&EPA
United States
Envirofunmlal Protection
Agnncy
Health Risk and Exposure Assessment
for Ozone
Final Report
Chapters 7-9 Appendices
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EPA-452/R-14-004e
August 2014
Health Risk and Exposure Assessment for Ozone
Final Report
Chapters 7-9 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
-------
DISCLAIMER
This final 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.
Questions related to this 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).
-------
CHAPTERS 7-9 APPENDICES
APPENDIX 7A:
APPENDIX 7B:
APPENDIX 7C:
Title
Detailed Information on Effect Estimates,
Baseline Incidence and Demographic Data Used
in the Epidemiological-Based Risk Assessment
Detailed Summary Tables and Figures of Core
Risk Estimates
Detailed Summary Tables and Figures of
Sensitivity Analysis Results
Pages
(7A-lto7A-ll)
(7B-lto7B-13)
(7C-1 to 7C-14)
APPENDIX 8A:
APPENDIX 8B:
City-Specific Ozone-Mortality Effect Estimates (8A-1 to 8A-5)
Supplement to the Representativeness Analysis of (8B-1 to 8B-39)
the 12 Urban Study Areas
APPENDIX 8C: National Representativeness of Ozone Response (8C-1 to 8C-48)
to Emissions Change
APPENDIX 9A: Figures Summarizing Exposure and Lung-
Function Risk Estimates for Sub-Regions of Each
Study Area (Urban Core, Outer Ring, and Total
Exposure Region)
(9A-1 to 9A-27)
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APPENDIX 7A
Detailed Information on Effect Estimates, Baseline Incidence and
Demographic Data Used in the Epidemiological-Based Risk
Assessment
This Appendix contains one table (Table 7A-1) summarizing the effect estimates,
baseline incidence, and population data used for the epidemiological-based risk assessment.
References are included immediately following the table.
7A-i
-------
Table 7A-1. Detailed Information on Effect Estimates, Baseline Incidence and Demographic Data Used in the
Epidemiological-Based Risk Assessment.
Endpoint
Study
Urban study
area
Study
area
template
Study information (C-R function)
Air metric
Risk
assessment
modeling
period
Age
range
Lag
Additional
study
details
Statistical
Model
Effect
estimate
(Beta)
SE (effect
estimate)3
Baseline incidence1"
2007
2009
Population
2007
2009
Core Risk - short-term exposure-related all-cause mortality
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
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
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
March-
October
April-
October
April-
September
April-
October
March-
September
April-
September
January-
December
January-
December
April-
October
April-
October
January-
December
April-
October
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
-
-
-
-
-
-
-
-
-
-
-
-
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
0.0002411
0.0004192
0.0002807
0.0005654
0.0001657
0.0006432
0.0004999
0.0002179
0.0010114
0.000714
0.0003016
0.0005401
0.0002919
0.00033
0.0003429
0.0003149
0.0003565
0.0003117
0.0002075
0.0001571
0.0002074
0.0002846
0.0003145
0.0003428
19,995
11,703
16,688
10,964
6,750
17,169
30,191
72,824
78,036
28,177
13,198
13,944
20,442
11,598
16,436
10,692
6,856
16,815
30,927
72,935
76,645
27,658
13,361
13,686
5,033,453
2,664,335
4,439,453
2,093,376
2,408,986
4,381,785
5,539,894
12,615,165
18,554,574
5,876,683
2,077,487
2,779,558
5,205,933
2,692,803
4,519,143
2,082,741
2,498,144
4,316,185
5,823,529
12,756,237
18,779,754
5,936,034
2,127,784
2,803,333
Core Risk - long-term exposure-related respiratory mortality
Mortality,
Respiratory
Mortality,
Respiratory
Mortality,
Respiratory
Jerrett et
al., 2009
Jerrett et
al., 2009
Jerrett et
al., 2009
Atlanta, GA
Baltimore,
MD
Boston, MA
CBSA
CBSA
CBSA
Seasonal-avg
DlhrMax
Seasonal-avg
DlhrMax
Seasonal-avg
DlhrMax
April-
September
April-
September
April-
September
30-99
30-99
30-99
NA
NA
NA
-
-
-
log-linear
log-linear
log-linear
0.0039221
0.0039221
0.0039221
0.0013249
0.0013249
0.0013249
3,133
2,056
3,685
3,216
2,034
3,622
2,833,399
1,587,538
2,690,981
2,954,650
1,609,957
2,747,634
7A-1
-------
Endpoint
Mortality,
Respiratory
Mortality,
Respiratory
Mortality,
Respiratory
Mortality,
Respiratory
Mortality,
Respiratory
Mortality,
Respiratory
Mortality,
Respiratory
Mortality,
Respiratory
Mortality,
Respiratory
Study
Jerrett et
al., 2009
Jerrett et
al., 2009
Jerrett et
al., 2009
Jerrett et
al., 2009
Jerrett et
al., 2009
Jerrett et
al., 2009
Jerrett et
al., 2009
Jerrett et
al., 2009
Jerrett et
al., 2009
Urban study
area
Cleveland,
OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles,
CA
New York,
NY
Philadelphia,
PA
Sacramento,
CA
St. Louis,
MO
Study
area
template
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
Study information (C-R function)
Air metric
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
April-
September
April-
September
April-
September
April-
September
April-
September
April-
September
April-
September
April-
September
April-
September
Age
range
30-99
30-99
30-99
30-99
30-99
30-99
30-99
30-99
30-99
Lag
NA
NA
NA
NA
NA
NA
NA
NA
NA
Additional
study
details
-
-
-
-
-
-
-
-
-
Statistical
Model
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
Effect
estimate
(Beta)
0.0039221
0.0039221
0.0039221
0.0039221
0.0039221
0.0039221
0.0039221
0.0039221
0.0039221
SE (effect
estimate)3
0.0013249
0.0013249
0.0013249
0.0013249
0.0013249
0.0013249
0.0013249
0.0013249
0.0013249
Baseline incidence1"
2007
1,833
1,549
3,230
2,790
7,480
12,304
4,993
1,669
2,535
2009
1,783
1,574
3,153
2,859
7,512
12,067
4,891
1,690
2,485
Population
2007
1,294,458
1,396,514
2,636,935
3,001,537
7,072,418
11,118,315
3,488,101
1,185,990
1,649,209
2009
1,294,845
1,454,586
2,628,339
3,165,283
7,236,439
11,303,888
3,545,106
1,221,735
1,676,509
Core Risk - short-term exposure-related morbidity
HA, All Respiratory
HA, All Respiratory
HA, Asthma
HA, Asthma
HA, Chronic Lung
Disease
HA, All Respiratory
Katsouyanni
etal., 2009
Katsouyanni
etal., 2009
Silverman
and Ito,
2010
Silverman
and Ito,
2010
Lin etal. (a),
2008
Linn et al.,
2000
Detroit, Ml
Detroit, Ml
New York,
NY
New York,
NY
New York,
NY
Los Angeles,
CA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
DIHourMax
DIHourMax
DSHourMax
DSHourMax
DIHourMax
D24HourMean
June-
August
June-
August
April-
October
April-
October
April-
October
June-
August
65-99
65-99
6-18
6-18
0-17
30-99
average of
lag 0 and
lagl
average of
lag 0 and
lagl
average of
lag 0 and
lagl
average of
lag 0 and
lagl
Lag2d
LagOd
penalized
splines
natural
splines
-
PM2.5
-
-
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
0.00056
0.00054
0.007907
0.0055553
0.0007609
0.0006
0.000352
0.0003571
0.0037862
0.0036926
0.000163
0.0007
6,538
6,538
1,697
1,697
4,340
19,320
6,694
6,694
1,683
1,683
4,300
20,259
539,077
539,077
3,197,360
3,197,360
4,388,434
7,072,418
557,511
557,511
3,173,355
3,173,355
4,344,448
7,236,439
7A-2
-------
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)
Study
Medina-
Ramon et
al, 2006
Medina-
Ramon et
al, 2006
Medina-
Ramon et
al, 2006
Medina-
Ramon et
al, 2006
Medina-
Ramon et
al, 2006
Medina-
Ramon et
al, 2006
Medina-
Ramon et
al, 2006
Medina-
Ramon et
al, 2006
Medina-
Ramon et
al, 2006
Medina-
Ramon et
al, 2006
Medina-
Ramon et
al, 2006
Urban 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
Study
area
template
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
Study information (C-R function)
Air metric
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
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
Age
range
65-99
65-99
65-99
65-99
65-99
65-99
65-99
65-99
65-99
65-99
65-99
Lag
distributed
lag 0-1 d
distributed
lag 0-1 d
distributed
lag 0-1 d
distributed
lag 0-1 d
distributed
lag 0-1 d
distributed
lag 0-1 d
distributed
lag 0-1 d
distributed
lag 0-1 d
distributed
lag 0-1 d
distributed
lag 0-1 d
distributed
lag 0-1 d
Additional
study
details
-
-
-
-
-
-
-
-
-
-
-
Statistical
Model
logistic
logistic
logistic
logistic
logistic
logistic
logistic
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
SE (effect
estimate)3
0.000199
0.000199
0.000199
0.000199
0.000199
0.000199
0.000199
0.000199
0.000199
0.000199
0.000199
Baseline incidence1"
2007
2,160
1,540
2,577
1,587
623
2,870
2,716
4,059
9,026
3,825
606
2009
2,358
1,593
2,657
1,612
665
2,935
2,922
4,302
9,235
3,920
649
Population
2007
412,999
320,763
559,310
305,763
227,092
539,077
451,335
1,309,329
2,359,351
755,595
235,921
2009
453,851
334,599
581,219
312,042
245,643
557,511
489,474
1,372,256
2,427,316
780,220
250,905
7A-3
-------
Endpoint
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
Study
Medina-
Ramon et
al, 2006
Strickland
etal., 2010
Strickland
etal., 2010
Tolbert et
al., 2007
Tolbert et
al., 2007
Tolbert et
al., 2007
Tolbert et
al., 2007
Tolbert et
al., 2007
Darrow et
al., 2011
Itoetal.,
2007
Itoetal.,
2007
Itoetal.,
2007
Itoetal.,
2007
Itoetal.,
2007
Gent etal.,
2003
Urban study
area
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
Study
area
template
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
Study information (C-R function)
Air metric
DSHourMean
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DIHourMax
Risk
assessment
modeling
period
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)
Age
range
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
Lag
distributed
lag 0-1 d
distributed
lag 0-7 d
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 Oand
lagl
average of
lag Oand
lagl
average of
lag Oand
lagl
average of
lag Oand
lagl
average of
lag Oand
lagl
Lag Id
Additional
study
details
-
-
-
-
CO
NO2
PM10
PM10,
NO2
-
-
PM2.5
NO2
CO
SO2
-
Statistical
Model
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
Effect
estimate
(Beta)
0.00054
0.0047864
0.002699
0.001286
0.0011408
0.0010287
0.0008032
0.0007749
0.0006852
0.0052134
0.0039757
0.0032337
0.0055437
0.004115
0.0007609
SE (effect
estimate)3
0.000199
0.0007602
0.0006456
0.0002062
0.0002283
0.0002506
0.000267
0.0002672
0.0001385
0.0009087
0.0009789
0.0009359
0.0008939
0.0009226
0.0020002
Baseline incidence1"
2007
1,653
33,322
33,322
122,122
122,122
122,122
122,122
122,122
122,122
52,867
52,867
52,867
52,867
52,867
138,691
2009
1,697
34,432
34,432
126,013
126,013
126,013
126,013
126,013
126,013
53,243
53,243
53,243
53,243
53,243
138,494
Population
2007
357,309
963,574
963,574
5,033,453
5,033,453
5,033,453
5,033,453
5,033,453
5,033,453
18,554,574
18,554,574
18,554,574
18,554,574
18,554,574
702,975
2009
368,743
995,654
995,654
5,205,934
5,205,934
5,205,934
5,205,934
5,205,934
5,205,934
18,779,754
18,779,754
18,779,754
18,779,754
18,779,754
700,631
7A-4
-------
Endpoint
Asthma
Exacerbation, Chest
Tightness
Asthma
Exacerbation, Chest
Tightness
Asthma
Exacerbation, Chest
Tightness
Asthma
Exacerbation,
Shortness of Breath
Asthma
Exacerbation,
Shortness of Breath
Asthma
Exacerbation,
Wheeze
Study
Gent et al.,
2003
Gent et al.,
2003
Gent et al.,
2003
Gent et al.,
2003
Gent et al.,
2003
Gent et al.,
2003
Urban study
area
Boston, MA
Boston, MA
Boston, MA
Boston, MA
Boston, MA
Boston, MA
Study
area
template
Boston,
MA
Boston,
MA
Boston,
MA
Boston,
MA
Boston,
MA
Boston,
MA
Study information (C-R function)
Air metric
DSHourMax
DIHourMax
DIHourMax
DIHourMax
DSHourMax
DIHourMax
Risk
assessment
modeling
period
April-
September
(6)
April-
September
(6)
April-
September
(6)
April-
September
(6)
April-
September
(6)
April-
September
(6)
Age
range
0-12
0-12
0-12
0-12
0-12
0-12
Lag
Lag Id
Lag Id
Lag Id
Lag Id
Lag Id
LagOd
Additional
study
details
-
PM2.5
PM2.5
-
-
PM2.5
Statistical
Model
logistic
logistic
logistic
logistic
logistic
logistic
Effect
estimate
(Beta)
0.0057036
0.0077052
0.0070131
0.003977
0.0052473
0.0060021
SE (effect
estimate)3
0.0020217
0.0022666
0.0022734
0.0017947
0.0021808
0.0020225
Baseline incidence1"
2007
138,691
138,691
138,691
173,364
173,364
323,613
2009
138,494
138,494
138,494
173,117
173,117
323,152
Population
2007
702,975
702,975
702,975
702,975
702,975
702,975
2009
700,631
700,631
700,631
700,631
700,631
700,631
Sensitivity Analysis - short-term exposure-related all-cause mortality
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Atlanta, GA
Baltimore,
MD
Boston, MA
Cleveland,
OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles,
CA
Epi study
based
Epi study
based
Epi study
based
Epi study
based
Epi study
based
Epi study
based
Epi study
based
Epi study
based
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
March-
October
April-
October
April-
September
April-
October
March-
September
April-
September
January-
December
January-
December
0-99
0-99
0-99
0-99
0-99
0-99
0-99
0-99
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
-
-
-
-
-
-
-
-
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
0.0002411
0.0004192
0.0002807
0.0005654
0.0001657
0.0006432
0.0004999
0.0002179
0.0002919
0.00033
0.0003429
0.0003149
0.0003565
0.0003117
0.0002075
0.0001571
SA
completed
for 2009
6,267
3,287
2,252
7,541
5,140
8,174
19,642
55,949
SA
completed
for 2009
1,589,914
621,421
715,296
1,287,137
1,578,451
1,842,465
4,017,371
9,776,644
7A-5
-------
Endpoint
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Study
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Urban study
area
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
Study
area
template
Epi study
based
Epi study
based
Epi study
based
Epi study
based
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
Study information (C-R function)
Air metric
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
Risk
assessment
modeling
period
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
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
Lag
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
Additional
study
details
-
-
-
-
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
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
Effect
estimate
(Beta)
0.0010114
0.000714
0.0003016
0.0005401
0.0002603
0.0009399
0.0008827
0.0006789
0.0000293
0.0007159
0.000423
0.0001988
0.0011223
SE (effect
estimate)3
0.0002074
0.0002846
0.0003145
0.0003428
0.0002359
0.0002829
0.0003004
0.0002637
0.0003502
0.0002622
0.0001825
0.000151
0.0001808
Baseline incidence1"
2007
SA
completed
for 2009
2009
33,006
7,835
9,225
1,688
20,442
11,598
16,436
10,692
6,856
16,815
30,927
72,935
76,645
Population
2007
SA
completed
for 2009
2009
9,066,479
1,513,040
1,405,572
319,302
5,205,933
2,692,803
4,519,143
2,082,741
2,498,144
4,316,185
5,823,529
12,756,237
18,779,754
7A-6
-------
Endpoint
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Mortality, Non-
Accidental
Study
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Smith et al.,
2009
Urban study
area
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
Study
area
template
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
Study information (C-R function)
Air metric
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
DSHourMax
Risk
assessment
modeling
period
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
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
Lag
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
distributed
lag 0-6 d
Additional
study
details
Regional
Bayes-
based
Regional
Bayes-
based
Regional
Bayes-
based
PM10
PM10
PM10
PM10
PM10
PM10
PM10
PM10
PM10
PM10
PM10
PM10
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
Effect
estimate
(Beta)
0.001026
0.000107
0.0006754
0.0001183
0.0004727
0.0001591
0.0004626
0.0000383
0.000286
0.000631
0.0000524
0.0004407
0.0005445
0.0002805
0.0003602
SE (effect
estimate)3
0.0002395
0.000323
0.00028
0.0005456
0.000531
0.0005752
0.0004335
0.0005263
0.0004066
0.0003623
0.0003473
0.0003904
0.0005186
0.0005434
0.0005813
Baseline incidence1"
2007
SA
completed
for 2009
2009
27,658
13,361
13,686
20,442
11,598
16,436
10,692
6,856
16,815
30,927
72,935
76,645
27,658
13,361
13,686
Population
2007
SA
completed
for 2009
2009
5,936,034
2,127,784
2,803,333
5,205,933
2,692,803
4,519,143
2,082,741
2,498,144
4,316,185
5,823,529
12,756,237
18,779,754
5,936,034
2,127,784
2,803,333
7A-7
-------
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
Study
Zanobetti &
Schwartz
(b), 2008
Zanobetti &
Schwartz
(b), 2008
Zanobetti &
Schwartz
(b), 2008
Zanobetti &
Schwartz
(b), 2008
Zanobetti &
Schwartz
(b), 2008
Zanobetti &
Schwartz
(b), 2008
Zanobetti &
Schwartz
(b), 2008
Zanobetti &
Schwartz
(b), 2008
Zanobetti &
Schwartz
(b), 2008
Zanobetti &
Schwartz
(b), 2008
Zanobetti &
Schwartz
(b), 2008
Zanobetti &
Schwartz
(b), 2008
Urban 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
Study
area
template
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
Study information (C-R function)
Air metric
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
DSHourMean
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
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
Lag
distributed
lag 0-3 d
distributed
lag 0-3 d
distributed
lag 0-3 d
distributed
lag 0-3 d
distributed
lag 0-3 d
distributed
lag 0-3 d
distributed
lag 0-3 d
distributed
lag 0-3 d
distributed
lag 0-3 d
distributed
lag 0-3 d
distributed
lag 0-3 d
distributed
lag 0-3 d
Additional
study
details
-
-
-
-
-
-
-
-
-
-
-
-
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
Effect
estimate
(Beta)
0.0002954
0.000515
0.0006816
0.0005962
0.0003518
0.0010459
0.0001629
0.0002737
0.0010925
0.0006246
0.0005691
0.0005444
SE (effect
estimate)3
0.0002886
0.000314
0.0003284
0.0003546
0.0004088
0.0003441
0.0002628
0.0002134
0.0002357
0.0003146
0.0003885
0.0003334
Baseline incidence1"
2007
SA
completed
for 2009
Sensitivity Analysis - long-term exposure-related respiratory mortality0
Mortality,
Respiratory
Jerrett et
al., 2009
Atlanta, GA
CBSA
Seasonal-avg
DlhrMax
April-
September
30-99
NA
Regional
log-linear
0.0113329
0.0031929
2009
8,448
5,327
8,726
4,838
3,351
8,977
8,712
19,665
34,611
12,678
3,657
6,359
3,216
Population
2007
SA
completed
for 2009
2009
5,205,933
2,692,803
4,519,143
2,082,741
2,498,144
4,316,185
5,823,529
12,756,237
18,779,754
5,936,034
2,127,784
2,803,333
2,954,650
7A-8
-------
Endpoint
Mortality,
Respiratory
Mortality,
Respiratory
Mortality,
Respiratory
Mortality,
Respiratory
Mortality,
Respiratory
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
Jerrett et
al., 2009
Jerrett et
al., 2009
Jerrett et
al., 2009
Jerrett et
al., 2009
Jerrett et
al., 2009
Jerrett et
al., 2009
Jerrett et
al., 2009
Jerrett et
al., 2009
Jerrett et
al., 2009
Jerrett et
al., 2009
Jerrett et
al., 2009
Jerrett et
al., 2009
Jerrett et
al., 2009
Jerrett et
al., 2009
Jerrett et
al., 2009
Jerrett et
al., 2009
Jerrett et
al., 2009
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
Baltimore,
MD
Boston, MA
Cleveland,
OH
Denver, CO
Detroit, Ml
Study
area
template
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
Study information (C-R function)
Air metric
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
Seasonal-avg
DlhrMax
Seasonal-avg
DlhrMax
Seasonal-avg
DlhrMax
Seasonal-avg
DlhrMax
Seasonal-avg
DlhrMax
Risk
assessment
modeling
period
April-
September
April-
September
April-
September
April-
September
April-
September
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
30-99
30-99
30-99
30-99
30-99
30-99
30-99
30-99
30-99
30-99
30-99
30-99
30-99
30-99
30-99
30-99
30-99
Lag
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
Additional
study
details
Regional
Regional
Regional
Regional
Regional
Regional
Regional
Regional
Regional
Regional
Regional
ozone-
only
ozone-
only
ozone-
only
ozone-
only
ozone-
only
ozone-
only
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
Effect
estimate
(Beta)
-0.001005
-0.001005
0
0.0058269
0
0.0113329
0.000995
-0.001005
-0.001005
0.0058269
0
0.0026642
0.0026642
0.0026642
0.0026642
0.0026642
0.0026642
SE (effect
estimate)3
0.0038531
0.0038531
0.0046043
0.0031178
0.0046043
0.0031929
0.0027674
0.0038531
0.0038531
0.0031178
0.0046043
0.0009693
0.0009693
0.0009693
0.0009693
0.0009693
0.0009693
Baseline incidence1"
2007
SA
completed
for 2009
SA
completed
for 2009
2009
2,034
3,622
1,783
1,574
3,153
2,859
7,512
12,067
4,891
1,690
2,485
3,216
2,034
3,622
1,783
1,574
3,153
Population
2007
SA
completed
for 2009
SA
completed
for 2009
2009
1,609,957
2,747,634
1,294,845
1,454,586
2,628,339
3,165,283
7,236,439
11,303,888
3,545,106
1,221,735
1,676,509
2,954,650
1,609,957
2,747,634
1,294,845
1,454,586
2,628,339
7A-9
-------
Endpoint
Mortality,
Respiratory
Mortality,
Respiratory
Mortality,
Respiratory
Mortality,
Respiratory
Mortality,
Respiratory
Mortality,
Respiratory
Study
Jerrett et
al., 2009
Jerrett et
al., 2009
Jerrett et
al., 2009
Jerrett et
al., 2009
Jerrett et
al., 2009
Jerrett et
al., 2009
Urban study
area
Houston, TX
Los Angeles,
CA
New York,
NY
Philadelphia,
PA
Sacramento,
CA
St. Louis,
MO
Study
area
template
CBSA
CBSA
CBSA
CBSA
CBSA
CBSA
Study information (C-R function)
Air metric
Seasonal-avg
DlhrMax
Seasonal-avg
DlhrMax
Seasonal-avg
DlhrMax
Seasonal-avg
DlhrMax
Seasonal-avg
DlhrMax
Seasonal-avg
DlhrMax
Risk
assessment
modeling
period
April-
September
April-
September
April-
September
April-
September
April-
September
April-
September
Age
range
30-99
30-99
30-99
30-99
30-99
30-99
Lag
NA
NA
NA
NA
NA
NA
Additional
study
details
ozone-
only
ozone-
only
ozone-
only
ozone-
only
ozone-
only
ozone-
only
Statistical
Model
log-linear
log-linear
log-linear
log-linear
log-linear
log-linear
Effect
estimate
(Beta)
0.0026642
0.0026642
0.0026642
0.0026642
0.0026642
0.0026642
SE (effect
estimate)3
0.0009693
0.0009693
0.0009693
0.0009693
0.0009693
0.0009693
Baseline incidence1"
2007
2009
2,859
7,512
12,067
4,891
1,690
2,485
Population
2007
2009
3,165,283
7,236,439
11,303,888
3,545,106
1,221,735
1,676,509
a all Beta distributions assumed to be normal.
b Gent et al., 2003 also uses the following prevalence rates: 0.028 (wheeze), 0.015 (shortness of breath), 0.012 (chest tightness) (from study).
0 Threshold models were considered as sensitivity analyses for long-term exposure-related respiratory mortality (see section HREA 7.3.2). Given that the same threshold-specific effect
estimate was used for all 12 study areas, they are not presented here to avoid repetition (see Sasser, 2014 for a listing of the coefficients and standard errors). Other model inputs used in
modeling thresholds for this effect endpoint are the same as for other applications of Jerrett et al., 2009 (see table entries).
7 A-10
-------
REFERENCES
Darrow, L.A.; M. Klein; J.A. Sarnat; J.A. Mulholland; MJ. Strickland; S.E. Sarnat, et al. 2011.
The use of alternative pollutant metrics in time-series studies of ambient air pollution and
respiratory emergency department visits. Journal of Exposure Science and Environmental
Epidemiology. 21:10-19.
Gent, J.F.; E.W. Triche; T.R. Holford; K. Belanger; M.B. Bracken; W.S. Beckett, et al. 2003.
Association of low-level ozone and fine particles with respiratory symptoms in children
with asthma. Journal of the American Medical Association. 290(14): 1859-1867.
Ito, K.; G.D. Thurston and R.A. Silverman. 2007. Characterization of PM2.5, gaseous pollutants,
and meteorological interactions in the context of time-series health effects models.
Journal of Exposure Science and Environmental Epidemiology. 17(S2):S45-60.
Katsouyanni, K.; J.M. Samet; H.R. Anderson; R. Atkinson; A.L. Tertre; S. Medina, et al. 2009.
Air Pollution and Health: A European and North American Approach (APHENA). Health
Effects Institute.
Lin, S; X. Liu; L.H. Le; S.A. Hwang. 2008. Chronic exposure to ambient ozone and asthma
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7 A-11
-------
APPENDIX 7B
Detailed Summary Tables and Figures of Core Risk Estimates
List of Tables
Table 7B-1. Core Short-Term Ozone-Attributable Mortality (2007) (incidence, percent of
baseline mortality, incidence per 100,000) (Smith et al., 2009) 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) 7B-2
Table 7B-3a. Core Short-Term Ozone-Attributable Morbidity - Hospital Admissions (2007).
7B-7
Table 7B-3b. Core Short-Term Ozone-Attributable Morbidity - Hospital Admissions (2009).
7B-8
Table 7B-4a. Core Short-Term Ozone-Attributable Morbidity - Emergency Room Visits
(2007) 7B-9
Table 7B-4b. Core Short-Term Ozone-Attributable Morbidity - Emergency Room Visits
(2009) 7B-10
Table 7B-5a. Core Short-Term Ozone-Attributable Morbidity - Asthma Exacerbations (2007).
7B-11
Table 7B-5b. Core Short-Term Ozone-Attributable Morbidity - Asthma Exacerbations (2007).
7B-10
Table 7B-6. Core Long-Term Ozone-Attributable Respiratory Mortality (2007) (incidence,
percent of baseline mortality, incidence per 100,000) (Jerrett et al., 2009). .. 7B-12
Table 7B-7. Core Long-Term Ozone-Attributable Respiratory Mortality (2009) (incidence,
percent of baseline mortality, incidence per 100,000) (Jerrett et al., 2009). .. 7B-13
List of Figures
Figure 7B-1. Core Short-Term Ozone-Attributable Mortality (2007) (heat map tables - absolute
ozone-attributable incidence) (Smith et al., 2009) 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 7B-4
Figure 7B-3. Core Short-Term Ozone-Attributable Mortality (2009) (heat map tables - absolute
ozone-attributable incidence) (Smith etal., 2009) 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 7B-6
7B-i
-------
Table 7B-1. Core Short-Term Ozone-Attributable Mortality (2007) (incidence, percent
baseline mortality, incidence per 100,000) (Smith et al., 2009).
of
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
250
(-350-840)
240
(-130-600)
210
(-290-680)
270
(-25-550)
59
(-190-300)
520
(26-990)
540
(100-970)
640
(-270-1500)
3400
(2000 - 4700)
960
(210-1700)
170
(-180-500)
370
(-92-810)
75ppb
220
(-310-740)
230
(-130-570)
200
(-290-670)
270
(-25-550)
58
(-190-300)
520
(26-990)
580
(110-1000)
750
(-310-1800)
3200
(1900-4500)
920
(200-1600)
160
(-170-480)
350
(-86-770)
70ppb
210
(-300-710)
220
(-120-560)
200
(-280-660)
260
(-24-540)
57
(-190-290)
500
(25-960)
580
(110-1000)
730
(-300-1700)
3100
(1900-4300)
890
(200-1600)
160
(-170-470)
330
(-83-740)
65ppb
200
(-280-680)
210
(-120-540)
190
(-270-640)
250
(-23-510)
55
(-180-280)
480
(25-930)
570
(110-1000)
700
(-290-1700)
2500
(1500-3500)
860
(190-1500)
160
(-160-470)
320
(-79-700)
60ppb
190
(-270-650)
210
(-110-520)
180
(-260-620)
230
(-21-470)
53
(-170-270)
460
(24-890)
560
(110-1000)
660
(-270-1600)
NA
830
(180-1500)
150
(-160-450)
300
(-74-660)
Change in Ozone-Attributable Incidence
Base -75
31
(-42-100)
12
(-6-30)
3
(-5-11)
0
(0--1)
1
(-2-3)
2
(0-4)
-39
(-7 --71)
-110
(46- -270)
170
(100-240)
47
(10-84)
5
(-5-15)
22
(-6-50)
75-70
10
(-13-32)
7
(-4-17)
4
(-6-14)
8
(-1-18)
1
(-4-7)
18
(1-35)
4
(1-8)
26
(-11-62)
150
(92-220)
26
(6-46)
3
(-3-9)
15
(-4-33)
75-65
18
(-24-60)
14
(-8-35)
11
(-16-39)
20
(-2-41)
3
(-10-15)
33
(2-64)
9
(2-17)
52
(-22-130)
740
(440-1000)
56
(12-100)
6
(-6-17)
31
(-8-70)
75-60
28
(-39-95)
23
(-13-59)
18
(-25-62)
40
(-4-83)
5
(-17-27)
54
(3-110)
20
(4-37)
96
(-40-230)
NA
86
(19-150)
10
(-11-31)
49
(-12-110)
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
0.9
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
1.1
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
3.1
1.2
2.3
60ppb
1.0
1.7
1.1
2.1
0.8
2.7
1.9
0.9
NA
3.0
1.1
2.1
Change in OrAttributable Risk
Base -75
12
5
2
-0.1
1
0.3
-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
13
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
5.0
9.0
4.6
13
2.4
12
9.8
5.1
18
16
8.0
13
75ppb
4.4
8.6
4.5
13
2.4
12
10
6.0
17
16
7.7
13
70ppb
4.2
8.3
4.5
12
2.4
11
10
5.8
17
15
7.6
12
65ppb
4.1
8.1
4.3
12
2.3
11
10
5.6
14
15
7.5
11
60ppb
3.8
7.7
4.1
11
2.2
11
10
5.2
NA
14
7.3
11
Base -75
0.61
0.44
0.074
-0.011
0.023
0.049
-0.70
-0.88
0.93
0.81
0.23
0.81
75-70
0.19
0.25
0.092
0.40
0.054
0.41
0.075
0.20
0.83
0.44
0.14
0.53
75-65
0.35
0.52
0.26
0.95
0.12
0.75
0.17
0.41
4.0
0.96
0.27
1.1
75-60
0.56
0.87
0.41
1.9
0.22
1.2
0.36
0.76
NA
1.5
0.49
1.7
NA: for NYC, the model-based adjustment methodology was unable to estimate ozone distributions which would meet the
alternative standard level of 60 ppb.
"0" incidence values denote non-zero estimates that round to zero.
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
Air Quality Scenario
Absolute Ozone-Attributable Incidence
Base
200
(-280-680)
210
(-120-530)
180
(-260-610)
250
(-23-510)
56
(-180- 290)
460
(23 - 880)
550
(100-990)
670
(-280- 1600)
2900
(1800-4100)
820
(180-1400)
170
(-180-500)
310
(-77-690)
75ppb
200
(-280-670)
210
(-110-520)
180
(-260-610)
250
(-23-510)
56
(-180-290)
460
(23-880)
600
(110- 1100)
770
(-320-1800)
3000
(1800-4200)
820
(180- 1400)
160
(-170-490)
310
(-77 - 690)
TOppb
190
(-270-650)
200
(-110-510)
180
(-260-620)
240
(-22-500)
56
(-180-290)
470
(24-910)
600
(110-1100)
750
(-310- 1800)
2900
(1800-4100)
810
(180-1400)
160
(-170-480)
300
(-75-670)
65ppb
190
(-260-620)
200
(-110-500)
180
(-260-600)
230
(-21-480)
55
(-180-280)
460
(23-890)
590
(110- 1100)
720
(-300-1700)
2500
(1500-3500)
790
(170- 1400)
160
(-170-470)
290
(-73 - 650)
eoppb
180
(-250-610)
190
(-110-480)
180
(-250-590)
220
(-20-450)
51
(-170-260)
440
(23-850)
580
(110-1000)
670
(-280-1600)
NA
770
(170-1400)
150
(-160-460)
280
(-69 - 620)
Change in Ozone-Attributable Incidence
Base-75
4
(-5-13)
3
(-2-7)
-1
(2 --4)
-3
(0--6)
0
(1--1)
NA
-47
(-9 --85)
-99
(41- -240)
-89
(-53- -120)
-4
(-1--8)
5
(-5-14)
1
(0-3)
T5-TO
7
(-10-24)
4
(-2-10)
-1
(1--2)
7
(-1-15)
0
(-1-1)
-17
(-1--33)
-1
(0--1)
25
(-10-60)
96
(57 - 130)
14
(3-25)
3
(-3-8)
7
(-2-15)
T5-65
13
(-18-45)
9
(-5-23)
3
(-4-10)
18
(-2-37)
1
(-4-7)
-5
(0--10)
3
(1-6)
53
(-22-130)
500
(300-700)
33
(7-58)
5
(-6-17)
17
(-4-37)
T5-60
19
(-26-64)
14
(-8-37)
8
(-11-27)
31
(-3-64)
5
(-15-25)
12
(1-23)
12
(2-22)
98
(-41 - 240)
NA
51
(11-90)
9
(-10-28)
30
(-7-67)
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
1.0
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
4.0
3.0
1.2
2.3
TOppb
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
2.9
1.2
2.1
eoppb
0.9
1.7
1.1
2.0
0.7
2.6
1.9
0.9
NA
2.8
1.1
2.0
Change in Or Attributable Risk
Base-75
2
1
-1
-1
-0.4
NA
-8
-15
-3
-1
3
0.4
T5-TO
3
2
-0.3
3
0.3
-4
-0.1
3
3
2
2
2
T5-65
7
4
2
7
2
-1
0.5
7
16
4
3
5
T5-60
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
Air Quality Scenario
Ozone-Attributable Deaths per 100,000 Change in Ozone-Attributable Deaths per 100,000
Base
3.9
7.8
4.0
12
2.2
11
9.4
5.3
16
14
7.8
11
75ppb
3.9
7.7
4.1
12
2.2
11
10
6.0
16
14
7.6
11
TOppb
3.7
7.6
4.1
12
2.2
11
10
5.8
16
14
7.5
11
65ppb
3.6
7.4
4.0
11
2.2
11
10
5.6
14
13
7.4
10
eoppb
3.5
7.2
3.9
11
2.1
10
10
5.3
NA
13
7.2
10
Base-T5
0.071
0.11
-0.028
-0.14
-0.0098
NA
-0.80
-0.77
-0.47
-0.070
0.21
0.041
T5-TO
0.14
0.14
-0.013
0.35
0.0081
-0.39
-0.010
0.19
0.51
0.24
0.13
0.24
T5-65
0.26
0.33
0.064
0.86
0.054
-0.11
0.054
0.42
2.7
0.55
0.26
0.60
T5-60
0.37
0.54
0.18
1.5
0.19
0.28
0.21
0.77
NA
0.85
0.44
1.1
NA: for NYC, the model-based adjustment methodology was unable to estimate ozone distributions which would meet the
alternative standard level of 60 ppb. For Detroit, already meeting existing standard
"0" incidence values denote non-zero estimates that round to zero.
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
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Dairy 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
1
3
0
1
0
15-20
1
0
2
0
0
14
47
5
2
20-25
±
5
5
0
5
33
93
15
7
1 1 1 | 2
25-30
4
10
10
14
0
23
38
169
39
10
9
30-35
10
10
27
28
31
69
339
63
17
17
35-40
13
25
24
30
48
58
549
70
25
34
40-45
17
20
36
45
76
96
326
118
19
49
45-50
24
28
22
34
96
84
446
97
21
33
50-55
34
30
17
33
50
81
306
112
20
58
55-60
47
29
18
25
12
30
79
228
117
19
48
60-65
29
18
14
23
12
41
35
222
69
10
32
65-70
30
33
10
15
6
20
20
266
93
7
25
70-75
20
20
5
6
3
29
15
205
86
5
23
>75
19
13
1
6
1
197
76
3
36
Total
252
240
205
268
59
518
643
3,391
961
165
369
Current Standard (75]
Alternative Standard 70
Alternative Standard 65
Alternative Standard 60
Study area
Atlanta, GA
Boston, MA
Cleveland, OH
Denver, CO
Detroit Ml
Houston, TX
Los Angeles, CA
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Dairy Shr Max Ozone Level (ppb)
0-5
0
0
0
0
0
0
0
0
0
0
5-10
0
0
0
0
0
0
0
0
0
0
10-15
0
0
0
0
0
0
0
0
0
0
15-20
0
0
1
0
0
0
0
2
0
1
20-25
2
2
3
0
1
14
0
0
1
2
25-30
4
11
9
0
5
42
0
25
8
6
30-35
15
26
25
1
33
107
0
46
23
15
35-40
20
29
41
3
56
124
10
115
43
52
40-45
34
33
55
4
97
126
204
157
29
53
45-50
43
33
50
9
116
81
268
175
29
61
50-55
52
20
27
12
59
42
233
155
17
60
55-60
31
12
25
15
41
42
27
122
9
38
60-65
12
17
19
10
44
2
8
75
2
24
65-70
5
5
8
3
16
0
3
31
1
23
70-75
3
7
6
1
34
0
0
7
0
10
>75
0
6
0
0
14
0
0
7
0
3
Total
222
202
268
58
516
580
753
916
161
348
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
Dairy 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
0
1
0
0
0
0
0
0
0
1
20-25
1
2
2
0
0
8
0
15
2
0
2
25-30
6
11
10
0
5
41
0
156
23
7
30-35
7
27
26
~0~
33
108
0
392
45
20
35-40
28
35
45
3
65
141
17
749
133
61
40-45
49
31
67
5
119
139
240
930
202
35
61
45-50
44
31
47
11
IB
81
362
597
167
30
68
50-55
43
21
24
17
50
45
98
224
160
9
47
55-60
26
16
21
15
55
11
5
20
89
6
34
60-65
11
8
14
4
23
0
5
0
57
0
24
65-70
5
7
4
2
24
0
0
0
6
1
9
70-75
2
4
0
0
13
0
0
0
7
0
0
>75
0
4
0
0
0
0
0
0
0
0
0
Total
222
198
260
57
499
576
727
3,083
891
158
333
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
Dairy 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
1
1
1
2
0
0
0
43
2
0
2
25-30
8
5
11
11
0
0
694
23
5
7
30-35
20
11
31
34
0
0
710
45
28
29
35-40
24
34
36
57
2
63
1,057
143
50
62
40-45
54
51
37
65
7
144
149
312
15
228
41
69
45-50
55
44
31
42
14
96
69
288
0
197
22
75
50-55
31
43
21
22
21
56
38
29
0
148
7
38
55-60
8
19
12
11
10
37
0
7
0
63
2
28
60-65
4
6
6
4
2
29
0
3
0
6
1
6
65-70
0
2
3
0
0
12
0
0
0
6
0
0
70-75
0
0
2
0
0
0
0
0
0
0
0
0
>75
0
0
0
0
0
0
0
0
0
0
0
0
Total
204
215
191
249
55
484
571
701
2,519
862
155
317
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
Dairy 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
0
0
0
0
0
0
0
0
0
0
20-25
2
1
1
3
0
0
0
0
2
0
2
25-30
0
2
5
8
0
21
4
8
30-35
21
12
39
51
0
39
136
7
61
33
45
35-40
41
45
29
66
2
106
192
225
161
59
73
40-45
53
56
53
70
9
139
152
264
NA
263
38
92
45-50
48
56
26
15
21
101
48
151
218
13
46
50-55
16
25
12
10
18
55-60
2
7
7
0
3
31
0
0
5
1
4
60-65
0
0
3
0
0
0
0
0
6
0
0
65-70
0
0
2
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
194
206
184
229
53
463
560
658
834
151
300
NA: for NYC, the model-based adjustment methodology was unable to estimate ozone distributions which would meet the
alternative standard level of 60 ppb.
7B-2
-------
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
-6
-7
0
-1
0
0
15-20
0
0
0
-1
0
0
-11
-18
-18
-3
-1
0
20-25
0
0
-1
-28
-30
-3
-2
0
25-30
0
-1
0
-2
0
-4
-15
-22
-31
-9
-2
-1
30-35
0
35-40
0
-1
0
-1
0
-4
-6
-14
-25
-5
0
0
40-45
1
0
0
-1
0
-3
0
-14
7
0
1
2
45-50
2
1
0
1
0
1
3
-5
44
3
2
2
50-55
9
0
55-60
6
2
1
1
0
2
3
7
38
12
3
4
60-65
5
2
1
1
1
3
4
5
38
9
2
3
65-70
5
4
1
1
0
2
4
4
56
14
1
3
70-75
4
3
0
1
0
3
5
3
48
14
1
3
> 5
Total
31
9
- 1
2
Change in risk
Inc.
0
-6
-4
-8
0
-19
-65
-134
-169
-36
-7
-3
Dec.
31
18
6
7
1
22
26
25
341
82
13
27
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
0
0
0
0
0
0
0
0
0
0
0
510
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
-1
0
-1
0
0
0
0
0
0
0
0
0
-1
0
-2
-1
0
0
30-35
0
0
0
0
0
0
-1
0
0
0
0
0
35-40
0
0
0
0
0
0
0
0
14
0
0
1
40-45
1
1
0
1
0
2
2
4
31
2
1
2
45-50
2
1
1
2
0
4
2
10
37
5
1
3
50-55
55-60
2
2
0
2
1
2
1
29
6
0
2
60-65
1
1
1
1
0
0
0
6
4
0
2
65-70
0
0
0
1
0
0
0
0
2
0
2
70-75
0
0
0
0
0
0
0
0
0
0
1
>75
0
0
0
0
0
0
0
0
1
0
0
Total
10
7
4
8
1
18
4
26
154
26
3
15
Change in risk
Inc.
0
0
0
0
0
0
-3
0
-13
-2
0
0
Dec.
10
6
3
10
1
19
8
25
167
27
4
16
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
0
0
0
0
-2
0
2
-1
0
0
30-35
1
0
0
0
0
0
2
0
35-40
1
0
1
1
0
0
0
0
98
0
1
2
40-45
2
2
1
4
0
3
4
8
172
5
1
4
45-50
4
2
2
4
0
7
4
20
156
11
2
6
50-55
6
55-60
3
4
1
3
1
4
4
2
103
14
1
5
60-65
1
2
2
3
1
5
0
1
22
9
0
3
65-70
1
1
1
1
0
2
0
0
0
4
0
3
70-75
0
1
1
1
0
5
0
0
0
1
0
2
>75
0
0
1
0
0
2
0
0
0
1
0
0
Total
18
14
11
20
3
33
9
52
735
56
6
31
Change in risk
Inc.
0
0
0
-1
0
-2
-8
0
-7
-4
-1
0
Dec.
18
15
12
20
3
35
16
52
742
60
6
31
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
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
0
0
0
0
0
0
-2
0
0
0
0
25-30
0
0
0
0
0
0
-4
0
-1
-1
0
30-35
1
0
0
0
0
-1
-4
0
-1
-1
0
35-40
2
0
1
3
0
1
1
1
1
2
4
40-45
4
3
2
7
0
6
45-50
6
4
3
9
0
11
7 8
24 | 35
NA
8
3
6
17
3
9
50-55
7
5
3
6
1
8
6
29
19
2
10
55-60
5
6
2
6
2
7
7
4
20
1
7
60-65
13
0
5
65-70
1
1
1
2
1
4
0
1
6
0
5
70-75
1
1
2
2
0
7
0
0
1
0
2
>75
0
0
1
0
0
3
0
0
2
0
1
Total
28
23
18
40
5
54
20
96
86
10
49
Change in risk
Inc.
0
0
0
-2
0
-2
-11
0
-4
-2
0
Dec.
29
25
19
41
6
57
31
95
89
11
49
NA: for NYC, the model-based adjustment methodology was unable to estimate ozone distributions which would meet the
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
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
NewYork, NY
Philadelphia, PA
Saoramento, CA
St. Louis, MO
Daily Shr Max Ozone Level (ppb)
0-5
0
0
0
0
0
0
0
0
0
0
0
^5^0
0
0
0
0
0
1
1
0
0
0
10-15
1
1
0
0
0
1
7
4
B
4
15-20
3
1
0
4
0
7
18
12
93
10
20-25
6
6
6
8
0
B
34
23
16B
22
25-30
16
12
19
17
1
21
68
40
248
B6
30-35
13
20
21
20
1
36
80
68
322
21
35-40
20
20
32
31
2
B3
SB
Bl
373
67
IB
47
40-45
36
20
29
BO
7
89
60
63
466
116
22
38
45-50
32
29
1
3
1
16
B
09
67
10
1
B
50-55
26
40
2B
3B
13
30
B3
98
370
114
19
60
55-60
23
33
6
13
40
240
124
13
39
60-65
18
IB
2
6
36
1B3
68
10
17
65-70
8
7
3
1
0
41
116
30
IB
9
70-75
1
B
B
1
17
12
2B
7
9
0
>75
0
0
2
0
0
B
10
0
0
3
0
Total
204
210
182
246
B6
4B6
B49
672
2,944
817
166
311
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
NewYork, NY
Philadelphia, PA
Saoramento, CA
St. Louis, MO
Daily 8hr
0-5
0
0
0
0
0
0
0
0
0
0
dax Ozone
5-10
0
0
0
0
0
0
0
0
0
0
Level (pp
10-15
1
0
0
0
0
0
0
0
0
0
3)
15-20
2
0
0
0
0
0
7
2
0
20-25
7
2
7
3
0
0
41
12
1
25-30
13
7
14
16
1
0
246
38
10
30-35
IB
21
26
28
1
489
118
28
22
35-40
28
36
33
42
107
10
407
93
30
44
40-45
41
33
29
46
%
168
724
162
32
42
45-50
37
47
31
BO
77
1%
B38
130
24
63
50-55
24
33
27
3B
72
297
314
1B1
B3
55-60
2B
23
4
17
31
91
201
67
14
60-65
8
6
2
7
23
B
64
BO
3
65-70
1
0
3
4
6
0
0
0
0
70-75
0
0
B
0
0
3
0
0
0
0
>75
0
0
2
0
0
3
0
0
0
0
Total
201
207
183
249
B6
B9B
770
3,031
822
162
Study area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Detroit, Ml
Houston, TX
Los Angeles, CA
NewYork, NY
Philadelphia, PA
Saoramento, 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
1
0
0
0
0
2
0
0
0
0
3
20-25
8
2
1
1
9
21
0
42
13
1
8
25-30
14
7
17
16
10
41
0
203
33
7
12
30-35
18
20
23
3B
33
104
1
B48
109
34
28
35-40
38
40
37
47
B8
124
24
609
127
3B
Bl
40-45
48
42
34
B3
82
99
198
847
1B2
3B
B8
45-50
27
46
33
49
137
97
301
434
180
21
B8
50-55
24
37
2B
31
66
70
18B
2B6
127
22
B2
55-60
16
10
3
B
BO
22
36
0
62
6
2B
60-65
1
0
0
B
7
10
0
0
B
0
8
65-70
0
0
B
0
IB
3
0
0
0
0
0
70-75
0
0
B
0
4
3
0
0
0
0
0
>75
0
0
0
0
0
0
0
0
0
0
0
Total
194
203
184
242
472
B96
74B
2,940
808
1B9
304
Study area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Detroit, Ml
Houston, TX
Los Angeles, CA
NewYork, NY
Philadelphia, PA
Saoramento, 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
1
0
0
0
0
0
0
0
0
0
1
20-25
7
1
1
1
8
10
0
43
11
0
10
25-30
10
6
17
IB
8
38
0
B40
31
6
10
30-35
27
22
27
BO
31
118
1
827
102
36
33
35-40
44
44
37
Bl
68
142
BB
171
43
61
40-45
B3
B6
40
B7
11B
11B
241
B8
193
34
70
45-50
21
38
43
13B
109
319
0
172
19
B2
50-55
23
29
10
B2
41
96
0
SB
18
46
55-60
1
2
B
26
12
B
0
2B
1
12
60-65
0
0
0
14
B
0
0
0
0
0
65-70
0
0
0
4
3
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
187
198
181
231
461
B92
717
2,B47
791
1B6
294
Study area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Los Angeles, CA
NewYork, NY
Philadelphia, PA
Saoramento, CA
St. Louis, MO
Daily Shr Max Ozone Level (ppb)
0-5
0
0
0
0
0
0
0
0
0
0
5-10
0
0
0
0
0
0
0
0
0
0
10-15
0
0
0
0
0
0
0
0
0
0
15-20
0
0
0
0
0
0
0
0
0
0
20-25
0
B
0
10
25-30
12
B
19
17
0
13
0
23
4
11
30-35
3B
27
34
68
0
31
4
109
38
47
35-40
47
B4
37
BO
B
9B
199
214
B2
76
40-45
47
BB
4B
B8
12
129
216
NA
220
31
64
45-50
2B
37
26
21
29
123
242
142
2B
B8
50-55
8
14
B
4
B
36
11
61
2
16
55-60
0
0
4
0
0
10
0
0
0
0
60-65
0
0
B
0
0
3
0
0
0
0
65-70
0
0
0
0
0
0
0
0
0
0
70-75
0
0
0
0
0
0
0
0
0
0
>75
0
0
0
0
0
0
0
0
0
0
Total
182
193
176
219
Bl
444
673
773
1B3
281
NA: for NYC, the model-based adjustment methodology was unable to estimate ozone distributions which would meet the
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 conditinos 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
-1
-2
0
0
0
0
10-15
0
-1
0
0
0
0
-4
-9
-3
-2
-1
0
15-20
0
0
0
-2
0
0
-7
20-25
0
-2
0
-2
0
0
-9
-15 -19
^4 | -6
-1 1 -2
0
0
25-30
-1
-2
0
-2
0
0
-12
-23
-42
-9
-2
0
30-35
0
-2
0
-2
0
0
-10
-26
-27
-7
-1
0
35-40
0
-1
0
-1
0
0
-8
-13
-18
-4
0
0
40-45
1
0
0
0
0
0
-3
-10
-4
1
1
0
45-50
1
2
0
1
0
0
-1
-8
10
3
2
0
50-55
1
3
0
2
0
0
1
1
23
5
2
1
55-60
1
3
0
1
0
0
2
5
20
9
2
1
60-65
1
2
0
1
0
0
1
7
16
5
2
0
65-70
1
1
0
1
0
0
1
7
13
3
3
0
70-75
0
1
0
0
0
0
1
2
3
1
2
0
>75
0
0
0
0
0
0
1
3
0
0
1
0
Total
4
3
-1
-3
0
0
-47
-99
-89
-4
5
1
Change in risk
Inc.
-1
-9
0
-10
0
0
-55
-126
-198
-36
-7
0
Dec.
6
13
0
7
0
0
7
26
109
32
15
2
Decrease 75 to 70
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
0
15-20
0
0
0
0
0
-1
0
-1
0
0
-1
20-25
0
0
-1
0
0
-2
0
-4
-1
25-30
0
0
0
0
0
-2
30-35
0
0
-1
0
0
-3
0 | 0
^2 | ^2
0 0 | 0
0
-1
0
35-40
1
0
0
1
0
-1
0
9
-1
0
0
40-45
1
1
0
1
0
1
3
26
3
1
1
45-50
2
1
0
2
0
1
6
36
4
1
2
50-55
2
1
0
2
0
2
12
26
6
1
2
55-60
2
1
0
1
0
1
4
21
3
1
2
60-65
1
0
0
0
0
1
0
7
3
0
1
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
7
4
-1
7
0
-1
25
96
14
3
7
Change in risk
Inc.
0
0
-3
0
0
-9
0
-44
-6
0
-2
Dec.
9
4
2
7
0
6
25
139
21
4
9
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
0
15-20
0
0
0
0
0
-3
-1
0
-1
0
0
-1
20-25
-1
0
-1
0
0
-1
25-30
-1
0
-1
-1
0
-5
30-35
0
0
-1
0
0
-4
-4 1 -4 | -5
0
-5
-2
0
-1
±
-1
-1
0
18
-3
0
0
35-40
1
0
0
2
0
-3
-1
0
60
-1
1
1
40-45
3
1
1
3
0
-2
2
6
122
8
2
2
45-50
4
3
1
5
0
3
3
14
138
8
2
5
50-55
3
2
2
4
0
1
5
25
93
13
1
5
55-60
3
2
0
3
1
4
3
8
72
7
1
5
60-65
1
1
0
1
0
4
3
0
24
6
0
1
65-70
0
0
0
1
0
0
1
0
0
0
0
1
70-75
0
0
1
0
0
2
1
0
0
0
0
0
>75
0
0
0
0
0
1
0
0
0
0
0
0
Total
13
9
3
18
1
-5
3
53
500
33
5
17
Change in risk
Inc.
-2
-1
-4
-1
0
-21
-15
0
-48
-11
-2
-4
Dec.
15
11
6
21
1
16
19
53
550
44
7
22
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
DailyShrT
0-5
0
0
0
0
0
0
0
0
0
0
0
.flax Ozone
5-10
0
0
0
0
0
0
0
0
0
0
0
Level (pp
10-15
0
0
0
0
0
-1
0
0
0
0
-1
)
15-20
0
0
0
0
0
-4
-2
0
-1
0
-2
20-25
-1
0
-1
0
0
-2
-6
0
-2
0
-1
25-30
-1
-1
-1
0
0
-6
-6
0
-4
-1
-1
30-35
0
0
-1
1
0
-4
-6
0
-3
-1
0
35-40
2
1
1
4
0
-2
0
1
0
1
3
40-45
4
2
1
5
0
1
4
19
12
3
4
45-50
5
5
3
8
0
8
7
26
NA
12
3
8
50-55
4
4
3
7
1
3
9
E
19
2
8
55-60
4
3
1
4
2
6
5
13
10
2
7
60-65
2
1
0
2
1
6
5
1
8
0
2
65-70
0
0
0
1
0
0
1
0
0
0
1
70-75
0
0
1
0
0
4
1
0
0
0
0
>75
0
0
0
0
0
1
1
0
0
0
0
Total
19
14
8
31
5
12
12
98
51
9
30
Change
In
0
-22
-22
0
-14
-2
-6
in risk
Dec.
21
16
11
33
5
32
35
97
65
11
34
NA: for NYC, the model-based adjustment methodology was unable to estimate ozone distributions which would meet the
alternative standard level of 60 ppb.
7B-6
-------
Table 7B-3a. Core Short-Term Ozone-Attributable Morbidity - Hospital Admissions
(2007).
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
HA
HA
HA
respiratory); Detroit (Katsouyanni et al., 2009)
Ihr max, penalized splines
Ihr max, natural splines
200
(-47-430)
190
(-58-430)
190
(-44-410)
180
(-54-400)
180
(-41 - 380)
170
(-51 - 380)
170
(-40-370)
160
(-49 - 360)
160
(-37-340)
150
(-45-340)
14
(-3.2-31)
13
(-4.0-31)
10
(-2.4-23)
9.8
(-2.9-22)
18
(-4.3-41)
18
(-5.3-40)
29
(-6.8-65)
28
(-8.4-65)
respiratory); NYC (Silverman and Ito, 2010; Lin et al., 2008)
HA Chronic Lung Disease (Lin)
HA Asthma (Silverman)
HA Asthma, PM2.5 (Silverman)
160
(92-220)
520
(39-860)
390
(-140-760)
140
(84-200)
490
(35-810)
360
(-130-710)
140
(80-190)
460
(33 - 780)
340
(-120-680)
110
(65- 160)
380
(26-660)
280
(-94-570)
NA
14
(8.0- 19)
58
(3.8-110)
42
(-13-91)
7.9
(4.6-11)
33
(2.1-63)
23
(-7.2-53)
34
(20-48)
140
(8.9-250)
98
(-31-210)
NA
respiratory);LA(Linnetal., 2000)
Ihr max penalized splines
370
(-480-1,200)
480
(-630-1,500)
460
(-610-1,500)
450
(-600-1,500)
440
(-580-1,400)
-110
(140- -370)
11
(-15-37)
23
(-29-74)
36
(-47-120)
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
64
(18- 110)
43
(12-73)
59
(17-100)
38
(11-65)
18
(5-32)
72
(20-120)
55
(15-94)
110
(31-190)
220
(63 - 380)
110
(30- 180)
17
(5-29)
46
(13-79)
55
(15-93)
40
(11-68)
58
(16-99)
37
(11-64)
18
(5-31)
71
(20-120)
57
(16-97)
110
(31-190)
200
(57 - 350)
97
(27-160)
15
(4-25)
43
(12-73)
52
(15-89)
38
(11-66)
57
(16-97)
36
(10-62)
18
(5-30)
69
(19-120)
56
(16-96)
110
(30-180)
190
(53 - 330)
93
(26-160)
14
(4-25)
41
(11-69)
50
(14-85)
37
(10-63)
54
(15-93)
34
(10-59)
17
(5-29)
67
(19-110)
55
(15-94)
100
(28-170)
150
(41 - 250)
90
(25- 150)
14
(4-24)
38
(11-66)
47
(13-80)
35
(10-60)
52
(15-90)
31
(9-53)
16
(5-27)
64
(18-110)
54
(15-92)
96
(27-160)
NA
86
(24- 150)
13
(4-23)
36
(10-62)
10
(3-17)
3
(1-6)
2
(0-3)
1
(0-1)
0
(0-1)
0
(0-1)
-2
(-1--4)
2
(0-3)
21
(6-37)
9
(2-15)
2
(1-3)
4
(1-6)
3
(1-5)
1
(0-3)
1
(0-2)
1
(0-2)
1
(0-1)
2
(1-4)
1
(0-1)
5
(1-9)
13
(4-22)
3
(1-6)
1
(0-1)
2
(1-4)
5
(1-9)
3
(1-5)
3
(1-6)
3
(1-6)
1
(0-2)
4
(1-8)
2
(0-3)
10
(3-17)
57
(16-98)
7
(2-12)
1
(0-2)
4
(1-8)
8
(2-14)
5
(1-8)
6
(2-9)
6
(2-11)
2
(1-4)
7
(2-13)
3
(1-6)
15
(4-26)
NA
11
(3-18)
2
(0-3)
7
(2-12)
NA: for NYC, the model-based adjustment methodology was unable to estimate ozone distributions which would meet the
alternative standard level of 60 ppb.
"0" incidence values denote non-zero estimates that round to zero.
7B-7
-------
Table 7B-3b. Core Short-Term Ozone-Attributable Morbidity - Hospital Admissions
(2009).
Endpoint/Study Are a/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
2009 Simulation Year
HA
HA
HA
respiratory); Detroit (Katsouyanni et al., 2009)
Ihr max, penalized splines
Ihr max, natural splines
170
(-40-380)
160
(-50-370)
170
(-40-380)
160
(-50-370)
170
(-40 - 370)
160
(-49 - 370)
160
(-38 - 350)
160
(-47 - 350)
ISO
(-36-330)
150
(-44-330)
NA
2.8
(-0.65-6.2)
2.7
(-0.80-6.2)
10
(-2.4-23)
9.8
(-2.9-22)
20
(-4.6-44)
19
(-5.6-43)
respiratory); NYC (Silverman and Ito, 2010; Lin et al., 2008)
HA Chronic Lung Disease (Lin)
HA Asthma (Silverman)
HA Asthma, PM2.5 (Silverman)
140
(80- 190)
480
(35-800)
350
(-130-700)
140
(80-190)
470
(34-790)
350
(-120-700)
130
(77 - 190)
450
(32-770)
330
(-120-670)
110
(66- 160)
390
(27-670)
280
(-97 - 580)
NA
0.053
(0.038 - 0.056)
9.4
(0.62-17)
6.8
(-2.2-14)
5.9
(3.4-8.4)
28
(1.8-54)
20
(-6.2-45)
25
(14-35)
110
(7.2-200)
79
(-25-170)
NA
respiratory);LA(Linnetal., 2000)
Ihr max penalized splines
390
(-510-1,200)
500
(-660-1,600)
490
(-650-1,600)
480
(-630-1,500)
460
(-610-1,500)
-120
(150- -390)
11
(-14-35)
23
(-30-76)
37
(-48-120)
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
53
(15-91)
38
(11-65)
53
(15-90)
36
(10-61)
18
(5-30)
64
(18-110)
60
(17- 100)
120
(33 - 200)
190
(54-330)
90
(25- 150)
18
(5-31)
41
(12-70)
52
(15-89)
37
(10-62)
53
(15-91)
36
(10-61)
18
(5-30)
64
(18-110)
63
(18-110)
120
(33 - 200)
190
(55-330)
88
(25-150)
16
(5-27)
41
(11-69)
50
(14-85)
36
(10-61)
53
(15-91)
35
(10-59)
18
(5-30)
66
(19-110)
63
(18-110)
110
(31-190)
190
(52-320)
87
(24-150)
15
(4-26)
39
(11-67)
48
(13-82)
35
(10-59)
52
(15-89)
33
(9-56)
17
(5-29)
65
(18-110)
62
(17- 110)
110
(30-180)
160
(43 - 270)
84
(24- 140)
15
(4-25)
38
(11-64)
46
(13-79)
34
(9-57)
51
(14-87)
31
(9-53)
16
(4-27)
63
(18-110)
60
(17- 100)
100
(28-170)
NA
82
(23- 140)
14
(4-24)
36
(10-61)
2
(0-3)
1
(0-3)
0
(0--1)
0
(0-0)
0
(0-0)
NA
-3
(-1--5)
3
(1-5)
-1
(0--1)
1
(0-2)
2
(1-4)
0
(0-1)
3
(1-4)
1
(0-1)
0
(0-0)
1
(0-2)
0
(0-0)
-3
(-1--4)
0
(0-1)
5
(1-8)
8
(2-14)
2
(0-3)
1
(0-1)
2
(0-3)
4
(1-8)
2
(1-3)
1
(0-1)
3
(1-5)
1
(0-1)
-1
(0--2)
1
(0-2)
10
(3-17)
40
(11-69)
4
(1-7)
1
(0-2)
3
(1-5)
6
(2-11)
3
(1-5)
2
(1-4)
5
(1-9)
2
(1-4)
1
(0-2)
3
(1-6)
16
(4-27)
NA
6
(2-11)
2
(1-3)
5
(1-9)
NA: for NYC, the model-based adjustment methodology was unable to estimate ozone distributions which would meet the
alternative standard level of 60 ppb. For Detroit, already meeting existing standard.
"0" incidence values denote non-zero estimates that round to zero.
7B-8
-------
Table 7B-4a. Core Short-Term Ozone-Attributable Morbidity - Emergency Room Visits
(2007).
Endpoint/Study Area/Descriptor
Ai r Quality Scenario
Absolute Ozone- Attributable Incidence
Base
75ppb
TOppb
65ppb
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 lag 0-7 days
Average day lag 0-2
7,400
(5,300-9,400)
4,400
(2,400-6,300)
6,600
(4,700-8,300)
3,900
(2,100-5,500)
6,300
(4,500-8,000)
3,700
(2,000-5,300)
6,000
(4,300-7,700)
3,600
(1,900-5,100)
5,700
(4,100-7,300)
3,400
(1,800-4,800)
1,100
(790- 1,500)
650
(350-950)
350
(240-460)
200
(110- 290)
650
(450-850)
370
(200-540)
1,000
(710-1,300)
580
(310-850)
ER-visits (respiratory); Atlanta (Tolbert et al., 2007, Darrowet al., 2011)
Tolbert
Tolbert-CO
Tolbert-NO2
Tolbert-PMlO
Tolbert-PMlO, NO2
Darrow
8,000
(5,500-10,000)
7,100
(4,400-9,800)
6,400
(3,400-9,400)
5,000
(1,800-8,200)
4,900
(1,600-8,000)
4,300
(2,600-6,000)
7,000
(4,900-9,200)
6,300
(3,800-8,600)
5,700
(3,000-8,300)
4,400
(1,600-7,300)
4,300
(1,400-7,100)
3,800
(2,300-5,300)
6,700
(4,700-8,800)
6,000
(3,700-8,300)
5,400
(2,900-7,900)
4,300
(1,500-7,000)
4,100
(1,300-6,800)
3,600
(2,200-5,100)
6,500
(4,500-8,500)
5,800
(3,500-8,000)
5,200
(2,800-7,600)
4,100
(1,400-6,700)
4,000
(1,300-6,600)
3,500
(2,100-4,900)
6,200
(4,300-8,000)
5,500
(3,400-7,600)
5,000
(2,600-7,300)
3,900
(1,400-6,400)
3,800
(1,200-6,200)
3,300
(2,000-4,600)
1,000
(680- 1,300)
880
(540- 1,200)
800
(420- 1,200)
620
(220- 1,000)
600
(200- 1,000)
530
(320-740)
310
(220-410)
280
(170-390)
250
(130-370)
200
(68-320)
190
(61-320)
170
(100-230)
580
(400-760)
510
(310-710)
460
(240-680)
360
(130-600)
350
(110-580)
310
(190-430)
920
(630- 1,200)
810
(490-1,100)
730
(380-1,100)
570
(200-940)
550
(180-920)
490
(300-680)
ER-visits (asthma); NYC (Ito et al, 2007)
single pollutant model
PM2.5
NO2
CO
SO2
11,000
(7,700-14,000)
8,800
(4,800-12,000)
7,300
(3,300-11,000)
12,000
(8,500-15,000)
9,100
(5,300-13,000)
11,000
(7,200-14,000)
8,300
(4,500-12,000)
6,800
(3,100-10,000)
11,000
(7,900-14,000)
8,500
(5,000-12,000)
10,000
(6,900- 13,000)
7,900
(4,200- 11,000)
6,500
(2,900-9,800)
11,000
(7,500- 13,000)
8,100
(4,700- 11,000)
8,200
(5,600-11,000)
6,400
(3,400-9,200)
5,300
(2,400-8,000)
8,700
(6,100-11,000)
6,600
(3,800-9,200)
NA
920
(610- 1,200)
710
(370- 1,000)
580
(260-890)
970
(680- 1,300)
730
(420- 1,000)
620
(410-830)
480
(250-700)
390
(170-610)
660
(460-870)
490
(280-710)
2,700
(1,800-3,600)
2,100
(1,100-3,100)
1,700
(760-2,700)
2,900
(2,000-3,800)
2,200
(1,200-3,100)
NA
NA: for NYC, the model-based adjustment methodology was unable to estimate ozone distributions which would meet the
alternative standard level of 60 ppb.
7B-9
-------
Table 7B-4b. Core Short-Term Ozone-Attributable Morbidity - Emergency Room Visits
(2009).
Endpoint/Study Area/Descriptor
Ai r Quality Scenario
Absolute Ozone- Attributable Incidence
Base
75ppb
TOppb
65ppb
eoppb
Change in Ozone- Attributable Incidence
Base-75
75-70
75-65
75-60
2009SimulationYear
ER Visits (repiratory); Atlanta (Strickland etal., 2007)
Distributed Iag0-7days
Average day lag 0-2
6,100
(4,300-7,700)
3,600
(2,000-5,100)
5,900
(4,200-7,600)
3,500
(1,900-5,000)
5,700
(4,100-7,300)
3,400
(1,800-4,800)
5,500
(3,900-7,100)
3,300
(1,800-4,700)
5,400
(3,800-6,900)
3,100
(1,700-4,500)
150
(100-200)
86
(46-130)
270
(190-350)
150
(81-220)
490
(340-640)
280
(150-410)
700
(480-910)
400
(210-580)
ER-visits (respiratory); Atlanta (Tolbertet al., 2007, Darrowet al., 2011)
Tolbert
Tolbert-CO
Tolbert-NO2
Tolbert-PMlO
Tolbert-PMlO, NO2
Darrow
6,600
(4,500-8,500)
5,800
(3,600-8,000)
5,300
(2,800-7,700)
4,100
(1,500-6,800)
4,000
(1,300-6,600)
3,500
(2,200-4,900)
6,400
(4,500-8,400)
5,700
(3,500-7,900)
5,200
(2,700-7,600)
4,100
(1,400-6,600)
3,900
(1,300-6,500)
3,500
(2,100-4,800)
6,200
(4,300-8,100)
5,500
(3,400-7,600)
5,000
(2,600-7,300)
3,900
(1,400-6,400)
3,800
(1,200-6,300)
3,400
(2,000-4,700)
6,000
(4,200-7,900)
5,400
(3,300-7,400)
4,900
(2,600-7,100)
3,800
(1,300-6,200)
3,700
(1,200-6,100)
3,300
(2,000-4,500)
5,900
(4,000-7,600)
5,200
(3,200-7,200)
4,700
(2,500-6,900)
3,700
(1,300-6,000)
3,600
(1,200-5,900)
3,200
(1,900-4,400)
120
(84-160)
110
(66-150)
97
(51-140)
76
(27-130)
73
(24-120)
65
(39-91)
230
(160-300)
200
(120- 290)
180
(97-270)
140
(50-240)
140
(45-230)
120
(74- 170)
440
(300-570)
390
(240-540)
350
(180-520)
270
(95-450)
260
(86-440)
230
(140-320)
620
(430-820)
550
(340-770)
500
(260-740)
390
(140-640)
380
(120-630)
330
(200-470)
ER-visits (asthma); NYC (Ito et al, 2007)
single pollutant model
PM2.5
NO2
CO
SO2
10,000
(7,000-13,000)
8,000
(4,300-11,000)
6,600
(3,000-9,900)
11,000
(7,600-14,000)
8,200
(4,800-11,000)
10,000
(7,000-13,000)
8,100
(4,300-11,000)
6,700
(3,000-10,000)
11,000
(7,700-14,000)
8,300
(4,800- 12,000)
9,900
(6,800- 13,000)
7,800
(4,200- 11,000)
6,400
(2,900-9,700)
10,000
(7,400- 13,000)
8,000
(4,700- 11,000)
8,500
(5,800-11,000)
6,700
(3,600-9,600)
5,500
(2,400-8,300)
9,000
(6,400-12,000)
6,900
(4,000-9,600)
NA
-84
(-52- -120)
-62
(-30 --97)
-49
(-20 --81)
-90
(-59- -130)
-64
(-34 --98)
470
(310-630)
360
(190-530)
290
(130-460)
500
(340-660)
370
(210-530)
2,100
(1,400-2,800)
1,600
(840-2,300)
1,300
(570-2,000)
2,200
(1,500-2,900)
1,700
(940-2,400)
NA
NA: for NYC, the model-based adjustment methodology was unable to estimate ozone distributions which would meet the
alternative standard level of 60 ppb.
7B-10
-------
Table 7B-5a. Core Short-Term Ozone-Attributable Morbidity - Asthma Exacerbations
(2007).
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 (Ihr max)
Chest Tightness (8hr max)
Chest Tightness (Ihr max, PM2.5)a
Chest Tightness (Ihr max, PM2.5)b
Shortness of Breath (Ihr max)
Shortness of Breath (8hr max)
Wheeze (PM2.5)
41,000
(22,000-57,000)
30,000
(10,000-47,000)
42,000
(20,000-59,000)
39,000
(16,000-57,000)
29,000
(3,700-51,000)
35,000
(7,200-58,000)
78,000
29,000 - 120,000)
40,000
(21,000-56,000)
30,000
(9,900 - 47,000)
41,000
(19,000-58,000)
38,000
(15,000-56,000)
29,000
(3,600 - 50,000)
35,000
(7,000 - 57,000)
76,000
28,000-120,000)
40,000
(21,000-55,000)
29,000
(9,800-46,000)
40,000
(19,000-57,000)
37,000
(15,000-55,000)
28,000
(3,500-49,000)
34,000
(6,900-56,000)
75,000
(28,000-110,000)
38,000
(20,000-53,000)
28,000
(9,400-45,000)
39,000
(18,000-56,000)
36,000
(14,000-53,000)
27,000
(3,400-47,000)
33,000
(6,700-55,000)
72,000
(26,000-110,000)
37,000
(19,000-52,000)
28,000
(9,100-43,000)
37,000
(17,000-54,000)
34,000
(14,000-52,000)
26,000
(3,200-45,000)
32,000
(6,400-53,000)
69,000
25,000-110,000)
1,500
(720 - 2,200)
530
(170-870)
1,500
(640 - 2,300)
1,400
(500 - 2,200)
970
(110-1,800)
610
(120-1,100)
2,700
(930 - 4,400)
1,200
(600-1,800)
680
(210-1,100)
1,200
(530-1,900)
1,100
(420-1,800)
800
(93-1,500)
780
(150-1,400)
2,200
(760-3,700)
3,300
(1,600-4,900)
1,900
(580-3,100)
3,300
(1,400-5,100)
3,000
(1,100-4,900)
2,200
(250-4,000)
2,100
(400-3,800)
6,000
(2,100-9,800)
5,100
(2,500-7,500)
3,000
(920 - 4,900)
5,100
(2,200-7,900)
4,700
(1,800-7,500)
3,400
(400 - 6,200)
3,400
(640 - 6,000)
9,300
(3,200 - 15,000)
a previous day;b same day.
Table 7B-5b. Core Short-Term Ozone-Attributable Morbidity - Asthma Exacerbations
(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
2009 Simulation Year
Asthma exacerbation (wheeze); Boston (Gent et al., 2003, 2004)
Chest Tightness (Ihr max)
Chest Tightness (8hr max)
Chest Tightness (Ihr max, PM2.5)a
Chest Tightness (Ihr max, PM2.5)b
Shortness of Breath (Ihr max)
Shortness of Breath (8hr max)
Wheeze (PM2.5)
38,000
(20,000-53,000)
28,000
(9,100-43,000)
38,000
(18,000-55,000)
35,000
(14,000-52,000)
26,000
(3,300-46,000)
32,000
(6,500-53,000)
71,000
26,000 - 110,000)
38,000
(20,000-53,000)
28,000
(9,200-44,000)
38,000
(18,000-55,000)
35,000
(14,000-53,000)
27,000
(3,300-46,000)
32,000
(6,500-54,000)
71,000
(26,000-110,000)
38,000
(20,000-53,000)
28,000
(9,200-44,000)
38,000
(18,000-55,000)
35,000
(14,000-52,000)
26,000
(3,300-46,000)
32,000
(6,500-54,000)
71,000
(26,000-110,000)
37,000
(19,000-52,000)
27,000
(9,100-43,000)
37,000
(17,000-54,000)
34,000
(14,000-51,000)
26,000
(3,200-45,000)
32,000
(6,400-53,000)
69,000
25,000-110,000)
36,000
(19,000-50,000)
27,000
(8,800-42,000)
36,000
(17,000-52,000)
33,000
(13,000-50,000)
25,000
(3,100-44,000)
31,000
(6,200-52,000)
67,000
25,000 - 100,000)
-92
(-44 - -140)
-220
(-66 - -370)
-93
(-39 - -150)
-84
(-30 - -140)
-59
(-6.8- -110)
-250
(-46 - -450)
-170
(-56 - -280)
290
(140-430)
-110
(-32 - -190)
300
(130-460)
270
(100-430)
190
(23 - 360)
-120
(-22 - -230)
530
(190-870)
1,400
(690-2,100)
470
(150-780)
1,400
(610 - 2,200)
1,300
(480-2,100)
930
(110-1,700)
540
(100-960)
2,600
(880 - 4,200)
2,800
(1,400-4,200)
1,300
(410-2,200)
2,900
(1,200-4,400)
2,600
(980 - 4,200)
1,900
(220 - 3,500)
1,500
(280 - 2,600)
5,200
(1,800-8,500)
" previous day;b same day.
7B-11
-------
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
Air Quality Scenario
Absolute Incidence
Base
690
(250-1100)
420
(150-650)
660
(240-1000)
340
(120-530)
340
(120-520)
620
(220-960)
470
(170-740)
1,600
(580 - 2500)
2,400
(860 - 3700)
1,000
(370 - 1600)
350
(130-530)
520
(190-800)
75ppb
590
(210-920)
390
(140-610)
640
(230-1000)
330
(120-510)
330
(120-500)
600
(220-940)
460
(160-720)
1,500
(560-2400)
2,100
(750-3300)
930
(330-1400)
300
(110-470)
480
(170-750)
70ppb
560
(200-870)
380
(140-590)
620
(220-980)
310
(110-490)
320
(110-490)
580
(210-900)
450
(160-710)
1,500
(540 - 2300)
2,000
(710 - 3100)
890
(320 - 1400)
290
(100-450)
460
(170-710)
65ppb
530
(190-840)
360
(130-560)
590
(210-930)
300
(110-470)
300
(110-470)
560
(200-880)
450
(160-700)
1,400
(510-2200)
1,600
(570-2600)
850
(310-1300)
280
(100-440)
430
(160-680)
eoppb
500
(180-790)
340
(120-540)
570
(200-900)
270
(97 - 430)
290
(100-450)
540
(190-840)
440
(160-690)
1,300
(490-2100)
NA
820
(290-1300)
260
(94-410)
410
(150-640)
Change in Incidence
base -75
120
(42-200)
41
(14-67)
24
(8-39)
13
(4-21)
16
(5-26)
24
(8-40)
18
(6-30)
57
(19-95)
320
(110-530)
120
(42-200)
56
(19-92)
48
(16-80)
75-70
35
(12-59)
17
(6-29)
20
(7-33)
16
(6-27)
13
(4-21)
28
(10-46)
8.0
(3-13)
82
(28-140)
140
(47 - 230)
42
(14-69)
14
(5-22)
27
(9-45)
75-65
64
(22-110)
35
(12-57)
53
(18-88)
35
(12-58)
26
(9-44)
50
(17-82)
16
(5-26)
160
(54-260)
550
(190-900)
87
(30-140)
26
(9-43)
56
(19-92)
75-60
100
(34-160)
57
(19-93)
82
(28-140)
64
(22-100)
43
(15-71)
78
(27-130)
27
(9-44)
240
(83 - 400)
NA
130
(44-210)
44
(15-73)
84
(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
Sacrame nto, CA
St. Louis, MO
Air Quality Scenario
Percent of Baseline Incidence
Base
21.7
20.3
17.7
18.2
21.6
19.0
16.9
21.0
19.0
20.4
20.5
20.3
TSppb
18.6
18.8
17.2
17.7
20.8
18.4
16.3
20.4
16.9
18.4
17.8
18.8
TOppb
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
17.2
15.9
18.8
13.1
17.0
16.5
17.0
eoppb
16.0
16.5
15.3
14.8
18.6
16.4
15.5
17.8
NA
16.3
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
7
7
9
6
7
3
8
23
8
7
10
75-60
14
12
11
16
11
11
5
13
NA
12
12
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
Sacrame nto, CA
St. Louis, MO
Air Quality Scenario
Ozone-Attributable Deaths per 100,000
Base
24
27
24
26
24
24
16
23
21
29
29
32
TSppb
21
25
24
25
23
23
15
22
19
27
25
29
TOppb
20
24
23
24
23
22
15
21
18
26
24
28
65ppb
19
23
22
23
22
21
15
20
15
24
23
26
eoppb
18
22
21
21
21
20
15
19
NA
23
22
25
Change in Ozone-Attributable Deaths per 100,000
Base-75
4.4
2.6
0.88
1.00
1.1
0.91
0.61
0.81
2.9
3.5
4.7
2.9
75-70
1.3
1.1
0.74
1.2
0.91
1.1
0.27
1.2
1.3
1.2
1.1
1.6
75-65
2.3
2.2
2.0
2.7
1.9
1.9
0.52
2.2
4.9
2.5
2.2
3.4
75-60
3.5
3.6
3.1
4.9
3.1
3.0
0.89
3.4
NA
3.7
3.7
5.1
NA: for NYC, the model-based adjustment methodology was unable to estimate ozone distributions which would meet the
alternative standard level of 60 ppb.
7B-12
-------
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 Incidence
Base
570
(210-890)
380
(140-590)
580
(210-910)
310
(110-490)
320
(120-490)
540
(190-850)
490
(170-760)
1,600
(590 - 2500)
2,100
(750 - 3300)
880
(320 - 1400)
360
(130-550)
450
(160-700)
75ppb
550
(200-860)
360
(130-560)
580
(210-920)
300
(110-470)
320
(120-490)
540
(190-850)
490
(180-770)
1,600
(570-2400)
2,000
(730-3200)
850
(310-1300)
310
(110-480)
440
(160-690)
TOppb
520
(190-820)
350
(120-540)
580
(210-910)
290
(100-460)
310
(110-490)
550
(200-850)
480
(170-750)
1,500
(550 - 2300)
1,900
(690 - 3000)
820
(300 - 1300)
300
(110-460)
430
(150-670)
65ppb
500
(180-790)
340
(120-530)
560
(200-890)
280
(98-430)
300
(110-470)
530
(190-830)
470
(170-740)
1,400
(520-2200)
1,700
(590-2700)
790
(280-1200)
280
(100-450)
410
(150-650)
eoppb
480
(170-760)
320
(120-510)
540
(190-860)
260
(92 - 410)
280
(100-440)
510
(180-800)
460
(160-720)
1,400
(500 - 2100)
NA
770
(270-1200)
270
(96 - 420)
390
(140-610)
Change in Incidence
base-75
26
(9-43)
25
(8-41)
-1.1
(0--2)
9.4
(3 - 16)
0.49
(0-1)
NA
-3.9
(-1--7)
63
(21-100)
61
(21-100)
40
(13 - 66)
61
(21-100)
5.6
(2-9)
75-70
32
(11-53)
12
(4-20)
3.7
(1-6)
14
(5-24)
5.8
(2-10)
-6.7
(-2 --11)
11
(4-18)
77
(26-130)
120
(40 - 200)
31
(11-52)
14
(5-24)
19
(6-31)
75-65
59
(20-98)
27
(9-44)
23
(8-38)
32
(11-53)
18
(6-30)
14
(5-23)
24
(8-40)
160
(54 - 260)
420
(140-690)
66
(23 - 110)
28
(9-46)
41
(14-67)
75-60
82
(28-140)
41
(14-68)
47
(16-77)
50
(17-82)
45
(16-75)
38
(13-64)
40
(14-66)
250
(84-400)
NA
97
(33 - 160)
44
(15-73)
66
(23-110)
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
Base
17.6
18.4
15.9
17.2
20.1
17.0
16.8
21.4
17.1
17.9
20.9
17.9
75ppb
17.0
17.4
16.0
16.8
20.0
17.0
16.9
20.7
16.7
17.2
18.0
17.7
70ppb
16.2
16.9
15.9
16.1
19.8
17.2
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
16.3
19.1
13.8
16.1
16.7
16.4
60ppb
14.8
15.7
14.9
14.5
17.7
16.0
15.8
18.1
NA
15.5
15.8
15.5
Change in O3-Attributable Risk
Base-75
4
5
-0.2
2
0.1
NA
-1
3
2
4
14
1
75-70
5
3
1
4
1
-1
2
4
5
3
4
3
75-65
9
6
3
9
5
2
4
8
18
6
7
8
75-60
13
10
7
14
12
6
7
13
NA
10
12
12
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
19
23
21
24
22
21
15
22
18
25
29
27
75ppb
19
22
21
23
22
21
15
22
18
24
25
27
70ppb
18
22
21
22
22
21
15
21
17
23
24
26
65ppb
17
21
21
21
21
20
15
20
15
22
23
25
60ppb
16
20
20
20
19
19
14
19
NA
22
22
23
Change in Ozone-Attributable Deaths per 100,000
Base-75
0.88
1.5
-0.041
0.73
0.034
NA
-0.12
0.87
0.54
1.1
5.0
0.34
75-70
1.1
0.75
0.13
1.1
0.40
-0.25
0.35
1.1
1.0
0.88
1.2
1.1
75-65
2.0
1.7
0.82
2.5
1.3
0.52
0.76
2.2
3.7
1.9
2.3
2.4
75-60
2.8
2.6
1.7
3.8
3.1
1.5
1.3
3.4
NA
2.7
3.6
3.9
NA: for NYC, the model-based adjustment methodology was unable to estimate ozone distributions which would meet the
alternative standard level of 60 ppb. For Detroit, already meeting existing standard.
"0" counts denote non-zero estimates that round to zero.
7B-13
-------
APPENDIX 7C
Detailed Summary Tables and Figures of Sensitivity Analysis
Results
List of Tables
Table 7C-1. Sensitivity Analysis - ST Mortality: Smaller Smith et al., 2009-based study area
(2009) (incidence, percent of baseline mortality, incidence per 100,000 - compare
with Core Results in Appendix B, Table 7B-2) 7C-1
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) 7C-3
Table 7C-3. Sensitivity Analysis - ST Mortality: Regional Bayes Adjustment (2009)
(incidence, percent of baseline mortality, incidence per 100,000 - compare with
Core Results in Table 7B-2) 7C-4
Table 7C-4. Sensitivity Analysis - ST Mortality: Copollutant model (PM10) (2009)
(incidence, percent of baseline mortality, incidence per 100,000 - compare with
Core Results in Table 7B-2) 7C-5
Table 7C-5. Sensitivity Analysis - ST Mortality: 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) 7C-6
Table 7C-6. Sensitivity Analysis - LT Mortality: Alternate risk model (regional effect
estimates) (2009) (incidence, percent of baseline mortality, incidence per 100,000
- compare with Core Results in Table 7B-7) 7C-7
Table 7C-7. Sensitivity Analysis - LT Mortality: 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) 7C-8
Table 7C-8. Sensitivity Analysis - LT Mortality: Threshold models (ozone-only effect
estimate) (2009 Baseline) (ozone-attributable deaths, percent of baseline
mortality, incidence per 100,000 - compare with Core Results in Table 7B-7)...
7C-9
Table 7C-9. Sensitivity Analysis - LT Mortality: Threshold models (ozone-only effect
estimate) (2009 Current Standard 75ppb) (ozone-attributable deaths, percent of
baseline mortality, incidence per 100,000 - compare with Core Results in Table
7B-7) 7C-10
Table 7C-10. Sensitivity Analysis - LT Mortality: Threshold models (ozone-only effect
estimate) (2009 Current Standard 70ppb) (ozone-attributable deaths, percent of
baseline mortality, incidence per 100,000 - compare with Core Results in Table
7B-7) 7C-11
Table 7C-11. Sensitivity Analysis - LT Mortality: Threshold models (ozone-only effect
estimate) (2009 Current Standard 65ppb) (ozone-attributable deaths, percent of
7C-i
-------
baseline mortality, incidence per 100,000 - compare with Core Results in Table
7B-7) 7C-12
Table 7C-12. Sensitivity Analysis - LT Mortality: Threshold models (ozone-only effect
estimate) (2009 Current Standard 60ppb) (ozone-attributable deaths, percent of
baseline mortality, incidence per 100,000 - compare with Core Results in Table
7B-7) 7C-13
List of Figures
Figure 7C-1. Sensitivity Analysis - ST Mortality: 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) 7C-2
7C-ii
-------
Table 7C-1. Sensitivity Analysis - ST Mortality: Smaller Smith et al., 2009-based study
area (2009) (incidence, percent of baseline mortality, incidence per 100,000 - compare with
Core Results in Appendix B, 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
64
(-89-210)
55
(-30-140)
24
(-34-82)
170
(-16-350)
41
(-130-210)
220
(11-420)
350
(65-620)
520
(-220-1200)
1200
(730-1700)
210
(46-370)
110
(-120-340)
36
(-9 - 80)
75ppb
64
(-90-210)
58
(-32 - 150)
25
(-35-84)
180
(-16-360)
42
(-140-210)
220
(11-420)
380
(72 - 690)
600
(-250 - 1400)
1400
(830 - 1900)
220
(49 - 390)
110
(-120-340)
37
(-9-81)
TOppb
64
(-89-210)
58
(-32-140)
26
(-37-87)
170
(-16-360)
42
(-140-220)
230
(12-440)
380
(72-690)
580
(-240-1400)
1400
(830-1900)
220
(49-390)
110
(-120-340)
39
(-10-86)
65ppb
62
(-86-210)
57
(-31-140)
26
(-37-87)
170
(-15-340)
42
(-140-210)
220
(11-430)
380
(72 - 690)
560
(-230-1300)
1200
(750 - 1700)
220
(49 - 390)
110
(-120-330)
39
(-10-87)
60ppb
61
(-84-200)
56
(-31-140)
26
(-36-86)
160
(-15-330)
40
(-130-200)
220
(11-420)
380
(71-680)
520
(-220-1200)
NA
220
(48-380)
110
(-110-320)
39
(-10-86)
Change in Ozone-Attributable Incidence
Base-75
-1
(1--2)
-3
(2 --8)
-1
(1--2)
-8
(1--17)
0
(2 --3)
NA
-36
(-7 --66)
-83
(34 - -200)
-170
(-100- -240)
-15
(-3 --27)
1
(-1-2)
-1
(0--2)
75-70
1
(-1-3)
0
(0-1)
-1
(2 - -4)
4
(0-8)
-1
(2 --3)
-11
(-1--22)
-2
(0--3)
21
(-9-50)
5
(3-6)
1
(0-1)
2
(-2-6)
-2
(1--5)
75-65
2
(-3-8)
1
(-1-3)
-1
(1--3)
10
(-1-21)
0
(0-0)
-7
(0--14)
-1
(0--2)
44
(-18-110)
140
(84 - 200)
3
(1-5)
4
(-4-11)
-3
(1--6)
75-60
4
(-6-13)
2
(-1-6)
-1
(1--2)
18
(-2-38)
2
(-7-11)
0
(0-0)
3
(1-6)
81
(-33-190)
NA
5
(1-9)
7
(-7-20)
-2
(1--5)
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
1.0
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
1.8
1.1
2.3
0.8
2.6
1.9
1.1
4.2
2.8
1.2
2.2
TOppb
1.0
1.7
1.1
2.3
0.8
2.8
2.0
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
60ppb
1.0
1.7
1.1
2.1
0.8
2.6
1.9
0.9
NA
2.8
1.2
2.3
Change in Oj-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
0.3
0.2
2
-6
75-65
4
2
-4
5
-0.2
-3
-0.3
7
10
1
3
-7
75-60
6
4
-2
10
5
0.03
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
Air Quality Scenario
Ozone-Attributable Deaths per 100,000 Change in Ozone-Attributable Deaths per 100,000
Base
4.0
8.8
3.4
13
2.6
12
8.6
5.3
13
14
8.2
11
75ppb
4.1
9.3
3.5
14
2.6
12
9.5
6.1
15
15
8.1
12
TOppb
4.0
9.3
3.6
13
2.7
12
9.6
5.9
15
15
8.0
12
65ppb
3.9
9.1
3.6
13
2.6
12
9.5
5.7
14
15
7.8
12
60ppb
3.8
9.0
3.6
12
2.5
12
9.4
5.3
NA
14
7.6
12
Base-75
-0.041
-0.52
-0.084
-0.63
-0.030
NA
-0.91
-0.85
-1.9
-1.0
0.060
-0.27
75-70
0.050
0.073
-0.16
0.28
-0.036
-0.62
-0.047
0.21
0.050
0.039
0.13
-0.66
75-65
0.15
0.21
-0.14
0.77
-0.0040
-0.38
-0.022
0.45
1.5
0.18
0.26
-0.82
75-60
0.25
0.38
-0.087
1.4
0.13
0.011
0.081
0.83
NA
0.34
0.46
-0.69
NA: for NYC, the model-based adjustment methodology was unable to estimate ozone distributions which would meet the
alternative standard level of 60 ppb.
"0" incidence values denote non-zero estimates that round to zero.
7C-1
-------
Figure 7C-1. Sensitivity Analysis - ST Mortality: 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)
ilyShr Max Ozone Level (ppb)
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
0
0
0
0
0
0
0
0
0
0
0
510
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
-1
0
0
0
0
0
0
0
0
0
0
0
-1
-1
0
0
0
0
0
0
0
0
0
-2
-1
0
-1
0
0
30-35
0
0
0
0
0
-2
-2
0
-1
0
0
35-40
0
0
0
1
0
-2
-1
0
0
0
0
40-45
0
0
0
1
0
-2
0
2
1
1
0
45-50
1
0
0
2
0
0
50-55
0
0
0
1
0
0
2
9
11
2
1
0
55-60
1
0
0
1
0
1
1
3
9
1
0
0
60-65
0
0
0
0
0
1
1
0
3
1
0
0
65-70
0
0
0
0
0
0
0
0
0
0
0
0
70-75
0
0
0
0
0
1
0
0
0
0
0
0
>75
0
0
0
0
0
0
0
0
0
0
0
0
Total
2
1
0
5
0
-8
0
19
41
4
2
1
Change in risk
Inc.
0
0
0
0
0
-11
-5
0
-19
-2
0
0
Dec.
2
0
0
6
0
3
5
19
59
6
3
0
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
-1
-1
0
-1
0
0
0
20-25
0
0
0
0
0
-1
-2
0
-2
0
0
0
25-30
0
0
0
0
0
-2
-3
0
-8
-1
-1
0
30-35
0
0
0
0
0
-2
-3
0
8
-1
0
0
35-40
0
0
0
2
0
-2
0
0
26
0
1
0
40-45
1
0
0
2
0
-1
1
4
53
2
1
0
45-50
1
1
0
4
0
1
2
10
59
2
1
1
50-55
1
1
0
3
0
1
3
19
40
4
1
1
55-60
60-65
0
0
0
1
0
2
2
0
10
2
0
0
65-70
0
0
0
0
0
0
0
0
0
0
0
0
70-75
0
0
0
0
0
1
0
0
0
0
0
0
>75
0
0
0
0
0
0
0
0
0
0
0
0
Total
5
Change in risk
Inc.
0
0
0
-1
0
-9
-10
0
-21
-3
-1
0
Dec.
4
3
0
14
1
9
10
39
236
12
5
3
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
0
10-15
0
0
0
0
0
0
0
0
0
0
0
15-20
0
0
0
0
20-25
0
0
0
0
0 | 0
-2
-1
0
±
0
0
0
-1
0
0
25-30
0
0
0
0
0
-3
-4
0
-1
-1
0
30-35
0
0
0
0
0
-2
-4
0
-1
0
0
35-40
1
0
0
3
0
-1
0
1
0
1
0
40-45
1
1
0
4
0
1
3
15
3
2
1
45-50
2
2
0
6
0
4
50-55
1
1
0
5
1
2
4 1 6
20 | _'9
NA
4
2
1
5
2
1
55-60
1
1
0
3
2
3
3
10
3
2
1
60-65
1
0
0
2
0
0
65-70
0
0
0
1
0
0
1
0
0
0
0
70-75
0
0
0
0
0
2
1
0
0
0
0
>75
0
0
0
0
0
1
0
0
0
0
0
Total
6
4
1
22
4
6
8
75
14
6
4
Change in risk
Inc.
0
0
0
-1
0
-10
-14
0
-4
-2
0
Dec.
7
5
0
24
4
17
22
76
18
9
4
NA: for NYC, the model-based adjustment methodology was unable to estimate ozone distributions which would meet the
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
56
(-180-290)
460
(23-880)
550
(100-990)
670
(-280-1600)
2900
(1800-4100)
820
(180-1400)
170
(-180-500)
TSppb
57
(-190-290)
460
(23-880)
580
(110-1000)
690
(-290-1700)
2900
(1800-4100)
810
(180-1400)
160
(-170-480)
TOppb
57
(-190-290)
460
(24-890)
580
(110-1000)
680
(-280-1600)
2900
(1800-4100)
790
(180-1400)
160
(-170-470)
65ppb
56
(-180-290)
450
(23-870)
580
(110-1000)
660
(-270-1600)
2700
(1600-3700)
780
(170-1400)
150
(-160-460)
eoppb
52
(-170-270)
430
(22-830)
560
(110-1000)
640
(-270- 1500)
NA
750
(170-1300)
150
(-160-450)
Change in Ozone-Attributable Incidence
Base -75
-1
(3 --5)
NA
-31
(-6 --57)
-19
(8 --46)
-3
(-2 --4)
9
(2-16)
7
(-7-20)
75-70
0
(0--1)
-9
(0--18)
-2
(0--3)
15
(-6-36)
24
(14-33)
16
(4-28)
3
(-3-10)
75-65
1
(-3-6)
4
(0-7)
2
(0-3)
32
(-13-77)
290
(170-400)
35
(8-61)
6
(-6-18)
75-60
5
(-16-25)
24
(1-46)
18
(3-32)
48
(-20-120)
NA
58
(13-100)
10
(-10-30)
Study Area
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
Study Area
Denver, CO
Detroit, Ml
Houston, TX
Los Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
Air Quality Scenario
Percent of Baseline Incidence Attributable to Ozone
Base
0.8
2.7
1.8
0.9
3.8
2.9
1.2
75ppb
0.8
2.7
1.9
0.9
3.8
2.9
1.2
70ppb
0.8
2.8
1.9
0.9
3.8
2.9
1.2
65ppb
0.8
2.7
1.9
0.9
3.5
2.8
1.1
eoppb
0.7
2.6
1.8
0.9
NA
2.7
1.1
Change in O3-Attributable Risk
Base -75
-2
NA
-6
-3
-0.1
1
4
75-70
-0.2
-2
-0.3
2
1
2
2
75-65
2
1
0.2
5
9
4
4
75-60
8
5
3
7
NA
7
6
Air Quality Scenario
Ozone-Attributable Deaths per 100,000 Change in Ozone-Attributable Deaths per 100,000
Base
2.2
11
9.4
5.3
16
14
7.8
TSppb
2.3
11
10.0
5.4
16
14
7.5
TOppb
2.3
11
10.0
5.3
16
13
7.4
65ppb
2.2
10
9.9
5.2
14
13
7.2
eoppb
2.1
10
9.7
5.0
NA
13
7.1
Base -75
-0.039
NA
-0.54
-0.15
-0.014
0.15
0.30
75-70
-0.0044
-0.21
-0.026
0.12
0.13
0.27
0.15
75-65
0.042
0.086
0.028
0.25
1.5
0.58
0.28
75-60
0.19
0.54
0.30
0.38
NA
0.99
0.46
NA: for NYC, the model-based adjustment methodology was unable to estimate ozone distributions which would meet the
alternative standard level of 60 ppb.
"0" incidence values denote non-zero estimates that round to zero.
7C-2
-------
Table 7C-3. Sensitivity Analysis - ST Mortality: Regional Bayes Adjustment (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
220
(-170-610)
460
(190-730)
570
(190-930)
290
(71-510)
10
(-230-240)
510
(140-860)
470
(72 - 850)
610
(-300-1500)
3300
(2200-4300)
1200
(640-1700)
59
(-300-400)
390
(74-690)
75ppb
220
(-170-590)
460
(190-720)
570
(190-940)
300
(72-520)
10
(-230-240)
510
(140-860)
500
(78-920)
700
(-350-1700)
3400
(2300-4400)
1200
(640-1700)
58
(-290-390)
390
(73 - 690)
70ppb
210
(-160-570)
450
(190-710)
570
(190-940)
290
(70-500)
10
(-230-240)
520
(150-890)
500
(79 - 930)
680
(-330-1700)
3300
(2200-4300)
1200
(630 - 1700)
57
(-280-390)
380
(72 - 680)
65ppb
200
(-160-560)
440
(180-690)
560
(190-920)
280
(67 - 480)
10
(-220-230)
510
(150-870)
500
(78-920)
650
(-320-1600)
2800
(1900-3700)
1100
(620-1600)
56
(-280-380)
370
(69 - 660)
eoppb
200
(-150-540)
430
(180-670)
550
(180-900)
260
(63 - 460)
9
(-210-220)
490
(140-840)
490
(77 - 910)
610
(-300-1500)
NA
1100
(600-1600)
54
(-270-370)
350
(66-630)
Change in Ozone-Attributable Incidence
Base- 75
4
(-3-11)
7
(3-10)
-4
(-1--7)
-4
(-1--6)
0
(1--1)
NA
-40
(-6 --73)
-90
(44- -220)
-98
(-67 - -130)
-6
(-3 --9)
2
(-8-11)
1
(0-3)
75-70
8
(-6-21)
9
(4-13)
-2
(-1--3)
9
(2-15)
0
(-1-1)
-19
(-5 --32)
-1
(0--1)
23
(-11-56)
110
(73 - 140)
20
(11-29)
1
(-5-7)
8
(2-15)
75-65
14
(-11-40)
20
(8-32)
9
(3 - 15)
21
(5-38)
0
(-5 - 6)
-5
(-2 --9)
3
(0-5)
49
(-24-120)
550
(380-730)
47
(25-68)
2
(-10-13)
21
(4-38)
75-60
21
(-16-57)
32
(13-51)
25
(8-41)
37
(9-65)
1
(-19-21)
13
(4-23)
10
(2-19)
90
(-44-220)
NA
73
(40 - 110)
3
(-16-23)
37
(7 - 68)
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
1.1
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 O3-Attributable Risk
Base-75
2
1
-1
-1
-0.4
NA
-8
-15
-3
-1
2
0.4
75-70
3
2
-0.3
3
0.2
-4
-0.1
3
3
2
2
2
75-65
7
4
1
7
2
-1
0.5
7
16
4
3
5
75-60
9
7
4
12
7
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
Air Quality Scenar o
Ozone-Attributable Deaths per 100,000 Change in Ozone-Attributable Deaths per 100,000
Base
4.2
17
13
14
0.40
12
8.0
4.8
17
20
2.8
14
75ppb
4.2
17
13
14
0.40
12
8.7
5.5
18
20
2.7
14
70ppb
4.0
17
13
14
0.40
12
8.7
5.3
17
19
2.7
13
65ppb
3.9
16
12
13
0.39
12
8.6
5.1
15
19
2.6
13
eoppb
3.8
16
12
13
0.36
11
8.5
4.8
NA
19
2.6
12
Base-75
0.077
0.24
-0.088
-0.17
-0.0017
NA
-0.68
-0.70
-0.52
-0.10
0.076
0.052
75-70
0.15
0.32
-0.043
0.42
0.0014
-0.43
-0.0085
0.18
0.57
0.34
0.046
0.30
75-65
0.28
0.74
0.20
1.0
0.0095
-0.12
0.045
0.38
3.0
0.79
0.091
0.74
75-60
0.40
1.2
0.55
1.8
0.034
0.31
0.18
0.70
NA
1.2
0.16
1.3
NA: for NYC, the model-based adjustment methodology was unable to estimate ozone distributions which would meet the
alternative standard level of 60 ppb.
"0" incidence values denote non-zero estimates that round to zero.
7C-4
-------
Table 7C-4. Sensitivity Analysis - ST Mortality: Copollutant model (PM10) (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
100
(-830 - 980)
240
(-290-740)
100
(-650 - 820)
200
(-170-560)
-13
(-370 - 330)
200
(-370 - 760)
690
(-88 - 1400)
160
(-2000-2200)
1300
(-970-3500)
630
(-560- 1800)
150
(-440 - 720)
210
(-460 - 840)
75ppb
99
(-810-970)
230
(-290-730)
100
(-650-820)
200
(-170-570)
-13
(-370-330)
200
(-370-760)
750
(-95 - 1600)
190
-2300-2600)
1300
-1000-3600)
630
(-560 - 1800)
150
(-430-710)
210
(-460-840)
70ppb
95
(-780-940)
230
(-280-720)
100
(-650-830)
200
(-170-550)
-13
(-370-330)
210
(-380-790)
750
(-95 - 1600)
180
(-2200-2500)
1300
(-970-3500)
620
(-550-1700)
150
(-420-690)
200
(-450-830)
65ppb
92
(-760-910)
220
(-270-700)
100
(-640-810)
190
(-160-530)
-13
(-360-320)
210
(-380-770)
750
(-95 - 1600)
170
(-2100-2400)
1100
(-840-3000)
610
(-540-1700)
150
(-420-680)
200
(-440-800)
60ppb
89
(-730 - 880)
220
(-270-680)
100
(-620-790)
180
(-150-500)
-12
(-340 - 300)
200
(-360 - 740)
730
(-93 - 1500)
160
(-2000-2200)
NA
590
(-520-1700)
140
(-410 - 670)
190
(-420 - 760)
Change in Ozone-Attributable Incidence
Base-75
2
(-15 - 18)
3
(-4-10)
-1
(4 --6)
-3
(2 --7)
0
(2 --2)
NA
-59
(7- -130)
-24
(280- -330)
-38
(28- -110)
-3
(3 - -9)
4
(-12-20)
1
(-2-3)
75-70
4
(-28-35)
4
(-5-14)
0
(2 --3)
6
(-5-17)
0
(-1-1)
-7
(13 --28)
-1
(0--2)
6
(-72-83)
42
(-31-110)
11
(-9-31)
3
(-7-12)
4
(-10-18)
75-65
7
(-53-65)
10
(-12-32)
2
(-10-13)
15
(-12-41)
0
(-9-8)
-2
(4 --8)
4
(-1-8)
13
(-150-180)
220
(-160-600)
25
(-22-71)
5
(-14-24)
11
(-24-46)
75-60
9
(-76-94)
16
(-20-52)
5
(-28-36)
25
(-21-71)
-1
(-31-28)
5
(-10-20)
16
(-2-33)
24
(-280-330)
NA
39
(-34-110)
9
(-24-41)
20
(-43 - 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
Air Quality Scenario
Percent of Baseline Incidence Attributable to Ozone
Base
0.5
2.0
0.6
1.9
-0.2
1.2
2.2
0.2
1.7
2.2
1.1
1.5
75ppb
0.5
2.0
0.6
1.9
-0.2
1.2
2.4
0.2
1.7
2.3
1.1
1.5
TOppb
0.4
2.0
0.6
1.8
-0.2
1.2
2.4
0.2
1.7
2.2
1.1
1.5
65ppb
0.4
1.9
0.6
1.8
-0.2
1.2
2.4
0.2
1.5
2.2
1.1
1.4
eoppb
0.4
1.9
0.6
1.7
-0.2
1.2
2.4
0.2
NA
2.1
1.0
1.3
Change inO3-Attributable Risk
Base-75
2
1
-1
-1
-0.5
NA
-8
-14
-3
-1
2
0.3
75-70
3
2
-0.4
3
1
-4
-0.1
3
3
2
2
2
75-65
6
4
1
7
3
-1
0.5
7
16
4
3
5
75-60
9
7
4
12
10
3
2
12
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
Air Quality Scenario
Ozone-Attributable Deaths per 100,000 Change in Ozone-Attributable Deaths per 100,000
Base
1.9
8.8
2.3
9.7
-0.52
4.7
12
1.3
6.9
11
7.3
7.4
75ppb
1.9
8.7
2.3
9.8
-0.52
4.7
13
1.5
7.1
11
7.1
7.4
TOppb
1.8
8.5
2.3
9.5
-0.52
4.9
13
1.4
6.9
10
7.0
7.2
65ppb
1.8
8.3
2.3
9.1
-0.51
4.8
13
1.4
6.0
10
6.8
7.0
eoppb
1.7
8.1
2.2
8.6
-0.48
4.6
13
1.3
NA
10.0
6.7
6.7
Base-75
0.035
0.12
-0.016
-0.12
0.0023
NA
-1.0
-0.19
-0.20
-0.053
0.20
0.028
75-70
0.066
0.16
-0.0076
0.28
-0.0019
-0.17
-0.013
0.047
0.22
0.18
0.12
0.16
75-65
0.13
0.37
0.036
0.70
-0.012
-0.049
0.068
0.10
1.2
0.42
0.24
0.40
75-60
0.18
0.61
0.100
1.2
-0.044
0.12
0.27
0.19
NA
0.65
0.41
0.71
NA: for NYC, the model-based adjustment methodology was unable to estimate ozone distributions which would meet the
alternative standard level of 60 ppb.
"0" incidence values denote non-zero estimates that round to zero.
7C-5
-------
Table 7C-5. Sensitivity Analysis - ST Mortality: 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
jos Angeles, CA
New York, NY
Philadelphia, PA
Sacramento, CA
St. Louis, MO
Air Quality Scenario
Absolute Ozone-Attributable Incidence
Base
120
(-110-330)
130
(-26-290)
220
(12-420)
120
(-20-260)
62
(-81 - 200)
370
(130-600)
52
(-110-220)
270
(-150-690)
1500
(900 - 2200)
360
(5-700)
110
(-37-250)
160
(-32 - 340)
75ppb
110
(-100-320)
120
(-24-260)
220
(12-420)
110
(-19-240)
62
(-80-200)
370
(130-600)
56
(-120-230)
270
(-140-670)
1500
(850-2100)
340
(4 - 660)
93
(-32-210)
150
(-31-330)
70ppb
100
(-94-290)
120
(-23 - 250)
210
(12-410)
110
(-18-230)
60
(-78-190)
380
(140-610)
56
(-120-230)
260
(-140-640)
1400
(790-1900)
320
(4 - 640)
89
(-31-210)
150
(-30-320)
65ppb
96
(-89-280)
110
(-22-240)
210
(12-400)
100
(-17-220)
57
(-75 - 180)
370
(130-600)
55
(-120-230)
240
(-130-600)
1000
(610 - 1500)
310
(4-610)
86
(-30-200)
140
(-28-300)
eoppb
91
(-84-260)
110
(-21-230)
200
(11-390)
95
(-16-200)
51
(-67-170)
350
(130-570)
54
(-120-220)
230
(-120-570)
NA
300
(4 - 590)
82
(-28-190)
130
(-26-280)
Change in Ozone-Attributable Incidence
Base-75
6
(-6-18)
13
(-3 - 29)
1
(0-2)
5
(-1-11)
0
(0-1)
NA
-4
(8 --15)
6
(-3-16)
96
(56-140)
24
(0-47)
15
(-5 - 36)
2
(0-5)
75-70
8
(-8-24)
4
(-1-10)
6
(0-11)
5
(-1-11)
2
(-2-6)
-6
(-2 --10)
0
(0-1)
13
(-7-32)
110
(64 - 160)
12
(0-24)
4
(-1-9)
8
(-2-17)
75-65
14
(-13-41)
10
(-2-21)
11
(1-22)
12
(-2-27)
4
(-6-14)
5
(2-8)
1
(-2-4)
27
(-14-69)
420
(240-600)
26
(0-51)
7
(-2-17)
15
(-3-34)
75-60
19
(-18-56)
15
(-3-32)
19
(1-37)
20
(-3-44)
10
(-13-33)
21
(8-35)
3
(-6-10)
40
(-21-100)
NA
38
(1-76)
12
(-4-27)
24
(-5-53)
Study Area
Atlanta, GA
Baltimore, MD
Boston, MA
Cleveland, OH
Denver, CO
Detroit, Ml
Houston, TX
jos 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
2.6
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
eoppb
1.1
2.0
2.3
2.0
1.5
3.9
0.6
1.2
NA
2.4
2.2
2.0
Change inO3-Attributable Risk
Base-75
5
10
0.3
4
1
NA
-7
2
6
6
14
1
75-70
7
4
2
4
3
-2
0.3
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
jos 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
2.2
4.9
4.9
5.7
2.5
8.6
0.90
2.2
8.2
6.1
5.1
5.5
75ppb
2.1
4.4
4.8
5.5
2.5
8.6
0.96
2.1
7.8
5.7
4.4
5.5
70ppb
2.0
4.3
4.7
5.3
2.4
8.8
0.96
2.0
7.2
5.5
4.2
5.2
65ppb
1.8
4.1
4.6
4.9
2.3
8.5
0.95
1.9
5.6
5.2
4.0
4.9
eoppb
1.7
3.9
4.4
4.6
2.1
8.2
0.92
1.8
NA
5.0
3.8
4.6
Base-75
0.12
0.49
0.017
0.25
0.014
NA
-0.062
0.050
0.51
0.40
0.72
0.075
75-70
0.16
0.16
0.13
0.25
0.077
-0.14
0.0029
0.10
0.59
0.20
0.17
0.28
75-65
0.27
0.35
0.25
0.59
0.17
0.12
0.016
0.21
2.2
0.43
0.34
0.55
75-60
0.37
0.55
0.42
0.97
0.41
0.50
0.043
0.31
NA
0.64
0.55
0.86
NA: for NYC, the model-based adjustment methodology was unable to estimate ozone distributions which would meet the
alternative standard level of 60 ppb.
"0" incidence values denote non-zero estimates that round to zero.
7C-6
-------
Table 7C-6. Sensitivity Analysis - LT Mortality: Alternate risk model (regional effect
estimates) (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
1,400
(720 - 1900)
-110
(-1200-590)
(-1700-920)
0
(-990-630)
450
(-26-780)
0
(-1700-1100)
1,200
(610 - 1600)
450
(-2400-2500)
-600
(-6200-3300)
-260
(-2700-1400)
500
(-29-870)
0
(-1400-910)
75ppb
1,300
(690-1800)
-100
(-1100 - 560)
-170
(-1700 - 920)
0
(-950-620)
450
(-26-780)
0
(-1700-1100)
1,200
(620-1600)
440
(-2300-2400)
-580
(-6000 - 3200)
-240
(-2500-1300)
440
(-25-770)
0
(-1400 - 910)
70ppb
1,300
(660 - 1800)
-100
(-1000-550)
-170
(-1700-920)
0
(-900-600)
440
(-26-770)
0
(-1700-1100)
1,200
(610 - 1600)
420
(-2200-2300)
-550
(-5600-3100)
-240
(-2400-1300)
420
(-24-750)
0
(-1400-880)
esppb
1,200
(630-1700)
-96
(-980-530)
-160
(-1600 - 890)
0
(-840-570)
430
(-25-760)
0
(-1700-1100)
1,200
(590-1600)
400
(-2100-2200)
-470
(-4600 - 2700)
-230
(-2300-1300)
400
(-23-720)
0
(-1300 - 850)
60ppb
1,200
(610 - 1700)
-92
(-930-510)
-150
(-1500-860)
0
(-780-540)
400
(-23 - 710)
0
(-1600-1000)
1,100
(580 - 1500)
380
(-1900-2100)
NA
-220
(-2200-1200)
380
(-21-690)
0
(-1200-810)
Chan{
Base-75
75
(34-110)
-6.4
(-55-41)
0.29
(3 --2)
0
(-22-22)
0.73
(0-2)
NA
-11
(-5 --18)
16
(-72-100)
-16
(-130-100)
-10
(-88-66)
90
(-5-180)
0
(-13-13)
e in Ozone-Attributable Incidence
75-70
92
(42 - 140)
-3.1
(-27-20)
-0.95
(-8-6)
0
(-34-33)
8.6
(0-18)
0
(15 --15)
32
(14-49)
19
(-87-120)
-31
(-260-200)
-8.0
(-69-52)
21
(-1-43)
0
(-44-43)
75-65
170
(77-260)
-6.9
(-59-44)
-5.8
(-50-38)
0
(-76-73)
27
(-1-55)
0
(-31-31)
69
(31-110)
41
(-180-260)
-110
(-960-690)
-17
(-150-110)
41
(-2-82)
0
(-96-92)
75-60
230
(110-350)
-11
(-93 - 68)
-12
(-100-77)
0
(-120-110)
67
(-3-130)
0
(-90-88)
110
(51 - 170)
63
(-290-400)
NA
-25
(-220-160)
65
(-3 - 130)
0
(-160-150)
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
42.6
-7.4
-6.1
0
27.5
0
41.0
4.7
-6.7
-7.1
28.5
0
75ppb
41.3
-6.9
-6.1
0
27.5
0
41.2
4.6
-6.5
-6.7
24.9
0
70ppb
39.6
-6.6
-6.0
0
27.1
0
40.6
4.4
-6.0
-6.5
24.0
0
65ppb
38.1
-6.3
-5.8
0
26.3
0
39.8
4.3
-5.0
-6.1
23.2
0
60ppb
36.9
-5.9
-5.5
0
24.5
0
38.9
4.1
NA
-5.9
22.1
0
Change in O3-Attributable Risk
Base-75
3.1
7.7
-0.2
0
0.1
NA
-0.5
2.4
3.4
5.3
12.8
0
75-70
4.0
4.0
0.7
0
1.3
0
1.5
3.1
6.8
4.3
3.6
0
75-65
7.6
8.7
4.5
0
4.2
0
3.4
6.7
23.5
9.1
6.9
0
75-60
10.7
13.4
9.2
0
10.7
0
5.7
10.6
NA
13.3
11.2
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
47
-6.8
-6.1
0
31
0
38
6.2
-5.3
-7.2
41
0
75ppb
46
-6.4
-6.1
0
31
0
38
6.0
-5.2
-6.9
36
0
70ppb
44
-6.2
-6.0
0
30
0
37
5.8
-4.9
-6.7
34
0
65ppb
42
-6.0
-5.8
0
30
0
37
5.5
-4.2
-6.4
33
0
60ppb
41
-5.7
-5.6
0
27
0
36
5.2
NA
-6.2
32
0
Change in Ozone-Attributable Deaths per 100,000
Base-75
2.5
-0.40
0.011
0
0.050
NA
-0.36
0.22
-0.14
-0.29
7.4
0
75-70
3.1
-0.19
-0.034
0
0.59
0
1.00
0.27
-0.27
-0.23
1.7
0
75-65
5.7
-0.43
-0.21
0
1.9
0
2.2
0.56
-0.97
-0.48
3.3
0
75-60
7.9
-0.66
-0.44
0
4.6
0
3.6
0.87
NA
-0.71
5.3
0
NA: for NYC, the model-based adjustment methodology was unable to estimate ozone distributions which would meet the
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 Incidence
Base
400
(120-660)
260
(80-430)
410
(120-670)
220
(65-360)
220
(68-370)
380
(110-620)
340
(100-560)
1,100
(350-1900)
1,500
(440-2400)
620
(190-1000)
250
(76-410)
320
(95-520)
75ppb
390
(120-630)
250
(75-410)
410
(120-670)
210
(63 - 350)
220
(68-360)
380
(110-620)
340
(100-560)
1,100
(340-1800)
1,400
(430-2300)
590
(180-970)
220
(65-350)
310
(94-510)
70ppb
370
(110-600)
240
(73 - 400)
400
(120-670)
200
(61-330)
220
(67-360)
380
(110-630)
340
(100-550)
1,100
(320-1700)
1,300
(400-2200)
580
(170-940)
210
(62-340)
300
(90-490)
esppb
350
(100-580)
230
(70-380)
390
(120-650)
190
(57-320)
210
(65-350)
370
(110-610)
330
(98-540)
1,000
(310-1700)
1,200
(350-1900)
550
(170-910)
200
(60-330)
290
(86-470)
eoppb
340
(100-550)
230
(67-370)
380
(110-620)
180
(54-300)
200
(59-320)
350
(110-580)
320
(95-520)
960
(290-1600)
NA
530
(160-880)
190
(56-310)
270
(81-450)
Change in ncidence
base-75
18
(5-30)
17
(5-29)
-0.77
(0--1)
6.4
(2-11)
0.34
(0-1)
NA
-2.7
(-1--5)
43
(12-73)
42
(12-71)
27
(8-46)
42
(12-71)
3.8
(1-7)
75-70
22
(6-37)
8.2
(2-14)
2.5
(1-4)
9.9
(3-17)
3.9
(1-7)
-4.5
(-1--8)
7.5
(2-13)
52
(15-89)
81
(23-140)
21
(6-36)
9.8
(3-17)
13
(4-22)
75-65
40
(12-69)
18
(5-31)
15
(4-26)
22
(6-37)
12
(4-21)
9.2
(3-16)
16
(5-28)
110
(31-180)
290
(83 - 490)
45
(13-77)
19
(5-32)
28
(8-47)
75-60
56
(16-96)
28
(8-48)
32
(9-54)
34
(10-58)
31
(9-53)
26
(8-45)
27
(8-46)
170
(49-290)
NA
66
(19-110)
30
(9-51)
45
(13-77)
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
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
11.2
11.8
14.1
11.9
11.9
14.6
11.7
12.1
12.6
12.4
70ppb
11.3
11.9
11.1
11.3
13.9
12.0
11.6
14.1
11.1
11.7
12.1
12.0
65ppb
10.8
11.4
10.8
10.7
13.5
11.7
11.4
13.4
9.6
11.2
11.7
11.5
eoppb
10.4
11.0
10.4
10.1
12.4
11.2
11.0
12.7
NA
10.9
11.1
10.9
Change in O3-Attributable Risk
Base-75
4
6
-0.2
3
0.1
NA
-1
3
3
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
14
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
Ai r Quality Scenario
Ozone-Attributable Deaths per 100,000 Change in Ozone-Attributable Deaths per 100,000
Base
14
16
15
17
15
14
11
16
13
17
21
19
75ppb
13
16
15
16
15
14
11
15
13
17
18
19
70ppb
12
15
15
16
15
15
11
15
12
16
17
18
65ppb
12
15
14
15
15
14
10
14
10
16
16
17
eoppb
11
14
14
14
14
14
10
13
NA
15
15
16
Base-75
0.60
1.0
-0.028
0.49
0.023
NA
-0.084
0.59
0.37
0.76
3.4
0.23
75-70
0.74
0.51
0.091
0.76
0.27
-0.17
0.24
0.72
0.71
0.60
0.80
0.76
75-65
1.4
1.1
0.56
1.7
0.85
0.35
0.51
1.5
2.5
1.3
1.5
1.6
75-60
1.9
1.7
1.2
2.6
2.1
1.00
0.86
2.3
NA
1.9
2.5
2.7
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.
"0" incidence values denote non-zero estimates that round to zero.
7C-8
-------
Table 7C-8. Sensitivity Analysis —LTMortality: Threshold models (ozone-only effect
estimate) (2009 Baseline) (ozone-attributable deaths, percent of baseline mortality,
incidence per 100,000 - compare with Core Results in Table 7B-7).
Ozone-Attributable Deaths
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
Type of Ozone Model
Non-Threshold'
86 city model
400
(120-660)
260
(80-430)
410
(120-670)
220
(65-360)
220
(68-370)
380
(110-620)
340
(100-560)
1100
(350-1900)
1500
(440-2400)
620
(190-1000)
250
(76-410)
320
(95-520)
96 city model
430
(160-670)
280
(110-440)
430
(160-690)
230
(86-370)
240
(90-370)
400
(150-640)
360
(130-570)
1200
(460-1900)
1600
(580-2500)
660
(240-1000)
270
(100-420)
340
(120-530)
Threshold
40ppb
99
(40-160)
77
(31-120)
52
(21-83)
48
(19-76)
85
(34-130)
77
(31-120)
66
(26-100)
500
(200-790)
310
(120-490)
160
(64-250)
100
(42-160)
83
(33-130)
45ppb
54
(22-84)
50
(21-78)
(---)
22
(9 - 35)
66
(28-100)
31
(13-49)
24
(10-37)
420
(180-660)
140
(56-210)
93
(39-150)
86
(36-130)
49
(20-77)
SOppb
(---)
17
(7-27)
(---)
(---)
43
(18-68)
(---)
(---)
320
(130-500)
(---)
12
(5-19)
62
(26-97)
8
(3 - 12)
55ppb
(---)
(---)
(---)
(---)
18
(8-28)
(---)
(---)
220
(99-340)
(---)
(---)
38
(17-59)
(---)
56ppb
(---)
(---)
(---)
(---)
12
(6-19)
(---)
(---)
200
(89-300)
(---)
(---)
33
(15-50)
(---)
60ppb
(---)
(---)
(---)
(---)
(---)
(---)
(---)
65
(22-110)
(---)
(---)
3
(1-6)
(---)
Percent of Baseline Incidence Attributable to Ozone
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
Type of Ozone Model
Non-Threshold'
86 city model
12.4
12.9
11.1
12.1
14.1
11.9
11.8
15.1
12.0
12.5
14.7
12.6
96 city model
13.2
13.8
11.9
12.9
15.1
12.7
12.6
16.2
12.8
13.4
15.8
13.5
Threshold
40ppb
3.1
3.8
1.4
2.7
5.4
2.5
2.3
6.7
2.6
3.3
6.2
3.3
45ppb
1.7
2.5
1.3
4.2
1.0
0.8
5.6
1.1
1.9
5.1
2.0
SOppb
0.8
2.7
4.2
0.2
3.7
0.3
55ppb
1.2
2.9
2.3
56ppb
0.8
2.6
1.9
60ppb
0.9
0.2
Ozone-Attributable Deaths per 100,000 Population
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
Type of Ozone Model
Non-Threshold*
86 city model
14
16
15
17
15
14
11
16
13
17
21
19
96 city model
15
18
16
18
16
15
11
17
14
19
22
20
Threshold
40ppb
3.3
4.8
1.9
3.7
5.8
2.9
2.1
6.9
2.7
4.5
8.6
5.0
45ppb
1.8
3.1
1.7
4.6
1.2
0.75
5.8
1.2
2.6
7.0
2.9
SOppb
1.1
3.0
4.4
0.34
5.1
0.47
55ppb
1.3
3.0
3.1
56ppb
0.84
2.7
2.7
60ppb
0.89
0.28
* The 86 city model is the ozone-only long-term mortality model used for a sensitivity analysis in the Ozone HREA
(see Table 7C-7). All other models (including threshold models) presented in this table were generated using the 96 city
dataset rather than the 86 city dataset (Jerrett et al, 2014).
7C-9
-------
Table 7C-9. Sensitivity Analysis - LT Mortality: Threshold models (ozone-only effect
estimate) (2009 Current Standard 75ppb) (ozone-attributable deaths, percent of baseline
mortality, incidence per 100,000 - compare with Core Results in Table 7B-7).
Ozone-Attributable Deaths
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
Type of Ozone Model
Non-Threshold*
86 city model
390
(120-630)
250
(75 - 410)
410
(120-670)
210
(63 - 350)
220
(68-360)
380
(110-620)
340
(100-560)
1100
(340 - 1800)
1400
(430 - 2300)
590
(180-970)
220
(65 - 350)
310
(94-510)
96 city model
410
(150-650)
270
(99 - 420)
440
(160-690)
230
(84-360)
240
(89 - 370)
400
(150-640)
370
(140-580)
1200
(440-1800)
1500
(560-2400)
630
(240-1000)
230
(85 - 360)
330
(120-520)
Threshold
40ppb
79
(31-130)
58
(23-92)
53
(21 - 85)
41
(16-65)
85
(34-130)
77
(31-120)
69
(28-110)
450
(180-720)
260
(100-420)
130
(52-210)
58
(23-91)
79
(32-120)
45ppb
32
(13-50)
29
(12-46)
-
(...)
14
(6-23)
66
(28-100)
31
(13-49)
27
(11-43)
370
(160-580)
83
(35 - 130)
59
(25-93)
34
(14-54)
44
(18-69)
SOppb
(...)
-
(...)
-
(...)
(...)
43
(18-67)
(...)
(...)
260
(110-410)
(...)
-
(...)
7
(3-11)
3
(1-4)
SSppb
(...)
-
(...)
-
(...)
(...)
18
(8-28)
(...)
(...)
160
(69 - 240)
(...)
-
(...)
(...)
(...)
S6ppb
(...)
-
(...)
-
(...)
(...)
12
(5-18)
(...)
(...)
130
(58-200)
(...)
-
(...)
(...)
(...)
eoppb
(...)
(...)
(...)
(...)
(...)
(...)
(...)
(...)
(...)
(...)
(...)
(...)
Percent of Baseline Incidence Attributable to Ozone
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
Type of Ozone Model
Non-Threshold*
86 city model
11.9
12.2
11.2
11.8
14.1
11.9
11.9
14.6
11.7
12.1
12.6
12.4
96 city model
12.7
13.1
11.9
12.6
15.1
12.7
12.7
15.6
12.5
12.9
13.5
13.3
Threshold
40ppb
2.4
2.8
1.5
2.3
5.4
2.5
2.4
6.0
2.2
2.6
3.4
3.2
45ppb
1.0
1.4
-
0.8
4.2
1.0
0.9
4.9
0.7
1.2
2.0
1.8
SOppb
-
-
2.7
-
3.5
-
-
0.4
0.1
SSppb
-
-
1.1
-
2.1
-
-
-
S6ppb
-
-
0.7
-
1.7
-
-
-
60ppb
Ozone-Attributable Deaths per 100,000 Popu ation
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
Type of Ozone Model
Non-Threshold*
86 city model
13
16
15
16
15
14
11
15
13
17
18
19
96 city model
14
17
16
17
16
15
12
16
13
18
19
20
Threshold
40ppb
2.7
3.6
1.9
3.1
5.8
2.9
2.2
6.3
2.3
3.7
4.7
4.7
45ppb
1.1
1.8
1.1
4.5
1.2
0.85
5.1
0.73
1.7
2.8
2.6
SOppb
-
2.9
-
3.6
-
0.55
0.16
SSppb
-
1.2
-
2.1
-
-
S6ppb
-
0.80
-
1.8
-
-
eoppb
* The 86 city model is the ozone-only long-term mortality model used for a sensitivity analysis in the Ozone HREA
(see Table 7C-7). All other models (including threshold models) presented in this table were generated using the 96 city
dataset rather than the 86 city dataset (Jerrett et al, 2014).
7C-10
-------
Table 7C-10. Sensitivity Analysis —LTMortality: Threshold models (ozone-only effect
estimate) (2009 Current Standard 70ppb) (ozone-attributable deaths, percent of baseline
mortality, incidence per 100,000 - compare with Core Results in Table 7B-7).
Ozone-Attributable Deaths
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
Type of Ozone Model
Non-Threshold*
86 city model
370
(110-600)
240
(73 - 400)
400
(120-670)
200
(61 - 330)
220
(67 - 360)
380
(110-630)
340
(100-550)
1100
(320-1700)
1300
(400-2200)
580
(170-940)
210
(62 - 340)
300
(90-490)
% city model
390
(140-620)
260
(96-410)
430
(160-680)
220
(80-340)
240
(88-370)
410
(150-640)
360
(130-570)
1100
(420-1800)
1400
(530-2300)
610
(230-970)
220
(82 - 350)
320
(120-510)
Threshold
40ppb
53
(21-85)
49
(19-77)
50
(20-80)
29
(12-47)
80
(32 - 130)
83
(33-130)
60
(24-96)
400
(160-630)
170
(68- 270)
110
(42 - 170)
46
(19-74)
64
(26-100)
45ppb
4
(2-6)
19
(8-30)
(...)
2
(1-3)
61
(26-96)
37
(15-58)
18
(7-28)
310
(130-480)
(...)
32
(14-51)
22
(9-35)
28
(12-44)
SOppb
(...)
(...)
(...)
(...)
38
(16-59)
(...)
(...)
200
(82 - 310)
(...)
(...)
(...)
(...)
SSppb
(...)
(...)
-
(...)
-
(...)
12
(5-18)
(...)
(...)
74
(33 - 120)
(...)
(...)
(...)
(...)
56ppb
(...)
(...)
-
(...)
-
(...)
5
(2-8)
(...)
(...)
45
(20-70)
(...)
(...)
(...)
(...)
eoppb
(...)
(...)
.
(...)
.
(...)
(...)
(...)
(...)
.
(...)
(...)
(...)
(...)
(...)
Percent of Baseline Incidence Attributable to Ozone
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
Type of Ozone Model
Non-Threshold*
86 city model
11.3
11.9
11.1
11.3
13.9
12.0
11.6
14.1
11.1
11.7
12.1
12.0
% city model
12.1
12.7
11.9
12.1
14.9
12.9
12.5
15.0
11.9
12.5
13.0
12.8
Threshold
40ppb
1.7
2.4
1.4
1.6
5.1
2.6
2.1
5.3
1.4
2.2
2.7
2.6
45ppb
0.1
0.9
0.1
3.9
1.2
0.6
4.1
0.7
1.3
1.1
SOppb
2.4
2.6
SSppb
0.7
-
-
1.0
-
56ppb
0.3
-
-
0.6
-
eoppb
.
.
.
.
.
Ozone-Attributable Deaths per 100,000 Popu ation
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
Type of Ozone Model
Non-Threshold*
86 city model
12
15
15
16
15
15
11
15
12
16
17
18
% city model
13
16
16
17
16
16
11
16
13
17
18
19
Threshold
40ppb
1.8
3.0
1.8
2.3
5.5
3.1
1.9
5.5
1.5
3.0
3.8
3.8
45ppb
0.14
1.2
0.15
4.2
1.4
0.56
4.2
0.91
1.8
1.7
SOppb
2.6
2.7
SSppb
-
-
0.80
1.0
-
-
-
-
56ppb
-
-
0.36
0.62
-
-
-
-
eoppb
.
.
.
.
.
.
-
* The 86 city model is the ozone-only long-term mortality model used for a sensitivity analysis in the Ozone HREA
(see Table 7C-7). All other models (including threshold models) presented in this table were generated using the 96 city
dataset rather than the 86 city dataset (Jerrett et al., 2014).
7C-11
-------
Table 7C-11. Sensitivity Analysis - LT Mortality: Threshold models (ozone-only effect
estimate) (2009 Current Standard 65ppb) (ozone-attributable deaths, percent of baseline
mortality, incidence per 100,000 - compare with Core Results in Table 7B-7).
Ozone-Attributable Deaths
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
Type of Ozone Model
Non-Threshold*
86 city model
350
(100-580)
230
(70 - 380)
390
(120-650)
190
(57 - 320)
210
(65 - 350)
370
(110-610)
330
(98 - 540)
1000
(310 - 1700)
1200
(350 - 1900)
550
(170-910)
200
(60 - 330)
290
(86 - 470)
96 city model
370
(140-590)
250
(92-400)
420
(150-670)
210
(76-330)
230
(85-360)
400
(150-620)
350
(130-550)
1100
(400-1700)
1200
(460-2000)
590
(220-940)
210
(79-330)
310
(110-480)
Threshold
40ppb
32
(13-51)
37
(15-59)
35
(14-56)
15
(6-25)
71
(28-110)
67
(27-110)
50
(20-80)
330
(130-530)
-
(...)
78
(31 - 120)
36
(14-58)
47
(19-75)
45ppb
-
(...)
6
(3-10)
-
(...)
(...)
51
(21-80)
20
(8-31)
7
(3 - 10)
240
(100-370)
-
(...)
2
(1-3)
11
(5-17)
9
(4-15)
SOppb
-
(...)
-
(...)
-
(...)
(...)
26
(11-42)
(...)
(...)
120
(50 - 190)
-
(...)
-
(...)
-
(...)
-
(...)
55ppb
-
(...)
-
(...)
-
(...)
(...)
(...)
(...)
(...)
(...)
-
(...)
-
(...)
-
(...)
-
(...)
56ppb
-
(...)
-
(...)
-
(...)
(...)
(...)
(...)
(...)
(...)
-
(...)
-
(...)
-
(...)
-
(...)
60ppb
-
(...)
-
(...)
-
(...)
(...)
(...)
(...)
(...)
(...)
-
(...)
-
(...)
-
(...)
-
(...)
Percent of Baseline Incidence Attributable to Ozone
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
Type of Ozone Model
Non-Threshold*
86 city model
10.8
11.4
10.8
10.7
13.5
11.7
11.4
13.4
9.6
11.2
11.7
11.5
96 city model
11.5
12.2
11.5
11.5
14.4
12.5
12.2
14.3
10.3
12.0
12.5
12.3
Threshold
40ppb
1.0
1.8
1.0
0.9
4.5
2.1
1.8
4.4
1.6
2.1
1.9
45ppb
-
0.3
-
3.2
0.6
0.2
3.2
0.0
0.6
0.4
SOppb
-
-
1.7
-
1.6
-
55ppb
-
-
-
-
-
56ppb
-
-
-
-
-
eoppb
.
.
.
.
.
Ozone-Attributable Deaths per 100,000 Population
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
Type of Ozone Model
Non-Threshold*
86 city model
12
15
14
15
15
14
10
14
10
16
16
17
96 city model
13
16
15
16
16
15
11
15
11
17
17
18
Threshold
40ppb
1.1
2.3
1.3
1.2
4.9
2.5
1.6
4.6
-
2.2
3.0
2.8
45ppb
0.39
-
3.5
0.75
0.21
3.3
-
0.060
0.89
0.55
SOppb
-
-
1.8
-
1.7
-
-
55ppb
-
-
-
-
-
-
56ppb
-
-
-
-
-
-
60ppb
-
-
-
-
-
-
* The 86 city model is the ozone-only long-term mortality model used for a sensitivity analysis in the Ozone HREA
(see Table 7C-7). All other models (including threshold models) presented in this table were generated using the 96 city
dataset rather than the 86 city dataset (Jerrett et al., 2014).
7C-12
-------
Table 7C-12. Sensitivity Analysis - LT Mortality: Threshold models (ozone-only effect
estimate) (2009 Current Standard 60ppb) (ozone-attributable deaths, percent of baseline
mortality, incidence per 100,000 - compare with Core Results in Table 7B-7).
Ozone-Attributable Deaths
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
Type of Ozone Model
Non-Threshold'
86 city model
340
(100-550)
230
(67 - 370)
380
(110-620)
180
(54 - 300)
200
(59 - 320)
350
(110-580)
320
(95-520)
960
(290-1600)
96 city model
360
(130-570)
240
(89-380)
400
(150-640)
190
(71-310)
210
(78-330)
380
(140-600)
340
(130-540)
1000
(380-1600)
Threshold
40ppb
13
(5-21)
26
(10-41)
16
(7-26)
1
(0-2)
50
(20-79)
47
(19-75)
38
(15-60)
260
(110-420)
45ppb
(---)
(---)
(---)
(---)
28
(12-43)
(---)
(---)
160
(68 - 260)
SOppb
(---)
(---)
(---)
(---)
1
(1-2)
(---)
(---)
40
(17-63)
55ppb
(---)
(---)
(---)
(---)
(---)
(---)
(---)
(---)
56ppb
(---)
(---)
(---)
(---)
(---)
(---)
(---)
(---)
eoppb
(---)
(---)
(---)
(---)
(---)
(---)
(---)
(---)
NA
530
(160-880)
190
(56 - 310)
270
(81-450)
570
(210-910)
200
(74-320)
290
(110-460)
53
(21-84)
23
(9-36)
26
(11-42)
(---)
(---)
(---)
(---)
(---)
(---)
(---)
(---)
(---)
(---)
(---)
(---)
(---)
(---)
(---)
Percent of Baseline Incidence Attributable to Ozone
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
Type of Ozone Model
Non-Threshold*
86 city model
10.4
11.0
10.4
10.1
12.4
11.2
11.0
12.7
96 city model
11.1
11.8
11.1
10.8
13.3
12.0
11.8
13.6
Threshold
40ppb
0.4
1.3
0.4
0.1
3.1
1.5
1.3
3.5
45ppb
1.7
2.2
SOppb
0.1
0.5
55ppb
56ppb
60ppb
NA
10.9
11.1
10.9
11.6
11.8
11.6
1.1
1.3
1.1
Ozone-Attributable Deaths per 100,000 Population
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
Type of Ozone Model
Non-Threshold*
86 city model
11
14
14
14
14
14
10
13
96 city model
12
15
15
15
14
14
11
14
Threshold
40ppb
0.44
1.6
0.59
0.073
3.4
1.8
1.2
3.7
45ppb
1.9
2.2
SOppb
0.096
0.55
55ppb
56ppb
60ppb
NA
15
15
16
16
16
17
1.5
1.9
1.6
* The 86 city model is the ozone-only long-term mortality model used for a sensitivity analysis in the Ozone HREA
(see Table 7C-7). All other models (including threshold models) presented in this table were generated using the 96 city
dataset rather than the 86 city dataset (Jerrett et al, 2014).
NA: for NYC, the model-based adjustment methodology was unable to adjust Os distributions such that they would
meet the alternative standard level of 60 ppb.
7C-13
-------
This page left intentionally blank
7C-14
-------
APPENDIX 8A
City-Specific Ozone-Mortality Effect Estimates
This Appendix contains two tables specifying the effect estimates from Smith et al. (2009)
(Table 8A-1) and Zanobetti and Schwartz (2008) (Table 8A-2) studies that were used in the
national-scale epidemiological-based risk assessment. References are included immediately
following the tables.
8A-i
-------
Table 8A-1. 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, Rl
Dallas/Ft Worth, TX
Dayton, OH
Denver, CO
Des Moines, IA
Detroit, Ml
El Paso, TX
Evansville
Ft Wayne, IN
Fresno, CA
Grand Rapids, Ml
Greensboro, NC
Honolulu, HI
Houston, TX
Huntsville, AL
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
0.000188
0.000377
0.000291
0.000451
0.000403
0.000548
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
0.000334
0.000335
0.000346
0.000358
0.000215
0.000357
Regional prior
Beta
0.000502
-5E-05
0.00091
0.000222
-1.6E-05
4.41 E-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
-2.6E-05
0.000537
0.000231
6.17E-05
0.00032
0.000349
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
0.000283
0.00028
0.000262
0.000236
0.000189
0.000271
8A-1
-------
Location
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, Wl
Memphis, TN
Miami, FL
Milwaukee, Wl
Mobile, AL
Modesto, CA
Muskegon, Ml
Nashville, TN
National Average
New Orleans, LA
New York, NY
Newark, NJ
North East
North West
Oakland, CA
Oklahoma City, OK
Omaha, NE
Orlando, FL
Philadelphia, PA
Phoenix, AZ
Pittsburgh, PA
National prior
Beta
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
-3.3E-05
0.000574
0.00034
0.000155
Std
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
0.000358
0.000296
0.000301
0.000306
Regional prior
Beta
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
7.91 E-05
0.000948
7.84E-06
0.000412
Std
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
0.000286
0.000253
0.00032
0.000272
8A-2
-------
Location
Portland, OR
Providence, Rl
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
National prior
Beta
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
Std
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
Regional prior
Beta
0.00025
0.000922
0.000223
2.3E-06
0.000923
0.000225
0.000215
-0.00012
7.61 E-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
-2.1 E-05
0.000277
-0.0002
0.000823
-0.00022
0.000946
Std
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
8A-3
-------
Table 8A-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, Ml
Greensboro, NC
Honolulu, HI
Houston, TX
Jersey city, NJ
Kansas City, KS
Los Angeles, CA
Miami, FL
Milwaukee, Wl
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
8A-4
-------
Location
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
Beta
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
Std
0.000389
0.000407
0.000373
0.000416
0.00038
0.000415
0.000333
0.000366
0.00042
0.000391
0.00036
0.000394
REFERENCES
Smith R.L.; B. Xu and P. Switzer. 2009. Reassessing the relationship between ozone and short-
term mortality in U.S. urban communities. Inhalation Toxicology. 21:37-61.
Zanobetti, A. and J. Schwartz. 2011. Ozone and survival in four cohorts with potentially
predisposing diseases. American Journal of Respiratory and Critical Care Medicine.
194:836-841.
8A-5
-------
APPENDIX 8B
Supplement to the Representativeness Analysis of the 12 Urban
Study Areas
Table of Contents
8B-1. ELEMENTS OF THE RISK EQUATION 8B-1
8B-2. VARIABLES EXPECTED TO INFLUENCE THE RELATIVE RISK FROM OZONE...
8B-17
8B-2.1 Demographic Variables 8B-17
8B-2.2 Health Conditions 8B-25
8B-2.3 Air Quality and Climate Variables 8B-34
8B-i
-------
List of Figures
Figure 8B-1. Comparison of distributions for key elements of the risk equation: Total
population 8B-1
Figure 8B-2. Comparison of distributions for key elements of the risk equation: Percent of
population younger than 15 years old 8B-2
Figure 8B-3. Comparison of distributions for key elements of the risk equation: Percent of
population 65 and older 8B-3
Figure 8B-4. Comparison of distributions for key elements of the risk equation: Percent of
population 85 and older 8B-4
Figure 8B-5 Comparison of distributions for key elements of the risk equation: Seasonal mean
8-hr daily maximum ozone concentration 8B-5
Figure 8B-6. Comparison of distributions for key elements of the risk equation: 4th highest 8-hr
daily maximum ozone concentration 8B-6
Figure 8B-7. Comparison of distributions for key elements of the risk equation: Seasonal mean
1-hr daily maximum ozone concentration 8B-7
Figure 8B-8. Comparison of distributions for key elements of the risk equation: Seasonal mean
ozone concentration 8B-8
Figure 8B-9. Comparison of distributions for key elements of the risk equation: Baseline all-
cause mortality 8B-9
Figure 8B-10. Comparison of distributions for key elements of the risk equation: Baseline non-
accidental mortality 8B-10
Figure 8B-11. Comparison of distributions for key elements of the risk equation: Baseline
cardiovascular mortality 8B-11
Figure 8B-12. Comparison of distributions for key elements of the risk equation: Baseline
respiratory mortality 8B-12
Figure 8B-13. Comparison of distributions for key elements of the risk equation: Non-accidental
mortality risk coefficient from Bell etal. (2004) 8B-13
Figure 8B-14. Comparison of distributions for key elements of the risk equation: All-cause
mortality risk coefficient from Zanobetti and Schwartz (2008) 8B-14
Figure 8B-15. Comparison of distributions for key elements of the risk equation: Cardiovascular
mortality risk coefficient from Zanobetti and Schwartz (2008) 8B-15
Figure 8B-16. Comparison of distributions for key elements of the risk equation: Respiratory
mortality risk coefficient from Zanobetti and Schwartz (2008) 8B-16
Figure 8B-17. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Population density 8B-17
Figure 8B-18. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Median age 8B-18
Figure 8B-19. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Percent less than high school education 8B-19
8B-ii
-------
Figure 8B-20. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Unemployment rate 8B-20
Figure 8B-21. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Percent non-white 8B-21
Figure 8B-22. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Urbanicity 8B-22
Figure 8B-23. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Air conditioning prevalence 8B-23
Figure 8B-24. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Percent commuting by public transportation 8B-24
Figure 8B-25. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Acute myocardial infarction prevalence 8B-25
Figure 8B-26. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Diabetes prevalence 8B-26
Figure 8B-27. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Stroke prevalence 8B-27
Figure 8B-28. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Coronary heart disease prevalence 8B-28
Figure 8B-29. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Obesity prevalence 8B-29
Figure 8B-30. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Vigorous activity at least 20 minutes per day 8B-30
Figure 8B-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 8B-31
Figure 8B-32. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Asthma prevalence 8B-32
Figure 8B-33. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Smoking prevalence 8B-33
Figure 8B-34. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Annual average PM2.5 concentration 8B-34
Figure 8B-35. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: 98th percentile PM2.5 concentration 8B-35
Figure 8B-36. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Percent of days with PM2.5 exceeding 35 |ig/m3. ... 8B-36
Figure 8B-37. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Average temperature 8B-37
Figure 8B-38. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: July temperature 8B-38
Figure 8B-39. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Relative humidity 8B-39
-------
Following the analysis discussed in the main body of the HREA 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.
8B-1. 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 8B-1. Comparison of distributions for key elements of the risk equation: Total
population.
8B-1
-------
Comparison of Urban Case Study Area with U.S. Distribution (3141 U.S.
Counties) - Percent Younger than 15 Years Old
14
16
18 20 22 24 26
% Younger than 15 Years Old, 2005
28
30
•All Counties CDF
Case Study Counties
Figure 8B-2. Comparison of distributions for key elements of the risk equation: Percent of
population younger than 15 years old.
8B-2
-------
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
11 13 15 17 19
% 65 Years and Older, 2005
21 23
•All Counties CDF
Case Study Counties
25 27
Figure 8B-3. Comparison of distributions for key elements of the risk equation: Percent of
population 65 and older.
8B-2
-------
Comparison of Urban Case Study Area with U.S. Distribution (3141 U.S.
Counties) - Percent 85 Years and Older
100%
90%
80%
S 70%
§ 60%
o
u
^ 50%
^ 40%
* 30%
20%
10%
0% -
<
^
H
^
1— 1
/
/
1 1
A
/
I-H
^
H
f
1 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
1.5 2 2.5 3 3.5
% 85 Years and Older, 2005
4.5
5.5
•All Counties CDF
Case Study Counties
Figure 8B-4. Comparison of distributions for key elements of the risk equation: Percent of
population 85 and older.
8B-4
-------
Comparison of Urban Case Study Area with U.S. Distribution (671 U.S.
Counties with Ozone Monitors) -
Seasonal Mean 8-hr Daily Max Ozone
100%
90%
80%
I 70%
o 60%
"S 50%
o
'E 40%
o
J 30%
S? 20%
10%
^^^^^ ^-1
/
Ul
/
1— 1
/'
1 — 1
/
II 1
Ul
1 — 1
y
/
i 1
r
l 1
l — i
ll
^
S
\ 1
ll
-— — —-
x^
1 , 1
^^^^^^^^
1 ,
30 40 50 60 70
Seasonal Mean 8-hr Daily Max Ozone Concentration, Average 2006-2008
(ppb)
•All Counties CDF
Case Study Counties
Figure 8B-5 Comparison of distributions for key elements of the risk equation: Seasonal
mean 8-hr daily maximum ozone concentration.
8B-5
-------
O
u
1
O
4->
'E
O
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
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
50 60 70 80 90 100
4th High 8-hr Daily Maximum Ozone, 2007 (ppb)
110
•All Counties CDF
Case Study Counties
Figure 8B-6. Comparison of distributions for key elements of the risk equation: 4th highest
8-hr daily maximum ozone concentration.
8B-6
-------
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
4-1
'E
o
°
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
^
1
X
1 1
1 III
40 50 60 70 80
Seasonal Mean 1-hr Daily Max Ozone Concentration, Average 2006-2008
(ppb)
•All Counties CDF
Case Study Counties
Figure 8B-7. Comparison of distributions for key elements of the risk equation: Seasonal
mean 1-hr daily maximum ozone concentration.
8B-7
-------
Comparison of Urban Case Study Area with U.S. Distribution (671 U.S.
Counties with Ozone Monitors) -
Seasonal Mean Ozone
100%
90%
80%
S 70%
§ 60%
o
£ 50%
S!
2 40%
c
| 30%
1 20%
10%
^^^^^ 1
>
X
i 1
/
i ii
L 1
'
IJ
1— 1
,'
1— II
*«
II
/
r
i — i
20 30 40 50
Seasonal Mean Ozone Concentration, Average 2006-2008 (ppb)
60
•All Counties CDF
Case Study Counties
Figure 8B-8. Comparison of distributions for key elements of the risk equation: Seasonal
mean ozone concentration.
8B-8
-------
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 8B-9. Comparison of distributions for key elements of the risk equation: Baseline
all-cause mortality.
8B-9
-------
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 8B-10. Comparison of distributions for key elements of the risk equation: Baseline
non-accidental mortality.
8B-10
-------
Comparison of Urban Case Study Area with U.S. Distribution (3110 U.S.
Counties) - Cardiovascular Mortality
100%
VI
Q)
c
3
o
u
"I
"S
*
90%
80%
70%
60%
50%
40%
30%
20%
10%
0% -
—=1
100
200 300 400 500
Cardiovascular Mortality per 100,000 Population, 1999-2005
600
•All Counties CDF
Case Study Counties
Figure 8B-11. Comparison of distributions for key elements of the risk equation: Baseline
cardiovascular mortality.
8B-11
-------
Comparison of Urban Case Study Area with U.S. Distribution (2993 U.S.
Counties) - Respiratory Mortality
100%
90%
80%
S 70%
"5
§ 60%
o
ri 50%
^ 40%
* 30%
20%
10%
0%
20
• 111111 •• •• 1 ill •
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 8B-12. Comparison of distributions for key elements of the risk equation: Baseline
respiratory mortality.
8B-12
-------
Comparison of Urban Case Study Area with U.S. Distribution (95
NMMAPS Cities) -
Non Accidental Mortality Risk ((J)
0%
0.0002
0.0004 0.0006 0.0008 0.001
Non Accidental Mortality Risk Coefficient ((J)
0.0012
•All Cities CDF
Case Study Cities
Figure 8B-13. Comparison of distributions for key elements of the risk equation: Non-
accidental mortality risk coefficient from Bell et al. (2004).
8B-13
-------
Comparison of Urban Case Study Area with U.S. Distribution (48 Z&S
Cities) - All Cause Mortality Risk (p)
0)
.a
o
c
TO
M
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
0.0002
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 8B-14. Comparison of distributions for key elements of the risk equation: All-cause
mortality risk coefficient from Zanobetti and Schwartz (2008).
8B-14
-------
Comparison of Urban Case Study Area with U.S. Distribution (48 Z&S
Cities) - Cardiovascular Mortality Risk Coefficient ((J)
1/1
0)
s
u
I
o
DL
N
ro
.c
£
(D
QJ
^
O
C
ro
M
'o
*
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
1
0.0002
0.0005 0.0008 0.0011
Cardiovascular Mortality Risk Coefficient
0.0014
0.0017
All Cities
•All Cities CDF
Case Study Cities
Figure 8B-15. Comparison of distributions for key elements of the risk equation:
Cardiovascular mortality risk coefficient from Zanobetti and Schwartz (2008).
8B-15
-------
Comparison of Urban Case Study Area with U.S. Distribution (48 Z&S
Cities) - Respiratory Mortality Risk ((J)
0%
0.0003
0.0005 0.0007 0.0009 0.0011
Respiratory Mortality Risk Coefficient ((J)
0.0013
All Cities
•All Cities CDF
Case Study Cities
Figure 8B-16. Comparison of distributions for key elements of the risk equation:
Respiratory mortality risk coefficient from Zanobetti and Schwartz (2008).
8B-16
-------
8B-2. VARIABLES EXPECTED TO INFLUENCE THE RELATIVE RISK FROM
OZONE
8B-2.1 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 8B-17. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Population density.
8B-17
-------
Comparison of Urban Case Study Area with U.S. Distribution (3141 U.S.
Counties) - Median Age
32 34 36 38
40 42 44 46
Median Age, 2005
48 50
52 54
•All Counties CDF
Case Study Counties
Figure 8B-18. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Median age.
8B-18
-------
100%
90%
80%
.2 70%
o 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 8B-19. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Percent less than high school education.
8B-19
-------
Comparison of Urban Case Study Area with U.S. Distribution (3141 U.S.
Counties) - Unemployment rate
6 8
Unemployment rate, 2005
10
•All Counties CDF
Case Study Counties
12
Figure 8B-20. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Unemployment rate.
8B-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 8B-22. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Urbanicity.
8B-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 8B-23. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Air conditioning prevalence.
8B-23
-------
Comparison of Urban Case Study Area with U.S. Distribution (366 U.S.
Cities) - Public Transportation Use
10 15 20 25 30
% Commuting by Public Transportation, 2010
35
40
•All Counties CDF
Case Study Counties
Figure 8B-24. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Percent commuting by public transportation.
8B-24
-------
8B-2.2 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 8B-25. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Acute myocardial infarction prevalence.
8B-25
-------
Comparison of Urban Case Study Area with U.S. Distribution (184 BFRSS
Cities) - Diabetes
8 9 10 11 12
Diabetes Prevalence, 2007 (%)
•All Counties CDF
Case Study Counties
13
14
Figure 8B-26. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Diabetes prevalence.
8B-26
-------
Comparison of Urban Case Study Area with U.S. Distribution (184 BFRSS
Cities) - Stroke
1.5
2 2.5 3 3.5 4
Stroke Prevalence, 2007 (%)
•All Counties CDF
Case Study Counties
4.5
Figure 8B-27. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Stroke prevalence.
8B-27
-------
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 8B-28. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Coronary heart disease prevalence.
8B-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 8B-29. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Obesity prevalence.
8B-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 8B-30. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Vigorous activity at least 20 minutes per day.
8B-30
-------
Comparison of Urban Case Study Area with U.S. Distribution (182 BFRSS
Cities) - Moderate Activity SOmin or Vigorous Activity 20min
S 60%
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 8B-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.
8B-31
-------
Comparison of Urban Case Study Area with U.S. Distribution (184 BFRSS
Cities) - Asthma Prevalence
.0)
§ 50%
8 10
Asthma Prevaldence, 2007(%)
12
•All Counties CDF
Case Study Counties
14
Figure 8B-32. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Asthma prevalence.
8B-32
-------
Comparison of Urban Case Study Area with U.S. Distribution (184 BFRSS
Cities) - Ever Smoked
10
15
20 25
Ever Smoked, 2007(%)
30
•All Counties CDF
Case Study Counties
35
Figure 8B-33. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Smoking prevalence.
8B-33
-------
8B-2.3 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)
•All Counties CDF
Case Study Counties
22
24
Figure 8B-34. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Annual average PMi.s concentration.
8B-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 8B-35. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: 98th percentile PMi.s concentration.
8B-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 8B-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.
8B-36
-------
Comparison of Urban Case Study Area with U.S. Distribution (202 U.S.
Counties in MCAPS Database) - Average Temperature
Average Temperature (°F)
•All Counties CDF
Case Study Counties
Figure 8B-37. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Average temperature.
8B-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
•All Counties CDF
Case Study Counties
84
86
Figure 8B-38. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: July temperature.
8B-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
•All Counties CDF
Case Study Counties
80
Figure 8B-39. Comparison of distributions for selected variables expected to influence the
relative risk from ozone: Relative humidity.
8B-39
-------
APPENDIX 8C
National Representativeness of Ozone Response to Emissions
Changes
Table of Contents
8C-1. AMBIENT TRENDS OVER A PERIOD OF NATIONALLY DECREASING NOX
EMISSIONS 8C-1
8C-1.1. Nationwide Maps Showing Absolute Changes in Ozone Between 2001-2003 and
2008-2010 8C-1
8C-1.2. Thirteen-year Ozone Trends Across the U.S. and in Urban Study Areas 8C-9
8C-2. MODELED OZONE CHANGES IN RESPONSE TO ACROSS THE BOARD
EMISSIONS REDUCTIONS 8C-24
8C-2.1. Maps of Ratios of Mean Ozone from 2007 CMAQ Simulations including
Emissions Reductions to Mean Ozone from 2007 Base CMAQ Simulations.8C-24
8C-2.2. Modeled Ozone Response Paired with Population Data 8C-34
8C-i
-------
List of Tables
Table 8C-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.... 8C-46
Table 8C-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 8C-47
Table 8C-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 urban study areas 8C-48
List of Figures
Figure 8C-1. Change in 5th percentile June-August summer season daily 8-hour maximum
ozone concentrations between 2001-2003 and 2008-2010 8C-2
Figure 8C-2. Change in 25th percentile June-August summer season daily 8-hour maximum
ozone concentrations between 2001-2003 and 2008-2010 8C-2
Figure 8C-3. Change in 50th percentile June-August summer season daily 8-hour maximum
ozone concentrations between 2001-2003 and 2008-2010 8C-3
Figure 8C-4. Change in 75th percentile June-August summer season daily 8-hour maximum
ozone concentrations between 2001-2003 and 2008-2010 8C-3
Figure 8C-5. Change in 95th percentile June-August summer season daily 8-hour maximum
ozone concentrations between 2001-2003 and 2008-2010 8C-4
Figure 8C-6. Change in 5th percentile April-October summer season daily 8-hour maximum
ozone concentrations between 2001-2003 and 2008-2010 8C-4
Figure 8C-7. Change in 25th percentile April-October summer season daily 8-hour maximum
ozone concentrations between 2001-2003 and 2008-2010 8C-5
Figure 8C-8. Change in 50th percentile April-October summer season daily 8-hour maximum
ozone concentrations between 2001-2003 and 2008-2010 8C-5
Figure 8C-9. Change in 75th percentile April-October summer season daily 8-hour maximum
ozone concentrations between 2001-2003 and 2008-2010 8C-6
Figure 8C-10. Change in 95th percentile April-October summer season daily 8-hour maximum
ozone concentrations between 2001-2003 and 2008-2010 8C-6
Figure 8C-11. Change in 5th percentile annual daily 8-hour maximum ozone concentrations
between 2001-2003 and 2008-2010 8C-7
Figure 8C-12. Change in 25th percentile annual daily 8-hour maximum ozone concentrations
between 2001-2003 and 2008-2010 8C-7
Figure 8C-13. Change in 50th percentile annual daily 8-hour maximum ozone concentrations
between 2001-2003 and 2008-2010 8C-8
Figure 8C-14. Change in 75th percentile annual daily 8-hour maximum ozone concentrations
between 2001-2003 and 2008-2010 8C-8
8C-ii
-------
Figure 8C-15. Change in 95th percentile annual daily 8-hour maximum ozone concentrations
between 2001-2003 and 2008-2010 8C-9
Figure 8C-16. Annual medians of ozone concentrations at each monitor based on different
subsets of months 8C-10
Figure 8C-17. Procedure for creating the display of Os distributions shown in Figure 8C-18....
8C-11
Figure 8C-18. KDEs of groups of monitors' annual Os 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 8C-12
Figure 8C-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 8C-13
Figure 8C-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 8C-13
Figure 8C-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 8C-14
Figure 8C-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 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 8C-15
Figure 8C-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 8C-15
Figure 8C-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 8C-16
Figure 8C-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 8C-16
Figure 8C-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 8C-17
Figure 8C-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 8C-17
Figure 8C-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 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 8C-18
Figure 8C-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
8C-iv
-------
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 8C-18
Figure 8C-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 8C-19
Figure 8C-31. Maps of NOx and VOC emissions by source sector for 2002, 2005, 2008, and
2011 8C-20
Figure 8C-32. Map of nine NOAA climate regions that were used to aggregate emissions and
ambient ozone trends. Dots show locations of ozone monitors 8C-21
Figure 8C-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.
8C-22
Figure 8C-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,
50th, 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 urban study areas) 8C-23
Figure 8C-35. Distributions of high population density monitor 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, 50th, 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 urban study areas) 8C-24
Figure 8C-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 8C-25
Figure 8C-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 8C-26
Figure 8C-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 8C-26
Figure 8C-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 8C-27
Figure 8C-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 8C-27
8C-v
-------
Figure 8C-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 8C-28
Figure 8C-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 8C-28
Figure 8C-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 8C-29
Figure 8C-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 8C-29
Figure 8C-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.. 8C-30
Figure 8C-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 8C-30
Figure 8C-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.. 8C-31
Figure 8C-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 8C-32
Figure 8C-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 8C-33
Figure 8C-50. 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
study area vs non-urban study area, urban versus non-urban and 50% NOx
reduction scenario vs 90% NOx reduction scenario 8C-35
Figure 8C-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 study area vs non-urban study area, urban versus non-
urban and 50% NOx/VOC reduction scenario vs 90% NOx/VOC reduction
scenario 8C-36
Figure 8C-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
8C-vi
-------
each panel (January, April-October). Panels split population by 15 urban 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 8C-37
Figure 8C-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
study areas while right plots show population numbers in locations included in
one of the urban 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 8C-3 8
Figure 8C-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
study areas while right plots show population numbers in locations included in
one of the urban 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 8C-39
Figure 8C-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
study areas while right plots show population numbers in locations included in
one of the urban 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 8C-40
Figure 8C-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
study areas while right plots show population numbers in locations included in
one of the urban 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 8C-41
Figure 8C-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
8C-vii
-------
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 urban
study areas while right plots show population numbers in locations included in
one of the urban 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 8C-42
Figure 8C-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 urban
study areas while right plots show population numbers in locations included in
one of the urban 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 8C-43
Figure 8C-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 urban
study areas while right plots show population numbers in locations included in
one of the urban 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 8C-44
Figure 8C-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 urban
study areas while right plots show population numbers in locations included in
one of the urban 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 8C-45
8C-viii
-------
This Appendix provides additional plots and information to support the analysis provided
in Chapter 8, section 8.2.3 of the main text of the Health Risk and Exposure Assessment
(HREA).
8C-1. AMBIENT TRENDS OVER A PERIOD OF NATIONALLY DECREASING NOX
EMISSIONS
8C-1.1. Nationwide Maps Showing Absolute Changes in Ozone Between 2001-2003 and
2008-2010
In HREA 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 5th, 25th, and 75th 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 HREA 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 95th 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. See Figure 8C-1 through Figure 8C-15
for details.
8C-1
-------
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 8C-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 8C-2. Change in 25th percentile June-August summer season daily 8-hour maximum
ozone concentrations between 2001-2003 and 2008-2010.
8C-2
-------
Change in June - August 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 8C-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
Increase 10+ ppb
Increase 5 ppb
No Change
Decrease 5 ppb
Decrease 10+ppb
Figure 8C-4. Change in 75th percentile June-August summer season daily 8-hour maximum
ozone concentrations between 2001-2003 and 2008-2010.
8C-2
-------
Change in June -August 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 8C-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 8C-6. Change in 5th percentile April-October summer season daily 8-hour
maximum ozone concentrations between 2001-2003 and 2008-2010.
8C-4
-------
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 8C-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 8C-8. Change in 50th percentile April-October summer season daily 8-hour
maximum ozone concentrations between 2001-2003 and 2008-2010.
8C-5
-------
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 8C-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 8C-10. Change in 95th percentile April-October summer season daily 8-hour
maximum ozone concentrations between 2001-2003 and 2008-2010.
8C-6
-------
Change in January - December 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 8C-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 8C-12. Change in 25th percentile annual daily 8-hour maximum ozone
concentrations between 2001-2003 and 2008-2010.
8C-7
-------
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 8C-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 8C-14. Change in 75th percentile annual daily 8-hour maximum ozone
concentrations between 2001-2003 and 2008-2010.
8C-8
-------
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 8C-15. Change in 95th percentile annual daily 8-hour maximum ozone
concentrations between 2001-2003 and 2008-2010.
8C-1.2. Thirteen-year Ozone Trends Across the U.S. and in Urban Study Areas
An initial illustrative summary of the Os trends by the categories described in HREA
Chapter 8, section 8.2.4 of the main text is shown in Figure 8C-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 8C-16, kernel density
estimates (KDEs) of the data were calculated. This process is displayed in Figure 8C-17.
8C-9
-------
Mania Baltimore Boston Chicago Cleveland Dnllas
Detroit Houston Lw Anqc-k-s How York Philadelphia Sacramento Salnl Louis WaslHn
i^|^8i^£S& 3*0*1
*My *W ^§fe *** vs*y i
s^: >*^t
r
g
o
o»
r^**=rNc
^^^-—^o^
v^vi ^^ a*»^c
^^^«v
S1 t
IT 3
I 8
II
JO-
BO -
eo -
ill ill ill ill ill ill ill ill ill ill ill ill ill ill
Year
Figure 8C-16. Annual medians of ozone concentrations at each monitor based on different
subsets of months.
Figure 8C-17 visually illustrates the process of forming and display a KDE from a year of
Os 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 Os
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
8C-17, where the color is related to the height of the curve in the middle panel.
8C-10
-------
1) Raw O3 Daily Data
oioo-
O
O 80-
'cc
•a 60-
!
i
Apt 1999
2) Kernel Density Estimate
Max 8-hr daily O3 Cone
3) Converting the KDE to a color stripe
Max 8-hr daily O3 Cone
O3 Prob
Dens
.
Figure 8C-17. Procedure for creating the display of Os distributions shown in Figure 8C-
18.
Each year of data shown in the groups in Figure 8C-16 was thus converted to a color-
based KDE as shown in Figure 8C-17, and the resulting collection of KDEs is shown in Figure
8C-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.
8C-11
-------
Boston Chieaqo Cleveland
.-; r-TrV Philadelphia Sacnamarilo Saint Louis
'"***
'"
'fv
: ;i:
iM ** -Mill Mil ' * IM ' • •
Trend
Chars
? 1 —Signil:Neg
E a
SignifiPos
InsignihNeg
" > lnsignif:Pos
'
Figure 8C-18. KDEs of groups of monitors' annual Os 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.
HREA chapter 8, section 8.2.3provided maps showing summertime (May-September)
ozone trends at specific monitor locations within two urban study areas. Here, we provide similar
maps for the other 13 urban study areas. In section 8.2.3 we also 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 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
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
8C-12
-------
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. See Figure 8C-19 through Figure 8C-30
for details.
Max4
Mean
Median
v
f
• Cnrtersville '*V
• Roswell
Marietta
trie
1 Cartersville
• Roswell,
Marietta
Atlanti
rie
Use in
Epi Studies
O Nol In Epi Study
@ Smith + Zano
O Zanobetli
Trend
Direction
Insignificant
V Negative
Figure 8C-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.
Max*
Mean
Median
Washngto
Alexandria
SI Charln
Use in
Epi Studies
O Not In Epi Study
O Zanobetli
Trend
Direction
Insignificant
V N«J.-lt:V.;
A Positive
Figure 8C-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.
8C-13
-------
Manchester
Manchester
Manchester
Leorr.nstor
/
Cambridgeji
•Woxester
•Worcester
Providence
Rrovidonce
Use in
Epi Studies
O Not In Epi Study
O Smith + Zano
O Zanobetli
Trend
Direction
Insignificant
V Negative
A Positive
Figure 8C-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.
8C-14
-------
Max4
Mean
Median
Use in
Epi Studies
O Not In Epi Study
O Smith + Zano
Trend
Direction
InsigniHcanl
V Negative
A Positive
Figure 8C-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 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
Fort Worth
Fort Worth
\
Fort Worth
Trend
Direction
Insignificant
V Negative
A Positive
Use in
Epi Studies
O Not In Epi Study
Figure 8C-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.
8C-15
-------
Max4
Mean
Median
•Gr
V
•Gr
Loveland
Longmont
• Boulder .
A^X, -\ x/
*
•Gr
Loveland
, y •
Lake woo
Use in
Epi Studies
O Not In Epi Study
O Smith
O Smith + Zano
Trend
Direction
Insignificant
V Negative
A Positive
Figure 8C-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
Mean
Median
• Ponliac
V'
jor
(£
_r~~\—\ vy~"
L--'T*Uvj7^^etroif
' - _pLbon/ V
Use in
Epi Studies
O Not In Epi Study
O Smith+ Zano
Trend
Direction
Insignificant
V Negative
Figure 8C-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.
8C-16
-------
Max4
Median
•Pasjden;
Sugat^and \
Use in
Epi Studies
O Not In Epi Study
O Smith + Zano
Trend
Direction
Insignificant
V Negative
A Positive
Figure 8C-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.
O Not In Epi Study
O Smith t Zano
Insignificanl
V Negative
A Positive
Figure 8C-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.
8C-17
-------
Max4
Median
Philadelphia^,
Philadelphia/^/
Use in
Ep! Studies
O Not In Epi Study
O Smith + Zano
Trend
Direction
Insignificant
V Negative
A Positive
Figure 8C-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 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.
VfYiito., C«y
Use in
Epi Studies
O Not In Epi Study
O Smith + Zano
Trend
Direction
Insignificant
V Negative
Figure 8C-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.
8C-18
-------
Max4
Median
gStaouis
• Bellt^ille.
^
,» St: Cartes.
x > i
Istaouls
• Belkvilte,
Use in
Epi Studies
O Not In Epi Study
® Smith * Zano
O Zanobetti
Trend
Direction
Insignificant
V Ne9ative
A Positive
Figure 8C-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, HREA Chapter 8 includes Table 8-8 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 8C-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.
8C-19
-------
Emission
(ton/yr)
1e+05
1e+04
1000
100
Figure 8C-31. Maps of NOX and VOC emissions by source sector for 2002, 2005, 2008, and
2011.
8C-20
-------
To analyze trends, emissions were spatially summed for each year and each sector across
the NOAA Climate Regions1 (shown in Figure 8C-32). The resulting trend lines for each sector
and emissions pollutant are shown in Figure 8C-33. For direct comparison to Os trends, the
ozone data from the urban 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
8C-34 and Figure 8C-35. The descriptors show in HREA Chapter 8 Table 8-8 of the main
document were derived from Figure 8C-33, Figure 8C-34, and Figure 8C-35.
Climate
Region
Central
EastNorthCentral
NorthEast
Northwest
South
SouthEast
Southwest
West
WestNorthCentral
Figure 8C-32. Map of nine NOAA climate regions that were used to aggregate emissions
and ambient ozone trends. Dots show locations of ozone monitors.
1 Climate regions are defined by NOAA's National Climate Data Center: http://www.ncdc.noaa.gov/monitoring-
references/maps/us-climate-regions.php
8C-21
-------
TIER1 DESCRIPTION
FUEL COMB IMDUSTRI*
WASTE DISPOSAL * RECYCLING
Figure 8C-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.
8C-22
-------
EMttMHMMl
Trend
Chars
— Signif:Neg
Signif:Pos
lnsignif:Neg
lnsignif:Pos
Year
Figure 8C-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, 50th, 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 urban study areas).
8C-23
-------
CastNoflhCenlral
Trend
Chars
— Signif:Neg
Signi(:Pos
InsignifiNeg
lnsignif:Pos
Year
Figure 8C-35. Distributions of high population density monitor 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, 50th, 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 urban study areas).
8C-2. MODELED OZONE CHANGES IN RESPONSE TO ACROSS THE BOARD
EMISSIONS REDUCTIONS
8C-2.1. Maps of Ratios of Mean Ozone from 2007 CMAQ Simulations including Emissions
Reductions to Mean Ozone from 2007 Base CMAQ Simulations.
In HREA Chapter 8 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
8C-24
-------
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. See Figure 8C-
36 through Figure 8C-47 for details.
0.4
0.6
1
0.8
1.0
1.2
1.4
ratio of seaonal mean ozone
Figure 8C-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.
8C-25
-------
0.4 0.6 0.8 1.0 1.2 1.4
ratio of seaonal mean ozone
Figure 8C-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 8C-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.
8C-26
-------
0.4 0.6 0.8 1.0 1.2 1.4
ratio of seaonal mean ozone
Figure 8C-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 1.4
ratio of seaonal mean ozone
Figure 8C-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.
8C-27
-------
0.4 0.6 0.8 1.0 1.2 1.4
ratio of seaonal mean ozone
Figure 8C-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 1.4
ratio of seaonal mean ozone
Figure 8C-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.
8C-28
-------
0.4 0.6 0.8 1.0 1.2 1.4
ratio of seaonal mean ozone
Figure 8C-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 8C-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.
8C-29
-------
0.4 0.6 0.8 1.0 1.2 1.4
ratio of seaonal mean ozone
Figure 8C-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 8C-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.
8C-30
-------
0.4 0.6 0.8 1.0 1.2 1.4
ratio of seaonal mean ozone
Figure 8C-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 8C-48 and Figure 8C-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 there 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.
8C-31
-------
NOxSOPer
NOxSOPer
NOxVOCSOPsr
NOxVOC90Per
25 50
75 100 25 50 75 100 25 50 75 100 25 50 75 100
Base O3 (ppb)
# Points
10000
5000
Figure 8C-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.
8C-32
-------
NOxSOPer
NOxSOPer
NOxVOCSOPer NOxVOCSOPer
I
.9
«
n
§ Population
• 1.56+07
16+07
5e+06
I.
•
I
Base Case O3 (ppb)
Figure 8C-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.
8C-33
-------
8C-2.2. Modeled Ozone Response Paired with Population Data
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 8C-50
through Figure 8C-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 HREA
chapter 8 show relative changes while the barplots in chapter 8 show absolute changes.
Figure 8C-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 an urban study area and for locations not in an urban
study area. Two regions, the Northwest and the West North Central regions, did not include any
urban 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 8C-51
shows the same information for the combined NOx and VOC reduction scenarios. Although there
are more total people living in non- urban study area locations than urban 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 8C-52 shows the same information for the 15 urban 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 8C-52 shows breakdowns by percentage of
urban study area population rather than by total population so that different urban study areas can
more easily be compared.
8C-34
-------
SoulhEaM S«rthWc-M SoulhWcM WeM
Figure 8C-50. 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 study area vs non-
urban study area, urban versus non-urban and 50% NOX reduction scenario vs 90% NOX
reduction scenario.
Study Area
Population
•• 1 e+08
1e+Q6
18+04
100
1
8C-35
-------
NtnrthEast HorthWi-st OhtoValk-y Oh ID Vn Iky South South
Study Area ShriyAr" Slwfy Af*n Stu^Arel Study Art
-------
% Study Area
Population
K 100
80
40
20
Figure 8C-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 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 urban
study areas together and all non- urban 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 8C-53 through Figure
8C-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 8C-1
provides the numbers going into the 50% NOx reduction and 90% NOx reduction histograms.
Table 8C-2 and Table 8C-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
urban study areas.
8C-37
-------
Non-Study Area
Study Area
40 -
20-
0-
g
IJ40
Q.
O
Q_
ID 20
0-
40 -
20
Ratio
Figure 8C-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 study areas while right plots show population
numbers in locations included in one of the urban 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.
8C-38
-------
Non-Study Area
Study Area
40 -
20
0
SO
c
g
JJ340
Q.
o
Q_
en
^ 20
5?
o
60
40 -
20
Ratio
Figure 8C-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 study areas while right
plots show population numbers in locations included in one of the urban 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.
8C-39
-------
Non-Study Area
Study Area
60
40-
20
0
60-
O
ro
"5 40
Q.
o
CL
CO
0-
40
20
Ratio
Figure 8C-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 study areas while right plots show population
numbers in locations included in one of the urban 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.
8C-40
-------
Non-Study Area
Study Area
60
20
0
g
CO
3 40
Q.
O
Q_
^> 20 -
0-
20 -
Ratio
Figure 8C-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 study areas while right
plots show population numbers in locations included in one of the urban 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.
8C-41
-------
Non-Study Area
Study Area
60
40-
20
o-
60
o
ZJ40
Q.
O
Q_
CO
3?
'20-
60
40 -
20 -
ppb change
Figure 8C-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 urban study areas while right plots show population numbers in
locations included in one of the urban 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.
8C-42
-------
Non-Study Area
Study Area
60
40 -
20
0-
60
O
"5 40
3.
o
Q_
CO
^> 20
40
20
ppb change
Figure 8C-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 urban study areas while right plots show population
numbers in locations included in one of the urban 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.
8C-43
-------
Non-Study Area
Study Area
60
40-
20
o-
60
O
Z!40
Q.
O
Q_
CO
3?
'20 -
60
40
20 -
ppb change
Figure 8C-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 urban study areas while right plots show population numbers in
locations included in one of the urban 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.
8C-44
-------
Non-Study Area
Study Area
60
40
20
0
O
340
Q.
O
Q_
t/3
3?
I 20
60
40
20
ppb change
Figure 8C-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 urban study areas while right plots show population
numbers in locations included in one of the urban 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.
8C-45
-------
Table 8C-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-
August
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
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
50% NOx Reduction
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
1.1
1.1
1.1
1.0
1.1
0.5
0.7
0.5
0.6
1.3
3.8
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
1.6
0.9
1.1
0.9
0.7
0.6
0.5
0.5
0.4
0.4
5.0
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
2.7
1.9
2.1
1.8
1.8
1.1
1.2
0.9
1.0
1.7
8.8
90% NOx Reduction
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
0.1
0.0
0.0
0.0
0.0
0.1
0.1
0.0
0.0
0.1
1.2
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
0.3
0.3
0.3
0.2
0.2
0.3
0.2
0.0
0.2
0.0
2.4
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
0.4
0.3
0.4
0.2
0.2
0.4
0.3
0.1
0.2
0.2
3.7
8C-46
-------
Table 8C-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 reduction
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
>1.05
50% NOx Reduction
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
0.3
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
1.7
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
2.0
90% NOx Reduction
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
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
0.8
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
0.9
8C-47
-------
Table 8C-3. Percentage of U.S. 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 urban 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
Sacramento
St. Louis
Washington
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
0.7
0.9
1.8
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
0.0
0.0
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
0.0
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
0.0
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
0.0
0.0
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
0.0
0.0
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
0.0
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
0.0
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
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
0.0
0.0
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
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
0.0
0.0
0.0
8C-48
-------
APPENDIX 9A
Figures Summarizing Exposure and Lung-Function Risk Estimates
for Sub-Regions of Each Study Area (Urban Core, Outer Ring,
and Total Exposure Region)
List of Figures
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) 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) 9A-4
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) 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) 9A-6
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) 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) 9A-8
Figure 9A-7. 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) (Houston) 9A-9
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) 9A-10
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) 9A-11
Figure 9A-10. 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) (Philadelphia) 9A-12
Figure 9A-11. 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) (Sacramento) 9A-13
9A-i
-------
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) 9A-14
Figure 9A-13. Lung-Function Risk Estimates - Percent of Person with Specified FEVi
Decrement. (Spatially stratified: all study area, urban study area, outer study area)
(Atlanta) 9A-15
Figure 9A-14. Lung-Function Risk Estimates - Percent of Person with Specified FEVi
Decrement. (Spatially stratified: all study area, urban study area, outer study area)
(Baltimore) 9A-16
Figure 9A-15. Lung-Function Risk Estimates - Percent of Person with Specified FEVi
Decrement. (Spatially stratified: all study area, urban study area, outer study area)
(Boston) 9A-17
Figure 9A-16. Lung-Function Risk Estimates - Percent of Person with Specified FEVi
Decrement. (Spatially stratified: all study area, urban study area, outer study area)
(Cleveland) 9A-18
Figure 9A-17. Lung-Function Risk Estimates - Percent of Person with Specified FEVi
Decrement. (Spatially stratified: all study area, urban study area, outer study area)
(Denver) 9A-19
Figure 9A-18. Lung-Function Risk Estimates - Percent of Person with Specified FEVi
Decrement. (Spatially stratified: all study area, urban study area, outer study area)
(Detroit) 9A-20
Figure 9A-19. Lung-Function Risk Estimates - Percent of Person with Specified FEVi
Decrement. (Spatially stratified: all study area, urban study area, outer study area)
(Houston) 9A-21
Figure 9A-20. Lung-Function Risk Estimates - Percent of Person with Specified FEVi
Decrement. (Spatially stratified: all study area, urban study area, outer study area)
(Los Angeles) 9A-22
Figure 9A-21. Lung-Function Risk Estimates - Percent of Person with Specified FEVi
Decrement. (Spatially stratified: all study area, urban study area, outer study area)
(New York) 9A-23
Figure 9A-22. Lung-Function Risk Estimates - Percent of Person with Specified FEVi
Decrement. (Spatially stratified: all study area, urban study area, outer study area)
(Philadelphia) 9A-24
Figure 9A-23. Lung-Function Risk Estimates - Percent of Person with Specified FEVi
Decrement. (Spatially stratified: all study area, urban study area, outer study area)
(Sacramento) 9A-25
Figure 9A-24. Lung-Function Risk Estimates - Percent of Person with Specified FEVi
Decrement. (Spatially stratified: all study area, urban study area, outer study area)
(St. Louis) 9A-26
9A-ii
-------
OVERVIEW
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 exposure model urban 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 FEVi 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 FEVi 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 FEVi 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,
for example, exposure estimates (based on the 60 ppb benchmark) for the urban core between
9A-1
-------
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
FEVi 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 FEVI 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
-------
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9A-3
-------
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9A-4
-------
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1
= ji -g = .a -5
ro ^- — ' ro ^- — '
=5 0 =5
0
Figure 9A-7. 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) (Houston).
9A-9
-------
Los Angeles: percent
9> i uu %
0)
•^ nno/
g yU% • ;
ro
Oono/
oU% • ;
13
in !
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»- /Uvo
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Q.
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>> 60% - -
3
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m
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=! 0
o o o c
1 1 1
in in m c
i^ i^ i^ i^
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1
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)
1
)
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00 00 00 00' 00'
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1 1 1
1
1
IB -e => IB -e
=! 0
!
o o o o c
1 1 1
O 0> 0> (U IT
^i S§ S§ S§ ^
) O O C
1 1
) in m c
. h. i^ |v.
o o
1 1 1
0 0
1 ^1 ^1
OO _& _& £} CO' CO CO' CO' CO' CO'
^~ i i ^~ ^~ ^~ ^~ ^~ ^~
CO 00 00 00 CO. CO. CO. CO. CO. CO.
1 ^" ^" ^"
1 . .1
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-^11 OJ i- ^ OJ i- ^
0 — o -^
IB -e =>
=! 0
=! 0
=! 0
tracts_studyarea_AQscenario_year
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).
9 A-10
-------
100%
s
o
.a
ro
O
ro
-------
o> 1 00% ;
V
> 90% -
ro
i_
o 80% •
4-1
ro
3
O
g 60% •
| 50% •
O)
| 40% -
01
g_ 30% •
X
01
c 20% -
o
i_
01
f- 10% -
15
-i
°l °l
0 0
ro ro
.Q -Q
oo1 oo1
CM CM
l' -§'
Philadelphia: percent of persons, 1-hour exposures
~
°'
in
ro
«'
CM
•5
O
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I
I
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-' -o' ^'
ro -§ g o
=' €'
I
1
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1
5, 8, 8, 8
D
-------
Sacramento: percent of persons, 1-hour exposures
o> 1 00% ~
01
01
g ao%
.Q
to
oO% •
4-1
to
| 70% •
o
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tracts_studyarea_AQscenario_year
Figure 9A-11. 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) (Sacramento).
9 A-13
-------
St Louis: percent of persons, 1 -hour exposures
a 100% -r
.2
ai
> 90% -:
st
ra
o 80% •'•
ra
| 70% -•
o
Q.
x 60% ••
01
2
5 50% •'•
I 40% - ;
c
01
g_ 30% •;
X
01
c 20% -:
o
S2 :
ai
f- 10% •;
15
^ 0% -P
1
•
1
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1
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n
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I
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1
k
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k
d N_MaxO3_60
• N_MaxO3_70
DN MaxOS 80
D N_MaxO3_90
• N_MaxO3_100 -
n
•
I • m j
1 1 1 1
1
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1
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I
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r*^ r*^ r*^ r^ i^ i1^ r^ r^ i1^ 05 05 05 05 05 05 05 05 05
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1
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^— i i i ro ^— ro ~
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tracts_studyarea_AQscenario_year
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).
9 A-14
-------
Atlanta: percent of persons, dFEV1
- 12.0%
tracts_studyarea_AQscenario_year
Figure 9A-13. Lung-Function Risk Estimates - Percent of Person with Specified FEVi Decrement. (Spatially stratified: all
study area, urban study area, outer study area) (Atlanta).
9 A-15
-------
Baltimore: percent of persons, dFEV1
tracts_studyarea_AQscenario_year
Figure 9A-14. Lung-Function Risk Estimates - Percent of Person with Specified FEVi Decrement. (Spatially stratified: all
study area, urban study area, outer study area) (Baltimore).
9 A-16
-------
Boston: percent of persons, dFEV1
tracts_studyarea_AQscenario_year
Figure 9A-15. Lung-Function Risk Estimates - Percent of Person with Specified FEVi Decrement. (Spatially stratified: all
study area, urban study area, outer study area) (Boston).
9 A-17
-------
Cleveland: percent of persons, dFEV1
£ 7.5%
™ 3.5% -:
c
| 3.0% --
§_ 2.5% •:
^ 2.0% •-
tracts_studyarea_AQscenario_year
Figure 9A-16. Lung-Function Risk Estimates - Percent of Person with Specified FEVi Decrement. (Spatially stratified: all
study area, urban study area, outer study area) (Cleveland).
9 A-18
-------
Denver: percent of persons, dFEV1
O> -'•"'"
o 2.5%
v
'= 2.0%
5
n n
n
ni\l_CdFEV10
• N_CdFEV15
DN CdFEV20
Hi~~H
n
(i
i
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(/)
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tracts_studyarea_AQscenario_year
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Cxi
Figure 9A-17. Lung-Function Risk Estimates - Percent of Person with Specified FEVi Decrement. (Spatially stratified: all
study area, urban study area, outer study area) (Denver).
9 A-19
-------
§ 8.5%
E
S! 8.0% - —
o
•§ 7.5% -•
53 7.0% --
| 6.5% -:
o 6.0% -•
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ai
o 5.0% --
4->
| 4.5% -:
13 40o/o
O)
I 3.5% -:
c
I 3-0% ~
g 2.5% -:
5 1.5% f
^ 1.0% f
| 0.5% f
£> 0.0%
ro
Detroit: percent of persons, dFEV1
ro
o
CM
I
i
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ro
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ro
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ro
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ro
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tracts_studyarea_AQscenario_year
Figure 9A-18. Lung-Function Risk Estimates - Percent of Person with Specified FEVi Decrement. (Spatially stratified: all
study area, urban study area, outer study area) (Detroit).
9A-20
-------
•£ 7.5%
| 7.0% -
| 6.5% -
> 6.0% -
LLJ
£ 5.5% -
jj 5.0% -
I 4.5% -
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ro 3.0% -
O>
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o
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8
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£ 1.0% •
5 0.5% •
Q.
= 0.0% -
;
-
r
•
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:
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'r
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•£ a
Houston: percent of persons, dFEV1
-
i
...
-
1
r-
c
0.
...
...
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—
-
g ro S§
m
Q. 00
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1^1 1 1 „! oo
-e "3 TO -e "3
-------
Los Angeles: percent of persons, dFEV1
8.
t racts_studya rea_AQscena rio_yea r
Figure 9A-20. Lung-Function Risk Estimates - Percent of Person with Specified FEVi Decrement. (Spatially stratified: all
study area, urban study area, outer study area) (Los Angeles).
9A-22
-------
I 8.0% •
-- 7.5% •
o
% 7.0% -
LLI R f^O/
£ b.b%
1 6.0% -
CO
£ 5.5% •
a 5.0% -
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;; 4.0% -
f 3.5% •
§ 3.0% -
g- 2.5% •
o>
g 2.0% •
o
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i
New York: percent of persons, dFEV1
^^^^^^^^^^^^^^^^
E
zi_z_z:_z_zt._iz
.M 1 • I
II
llh ^ i, \\i 1 J!
"
i i i i i i i i
o o o o o o o o c
1 1 1 1 1
in in m o o o CD CD CD
h. h. 1^. [s. [s. [s. (/) (/) (/
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—
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F
—
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i
CdFEVIO
CdFEV15
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...
—
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—
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i i i
in in m
[s. [s. [s.
1 1 1
co oo oo
OOOOOO I OOO
•^•^•^••sr^'^-oooooo'sr'^'^-
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ro=!0ro=!0 — n^ro=!0
m "tr ^
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tracts_studyarea_AQscenario_year
D
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F
1
8
1
0
1
oo
=!
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r
8
0
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J
0
Figure 9A-21. Lung-Function Risk Estimates - Percent of Person with Specified FEVi Decrement. (Spatially stratified: all
study area, urban study area, outer study area) (New York).
9A-23
-------
Philadelphia: percent of persons, dFEV1
1 9.5%
| 9.0%
| 8.5%
> 8.0%
UJ
£ 7'5%
1 7.0%
=o 6.5%
0 6.0%
° 5.5%
jjj 5.0%
« 4.5% r
O)
•| 4.0% --
| 3.5% -:
| 3.0%
J 2.5%
| 2.0%
I 1.5%
ra 1.0%
•2 0.5%
S 0.0%
01
Q.
1
ro
1
1
co
CM
-e
oo
CM
CM
U)
ro
-e
ro
co
CM
ro
CM
O)
-e
8. 8
in
CM
S
1^
-e
tracts_studyarea_AQscenario_year
Figure 9A-22. Lung-Function Risk Estimates - Percent of Person with Specified FEVi Decrement. (Spatially stratified: all
study area, urban study area, outer study area) (Philadelphia).
9A-24
-------
Sacramento: percent of persons, dFEV1
tracts_studyarea_AQscenario_year
Figure 9A-23. Lung-Function Risk Estimates - Percent of Person with Specified FEVi Decrement. (Spatially stratified: all
study area, urban study area, outer study area) (Sacramento).
9A-25
-------
St Louis: percent of persons, dFEV1
tracts_studyarea_AQscenario_year
Figure 9A-24. Lung-Function Risk Estimates - Percent of Person with Specified FEVi Decrement. (Spatially stratified: all
study area, urban study area, outer study area) (St. Louis).
9A-26
-------
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9A-27
-------
United States Office of Air Quality Planning and Standards Publication No. EPA-452/R-14-004e
Environmental Protection Health and Environmental Impacts Division August 2014
Agency Research Triangle Park, NC
------- |