASE-
STUDY AREAS
An initial illustrative summary of the Os trends by the categories described in Section
8.2.4 of the main text is shown in Figure 16, where the trend for annual medians of each monitor
under study are displayed as separate lines. Although it generally illustrates the range in which
average concentrations of Os tend to fall (often 40-60 ppb), the simplicity of the plot makes it
difficult to discern either spatial or temporal trends. Information about other parts of the annual
distribution are also likely to be useful. To concisely display many different distributions in the
same template of panels as Figure 16, kernel density estimates (KDEs) of the data were
calculated. This process is displayed in Figure 17.
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Boston Chicago Cfcvc-land Dwlln
Q*4rott Houston Los Angsts Mew York PhHwfelphJa Sacramento Salm Louis Washington
V
/v.
g-
o
1
Year
Figure 16: Annual medians of O3 concentrations at each monitor based on different
subsets of months.
Figure 17 visually illustrates the process of forming and display a KDE from a year of O^
data from a single monitoring site. This raw data is displayed in the top panel as a time series of
Os concentrations. A KDE is then formed from the raw data, which is similar in principle to a
histogram, which gives counts of data that fall within user-defined bins. However, the KDE
"smoothes" out the histogram so that arbitrary bins do not need to be set, and converts the counts
to a "density". The density can yield a probability if desired, but that is beyond the scope of this
display; for our purposes, a higher density for a given concentration simply means that more 63
measurements were collected near that value compared to other possible concentrations. The
curve of the KDE can then be converted to a color stripe as shown in the bottom panel of Figure
17, where the color is related to the height of the curve in the middle panel.
-------
1) RawOS Daily Data
O
O 80-
Apr 1999
2) Kernel Density Estimate
Max 8-hr daily O3 Cone
3) Converting the KDE to a color stripe
O3 Prob
Dens
Max 8-hr daily O3 Cone
Figure 17: Procedure for creating the display of O3 distributions shown in Figure 18
001
0.001
0.0001
le-05
Each year of data shown in the groups in Figure 16 was thus converted to a color-based
KDE as shown in Figure 17, and the resulting collection of KDEs is shown in Figure 18. Annual
medians and modes of the distributions across all monitors in each group indicated by the plot's
panels are also shown, with color indicating the direction of the trend over time. Statistical
significance for multi-year ozone trends was determined using the Spearman rank order
correlation coefficient (p-value < 0.05). The general pattern of KDEs over time appears to be
either small or insignificant changes to the central tendencies of the distributions (i.e. mode and
median), but with a "condensing" of the concentration to the 40-50 ppb range, meaning that
lower concentrations grow and high concentrations decrease.
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C h icago Cbvalind Dallas Owner Ihrirofl Hwrelwr LOT Angela New Ywk PWtadelphta Sacnnwnto Siirt Louis Washington
i
•;**
Trend
Chars
— Signil:Neg
Signif:Pos
InsignifiNeg
InsigniliPos
Figure 18: KDEs of groups of monitors' annual O3 concentrations for different subsets of
months, shown on a linear color scale. The modes and medians of these
concentrations across the year and monitors for each group are shown in the
overlaying lines.
Section 8.2.3 in the main text provided maps showing summertime (May-September)
ozone trends at specific monitor locations within two urban case study areas. Here, we provide
similar maps for the other 13 case study areas. In section 8.2.3 we described the general trend of
fourth high ozone values decreasing in most locations while mean and median values were more
likely to increase in core urban areas and decrease in surrounding suburban and rural areas. In
addition, in most cities, the monitor with the highest design values did not occur in the urban
core. These trends were demonstrated by maps of the New York and Chicago areas in the main
text. Here we see that the trends are visible in many other urban case study areas, including
Baltimore, Boston, Cleveland, Denver, Houston, Los Angeles, and Saint Louis. However, ozone
trends in a few urban areas exhibit different behavior. In Atlanta and Sacramento, the highest
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design value monitor occurs near the urban core. In Atlanta, mid-range ozone has statistically
significant decreases trends at monitors both in the urbanized and in the surrounding area. All
urban monitors in Detroit and Sacramento showed no significant trend in either mean or median
ozone values. In Dallas, significant increases in mid-range ozone occurred at sites outside of the
urban core. Finally in Philadelphia, there was no statistically significant trend at any monitor for
the fourth highest 8-hour daily maximum ozone value.
Max4
Mean
Median
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Figure 19: Map of ozone trends at specific monitor locations in the Atlanta area. All
upward and downward facing triangles represent statistically significant
trends from 1998-2001 (p<0.05), circles represent locations with no
significant trends. The pink star indicates the site with the highest design
values in 2011. Left panel shows trends in May-September 4th highest 8-hour
daily maximum ozone values, center panel shows trends in May-September
mean 8-hour daily maximum, and left panel shows trends in May-September
median 8-hour daily maximum ozone values.
-------
Max4
Mean
Median
Use in
Epi Studies
O Not In Epi Study
O Zanobetti
Trend
Direction
Insignificant
V Negative
A Positive
Figure 20: Map of ozone trends at specific monitor locations in the Baltimore/Washington
D.C. area. All upward and downward facing triangles represent statistically
significant trends from 1998-2001 (p<0.05), circles represent locations with
no significant trends. The pink star indicates the site with the highest design
values in 2011. Left panel shows trends in May-September 4th highest 8-hour
daily maximum ozone values, center panel shows trends in May-September
mean 8-hour daily maximum, and left panel shows trends in May-September
median 8-hour daily maximum ozone values.
-------
Mean
Median
Mancfiester
• X» Lawrence?
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Epi Studies
O Not In Epi Study
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O Zanobetti
Trend
Direction
Insignificant
V Negative
A Positive
Figure 21: Map of ozone trends at specific monitor locations in the Boston area. All
upward and downward facing triangles represent statistically significant
trends from 1998-2001 (p<0.05), circles represent locations with no
significant trends. The pink star indicates the site with the highest design
values in 2011. Left panel shows trends in May-September 4th highest 8-hour
daily maximum ozone values, center panel shows trends in May-September
mean 8-hour daily maximum, and left panel shows trends in May-September
median 8-hour daily maximum ozone values.
-------
Use in
Epi Studies
O Not In Epi Study
O Smith + Zano
Trend
Direction
Insignificant
V Negative
A Positive
Figure 22: Map of ozone trends at specific monitor locations in the Cleveland area. All
upward and downward facing triangles represent statistically significant
trends from 1998-2001 (p<0.05), circles represent locations with no
significant trends. The pink star indicates the site with the highest design
values in 2011. Left panel shows trends in May-September 4* highest 8-hour
daily maximum ozone values, center panel shows trends in May-September
mean 8-hour daily maximum, and left panel shows trends in May-September
median 8-hour daily maximum ozone values.
Median
Denton
Fort Worth
Fort Worth
A
Trend
Direction
Insignificant
V Negative
A Positive
Use in
Epi Studies
O Not In Epi Study
Figure 23: Map of ozone trends at specific monitor locations in the Dallas area. All
upward and downward facing triangles represent statistically significant
trends from 1998-2001 (p<0.05), circles represent locations with no
significant trends. The pink star indicates the site with the highest design
values in 2011. Left panel shows trends in May-September 4th highest 8-hour
daily maximum ozone values, center panel shows trends in May-September
mean 8-hour daily maximum, and left panel shows trends in May-September
median 8-hour daily maximum ozone values.
-------
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v
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V I
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O Not In Epi Study
O Smith
O Smith + Zano
Trend
Direction
Insignificant
V Negative
A Positive
Figure 24: Map of ozone trends at specific monitor locations in the Denver area. All
upward and downward facing triangles represent statistically significant
trends from 1998-2001 (p<0.05), circles represent locations with no
significant trends. The pink star indicates the site with the highest design
values in 2011. Left panel shows trends in May-September 4th highest 8-hour
daily maximum ozone values, center panel shows trends in May-September
mean 8-hour daily maximum, and left panel shows trends in May-September
median 8-hour daily maximum ozone values.
Max4
Livonia
I .^Detroit
Dearborn' \
Use in
Epi Studies
O Not In Epi Study
O Smith + Zano
Trend
Direction
Insignificant
V Negative
-------
Figure 25: Map of ozone trends at specific monitor locations in the Detroit area. All
upward and downward facing triangles represent statistically significant
trends from 1998-2001 (p<0.05), circles represent locations with no
significant trends. The pink star indicates the site with the highest design
values in 2011. Left panel shows trends in May-September 4th highest 8-hour
daily maximum ozone values, center panel shows trends in May-September
mean 8-hour daily maximum, and left panel shows trends in May-September
median 8-hour daily maximum ozone values.
Max4
Mean
Median
Use in
Epi Studies
O Not In Epi Study
O Smith+ Zano
Trend
Direction
Insignificant
V Negative
A Positive
Figure 26: Map of ozone trends at specific monitor locations in the Houston area. All
upward and downward facing triangles represent statistically significant
trends from 1998-2001 (p<0.05), circles represent locations with no
significant trends. The pink star indicates the site with the highest design
values in 2011. Left panel shows trends in May-September 4th highest 8-hour
daily maximum ozone values, center panel shows trends in May-September
mean 8-hour daily maximum, and left panel shows trends in May-September
median 8-hour daily maximum ozone values.
-------
Max4
Mean
Median
Use in
Epi Studies
O Not In Epi Study
O Smith + Zano
Trend
Direction
Insignificant
V Negative
A Positive
Figure 27: Map of ozone trends at specific monitor locations in the Los Angeles area. All
upward and downward facing triangles represent statistically significant
trends from 1998-2001 (p<0.05), circles represent locations with no
significant trends. The pink star indicates the site with the highest design
values in 2011. Left panel shows trends in May-September 4th highest 8-hour
daily maximum ozone values, center panel shows trends in May-September
mean 8-hour daily maximum, and left panel shows trends in May-September
median 8-hour daily maximum ozone values.
Max4
Mean
Median
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Keadinp
Philadelphia'
•, Wilmington/
r Newark
Vine
Philadelphia
V
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Use in
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Direction
Insignificant
V Negative
A Positive
Figure 28: Map of ozone trends at specific monitor locations in the Philadelphia area. All
upward and downward facing triangles represent statistically significant
trends from 1998-2001 (p<0.05), circles represent locations with no
significant trends. The pink star indicates the site with the highest design
values in 2011. Left panel shows trends in May-September 4* highest 8-hour
daily maximum ozone values, center panel shows trends in May-September
mean 8-hour daily maximum, and left panel shows trends in May-September
median 8-hour daily maximum ozone values.
-------
Mean
Median
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V Negative
Figure 29: Map of ozone trends at specific monitor locations in the Sacramento area. All
upward and downward facing triangles represent statistically significant
trends from 1998-2001 (p<0.05), circles represent locations with no
significant trends. The pink star indicates the site with the highest design
values in 2011. Left panel shows trends in May-September 4th highest 8-hour
daily maximum ozone values, center panel shows trends in May-September
mean 8-hour daily maximum, and left panel shows trends in May-September
median 8-hour daily maximum ozone values.
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Figure 30: Map of ozone trends at specific monitor locations in the Saint Louis area. All
upward and downward facing triangles represent statistically significant
trends from 1998-2001 (p<0.05), circles represent locations with no
significant trends. The pink star indicates the site with the highest design
values in 2011. Left panel shows trends in May-September 4th highest 8-hour
daily maximum ozone values, center panel shows trends in May-September
mean 8-hour daily maximum, and left panel shows trends in May-September
median 8-hour daily maximum ozone values.
-------
In addition to the ozone trends, Chapter 8 includes Table 8.7 which shows relationships
between regional trends in NOx and VOC emissions and regional ozone trends. The objective
was to investigate possible similarities in broad trends of Os concentrations and anthropogenic
NOx and VOC emissions. Trends of emissions were derived from county-level emissions data
from the 2002, 2005, 2008, and 2011 EPA National Emissions Inventory (NEI). This data was
in the form of annual totals for the 'Tier 1' sectors, which refers to the most general classification
scheme of source categories in the NEI. This raw data is plotted in U.S. maps in Figure 31. The
row of maps labeled "TierTotal" refers to the sum of all the other maps. Note that the Wildfires
and Biogenics sectors are absent from all these analyses due to their large magnitude and non-
anthropogenic origin.
To analyze trends, emissions were spatially summed for each year and each sector across
the NOAA Climate Regions1 (shown in Figure 32). The resulting trend lines for each sector and
emissions pollutant are shown in Figure 33. For direct comparison to O3 trends, the ozone data
from the study areas was grouped together by the same NOAA climate regions, and annual
percentiles of the resulting distributions were calculated, which are shown in Figure 34 and
Figure 35. The descriptors show in Table 8.7 of the main document were derived from Figure
33, Figure 34, and Figure 35.
1 Climate regions are defined by NOAA's National Climate Data Center: http://www.ncdc.noaa.gov/monitoring-
references/maps/us-climate-regions.php
-------
VOC VOC
wASTt t*5PP5Av t. ntcYcuws
16+05
1e+04
Figure 31: Maps of NOx and VOC emissions by source sector for 2002, 2005, 2008, and
2011
-------
Climate
Region
Central
EaslNorthCentral
NorthEast
Northwest
South
Southeast
Southwest
West
WestNorthCentral
Figure 32: Map of nine NOAA climate regions that were used to aggregate emissions and
ambient ozone trends. Dots show locations of ozone monitors.
-------
TIER1 DESCRIPTION
FUEL COMB. INDUSTRIE
. METALS PROCESSING
Figure 33: Plots of NOx and VOC emissions trends by source sector. Emissions are
aggregated by NOAA climate region and by urban, rural, and suburban
location.
-------
Trend
Chars
— Signil:Neg
Signifies
lnsignif:Neg
lnsignit:Pos
Year
Figure 34: Distributions of low population density (rural) monitors' Os concentrations for
different subsets of months over a 13-year period. From top to bottom in
each ribbon plot, the blue and white lines indicate the spatial mean of the
95th, 75th, 50 , 25th, and 5th percentiles for each monitor for every year from
1998-2011. Trend are shown for 7 of 9 NOAA climate regions (The
Northwest and West North Central regions did not contain any case-study
areas).
-------
Trend
Chars
— Signil:Neg
Signifies
lnsignif:Neg
lnsignit:Pos
Year
Figure 35: Distributions of high population density monitors' Os concentrations for
different subsets of months over a 13-year period. From top to bottom in
each ribbon plot, the blue and white lines indicate the spatial mean of the
95th, 75th, 50 , 25th, and 5th percentiles for each monitor for every year from
1998-2011. Trend are shown for each of 7 of 9 NOAA climate regions (The
Northwest and West North Central regions did not contain any case-study
areas).
2. MODELED OZONE CHANGES IN RESPONSE TO ACROSS THE
BOARD EMISSIONS REDUCTIONS
2.1 MAPS OF RATIOS OF MEAN OZONE FROM 2007 CMAQ SIMULATIONS
INCLUDING EMISSIONS REDUCTIONS TO MEAN OZONE FROM 2007 BASE
CMAQ SIMULATIONS.
In section 8.2.3.2 we evaluated ozone response from two CMAQ model simulations with
across-the-board reductions in US anthropogenic emissions. We presented results using ratios of
the mean ozone concentrations in the emissions reduction scenario to mean ozone concentrations
in the 2007 base CMAQ simulation. Here we provide a full set of maps which include mean
ozone response over three different time periods (January 2007, April-October 2007, and May-
September 2007) and for four different emissions reduction scenarios (50% NOx reductions,
50% NOx and VOC reductions, 90% NOx reductions, and 90% NOx and VOC reductions).
These plots show that ozone increases are most pronounced in cooler months with January maps
-------
showing broad ozone increases across most of the modeling domain while May-September maps
show broad ozone decreases across most of the modeling domain. The April-October maps
show ozone decreases in most areas but localized increases in some large cities. Also,
comparing the NOx and VOC reductions to reductions in NOx alone show the VOC has some
effect at decreasing region ozone but does not fully mitigate ozone increases in urban areas in the
April-October maps nor change the general trends described above.
0.4 0.6 0.8 1.0 1.2 1.4
ratio of seaonal mean ozone
Figure 36: Ratio of January monthly average ozone concentrations in brute force 50%
NOx emissions reduction CMAQ simulation to January monthly average
ozone concentration in the 2007 base CMAQ simulation.
-------
0.4 0.6 0,8 1.0 1.2 1.4
ratio of seaonal mean ozone
Figure 37: Ratio of January monthly average ozone concentrations in brute force 50%
NOx and VOC emissions reduction CMAQ simulation to January monthly
average ozone concentration in the 2007 base CMAQ simulation.
0.4 0.6 0.8 1.0 1.2 1.4
ratio of seaonal mean ozone
Figure 38: Ratio of January monthly average ozone concentrations in brute force 50%
NOx and VOC emissions reduction CMAQ simulation to January monthly
average ozone concentration in the 2007 base CMAQ simulation.
-------
0.4 0.6 0,8 1.0 1.2 1.4
ratio of seaonal mean ozone
Figure 39: Ratio of January monthly average ozone concentrations in brute force 90%
NOx and emissions reduction CMAQ simulation to January monthly average
ozone concentration in the 2007 base CMAQ simulation.
0.4 0.6 0.8 1.0 1.2
ratio of seaonal mean ozone
1.4
Figure 40: Ratio of April-October seasonal average ozone concentrations in brute force
50% NOx emissions reduction CMAQ simulation to April-October seasonal
average ozone concentration in the 2007 base CMAQ simulation.
-------
0.4 0.6 0.8 1.0 1.2
ratio of seaonal mean ozone
1.4
Figure 41: Ratio of April-October seasonal average ozone concentrations in brute force
50% NOx and VOC emissions reduction CMAQ simulation to April-October
seasonal average ozone concentration in the 2007 base CMAQ simulation.
0.4 0.6 0.8 1.0 1.2
ratio of seaonal mean ozone
1.4
Figure 42: Ratio of April-October seasonal average ozone concentrations in brute force
90% NOx emissions reduction CMAQ simulation to April-October seasonal
average ozone concentration in the 2007 base CMAQ simulation.
-------
0.4 0.6 0,8 1.0 1.2 1.4
ratio of seaonal mean ozone
Figure 43: Ratio of April-October seasonal average ozone concentrations in brute force
90% NOx and VOC emissions reduction CMAQ simulation to April-October
seasonal average ozone concentration in the 2007 base CMAQ simulation.
0.4 0.6 0.8 1.0 1.2 1.4
ratio of seaonal mean ozone
Figure 44: Ratio of May-September seasonal average ozone concentrations in brute force
50% NOx emissions reduction CMAQ simulation to May-September
seasonal average ozone concentration in the 2007 base CMAQ simulation.
-------
0.4 0.6 0.8 1.0 1.2
ratio of seaonal mean ozone
1.4
Figure 45: Ratio of May-September seasonal average ozone concentrations in brute force
50% NOx and VOC emissions reduction CMAQ simulation to May-
September seasonal average ozone concentration in the 2007 base CMAQ
simulation.
0.4 0.6 0.8 1.0 1.2 1.4
ratio of seaonal mean ozone
-------
Figure 46: Ratio of May-September seasonal average ozone concentrations in brute force
90% NOx emissions reduction CMAQ simulation to May-September
seasonal average ozone concentration in the 2007 base CMAQ simulation.
0.4 0.6 0,8 1.0 1.2 1.4
ratio ofseaonal mean ozone
Figure 47: Ratio of May-September seasonal average ozone concentrations in brute force
90% NOx and VOC emissions reduction CMAQ simulation to May-
September seasonal average ozone concentration in the 2007 base CMAQ
simulation.
These maps can be further understood by breaking down response by month and binning
increases and decreases by base ozone concentration. Figure 48 and Figure 49 show this
breakdown for each emissions reduction scenario. This plot clearly shows that ozone increases
predominantly occur at lower base ozone concentrations while high modeled base ozone
concentrations appear to decrease in almost all cases in the emissions reduction scenarios. The
ozone decreases occur more often and are more substantial during the months of June, July,
August, and September. The 90% NOx reduction simulations have few locations with ozone
increases than the 50% NOx reduction simulation however the are a limited number of grid cells
in which the ozone increases are larger in the 90% NOx reduction than in the 50% NOx
reduction simulation. Overall, the distributions of ozone response look similar when VOC
reductions are added on top of NOx reductions, although the NOx and VOC reduction cases are
shifted slightly more toward reducing ozone than the NOx only reduction cases.
-------
NOx50Per
NOx90Per
NOxVOCSOPer NOxVOC90Per
# Points
•
10000
5000
25 50 75 100 25 50 75 100 25 50 75 100 25 50 75 100
Base 03 (ppb)
Figure 48: Density scatter plot comparing modeled monthly mean ozone in the 2007 base
CMAQ simulation to modeled monthly mean ozone in the emissions
reduction CMAQ simulations. Colors depict the number of points occurring
at any location on the scatter plot.
-------
NOxSOPer
NOxSQPer
NOxVOCSOPer
IMQxVOC90Per
Population
• I.5e+07
16+07
5e+06
0
2S 50 75 25 50 75 29 50 75 25 50 75
Base Case 03 (ppb)
Figure 49: Density scatter plot comparing modeled monthly mean ozone in the 2007 base
CMAQ simulation to the relative change in monthly mean ozone from the
emissions reduction CMAQ simulations. Relative change is shown as the
ratio of ozone in the emissions reduction simulation to ozone in the 2007 base
simulation. Colors depict the number of people living in areas that fall at
any location on the scatter plot.
-------
2.2 MODELED OZONE RESPONSE PAIRED WITH POPULATION
In addition to maps showing increases and decreases in mean ozone values, the gridded
model data were paired with population information to quantify the number of people living in
locations where modeled ozone decreased and increased for various time periods. Figure 50-
Figure 60 break down this information by location. These figures show changes in ozone using
two different metrics: a relative metric (the ratio of mean ozone in the NOx reduction CMAQ
simulations (50% and 90%) to mean ozone in the 2007 base CMAQ simulation) and an absolute
metric (the ppb change in mean ozone from the 2007 base CMAQ simulation to the emissions
reduction CMAQ simulations). Note that the maps in the main text of chapter 8 show relative
changes while the barplots in chapter 8 show absolute changes.
Figure 50 shows the total population living in areas experiencing different ratios of mean
ozone in the NOx reduction CMAQ simulations (50% and 90%) to mean ozone in the 2007 base
CMAQ simulation for the nine NOAA climate regions of the U.S. For each climate region, this
information is shown for locations in a case-study area and for locations not in a case-study area.
Two regions, the Northwest and the West North Central regions, did not include any case study
areas. Each area is further split out into high and low-mid population density classifications.
Values for each month are displayed along the x-axis of each panel. Figure 51 shows the same
information for the combined NOx and VOC reduction scenarios. Although there are more total
people living in non-study area locations than study area locations within each region, the
patterns in the two look similar for within each population density classification in each region.
It should be noted that for the two regions of the country without an urban study area, the
Northwest has larger percentages of their population living in areas where the ratio is > 1 (ozone
increases) than most other regions and the West North Central has larger percentages of their
population living in areas where the ratio is < 1 (ozone decreases) than most other regions.
Figure 52 shows the same information for the 15 urban case study areas from all four emissions
reduction CMAQ simulations but does not split out high versus low-mid population density
locations. Also note that Figure 52 shows breakdowns by percentage of case-study area
population rather than by total population so that different case-study areas can more easily be
compared.
-------
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(0-S.o.ej -
(
-------
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M.WvW^ r-^if
Figure 51: Populations living in locations with various ranges of ratios of monthly mean
ozone in the combined NOx and VOC reduction simulations to monthly
mean ozone in the 2007 base CMAQ simulation. Eight different monthly
ratios are shown in each panel (January, April-October). Panels split
population by 9 climate regions, urban case study area vs non-urban case
study area, urban versus non-urban and 50% NOx/VOC reduction scenario
vs 90% NOx/VOC reduction scenario.
1e+06
1e+04
K 100
-------
•j'j1"/ flUW^ff'iVV/i'lYV
Figure 52: Percent of population living in locations with various ranges of ratios of
monthly mean ozone in the four emissions reduction simulations to monthly
mean ozone in the 2007 base CMAQ simulation. Eight different monthly
ratios are shown in each panel (January, April-October). Panels split
population by 15 urban case-study areas and by four emissions reduction
simulations: from top to bottom, 50% NOx reduction, 90% NOx reduction,
50% NOx and VOC reduction, 90% NOx and VOC reduction.
Section 8.2.3 further examined these ozone ratios using histograms and lumping all study
areas together and all non-study areas together. The main text provided histograms for the NOx
reduction scenarios only. This appendix provides histograms for all four emission reduction
simulations in using both relative and absolute metrics (Figure 53-Figure 60). These figures
show that the breakdown of people living in locations of increasing versus decreasing ozone for
various monthly and seasonal time-periods does not change much between the NOx reduction
scenarios and the equivalent NOx and VOC reduction scenarios. Table 1 provides the numbers
going into the 50% NOx reduction and 90% NOx reduction histograms. Table 2 and Table 3
break down the April-October seasonal mean ozone results by two further classification
schemes: high versus low-mid population density locations and by the 15 case study areas.
-------
Non-Study Area
60 -
0
60
Study Area
c
g
CL
O
CL
CO
0-
60
20-
o
Ratio
Figure 53: Histograms of US population living in locations with increasing and decreasing
mean ozone. Values on the x-axis represent the ratio of mean ozone in the
50% NOx cut CMAQ simulation to the mean ozone in the 2007 base CMAQ
simulation. The percentages of the US population living in areas that have
ratios less than 0.95, from 0.95 to 1.05 and greater than 1.05 are shown on the
y-axis. Left plots show population numbers in locations not included in one
of the urban case study areas while right plots show population numbers in
locations included in one of the urban case study areas. Top plots show
ratios of January monthly mean ozone, middle plots show ratios of season
mean June-August ozone, and bottom plots show ratios of seasonal mean
April-October ozone.
-------
Non-Study Area
o
60
c
o
Q.
O
Q_
Q
60
40 -
20-
0
Ratio
Figure 54: Histograms of US population living in locations with increasing and decreasing
mean ozone. Values on the x-axis represent the ratio of mean ozone in the
50% NOx and VOC cut CMAQ simulation to the mean ozone in the 2007
base CMAQ simulation. The percentages of the US population living in
areas that have ratios less than 0.95, from 0.95 to 1.05 and greater than 1.05
are shown on the y-axis. Left plots show population numbers in locations not
included in one of the urban case study areas while right plots show
population numbers in locations included in one of the urban case study
areas. Top plots show ratios of January monthly mean ozone, middle plots
show ratios of season mean June-August ozone, and bottom plots show ratios
of seasonal mean April-October ozone.
-------
Non-Study Area
Study Area
40
20-
0
Ratio
Figure 55: Histograms of US population living in locations with increasing and decreasing
mean ozone. Values on the x-axis represent the ratio of mean ozone in the
90% NOx cut CMAQ simulation to the mean ozone in the 2007 base CMAQ
simulation. The percentages of the US population living in areas that have
ratios less than 0.95, from 0.95 to 1.05 and greater than 1.05 are shown on the
y-axis. Left plots show population numbers in locations not included in one
of the urban case study areas while right plots show population numbers in
locations included in one of the urban case study areas. Top plots show
ratios of January monthly mean ozone, middle plots show ratios of season
mean June-August ozone, and bottom plots show ratios of seasonal mean
April-October ozone.
-------
Non-Study Area
Study Area
60 -
40
20 -
0
Ratio
Figure 56: Histograms of US population living in locations with increasing and decreasing
mean ozone. Values on the x-axis represent the ratio of mean ozone in the
90% NOx and VOC cut CMAQ simulation to the mean ozone in the 2007
base CMAQ simulation. The percentages of the US population living in areas
that have ratios less than 0.95, from 0.95 to 1.05 and greater than 1.05 are
shown on the y-axis. Left plots show population numbers in locations not
included in one of the urban case study areas while right plots show
population numbers in locations included in one of the urban case study
areas. Top plots show ratios of January monthly mean ozone, middle plots
show ratios of season mean June-August ozone, and bottom plots show ratios
of seasonal mean April-October ozone.
-------
Non-Study Area
40
o
Study Area
60 -
40-
o-
ppb change
Figure 57: Histograms of US population living in locations with increasing and decreasing
mean ozone. Values on the x-axis represent the absolute (ppb) change of
mean ozone from the 2007 base CMAQ simulation to the 50% NOx cut
CMAQ simulation to the mean ozone in the 2007 base CMAQ simulation.
The percentages of the US population living in areas that have changes less
than -1 ppb, between -1 and +1 ppb and greater than +1 ppb are shown on
the y-axis. Left plots show population numbers in locations not included in
one of the case study areas while right plots show population numbers in
locations included in one of the case study areas. Top plots show ratios of
January monthly mean ozone, middle plots show ratios of season mean June-
August ozone, and bottom plots show ratios of seasonal mean April-October
ozone.
-------
Non-Study Area
60 -
40 -
20-
o-
Study Area
60-
O
CL
O
Q.
cfl
=>20-
o-
60
40 -
20-
0-
ppb change
Figure 58: Histograms of US population living in locations with increasing and decreasing
mean ozone. Values on the x-axis represent the absolute (ppb) change of
mean ozone from the 2007 base CMAQ simulation to the 50% NOx and
VOC cut CMAQ simulation to the mean ozone in the 2007 base CMAQ
simulation. The percentages of the US population living in areas that have
changes less than -1 ppb, between -1 and +1 ppb and greater than +1 ppb are
-------
shown on the y-axis. Left plots show population numbers in locations not
included in one of the case study areas while right plots show population
numbers in locations included in one of the case study areas. Top plots show
ratios of January monthly mean ozone, middle plots show ratios of season
mean June-August ozone, and bottom plots show ratios of seasonal mean
April-October ozone.
40
20
60
O
1
13 40
Q.
O
Q_
CD
=>20-
3?
0
60
40
20 -
o-
ppb change
Figure 59: Histograms of US population living in locations with increasing and decreasing
mean ozone. Values on the x-axis represent the absolute (ppb) change of
mean ozone from the 2007 base CMAQ simulation to the 90% NOx cut
CMAQ simulation to the mean ozone in the 2007 base CMAQ simulation.
The percentages of the US population living in areas that have changes less
than -1 ppb, between -1 and +1 ppb and greater than +1 ppb are shown on
-------
the y-axis. Left plots show population numbers in locations not included in
one of the case study areas while right plots show population numbers in
locations included in one of the case study areas. Top plots show ratios of
January monthly mean ozone, middle plots show ratios of season mean June-
August ozone, and bottom plots show ratios of seasonal mean April-October
ozone.
Non-Study Area
eo
40
20
60-
O
D40
Q.
O
Q_
35
0-
60
40
20 -
0-
ppb change
Figure 60: Histograms of US population living in locations with increasing and decreasing
mean ozone. Values on the x-axis represent the absolute (ppb) change of
mean ozone from the 2007 base CMAQ simulation to the 90% NOx and
VOC cut CMAQ simulation to the mean ozone in the 2007 base CMAQ
-------
simulation. The percentages of the US population living in areas that have
changes less than -1 ppb, between -1 and +1 ppb and greater than +1 ppb are
shown on the y-axis. Left plots show population numbers in locations not
included in one of the case study areas while right plots show population
numbers in locations included in one of the case study areas. Top plots show
ratios of January monthly mean ozone, middle plots show ratios of season
mean June-August ozone, and bottom plots show ratios of seasonal mean
April-October ozone.
Table 1: Percentage of US population living in locations with increasing and decreasing
mean ozone for the 50% NOx reduction and 90% NOx reductions CMAQ
simulations broken down by different seasonal and monthly time periods.
January
April-
October
June-
Ratio
<0.95
0.95-0.96
0.96-0.97
0.97-0.98
0.98-0.99
0.99-1.00
1.00-1.01
1.01-1.02
1.02-1.03
1.03-1.04
1.04-1.05
>1.05
<0.95
0.95-0.96
0.96-0.97
0.97-0.98
0.98-0.99
0.99-1.00
1.00-1.01
1.01-1.02
1.02-1.03
1.03-1.04
1.04-1.05
>1.05
<0.95
50% NOx
Study
Area
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.1
0.2
28.7
8.4
2.1
1.7
1.7
1.4
1.5
0.8
1.1
0.8
1.1
0.7
7.6
16.4
Non Study
Area
0.0
0.0
0.0
0.1
0.4
0.7
0.9
1.1
1.1
1.4
1.7
63.6
50.6
3.6
2.8
1.9
1.6
1.4
0.7
0.7
0.9
0.5
0.7
5.5
58.4
US
0.0
0.0
0.0
0.1
0.4
0.7
1.0
1.1
1.2
1.5
1.9
92.3
59.0
5.7
4.5
3.7
3.0
2.9
1.5
1.8
1.7
1.6
1.4
13.1
74.8
90% NOx
Study Area
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
28.9
22.3
0.5
0.6
0.2
0.5
0.5
0.2
0.2
0.2
0.4
0.1
3.4
27.4
Non Study
Area
0.6
0.3
0.3
0.5
0.7
0.7
0.8
0.8
1.0
1.2
1.3
62.6
64.7
0.2
0.6
0.5
0.2
0.2
0.5
0.2
0.3
0.3
0.2
3.2
66.3
US
0.6
0.3
0.3
0.5
0.7
0.8
0.8
0.8
1.1
1.2
1.3
91.5
87.0
0.8
1.2
0.7
0.6
0.8
0.6
0.3
0.5
0.7
0.3
6.6
93.7
-------
August
0.95-0.96
0.96-0.97
0.97-0.98
0.98-0.99
0.99-1.00
1.00-1.01
1.01-1.02
1.02-1.03
1.03-1.04
1.04-1.05
>1.05
1.1
1.1
1.1
1.0
1.1
0.5
0.7
0.5
0.6
1.3
3.8
1.6
0.9
1.1
0.9
0.7
0.6
0.5
0.5
0.4
0.4
5.0
2.7
1.9
2.1
1.8
1.8
1.1
1.2
0.9
1.0
1.7
8.8
0.1
0.0
0.0
0.0
0.0
0.1
0.1
0.0
0.0
0.1
1.2
0.3
0.3
0.3
0.2
0.2
0.3
0.2
0.0
0.2
0.0
2.4
0.4
0.3
0.4
0.2
0.2
0.4
0.3
0.1
0.2
0.2
3.7
Table 2: Percentage of US population living in locations with increasing and decreasing
April-October seasonal mean ozone in the 50% NOx reduction and 90%
NOx reductions CMAQ simulations broken down by high and low-mid
population density areas.
High
population
density
Low-Mid
population
density
Ratio
<0.95
0.95-0.96
0.96-0.97
0.97-0.98
0.98-0.99
0.99-1.00
1.00-1.01
1.01-1.02
1.02-1.03
1.03-1.04
1.04-1.05
>1.05
<0.95
0.95-0.96
0.96-0.97
0.97-0.98
0.98-0.99
0.99-1.00
1.00-1.01
1.01-1.02
1.02-1.03
1.03-1.04
1.04-1.05
50% NOx
Study Area
0.8
0.6
0.8
0.9
0.9
1.1
0.7
0.9
0.7
1.0
0.7
7.3
7.6
1.5
0.9
0.8
0.5
0.4
0.1
0.2
0.1
0.1
0.0
Non Study Area
1.7
0.7
0.6
0.5
0.6
0.7
0.3
0.4
0.7
0.3
0.5
3.8
48.9
3.0
2.1
1.4
0.9
0.7
0.4
0.3
0.3
0.2
0.2
US
2.5
1.3
1.4
1.5
1.6
1.8
1.0
1.3
1.4
1.3
1.1
11.1
56.5
4.5
3.1
2.2
1.4
1.1
0.5
0.5
0.3
0.3
0.3
90% NOx
Study Area
9.8
0.5
0.6
0.2
0.5
0.5
0.2
0.2
0.2
0.4
0.1
3.4
12.5
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Non Study Area
6.7
0.1
0.4
0.3
0.1
0.1
0.3
0.1
0.1
0.2
0.1
2.3
58.1
0.2
0.1
0.2
0.1
0.1
0.1
0.1
0.1
0.1
0.1
US
16.5
0.6
1.0
0.5
0.6
0.6
0.5
0.2
0.3
0.6
0.1
5.7
70.6
0.2
0.1
0.2
0.1
0.1
0.2
0.1
0.1
0.1
0.1
-------
>1.05
0.3
1.7
2.0
0.0
0.8
0.9
Table 3: Percentage of US population living in locations with increasing and decreasing
April-October seasonal mean ozone in the 50% NOx reduction and 90%
NOx reduction CMAQ simulations broken down by 15 case study areas.
Scenario
50%
NOx
reduction
90%
NOx
reduction
Study Area
Not in Study Area
Atlanta
Baltimore
Boston
Chicago
Cleveland
Dallas
Denver
Detroit
Houston
Los Angeles
New York
Philadelphia
Sacramento
St. Louis
Washington
Not in Study Area
Atlanta
Baltimore
Boston
Chicago
Cleveland
Dallas
Denver
Detroit
Houston
Los Angeles
New York
Philadelphia
Ratio of April-October seasonal mean ozone in reduced emissions CMAQ simulation to April-October
seasonal mean ozone in base 2007 CMAQ simulation
0-
0.95
50.6
1.6
0.4
0.4
0.5
0.2
1.0
0.1
0.1
0.8
0.2
0.5
0.7
0.2
0.6
1.1
64.7
1.7
0.9
1.2
2.4
0.6
2.0
0.7
1.0
1.7
1.7
3.2
2.0
0.95-
0.96
3.6
0.1
0.0
0.2
0.1
0.1
0.4
0.2
0.1
0.1
0.1
0.3
0.1
0.2
0.1
0.1
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.1
0.3
0.0
0.96-
0.97
2.8
0.0
0.2
0.1
0.2
0.1
0.2
0.1
0.1
0.0
0.1
0.3
0.2
0.0
0.0
0.2
0.6
0.0
0.0
0.2
0.3
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.97-
0.98
1.9
0.0
0.0
0.1
0.2
0.0
0.1
0.0
0.0
0.2
0.0
0.2
0.3
0.1
0.1
0.2
0.5
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.1
0.0
0.0
0.98-
0.99
1.6
0.0
0.1
0.1
0.3
0.1
0.1
0.1
0.1
0.1
0.0
0.2
0.2
0.1
0.0
0.1
0.2
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.1
0.0
0.0
0.3
0.0
0.99-
1.00
1.4
0.0
0.0
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.4
0.3
0.2
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.3
0.0
0.0
0.0
0.0
0.0
0.2
0.1
0.0
1.00-
1.01
0.7
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.1
0.0
0.1
0.1
0.1
0.1
0.1
0.5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.1
0.0
0.0
1.01-
1.02
0.7
0.0
0.0
0.2
0.2
0.1
0.1
0.1
0.1
0.0
0.1
0.2
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.1
0.0
0.0
1.02-
1.03
0.9
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.2
0.1
0.2
0.2
0.0
0.0
0.0
0.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.1
0.0
0.0
0.0
1.03-
.04
0.5
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.2
0.1
0.2
0.1
0.2
0.0
0.0
0.0
0.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.2
0.0
1.04-
1.05
0.7
0.0
0.1
0.2
0.1
0.0
0.0
0.0
0.1
0.1
0.0
0.1
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
>1.05
5.5
0.0
0.0
0.0
0.9
0.0
0.0
0.1
0.3
0.2
2.8
3.4
0.0
0.0
0.0
0.0
3.2
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
1.4
1.9
0.0
-------
Sacramento
St. Louis
Washington
0.7
0.9
1.8
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
-------
Appendix 9-A
Exposure and Lung-Function Risk Estimates for Sub-Regions of Each Study
Area (urban core, outer ring, total regions)
Simulated populations within different sub-regions of a given urban study area may have
different exposure and lung-function risk distributions reflecting potential differences both in
their patterns of behavior (e.g., commuting patterns, outdoor activities) as well as differences in
the spatio-temporal ambient ozone fields estimated for each sub-region. To explore potential
spatial heterogeneity in both the exposure and lung-function risk estimates, we have completed a
stratified analysis of risk for both of these assessments. These stratified analysis consider two
sub-regions within each study area including: (a) a smaller urban core sub-area matching that
used in the Smith et al., 2009 epidemiology study providing the effect estimates used in
modeling short-term exposure-based mortality risk and (b) the outer ring reflecting the remainder
of the larger study area used in the exposure and lung-function assessment (excluding the core
urban area). In presenting risk estimates based on these two sub-regions, we also include risk
estimates based on the entire study area for completeness.
Generating these sub-region risk estimates is relatively straight-forward. As part of our
standard APEX output for the exposure and lung function risk estimates summarized in Chapters
5 and 6 respectively, limited exposure and FEV1 results are retained for each simulated person
including their daily maximum 1-hour ozone exposure and counts per ozone season of each time
a simulated person experienced an FEV1 decrement (10%, 15%, and 20%). Also retained is the
location of their home census tract (and corresponding location of ambient concentration source
used for calculating exposures) within the larger study areas used in the exposure and lung-
function analyses. To generate the sub-region estimates, we subset these broader study area
exposure and FEV1 risk results into two sets of exposure results for each of 12 study areas: one
containing those persons residing within the urban core and the other containing persons residing
in the outer ring outside the urban core. In addition, two years of data were evaluated for the 12
study areas (2007 and 2009), matching the two years for which short term mortality risks were
estimated. In generating these sub-region estimates, we focused on the 12 urban study areas used
in the epidemiology-based risk assessment to allow these stratified results to be compared
alongside the urban core and CBSA-based estimates generated as part of the epidemiological-
based risk assessment.
In summarizing these risk estimates, we first focus on the exposure estimates (figures 9A-
1 through 9A-12), including the percent of all simulated individuals experiencing 1-hour
exposure at or above each specified benchmark (see Chapter 5 for additional detail on this risk
metric). Estimates are presented for both 2007 and 2009 within each figure. In order to compare,
9A-1
-------
for example, exposure estimates (based on the 60 ppb benchmark) for the urban core between
current conditions and the current standard for 2007, we would compare the darker blue column
for urb 122 base 07 with the darker blue column for urb_122_75_07.
After presenting the exposure estimates, we then present lung-function estimates (figures
9A-13 through 9A-24) including percent of all simulated individuals experiencing at least one
FEV1 decrement of 10, 15, or 20% (see Chapter 6 for additional detail on this risk metric).
Estimates are presented for both 2007 and 2009 within each figure. In order to compare, for
example, exposure estimates (based on the 20 percent FEV1 decrement) for the urban core
between current conditions and the current standard for 2007, we would compare the light tan
column for urb 122 base 07 with the light tan column for urb_122_75_07.
Generally for both the exposure and lung-function risk estimates, we see either a pattern
of risk reduction or no change in risk when we look across air quality scenarios (recent
conditions - current standard - alternative standard 70 ppb) for a given sub-region (i.e., urban
core, outer ring or total combined area). Note however, that in one case (Boston for 2009 for the
urban sub-region) we do see a slight risk increase for both exposure and lung function risk (see
Figure 9A-3 and 9A-15, respectively). When we compare patterns of risk reduction for the urban
core and outer ring (across urban study areas), we generally see larger degrees of risk reduction
for the outer rings. This may reflect two factors: (a) design monitors (targeted for ozone
reductions under simulated attainment of the current and alternative standard levels) tend to be
located in the outer ring and consequently ozone levels near these monitors are likely to
experience greater degrees of reduction and (b) there may be a degree of dampening of risk
reduction in the urban core reflecting the non-linear nature of ozone formation which can result
in increase in ozone on lower ozone days following simulation of both current and alternative
standard levels (see section 7.1.1 for additional discussion).
9A-2
-------
Figure 9A-1 Exposure Risk Estimates - Percent of Person with 1-Hour Exposures at or Above Benchmarks
(Spatially stratified: all study area, urban study area, outer study area) (Atlanta)
Atlanta: percent of persons, 1-hour exposures
100%
90% -•
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9A-3
-------
Figure 9A-2 Exposure Risk Estimates - Percent of Person with 1-Hour Exposures at or Above Benchmarks
(Spatially stratified: all study area, urban study area, outer study area) (Baltimore)
> 90% -
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Figure 9A-3 Exposure Risk Estimates - Percent of Person with 1-Hour Exposures at or Above Benchmarks
(Spatially stratified: all study area, urban study area, outer study area) (Boston)
Boston: percent of persons, 1-hour exposures
tracts_studyarea_AQscenario_year
9A-5
-------
Figure 9A-4 Exposure Risk Estimates - Percent of Person with 1-Hour Exposures at or Above Benchmarks
(Spatially stratified: all study area, urban study area, outer study area) (Cleveland)
a, :
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Figure 9A-5 Exposure Risk Estimates - Percent of Person with 1-Hour Exposures at or Above Benchmarks
(Spatially stratified: all study area, urban study area, outer study area) (Denver)
Denver: percent of persons, 1 -hour exposures
|100A
> 90% -
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9A-7
-------
Figure 9A-6 Exposure Risk Estimates - Percent of Person with 1-Hour Exposures at or Above Benchmarks
(Spatially stratified: all study area, urban study area, outer study area) (Detroit)
Detroit: percent of persons, 1 -hour exposures
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(Spatially stratified: all study area, urban study area, outer study area) (Houston)
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Figure 9A-8 Exposure Risk Estimates - Percent of Person with 1-Hour Exposures at or Above Benchmarks
(Spatially stratified: all study area, urban study area, outer study area) (Los Angeles)
Los Angeles: percent of persons, 1 -hour exposures
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Figure 9A-9 Exposure Risk Estimates - Percent of Person with 1-Hour Exposures at or Above Benchmarks
(Spatially stratified: all study area, urban study area, outer study area) (New York)
New York: percent of persons, 1-hour exposures
I 100%
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(Spatially stratified: all study area, urban study area, outer study area) (Philadelphia)
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(Spatially stratified: all study area, urban study area, outer study area) (Sacramento)
Sacramento: percent of persons, 1 -hour exposures
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9 A-13
-------
Figure 9A-12 Exposure Risk Estimates - Percent of Person with 1-Hour Exposures at or Above Benchmarks
(Spatially stratified: all study area, urban study area, outer study area) (St. Louis)
I 100%
01
S
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Figure 9A-13 Lung-Function Risk Estimates - Percent of Person with Specified FEV1 Decrement
(Spatially stratified: all study area, urban study area, outer study area) (Atlanta)
~ 12.0% i
0)
S 11 n% -
^ 10.0% -
LL Q no/ -
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9 A-15
-------
Figure 9A-14 Lung-Function Risk Estimates - Percent of Person with Specified FEV1 Decrement
(Spatially stratified: all study area, urban study area, outer study area) (Baltimore)
Baltimore: percent of persons, dFEV1
tracts_studyarea_AQscenario_year
9 A-16
-------
Figure 9A-15 Lung-Function Risk Estimates - Percent of Person with Specified FEV1 Decrement
(Spatially stratified: all study area, urban study area, outer study area) (Boston)
Boston: percent of persons, dFEV1
tracts_studyarea_AQscenario_year
9 A-17
-------
Figure 9A-16 Lung-Function Risk Estimates - Percent of Person with Specified FEV1 Decrement
(Spatially stratified: all study area, urban study area, outer study area) (Cleveland)
£ 7.5%
Cleveland: percent of persons, dFEV1
i 7-0% *•
| 6.5%
u! 6.0% -f
•O
15 5.5%
1 5.0%
| 4.5%
4.0%
ro 3-5%
1 3.0%
'o 2.5% -E
S 2.0%
c
| 1.5%
= 1.0%
re
° 0.5% f
-------
Figure 9A-17 Lung-Function Risk Estimates - Percent of Person with Specified FEV1 Decrement
(Spatially stratified: all study area, urban study area, outer study area) (Denver)
~ 8.0%
7.5%
7.0%
6.5%
6.0%
5.5%
5.0%
4.5%
4.0%
3.5%
3.0%
2.5%
2.0%
1.5%
1.0%
0.5%
0.0%
Denver: percent of persons, dFEV1
n
1
n|\|_CdFEV10
• N_CdFEV15
DN CdFEV20
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tracts_studyarea_AQscenario_year
ts:
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05
o
o
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9 A-19
-------
Figure 9A-18 Lung-Function Risk Estimates - Percent of Person with Specified FEV1 Decrement
(Spatially stratified: all study area, urban study area, outer study area) (Detroit)
Detroit: percent of persons, dFEV1
g 8.5%
S! 8.0%
•§ 7.5%
53 7.0%
•g 6.5% -I
o 6.0%
•c
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01
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§ 2.0%
| 1.5%
1 1.0%
| 0.5%
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9A-20
-------
Figure 9A-19 Lung-Function Risk Estimates - Percent of Person with Specified FEV1 Decrement
(Spatially stratified: all study area, urban study area, outer study area) (Houston)
Houston: percent of persons, dFEV1
tracts_studyarea_AQscenario_year
9A-21
-------
Figure 9A-20 Lung-Function Risk Estimates - Percent of Person with Specified FEV1 Decrement
(Spatially stratified: all study area, urban study area, outer study area) (Los Angeles)
Los Angeles: percent of persons, dFEV1
11.0%
10.5%
10.0%
9.5%
9.0%
8.5%
8.0%
7.5%
7.0%
6.5%
6.0%
5.5%
5.0%
4.5%
4.0%
3.5% ••
3.0% -;
2.5% -•
2.0% -;
1.5% -•
1.0% -;
0.5% ••
0.0%
01
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9A-22
-------
Figure 9A-21 Lung-Function Risk Estimates - Percent of Person with Specified FEV1 Decrement
(Spatially stratified: all study area, urban study area, outer study area) (New York)
New York: percent of persons, dFEV1
DN_CdFEV10
•N_CdFEV15
DN CdFEV20
tracts_studyarea_AQscenario_year
9A-23
-------
Figure 9A-22 Lung-Function Risk Estimates - Percent of Person with Specified FEV1 Decrement
(Spatially stratified: all study area, urban study area, outer study area) (Philadelphia)
Philadelphia: percent of persons, dFEV1
tracts_studyarea_AQscenario_year
9A-24
-------
Figure 9A-23 Lung-Function Risk Estimates - Percent of Person with Specified FEV1 Decrement
(Spatially stratified: all study area, urban study area, outer study area) (Sacramento)
1 10.0%
9.5%
9.0%
8.5%
8.0%
7.5%
7.0%
6.5%
6.0%
5.5%
5.0%
4.5%
4.0%
3.5%
3.0%
2.5%
2.0%
1.5%
1.0%
0.5%
0.0%
Sacramento: percent of persons, dFEV1
,
1
i
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Figure 9A-24 Lung-Function Risk Estimates - Percent of Person with Specified FEV1 Decrement
(Spatially stratified: all study area, urban study area, outer study area) (St Louis)
St Louis: percent of persons, dFEV1
£ 9.5%
I 9.0% +
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9A-26
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United States Office of Air Quality Planning and Standards Publication No. EPA-452/P-14-004e
Environmental Protection Air Quality Strategies and Standards Division February 2014
Agency Research Triangle Park, NC
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