United States Office of Air Quality EPA 454/R-01-004
Environmental Protection Planning and Standards March 2001
Agency Research Triangle Park NC 27711
Air
&EPA National Air Quality and
Emissions Trends Report, 1999
1999 Annual Mean PM25 Concentrations (|jg/m3)
c§
• SQ£P—° Q
^ rO ri st
Q
Oftd. ££> o Q
Puerto Rico
Alaska
Hawaii
Data Completeness
o <4 quarters
O One or more quarters with <11 samples
O All quarters with at least 11 samples
O All quarters 75% or more complete
Concentration (iig/m3)
# >20
O 15-20
# 10-15
# 0-10
Source: US EPA AIRS Data base as of 7/12/00 without data flaggod as 1,2,3,4, T, W, Y, or X.
-------
-------
United States
Environmental Protection
Agency
Office of Air Quality
Planning and Standards
Research Triangle Park NC 27711
EPA 454/R-01 -004
March 2001
&EPA Errata for:
National Air
Emissions
Revised Janua
Page ii:
Change date in "Data Source: U.S. EPA AIRS Data Base
1/30/01"to"7/12/00."
Page 21, Figure 2-13:
Add new legend to map.
Page 44, Figure 2-41:
Figure re-plotted using the major categories within the
Miscellaneous category (instead of "Miscellaneous").
Page 52, Figure 2-51:
Replaced with new map.
Page 59, Figure 2-60:
Figure re-plotted using the major categories within
Miscellaneous (instead of Miscellaneous).
Page 237
Notes added on "Data Sources for Figure 2-55."
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
About the Cover
The map on the cover depicts nationwide annual mean PM2 5 concentra-
tions from the Federal Reference Method (FRM) monitoring network, as
well as information on data completeness. Annual mean concentrations
are generally above the level of the 1997 standard of 15 jig/m3 in much of
the eastern United States and throughout California. Annual mean con-
centrations above 20 jig/m3 are seen in several major metropolitan areas
including Pittsburgh, Cleveland, Atlanta, Chicago, and St. Louis and Los
Angeles The western Great Plains and mountain regions show notably
low annual mean concentrations, most below 10 jjg/m3.
Data Source: U.S. EPA AIRS Data Base 7/12/00.
Disclaimer
This report has been reviewed and approved for publication by the U.S.
Environmental Protection Agency's Office of Air Quality Planning and
Standards. Mention of trade names or commercial products are not intended
to constitute endorsement or recommendation for use.
Acknowledgments
The Trends Team would like to acknowledge the members of EPA's Office of
Research and Development, Office of Atmospheric Programs, Office of
Radiation and Indoor Air and Office of Transportation and Air Quality for
peer reviewing this report prior to publication; Support for the statistical
analyses of air toxics trends provided under EPA contract 68D70066;
Colorado State University for providing summary data from the
IMPROVE monitoring network; Support for desktop publishing and Web
site development provided under EPA contract 68W99004; and the Trends
Workgroup in EPA's Office of Air Quality Planning and Standards for
providing comments throughout report development.
2
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 2-13. Pb maximum quarterly concentration in the vicinity of Pb point sources, 1999.
Rank
ST
MO
Emission Source
Doe Run (Herculeneum)
Chemetco
Max. Qtr. Avg. (ug/m3)
6.75
Z5
• Exceeds the NAAQS
• Meets the NAAQS
Figure 2-14. Highest
180 "
170 "
160 "
150
140 "
130 "
120"
M
I no-
li
c 100-
Concentration (ug/m3) <0.75 0.75-1.54 1.55-3.04 >=6.05
Pb maximum quarterly mean by county, 1999
CHAPTER 2 • CRITERIA POLLUTANTS —NATIONAL TRENDS 21
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 2-41. Total PM10 emissions by source category, 1999.
Agriculture and Forestry
r 20.6%
J \ Traditionally Inventoried Sources
~_ "
Other Combustion
\ 43%
Fugitive Dust
62.2% ""
ried sources, shown in Figures 2-39
and 2-40. These include fuel combus-
tion, industrial processes, and trans-
portation. Of these, the fuel
combustion category saw the largest
decrease over the 10-year period (14
percent), with most of the decline
attributable to a decrease in emissions
from electric utility coal and oil com-
bustion. Emissions from the industri-
al processes category decreased 3
percent, and emissions from the
transportation category decreased
10 percent. The recent upward move-
ment between 1998 and 1999 for in-
dustrial processing is attributed to
new sources of emissions for open
burning (of residential yard wastes
and land clearing debris) that had not
been characterized previously.
The second group of direct PM10
emissions is a combination of miscel-
laneous and natural sources includ-
ing agriculture and forestry, wildfires
and managed burning, and fugitive
dust from paved and unpaved roads.
It should be noted that fugitive dust
emissions from geogenic wind ero-
sion have been removed from the
emissions inventory for all years,
since the annual emission estimates
based on past methods for this cat-
egory are not believed to be represen-
tative. As Figure 2-41 shows, these
miscellaneous and natural sources
actually account for a large percent-
age of the total direct PM10 emissions
nationwide, although they can be
difficult to quantify compared to the
traditionally inventoried sources.
The trend of emissions in the miscel-
laneous/natural group may be more
uncertain from one year to the next or
over several years because these
emissions tend to fluctuate a great
deal from year to year. It should be
noted that a change in methodology
occurred between 1995 and 1996 in
calculating PM10 emissions from
unpaved roads. This has led to lower
PMio emissions from 1996 through
1999 than would have been predicted
using the older methodology.
Table A-6 lists PM10 emissions
estimates for the traditionally inven-
toried sources for 1990-1999. Miscel-
laneous and natural source PM10
emissions estimates are provided in
Table A-7.
Figure 2-42 shows the emission
density for PM10 in each U.S. county.
PMio emission density is the highest
in the eastern half of the United
States, in large metropolitan areas,
areas with a high concentration of
agriculture such as the San Joaquin
Valley in California and along the
Pacific coast. This closely follows
patterns in population density. One
exception is that open biomass burn-
ing is an important source category
that is more prevalent in forested
areas and in some agricultural areas.
Fugitive dust is an important compo-
nent in arid and agricultural areas.
PM10 Regional Air Quality Trends
Figure 2-43 is a map of regional
trends for the PM10 annual mean
from 1990-1999. All 10 EPA regions
show decreasing trends over the
10-year period, with declines ranging
from 5-33 percent. The largest de-
creases are generally seen in the west-
ern part of the United States. This is
significant since PM10 concentrations
are typically higher in the West. In
the western states, programs such as
those with residential wood stoves
and agricultural practices have
helped reduce emissions of PM10. In
the eastern United States, the Clean
Air Act's Acid Rain Program has
contributed to the decrease in PM10
emissions. The program has reduced
44
CRITERIA POLLUTANTS —NATIONAL TRENDS • CHAPTER 2
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 2-51. Annual mean PM25 concentrations in 1999.
4.2
6.2
® 3.4
3.0
3.0
6.5
7.0
5.2
2.8
3.2
,7.1
7.2
3.0
x
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 2-60. Total direct PM2.5 emissions by source category, 1999. PM10_2.5 concentrations. Though the
Southeast data is relatively incom-
plete, preliminary estimates suggest
relatively low PM10_2.5 levels through-
out that region.
Figure 2-61. National ammonia emissions by principal source categories, 1999.
Waste Disposal & Recycling
Chemical & Allied
Product Manufacturing
All Other 2.9%
1.8%
2.7%
Onroad &
I Nonroad Engineering
5.4%
Miscellaneous
(Includes livestock
& fertilzer)
87.2%
Agriculture & Forest
14.0%
Other Combustion
12.9%
Traditionally Invent
34.3%
Fugitive Dust
38.9%
59 CRITERIA POLLUTANTS —NATIONAL TRENDS • CHAPTER 2
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
the 1997 annual average. Other-
wise, any missing annual averages
were filled in using simple linear
interpolation from the two surround-
ing annual averages.
Notes on Data Sources for
Figure 2-55
Composition and concentration data
for all non urban locations were ob-
tained from the Interagency Monitor-
ing of Protected Visual Environments
(IMPROVE). Washington, D.C. and
Seattle data were also obtained from
IMPROVE [Reference: IMPROVE,
Cooperative Center for Research in
the Atmosphere, Colorado State Uni-
versity, Ft. Collins, CO, May 2000].
and the Rochester data are based on a
study conducted for NESCAUM.
[Reference: Salmon, Lynn and Glen
R. Cass, October, 1997, Progress Re-
port to NESCAUM: Determination of
Fine Particle Contraction and Chemi-
cal Composition in the Northeastern
United States, 1995, California Insti-
tute of Technology, Pasadena, CA
91125.] The South Coast information
is adapted from data collected in the
South Coast area since 1982. [Refer-
ence: Christoforou, C.S., Lynn G.
Salmon, Michael P. Hannigan, Paul A.
Soloman and Glen R. Cass, Trends in
Fine Particle Concentration and
Chemical Composition. Journal of
Air and Waste Management Associa-
tion, Pittsburgh, PA. January 2000.]
The Phoenix data is from a report by
ENSR, "Plots and Tables to Character-
ize Particulate Matter in Phoenix,
Arizona," prepared for the Arizona
Department of Environmental Quali-
ty, ENSR Document 0493-018-8, No-
vember 1999. The San Joaquin data
are from Desert Research Institute
[Reference: PM10 and PM2.5 Variations
in Time and Space, Desert Research
Institute, Reno, NV, October 1995. ].
Knoxville data was provided by the
Tennessee Valley Authority. [Refer-
ence: (a) Tanner, R. (Tennessee Valley
Authority) Personal Communication
with T.G. Pace, January, 1998.] The
El Paso and Dallas data were report-
ed as a part of the Texas PM2.5 Sam-
pling and Analysis Study, Desert
Research Institute, December, 1998.
The Denver data was collected under
the Northern Front Range Air Quality
Study (NFRAQS). [Reference:
NFRAQS Final Report, Desert Re-
search Institute, Reno NV, June 1998.
Note that this compositional data is
the average of winter and summer
sampling seasons; thus, no annual
average is reported. The New Haven
data was provided to Scott Mathias in
a personal communication from John
Graham, Connecticut Department of
Environmental Protection, Bureau of
Air Management August 16,2000.
Non urban data are based on aver-
ages of several monitoring locations
in the region. Urban data are mainly
based on only one location in each
area and may not represent the entire
urban area. The exceptions to this are
the South Coast and San Joaquin
Valley areas of California where mul-
tiple locations are averaged together.
In the South Coast basin, Rubidoux
recorded the highest average PM25
and nitrate concentrations. Addi-
tional information on the composition
of PM2.5 within these areas of Califor-
nia is discussed further in
Christoforou (above) and DRI [Refer-
ence: PM10 and PM2 5 Variations in
Time and Space, Desert Research
Institute, Reno, NV, October 1995. ]
References
1. Clean Air Act Amendments of
1990, U.S. Code, volume 42, section
7403 (c)(2), 1990.
2. Ambient Air Quality Surveillance,
44 CFR 27558, May 10, 1979.
3. Aerometric Information Retrieval
System (AIRS), Volume 2, U.S. Envi-
ronmental Protection Agency, Office of
Air Quality Planning and Standards,
Research Triangle Park, NC, October,
1993.
4. Falke, S. and Husar, R. (1998) Cor-
rection of Particulate Matter Concen-
trations to Reference Temperature and
Pressure Conditions, Paper Number
98-A920, Air & Waste Management
Association Annual Meeting, San Di-
ego, CA, June 1998.
5. Ambient Air Quality Surveillance,
51 FR 9597, March 19, 1986.
6. U.S. Environmental Protection
Agency Intra-Agency Task Force Re-
port on Air Quality Indicators,
EPA-450/4-81-015, U.S. Environmental
Protection Agency, Office of Air Quali-
ty Planning and Standards, Research
Triangle Park, NC, February 1981.
7. Rosenbaum, A. S., Stiefer, M. P.,
and Iwamiya, R. k. November, 1999.
Air Toxics Data Archive and AIRS Com-
bined Dataset: Contents Summary Report.
SYSAPP-99/26d. Systems Applications
International, San Rafael, CA.
8. In all cases analyzed, four non-
missing quarterly means were avail-
able after applying the GLM method,
so that the resulting annual mean is
the arithmetic mean of the four quar-
terly averages.
9. Cohen, J.P. and A. K. Pollack. 1990.
General Linear Models Approach to Esti-
mating National Air Quality Trends As-
suming Different Regional Trends.
SYSAPP-90/102. Systems Applications
International, San Rafael, CA.
APPENDIX B • AIRS METHODOLOGY
237
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EPA 454/R-01-004
National Air Quality and
Emissions Trends Report,
1999
U.S. Environmental Protection Agency
Office of Air Quality Planning and Standards
Emissions Monitoring and Analysis Division
Air Quality Trends Analysis Group
Research Triangle Park, North Carolina 27711
March 2001
Printed on recycled paper.
-------
About the Cover
The map on the cover depicts nationwide annual mean PM2 5 concentra-
tions from the Federal Reference Method (FRM) monitoring network, as
well as information on data completeness. Annual mean concentrations
are generally above the level of the 1997 standard of 15 ]iig/m3 in much of
the eastern United States and throughout California. Annual mean con-
centrations above 20 ]Lig/m3 are seen in several major metropolitan areas
including Pittsburgh, Cleveland, Atlanta, Chicago, and St. Louis and Los
Angeles The western Great Plains and mountain regions show notably
low annual mean concentrations, most below 10 ]Ug/m3.
Data Source: U.S. EPA AIRS Data Base 1/30/01.
Disclaimer
This report has been reviewed and approved for publication by the U.S.
Environmental Protection Agency's Office of Air Quality Planning and
Standards. Mention of trade names or commercial products are not intended
to constitute endorsement or recommendation for use.
Acknowledgments
The Trends Team would like to acknowledge the members of EPA's Office of
Research and Development, Office of Atmospheric Programs, Office of
Radiation and Indoor Air and Office of Transportation and Air Quality for
peer reviewing this report prior to publication; Support for the statistical
analyses of air toxics trends provided under EPA contract 68D70066;
Colorado State University for providing summary data from the
IMPROVE monitoring network; Support for desktop publishing and Web
site development provided under EPA contract 68W99004; and the Trends
Workgroup in EPA's Office of Air Quality Planning and Standards for
providing comments throughout report development.
-------
Preface
This is the 27th annual report on air pollution trends in the United
States issued by the U.S. Environmental Protection Agency. The
report is prepared by the Air Quality Trends Analysis Group
(AQTAG) in Research Triangle Park, North Carolina and is directed
toward both the technical air pollution audience and other interest-
ed parties and individuals.
The report can be accessed via the Internet at http://www.epa.gov/
airtrends/. AQTAG solicits comments on this report and welcomes
suggestions regarding techniques, interpretations, conclusions, or
methods of presentation. Comments can be submitted via the web-
site or mailed to:
Attn: Trends Team
AQTAG (MD-14)
U.S. EPA
Research Triangle Park, NC 27711
Readers can access data from the Aerometric Information Retrieval
System (AIRS) at http://www.epa.gov/airsdata/ and real time air
pollution data at http://www.epa.gov/airnow/.
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IV
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Contents
Chapter 1
Executive Summary 1
Chapter 2 2
Chapter 3 2
Chapter 4 3
Chapter 5 3
Chapter 6 4
Chapter 7 6
References and Notes 7
Chapter 2
Criteria Pollutants — National Trends 9
Carbon Monoxide 11
Lead 17
Nitrogen Dioxide 23
Ozone 29
Particulate Matter 40
Sulfur Dioxide 61
References 67
Chapter 3
Criteria Pollutants — Metropolitan Area Trends 69
Status: 1999 69
Trends Analysis 70
The Air Quality Index 70
Summary of AQI Analyses 72
References and Notes 74
Chapter 4
Criteria Pollutants — Nonattainment Areas 75
V
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Chapter 5
Air Toxics 79
Background 79
Health and Environmental Effects 79
National Air Toxics Control Program 80
Air Toxics Emissions in 1996 82
Trends in Air Toxics Emissions 84
Ambient Monitoring 84
Trends In Ambient Concentrations 85
National Atmospheric Deposition Program/Mercury Deposition Network 96
Integrated Atmospheric Deposition Network 96
References 97
Chapter 6
Visibility Trends 99
Introduction 99
Nature and Sources of the Problem 100
Long-Term Trends (1981-1995) 102
Recent Trends (1990-1999) from IMPROVE Data 103
Regional Visibility Trends for the Eastern and Western United States 104
The Components of PM Contributing to Trends in Visibility Impairment 105
Current Visibility Conditions 109
Programs to Improve Visibility 113
References 114
Chapter 7
Atmospheric Deposition of Sulfur and Nitrogen Compounds 115
Primary Atmospheric Deposition Monitoring Networks 116
National Atmospheric Deposition Network/National Trends Network 116
Trends Analyses for Sulfate and Nitrogen Concentrations in Wet Deposition 117
Clean Air Status and Trends Network 118
Dry Deposition 119
Concentration Trends Analysis at CASTNet Sites 119
Seasonal Trends in S02 Emissions and Related Air Quality 122
Sulfur and Nitrogen Deposition 124
References 125
Appendix A
Data Tables 127
Appendix B
Methodology 229
AIRS Methodology 229
Emissions Estimates Methodology 233
IMPROVE Methodology 234
Air Toxics Methodology 234
References 237
VI
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Figures
Figure 2-1. Trend in 2nd maximum non-overlapping 8-hour average CO concentrations, 1980-1999 11
Figure 2-2. Trend in 2nd maximum non-overlapping 8-hour average CO concentrations by type of location, 1980-1999 12
Figure 2-3. Trend in CO 2nd maximum non-overlapping 8-hour concentrations by EPA region, 1980-1999 12
Figure 2-4. CO emissions by source category, 1999 13
Figure 2-5. Density map of 1999 carbon monoxide emissions, by county. 13
Figure 2-6. Trend in national total CO emissions, 1980-1999 14
Figure 2-7. Highest 2nd maximum non-overlapping 8-hour average CO concentration by county, 1999 15
Figure 2-8. Trend in maximum quarterly average Pb concentrations (excluding point-source oriented sites), 1980-1999 18
Figure 2-9. Pb maximum quarterly mean concentration trends by location (excluding point-source oriented sites), 1980-1999 18
Figure 2-10. Trend in Pb maximum quarterly mean concentration by EPA region, 1980-1999 19
Figure 2-11. National total Pb emissions trend, 1980-1999 20
Figure 2-12. Pb emissions by source category, 1999 20
Figure 2-13. Pb maximum quarterly concentration in the vicinity of Pb point sources, 1999 21
Figure 2-14. Highest Pb maximum quarterly mean by county, 1999 21
Figure 2-15. Trend in annual N02 mean concentrations, 1980-1999 24
Figure 2-16. Trend in annual mean N02 concentrations by type of location, 1980-1999 24
Figure 2-17. Trend in N02 maximum quarterly mean concentration by EPA region, 1980-1999 25
Figure 2-18. Trend in national total NOx emissions, 1980-1999 26
Figure 2-19. NOx emissions by source category, 1999 26
Figure 2-20. Density map of 1999 nitrogen dioxide emissions, by county. 27
Figure 2-21. Highest N02 annual mean concentration by county, 1999 28
Figure 2-22. Trend in annual 2nd-highest daily maximum 1-hour, and 4th-highest daily 8-hour 03 concentrations, 1980-1999 30
Figure 2-23. Trend in 4th-highest daily 8-hour 03 concentrations, 1980-1999 31
Figure 2-24. Trend in 2nd highest daily 1-hour 03 concentration by EPA region, 1980-1999 32
Figure 2-25. Trend in 4th highest daily 8-hour 03 concentration by EPA region, 1980-1999 32
Figure 2-26. Trend in annual 2nd-highest daily maximum 1-hour 03 concentrations by location, 1980-1999 33
Figure 2-27. Comparison of actual and meteorologically adjusted 1-hour 03 trends, 1980-1999 33
Figure 2-28. Areas with PAMS networks 34
Figure 2-29. A comparison of the median change in summer morning concentrations of the most abundant VOC species measured
at all PAMS sites and PAMS type 2 sites from 1995 and 1999 34
Figure 2-30. Trend in 4th-highest daily 8-hour 03 based on 34 CAST Net sites in the rural eastern United States, 1980-1999 35
Figure 2-31. Trend in annual 4th-highest daily maximum 8-hour 03 concentrations in National Parks, 1980-1999 35
Figure 2-32. Trend in national total anthropogenic VOC emissions, 1980-1999 36
Figure 2-33. Anthropogenic VOC emissions by source category, 1999 36
Figure 2-34. Density map of 1999 VOC emissions, by county. 38
Figure 2-35. Highest second daily maximum 1-hour 03 concentration by county, 1999 38
Figure 2-36. Highest fourth daily maximum 8-hour 03 concentration by county, 1999 39
Figure 2-37. Trend in annual mean PM10 concentrations, 1990-1999 42
Figure 2-38. PM10 annual mean concentration trends by location, 1990-1999 42
Figure 2-39. National PM10 emissions trend, 1980-1999 (traditionally inventoried sources only) 43
Figure 2-40. PM10 emissions from traditionally inventoried source categories, 1999 43
VII
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44
45
45
46
47
48
48
49
50
51
52
52
53
53
55
56
57
58
58
59
59
60
60
62
62
63
63
64
65
65
66
72
73
73
75
76
82
82
83
84
84
85
86
88
88
89
89
90
90
92
Total PM10 emissions by source category, 1999
PMW emissions density by county 1999
Trend in PM10 annual mean concentration by EPA region, 1990-1999
Highest 2nd maximum 24-hour PM10 concentration by county, 1999
Status of PM2 5 monitor network, as of May 2001
1999 annual mean PM25 concentrations (jig/m3)
1999 98th percentile 24-hour average PM25 concentrations (jig/m3)
Urban PM25 monthly patterns by region, 1999
Rural PM2 5 monthly patterns by region, 1999
Class I Areas in the IMPROVE Network meeting the data completeness criteria in Appendix B
Annual mean PM25 concentrations in 1999
PM2 5 concentrations, 1992-1999 at eastern IMPROVE sites meeting trends criteria
PM2 5 concentrations, 1990-1999 at western IMPROVE sites meeting trends criteria
PM25 concentrations, 1990-1999 at the Washington D.C. IMPROVE site
PM2 5 ambient composition
PM2 5 emission sources
Direct PM25 emissions density by county, 1999
National direct PM25 emissions trend, 1990-1999 (traditionally inventoried sources only)
Direct PM2 5 emissions from traditionally inventoried source categories, 1999
Total direct PM2 5 emissions by source category, 1999
National ammonia emissions by principle source categories, 1999
Estimated 1999 annual mean PM10-2.5
Estimated 1999 98th percentile 24-hour average PM10-2.5 developed from 1999 FRM monitor data
Trend in annual mean S02 concentrations, 1980-1999
Annual mean S02 concentration by trend location, 1980-1999
National total S02 emissions trend, 1980-1999
S02 emissions by source category, 1999
Long-term ambient S02 trend, 1980-1999
Trend in S02 annual arithmetic mean concentration by EPA region, 1980-1999
Plants affected by the Acid Rain Program
Highest 2nd maximum 24-hour S02 concentration by county, 1999
Air Quality Index logo
Number of days with AQI values > 100, as a percentage of 1990 value
Percent of days over 100 due to ozone
Location of nonattainment areas for criteria pollutants, September 2000
Classified ozone nonattainment areas
National contribution of source types to 1996 NTI emissions for the 188 HAPs
National contribution of source types to 1996 NTI emissions for the urban HAPs
National contribution by emission source type for individual urban HAPs and diesel particulate matter, 1996.
Urban/rural splits by source type for the 1996 national emissions of 188 HAPs
Urban/rural splits by source type for the 1996 national emissions of 33 urban HAPs
Change in national air toxics emissions - baseline (1990-1993) to 1996
Locations for urban and rural air toxics monitors with long-term data
National trend in annual average benzene concentrations in metropolitan areas, 1994-1999
National trend in annual average 1,3-butadiene concentrations in metropolitan areas, 1994-1999
National trend in annual average total suspended lead concentrations in metropolitan areas, 1994-1999
National trend in annual average perchloroethylene concentrations in metropolitan areas, 1994-1999
National trend in annual average styrene concentrations in metropolitan areas, 1994-1999
National trend in annual average toluene concentrations in metropolitan areas, 1994r-1999
Trend in annual average benzene concentrations for metropolitan sites in California, 1990-1999
-------
Figure 5-9b. Trend in annual average 1,3-butadiene concentrations for metropolitan sites in California, 1990-1999 92
Figure 5-9c. Trend in annual average total suspended lead concentrations for metropolitan sites in California, 1990-1999 93
Figure 5-9d. Trend in annual average perchloroethylene concentrations for metropolitan sites in California, 1990-1999 93
Figure 5-9e. Trend in annual average styrene concentrations for metropolitan sites in California, 1990-1999 94
Figure 5-9f. Trend in annual average toluene concentrations for metropolitan sites in California, 1990-1999 94
Figure 6-1. IMPROVE sites meeting data completeness requirements for sites operating in 1999 100
Figure 6-2. Comparison of the three visibility metrics (extinction, deciview and visual image) 101
Figure 6-2a. Images of Shenandoah National Park and Yosemite National Park 101
Figure 6-3. Shenandoah National Park on clear and hazy days and the effect of adding 10 jig/m3 of fine particles to each 102
Figure 6-4. Long-term trends for 75th percentile light extinction coefficient from airport visual data (July-September) 103
Figure 6-5a. Visibility trends for 10 eastern U.S. Class I areas for clearest, middle, and haziest 20 percent days in the
distribution, 1992-1999 104
Figure 6-5b. Visibility trends for 26 western U.S. Class I areas for clearest, middle, and haziest 20 percent days in the distribution,
1992-1999 104
Figure 6-6a. Aerosol light extinction in 10 eastern Class I areas for the clearest 20 percent of the days in the distribution, 1992-1999. 105
Figure 6-6b. Aerosol light extinction in 10 eastern Class I areas for the middle 20 percent of the days in the distribution, 1992-1999. 105
Figure 6-6c. Aerosol light extinction in 10 eastern Class I areas for the haziest 20 percent of the days in the distribution, 1992-1999.. 105
Figure 6-6d. Aerosol light extinction in 26 western Class I areas for the clearest 20 percent of the days in the distribution, 1990-1999.106
Figure 6-6e. Aerosol light extinction in 26 western Class I areas for the middle 20 percent of the days in the distribution, 1990-1999. 106
Figure 6-6f. Aerosol light extinction in 26 western Class I areas for the haziest 20 percent of the days in the distribution, 1990-1999. 106
Figure 6-7a. Class I area significant trends in deciviews for the clearest 20 percent, middle 20 percent, and haziest 20 percent days
as summarized in Table 6-1 108
Figure 6-7b. Class I area significant trends light extinction due to sulfate for the clearest 20 percent, middle 20 percent, and haziest
20 percent days as summarized in Table 6-1 108
Figure 6-7c. Class I area significant trends for light extinction due to organic carbon for the clearest 20 percent, middle 20 percent,
and haziest 20 percent days as summarized in Table 6-1 109
Figure 6-8a. Aerosol light extinction in (Mm-1) for the clearest 20 percent days and contribution by individual particulate matter
constituents, based on 1997-1999 IMPROVE data 110
Figure 6-8b. Aerosol light extinction in (Mm-1) for the middle 20 percent days and contribution by individual particulate matter
constituents, based on 1997-1999 IMPROVE data 110
Figure 6-8c. Aerosol light extinction in (Mm-1) for the haziest 20 percent days and contribution by individual particulate matter
constituents, based on 1997-1999 IMPROVE data Ill
Figure 6-9a. Current visibility impairment expressed in deciviews for the clearest 20 percent days based on 1997-1999
IMPROVE data 112
Figure 6-9b. Current visibility impairment expressed in deciviews for the middle 20 percent days based on 1997-1999
IMPROVE data 112
Figure 6-9c. Current visibility impairment expressed in deciviews for the haziest 20 percent days based on 1997-1999
IMPROVE data 113
Figure 7-1. The National Atmospheric Deposition Program/National Trends Network 116
Figure 7-2. Annual mean sulfate deposition from precipitation, 1990-1992 vs. 1997-1999 117
Figure 7-3. Annual mean ammonium deposition from precipitation, 1990-1992 vs. 1997-1999 118
Figure 7-4. Annual mean nitrate deposition from precipitation, 1990-1992 vs. 1997-1999 119
Figure 7-5. Rural annual mean S02 concentrations from CAST Net, 1990-1992 vs. 1997-1999 120
Figure 7-6. Rural annual average sulfate concentrations from CASTNet, 1990-1992 vs. 1997-1999 121
Figure 7-7. CASTNet and subset of 34 long-term monitoring sites used for 1990-1999 trends analysis 121
Figure 7-8. Trend in ambient sulfates in the rural eastern United States, based on CASTNet monitoring data, 1990-1999 122
Figure 7-9. Trend in ambient sulfur dioxide in the rural eastern United States, based on CASTNet monitoring data, 1990-1999 122
Figure 7-10. Rural annual mean ammonium concentrations from CASTNet, 1990-1992 vs. 1997-1999 123
Figure 7-11. Rural annual mean total nitrate concentrations from CASTNet, 1990-1992 vs. 1997-1999 123
Figure 7-12. Trend in annual mean ambient sulfur dioxide and sulfate concentrations, based on CASTNet monitoring data, and
regional S02 emissions from electric utilities in rural eastern United States, 1990-1999 124
IX
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Figures 7- 13a. and Figure 7- 13b. Trend in annual mean ambient sulfur dioxide and sulfate concentrations, based on CASTNet
monitoring data, and regional S02 emissions from electric utilities in rural eastern United States by calendar quarter,
1990-1999 124
Figures 7-13c. and 7-13d. Trend in annual mean ambient sulfur dioxide and sulfate concentrations, based on CASTNet monitoring
data, and regional S02 emissions from electric utilities in rural eastern United States by calendar quarter, 1990-1999 125
Figure 7-14. Wet and dry components of sulfur deposition, 1999 126
Figure 7-15. Wet and dry components of nitrogen deposition, 1999 126
Figure A-l. (Multiple NA areas within a larger NA area) Two S02 areas inside the Pittsburgh-Beaver Valley ozone NA 226
Figure A-2. (Overlapping NA areas) Searles Valley PM10 NA partially overlaps the San Joaquin Valley ozone NA 226
Figure B-l. Carbon monoxide monitoring network, 1999 230
Figure B-2. Lead monitoring network, 1999 230
Figure B-3. Nitrogen dioxide monitoring network, 1999 231
Figure B-4. Ozone monitoring network, 1999 231
Figure B-5. PM10 monitoring network, 1999 232
Figure B-6. Sulfur dioxide monitoring network, 1999 232
Figure B-7. Class I Areas in the Improve Network meeting data completeness criteria 234
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Tables
Table 2-1. NAAQS in effect as of December 1999 9
Table 2-2. Milestones in Motor Vehicle Emissions Control 14
Table 2-3. Summary of Changes in Summer 6-9 a.m. Mean Concentrations of NOx and TNMOC at PAMS Sites 34
Table 2-4. Biogenic Sources of VOC Emissions By Region 37
Table 2-5. Percent Contribution to PM2 5 by Component, 1999 52
Table 2-6. Total S02 Emissions from Phase I and Non-Phase I Acid Rain Sources: 1990-1999 (million tons) 64
Table 3-1. Summary of MSA Trend Analyses by Pollutant, 1990-1999 70
Table 3-2. AQI Categories, Colors, and Ranges 72
Table 4-1. Areas Redesignated Between September 1999 and September 2000 77
Table 5-1. List of 33 Urban Air Toxics Strategy HAPs 81
Table 5-2. National Summary of Ambient HAP Concentration Trends in Metropolitan Areas, 1994^-1999 87
Table 5-3. National Summary of Ambient HAP Concentration Trends in Rural Areas, 1994-1999 95
Table 6-1. Summary of Class I Area Trend 1 Analysis 107
Table A-la. National Air Quality Trends Statistics for Criteria Pollutants, 1980-1989 128
Table A-lb. National Air Quality Trends Statistics for Criteria Pollutants, 1990-1999 130
Table A-2. National Carbon Monoxide Emissions Estimates, 1970, 1975,1980, 1985, 1989-1999 (thousand short tons) 132
Table A-3. National Lead Emissions Estimates, 1970,1975, 1980, 1985, 1989-1999 (short tons) 136
Table A-4. National Nitrogen Oxides Emissions Estimates, 1970, 1975,1980, 1985, 1989-1999 (thousand short tons) 138
Table A-5. National Volatile Organic Compounds Emissions Estimates, 1970,1975, 1980, 1985,1989-1999 (thousand short tons) 142
Table A-6. National PM10 Emissions Estimates, 1970, 1975,1980, 1985, 1989-1999 (thousand short tons) 148
Table A-7. Miscellaneous and Natural PM10 Emissions Estimates, 1970, 1975,1980, 1985, 1989-1999 (thousand short tons) 152
Table A-8. National Sulfur Dioxide Emissions Estimates, 1970, 1975, 1980,1985, 1989-1999 (thousand short tons) 153
Table A-9. National PM25 Emissions Estimates, 1990-1999 (thousand short tons) 156
Table A-10. National Ammonia Emissions Estimates, 1990-1999 (thousand short tons) 160
Table A-ll. National Long-Term Air Quality Trends, 1980-1999 162
Table A-12a. National Air Quality Trends by Monitoring Location, 1980-1989 163
Table A-12b. National Air Quality Trends by Monitoring Location, 1990-1999 164
Table A-13a. National Air Quality Trends Statistics by EPA Region, 1980-1989 165
Table A-13b. National Air Quality Trends Statistics by EPA Region, 1990-1999 167
Table A-14. Maximum Air Quality Concentrations by County, 1999 169
Table A-15. Maximum Air Quality Concentrations by Metropolitan Statistical Area, 1999 188
Table A-16. Metropolitan Statistical Area Air Quality Trends, 1990-1999 194
Table A-17. Number of Days with AQI Values Greater Than 100 at Trend Sites, 1990-1999, and All Sites in 1999 219
Table A-18. (Ozone only) Number of Days with AQI Values Greater Than 100 at Trend Sites, 1990-1999, and All Sites in 1999 221
Table A-19. Condensed Nonattainment Areas List(a) 223
Table A-20. Trend in 8-hr ozone concentrations (ppm) exceedances at National Park and National Monument sites, 1990-1999 ... 227
Table A-21. Onroad and Nonroad Emissions of 21 Mobile Source Air Toxics, 1996 228
Table B-l. Number of Ambient Monitors Reporting Data to AIRS 229
XI
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Acronyms
AIRS Aerometric Information Retrieval
System
AQRV Air-Quality Related Values
AIRMoN Atmospheric Integrated Assessment
Monitoring Network
CAA Clean Air Act
CAAA Clean Air Act Amendments
CARB California Air Resources Board
CAS AC Clean Air Scientific Advisory
Committee
CASTNet Clean Air Status and Trends Network
CEMs Continuous Emissions Monitors
CFR Code of Federal Regulations
CO Carbon Monoxide
CMS A Consolidated Metropolitan Statistical
Area
DST Daylight Savings Time
EPA Environmental Protection Agency
FRM Federal Reference Method
GDP Gross Domestic Product
GLM General Linear Model
HAPs Hazardous Air Pollutants
IADN Integrated Atmospheric Deposition
Network
I/M Inspection and Maintenance
Programs
IMPROVE Interagency Monitoring of PROtected
Environments
MACT Maximum Achievable Control
Technology
MARAMA Mid-Atlantic Regional Air
Management Association
MDN Mercury Deposition Network
MSA Metropolitan Statistical Area
MDL Minimum Detectable Level
NAAQS National Ambient Air Quality
Standards
NADP/NTN National Atmospheric Deposition
Program/National Trends Network
NAMS National Air Monitoring Stations
NAPAP National Acid Precipitation
Assessment Program
NARSTO
NESCAUM
NLEV
NMOC
no2
NOx
NPS
NTI
03
OTAC.
PAHs
PAMS
PAN
Pb
PBTs
PCBs
PMi„
pmZ5
POM
PPm
PSI
RFG
RVP
SLAMS
SNMOC
so2
sox
TNMOC
TRI
TSP
UATMP
VMT
VOCs
jig/m3
North American Research Strategy for
Tropospheric Ozone
Northeast States for Coordinated Air
Use Management
National Low Emission Vehicle
Non-Methane Organic Compound
Nitrogen Dioxide
Nitrogen Oxides
National Park Service
National Toxics Inventory
Ozone
The Ozone Transport Assessment
Group
Polyaromatic Hydrocarbons
Photochemical Assessment
Monitoring Stations
Peroxyacetyl Nitrate
Lead
Persistent and Bioaccumulative Toxics
Poly chlorinated Biphenyls
Particulate Matter of 10 micrometers
in diameter or less
Particulate Matter of 2.5 micrometers
in diameter or less
Polycyclic Organic Matter
Parts Per Million
Pollutant Standards Index
Reformulated Gasoline
Reid Vapor Pressure
State and Local Air Monitoring
Stations
Speciated Non-Methane Organic
Compound
Sulfur Dioxide
Sulfur Oxides
Total Non-Methane Organic
Compound
Toxic Release Inventory
Total Suspended Particulate
Urban Air Toxics Monitoring Program
Vehicle Miles Traveled
Volatile Organic Compounds
Micrograms Per Cubic Meter
XII
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CHAPTER 1
Executive Summary
http://www.epa.gov/oar/aqtrnd99/chapter1.pdf
Criteria pollutants are those pollutants
for which the United States
Environmental Protection Agency has
established National Ambient Air Quality
Standards (NAAQS). They include
carbon monoxide (CO), lead (Pb),
nitrogen dioxide (N02), ozone (03),
particulate matter (PM), and sulfur
dioxide (S02).
Percent Decrease in National
Air Quality Concentrations
1980-1999 1990-1999
57
Carbon Monoxide
36
94
Lead
60
25
Nitrogen Dioxide
10
20
Ozone*
4
—
Particulate Matter (PM10)
18
50
Sulfur Dioxide
36
* based on 1-hour level.
Worth Noting:
20-YEAR TRENDS
• National levels of all the criteria pollutants are down.
• Visibility has improved in the East.
10-YEAR TRENDS
™2,
• In the rural east, sulfates (which comprise approximately 50 percent of
PM25) are down 24 percent over the last 10 years and in 1999 have returned
to 1996-1997 levels, after higher levels in 1998.
• At the Class I areas, PM25 levels, on average, are also back down in 1999.
Visibility
• Overall, the eastern Class I sites do not appear to be getting any worse.
• The eastern Class I sites as an aggregate, showed a 15-percent improvement
for the haziest days from 1992-1999. The light extinction due to sulfates
reached its lowest level of the 1990s.
Ozone
• While national levels improved in the last 10 years, 1-hour ozone levels in
selected regions increased, and 8-hour levels in rural areas increased.
Air Toxics
• Large national emission reductions have been achieved in air toxics (also
known as hazardous air pollutants) between the baseline period (1990-1993)
and 1996. Improvements come from "major" stationary sources and high-
way vehicles.
Air quality concentrations are based
on actual measurements of pollutant
concentrations in the air at selected
monitoring sites across the country.
Fine particulate matter, or PM25, are
those particles whose aerodynamic
diameter is less than or equal to 2.5
micrometers.
INTRODUCTION
This is the 27th annual report documenting air pollution trends in the United
States.1-25,27 This document highlights the Environmental Protection Agency's
(EPA's) most recent assessment of the nation's air quality, focusing on the
20-year period from 1980-1999. It features comprehensive information for the
criteria pollutants and hazardous air pollutants, as well as relevant ambient air
pollution information for visibility impairment and acid rain.
Discussions throughout this report are based on the principle that many of
the programs designed to reduce ambient concentrations of the criteria pollut-
ants also aid in reducing pollution that contributes to air toxics pollution, vis-
ibility impairment, and acid rain. Likewise, requirements under the various air
CHAPTER 1 • EXECUTIVE SUMMARY 1
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
toxics, visibility, and acid rain programs can also help reduce emissions that
contribute to ambient concentrations of the criteria pollutants.
EPA tracks trends associated with the criteria pollutant standards. The na-
tional and regional air quality trends, along with supporting emissions data,
are presented in this chapter. National levels of all criteria pollutants are
down over the last 20 years. Over the last 20 years, ozone (03) (1-hour and
8-hour) levels nationally have improved considerably. Some parts of the coun-
try show increases in levels over the last 10 years, due mainly to increased
NOx emissions and weather conditions favorable to 03 formation. Rural 03
levels appear to be increasing in the short term. However, 03 levels in urban
areas where 03 problems have historically been the most severe have shown
marked improvement in response to stringent controls. Over the last 20 years,
urban N02 concentrations across the country have decreased. All areas of the
country that once violated the NAAQS for N02 now meet this standard. Since
1988 represents the first complete year of PM10 data for most monitors, a
20-year trend is not available. However, the most recent 10-year period (1990-
1999) shows that the national average of annual mean PM10 concentrations
decreased 18 percent. The national composite average of S02 annual mean
concentrations decreased 36 percent between 1990-1999 with the largest single-
year reduction occurring between 1994 and 1995. Nationally carbon monoxide
(CO) levels for 1999 are the lowest recorded in the last 20 years and this air
quality improvement is consistent across all regions of the country. Presently
only six areas of the country have CO levels violating the NAAQS. From
1980-1999, there has been a 94-percent decrease in lead (Pb) emissions with a
corresponding 94-percent decrease in maximum quarterly average Pb concen-
trations at population oriented monitors. There are only six areas in the coun-
try in nonattainment for Pb and these are associated with specific point
sources.
CHAPTER 2
CRITERIA POLLUTANTS -
NATIONAL TRENDS
Summary of MSA Trend Analyses by Pollutant, 1990-1999
CHAPTER 3
# MSAs
Total # # MSAs # MSAs with No
MSAs Up Down Significant
Change
CRITERIA POLLUTANTS -
METROPOLITAN AREA TRENDS
CO second max 8-hour
Lead max quarterly mean
NOz arithmetic mean
Ozone fourth max 8-hour
Ozone second daily max 1-hour
PM10 90th percentile
PM10 weighted annual mean
S02 arithmetic mean
S02 second max 24-hour
Trend Statistic
138 0
69 1
99 3
207 25
207 17
216 1
216 2
148 1
149 1
107
44
41
10
14
113
126
86
82
31
24
55
172
176
102
88
61
66
Chapter 3 characterizes air quality on
a more local level, using three differ-
ent indicators. First, this chapter lists
the 1999 peak air quality concentra-
tions for metropolitan statistical areas
(MSAs). Second, 10-year trends are
assessed for each area using a statisti-
cal method to measure whether the
trend is up or down. The results show
that of the 263 areas examined: 1) 214
had downward trends in at least one
of the criteria pollutants; 2) 34 had
upward trends; 3) 41 areas had no
significant trends. A closer look at the
2 EXECUTIVE SUMMARY • CHAPTER 1
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
34 areas with upward trends reveals that most were exceeding the level of the
8-hour ozone standard.
The third way in which local air quality is evaluated is by looking at the Air
Quality Index (AQI) in the nation's 94 largest metropolitan areas. Ozone ac-
counts for majority of the days with AQI values over 100. Between 1990 and
1999, the total number of days with AQI values greater than 100 decreased 62
percent in southern California but actually rose 25 percent in the remaining
major cities across the United States.
CHAPTER 4
CRITERIA POLLUTANTS -
OFFICIAL NONATTAINMENT AREAS
Chapter 4 summarizes the current status of nonattainment areas, which are
those officially designated areas not meeting the NAAQS for at least one of the
six criteria pollutants. As of September 2000,114 areas are designated non-
attainment. These areas are displayed on a map in this chapter. A second map
depicts the current ozone nonattainment areas, color-coded to indicate the
severity of the ozone problem in each area. The condensed list of nonattain-
ment areas as of September 2000 is presented in Table A-19.
CHAPTER 5
AIR TOXICS
Chapter 5 presents information on Hazardous Air Pollutants (HAPs), com-
monly called air toxics. These are pollutants known to cause or suspected of
causing cancer or other serious human health effects or ecosystem damage. As
of the date of this publication, the 1996 National Toxics Inventory (NTI) con-
tains the most complete, up-to-date air toxics emission estimates available for
188 HAPs. For purposes of this report, the information in the NTI has been
divided into four overarching source types: 1) large industrial or "major"
sources; 2) "area and other sources," which include smaller industrial sources,
such as small drycleaners and gasoline stations, as well as natural sources,
such as wildfires; 3) "onroad" mobile, including highway vehicles; and 4)
"nonroad" mobile sources, like aircraft, locomotives, and lawn mowers. Sum-
maries of the 1996 emissions provide detail that includes contributions of
source types to the 188 HAPs, the subset of 33 urban HAPs as well as the re-
cently designated 21 mobile source air toxics.
A comparison of the 1996 NTI to the baseline period (1990-1993) shows that
large national emission reductions have been achieved. For 188 HAPs, there is
a 23-percent reduction between the baseline and 1996. For the 33 urban HAPs,
there is a 30-percent reduction between the baseline and 1996. Improvements
come from "major" stationary sources and highway vehicles. Further reduc-
tions are expected from both existing programs and planned future efforts.
Although there is currently no national air toxics monitoring network, there
are approximately 300 monitoring sites currently producing ambient data on
some of the HAPs. Although the sites are not necessarily at locations which
represent the highest area-wide concentrations, they can still be used to pro-
vide useful information on trends in ambient air toxics. Ambient monitoring
results generally reveal downward trends for most pollutants. The most con-
sistent improvements are apparent for benzene and for total suspended lead.
From 1994-1999, annual average concentrations for these two HAPs declined
40 and 47 percent respectively. EPA is working together with state and local air
monitorinp- ap-encies to build upon the existing monitorinp- sites to develop a
national monitoring network. chapter 1 • executive summary 3
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
CHAPTER 6
VISIBILITY TRENDS
The Clean Air Act (CAA) authorizes EPA to protect visibility, or visual air qual-
ity, through a number of programs. These programs include the National
Visibility Program under sections 169a and 169b of the Act, the Prevention of
Significant Deterioration Program for the review of potential impacts from
new and modified sources, the secondary National Ambient Air Quality Stan-
dards (NAAQS) for PM10 and PM2.s, and the Acid Rain Program under section
401. The National Visibility Program, established in 1980, requires the protec-
tion of visibility in 156 mandatory federal Class I areas across the country (pri-
marily national parks and wilderness areas). The CAA established as a
national visibility goal "the prevention of any future, and the remedying of
any existing, impairment of visibility in mandatory federal Class I areas in
which impairment results from man-made air pollution." The Act also calls for
state programs to make "reasonable progress" toward the national goal.
The trends analyses presented in this chapter are based on data from the
IMPROVE network. There were 34 sites having data adequate for assessing
trends between 1990 and 1999. The network recently has been expanded to
provide complete coverage of all mandatory federal Class I areas.
Because of the significant regional variations in visibility conditions, the
trends are grouped into eastern and western regions, rather than a national
aggregate. The trends are presented in terms of the annual average values for
the "clearest," "typical," and "haziest" days monitored each year.
The results show that, in general, visibility is worse in the East than in the
West. In fact, visibility impairment for the worst days in the West is close to the
level of impairment for the best day in the East.
This year's analyses show that the 10 eastern U.S. Class I sites as an aggre-
gate show improvement for the haziest days over the 1992-1999 timeframe
primarily due to reduced levels of sulfate. The 26 western U.S. Class I sites as
an aggregate show improvement for the clearest 20 percent and middle 20
percent of days over 1990-1999 timeframe.
Long-term visibility trends (1990-1999) illustrated in the figures show that
summer visibility in the eastern United States improved between 1991-1995.
This trend follows overall trends in sulfur dioxides emissions discussed in
Chapter 2.
CHAPTER 7
ATMOSPHERIC DEPOSITION OF
SULFURAND NITROGEN COMPOUNDS
Sulfur and nitrogen oxides are emitted into the atmosphere primarily from the
burning of fossil fuels. These emissions react in the atmosphere to form com-
pounds that are transported long distances and are subsequently deposited in
the form of pollutants such as particulate matter (sulfates, nitrates) and related
4 EXECUTIVE SUMMARY • CHAPTER 1
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Long-term Trends for 75th Percentile Light Extinction Coefficient from
Airport Visual Data (July-September)
-SI
fi*"
' Sw-'ia Quartur J
3u«-Ur J
CHAPTER 1 • EXECUTIVE SUMMARY 5
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Rural Annual Average Sulfate
gases (nitrogen dioxide, sulfur dioxide and nitric acid). Nitrogen oxides will
also interact with volatile organic compounds to form ozone. The effects of
atmospheric deposition include acidification of lakes and streams, nutrient
enrichment of coastal waters and large river basins, soil nutrient depletion and
decline of sensitive forests, agricultural crop damage, and impacts on ecosys-
Concentrations FrorrTcASTNet, tem biodiversity. Toxic pollutants and metals can also be transported and
1990-1992 vs. 1997-1999 deposited through atmospheric processes.
Both local and long-range emission sources contribute to atmospheric depo-
sition. Total atmospheric deposition is determined using both wet and dry
deposition measurements. Wet deposition is the portion dissolved in cloud
droplets and is deposited during rain or other forms of precipitation. Dry
deposition includes both gas and particle transfer to surfaces during periods of
no precipitation. Although the term "acid rain" is widely recognized, the dry
deposition portion can range from 20-60 percent of total deposition.
EPA is required by several Congressional and other mandates to assess the
effectiveness of air pollution control efforts. These mandates include Title IX
of the 1990 Clean Air Act Amendments (the National Acid Precipitation As-
sessment Program), the Government Performance and Results Act, and the
U.S./Canada Air Quality Agreement. One measure of effectiveness of these
efforts is whether sustained reductions in the amount of atmospheric deposi-
tion over broad geographic regions are occurring. However, permanent
changes in SO2 emissions happen very slowly and atmospheric trends are
often obscured by the wide variability of measurements and climate. Numer-
ous years of continuous and consistent data are required to overcome this
variability, making long-term monitoring networks especially critical for char-
acterizing deposition levels and identifying relationships among emissions,
atmospheric loadings and effects on human health and the environment.
Sulfate concentrations in precipitation have decreased over the past two
decades. The reductions were relatively large in the early 1980s followed by
more moderate declines until 1995. These reductions in wet sulfates are similar
to changes in SO2 emissions. In 1995 and 1996, however, concentrations of
sulfates in precipitation over a large area of the eastern United States exhibited
a dramatic and unprecedented reduction. Sulfates in rain have been estimated
to be 10-25 percent lower than levels expected with a continuation of 1983-
1994 trends. The wet sulfate deposition levels in the 1990-1992 and 1997-1999
time periods, together with the absolute change, are illustrated in the figure.
This important reduction in acid precipitation is directly related to the large
regional decreases in SO2 emissions resulting from phase I of the Acid Rain
Program (See "Trends in SO2" in Chapter 2 of this report). The largest reduc-
tions in sulfate deposition occurred along the Ohio River Valley and in states
to the north and immediately downwind of this region. Nitrogen trends paint
a different picture. Nitrate and ammonium deposition derived from National
Atmospheric Deposition Program measurement sites reveal 10-year improve-
ment in some areas, including eastern TX, MI, PA and NY. Increased deposi-
tion is estimated for the Plains states; and the Western Ohio River and Central
Mississippi River Valleys. From ammonium in rain, increases are also noted for
eastern NC. However, nitrogen levels for most areas of the county in 1997-
1999 were not appreciably different from historical levels.
Source: CASTNet
Source: CASTNet
S042-
(Mg/m3)
S042-
(Mg/m3)
I
Change
Source: CASTNet
(M9#m3)
6 EXECUTIVE SUMMARY • CHAPTER 1
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
REFERENCES AND NOTES
1. The National Air Monitoring Program: Air Quality and Emissions Trends-
Annual Report, EPA-450/l-73-001a and b, U.S. Environmental Protection
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Park, NC 27711, July 1973.
2. Monitoring and Air Quality Trends Report, 1972, EPA-450/1-73-004, U.S.
Environmental Protection Agency, Office of Air Quality Planning and Stan-
dards, Research Triangle Park, NC 27711, December 1973.
3. Monitoring and Air Quality Trends Report, 1973, EPA-450/1-74-007, U.S.
Environmental Protection Agency, Office of Air Quality Planning and Stan-
dards, Research Triangle Park, NC 27711, October 1974.
4. Monitoring and Air Quality Trends Report, 1974, EPA-450/1-76-001, U.S.
Environmental Protection Agency, Office of Air Quality Planning and Stan-
dards, Research Triangle Park, NC 27711, February 1976.
5. National Air Quality and Emissions Trends Report, 1975, EPA-450/1-76-
002, U.S. Environmental Protection Agency, Office of Air Quality Planning
and Standards, Research Triangle Park, NC 27711, November 1976.
6. National Air Quality and Emissions Trends Report, 1976, EPA-450/1-77-
002, U.S. Environmental Protection Agency, Office of Air Quality Planning
and Standards, Research Triangle Park, NC 27711, December 1977.
7. National Air Quality and Emissions Trends Report, 1977, EPA-450/2-78-
052, U.S. Environmental Protection Agency, Office of Air Quality Planning
and Standards, Research Triangle Park, NC 27711, December 1978.
8. 1980 Ambient Assessment-Air Portion, EPA-450/4-81-014, U.S. Environ-
mental Protection Agency, Office of Air Quality Planning and Standards,
Research Triangle Park, NC 27711, February 1981.
9. National Air Quality and Emissions Trends Report, 1981, EPA-450/4-83-
011, U.S. Environmental Protection Agency, Office of Air Quality Planning
and Standards, Research Triangle Park, NC 27711, April 1983.
10. National Air Quality and Emissions Trends Report, 1982, EPA-450/4-84-
002, U.S. Environmental Protection Agency, Office of Air Quality Planning
and Standards, Research Triangle Park, NC 27711, March 1984.
11. National Air Quality and Emissions Trends Report, 1983, EPA-450/4-84-
029, U.S. Environmental Protection Agency, Office of Air Quality Planning
and Standards, Research Triangle Park, NC 27711, April 1985.
12. National Air Quality and Emissions Trends Report, 1984, EPA-450/4-86-
001, U.S. Environmental Protection Agency, Office of Air Quality Planning
and Standards, Research Triangle Park, NC 27711, April 1986.
13. National Air Quality and Emissions Trends Report, 1985, EPA-450/4-87-
001, U.S. Environmental Protection Agency, Office of Air Quality Planning
and Standards, Research Triangle Park, NC 27711, February 1987.
14. National Air Quality and Emissions Trends Report, 1986, EPA-450/4-88-
001, U.S. Environmental Protection Agency, Office of Air Quality Planning
and Standards, Research Triangle Park, NC 27711, February 1988.
15. National Air Quality and Emissions Trends Report, 1987, EPA-450/4-89-
001, U.S. Environmental Protection Agency, Office of Air Quality Planning
and Standards, Research Triangle Park, NC 27711, March 1989.
16. National Air Quality and Emissions Trends Report, 1988, EPA-450/4-90-
002, U.S. Environmental Protection Agency, Office of Air Quality Planning
and Standards, Research Triangle Park, NC 27711, March 1990.
CHAPTER 1 • EXECUTIVE SUMMARY 7
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
17. National Air Quality and Emissions Trends Report, 1989, EPA-450/4-91-
003, U.S. Environmental Protection Agency, Office of Air Quality Planning
and Standards, Research Triangle Park, NC 27711, February 1991.
18. National Air Quality and Emissions Trends Report, 1990, EPA-450/4-91-
023, U.S. Environmental Protection Agency, Office of Air Quality Planning
and Standards, Research Triangle Park, NC 27711, November 1991.
19. National Air Quality and Emissions Trends Report, 1991, EPA-450/R-92-
001, U.S. Environmental Protection Agency, Office of Air Quality Planning
and Standards, Research Triangle Park, NC 27711, October 1992.
20. National Air Quality and Emissions Trends Report, 1992, EPA-454/R-93-
031, U.S. Environmental Protection Agency, Office of Air Quality Planning
and Standards, Research Triangle Park, NC 27711, October 1993.
21. National Air Quality and Emissions Trends Report, 1993, EPA-454/R-94-
026, U.S. Environmental Protection Agency, Office of Air Quality Planning
and Standards, Research Triangle Park, NC 27711, October 1994.
22. National Air Quality and Emissions Trends Report, 1994, EPA-454/R-95-
014, U.S. Environmental Protection Agency, Office of Air Quality Planning
and Standards, Research Triangle Park, NC 27711, October 1995.
23. National Air Quality and Emissions Trends Report, 1995, EPA-454/R-96-
005, U.S. Environmental Protection Agency, Office of Air Quality Planning
and Standards, Research Triangle Park, NC 27711, October 1996.
24. National Air Quality and Emissions Trends Report, 1996, EPA-454/R-97-
013, U.S. Environmental Protection Agency, Office of Air Quality Planning
and Standards, Research Triangle Park, NC 27711, January 1998.
25. National Air Quality and Emissions Trends Report, 1996, EPA-454/R-97-
013, U.S. Environmental Protection Agency, Office of Air Quality Planning
and Standards, Research Triangle Park, NC 27711, January 1998.
26. Based on the level of the 8-hour ozone standard (0.08 ppm).
27. National Air Quality and Emissions Trends Report, 1998, EPA-454/R-00-
003, U.S. Environmental Protection Agency, Office of Air Quality Planning
and Standards, Research Triangle Park, NC 27711, March 2000.
8 EXECUTIVE SUMMARY • CHAPTER 1
-------
CHAPTER 2
Criteria Pollutants —
National Trends
http://www.epa.gov/oar/aqtrnd99/chapter2.pdf
This chapter presents national and
regional trends for each of the pollut-
ants for which the United States En-
vironmental Protection Agency (EPA)
has established National Ambient Air
Quality Standards (NAAQS). NAAQS
are in place for the following six crite-
ria pollutants: carbon monoxide
(CO), lead (Pb), nitrogen dioxide
(N02), ozone (03), particulate matter
(PM), and sulfur dioxide (S02). Table
2-1 lists the NAAQS for each pollut-
ant in terms of the level and averag-
ing time of the standard used to
evaluate compliance.
There are two types of standards:
primary and secondary. Primary
standards protect against adverse
human health effects, whereas sec-
ondary standards protect against
welfare effects such as damage to
crops, ecosystems, vegetation, build-
ings, and decreased visibility. There
are primary standards for all of the
criteria pollutants. Some pollutants
(PM and S02) have primary stan-
dards for both long-term (annual
average) and short-term (24 hours or
less) averaging times. Short-term
standards most directly protect
people from adverse health effects
associated with peak short-term ex-
posures to air pollution, while
long-term standards can protect
people from adverse health effects
associated with short- and long-term
exposures to air pollution.
CHAPTER 2 • CRITERIA POLLUTANTS — NATIONAL TRENDS 9
Table 2-1. NAAQS in effect as of December 2000.
Pollutant
Primary Standard
(Health Related)
Type of Average Standard Level
Concentration3
Secondary Standard
(Welfare Related)
Type of Average Standard Level
Concentration
CO
8-hourb 9 ppm
(10 mg/m3)
No Secondary Standard
1-hourb 35 ppm
(40 mg/m3)
No Secondary Standard
Pb
Maximum 1.5 |jg/m3
Quarterly Average
Same as Primary Standard
no2
Annual 0.053 ppm
Arithmetic Mean (100 |jg/m3)
Same as Primary Standard
03
Maximum Daily 0.12 ppm
1-hour Average0 (235 |jg/m3)
Same as Primary Standard
4th Maximum Dailyd 0.08 ppm
8-hour Average (157 |jg/m3)
Same as Primary Standard
PM10
Annual 50 |jg/m3
Arithmetic Mean
Same as Primary Standard
24-hourb 150 |jg/m3
Same as Primary Standard
pm25
Annual 15 |jg/m3
Arithmetic Meane
Same as Primary Standard
24-hourf 65 |jg/m3
Same as Primary Standard
so2
Annual 0.03 ppm
Arithmetic Mean (80 |jg/m3)
24-hourb 0.14 ppm
(365 |jg/m3)
3-hourb
0.50 ppm
(1,300 |jg/m3)
a Parenthetical value is an approximately equivalent concentration. (See 40 CFR Part 50).
b The short-term (24-hour) standard of 150 |jg/m3 is not to be exceeded more than once per
year on average over three years.
c The standard is attained when the expected number of days per calendar year with
maximum hourly average concentrations above 0.12 ppm is equal to or less than one,
as determined according to Appendix H of the Ozone NAAQS.
d Three-year average of the annual 4th highest daily maximum 8-hour average concen-
tration.
e Spatially averaged over designated monitors.
f The form is the 98th percentile.
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Any
Secondary standards have been
established for each criteria pollutant
except CO. Secondary standards are
identical to the primary standards,
with the exception of S02. Approxi-
mately 125 million people in the
United states reside in counties that
did not meet the primary standard
for at least one of the criteria pollut-
ants for the single year 1999.
CO
Pb
no2
O.
so,
0.4
0
153.8 (1-hour)
(8-hour) 1122.5
I 3
Data not yet ava
ilable.
0
1 (1-hour)
(8-hour) 1125.3
0 20 40 60 SO 100 120 140
Millions of People
Number of people living in counties with
air quality concentrations above the level
of NAAQS in 1999.
On July 18, 1997, EPA revised the
ozone and PM NAAQS. The averag-
ing time of the ozone standard
changed from a 1-hour average to an
8-hour average to protect against
longer exposure periods that are of
concern for both human health and
welfare. The primary PM standards
were revised to change the form of
the PM10 standards and to add two
new PM2.5 standards to protect
against fine particles.
In May 1999, however, the U.S.
Court of Appeals for the D.C. Circuit
issued an opinion affecting these
revised standards. In particular, the
court remanded the ozone standard
back to EPA for further consideration.
The court also vacated the revised
PM10 standard and remanded the
PM2.5 standards back to EPA for fur-
ther consideration. Following the
denial of a petition for a rehearing by
the D.C. Circuit, the Justice Depart-
ment has filed a petition for review
before the Supreme Court. Refer to
http://www.epa.gov/airlinks for up-
to-date information concerning ac-
tions surrounding the revised
standards.
The trends information presented
in this chapter is based on two types
of data: ambient concentrations and
emissions estimates. Ambient con-
centrations are measurements of
pollutant concentrations in the ambi-
ent air from monitoring sites across
the country. This year's report con-
tains trends data accumulated from
1990-1999 on the criteria pollutants
at thousands of monitoring stations
located throughout the United states.
The trends presented here are de-
rived from the composite average of
these direct measurements. The
averaging times and air quality sta-
tistics used in the trends calculations
relate directly to the NAAQS.
The second type of data presented
in this chapter are national emissions
estimates. These are based largely on
engineering calculations of the
amounts and kinds of pollutants
emitted by automobiles, factories,
and other sources over a given pe-
riod. In addition, some emissions
estimates are based on measurements
from continuous emissions monitors
(CEMs) that have recently been in-
stalled at major electric utilities to
measure actual emissions. This re-
port incorporates data from CEMs
collected between 1994 and 1999 for
NOx and S02 emissions at major
electric utilities. [The emissions data
summarized in this chapter and in
Appendix A were obtained from the
National Emission Inventory data
located at http://www.epa.gov/ttn/
chief. For assistance call INFO
CHIEF (919 541-1000).]
Changes in ambient concentra-
tions do not always track changes in
national emissions estimates. There
are five known reasons for this. First,
because most monitors are posi-
tioned in urban, population-oriented
locales, air quality trends are more
likely to track changes in urban emis-
sions rather than changes in total
national emissions. Urban emissions
are generally dominated by mobile
sources, while total emissions in rural
areas may be dominated by large
stationary sources such as power
plants and smelters.
Second, emissions for some pollut-
ants are calculated or measured in a
different form than the primary air
pollutant. For example, concentra-
tions of ozone are caused by VOC
emissions as well as NOx emissions.
Third, the amount of some pollut-
ants measured at monitoring loca-
tions depends on what chemical
reactions, if any, occur in the atmo-
sphere during the time it takes the
pollutant to travel from its source to
the monitoring station.
Fourth, meteorological conditions
often control the formation and
buildup of pollutants in the ambient
air. For example, peak ozone concen-
trations typically occur during hot,
dry, stagnant summertime conditions.
CO is predominately a cold weather
problem. Also, the amount of rainfall
can affect particulate matter levels.
Finally, emission estimates have
uncertainties and may not reflect
actual emissions. In some cases,
estimation methods are not consis-
tent across all 20 years presented in
this report.
For a more detailed discussion of
the methodology used to compute
the trend statistics in this chapter,
please refer to Appendix B.
10 CRITERIA POLLUTANTS — NATIONAL TRENDS • CHAPTER 2
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Carbon Monoxide
Figure 2-1. Trend in 2nd maximum non-overlapping 8-hour average CO
concentrations, 1980-1999.
Air Quality Concentrations
1980-99
57%
decrease
1990-99
36%
decrease
1998-99
3%
decrease
Emissions
1980-99
21%
decrease
1990-99
2%
decrease
1998-99
1%
increase
Concentration, ppm
16
Worth Noting
• Nationally, carbon monoxide (CO) levels
for 1999 are the lowest recorded in last 20
years and this air quality improvement is
consistent across all regions of the country.
• Presently, only six areas have CO
levels violating the NAAQS (three of these
are previous nonattainment areas).
• The National Academy of Sciences
is currently initiating a study of persistent
CO problem in Fairbanks, Alaska.
Nature and Sources
Carbon monoxide is a colorless,
odorless, and (at much higher levels)
poisonous gas, formed when carbon
in fuels is not burned completely. It is
a product of motor vehicle exhaust,
which contributes about 60 percent of
all CO emissions nationwide. High
concentrations of CO generally occur
in areas with heavy traffic conges-
tion. In cities, as much as 95 percent
of all CO emissions may emanate
from automobile exhaust. Other
sources of CO emissions include
industrial processes, non-transporta-
tion fuel combustion, and natural
sources such as wildfires. Wood-
stoves, cooking, cigarette smoke, and
space heating are sources of CO in
indoor environments. Peak CO con-
centrations typically occur during the
colder months of the year when CO
90% of sites have concentrations below this line
National Standard
304 Sites
A
Average
388 Sites
10% of sites have concentrations below this line
80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98
automotive emissions are greater and
nighttime inversion conditions are
more frequent.
Health Effects
Carbon monoxide enters the blood-
stream through the lungs and reduc-
es oxygen delivery to the body's
organs and tissues. The health threat
from lower levels of CO is most seri-
ous for those who suffer from cardio-
vascular disease, such as angina
pectoris. At much higher levels of
exposure, CO can be poisonous, and
healthy individuals may also be af-
fected. Impairment of cognitive skills,
vision and work capacity may occur
at elevated CO levels in healthy indi-
viduals.
Primary Standards
There are two primary NAAQS for
ambient CO: a 1-hour average of
35 ppm, and an 8-hour average of
9 ppm. These concentrations are not
to be exceeded more than once per
year. There currently are no second-
ary standards for CO.
National Air Quality Trends
Nationally, CO concentrations have
consistently declined over the last 20
years. Figure 2-1 reveals a 57-percent
improvement in composite average
ambient CO concentrations from 1980
to 1999 and a 36 percent reduction
over the last 10 years.1 Following an
upturn in 1994, the nation has experi-
enced year-to-year reductions in peak
8-hour CO concentrations through
the remainder of the decade. In fact,
the 1999 CO levels are generally the
lowest recorded during the past 20
years of monitoring. Exceedances of
the 8-hour CO NAAQS (which are
simply a count of the number of
times the level of the standard is
exceeded) have declined 93 percent
since 1990.
Long-term reductions in ambient
CO concentrations have been mea-
sured across all monitoring environ-
CHAPTER 2 • CRITERIA POLLUTANTS — NATIONAL TRENDS
11
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
ments—rural, suburban, and urban
sites. Figure 2-2 shows that on aver-
age, urban monitoring sites record
higher CO concentrations than subur-
ban sites, with the lowest levels
found at 16 rural sites. During the
past 20 years, the 8-hour CO concen-
trations decreased 65 percent at 16
rural monitoring sites, 54 percent at
289 suburban sites, and 57 percent at
381 urban sites.
Regional Air Quality Trends
The map in Figure 2-3 shows region-
al trends in ambient CO concentra-
tions during the past 20 years,
1980-1999. All 10 EPA Regions re-
corded 20-year improvements in CO
levels as measured by the regional
composite mean concentrations. Sig-
nificant 20-year concentration reduc-
tions of 50 percent or more are
evidenced across the nation except in
Figure 2-2. Trend in 2nd maximum non-overlapping 8-hour average CO
concentrations by type of location, 1980-1999.
Concentration, ppm
10
1980-89 1990-99
Rural Sites 3 13
Suburban Sites 132 157
Urban Sites 166 215
80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99
Note: When the total number of rural, suburban, and urban sites are summed for either the
1980-89 or 1990-99 time periods in Figure 2-2, this number may not equal the total
number of sites shown in Figure 2-1 for the same time periods. This is due to a few
monitoring sites falling outside the definitions of rural, suburban, or urban sites.
Figure 2-3. Trend in CO 2nd maximum non-overlapping 8-hour concentrations by EPA region, 1980-1999.
12.6
~ 56%
| 63%
f 60%
f 60%
9.4
^V-6 f61S%SV7
10%
8.8
V
~ 56%
7.7
3.9
"V^.4
~ 56%
f 56%
8.2
#¦ 55%
3.7
f 53%^
The National Trend
Alaska is in EPA Region 10; Hawaii, EPA Region 9; and Puerto Rico, EPA Region 2.
Concentrations are ppm.
Note: These trends are
influenced by the
distribution of monitoring
locations in a given region
and, therefore, can be
driven largely by urban
concentrations. For this
reason, they are not
indicative of background
regional concentrations.
12
CRITERIA POLLUTANTS
— NATIONAL TRENDS • CHAPTER 2
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 2-4. CO emissions by source category, 1999.
Transportation 77.1 %
Industrial Processes 7.8%
Fuel Combustion 5.5%
Miscellaneous 9.6%
the Midwest where reductions were
only slightly smaller.
National Emissions Trends
Figure 2-4 shows that the transporta-
tion category composed of onroad
and nonroad sources, accounted for
77 percent of the nation's total CO
emissions in 1999. Figure 2-5 pre-
sents the broad geographic distribu-
tions of 1999 CO emissions based on
the tonnage per square mile for each
county. This visualization clearly
shows that the eastern third of the
country and the west coast emitted
more CO (on a density basis) than the
western two-thirds of the continental
United States. National total CO
emissions have decreased 21 percent
since 1980 as shown in Figure 2-6.2
Despite a 57-percent increase in vehi-
cle miles traveled (VMT), emissions
from onroad vehicles decreased 56
Figure 2-5. Density map of 1999 carbon monoxide emissions, by county.
Tons/Year/Sq Mile
H 0 - 6.41
H 6.41 -14.23
H 14.23-27.13
¦ 27.13-56.03
¦ 56.03-13105.85
CHAPTER 2 • CRITERIA POLLUTANTS — NATIONAL TRENDS
13
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
percent during the past 20 years as a
result of automotive emissions con-
trol programs. However, emissions
from all transportation sources have
decreased only 23 percent over the
same period, primarily due to a 42-
-percent increase in off-road emis-
sions, which has offset the gains
realized in reductions of onroad vehi-
cle emissions.
Table 2-2 lists some of the major
milestones in the control of emissions
from automobiles starting with the
Clean Air Act (CAA) of 1970. At the
national level, these measures, which
have led to reductions in emissions of
CO as well as other pollutants, in-
clude establishing national standards
for tailpipe emissions, new vehicle
technologies, and clean fuels pro-
grams. State and local emissions
reduction measures include inspec-
tion and maintenance (I/M) pro-
grams and transportation
management programs.
In the area of clean fuels, the 1990
Clean Air Act Amendments (CAAA)
require oxygenated gasoline pro-
grams in several regions of the coun-
try during the winter months. Under
the program regulations, a minimum
oxygen content (2.7 percent by
weight) is required in gasoline to
ensure more complete fuel combus-
tion.3'4 Of the 36 CO nonattainment
areas that initially implemented the
program in 1992, 17 areas partici-
pated in the program during 1999.5
Blue Ribbon Panel on
Oxygenates in Gasoline
In November 1998, in response to the
public concern regarding the detec-
tion of MTBE (methyl tertiary butyl
ether—one of two fuel oxygenates
used in reformulated gasoline to help
improve air quality) in water, EPA
announced the creation of a blue
Figure 2-6. Trend in national total CO emissions, 1980-1999.2
~ Fuel CombustionH Industrial Processing
Thousand Short Tons Per Year ~Transportation ~Miscellaneous
140,000
120,000
100,000
80,000
60,000
40,000
20,000
0 1 = =
80 85 89 90 91 92 93 94
Notes: Emissions data not available for consecutive years 1980-1989.
Emission estimation methods continue to evolve and improve over time. Methods have
changed for many significant categories beginning with the years 1985, 1990, and 1996 and
consequently are not consistent across all years in this trend period. See Appendix B
Emissions Estimates Methodology for additional information.
Table 2-2. Milestones in Motor Vehicle Emissions Control
1970
New Clean Air Act sets auto
1990
CAAA set new tailpipe
emissions standards.
standards.
1971
Charcoal canisters appear to
1992
Oxyfuel introduced in cities
meet evaporative standards.
with high CO levels.
1973
EGR valves appear to meet
1993
Limits set on sulfur content of
NOx standards.
diesel fuel.
1974
Fuel economy standards are set.
1994
Phase-in begins of new vehicle
1975
The first catalytic converters
standards and technologies.
appear for hydrocarbon, CO.
1995
On-board diagnostic systems
Unleaded gas appears for use in
in 1996 model year cars.
catalyst equipped cars.
1995
Phase I Federal Reformulated
1981
3-way catalysts with on-board
Gasoline sales begin in worst
computers and O2 sensors
ozone nonattainment areas.
appear.
1998
Sales of 1999 model year
1983
I/M programs are established
California emissions equipped
in 64 cities.
vehicles begin in the Northeast.
1989
Fuel volatility limits are set for RVP.
ribbon panel of leading experts from
the public health and scientific com-
munities, automotive fuels industry,
water utilities, and local and state
governments to review the important
issues posed by the use of MTBE and
other oxygenates in gasoline. The
Panel's final report stated that "the
Wintertime Oxyfuel Program contin-
ues to provide a means for some
areas of the country to come into, or
maintain, compliance with the car-
bon monoxide standard. Los Angeles
areas continue to use MTBE in this
program. In most areas today, etha-
nol can, and is, meeting these winter-
14 CRITERIA POLLUTANTS — NATIONAL TRENDS • CHAPTER 2
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 2-7. Highest 2nd maximum non-overlapping 8-hour average CO concentration by county, 1999
Concentration (ppm)
time needs for oxygen without rais-
ing fuel volatility concerns given the
season of the year. The Panel recom-
mends that the Wintertime Oxyfuel
program be continued (a) for as long
as it provides a useful compliance
and/or maintenance tool for the
affected states and metropolitan ar-
eas, and (b) assuming that the clarifi-
cation of state and federal authority
described above is enacted to enable
states, where necessary, to regulate
and/or eliminate the use of gasoline
additives that threaten drinking sup-
plies."6 The Panel's Executive Sum-
mary and final report entitled Achieving
Clean Air and Clean Water: The Report
of the Blue Ribbon Panel on Oxygenates
in Gasoline can be found on the Pan-
el's homepage at: http://
www.epa.gov/otaq/consumer/fuels/
oxypanel/blueribb.htm.
Additionally, on March 20,2000,
the Clinton Administration, based on
the recommendations of the Blue
Ribbon Panel, announced a set of
legislative principles to address con-
cerns about the continued use of
MTBE. The Administration recom-
mended that Congress:
• Amend the CAA to provide the
authority to significantly reduce or
eliminate the use of MTBE.
• Ensure that air quality gains asso-
ciated with the use of MTBE are
not diminished.
• Replace the existing oxygen re-
quirement contained in the CAA
with a renewable fuel standard for
all gasoline.
The Administration stated that it
believed that the principles would
provide an environmentally sound
and cost effective approach to ad-
dressing the risks posed by the cur-
rent use of MTBE. Coincident with
issuance of the legislative principles,
EPA issued an Advance Notice of
Proposed Rulemaking under Section
6 of the Toxic Substances Control Act
(TSCA) to initiate a regulatory pro-
cess to address MTBE risks using
current authorities in the event that
Congress did not act to amend the
CAA.6
1999 Air Quality Status
The map in Figure 2-7 shows the
variations in CO concentrations
across the country in 1999. The air
quality indicator is the largest annual
second maximum 8-hour CO concen-
tration measured at any site in each
county. The bar chart to the left of the
CHAPTER 2 • CRITERIA POLLUTANTS — NATIONAL TRENDS
15
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
map displays the number of people
living in counties within each concen-
tration range. The colors on the map
and bar chart correspond to the col-
ors of the concentration ranges dis-
played in the map legend. Only four
of the 526 monitoring sites reporting
ambient CO data to the Aerometric
Information Retrieval System (AIRS)
failed to meet the CO NAAQS in
1999. These four sites are located in
three counties—Los Angeles County,
CA; Fairbanks Borough, AK; and
Imperial County, CA (Calexico, CA).
The site in this latter area is located
just north of the border crossing with
Mexicali, Mexico. There are 9 million
people living in these three counties,
compared to the 1998 count of six
counties with a total population of 10
million people.
16 CRITERIA POLLUTANTS — NATIONAL TRENDS • CHAPTER 2
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Lead
Air Quality Concentrations
1980-99
94%
decrease
1990-99
60%
decrease
1998-99
no change
Emissions
1980-99
94%
decrease
1990-99
16%
decrease
1998-99
4%
increase
Nature and Sources
Twenty-five years ago, automotive
sources were the major contributor of
lead emissions to the atmosphere. As
a result of EPA's regulatory efforts to
reduce the content of lead in gasoline,
however, the contribution from the
transportation sector, and particular-
ly the automotive sector, has greatly
declined. Though aviation fuels still
contain relatively large amounts of
lead, industrial processes (primarily
metals processing) are the major
source of lead emissions to the atmo-
sphere today. The highest ambient
air concentrations of lead are found
in the vicinity of ferrous and nonfer-
rous smelters, battery manufacturers,
and other stationary sources of lead
emissions.
Health and Environmental
Effects
Exposure to lead occurs mainly
through inhalation and through in-
gestion of lead in food, water, soil, or
dust. It accumulates in the blood,
bones, and soft tissues. Lead can also
adversely affect the kidneys, liver,
nervous system, and other organs.
Excessive exposure to lead may cause
neurological impairments such as
seizures, mental retardation, and/or
behavioral disorders. Lead may be a
factor in high blood pressure and
subsequent heart disease. Addition-
ally, at low doses, fetuses and chil-
dren may suffer from central nervous
system damage. Neurobehavioral
changes (i.e., low I.Q.) may result
from lead exposure during the child's
first years of life.
Airborne lead can also have ad-
verse impacts on the environment.
Wild and domestic grazing animals
may ingest lead that has deposited
on plant or soil surfaces or that has
been absorbed by plants through
leaves or roots. At relatively low
concentrations (2-10 ]Ug/m3), lead
can inhibit plant growth and result in
a shift to more tolerant plant species
growing near roadsides and station-
ary source emissions. See also the
Toxics chapter in this report for a
discussion of the long-term impact of
lead on ecosystem function and sta-
bility.
Primary and Secondary
Standards
The primary as well as secondary
NAAQS for lead is a quarterly aver-
age concentration not to exceed
1.5 ]Ug/m3.
National Air Quality Trends
The statistic used to track ambient
lead air quality is the maximum
quarterly mean concentration for
each year. From 1980-1989, a total of
216 ambient lead monitors met the
trends completeness criteria; and a
total of 175 ambient lead monitors
met the trends data completeness
criteria for the 10-year period 1990-
1999. Point-source oriented monitor-
ing data were omitted from all
ambient trends analysis presented in
this section to avoid masking the
underlying urban trends.
Figure 2-8 indicates that between
1990 and 1999, maximum quarterly
average lead concentrations de-
creased 60 percent at population-
oriented monitors. Between 1998 and
1999, national average lead concen-
trations (approaching the minimum
detectable level) remained un-
changed. The effect of the conversion
to unleaded gasoline usage in ve-
hicles on ambient lead concentra-
tions is most evident when viewed
over a longer period, such as illus-
trated in Figure 2-8. Between 1980
and 1999, ambient monitor data indi-
cate that concentrations of lead de-
clined 94 percent. This large decline
tracks well with overall lead emis-
sions, which also declined 94 percent
between 1980 and 1999.
Figure 2-9 looks at urban, rural,
and suburban 20-year trends sepa-
Worth Noting
• From 1980-1999, there has been a
94-percent decrease in lead emissions with
a corresponding 94-percent decrease in
maximum quarterly average lead
concentrations at population-oriented
monitors.
• Lead emissions are slightly increasing
from 1998-1999 even though lead air
quality continues its "no-change" status
from previous years. Probable cause for the
small emissions increase is increased use
of aviation fuel, which can still contain large
amounts of lead.
• In 1999, only two areas across the
country were violating the lead NAAQS, but
six are still nonattainment for lead. These
areas tend to contain the lead point sources
that had one or more source-oriented
monitors that violated the NAAQS. These
point sources are in Missouri (Doe Run/
Herculeneum plant) and Illinois (Chemetco
facility).
CHAPTER 2 • CRITERIA POLLUTANTS — NATIONAL TRENDS
17
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
rately. The overall downward trend
in lead concentrations can be noted
for all locations from 1980-1999. The
one slight oddity in Figure 2-9 is the
slight upturn in Pb concentration
seen at the rural sites in 1995. One of
the rural sites in Louisiana (in St.
John the Baptist parish) showed a
concentration of 5.8 ]Ug/m3 in Decem-
ber 1995 causing the overall average
to increase to 0.411 (up from normal
levels of about 0.05 ]Ug/m3). Region 6
has been consulted regarding this
issue and they, in turn, contacted the
Louisiana Department of Environ-
mental Quality (LDEQ) to confirm
the high lead reading that occurred
on December 17,1995. LDEQ per-
sonnel have stated that this is a true
reading and that the sampler must
have been influenced by lead-rich
plumes emitted by the industrial
operations that took place at two
nearby facilities: Bayou Steel and a
recycling business.
Regional Air Quality Trends
Figure 2-10 segregates the ambient
trend analysis by EPA region. Al-
though most regions showed large
concentration reductions between
1980 and 1999, there were some inter-
mittent upturns including a rather
large upturn in the Region 1 trends
plot. Most of these "bumps" in the
trends graphs can be attributed to the
inherent variability and noise associ-
ated with data reported near mini-
mum detectable levels.
National Emission Trends
The lead emission estimates present-
ed are a result of data developed for
the National Emission Trends (NET)
criteria database. Lead emissions for
1996 were also estimated in the Na-
tional Toxics Inventory (NTI) and
were used in the nationwide disper-
Figure 2-8. Trend in maximum quarterly average Pb concentrations (excluding point-
source oriented sites), 1980-1999.
3
Concentration, |jg/m
National Standard
.90% of sites have concentrations below this line
216 Sites
0.5
Average
175 Sites
10% of sites hi
ratinnc holpw this line
80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99
Note: When the total number of rural, suburban, and urban sites are summed for
either the 1980-89 or 1990-99 time periods in Figure 2-9, this number may not
equal the total number of sites shown in Figure 2-8 for the same time periods. This is
due to a few monitoring sites falling outside the definitions of rural, suburban, or
urban sites.
Figure 2-9. Pb maximum quarterly mean concentration trends by location (excluding
point-source oriented sites), 1980-1999.
Concentration, pg/m3
0.8
1980-89 1990-99
Rural Sites
Suburban Sites
0.6
Urban Sites
0.4
0.2
80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99
18 CRITERIA POLLUTANTS — NATIONAL TRENDS • CHAPTER 2
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 2-10. Trend in Pb maximum quarterly mean concentration by EPA Region, 1980-1999.
2.05
.04
f 98%
~ 96%
The National Trend
,65V
#96%
.31\
f 87%
.04
.03
194%
Alaska is in EPA Region 10; Hawaii, EPA Region 9; and Puerto Rico, EPA Region 2.
Concentrations are |jg/m3.
f 98%
.46^
# 93%^ _^03
Note: These trends are
influenced by the
distribution of monitoring
locations in a given region
and, therefore, can be
driven largely by urban
concentrations. For this
reason, they are not
indicative of background
regional concentrations.
si on modeling as part of EPA's Na-
tional Air Toxics Assessment (NATA).
For 1996, the NTI estimates would be
the preferred source for data. In the
future, the criteria emissions data-
base (formerly the NET) will be com-
bined with air toxics estimates
(formerly in the NTI) in a single data
base called the National Emissions
Inventory (NEI).
Because of the phase-out of leaded
gasoline, lead emissions (and concen-
trations) decreased sharply during
the 1980s and early 1990s. Figure
2-11 indicates that total lead emis-
sions decreased 16 percent between
1990 and 1999. Figure 2-11 also
shows that lead emissions decreased
94 percent between 1980 and 1999.
The large ambient and emission re-
ductions in lead going from 1980-
1990 can be largely attributed to the
phasing out of leaded gasoline for
automobiles. The magnitude of lead
emission reductions after 1990 is a
waning result of the phase-out of
leaded gasoline use in automotive
sources. The 4-percent increase in
lead emissions from 1998-1999 is
largely attributable to increased use
of aviation gasoline. Aviation gaso-
line is not regulated for lead content
and can use significant amounts of
lead to comply with octane require-
ments for aviation fuel.
Figure 2-12 shows that industrial
processes were the major source of
lead emissions in 1999, accounting
for 75 percent of the total. The trans-
portation sector (which includes both
onroad and nonroad sources) now
accounts for only 13 percent of the
total 1999 lead emissions, with most
of that coming from aircraft.
1999 Air Quality Status
The large reductions in long-term
lead emissions from transportation
sources have changed the nature of
the ambient lead problem in the Unit-
ed States. Because industrial pro-
cesses are now responsible for all
violations of the lead standard, the
lead monitoring strategy now focuses
on emission from these point sources.
The map in Figure 2-13 shows the
lead monitors located in the vicinity
of major sources of lead emissions.
In 1999, two lead point sources had
one or more source-oriented monitors
that violated the NAAQS. These two
sources are the Chemetco plant in
Illinois and the Doe Run (Herculene-
CHAPTER 2 • CRITERIA POLLUTANTS — NATIONAL TRENDS
19
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
urn) plant in Missouri. It should be
noted that the Franklin smelter in
Pennsylvania, which in the past has
emitted large amounts of lead, was
shut down in 1997. These point
sources are ranked in Figure 2-13
according to the site with the greatest
maximum quarterly mean. Various
enforcement and regulatory actions
are being actively pursued by EPA
and the states for cleaning up these
sources.
The map in Figure 2-14 shows the
highest quarterly mean lead concen-
tration by county in 1999. Two areas,
with a total population of approxi-
mately 0.42 million, and containing
the point sources identified in Figure
2-13, did not meet the lead NAAQS in
1999.
Monitoring Status
Due to the shift in ambient air moni-
toring focus from mobile-source
emissions to stationary point sources
of lead air pollution, EPA revised the
lead air monitoring regulations by
publishing a new rule on January 20,
1999. This action was taken at the
direct request of numerous states and
local agencies whose onroad mobile-
source oriented lead monitors have
been reporting peak lead air pollu-
tion values that are many times less
than the quarterly lead NAAQS of
1.5 ]Ug/m3 for a number of consecu-
tive years.
The previous regulation required
that each urbanized area with a
population of 500,000 or more oper-
ate at least two lead National Air
Monitoring Stations (NAMS). The
new rule allows state and local agen-
cies more flexibility. The rule sub-
stantially reduces the requirements
for measuring lead air pollutant con-
centrations near major highways,
Figure 2-11. National total Pb emissions trend, 1980-1999.
Short Tons Per Year
80,000
~ Fuel Combustion ¦ Industrial Processing
~ Transportation
60,000
40,000
20,000
80
85
90 91 92 93 94 95
97 98 99
Notes: Emissions data not available for consecutive years 1980-1989.
Emission estimation methods continue to evolve and improve over time. Methods have
changed for many significant categories beginning with the years 1985, 1990, and 1996 and
consequently are not consistent across all years in this trend period. See Appendix B
Emissions Estimates Methodology for additional information.
Figure 2-12. Pb emissions by source category, 1999.
Fuel Combustion 11.9%
Industrial Processes 75.3%
Transportation 12.8%
Including on-road
and off-road sources.
20 CRITERIA POLLUTANTS — NATIONAL TRENDS • CHAPTER 2
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 2-13. Pb maximum quarterly concentration in the vicinity of Pb point sources, 1999.
Rank ST Emission Source
1 MO Doe Run (Herculeneum)
Max. Qtr. Avg. (ug/m3)
6.75
IL Chemetco
Figure 2-14. Highest Pb maximum quarterly mean by county, 1999
Concentration (ug/m3)
CHAPTER 2 • CRITERIA POLLUTANTS — NATIONAL TRENDS 21
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
thus shifting the focus to point
sources and their impact on neigh-
boring populations. The regulation
also allows states to reduce the num-
ber of NAMS from approximately 85
to approximately 15. This reduction
will still retain adequate monitoring
to ensure attainment of the NAAQS,
but it allows efficient refocusing of
available monitoring.
22 CRITERIA POLLUTANTS — NATIONAL TRENDS • CHAPTER 2
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Nitrogen Dioxide
Air Quality Concentrations
1980-99 25% decrease
1990-99 10% decrease
1998-99 no change
Emissions
1980-99 4% increase
1990-99 5% increase
1998-99 2% decrease
Worth Noting
• Over the past 20 years, nitrogen dioxide
(N02) concentrations across the country
have decreased significantly.
• All areas of the country that once
violated the national air quality standard for
N02 now meet that standard.
• The last N02 nonattainment area, Los
Angeles, was redesignated to attainment in
July 1998.
Nature and Sources
Nitrogen dioxide is a reddish brown,
highly reactive gas that is formed in
the ambient air through the oxidation
of nitric oxide (NO). Nitrogen oxides
(NOx), the term used to describe the
sum of NO, N02 and other oxides of
nitrogen, play a major role in the
formation of ozone in the atmosphere
through a complex series of reactions
with volatile organic compounds
(VOCs). A variety of NOx com-
pounds and their transformation
products occur both naturally and as
a result of human activities. Anthro-
pogenic (i.e., man-made) emissions of
NOx account for a large majority of
all nitrogen inputs to the environ-
ment. The major sources of anthropo-
genic NOx emissions are
high-temperature combustion pro-
cesses, such as those occurring in
automobiles and power plants.
Most of NOx from combustion
sources (about 95 percent) is emitted
as NO; the remainder is largely
N02. Because NO is readily con-
verted to N02 in the environment,
the emissions estimates reported
here assume nitrogen oxides are in
the N02 form. Natural sources of
NOx are lightning, biological and
abiological processes in soil, and
stratospheric intrusion. Ammonia
and other nitrogen compounds
produced naturally are important in
the cycling of nitrogen through the
ecosystem. Home heaters and gas
stoves also produce substantial
amounts of N02 in indoor settings.
Health and Environmental
Effects
Nitrogen dioxide is the most wide-
spread and commonly found nitro-
gen oxide and is a matter of public
health concern. The health effects of
most concern associated with short-
term exposures (i.e., less than three
hours) to N02 at or near the ambi-
ent N02 concentrations seen in the
United States, include cough and
increased changes in airway respon-
siveness and pulmonary function in
individuals with preexisting respira-
tory illnesses, as well as increases in
respiratory illnesses in children 5-12
years old.7'8 Evidence suggests that
long-term exposures to N02 may
lead to increased susceptibility to
respiratory infection and may cause
structural alterations in the lungs.
Atmospheric transformation of
NOx can lead to the formation of
ozone and nitrogen-bearing par-
ticles (e.g., nitrates and nitric acid).
As discussed in the ozone and PM
sections of this report, exposure to
both PM and ozone is associated
with adverse health effects.
Nitrogen oxides contribute to a
wide range of effects on public wel-
fare and the environment, including
global warming and stratospheric
ozone depletion. Deposition of nitro-
gen can lead to fertilization, eutrophi-
cation, or acidification of terrestrial,
wetland and aquatic (e.g., fresh water
bodies, estuaries, and coastal water)
systems. These effects can alter com-
petition between existing species,
leading to changes in the number and
type of species (composition) within a
community. For example, eutrophic
conditions in aquatic systems can
produce explosive algae growth lead-
ing to a depletion of oxygen in the
water and/or an increase in levels of
toxins harmful to fish and other
aquatic life.
Primary and Secondary
Standards
The level for both the primary and
secondary NAAQS for N02 is 0.053
ppm annual arithmetic average
(mean), not to be exceeded. In this
report, the annual arithmetic average
(mean) concentration is the metric
used to evaluate and track ambient
N02 air quality trends.
National Air Quality Trends
Nationally, annual mean N02 concen-
trations have decreased approximate-
ly 25 percent since 1980.9 As
discussed in previous sections of this
report, long-term national ambient air
quality trends are difficult to assess
because few monitoring sites have
operated continuously in the same
location for 20 years. Figure 2-15
presents 20-year trends in ambient
N02 concentrations by combining
two separate 10-year trends databas-
es, 1980-1989 (156 sites) and 1990-
1999 (230 sites). Annual mean N02
concentrations declined in the early
CHAPTER 2 • CRITERIA POLLUTANTS — NATIONAL TRENDS
23
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
1980s, were relatively unchanged
during the mid-to-late 1980s, and
resumed their decline in the 1990s.
Figure 2-15 shows that the national
composite annual mean N02 concen-
tration in 1999 is 10 percent lower
than that recorded in 1990, and is
unchanged from the 1998 level. Ex-
cept for 1994, N02 concentrations
have decreased, or remained un-
changed, each year since 1989.
Figure 2-16 reveals how the trends
in annual mean N02 concentrations
vary among rural, suburban and
urban locations. The highest annual
mean N02 concentrations are typi-
cally found in urban areas, with sig-
nificantly lower annual mean
concentrations recorded at rural sites.
The 1999 composite mean at 137
urban sites is 24 percent lower than
the 1980 level, compared to a 27-per-
cent reduction at 180 suburban sites.
At 66 rural sites, the composite mean
N02 concentration in 1999 is the
same as it was in 1980.
Interestingly, at the same time the
nation has experienced these signifi-
cant decreases in N02 air quality,
nitrogen oxide emissions are increas-
ing, as described in more detail later
in this section of the chapter. One
possible explanation involves the
location of the majority of the
nation's N02 monitors. Most N02
monitoring sites are mobile-source
oriented sites in urban areas, and the
20-year decline in ambient N02 levels
closely tracks the 19-percent reduc-
tion in emissions from gasoline pow-
ered vehicles over the same time
period. However, nitrogen chemistry
in the atmosphere is non-linear and,
therefore, a change in NOx emissions
may not have a proportional change
in ambient concentrations of N02.
The relationship between emissions
and ambient air quality levels is de-
Figure 2-15. Trend in annual N02 mean concentrations, 1980-1999.
Concentration, ppm
0.06
0.05
0.04
0.03
0.02
0.01
0
80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99
Note: When the total number of rural, suburban, and urban sites are summed for either the
1980-89 or 1990-99 time periods in Figure 2-16, this number may not equal the total
number of sites shown in Figure 2-15 for the same time periods. This is due to a few
monitoring sites falling outside the definitions of rural, suburban, or urban sites.
Figure 2-16. Trend in annual mean N02 concentrations by type of location, 1980-1999.
Concentration, ppm
0.035
0.030
0.025
0.020
0.015
0.010
0.005
0.000
80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99
National Standard
90% of sites have concentrations below this line
230 Sites
A
Average
A
10% of sites have concentrations below this line
1980-89
23
1990-99
43
-
Rural Sites
Suburban Sites
75
105
Urban Sites
57
80
24 CRITERIA POLLUTANTS — NATIONAL TRENDS • CHAPTER 2
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 2-17. Trend in N02 maximum quarterly mean concentration by EPA Region, 1980-1999.
Insufficient
Trend Data
.031
_.019
f 39%
The National Trend
.024
.018
#• 25%
¦013^ £13
0%
.019
.022
.029
.027
.029
.019
4 16%
.oie^^^oi7
1 6%
¦017_ .014
f 18%
f 7%
f 34%
,024^
f.21% -019
.018
.014
# 22%
Note: These trends are
influenced by the
distribution of monitoring
locations in a given region
and, therefore, can be
driven largely by urban
concentrations. For this
reason, they are not
indicative of background
regional concentrations.
Alaska is in EPA Region 10; Hawaii, EPA Region 9; and Puerto Rico, EPA Region 2. Concentrations are ppm.
pendent on a number of factors such
as concentrations of compounds
which react with NOx emissions (e.g.,
free radicals and VOCs) as well as
the form and concentration of various
nitrogen compounds in the area be-
ing monitored. For example, an area
could experience improving N02 air
quality in conjunction with increased
NOx emissions, if the emissions are
rapidly converted to nitrates, a form
of atmospheric nitrogen not detected
by the N02 monitors. Alternatively,
if levels of the compounds which
react with NOx emissions to form
ambient N02 are declining, increased
NOx emissions may not translate into
elevated levels of converted N02.
Regional Air Quality Trends
The map in Figure 2-17 provides
regional trends in N02 concentra-
tions during the past 20 years, 1980-
1999 (except Region 10 which does
not have any N02 trend sites). The
trends statistic is the regional com-
posite mean of the N02 annual mean
concentrations across all sites with at
least eight years of ambient measure-
ments. The largest reductions in N02
concentrations occurred in the south
coast of California and the New En-
gland states. Smaller reductions in
mean N02 concentrations were re-
corded in the Mid-Atlantic, South-
east, and Southwest. Interestingly,
N02 concentrations have actually
increased in both the North Central
and Midwest states. This increase in
air quality levels coincides with in-
creases in nitrogen oxide emissions
from transportation (both onroad and
nonroad) as well as power plants in
selected states with N02 monitors in
these areas.
National Emissions Trends
Nationally, emissions of nitrogen
oxides have increased over the last 20
years by 4 percent and by 5 percent
over the most recent 10-year period
from 1990 to 1999. Figure 2-18 shows
the temporal trend in NOx emissions
nationwide. These increases are the
result of a number of factors, the largest
being an increase in nitrogen oxides
emissions from transportation sources.
Figure 2-19 indicates that the two
primary sources of NOx emissions
are stationary source fuel combustion
and transportation. Together, these
two sources comprise 95 percent of
1999 total NOx emissions. Emissions
from transportation sources have
increased over the last 20 years (16
CHAPTER 2 • CRITERIA POLLUTANTS — NATIONAL TRENDS
25
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
percent) and during the past 10 years
(17 percent). For both light duty
gasoline vehicles and light duty gaso-
line trucks, NOx emissions peaked in
1994, and then began a steady de-
crease through 1999. This decrease
can be attributed primarily to the
implementation of the Tier 1 emission
standards which lowered NOx emis-
sions from new cars and light duty
trucks. In contrast, NOx emissions
from heavy duty vehicles, both gaso-
line and diesel increased significantly
over the 10-year period (50 percent
for gasoline and 61 percent for die-
sel). A portion of this increase is due
to the increase in VMT for these cat-
egories (104 percent for heavy duty
gasoline vehicles and 99 percent for
heavy duty diesel trucks). In addi-
tion, emissions from heavy duty
diesel vehicles increased over this
period due to the identification of
"excess emissions" in many of these
vehicles. New emission standards
will lead to reductions in emissions
from heavy duty vehicles in the fu-
ture. Further, emissions from off-
road vehicles particularly those
diesel-fueled have steadily increased
over the last 10 years.
Reductions in NOx emissions from
fuel combustion have partially offset
the impact of increases in the transpor-
tation sector. Emissions from electric
utility fuel combustion sources have
declined over the 20-year period
1980-1999 (11 percent) and over the
10-year period from 1990-1999
(8 percent). The Acid Deposition
Control provisions of the CAA (Title
IV) required EPA to establish NOx
annual emission limits for coal-fired
electric utility units in two phases
resulting in NOx reductions of approxi-
mately 400,000 tons per year during
Phase I (1996-1999) and two million
Figure 2-18. Trend in national total NOx emissions, 1980-1999.
Thousand Short Tons Per Year
30,000
25,000
~ Fuel Combustion ¦ Industrial Processing
~Transportation ~Miscellaneous
20,000
15,000
10,000
5,000
^ In 1985, EPA refined its methods for estimating emissions.
80
85
90 91 92 93 94 95 96 97 98 99
Notes: Emissions data not available for consecutive years 1980-1989.
Emission estimation methods continue to evolve and improve over time. Methods have
changed for many significant categories beginning with the years 1985, 1990, and 1996 and
consequently are not consistent across all years in this trend period. See Appendix B
Emissions Estimates Methodology for additional information.
Figure 2-19. NOx emissions by source category, 1999.
Fuel Combustion 39.5%
Industrial Processes 3.7%
Miscellaneous 1.
Transportation 55.5%
26 CRITERIA POLLUTANTS — NATIONAL TRENDS • CHAPTER 2
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 2-20. Density map of 1999 nitrogen dioxide emissions, by county.
Tons/Year/Sq Mile
0-1.72
1.72-3.36
~ 3.36 - 6.24
H 6.24 -14.64
H 14.64 - 2785.93
tons per year in Phase II (year 2000 and
subsequent years).10
Figure 2-20 shows the geographic
distribution of 1999 NOx emissions
based on the tonnage per square mile
for each county. This map illustrates
that the eastern half of the country
and the west coast emit more NOx
(on a density basis) than the western
half of the continental United States.
1999 Air Quality Status
All monitoring locations across the
nation, including Los Angeles, met the
N02 NAAQS in 1999. This is reflected
on the map in Figure 2-21 that displays
the highest annual mean N02 concen-
tration measured in each county.
CHAPTER 2 • CRITERIA POLLUTANTS — NATIONAL TRENDS
27
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 2-21. Highest N02 annual mean concentration by county, 1999
Concentration (ppm)
28 CRITERIA POLLUTANTS — NATIONAL TRENDS • CHAPTER 2
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Ozone
Air Quality Concentrations
1980-99
20% decrease (1-hr)
12% decrease (8-hr)
1990-99
4% decrease (1-hr)
no change (8-hr)
1989-99
3% decrease (1-hr)
1% decrease (8-hr)
Emissions (Anthropogenic VOCs)
1980-99
31% decrease
1990-99
14% decrease
1998-99
3% decrease
Worth Noting
• Over the last 20 years, ozone (03)
levels (1-hour and 8-hour) have improved
considerably nationwide.
• Rate of improvement, however,
appears to have slowed recently.
• Some parts of the country show
increases in 03 levels over the last 10
years, due largely to increased NOx
emissions and weather conditions favorable
to 03 formation.
• Trends for selected urban areas after
adjusting for meteorological conditions
show slowing progress since the mid-1990s.
• 03 levels in urban areas, however,
where the 03 problem has historically been
the most severe, have shown marked
improvement in response to stringent
control programs.
• Rural 03 levels appear to be increasing
in the short term.
- 1 -hour levels are higher than those
seen in urban areas for the second
consecutive year.
- 8-hour levels increasing
nationally over the last 10 years.
- Trends in 8-hour levels at
CASTNet sites up since 1990.
- 8-hour levels in a number of
the nation's national parks are
showing significant increases
since 1990.
Nature and Sources
Ground level 03 remains a pervasive
pollution problem in the United
States. Ozone is readily formed in the
atmosphere by the reaction of VOCs
and NOx in the presence of heat and
sunlight, which are most abundant in
the summer. VOCs are emitted from
a variety of sources including: motor
vehicles, chemical plants, refineries,
factories, consumer and commercial
products, other industries, and natu-
ral (biogenic) sources. Nitrogen ox-
ides are emitted from motor vehicles,
power plants, and other sources of
combustion, and natural sources
including lightning and biological
processes in soil. Changing weather
patterns contribute to yearly differ-
ences in 03 concentrations. Ozone
and the precursor pollutants that
cause 03 also can be transported into
an area from pollution sources locat-
ed hundreds of miles upwind.
Health and Environmental
Effects
Ozone occurs naturally in the strato-
sphere and provides a protective
layer high above the Earth. Howev-
er, at ground level, it is the prime
ingredient of smog. Short-term (1-3
hours) and prolonged (6-8 hours)
exposures to ambient 03 concentra-
tions have been linked to a number of
health effects of concern. For exam-
ple, increased hospital admissions
and emergency room visits for respi-
ratory causes have been associated
with ambient 03 exposures.
Exposures to O3 result in lung
inflammation, aggravate preexisting
respiratory diseases such as asthma,
and may make people more suscep-
tible to respiratory infection. Other
health effects attributed to short-term
and prolonged exposures to 03,
generally while individuals are en-
gaged in moderate or heavy exertion,
include significant decreases in lung
function and increased respiratory
symptoms such as chest pain and
cough. Children active outdoors
during the summer when 03 levels
are at their highest are most at risk of
experiencing such effects. Other at-
risk groups include adults who are
active outdoors, such as outdoor
workers, and individuals with preex-
isting respiratory disorders such as
asthma and chronic obstructive lung
disease. Within each of these groups
are individuals who are unusually
sensitive to 03. In addition, repeated
long-term exposure to 03 presents
the possibility of irreversible changes
in the lungs which could lead to pre-
mature aging of the lungs and/or
chronic respiratory illnesses.
Ozone also affects sensitive veg-
etation and ecosystems. Specifically,
03 can lead to reductions in agricul-
tural and commercial forest yields,
reduced survivability of sensitive tree
seedlings, and increased plant sus-
ceptibility to disease, pests, and other
environmental stresses such as harsh
weather. In long-lived species, these
effects may become evident only after
several years or even decades. As
these species are out-competed by
others, long-term effects on forest
ecosystems and habitat quality for
wildlife and endangered species
occurs. Furthermore, 03 injury to the
foliage of trees and other plants can
decrease the aesthetic value of orna-
mental species as well as the natural
beauty of our national parks and
recreation areas.
Primary and Secondary 1-hour
Ozone Standards
In 1979, EPA established 1-hour pri-
mary and secondary standards for
03. The level of the 1-hour primary
CHAPTER 2 • CRITERIA POLLUTANTS — NATIONAL TRENDS
29
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
and secondary 03 NAAQS is 0.12
ppm daily maximum 1-hour concen-
tration that is not to be exceeded
more than once per year on average.
To encourage an orderly transition to
the revised 03 standards (promulgat-
ed in 1997; see following section for
more information), EPA initiated a
policy in which the 1-hour standards
would no longer apply once an area
experienced air quality data meeting
the 1-hour standards. In 1998 and
early 1999, EPA revoked the 1-hour
03 NAAQS in 2,942 counties in the
United States, leaving 201 counties
where the 1-hour standard still ap-
plies.11' 12<13 However, due to unre-
solved legal challenges, the Agency is
unable to enforce and effectively
implement the 8-hour standard. As a
result, many areas were without
applicable air quality standards ade-
quate to ensure public health and
welfare. Therefore, in July 2000, EPA
reinstated the 1-hour standard nation-
wide to alleviate this unanticipated
policy outcome and provide protection
of public health and welfare.14
Primary and Secondary 8-hour
Ozone Standards
On July 18,1997, EPA strengthened
the 03 NAAQS based on the latest
scientific information showing ad-
verse effects from exposures allowed
by the then existing standards. The
standard was set in terms of an
8-hour averaging time.15 Numerous
industry and environmental petition-
ers, including the American Trucking
Associations (ATA), challenged the
03 and the new PM15 standards in
the United States Court of Appeals
for the District of Columbia Circuit.
On May 14,1999, a three-judge panel
of that court concluded that EPA's
interpretation of the Clean Air Act
unconstitutionally delegated legisla-
Figure 2-22. Trend in annual 2nd-highest daily maximum 1-hour, and 4th-highest daily
8-hour 03 concentrations, 1980-1999.
Concentration, ppm
0.2
90% of sites have concentrations below this line
0.15
Average
National'Standard
441 Sites
0.1
703 Sites
10% of sites have concentrations below this line
0.05
80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99
tive power to EPA and remanded the
standards to EPA. EPA appealed that
ruling, and on February 27,2001, the
Supreme Court unanimously upheld
the constitutionality of Clean Air Act
section 109 and affirmed EPA's ability
to set NAAQS based solely on public
health and welfare factors, without
consideration of costs, which are
considered in the implementation of
the standards. The court rejected the
D.C. Circuit's conclusion that EPA's
interpretation of the implementation
provisions violated the statute's clear
terms, but nevertheless remanded the
implementation policy to EPA on the
basis that EPA's policy was not a
reasonable interpretation of ambigu-
ous statutory language. Because the
D.C. Circuit originally remanded, but
did not vacate the 03 and PM2.5 stan-
dards, they have remained legally
effective throughout the ongoing
litigation. The case has now been
returned to the Court of Appeals,
where the remaining issues are to be
considered in accordance with the
decision of the Supreme Court.
For a variety of reasons, EPA has
not yet taken actions to implement
either standard. EPA is currently
reviewing the results of the litigation
and will be conferring with states
and other interested parties to deter-
mine the approach and schedule for
moving forward with implementing
the 03 NAAQS. Refer to http://
www.epa.gov/airlinks for up-to-date
information concerning actions sur-
rounding the revised standards.
Air Quality Trends
Because the 1-hour and 8-hour
NAAQS have different averaging
times and forms, two different statis-
tics are used in this report to track
ambient 03 air quality trends. For
the 1-hour 03 NAAQS, this report
uses the composite mean of the annu-
al second-highest daily maximum
30 CRITERIA POLLUTANTS — NATIONAL TRENDS • CHAPTER 2
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 2-23. Trend in 4th-highest daily 8-hour 03 concentrations, 1980-1999.
Concentration, ppm
0.2
0.15
90% of sites have concentrations below this line
Average
0.1
705 Sites
National Standard
441 Sites
10% of sites have concentrations below this line
0.05
80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99
1-hour 03 concentration as the statis-
tic to evaluate trends. For the 8-hour
03 NAAQS, the report relies on the
annual fourth-highest 8-hour daily
maximum 03 concentration as the
statistic of interest to assess trends.
National Air Quality Trends
Figure 2-22 clearly shows that, over
the past 20 years, peak 1-hour 03
concentrations have declined consid-
erably at monitoring sites across the
country. From 1980 to 1999, national
1-hour 03 levels improved 20 percent
with 1980, 1983, 1988 and 1995 repre-
senting peak years for this pollutant.
Because only a few sites have moni-
tored continuously for two decades,
the 20-year trends line in Figure 2-22
is composed of two segments—441
sites with complete data during the
first 10 years (1980-1989) and 705
sites meeting the data completeness
criteria in the most recent 10 years
(1990-1999). It is important to inter-
pret such long-term, quantitative
ambient 03 trends carefully given
changes in network design, siting
criteria, spatial coverage and moni-
toring instrument calibration proce-
dures during the past two decades.
More recently, national 1-hour 03
levels have continued to improve but
the progress has been less rapid evi-
denced by the 4-percent decrease
from 1990-1999.
Figure 2-23 shows the national
trend in 8-hour 03 concentrations
across the same sites used to estimate
the national 1-hour 03 trends. As
was the case with the 1-hour graphic,
the 20-year trends line in Figure 2-23
is composed of two segments—441
sites with complete data during the
first 10 years (1980-1989) and 705
sites meeting the data completeness
criteria in the most recent 10 years
(1990-1999). Nationally, 8-hour lev-
els have decreased 12 percent over
the last 20 years with even more
substantial improvement (18 percent)
at higher concentration sites (as
shown by the 90th percentile). How-
ever, just as is true for the 1-hour
levels, the progress in 8-hour 03 lev-
els over last 10 years has dampened
with no change in national levels
between 1990 and 1999. The trend in
the 8-hour 03 statistic is similar to the
trend in the 1-hour values, although
the concentration range is smaller.
Regional Air Quality Trends
The maps in Figures 2-24 and 2-25
examine the trend in 1-hour and
8-hour 03 concentrations during the
past 20 years by geographic region of
the country. The 03 levels (both
1-hour and 8-hour) in all areas have
generally followed the pattern of
declining trends since 1980 similar to
that of the national observations.
However, the magnitude of improve-
ment has not been consistent across
all Regions. The most pronounced
declines in 03 levels have occurred in
the Northeast and West, while the
Southeast has evidenced the least
improvement. Further, over the last
10 years, 03 concentrations (both
1-hour and 8-hour) in the Mid-Atlan-
tic, Southeast, Midwest and North
Central regions of the country have
actually increased. These increases
appear to be explained by weather
conditions more conducive to 03
formation (i.e., higher summer tem-
peratures and drier conditions) in
1999 relative to 1990 paired with
increased NOx emissions in many of
the affected states (except the Mid-
Atlantic region which seems to have
been most affected by more condu-
cive meteorological conditions).
In Figure 2-26, the national 1-hour
03 trend is disaggregated to show the
20-year change in ambient 03 concen-
trations among rural, suburban, and
CHAPTER 2 • CRITERIA POLLUTANTS — NATIONAL TRENDS
31
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 2-24. Trend in 2nd highest daily 1-hour 03 concentration by EPA Region, 1980-1999.
095
f 23%
.102
.086
#16%
~ 12%
¦ 1« .
f 19%
.115
¦16^A~/13
~ 30%
.164
\A\
-^03
~ 37%
¦^\^.1°1
#14%
133 A
.120
#10%
.131
.112
# 15%
^109
# 6%
The National Trend
.134
# 20%
.107
Alaska is in EPA Region 10; Hawaii, EPA Region 9; and Puerto Rico, EPA Region 2. Concentrations are ppm.
Figure 2-25. Trend in 4th highest daily 8-hour 03 concentration by EPA Region, 1980-1999.
J 9%
¦0^La^°88
f4%
.106 . 113^A
"^-V^S3 J2:
# 12%
.087
22%
.109
.079
~ 28%
~2§°
#8%
¦09J
*A,
1%
.096
.093
_ .086
f 8%
.089 ^
0%
The National Trend
J»5
#12%
Alaska is in EPA Region 10; Hawaii, EPA Region 9; and Puerto Rico, EPA Region 2.
Concentrations are ppm.
Note: These trends are
influenced by the
distribution of monitoring
locations in a given region
and, therefore, can be
driven largely by urban
concentrations. For this
reason, they are not
indicative of background
regional concentrations.
32 CRITERIA POLLUTANTS — NATIONAL TRENDS • CHAPTER 2
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 2-26. Trend in annual 2nd-highest daily maximum 1-hour 03 concentrations by
location, 1980-1999.
Concentration, ppm
0.14
0.12
0.10
0.08
0.06
1980-89 1990-99
121
0.04
Rural Sites
239
Suburban Sites 215
325
0.02
Urban Sites
121
0.00
80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99
Note: When the total number of rural, suburban, and urban sites are summed for either the
1980-89 or 1990-99 time periods in Figure 2-26, this number may not equal the total
number of sites shown in Figure 2-22 for the same time periods. This is due to a few
monitoring sites falling outside the definitions of rural, suburban, or urban sites.
Figure 2-27. Comparison of actual and meteorologically adjusted 1 -hour 03 trends,
1980-1999.
Concentration, ppm
0.15
0.10
0.05
0.00
80 82 84 86 88 90 92 94 96 98
National Trend in Annual 2nd Maximum 1-Hour Concentrations
(1980-1989: 441 sites; 1990-1999: 705 sites)
Selected Area Trend in Average Daily Maximum 1-Hour Concentrations
f (53 Metropolitan Areas)
Meteorolically Adjusted Trend in Average Daily Maximum 1-Hour Concentrations
(53 Metropolitan Areas)
urban monitoring sites. The highest
ambient 03 concentrations are typi-
cally found at suburban sites, consis-
tent with the downwind transport of
emissions from the urban center.
During the past 20 years, 03 concen-
trations decreased by 20 percent at
540 suburban sites, and 25 percent at
217 urban sites. However, at 360 rural
sites, 1-hour 03 levels for 1999 are
only 14 percent lower than the 1980
level and, for the second consecutive
year, are greater than the level ob-
served for urban sites.
Urban Area Air Quality Trends
Figure 2-27 presents the meteorologi-
cally-adjusted trend in 1-hour 03
concentrations for 53 metropolitan
areas between 1980 and 1999. Ambi-
ent 03 trends are influenced by year-
to-year changes in meteorological
conditions, population growth,
changes in emissions levels from
ongoing control measures as well as
the relative levels of 03 precursors
VOCs and NOx. As discussed in
previous Trends Reports, EPA uses a
statistical model to adjust data on the
annual rate of change in 03 from
individual metropolitan areas to
account for meteorological impacts,
including surface temperature and
wind speed.16 As seen in this figure,
after adjusting for meteorological
conditions, 1-hour 03 levels in these
selected areas show steady improve-
ment from 1980 through the mid-
1990s. The adjusted 03 levels
decreased an average of 1 percent
annually through 1994. However,
beginning in 1994, the improvement
appears to slow. Since the mid-1990s,
national 1-hour 03 levels adjusted to
account for variable weather condi-
tions are nearly unchanged.
However, urban areas with the
most severe and persistent 03 prob-
CHAPTER 2 • CRITERIA POLLUTANTS — NATIONAL TRENDS
33
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
lems (i.e., those classified as extreme,
severe, and serious 03 nonattainment
areas) show decreases in 1-hour 03
concentrations between 1990 and
1999 (12 percent) and between 1995
and 1999 (10 percent). These de-
clines, based on data from sites in the
areas required to operate the Photo-
chemical Assessment Monitoring
Stations (PAMS) network, are consis-
tent with, but more pronounced than,
the 4-percent improvement seen
nationwide (at the 705 trend sites).17
Areas with PAMS networks are
shown in Figure 2-28. In addition to
Table 2-3. Summary of Changes in
Summer 6-9 a.m. Mean Concentrations
of NOx and TNMOC at PAMS Sites
Figure 2-28. Areas with PAMS networks.
Springfield
Chicago
Santa Barbara
# of
Median
Total
Up
Down
Change
1998-99 (all sites)
NOx 58
10
11
2%
TNMOC 42
2
14
-8%
1995-99 (all sites)
NOx 34
9
9
-6%
TNMOC 17
0
10
-24%
1995-99 (type 2 sites)
NOx 17
3
5
-4%
TNMOC 11
0
6
-24%
Note: 1. The numbers shown in the "Up"
and "Down" columns refer to the number of
sites in which the change in summer 6-9
a.m. mean concentrations between 1995
and 1999 is statistically significant. The
total number of sites ("Total") may not equal
the sum of the corresponding "Up" and
"Down" categories.
2. PAMS type 2 sites are monitoring sites
located to detect the maximum downwind
ozone precursor emissions impacts.
measuring 03 levels, PAMS sites
include measurements of NOx, total
non-methane organic compounds
(TNMOC), a target list of VOC spe-
cies including several carbonyls, plus
surface and upper air meteorology
during summer months when
weather conditions are most condu-
cive to 03 formation. Table 2-3 shows
Figure 2-29. A comparison of the median change
of the most abundant VOC species measured at al
from 1995 and 1999.
~ All Sites II Type 2 Sites
in summer morning concentrations
I PAMS sites and PAMS type 2 sites
Number of Sites
All Sites Type 2 Sites
Isopentane
Propane
Toluene
Ethane
n-Pentane
n-Butane
Ethylene
m&p-Xylenes
2-methylpentane
Isobutane
Acetylene
Benzene
Propylene
2,2,4-trimethylpen
3-Methylpentane
Isoprene
1,2,4-trimethylben
Methylcyclopentane
o-Xylene
3-methylhexane
Ethyl benzene
m-Ethyltoluene
2,3-dimethylpentan
n-Heptane
Total
Up/Down
Total
Up/Down
19
0/9
11
0/3
21
0/7
12
0/2
21
0/10
12
0/4
21
1/10
12
1/5
20
1/11
12
0/5
21
0/12
12
0/5
21
1/12
12
0/7
19
1/9
12
0/6
21
2/10
12
1/4
21
2/10
12
2/4
21
0/13
12
0/7
21
1/14
12
1/8
21
1/13
12
0/6
21
2/11
12
1/6
21
3/8
12
2/4
20
2/12
12
0/7
21
5/5
12
4/3
21
4/15
12
1/9
21
2/10
12
0/6
?1
0/14
12
0/9
?1
2/9
12
0/5
?1
1/12
12
0/7
18
2/8
10
1/4
21
2/8
1?
1/4
21
1/8
12
0/5
-45 -30 -15 0 15 30 45
Percent Change
Notes: 1. The numbers shown in the "Up" and "Down" columns refer to the number of sites
in which the change in summer 6-9 a.m. mean concentrations between 1995 and 1999 is
statistically significant. The total number of sites "Total" may not equal the sum of the
corresponding "Up" and "Down" categories.
2. Results for formaldehyde and acetaldehyde (both carbonyl compounds) were not
included in this analysis because of sampling issues with carbonyl compounds in the PAMS
network. EPA is continuing to assess the issues for further comparison of the
measurements.
3. Results for acetone and isoprene were not included due to lack of consistency in analytic
results.
34 CRITERIA POLLUTANTS — NATIONAL TRENDS • CHAPTER 2
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 2-30. Trend in 4th-highest daily 8-hour 03 based on 34 CASTNet sites in the
rural eastern United States, 1980-1999.
Concentration fopb^
120
110
100
90
80
70
- 90th Percentile
- Median
- Mean
- 10th Percentile
34 Sites
90 91 92 93 94 95 96 97 98 99
changes in summer 6:00-9:00 a.m.
TNMOC and NOx concentrations for
selected PAMS sites.18 Morning NOx
concentrations showed a median
decline of 6 percent between 1995
and 1999 across 34 PAMS sites, while
summer morning TNMOC concen-
trations registered a median decline
of 24 percent across 17 PAMS sites.
Figure 2-29 presents the median
changes in summer morning concen-
trations of the most abundant VOC
species measured at PAMS sites.19
All 24 compounds included in this
analysis showed declines in median
values between 1995 and 1999.
Rural Area Air Quality Trends
Figure 2-30 presents the trend in
8-hour 03 concentrations for 34 rural
sites from the Clean Air Status and
Trends Network (CASTNet) for the
Figure 2-31. Trend in annual 4th-highest daily maximum 8-hour 03 concentrations in National Parks, 1980-1999.
0.052
Voyageurs, MN
0.083 0.098 0.092 0.106
Mammoth Cave, KY Great Smoky Mountains, TN
0.094
Cowpens, SC
0.080
0.060
Cape Romain, SC
0.057 0.064
Big Bend, TX
0.060
Everglades, FL
T Indicates a statistically significant upward trend. Otherwise the trend was not statistically significant. Concentrations are ppm.
CHAPTER 2 • CRITERIA POLLUTANTS — NATIONAL TRENDS 35
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
most recent 10-year period, 1990-
1999.20 The 8-hour 03 concentrations
at these eastern sites, which were the
highest during the hot and dry sum-
mers of 1991 and 1998, have in-
creased 2 percent over the last 10
years and register no significant
change from 1997-1998. This trend in
8-hour 03 levels at 34 selected sites is
mirrored at other rural sites nation-
wide. Across the nation, rural 8-hour
03 levels improved 9 percent from
1980-1999, but increased by 2 percent
over the last 10 years.21
Figure 2-31 further examines pat-
terns in rural 03 levels by presenting
the 10-year trends in the 8-hour 03
concentrations at seven selected Na-
tional Park Service (NPS) sites.22
These sites are located in Class I ar-
eas, a special subset of rural environ-
ments (all national parks and
wilderness areas exceeding 5,000
acres) accorded a higher degree of
protection under the CAA provisions
for the prevention of significant dete-
rioration. There are more than 26
NPS sites nationally; however, this
analysis focuses on the specific sites
with sufficient data to evaluate
10-year trends. Over the last 10
years, 8-hour 03 concentrations in 25
of our national parks increased
nearly 8 percent. Nine monitoring
sites in eight of these parks experi-
enced statistically significant upward
trends in 8-hour 03 levels: Great
Smoky Mountain (TN), Big Bend
(TX), Cape Romain (SC), Cowpens
(SC), Denali (AK), Everglades (FL),
Mammoth Cave (KY), and Voyageurs
(MN). For the remaining 17 parks,
8-hour 03 levels at eight increased
only slightly between 1990 and 1999,
while seven showed decreasing lev-
els and two were unchanged.
Figure 2-32. Trend in national total anthropogenic VOC emissions, 1980-1999.
Thousand Short Tons Per Year
30,000
25,000
~ Fuel Combustion ¦ Industrial Processing
~ Transportation ~Miscellaneous
20,000
15,000
10,000
5,000
90 91 92 93 94 95 96 97 98
Notes: Emissions data not available for consecutive years 1980-1989.
Emission estimation methods continue to evolve and improve over time. Methods have
changed for many significant categories beginning with the years 1985, 1990, and 1996 and
consequently are not consistent across all years in this trend period. See Appendix B
Emissions Estimates Methodology for additional information.
Figure 2-33. Anthropogenic VOC emissions by source category, 1999.
Industrial Processes 44.1%
Fuel Combustion 5.0%
Miscellaneous 3.9%
Transportation 47.0%
36 CRITERIA POLLUTANTS — NATIONAL TRENDS • CHAPTER 2
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table 2-4. Biogenic Sources of VOC Emissions By Region
Region
VOC
Source
Southwestern United States
Isoprene
Oak (mostly), citrus,
eucalyptus
Monoterpenes
Pine, citrus, eucalyptus
Northeastern United States
Isoprene
Oak (mostly), spruce
Monoterpenes
Maple, hickory, pine,
spruce, fir, cottonwood
National Emissions Trends
Figure 2-32 shows that national total
VOC emissions (which contribute to
03 formation) from anthropogenic
(man-made) sources decreased 31
percent between 1980 and 1999, and
14 percent over the last 10 years.
National total NOx emissions (the
other major precursor to 03 forma-
tion) increased 4 percent and 5 per-
cent respectively over the same two
periods.
Nationally the two major sources
of VOC emissions are industrial pro-
cesses (44 percent) and transportation
sources (47 percent) as shown in Fig-
ure 2-33. Solvent use comprises 60
percent of the industrial process
emissions category and 26 percent of
total VOC emissions. Industrial VOC
emissions have decreased 21 percent
since 1990, in part due to the imple-
mentation of MACT controls that
affect specific chemical and solvent
industries. The VOC emissions totals
by source category and year are pre-
sented in Table A-5 in Appendix A.
Recent control measures to reduce
transportation sector emissions in-
clude regulations to lower fuel vola-
tility and to reduce NOx and VOC
emissions from tailpipes.23 The effec-
tiveness of these control measures is
reflected in a decrease in VOC emis-
sions from highway vehicles. VOC
emissions from highway vehicles
have declined 18 percent since 1990,
while highway vehicle NOx emis-
sions have increased 19 percent over
the same period.
The nonroad methodology for
estimating emissions was changed
this year with the use of an improved
nonroad model for the years 1996 and
later. However, this model was not
used for the earlier years resulting in a
"discontinuity" of about 40 percent for
VOC emissions going from 1995-1996.
As required by the CAA, the Fed-
eral Reformulated Gasoline Program
(RFG) implemented in 1995 has re-
sulted in emissions reductions that
exceed those required by law.24'25
However, the discovery of MTBE
(one of two fuel oxygenates used in
reformulated gasoline to help im-
prove air quality) in the water sup-
plies around the country has required
examination of the approach used in
this program. As previously de-
scribed in the CO section of this re-
port, in November 1998, EPA
announced the creation of a blue
ribbon panel of leading experts from
the public health and scientific com-
munities, automotive fuels industry,
water utilities, and local and state
government to review the important
issues posed by the use of MTBE and
other oxygenates in gasoline. The
Panel concluded that RFG provides
considerable air quality improve-
ments and benefits for millions of
U.S. citizens. However, due to
MTBE's persistence and mobility in
water, and its likelihood to contami-
nate ground and surface water, the
Panel recommended that its use in
gasoline be substantially reduced.26
Additionally, on March 20,2000, the
Clinton Administration, based on the
recommendations of the Blue Ribbon
Panel, announced a set of legislative
principles to address concerns about
the continued use of MTBE. The
Administration recommended that
Congress:
• Amend the CAA to provide the
authority to significantly reduce or
eliminate the use of MTBE.
• Ensure that air quality gains asso-
ciated with the use of MTBE are
not diminished.
• Replace the existing oxygen re-
quirement contained in the CAA
with a renewable fuel standard for
all gasoline.
In addition to anthropogenic
sources of VOC and NOx, there are
natural or biogenic sources of these
compounds as well. Table 2-4 shows
the different predominant plant spe-
cies responsible for VOC emissions in
different parts of the country for two
major biogenic species of concern,
isoprene and monoterpenes. Though
it is not possible to control the level of
these natural emissions, when devel-
oping 03 control strategies, their
presence is an important factor to
consider. Biogenic NOx emissions are
associated with lightning and biologi-
cal processes in soil. On a regional
basis, biogenic VOC emissions can be
greater than anthropogenic VOC
emissions. Biogenic NOx emissions,
CHAPTER 2 • CRITERIA POLLUTANTS — NATIONAL TRENDS
37
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 2-34. Density map of 1999 anthropogenic VOC emissions, by county.
Tons/Year/Sq Mile
1 0 -1.45
1.45-2.82
¦ 2.82-5.16
| 5.16-11.2
¦ 11.2 - 2522.22
Figure 2-35. Highest second daily maximum 1 -hour 03 concentration by county, 1999
Concentration (ppm)
38 CRITERIA POLLUTANTS — NATIONAL TRENDS • CHAPTER 2
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 2-36. Highest fourth daily maximum 8-hour 03 concentration by county, 1999.
Concentration (ppm)
on the other hand, are less than 10
percent of total NOx emissions.27
Figure 2-34 shows the geographic
distribution of 1999 VOC emissions
based on the tonnage per square mile
for each county. This map illustrates
that the eastern half of the country
and the west coast emit more VOC
(on a density basis) than the western
half of the continental United States.
Air Quality Status
The map in Figure 2-35 presents sec-
ond highest daily maximum 1-hour
03 concentrations by county in 1999.
The accompanying bar chart to the
left of the map reveals that in 1999
approximately 54 million people
lived in 101 counties where 03 con-
centrations were above the level of
the 1-hour 03 NAAQS. These num-
bers represent a slight increase from
the totals reported last year (51 mil-
lion people living in 92 counties) with
03 concentrations above the level of
the 03 NAAQS in 1998. The map in
Figure 2-35 shows large spatial differ-
ences, with higher 03 concentrations
typically found in Southern Califor-
nia, the Gulf Coast, and the North-
east and North Central states.
Historically, the highest 1-hour con-
centrations have been found in Los
Angeles; however, in 1999, Harris
County, TX has the highest second
daily maximum value.
Figure 2-36 presents a map of
fourth highest daily maximum
8-hour 03 values by county in 1999
and an accompanying bar chart of the
number of people in counties corre-
sponding to various air quality
ranges. The map reveals widespread
areas with high 8-hour 03 concentra-
tions (i.e., greater than 0.084 ppm) in
much of the eastern half of the coun-
try and in California as well as iso-
lated counties in the West. The corre-
sponding bar chart indicates that
roughly 123 million people live in
counties where fourth highest daily
maximum 8-hour 03 concentrations
were greater than 0.084 ppm.
CHAPTER 2 • CRITERIA POLLUTANTS — NATIONAL TRENDS
39
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Particulate Matter
PM10 Air Quality Concentrations
1980-99 NA
1990-99
18%
decrease
1998-99
1%
increase
PM10 Emissions
1980-99
NA
1990-99
15%
decrease
1998-99
9%
decrease
PM2 5 Air Quality Concentrations
1980-99 Trend not yet available
1990-99
Trend not yet available
1998-99
Trend not yet available
PM25 Emissions
1980-99
NA
1990-99
17%
decrease
1998-99
18%
decrease
• The Franklin Smelter facility, respon-
sible for historically high recorded PM10
concentrations in Philadelphia, shut down
in August 1997 and dismantled in late
1999. This has brought peak concentra-
tions down below the level of the standard
at the nearby monitoring site. In 1998 and
1999, the second maximum was only 61
and 52 |jg/m3, respectively, compared to
264 |jg/m3 in 1997.
PM2,
• The first complete year of PM25 data
(1999) collected by EPA's Federal Refer-
ence Method Monitoring network confirms
that PM2 5 varies regionally. In the East,
higher levels extend from the Southeastern
to Mid-Atlantic states and west into the
Ohio River Valley area. Florida and the
Northeast (New York State to Maine) tend
to have annual mean concentrations below
15 |jg/m3. California, especially central to
southern California, seems to be the only
area widespread in the West with annual
mean concentrations above 15 |jg/m3.
• Data from the IMPROVE network show
that average PM2 5 concentrations in the
rural east decreased 7 percent from 1998-
1999.
• Sulfate concentrations in the rural east
decreased 7 percent based on the 10
IMPROVE sites (and 10 percent based on
the 34 CASTNet sites) from 1998-1999.
• Organic carbon concentrations in the
rural east decreased 4 percent from 1998-
1999, and are still up 18 percent from 1997.
Nature and Sources
Particulate matter (PM) is the general
term used for a mixture of solid parti-
cles and liquid droplets found in the
air. PM originates from a variety of
sources, including diesel trucks, pow-
er plants, wood stoves and industrial
processes. The chemical composition
and physical properties of these parti-
cles vary widely. While individual
particles cannot be seen with the
naked eye, collectively they can ap-
pear as black soot, dust clouds, or
haze.
Particles less than or equal to 2.5
micrometers in diameter, or PM2.5, are
known as "fine" particles. Those
larger than 2.5 micrometers but less
than or equal to 10 micrometers are
known as "coarse" particles. PM10
refers to all particles less than or
equal to 10 micrometers in diameter.
Fine particles result from fuel com-
bustion (from motor vehicles, power
generation, industrial processes),
residential fireplaces and wood
stoves. Fine particles also can be
formed in the atmosphere from gases
such as sulfur dioxide, nitrogen ox-
ides, and volatile organic com-
pounds.
Coarse particles are generally
emitted from sources such as vehicles
traveling on unpaved roads, materi-
als handling, and crushing and grind-
ing operations, and windblown dust.
Fine and coarse particles typically
exhibit different behavior in the at-
mosphere. Coarse particles can settle
rapidly from the atmosphere within
hours, and their spatial impact is
Note: The methods used to estimate
PM-io emissions of some source
categories are not consistent in all years
over the period between 1980 and 1999.
Changes from one method to another
make the emissions trend over time
appear different than it actually has been.
Of particular note is that for 1999 PM10
emissions from three source categories of
open burning are estimated differently
than in previous years and show a
substantial increase compared to
estimates for prior years. These
categories of open burning of residential
waste, yard waste, and land clearing
waste are included in the "industrial
processing" sector of Figures 2-39 and 2-
40. The apparent increase in emissions
from this sector, and in total PM10
emissions, from 1998-1999 is the result of
this change in estimation methodology.
Worth Noting:
PM10
• Between 1998 and 1999, annual aver-
age PM10 concentrations increased nation-
ally for the first time since EPA began
tracking PM10 trends in 1988. The small
increase (1 percent) is largely influenced
by increases in the West, particularly in
California. PM10 concentrations in Califor-
nia were higher than normal from Septem-
ber to December 1999, a period which
coincided with major wildfires and particu-
larly dry conditions.
• Beginning in 1998, the number of
monitoring sites in the PM10 network began
to decrease. This follows the PM monitor-
ing strategy published in July 1997 which
encourages reducing the number of PM10
monitoring sites in areas of low concentra-
tions where the PM10 NAAQS are not
expected to be violated. In 1999, only 667
sites had data, compared to 887 sites in
1998 and 992 sites in 1997.
40 CRITERIA POLLUTANTS —NATIONAL TRENDS • CHAPTER 2
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
typically limited because they tend to
fall out of the air in the downwind
area near their emission point. Larg-
er coarse particles are not readily
transported across urban or broader
areas, because they are generally too
large to follow air streams and they
tend to be removed easily by impac-
tion on surfaces. Smaller-sized coarse
particles can have longer lives and
longer travel distances, especially in
extreme circumstances, such as dust
storms.
Because fine particles remain sus-
pended for longer times, typically on
the order of days to weeks and travel
much father than coarse particles, all
else being equal, fine particles are
theoretically likely to be more uni-
formly dispersed at urban and re-
gional scales than coarse particles.
Analyses of 1999 PM2.5 data from
sites in Atlanta, Detroit, Phoenix, and
Seattle indicate that PM2.5 concentra-
tions tend to be highly correlated
among sites within an urban area. In
contrast, coarse particles tend to ex-
hibit more localized elevated concen-
trations near sources.28
Health and Environmental Effects
Scientific studies show a link between
inhalable PM (alone, or combined
with other pollutants in the air) and a
series of significant health effects.
Inhalable PM includes both fine and
coarse particles. Both coarse and fine
particles can accumulate in the respi-
ratory system and are associated with
numerous adverse health effects.
Exposure to coarse particles is prima-
rily associated with the aggravation
of respiratory conditions such as
asthma. Fine particles are most close-
ly associated with adverse health
effects including decreased lung func-
tion, increased hospital admissions
and emergency room visits, increased
respiratory symptoms and disease,
and premature death. Sensitive
groups that appear to be at greatest
risk to such PM effects include the
elderly, individuals with cardiopul-
monary disease such as asthma or
congestive heart disease, and chil-
dren.
Particulate matter also can also
cause adverse impacts to the environ-
ment. Fine particles are the major
cause of reduced visibility in parts of
the United States, including many of
our national parks. Other environ-
mental impacts occur when particles
deposit onto soils, plants, water, or
materials. For example, particles
containing nitrogen and sulfur that
deposit onto land or water bodies
may change the nutrient balance and
acidity of those environments so that
species composition and buffering
capacity change. Particles that are
deposited directly onto the leaves of
plants can, depending on their chemi-
cal composition, corrode leaf surfaces
or interfere with plant metabolism.
Finally, PM causes soiling and erosion
damage to materials, including cul-
turally important objects such as
carved monuments and statues.
Primary and Secondary PM
Standards
The standards for PM10 include both
short- and long-term NAAQS. The
short-term (24-hour) standard of 150
]ig/m3 is not to be exceeded more
than once per year on average over
three years. The long-term standard
specifies an expected annual arith-
metic mean not to exceed 50 ]Lig/m3
averaged over three years.
The standards for PM2.5 are set at
15 ]ig/m3 and 65 ]Ug/m3, respectively,
for the annual and 24-hour stan-
dards.29 These are the primary, or
health-based, standards. The second-
ary, or welfare-based, standards for
PM10 are identical to the primary
standards. The secondary (welfare-
based) PM2.5 standards were made
identical to the primary standards.
Numerous industry and environ-
mental petitioners, including the
American Trucking Associations
(ATA), challenged the 03 and PM
standards in the United States Court
of Appeals for the District of Colum-
bia Circuit. On May 14, 1999, a three-
judge panel of that court concluded
that EPA's interpretation of the Clean
Air Act unconstitutionally delegated
legislative power to EPA and re-
manded the standards to EPA. EPA
appealed that ruling, and on Febru-
ary 27,2001, the Supreme Court
unanimously upheld the constitution-
ality of Clean Air Act section 109 and
affirmed EPA's ability to set NAAQS
based solely on public health and
welfare factors, without consideration
of costs, which are considered in the
implementation of the standards. The
court rejected the D.C. Circuit's con-
clusion that
EPA's interpretation of the implemen-
tation provisions violated the
statute's clear terms, but nevertheless
remanded the implementation policy
to EPA on the basis that EPA's policy
was not a reasonable interpretation of
ambiguous statutory language. Be-
cause the D.C. Circuit originally re-
manded, but did not vacate the 03
and PM2.5 standards, they have re-
mained legally effective throughout
the ongoing litigation. The case has
now been returned to the Court of
Appeals, where the remaining issues
are to be considered in accordance
with the decision of the Supreme
Court.
For a variety of reasons, EPA has
not yet taken actions to implement
either standard. The litigation over
CHAPTER 2 • CRITERIA POLLUTANTS — NATIONAL TRENDS
41
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
the PM NAAQS has not yet affected
EPA or state activities related to these
standards. EPA cannot start imple-
menting the 1997 PM2.5 standards
until EPA and the states have col-
lected three years of monitoring data
to determine which areas are not
attaining the standards. The fine
particle monitoring network has been
operational since 1999 and was com-
pleted in 2000. In most cases, areas
would not be designated "attain-
ment" or "nonattainment" for the
PM2.5 standards until 2004-2005.
Refer to http://www.epa.gov/airlinks
for up-to-date information concern-
ing actions surrounding the revised
standards.
National 10-Year PM10 Air
Quality Trends
Since 1988 represents the first com-
plete year of PM10 data for most mon-
itored locations, a 20-year trend is not
available. However, the most recent
10-year period (1990-1999) shows
that the national average of annual
mean PM10 concentrations at 954
monitoring sites decreased 18 percent
in Figure 2-37. The downward trend
is apparent through 1998. However,
between 1998 and 1999, the national
average increased 1 percent. This
slight increase is largely influenced
by increases in the West, particularly
in California. PM10 concentrations in
California were higher than normal
from September-December 1999, a
period which coincided with major
wildfires and particularly dry condi-
tions.
When the sites are grouped as
rural, suburban, and urban, as in
Figure 2-38, the trend is similar to the
national trend. The highest values
are generally found at the urban sites,
followed closely by the suburban
sites. The annual mean is much
Figure 2-37. Trend in annual mean PM10 concentrations, 1990-1999.
Concentration, |jg/m3
60
50 -
40
30
20
10
0 r
80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99
Figure 2-38. PM-iq annual mean concentration trends by location, 1990-1999.
Concentration, ^ig/m3
35
30
25
20
15
10
5
0
90 91 92 93 94 95 96 97 98 99
National Standard
90% of sites have concentrations below this line
T
Ten-year trend
not available
before 1990.
Average ——_____—
954 Sites
A
10% of sites have concentrations below this line
Rural (153 sites) Suburban (375 sites) Urban (408 sites)
42 CRITERIA POLLUTANTS —NATIONAL TRENDS • CHAPTER 2
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 2-39. National PM10 emissions trend, 1980-1999 (traditionally inventoried
sources only).
Thousand Short Tons Per Year
7,000
~ Fuel Combustion ¦ Industrial Processing
~ Transportation
6,000
5,000
4,000
3,000
2,000
1.000
90 91 92 93 94 95 96 97 98 99
Notes: Emissions data not available for consecutive years 1980-1989.
Emission estimation methods continue to evolve and improve overtime. Methods have
changed for many significant categories beginning with the years 1985, 1990, and 1996 and
consequently are not consistent across all years in this trend period. See Appendix B
Emissions Estimates Methodology for additional information.
Figure 2-40. PM10 emissions from traditionally inventoried source categories, 1999.
Fuel Combustion 33.8%
Industrial Processes 41.5%
Transportation 24.7%
lower at the rural sites, which are
generally located away from local
sources of PM10.
Beginning in 1998, the number of
monitoring sites in the PM10 network
began to decrease. This follows the
PM monitoring strategy published in
July 1997 which encourages reducing
the number of PM10 monitoring sites
in areas of low concentrations where
the PM10 NAAQS are not expected to
be violated. Specifically, it calls for
eliminating sites not needed for
trends or with maximum concentra-
tions less than 60 percent of the
NAAQS.30 In 1999, only 667 sites had
data, compared to 887 sites in 1998
and 992 sites in 1997. This decrease in
the number of monitors has not af-
fected the calculation of the national
trend.
Several factors have played a role
in reducing PM10 concentrations.
Where appropriate, states required
emissions from industrial sources and
construction activities to be reduced
to meet the PM10 standards. Mea-
sures were also adopted to reduce
street dust emissions, including the
use of clean anti-skid materials like
washed sand, better control of the
amount of material used, and re-
moval of the material from the street
as soon as the ice and snow melt.
Cleaner burning fuels like natural gas
and fuel oil have replaced wood and
coal as fuels for residential heating,
industrial furnaces, and electric util-
ity and industrial boilers.
National PM10 Emissions Trends
Nationally, annual estimates of PM10
direct emissions decreased 15 percent
between 1990 and 1999 (see
Table A-6). Direct PM10 emissions are
generally examined in two separate
groups. First there are the emissions
from the more traditionally invento-
CHAPTER 2 • CRITERIA POLLUTANTS — NATIONAL TRENDS
43
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 2-41. Total PM10 emissions by source category, 1999.
^ navjiuui icuiy g
Inventoried
jus 46.6% /
\ Fugitiv
Agriculture & Forest 11.0% Other Combustion 2.3%
ried sources, shown in Figures 2-39
and 2-40. These include fuel combus-
tion, industrial processes, and trans-
portation. Of these, the fuel
combustion category saw the largest
decrease over the 10-year period (14
percent), with most of the decline
attributable to a decrease in emissions
from electric utility coal and oil com-
bustion. Emissions from the industri-
al processes category decreased 3
percent, and emissions from the
transportation category decreased
10 percent. The recent upward move-
ment between 1998 and 1999 for in-
dustrial processing is attributed to
new sources of emissions for open
burning (of residential yard wastes
and land clearing debris) that had not
been characterized previously.
The second group of direct PM10
emissions is a combination of miscel-
laneous and natural sources includ-
ing agriculture and forestry, wildfires
and managed burning, and fugitive
dust from paved and unpaved roads.
It should be noted that fugitive dust
emissions from geogenic wind ero-
sion have been removed from the
emissions inventory for all years,
since the annual emission estimates
based on past methods for this cat-
egory are not believed to be represen-
tative. As Figure 2-41 shows, these
miscellaneous and natural sources
actually account for a large percent-
age of the total direct PM10 emissions
nationwide, although they can be
difficult to quantify compared to the
traditionally inventoried sources.
The trend of emissions in the miscel-
laneous/natural group may be more
uncertain from one year to the next or
over several years because these
emissions tend to fluctuate a great
deal from year to year. It should be
noted that a change in methodology
occurred between 1995 and 1996 in
calculating PM10 emissions from
unpaved roads. This has led to lower
PM10 emissions from 1996 through
1999 than would have been predicted
using the older methodology.
Table A-6 lists PM10 emissions
estimates for the traditionally inven-
toried sources for 1990-1999. Miscel-
laneous and natural source PM10
emissions estimates are provided in
Table A-7.
Figure 2-42 shows the emission
density for PM10 in each U.S. county.
PM10 emission density is the highest
in the eastern half of the United
States, in large metropolitan areas,
areas with a high concentration of
agriculture such as the San Joaquin
Valley in California and along the
Pacific coast. This closely follows
patterns in population density. One
exception is that open biomass burn-
ing is an important source category
that is more prevalent in forested
areas and in some agricultural areas.
Fugitive dust is an important compo-
nent in arid and agricultural areas.
PM10 Regional Air Quality Trends
Figure 2-43 is a map of regional
trends for the PM10 annual mean
from 1990-1999. All 10 EPA regions
show decreasing trends over the
10-year period, with declines ranging
from 5-33 percent. The largest de-
creases are generally seen in the west-
ern part of the United States. This is
significant since PM10 concentrations
are typically higher in the West. In
the western states, programs such as
those with residential wood stoves
and agricultural practices have
helped reduce emissions of PM10. In
the eastern United States, the Clean
Air Act's Acid Rain Program has
contributed to the decrease in PM10
emissions. The program has reduced
44 CRITERIA POLLUTANTS —NATIONAL TRENDS • CHAPTER 2
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 2-42. PM10 emissions density by county, 1999.
Tons/Year/Sq Mle
1 0-4
1 5-7
18-11
" 12-17
H 18-696
Figure 2-43. Trend in PM-iq annual mean concentration by EPA region, 1990-1999.
31.1
f 33%
24.2
#23%
30.4
f 18%
23.0
26.5
19.4
22.4
| 15%
#16%
37.8
#19%
30.3
26.7
# 12%
29.4
#18%
The National Trend
29.2
# 18%
26.2
#5%
25.0
29.3
#19%
Note: These trends are
influenced by the
distribution of monitoring
locations in a given region
and, therefore, can be
driven largely by urban
concentrations. For this
reason, they are not
indicative of background
regional concentrations.
Alaska is in EPA Region 10; Hawaii, EPA Region 9; and Puerto Rico,
EPA Region 2. Concentrations are |jg/m3.
CHAPTER 2 • CRITERIA POLLUTANTS — NATIONAL TRENDS
45
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 2-44. Highest 2nd maximum 24-hour PM10 concentration by county, 1999.
180 -
170 -
= 110-
i
£ 1 00 ~
Concentration (ug/m3)
<55
255- 354
55-154
355- 424
155-254
>=425
S02 and NOx emissions, both precur-
sors of particulate matter in the atmo-
sphere (see Chapter 7 on Atmospheric
Deposition and the S02 section in this
chapter for more information on the
Acid Rain Program).
PM10 1999 Air Quality Status
The map in Figure 2-44 displays the
highest second maximum 24-hour
PM10 concentration in each county for
1999. The largest of these was record-
ed in Inyo County California, caused
by wind blown dust from a dry lake
bed.31 The bar chart which accompa-
nies the national map shows the
number of people living in counties
within each concentration range. The
colors on the map and bar chart cor-
respond to the colors of the concen-
tration ranges displayed in the map
legend. In 1999, approximately 5
million people lived in 11 counties
where the highest second maximum
24-hour PM10 concentration was
above the level of the 24-hour PM10
NAAQS. When both the annual and
24-hour PM10 standards are consid-
ered, there were 20 million people
living in 19 counties with PM10 con-
centrations above the NAAQS in
1999. See Chapter 4 for information
concerning officially designated PM10
nonattainment areas.
The Franklin Smelter facility, re-
sponsible for historically high re-
corded PM10 concentrations in
Philadelphia, shut down in August
1997 and dismantled in late 1999.32
This has brought peak concentrations
down below the level of the standard
at the nearby monitoring site. In 1998
and 1999, the second maximum was
only 61 and 52 jig/m3, respectively,
compared to 264 ]Ug/m3 in 1997.
Characterizing PM25 Air Quality
A new monitoring network designed
to assess fine PM data with respect to
the new PM2.5 standards began de-
ployment in early 1999. The status of
this network is shown in Figure 2-45.
As of February 2001,1,108 Federal
Reference Method (FRM) monitoring
sites were operating and 1,044 of
them have reported data to EPA's
Aerometric Information Retrieval
System (AIRS). Analyses of the first
complete year of data (1999) collected
by this network are summarized in
the "FRM Network Results" section.
Data from another network, the
IMPROVE network of rural sites,
were used to assess the composition of
and trends in ambient PM2.5 concen-
46 CRITERIA POLLUTANTS —NATIONAL TRENDS • CHAPTER 2
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 2-45. Status of PM2 5 monitor network, as of May 2001.
Alaska
Hawaii
Puerto Rico
Virgin Islands
trations. Since the monitors in the
IMPROVE network are non-FRM, the
data cannot be used for compliance
purposes. Analyses of these data are
summarized in the "IMPROVE Net-
work Results" section.
As additional analyses of PM2.5
data are completed, they will be pub-
lished on EPA's PM2.5 Data Analysis
Web site at http://www.epa.gov/oar/
oaqps/pm25/.
CHAPTER 2 • CRITERIA POLLUTANTS — NATIONAL TRENDS
47
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
FRM Network Results
1999 Annual Mean PM25
Concentrations
Figure 2-46 depicts nationwide annu-
al mean PM2.5 concentrations from
the FRM monitoring network. Data
completeness is illustrated by the size
of the circles on the map, with small-
er circles indicating relatively incom-
plete data for the year. Many
locations in the eastern United States
and in California were above 15 jag/
m3. Annual mean concentrations
were above 20 ]Ug/m3 in several ma-
jor urban areas throughout the east-
ern United States including
Pittsburgh, Cleveland, Atlanta, Chica-
go, and St. Louis. Los Angeles and
the central valley of California also
had levels above 20 ]Ug/m3. Sites in
the central and western mountain
regions of the United States had gen-
erally low annual mean concentra-
tions, most below 10 ]Ug/m3.
1999 24-hour PM2 5
Concentrations
Figure 2-47 depicts nationwide 98th
percentile 24-hour average PM2 5
concentrations from the FRM moni-
toring network. Concentrations
above 65 ]Ug/m3 are relatively rare in
the eastern United States, but more
prevalent in California. Values in the
40-65 ]Ug/m3 range are more common
in the eastern United States and the
west coast, but relatively rare in the
central and western mountain regions.
Readers should be cautioned not
to draw conclusions regarding the
attainment or nonattainment status
inferred by a single year of PM2.5
monitoring data. EPA regulations in
40 CFR part 50, Appendix N, require
three years of monitoring data and
specify certain minimum data com-
pleteness requirements for data used to
make decisions regarding attainment
Figure 2-46. 1999 annual mean PM2 5 concentrations (|jg/m3).
Alaska
Hawaii
Data Completeness
° <4 quarters
O one or more quarters with <11 samples
O All quarters with at least 11 samples
O All quarters 75% or more complete
Puerto Rico
Concentration (uq/m3)
0 >20
O 15-20
# 10-15
# 0-10
Source: US EPA AIRS Data base as of 7/12/00 without data flagged as 1, 2, 3, 4, T, W, Y, or X
Figure 2-47. 1999 98th percentile 24-hour average PM2 5 concentrations (|jg/m3).
Alaska Hawaii
Data Completeness
o <4 quarters of data
O one or more quarters with < 75% of scheduled samples
O All quarters with at least 75% of scheduled samples
Puerto Rico
Concentration fua/m3)
• >65
O 40-65
• 30-40
• 0-30
Source: US EPA AIRS Data base as of 7/12/00 without data flagged as 1, 2, 3, 4, T, W, Y, or X
48 CRITERIA POLLUTANTS —NATIONAL TRENDS • CHAPTER 2
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 2-48. Urban PM2s monthly patterns by region, 1999.
Northwest
Southern
California
Upper Midwest
Southwest
Industrial Midwest
Southeast'
Northeast ,
Notes: St. Louis and Buffalo = Industrial
Midwest; Dallas = Southeast; Rochester =
Northeast; Fresno, San Joaquin Valley, and
Las Vegas = Southern California.
Hawaii, Alaska, and Puerto Rico are not
included in regional summaries.
status. As indicated by the size of the
circles on the maps, many sites have
relatively incomplete data for 1999 at
the time of the data summarization.
Seasonal Patterns in PM
Concentrations
Data from the 1999 PM2g FRM net-
work show distinct seasonal variation
in average PM2.5 concentrations. The
regional summaries in Figure 2-48
(urban) and Figure 2-49 (rural) dem-
onstrate the geographic variability of
PM2.s concentrations. The months
with peak urban I'M; - concentrations
vary by region. The urban areas in
the eastern regions all show peaks in
the summer months, and the western
regions all show peaks in the winter
months. The Industrial Midwest
shows peaks in June and July/the
upper Midwest shows peaks in July
and August, and the Southeast shows
peaks in August. The Northwest,
Southwest, and Southern California
all show peaks in January. The
CHAPTER 2 • CRITERIA POLLUTANTS — NATIONAL TRENDS
49
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 2-49. Rural PM2 s monthly patterns by region, 1999.
Northwest
h R ~
Southern
California
Upper Midwest
Not enough
data available
Southwest
Industrial Midwest
: p ^
Southeast'
Northeast
Notes: St. Louis and Buffalo = Industrial
Midwest; Dallas = Southeast; Rochester =
Northeast; Fresno, San Joaquin Valley, and
Las Vegas = Southern California.
Hawaii, Alaska, and Puerto Rico are not
included in regional summaries.
Southwest and Southern California
show a second peak in November.
Differences between urban and
rural locations are apparent from the
plots. Southern California urban and
rural monitors show different sea-
sonal patterns, with urban winter
peaks not present in rural areas. In
the Northwest the rural winter peak
is not as pronounced as it is in urban
areas. In all other regions the urban
and rural patterns are very similar.
IMPROVE Network Results
The IMPROVE network was estab-
lished in 1987 to track visibility im-
pairment in the nation's most pristine
areas, like national parks and wilder-
ness areas. For this reason, the data
primarily represent rural areas. There
are, however, two non-rural sites (in
Washington, D.C. and South Lake
Tahoe) that use the same monitoring
protocol. Data from these and other
sites meeting data completeness crite-
ria described in Appendix B, are
presented in this section. Figure 2-50
shows the location of these sites by
region. (The IMPROVE network is
discussed in further detail in Chapter
50 CRITERIA POLLUTANTS —NATIONAL TRENDS • CHAPTER 2
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 2-50. Class I Areas in the IMPROVE Network meeting the data completeness criteria in Appendix B.
6: Visibility Trends. Also, visit http://
vista.cira.colostate.edu/improve/
Data/IMPROVE/improve_data.htm
for more information concerning the
IMPROVE network.)
1999 Rural PM25 Concentrations
and Composition
Rural PM2.5 concentrations vary re-
gionally, with sites in the East typical-
ly having higher annual mean
concentrations. Figure 2-51 shows
the annual mean PM2 5 concentrations
in 1999. Much of the East/West dif-
ference is attributable to higher sul-
fate concentrations in the eastern
United States. Sulfate concentrations
in the eastern sites are 4-5 times
greater than those in the western
sites. Sulfate concentrations in the
East largely result from sulfur dioxide
emissions from coal-fired power
plants. EPA's Acid Rain Program,
which is discussed in more detail in
the S02 section and in the S02 section
in Chapter 7, sets restrictions on these
power plants.
Within the East, rural PM2 5 levels
are higher in the Southeastern and
mid-Atlantic states (ranging roughly
from 10-16 ]Ug/m3), while the sites in
the northeast are between 6-7 ]Ug/m3.
In the West, rural PM2 5 levels are
generally less than 5 ]Ug/m3. Califor-
nia, Montana and Texas are the only
states in the West with sites above
that level.
The chemical composition of PM2 5
also varies regionally. Sulfate and
organic carbon account for most of
the PM2.s concentrations in the East
and the West. Sites in the East on
average have a higher percentage of
sulfate concentrations (56 percent)
relative to those in the West (33 per-
Moosehorn
Mount Rainier
Three Sisters
Yellowstone
Bridger Badlands
Crater Lake
irbidge
Lassen Volcanic
Point Reyes Lone
51 Great Basin *
H h Yosemite *
Pinnacles x Bryce Cannon
Sequoia Mesa V(
Indian Gardens *
a
San Gorgonio
Mount
Rocky Mountain
Canyonlands
Shenandoah
Great Sand Dunes
Weminuche
Q Bandelier
'etrified Forest
Upper Buffali
Chirici
Guadalupe Mntns
~ Okefenokee
Big Bend
Chassahowitz.
Denali
Brigantine
Cape Romain
ei Complete for Both
~ Complete for Trends Only
x Complete for 1999 Only
CHAPTER 2 • CRITERIA POLLUTANTS — NATIONAL TRENDS
51
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 2-51. Annual mean PM25 concentrations in 1999.
Units are |jg/m3.
Pie chart sizes are scaled by the annual
average PM2 5 concentrations.
Sulfate
Nitrate
Organic Carbon
Elemental Carbon
Crustal Material
cent). Table 2-5 shows the difference
in percent contribution of each spe-
cies for the eastern versus western
regions of the United States.
Table 2-5. Percent Contribution to PM25
by Component, 1999
East West
(10 sites) (26 sites)
Sulfate
56
33
Elemental Carbon
5
6
Organic Carbon
27
36
Nitrate
5
8
Crustal Material
7
17
Figure 2-52. PM2 5 concentrations, 1992-1999 at eastern IMPROVE sites meeting
trends criteria.
Concentration, |jg/m3
15
Measured PM2.5
10 Sites
Sulfate
Organic Carbon
Nitrate
Crustal Material
Elemental Carbon
Note: Measured PM2.5 represents the direct mass measurement from the filter.
The sum of the component concentrations do not equal this value because they
do not account for all measured mass.
52 CRITERIA POLLUTANTS —NATIONAL TRENDS • CHAPTER 2
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 2-53. PM2 5 concentrations, 1990-1999 at western IMPROVE sites meeting
trends criteria.
Concentration, |jg/m3
6
26 Sites
Measured PM2.5
Organic Carbon
Sulfate
Crustal Material
Nitrate
Elemental Carbon
90 91 92 93 94 95 96 97 98 99
Note: Measured PM2.5 represents the direct mass measurement from the filter.
The sum of the component concentrations do not equal this value because they
do not account for all measured mass.
Figure 2-54. PM2 s concentrations, 1990-1999 at the V\feshington D.C. IMPROVE site.
Concentration, |jg/m3
25
Measured PM2.5
Sulfate
Organic Carbon
Nitrate
Elemental Carbon
Crustal Material
90 91 92 93 94 95 96 97 98 99
Note: Measured PM2.5 represents the direct mass measurement from the filter.
The sum of the component concentrations do not equal this value because they
do not account for all measured mass.
PM2 5 Air Quality Trends in Rural
Areas
Because of the significant regional
variations in rural PM2 5 concentra-
tions, trends are aggregated by east-
ern and western regions as shown in
Figures 2-52 and 2-53. Based on the
10 sites with trend data in the East,
average PM2 5 concentrations in the
rural east decreased 7 percent from
1998-1999. The 1999 level is down 5
percent from the 1992 level, but it is
up 4 percent from the 1995 level (the
lowest level during the trend period).
Sulfate concentrations in the rural
east decreased 7 percent from 1998 to
1999. Organic carbon concentrations
in the rural east decreased 4 percent
from 1998-1999, but are still up 18
percent from 1997 (the lowest level
during the trend period).
The average PM15 concentrations
in the West increased 10 percent from
1998-1999. However, the 1999 level is
down 15 percent from the 1990 level.
PM25 Trends in Non-rural Areas
Figure 2-54 shows that annual aver-
age PM2.5 concentrations at the Wash-
ington, D.C. site decreased 2 percent
between 1990 and 1999, but increased
1 percent between 1998 and 1999.
Characterizing PM25 Emissions
To get some idea of the nature of fine
PM, some emissions information
coupled with ambient data measure-
ments can be examined. EPA is
working to improve the PM2 5 emis-
sion inventory. In the meantime, a
general assessment of the emission
sources contributing to PM2 5 can be
obtained by evaluating PM2 5 moni-
toring data in conjunction with emis-
sion inventory information. The
paragraphs below provide a broad
overview of the nationwide concen-
trations, composition, and sources of
CHAPTER 2 • CRITERIA POLLUTANTS — NATIONAL TRENDS
53
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
PM2.5 based on actual PM2 5 measure-
ments and the emission inventory of
sources contributing within each
composition category.
PM2.5 is composed of a mixture of
particles directly emitted into the air
and particles formed in the air from
the chemical transformation of gas-
eous pollutants. The principal types
of secondary particles are ammonium
sulfate and ammonium nitrate
formed in the air from gaseous emis-
sions of S02 and NOx/ reacting with
ammonia. The main source of S02 is
combustion of fossil fuels in boilers
and the main sources of NOx are
combustion of fossil fuel in boilers
and mobile sources. Some secondary
particles are also formed from volatile
organic compounds which are emit-
ted from a wide range of combustion
and other sources.
The principle types of directly
emitted particles are those that pre-
dominantly consist of crustal materi-
als and those consisting of elemental
and organic carbonaceous materials
resulting from the incomplete com-
bustion of fossil fuels and biomass
materials. The main sources of
crustal particles are road surface ma-
terials, construction activity and
certain agricultural activities. The
main sources of combustion-related
particles are mobile sources such as
diesels, managed and unmanaged
biomass burning, residential wood
combustion, utility, commercial and
industrial boilers. Note however, that
crustal particles contain some carbon-
aceous materials, some combustion
process emissions contain crustal
materials (e.g., wild and prescribed
fires), and even fossil fuels contain fly
ash that is chemically similar to soil
and thus would be classified as
crustal in the compositional analysis
of ambient samples reported herein.
Figure 2-55 summarizes informa-
tion from actual measurements of
ambient PM2.5. It shows how PM2.5
composition varies in both the east-
ern and western United States. The
ambient samples were chemically
analyzed to determine the amount of
ammonium sulfate and nitrate,
crustal material and carbonaceous
material. The concentration and
composition data are based on at least
one year of data from each monitor-
ing location, with the exception of
Denver. The data were collected
using a variety of non-federal refer-
ence methods and should not be used
to determine compliance with the
PM2.5 NAAQS. The composition in-
formation represents a range of urban
and non urban locations. The pub-
lished composition data for the East
are somewhat limited, but prelimi-
nary information from several re-
cently completed urban studies is
included. It shows relatively consis-
tent composition of PM2.5 across
much of the East. The available infor-
mation consistently shows that PM2.5
in the East is dominated by ammo-
nium sulfate on a regional scale and
also by carbonaceous particles emit-
ted directly by combustion processes.
Regional concentrations of PM2.5 are
generally higher throughout much of
the East, due to the regional influence
of ammonium sulfate caused by
higher S02 emissions throughout
much of the East and the ubiquitous
nature of combustion processes. (See
Chapter 7 for a description of spatial
patterns and trends of sulfate air
quality.) The regional concentrations
of PM2.5 are lower in the western
United States than in the East and the
composition is more variable. The
west differs from the East in two
important ways. First, non urban
PM2.5 concentrations are much lower
in the West than in the East. This is
because the East is blanketed region-
ally by relatively higher concentra-
tions of ammonium sulfate, whereas
regional sulfate concentrations in the
West are much lower. Second, sev-
eral western areas, notably the San
Joaquin Valley and the Rubidoux area
California's South Coast basin have
higher ammonium nitrate concentra-
tions. Nitrate concentrations are also
higher in non-urban inland areas of
southern California. Such pockets of
high nitrate concentrations are not as
pronounced in the East. Crustal ma-
terial is a relatively small constituent
of PM2.s in both the West and east,
even in arid and agricultural areas
such as Phoenix, Arizona and the San
Joaquin Valley of California.
Figure 2-56 depicts the link between
sources and the composition compo-
nents of PM2.5. EPA has developed a
National Emissions Inventory (NEI)
inventory for use in analyzing trends in
emissions over time, conducting vari-
ous in house analyses for PM, and for
use in regional scale modeling.33 The
NEI covers all 50 states and includes
point, area, onroad mobile, nonroad
mobile sources and biogenic/geogenic
emissions. Point sources are identified
individually while county tallies are
used for area and mobile source cat-
egory groups. The inventory includes
emissions of S02, NOx, VOC, CO,
PM10, PM2.5, and NH3. Of these pollut-
ants, only carbon monoxide is not a
contributor to the ambient fine particle
burden.
Figure 2-56 provides a link be-
tween the sources in the NET inven-
tory and the composition information
shown in Figure 2-55. The stacked
bar graphs show the relative magni-
tude of emissions of sulfur dioxide,
54 CRITERIA POLLUTANTS — NATIONAL TRENDS • CHAPTER 2
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
nitrogen oxides, carbonaceous and
crustal-related particles. S02 is emit-
ted mostly from the combustion of
fossil fuels in boilers operated by
electric utilities and industry. Less
than 20 percent of S02 emissions
nationwide are from other sources,
mainly industrial processes and
mobile sources. NOx emissions are
more evenly divided between station-
ary source and onroad mobile source
fuel combustion, accounting for al-
most 80 percent of S02 emissions.
Nonroad mobile sources account for
most of the remaining emissions. S02
and NOx combine with ammonia in
the atmosphere under certain condi-
tions to form ammonium sulfate and
nitrate particles. Animal husbandry,
mobile sources, fertilizer application
and industrial processes are the main
sources of ammonia, with animal
husbandry contributing about 80
percent of the emissions. The main
sources of carbonaceous particles are
biomass and fossil fuel combustion
with the open burning of biomass
accounting for about one-third of the
carbonaceous material emissions.
Other important categories are mo-
bile sources, various industrial pro-
cesses, residential wood stoves and
fireplaces, and organic soils and plant
materials. Principal mobile sources
include both on and off road diesels,
gasoline engines, aircraft, railroads,
and ships. The main sources of crust-
al particles are roads, construction
and agriculture, but as discussed
earlier, some of the crustal materials
reported in Figures 2-55 and 2-56
come from combustion emissions.
High wind events also can contribute
large quantities of crustal materials to
the air. However, since wind events
are of relatively short duration, they
are not included in annual emission
estimates such as the NEI. While
Figure 2-55. PM2 5 ambient composition.
I Carbonaceous ~ Nitrate ¦ Crustal ~ Sulfate ~ Comically
Characterized
Urban
(8.7 pg/m3)
(14.9 u0/m3)
San Joaquin Valley
(Avg - 37 |ig/m3)
New Haven
(13.7 pg/m3)
S. Coast
Washington, DC
(14.5 u0/m3)
(Avg 28 |jg/m3)
$
© ©
ei Paso
(22.5 iig/m3)
Dallas Birmingham
(18.3 |ig/m3) (21.3 M
(13.3 pg/m3)
(18.8 |ig/mj)
Sonoran Desert
(3.9 iig/m3)
Colorado Plateau
(3 pg/m3)
Badlands
(4 pg/m3)
Mid-South
(11.4 Mg/m3)
Notes:
See Appendix B for a full discussion of data sources.
PM2.5 mass concentrations are determined using at least 1 year of monitoring at each
location using a variety of sampling methods. They should not be used for comparisons to
the PM25 NAAQS.
©
Boundary Waters
(4.5 |jg/m3)
Sierra Nevada
(6.6 |jg/m3)
0
Cascade
(3.4 |ig/m3)
Nonurban
(2.8 pg/m3)
N. New England
(5.3 |ig/m3)
Appalachian & Mid-Atlantic
(9.9 pg/m3)
CHAPTER 2 • CRITERIA POLLUTANTS — NATIONAL TRENDS
55
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 2-56. PM2 5 emission sources.
Sulfur Dioxide
Ammonium sulfate particles are formed from emissions of gaseous S02
(and also S03 and sulfuric acid aerosols) emitted mostly from utility and
industrial boilers and to a lesser degree from certain industrial processes
and mobile sources.
Nitrogen Oxides
Ammonium nitrate particles are formed from emissions of gaseous NOx
emitted mostly from utility and industrial boilers but also from highway and
off highway mobile sources and to a lesser degree, biogenic and
miscellaneous combustion sources and certain industrial processes.
Ammonia
Ammonium sulfate and nitrate particles are formed from emissions of S02
and NOx reacting with gaseous ammonia. Emission sources are animal
husbandry, fertilizer manufacturing and application and to a lesser degree
from mobile sources, and other combustion and industrial processes.
Carbonaceous
Particles
Carbonaceous particles are emitted directly and as condensed liquid
droplets from fuel combustion, burning of forests, rangelands and fields;
off highway and highway mobile sources (gas and diesel); and certain
industrial processes.
Crustal
Particles emitted directly from non industrial surface (e.g., paved and
unpaved road traffic, construction, agricultural operations, high wind
events) and some industrial processes.
Source category contributions to National emissions of PM2.5 (directly emitted crustal and elemental/
organic carbon-related particles and SOaand NOx, precursors to ammonium sulfate and nitrate.)
_ Fuel Combustion
(Boilers / Res Heating)
Industrial Processes (Organic]
Highway Vehicles
Off Highway
Open / Biomass and
Waste Burning
Fugitive Dust
(Non Industrial)
Industrial Processes (Inorganii
»»>'
vvvvy
1
Fuel Combustion
(Boilers / Res Heating)"
Industrial Processes (Organic)
Highway Vehicles
Off Highway
Open / Biomass and _
Waste Burning
Fugitive Dust
(Non Industrial)
Industrial Processes (Inorganic)-
Carbonaceous Crustal
Particles
Note:
Composition and source contributions vary among urban areas. Also, some carbonaceous material is formed from
organic gases reacting in the atmosphere. The magnitude of these "secondary" organics is believed small but more
studies are needed by the research community.
56 CRITERIA POLLUTANTS —NATIONAL TRENDS • CHAPTER 2
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 2-57. Direct PM2 5 emissions density by county, 1999.
Tons/Year/Sq Mile
| 0-1.14
H 1-14-1.8
H 1-8-2.68
| 2.68-4.18
¦ 4.18-379.04
crustal materials are the predominant
component of PM10, Figure 2-56
shows that PM2.5 is predominantly
comprised of secondary particles and
directly emitted carbonaceous parti-
cles. The composition (and thus the
sources) of PM2.5 and PM10 are mark-
edly different because most of the
crustal material particles are larger
than 2.5 micrometer aerodynamic
diameter while almost all of the sec-
ondary particles and directly emitted
carbonaceous particles are smaller
than 2.5 micrometers.
Used together, Figures 2-55 and
2-56 can give a qualitative feel for the
combined influence of specific source
types on ambient PM2.5 overall (e.g.,
fuel combustion in boilers, organic
and inorganic industrial processes,
highway and off highway mobile
sources, open burning of waste/
biomass and fugitive dust). For ex-
ample, Figure 2-56 shows that fuel
combustion in boilers contributes
significantly to both sulfate and car-
bonaceous mass. Figure 2-57 shows
that both sulfate and carbonaceous
particles are found in abundance in
PM2.5 in the east and that carbon-
aceous particles are also abundant in
the west. Thus, one could conclude
that fuel combustion in boilers is a
significant contributor to PM2.5 in the
ambient air. In contrast, one could
conclude that fugitive dust sources
do not play a particularly important
role in ambient air samples of PM2 5.
It is important to note, however, that
PMio crustal particles have been
shown to be significant contributors
to visibility impairment in the west-
ern United States.34
National Trends in PM25
Emissions
Figure 2-57 shows the emission densi-
ty for PM2 5 in each U.S. county. PM2 5
emission density is the highest in the
eastern half of the United States, in
large metropolitan areas, areas with a
high concentration of agriculture
such as the San Joaquin Valley in
California and along the Pacific coast.
This closely follows patterns in popu-
lation density. One exception is that
open biomass burning is an impor-
tant source category that is more
prevalent in forested areas and in
some agricultural areas. Fugitive dust
is a lower fraction of PM2 5 emissions
than they are for PM10.
Figure 2-58 shows that total direct
PM2.s emissions decreased 12 percent
between 1990 and 1999, which is a
CHAPTER 2 • CRITERIA POLLUTANTS — NATIONAL TRENDS
57
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
similar 10-year trend to that for PM10.
The relative source contribution to
PM2.5 versus PM10 is different, as
shown in Figures 2-59 and 2-60.
When both traditionally inventoried
and miscellaneous categories are con-
sidered together, combustion sources
account for a higher percentage of total
emissions for PM2.5 than for PM10.
As discussed earlier, ammonia is
important in explaining the formation
of sulfate and nitrate. Figure 2-61 is a
pie chart showing 1999 NH3 emissions
by source category. It shows that live-
stock (and to a lesser extent fertilizer
application) are the most important
NH3 sources, accounting for 87 percent
of total ammonia emissions.
Characterizing Coarse Fraction
PM Air Quality
An approximation of course fraction
PM can be obtained by subtracting
PM2.5 from PM10 at collocated FRM
monitors. Since the protocol for each
monitor is not identical, the resulting
estimate should be viewed with cau-
tion. A more complete and accurate
view of PM10_2.5 values can be ob-
tained by nationwide deployment of
PM10 and PM15 monitors that use an
equivalent monitoring protocol. Fig-
ure 2-62 shows estimated annual
mean PM10_2.5 and Figure 2-63 shows
the estimated 98th percentile 24-hour
average PM10_2.5 developed from 1999
FRM monitor data. The limited data
show that annual mean concentra-
tions vary widely, with higher con-
centrations in several areas of the
Midwest and southern California. A
similar pattern emerges for the esti-
mated 98th percentile 24-hour average
Figure 2-58. National direct PM2 5 emissions trend, 1990-1999 (traditionally
inventoried sources only).
~ Fuel Combustion ¦ Industrial Processing ~ Transportation
Thousand Short Tons Per Year
3,000
2,500
2,000
500
0
90 91 92 93 94 95 96 97 98 99
Figure 2-59. Direct PM2s emissions from traditionally inventoried source categories,
1999.
Fuel Combustion 33.0%
Industrial Processes 39.4%
Transportation 27.6%
58 CRITERIA POLLUTANTS —NATIONAL TRENDS • CHAPTER 2
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 2-60. Total direct PM2 5 emissions by source category, 1999. PM10_2.5 concentrations. Though the
Southeast data is relatively incom-
plete, preliminary estimates suggest
Traditionally Invent 20.7% relatively low PMUV2 5 levels through-
out that region.
Miscellaneous 39.7%
/ Fugitive
Other Combustion 7.8%
Agriculture & Forest 8.4%
Figure 2-61. National ammonia emissions by principal source categories, 1999.
Waste Disposal & Recycling
Chemical & Allied
Product Manufacturing
All Other 2.9%
1.8%
2.7%
Onroad &
Nonroad Engineering
5.4%
Miscellaneous
(Includes livestock
& fertilzer)
87.2%
CHAPTER 2 • CRITERIA POLLUTANTS — NATIONAL TRENDS
59
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 2-62. Estimated 1999 annual mean PM10_2 5.
Alaska
Hawaii
Data Completeness Concentration (uo/m31
less o <4 quarters 0 >30
IO one or more quarters with < 11 samples O 15-30
O All quarters with at least 11 samples 9 10-15
more O All quarters 75% or more complete # 0-10
Figure 2-63. Estimated 1999 98th percentile 24-hour average PM10-2.5 developed from 1999 FRM monitor data.
Alaska
Hawaii
Puerto Rico
Data Completeness Concentration (ua/m3>
less o <4 quarters of data 0 >90
to one or more quarters with < 75% of scheduled samples O 40-90
O All quarters with at least 75% of scheduled samples # 25-40
more 0 Q. 25
60 CRITERIA POLLUTANTS —NATIONAL TRENDS • CHAPTER 2
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Sulfur Dioxide
Nature and Sources
Sulfur dioxide (S02) belongs to the
family of sulfur oxide (SOx) gases.
These gases are formed when fuel
containing sulfur (mainly coal and
oil) is burned, and during metal
smelting and other industrial process-
es. The highest monitored concentra-
tions of S02 have been recorded in the
vicinity of large industrial facilities.
Health and Environmental Effects
High concentrations of S02 can result
in temporary breathing impairment
for asthmatic children and adults
who are active outdoors. Short-term
exposures of asthmatic individuals to
elevated S02 levels while at moderate
exertion may result in reduced lung
function that may be accompanied by
symptoms such as wheezing, chest
tightness, or shortness of breath.
Other effects that have been associat-
ed with longer-term exposures to
high concentrations of S02, in con-
junction with high levels of PM, in-
clude respiratory illness, alterations
in the lungs' defenses, and aggrava-
tion of existing cardiovascular dis-
ease. The subgroups of the
population that may be affected un-
der these conditions include individ-
uals with cardiovascular disease or
chronic lung disease, as well as chil-
dren and the elderly.
Additionally, there are a variety of
environmental concerns associated
with high concentrations of S02.
Because S02, along with NOx, is a
major precursor to acidic deposition
(acid rain), it contributes to the acidi-
fication of soils, lakes and streams
and the associated adverse impacts
on ecosystems (see Chapter 7, Atmo-
spheric Deposition of Sulfur and
Nitrogen Compounds). Sulfur diox-
ide exposure to vegetation can in-
crease foliar injury, decrease plant
growth and yield, and decrease the
number and variety of plant species
in a given community. Sulfur dioxide
also is a major precursor to PM25
(aerosols), which is of significant
concern to human health (as dis-
cussed in the particulate matter sec-
tion of this chapter), as well as a main
pollutant that impairs visibility (see
Chapter 6, Visibility Trends). Finally,
S02 can accelerate the corrosion of
natural and man-made materials
(e.g., concrete and limestone) which
are used in buildings and monu-
ments, as well as paper, iron-contain-
ing metals, zinc and other protective
coatings.
Primary and Secondary
Standards
There are both short- and long-term
primary NAAQS for S02. The
short-term (24-hour) standard of 0.14
ppm (365 ]Ug/m3) is not to be exceed-
ed more than once per year. The
long-term standard specifies an annu-
al arithmetic mean not to exceed
0.030 ppm (80 ]Ug/m3). The second-
ary NAAQS (3-hour) of 0.50 ppm
(1,300 ]Ug/m3) is not to be exceeded
more than once per year. The stan-
dards for S02 have undergone peri-
odic review, but the science has not
warranted a change since they were
established in 1972.
National 10-Year Air Quality
Trends
The national composite average of
S02 annual mean concentrations
decreased 36 percent between 1990-
1999 as shown in Figure 2-64, with
the largest single-year reduction (16
percent) occurring between 1994 and
1995.30 The composite trend has since
leveled off, declining only 3 percent
from 1998-1999. This same general
trend is seen in Figure 2-65, which
plots the ambient concentrations
grouped by rural, suburban, and
urban sites. It shows that the mean
concentrations at the urban and sub-
urban sites are consistently higher
than those at the rural sites. Howev-
er, the 1994-1995 reduction in the
concentrations at non-rural sites does
narrow the gap between the trends.
The greater reduction seen in the
non-rural sites reflects the fact that
the proportion of non-rural sites is
greater in the eastern United States,
which is where most of the 1994-1995
emissions reductions at electric utili-
ties occurred.34 The national compos-
ite second maximum 24-hour S02
annual mean concentrations de-
creased 38 percent between 1990 and
1999, as shown in Figure 2-64 with
the largest single-year reduction (25
percent) occurring between 1994 and
1995. See also Chapter 7, Atmospher-
ic deposition of Sulfur and Nitrogen
Compounds. A map of 1999 S02
Air Quality Concentrations
1980-99
50%
decrease
1990-99
36%
decrease
1998-99
2%
decrease
Emissions
1980-99
27%
decrease
1990-99
20%
decrease
1998-99
3%
decrease
Worth Noting:
• Steady 20-year improvement has
reduced S02 ambient concentrations by
one-half and emissions by one-third.
• Phase II of the Acid Rain Program was
implemented in 2000 and should result in
significant new reductions.
CHAPTER 2 • CRITERIA POLLUTANTS — NATIONAL TRENDS
61
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
monitor locations may be found in
Figure B-6 in Appendix B.
National Emissions Trends
National S02 emissions decreased 20
percent between 1990 and 1999, with
a sharp decline between 1994 and
1995, similar to the decline in the
ambient concentrations. Unlike the
air quality trend, however, the emis-
sions trend remains essentially level
from 1996-1999, as shown in Figure
2-66. This dramatic reduction in 1995
was caused by implementation of the
Acid Rain Program; subsequent year-
to-year variations are driven in part
by the yearly changes in emissions
from the electric utility industry. The
electric utility industry accounts for
most of the fuel combustion category
in Figure 2-67. In particular, the coal-
burning power plants have consis-
tently been the largest contributor to
S02 emissions, as documented in
Table A-8 in Appendix A. See also
Chapter 7, Atmospheric Deposition of
Sulfur and Nitrogen Compounds.
The Acid Rain Program
The substantial national reductions in
S02 emissions and ambient S02 and
sulfate concentrations from 1994-
1999) are due mainly to Phase I im-
plementation of the Acid Rain
Program. Established by EPA under
Title IV of the CAAA, the Acid Rain
Program's principal goal is to achieve
significant reductions in S02 and NOx
emissions from electric utilities.
Phase I compliance for S02 began in
1995 and significantly reduced emis-
sions from the participating utilities.35
Table 2-6 shows this reduction in terms
of units required to participate in
Phase I and other units.
Between 1996-1998 total S02 emis-
sions from electric utilities have in-
creased slightly, compared to 1995. In
Figure 2-64. Trend in annual mean S02 concentrations, 1980-1999.
Concentration, ppm
0.04
National Standard
0.03
0.02
90% of sites have concentrations below this line
438 Sites
0.01
480 Sites
Average
A 1 Q% of sites have concentrations below this line
80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99
Note: When the total number of rural, suburban, and urban sites are summed for either the
1980-89 or 1990-99 time periods in Figure 2-26, this number may not equal the total
number of sites shown in Figure 2-25 for the same time periods. This is due to a few
monitoring sites falling outside the definitions of rural, suburban, or urban sites.
Figure 2-65. Annual mean S02 concentration by trend location, 1980-1999.
Concentration, ppm
0.012
0.01
0.008
0.006
0.004
1980-89 1990-99
117
Rural Sites
123
Suburban Sites 180
215
0.002
Urban Sites
133
131
80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99
62 CRITERIA POLLUTANTS —NATIONAL TRENDS • CHAPTER 2
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 2-66. National total S02 emissions trend, 1980-1999.
Thousand Short Tons Per Year
30,000
25,000
~ Fuel Combustion ¦ Industrial Processing
~Transportation ~Miscellaneous
20,000
15,000
10,000
5,000
In 1985, EPA refined its methods for estimating emissions
90 91 92 93 94 95 96 97 98 99
Figure 2-67. S02 emissions by source category, 1999.
Miscellaneous 0.1%
Transportation 6.9%
Industrial Processes 7.8%
Fuel Combustion 85.3%
1999, however, total S02 emissions
have decreased, matching 1995 levels.
Again, Table 2-6 explains this increase
in terms of Phase I units and Non-
Phase I units. Most Phase I plants
over-complied in Phase I (1995-1999),
banking their S02 allowances for use
in Phase II, resulting in significant
early reductions. However, some
Phase I units did increase their emis-
sions during these years, compared to
1995. Since Phase I units account for
only 18 percent of the total 1996-1998
increase, the majority of the increase
is attributed to those units not yet
participating in the Acid Rain Pro-
gram until Phase II, which began in
2000. When fully implemented, total
S02 emissions from electric utilities
will be capped at 8.95 million tons
per year under the Acid Rain Pro-
gram. For more information on the
Acid Rain Program, visit http://
www.epa.gov/airmarkets. See also
Chapter 7, Atmospheric Deposition of
Sulfur and Nitrogen Compounds.
National 20-Year Air Quality
Trends
The progress in reducing ambient S02
concentrations during the past 20
years is shown in Figure 2-68. While
there is a slight disconnect in the
trend line between 1989 and 1990 due
to the mix of trend sites in each
10-year period, an overall downward
trend is evident. The national 1999
composite average S02 annual mean
concentration is 50 percent lower
than 1980. In addition to the previ-
ously mentioned effects of the Acid
Rain Program, these steady reduc-
tions over time were accomplished by
installing flue-gas control equipment
at coal-fired generating plants, reduc-
ing emissions from industrial pro-
cessing facilities such as smelters and
sulfuric acid manufacturing plants,
CHAPTER 2 • CRITERIA POLLUTANTS — NATIONAL TRENDS 63
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
reducing the average sulfur content
of fuels burned, and using cleaner
fuels in residential and commercial
burners.
Regional Air Quality Trends
The map of regional trends in Figure
2-69shows that ambient S02 concen-
trations are generally higher in the
eastern United States. The effects of
Phase I of the Acid Rain Program are
seen most vividly in the northeast. In
particular, concentrations fell 20-25
percent between 1994 and 1995 in
EPA Regions 1,2,3, and 5. These
broad regional trends are not surpris-
ing since most of the units affected by
Phase I of the Acid Rain Program also
are located in the east as shown in
Figure 2-70 This figure also shows
that ambient concentrations have
increased slightly between 1995 and
1997 in Regions 3 and 4 where many
of the electric utility units not yet
affected by the Acid Rain Program
are located.
1999 Air Quality Status
The most recent year of ambient data
shows that all counties did meet the
primary S02 short-term standard,
according to Figure 2-71.
Table 2-6. Total S02 Emissions from Phase I and Non-Phase I Acid Rain Sources:
1990-1999 (million tons).
1990***
1995
1996
1997
1998
1999
Phase I (Table I) Units*
Non-Phase I Units**
All Electric Utility Units
8.7
7.03
15.73
4.455
7.408
11.863
4.765
7.749
12.514
4.769
8.209
12.978
4.66
8.474
13.134
4.348
8.104
12.452
* does not include substitution, compensating and opt-in units
** includes substitution, compensating, opt-in and Phase II units
*** Acid Rain phased requirements began in 1995
S02 Emissions from Title IV Sources
20
18
16
14
CM
o
to 12
0 10
1 8
1 6
4
2
0
1980 1985 1990 1995 1996 1997 1998 1999
Allowances issued/allowable
emissions for 263 Phase I units.
Figure 2-68. Long-term ambient S02 trend, 1980-1999.
Concentration, ppm
0.014
0.012
0.01
0.008
0.006
0.004
0.002
0
80 82 84 86 88 90 92 94 96 98
~ Phase II Sources
17.30
~ Substitution, Compensating & Opt-in units
¦ Phase I Sources
16 09 I 15.73
12.51 12.98 13.13
11.87
4.35
4.45
4.77
4.77
4.66
8.70
9.30
9.40
1980-89 1990-99
(438 sites) (480 sites)
64 CRITERIA POLLUTANTS —NATIONAL TRENDS • CHAPTER 2
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 2-69. Trend in S02 annual arithmetic mean concentration by EPA region, 1980-1999.
.0120
¦¦^0050
~ 58%
.0064
~ 52%
.0112
f 47%
V.0059
.0148"^
64%
. .0054
.0107
•f- 56%
,.0047
.0051
.0032
#63%
.0094
f 50%
s.0047
.0141
f 43%
, .0080
The National Trend
.0103
.0052
~ 50%
.0066
. .0038
f - 42%
.0096
154%
.0044
Note: These trends are
influenced by the
distribution of monitoring
locations in a given region
and, therefore, can be
driven largely by urban
concentrations. For this
reason, they are not
indicative of background
regional concentrations.
Alaska is in EPA Region 10; Hawaii, EPA Region 9; and Puerto Rico, EPA Region 2.
Concentrations are ppm.
Figure 2-70. Plants affected by the Acid Rain Program.
Phase 1 (1995)
Phase 2 (2000)
CHAPTER 2 • CRITERIA POLLUTANTS — NATIONAL TRENDS
65
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 2-71. Highest 2nd maximum 24-hour S02 concentration by county, 1999.
Concentration (ppm)
66 CRITERIA POLLUTANTS —NATIONAL TRENDS • CHAPTER 2
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
References
1. Note that due to the annual loss
and replacement of ambient monitor-
ing sites (e.g., redevelopment, new
leases, etc.), too few sites possess a
monitoring record sufficient to con-
struct a representative 20-year trend
for the nation. Therefore, this report
assesses long-term trends by piecing
together two separate 10-year trends
databases.
2. The methods used to estimate CO
emissions of some source categories
are not consistent in all years over the
period between 1980 and 1999. Chang-
es from one method to another make
the emissions trend over time appear
different than it actually has been. Of
particular note is that for 1999, CO
emissions from three source categories
of open burning are estimated differ-
ently than in previous years and show
a substantial increase compared to
estimates for prior years. These cate-
gories of open burning of residential
waste, yard waste, and land clearing
waste are included in the 'industrial
processing' sector of Figure 2-6. The
apparent increase in emissions from
this sector, and in total CO emissions,
from 1998 to 1999 is the result of this
change in estimation methodology.
3. Oxygenated Gasoline Implementation
Guidelines, EPA, Office of Mobile
Sources, Washington, D.C., July 27,
1992.
4. Guidelines for Oxygenated Gasoline
Credit Programs and Guidelines on Estab-
lishment of Control Periods Under Section
211(m) of the Clean Air Act as Amended,
57 FR 47853 (October 20, 1992).
5. Interagency Assessment of Oxygenat-
ed Fuels, National Science and Technol-
ogy Council, Executive Office of the
President, Washington, D.C., June
1997.
6. Section 6 of TSCA gives EPA au-
thority to ban, phase out, limit or con-
trol the manufacture of any chemical
substance deemed to pose an unrea-
sonable risk to the public or the envi-
ronment. EPA expects to issue a full
proposal to ban or phase down MTBE
in early 2001.
7. "National Ambient Air Quality
Standards for Nitrogen Dioxide: Final
Decision," Federal Register, 61 FR 196,
Washington, D.C., October 8, 1996.
8. "Review of the National Ambient
Air Quality Standards for Nitrogen
Oxides: Assessment of Scientific and
Technical Information," EPA-452/R-95-
005, U.S. Environmental Protection
Agency, Research Triangle Park, N.C.,
September 1995.
9. Atmospheric concentrations of N02
are determined by indirect photomulti-
plier measurement of the luminescence
produced by a critical reaction of NO
with ozone. The measurement of N02
is based first on the conversion of N02
to NO, and then subsequent detection
of NO using this well characterized
chemiluminescence technique. This
conversion is not specific for N02,
hence chemiluminescence analyzers
are subject to interferences produced
by response to other nitrogen contain-
ing compounds (e.g., peroxyacetyl
nitrate [PAN]) that can be converted to
NO). The chemiluminescence tech-
nique has been reported to overesti-
mate N02 due to these interferences.
This is not an issue for compliance
since there are no violations of the N02
NAAQS. In addition, the interferences
are believed to be relatively small in
urban areas. The national and regional
air quality trends depicted are based
primarily on data from monitoring
sites in urban locations, and are ex-
pected to be reasonable representations
of urban N02 trends. That is not the
case in rural and remote areas, howev-
er, where air mass aging could foster
greater relative levels of PAN and
nitric acid and interfere significantly
with the interpretation of N02 moni-
toring data.
10. "1998 Compliance Report," U.S.
Environmental Protection Agency,
Acid Rain Program, Washington, D.C.,
August 1999.
11. "Identification of Ozone Areas
Attaining the 1-hour Standard and to
Which the 1-hour Standard is No
Longer Applicable; Final Rule," Federal
Register, 63 FR 2804, Washington, D.C.,
June 5, 1998.
12. "Identification of Additional Ozone
Areas Attaining the 1-hour Standard
and to Which the 1-hour Standard is
No Longer Applicable; Final Rule,"
Federal Register, 63 FR 39431, Washing-
ton, D.C., July 22, 1998.
13. "Identification of Additional Ozone
Areas Attaining the 1-hour Standard
and to Which the 1-hour Standard is
No Longer Applicable; Final Rule,"
Federal Register, 64 FR 30911, Washing-
ton, D.C., June 9, 1999.
14. "Rescinding Findings that the 1-
hour Ozone Standard No Longer Ap-
plies to Certain Areas; Final Rule,"
Federal Register, 64 FR 57424, Washing-
ton, D.C., November 5, 1999.
15. "National Ambient Air Quality
Standards for Ozone; Final Rule,"
Federal Register, 62 FR 38856, Washing-
ton, D.C., July 18, 1997.
16. W.M. Cox and S.H. Chu, "Meteoro-
logically Adjusted Ozone Trends in
Urban Areas: A Probabilistic Ap-
proach," Atmospheric Environment, Vol.
27B, No. 4, Pergamon Press, Great
Britain, 1993.
17. Currently, 24 of the nation's re-
maining 31 nonattainment areas for
the 1-hour ozone NAAQS are required
to operate PAMS sites ("Ambient Air
Quality Surveillance: Final Rule,"
Federal Register, 58FR 8452, Washing-
ton, D.C., February 12, 1993). Each
PAMS network consists of as many as
five monitoring stations, depending on
the area's population. These stations
are carefully located according to mete-
orology, topography, and relative prox-
imity to emissions sources of VOC and
NO . As of October 1999, there were
x '
83 active designated PAMS sites.
18. "Selected PAMS sites" refers to the
inclusion of only those sites with mea-
surements of NO or VOCs in both
x
CHAPTER 2 • CRITERIA POLLUTANTS — NATIONAL TRENDS
67
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
1995 and 1999. Morning periods for
NO and VOCs are used because those
x
time frames are generally thought to be
an appropriate indicator of anthropo-
genic emissions.
19. These 24 VOC species are the focus
of this analysis because they account
for more than 75 percent (by volume)
of the VOCs concentrated on in the
PAMS program.
20. CASTNet is considered the nation's
primary source for atmospheric data to
estimate dry acidic deposition and to
provide data on rural ozone levels.
Used in conjunction with other nation-
al monitoring networks, CASTNet is
used to determine the effectiveness of
national emission control programs.
Established in 1987, CASTNet now
comprises 79 monitoring stations
across the United States. The longest
data records are primarily at eastern
sites. The majority of the monitoring
stations are operated by EPA's Office of
Air and Radiation; however, 27 sta-
tions are operated by the National Park
Service (NPS) in cooperation with EPA.
The CASTNet data complement the
larger ozone data sets gathered by the
State and Local Monitoring (SLAMS)
and National Air Monitoring (NAMS)
networks with additional rural cover-
age. A more detailed treatment of
CASTNet's atmospheric deposition
role and data are provided in Chapter
7: Atmospheric Deposition of Sulfur
and Nitrogen Compounds.
21. Similarly, although registering
declines in 8-hour ozone levels of 17
and 12 percent respectively over the
last 20 years, neither urban nor subur-
ban sites have shown any improve-
ment in ozone concentrations between
1990-1999.
22. This analysis utilizes a non-para-
metric regression procedure to assess
statistical significance a description of
which is provided in Chapter 3: Crite-
ria Pollutants - Metropolitan Area
Trends.
23. "Volatility Regulations for Gasoline
and Alcohol Blends Sold in Calendar
Years 1989 and Beyond," Federal Regis-
ter, 54 FR 11868, Washington, D.C.,
March 22,1989.
24. "Reformulated Gasoline: A Major
Step Toward Cleaner Air," EPA-420-B-
94-004, U.S. Environmental Protection
Agency, Office of Air and Radiation,
Washington, D.C., September 1994.
25. The Clean Air Act requires that
RFG contain 2 percent oxygen by
weight. "Requirements for Reformu-
lated Gasoline," Federal Register, 59 FR
7716, Washington, D.C., February 16,
1994.
26. The Panel's Executive Summary
and final report entitled "Achieving
Clean Air and Clean Water: The Report of
the Blue Ribbon Panel on Oxygenates in
Gasoline" can be found at: http://
www.epa.gov/oms/consumer/fuels/
oxypanel/blueribb.htm
27. National Air Pollutant Emission
Trends, 1900-1998, EPA-454/R-00-002,
U.S. Environmental Protection Agency,
Research Triangle Park, NC 2000.
28. 1996 PM Criteria Document, http://
www.epa.gov/ttn/oarpg/tlcd.html.
29. National Ambient Air Quality Stan-
dards for Particulate Matter: Final Rule,
July 18, 1997. (62 FR 38652), http://
www.epa.gov/ttn/oarpg/tl/fr_notices/
pmnaaqs.pdf.
30. Revised Requirements for Designation
of Reference and Equivalent Methods for
PM2.5 and Ambient Air Quality Surveil-
lance for Particulate Matter: Final Rule,
July 18, 1997, http://www.epa.gov/ttn/
oarpg/tl/fr_notices/pm_mon.pdf.
31. Personal communication with EPA
Region 9.
32. Personal communication with EPA
Region 3.
33. National Air Pollutant Emissions
Trends, 1900-1998, EPA-454/R-00-002,
U.S. Environmental Protection Agency,
Office of Air Quality Planning and
Standards, Research Triangle Park, NC
27711, March 2000.
34. IMPROVE, Cooperative Center for
Research in the Atmosphere, Colorado
State University, Ft. Collins, CO, May
2000.
35. 1997 Compliance Report: Acid Rain
Program, EPA-430-R-98-012, U.S. Envi-
ronmental Protection Agency, Office
of Air and Radiation, Washington,
D.C., August 1998.
68 CRITERIA POLLUTANTS —NATIONAL TRENDS • CHAPTER 2
-------
Criteria Pollutants —
Metropolitan Area Trends
http://www.epa.gov/oar/aqtrnd99/chapter3.pdf
Worth Noting:
• Out of 263 metropolitan statistical areas, 34 have significant upward trends.
• Of these, trends with values over the level of the air quality standards involved only
8-hour ozone.
This chapter presents status and
trends in criteria pollutants for metro-
politan statistical areas (MSAs) in the
United States. The MSA status and
trends give a local picture of air pol-
lution and can reveal regional pat-
terns of trends. Such information can
allow one to gauge the air pollution
situation where they live, and can be
very useful in formulating plans for
community based programs.1 Not all
areas in the country are in MSAs, and
not all MSAs are included here. A
complete list of MSAs and their
boundaries can be found in the Statis-
tical Abstract of the United States.2
The status and trends of metropolitan
areas are based on four tables found
in Appendix A (A-15 through A-18).
Table A-15 gives the 1999 peak statis-
tics for all MSAs, providing the status
of that year. Ten-year trends are
shown for the 263 MSAs having data
that meet the trends requirements
explained in Appendix B. Table A-16
lists these MSAs and reports criteria
pollutant trends as "upward" or
"downward," or "not significant."
These categories are based on a statis-
tical test, known as the Theil test,
described later in this chapter.
Another way to assess trends in
MSAs is to examine Air Quality Index
(AQI) values.3'4'5 The AQI is used to
present daily information, on one or
more criteria pollutants in an easily
understood format, to the public in a
timely manner. Tables A-17 and A-18
list the number of days with AQI
values greater than 100 for the
nation's 94 largest metropolitan areas
(population greater than 500,000).
Table A-17 lists AQI values based on
all pollutants, while Table A-18 lists
AQI values based on ozone alone.
The tables listing PSI data from previ-
ous reports may not agree with the
tables in this report because of the
new way to calculate the AQI. These
changes are presented in more detail
later in this chapter.
Not every MSA appears in these
tables. Some do not appear because
the population is so small or the air
quality is so good that AQI reporting
is not presently required. There are
MSAs with no ongoing air quality
monitoring for one or more of the
criteria pollutants, because it is not
needed. Ambient monitoring for a
particular pollutant may not be con-
ducted if there is no problem. In
addition, there are also MSAs with
too little monitoring data for trends
analysis purposes (see Appendix B).
Status: 1999
The air quality status for MSAs can
be found in Table A-15.** Table A-15
lists peak statistics for all criteria
pollutants measured in an MSA. As
discussed above, not all criteria pol-
lutants are measured in all MSAs.
This is why data for some MSAs are
designated as "ND" (no data) for
those pollutants. Examining Table
A-15 shows that 163 areas had peak
concentrations exceeding standard
levels for at least one criteria pollut-
ant. The number of these areas de-
creased 6 percent over the count from
1998 data (173 areas). These 163 areas
contain 58 percent of the U.S. popula-
tion. Similarly, there were eight areas
(with 8 percent of the population)
that had peak statistics that exceeded
two or more standards. Only one
area, Los Angeles, CA (with 4 percent
of the U.S. population), had peak
statistics from three pollutants that
**For related information, see Table A-14,
peak concentrations for all counties with moni-
tors that reported to the Aerometric Information
Retrieval System (AIRS) database.
CHAPTER 3 • CRITERIA POLLUTANTS—METROPOLITAN AREA TRENDS 69
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table 3-1. Summary of MSATrend Analyses by Pollutant, 1990-1999
Trend Statistic
Total #
MSAs
# MSAs
Up
# MSAs
Down
# MSAs
with No
Significant
Change
CO
second max 8-hour
138
0
107
31
Lead
max quarterly mean
69
1
44
24
no2
arithmetic mean
99
3
41
55
Ozone
fourth max 8-hour
207
25
10
172
Ozone
second daily max 1-hour
207
17
14
176
PM-io
90th percentile
216
1
113
102
PM-io
weighted annual mean
216
2
126
88
so2
arithmetic mean
148
1
86
61
so2
second max 24-hour
149
1
82
66
exceeded the respective standards.
There were no areas that violated
four or more standards.
Trends Analysis
Table A-16 displays air quality trends
for MSAs. The data in this table are
average statistics of pollutant concen-
trations from the subset of ambient
monitoring sites that meet the trends
criteria explained in Appendix B. A
total of 258 MSAs have at least one
monitoring site that meets these crite-
ria. As stated previously not all pol-
lutants are measured in every MSA.
From 1990-1999, statistics based on
the Standards were calculated for
each site and pollutant with available
data. Spatial averages were obtained
for each of the 263 MSAs by averag-
ing these statistics across all sites in
an MSA. This process resulted in one
value per MSA per year for each pol-
lutant. Although there are seasonal
patterns of high values for some pol-
lutants in some locations, the averag-
es for every MSA and year provide a
consistent indicator with which to
assess trends.
Since air pollution levels are af-
fected by variations in meteorology,
emissions, and day-to-day activities
of populations in MSAs, trends in air
pollution levels are not always well
defined. To assess upward or down-
ward trends, a statistical significance
test was applied to these data. An
advantage of using the statistical test
is the ability to test whether or not
the upward or downward trend is
real (significant) or just a chance
product of year-to-year variation (not
significant). Since the underlying
pollutant distributions do not meet
the usual assumptions required for
common significance tests, the test
was based upon a nonparametric
method commonly referred to as the
Theil test.6'7'8'9 Because linear regres-
sion estimates the trend from changes
during the entire 10-year period, it is
possible to detect an upward or
downward trend even when the con-
centration level of the first year
equals the concentration level of the
last year.
Table 3-1 summarizes the trend
analysis performed on the 263 MSAs.
It shows that there were no upward
trends in carbon monoxide (CO) for
any MSA. Lead, the 90th percentile of
PMio and sulfur dioxide had upward
trends at only one MSA over the past
decade. Further examination of Table
A-16 shows that of the 263 MSAs: 1)
214 had downward trends in at least
one of the criteria pollutants; 2) 34
had upward trends (of these 34,26
also had downward trends in other
pollutants (leaving 8 MSAs with
exclusively upward trends); and 3) 41
MSAs had no significant trends. A
closer look at the 34 MSAs with up-
ward trends reveals that most (20)
were exceeding the level of the
8-hour ozone standard. For all other
pollutants with upward trends in any
MSA, the levels observed were well
below standard levels. Taken as a
whole, these results demonstrate
significant improvements in urban air
quality over the past decade for the
nation.
The Air Quality Index
The AQI provides information on
pollutant concentrations for
ground-level ozone, particulate mat-
ter, carbon monoxide, sulfur dioxide,
and nitrogen dioxide. Formerly
known as the Pollutant Standards
Index (PSI), this nationally uniform
air quality index is used by state and
local agencies for reporting daily air
quality to the public. In 1999, EPA
updated the AQI to reflect the latest
science on air pollution health effects
and to make it more appropriate for
use in contemporary news media,
thereby enhancing the public's un-
derstanding of air pollution across
the nation. Currently, the AQI may be
found in national media such as USA
Today and on the Weather Channel, as
well as local newspapers and broad-
70 CRITERIA POLLUTANTS—METROPOLITAN AREA TRENDS • CHAPTER 3
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
casts across the country. It also serves
as a basis for community-based pro-
grams that encourage the public to
take action to reduce air pollution on
days when levels are projected to be
of concern. An Internet website,
AIRNOW (http://www.epa.gov/
airnow), which presents "real time"
air quality data and forecasts of sum-
mertime smog levels for most states,
uses the AQI to communicate infor-
mation about air quality. The Index
has been adopted by many other
countries (e.g., Mexico, Singapore,
and Taiwan) and is used around the
world to provide the public with infor-
mation on air pollutants.
AQI values for each of the pollut-
ants are derived from concentrations
of that pollutant. The Index is "nor-
malized" across each pollutant so
that, generally, an Index value of 100
is set at the level of the short-term,
health-based standard for that pollut-
ant. An Index value of 500 is set at
the significant harm level, which
represents imminent and substantial
endangerment to public health.***
The higher the Index value, the
greater the level of air pollution and
health risk. To make the AQI as easy
to understand as possible, EPA has
divided the AQI scale into six general
categories that correspond to a differ-
ent level of health concern. Because
different groups of people are sensi-
tive to different pollutants, there are
pollutant-specific health effects and
cautionary statements for each cat-
egory in the AQI:
• Good (AQI values between 0 and
50) Air quality is considered satis-
factory and air pollution poses lit-
tle or no risk.
• Moderate (AQI values between 51
and 100) Air quality is acceptable;
however, for some pollutants there
may be a moderate health concern
for a very small number of individu-
als. For example, people who are
unusually sensitive to ozone may
experience respiratory symptoms.
• Unhealthy for Sensitive Groups
(AQI values between 101 and 150)
Certain groups of people are par-
ticularly sensitive to the harmful
effects of certain air pollutants.
This means they are likely to be af-
fected at lower levels than the gen-
eral public. For example, children
and adults who are active out-
doors and people with respiratory
disease are at greater risk from ex-
posure to ozone, while people
with heart disease are at greater
risk from carbon monoxide. When
the AQI is in this range, members
of sensitive groups may experience
health effects, but the general pub-
lic is not likely to be affected.
• Unhealthy (AQI values between
151 and 200) Everyone may begin
to experience health effects. Mem-
bers of sensitive groups may expe-
rience more serious health effects.
• Very Unhealthy (AQI values be-
tween 201 and 300) Air quality in
this range triggers a health alert,
meaning everyone may experience
more serious health effects.
• Hazardous (AQI values over 300)
Air quality in this range triggers
health warnings of emergency con-
ditions. The entire population is
likely to be affected.
An AQI report will contain an
Index value, category name, and the
pollutant of concern, and is often
featured on local television or radio
news programs and in newspapers,
especially when values are high. For
national consistency and ease of un-
derstanding, there are specific colors
associated with each category that are
required if the AQI is reported using
color. Examples of the use of color in
Index reporting include the color bars
that appear in many newspapers, and
the color contours of the ozone Map.
The six AQI categories, their respec-
tive health effects descriptors, colors,
index ranges, and corresponding
concentration ranges are listed in
Table 3-2. The EPA has also developed
an AQI logo (Figure 3-1) to increase the
awareness of the AQI in such reports
and also to indicate that the AQI is
uniform throughout the country.
The AQI integrates information on
pollutant concentrations across an
entire monitoring network into a
single number that represents the
worst daily air quality experienced in
an urban area. For each of the pollut-
ants, concentrations are converted
into Index values between zero and
500. The pollutant with the highest
Index value is reported as the AQI for
that day. There is a new AQI require-
ment to report any pollutant with an
Index value above 100. In addition,
when the AQI is above 100 a
pollutant-specific statement indicat-
ing what specific groups are most at
risk must be reported. For example,
when the Index is above 100 for
ozone the AQI report will contain the
statement "Children and people with
asthma are the groups most at risk."
The AQI must be reported in all
MS As with air quality problems and
populations greater than 350,000
according to the 1990 census. Previ-
ously, urbanized areas with popula-
tions greater than 200,000 were
required to report the Index.
"""Based on the short-term standards, Federal
Episode Criteria, and Significant Harm Levels,
the AQI is computed for PM (particulate
matter), SO2, CO, O3, and NO2. Lead is the
only criteria pollutant not included in the
index because it does not have a short-term
standard, a Federal Episode Criteria, or a
Significant Harm Level.
CHAPTER 3 • CRITERIA POLLUTANTS—METROPOLITAN AREA TRENDS 71
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table 3-2. AQI Categories, Colors, and Ranges
Category AQI 03 (ppm) 03 (ppm) PM2 5 PM10 CO (ppm) S02 (ppm) N02 (ppm)
8-hour 1-hour (|jg/m3) (|jg/m3)
Good
0-
¦50
0.000 -
-0.064
(2)
0.0'
-15.4
0-
-54
0.0-
-4.4
0.000 -
-0.034
(:
!)
Moderate
51 -
¦100
0.065 -
-0.084
(2)
15.5
-40.4
55-
-154
4.5-
-9.4
0.035 -
-0.144
f
!)
Unhealthy for
101 ¦
-150
0.085 -
-0.104
0.125-0.164
40.5
-65.4
155
-254
9.5-
12.4
0.145 -
-0.224
(:
!)
Sensitive Groups
Unhealthy
151 ¦
-200
0.105 -
-0.124
0.165-0.204
65.5 -
-150.4
255
-354
12.5 -
-15.4
0.225 -
-0.304
(:
!)
Very unhealthy
201 ¦
-300
0.125 -
-0.374
0.205-0.404
150.5
-250.4
355
-424
15.5 -
-30.4
0.305 -
-0.604
0.65 -
-1.24
Hazardous
301 ¦
-400
(
')
0.405-0.504
250.5
-350.4
425
-504
30.5-
-40.4
0.605-
-0.804
1.25-
-1.64
401 ¦
-500
(
')
0.505-0.604
350.5
-500.4
505
-604
40.5-
-50.4
0.805-
-1.004
1.65-
-2.04
1. No health effects information for these levels-use 1-hour concentrations.
2. 1 -hour concentrations provided for areas where the AQI is based on 1 -hour values might be more cautionary.
3. N02 has no short-term standard but does have a short-term "alert" level.
Figure 3-1. Air Quality Index logo.
AIR QUALITY INDEX
Summary of AQI
Analyses
Of the five criteria pollutants used to
calculate the AQI, only four (CO, 03,
PM10, and S02) generally contribute
to the AQI value. Nitrogen dioxide is
rarely the highest pollutant measured
because it does not have a short-term
standard and can only be included
when the Index reaches a value of 200
or greater. Ten-year AQI trends are
based on daily maximum pollutant
concentrations from the subset of ambi-
ent monitoring sites that meet the
trends requirements in Appendix B.
Since an AQI value greater than
100 indicates that at least one criteria
pollutant has reached levels where
people in sensitive groups are likely
to suffer health effects, the number of
days with AQI values greater than
100 provides an indicator of air qual-
ity in urban areas. Figure 3-2 shows
the trend in the number of days with
AQI values greater than 100 summed
across the nation's 94 largest metro-
politan areas. This number is ex-
pressed as a percentage of the days in
the first year (1990). Because of their
magnitude, AQI totals for Los Ange-
les, CA; Riverside, CA; Bakersfield,
CA; Ventura CA; Orange County, CA;
and San Diego, CA are shown sepa-
rately as southern California. Plot-
ting these values as a percentage of
1990 values allows two trends of
different magnitudes to be compared
on the same graph. The long-term air
quality improvement in southern
California urban areas is evident in
this figure. Between 1990 and 1999,
the total number of days with AQI
values greater than 100 decreased 62
percent in southern California but
actually rose 25 percent in the re-
maining major cities across the
United States (see Figure 3-2).
While five criteria pollutants can
contribute to the AQI, the index is
driven mostly by ozone. AQI esti-
mates depend on the number of pol-
lutants monitored as well as the
number of monitoring sites where
data are collected. The more pollut-
ants measured and the more sites that
are available in an area, the better the
estimate of the AQI for a given day.
Historically, ozone accounts for the
majority of days with AQI values
above 100. Soon, PM2.5 will also be
monitored and reported on a regular
basis, which will reduce the percent-
age of days that ozone is the AQI
pollutant. Table A-18 shows the num-
ber of days with AQI values greater
than 100 that are attributed to ozone
alone. Comparing Table A-17 and
A-18, the number of days with a AQI
above 100 are increasingly due to
ozone. In fact, the percentage of days
with a AQI above 100 due to ozone
have increased from 91 percent in
1990, to 98 percent in 1999 (See Figure
3-3). This increase reveals that ozone
increasingly accounts for those days
72 CRITERIA POLLUTANTS—METROPOLITAN AREA TRENDS • CHAPTER 3
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 3-2. Number of days with AQI values > 100, as a percentage of 1990 value.
A Others
Southern
California
above the 100 level and, therefore,
reflects the success in achieving lower
CO and PM10 concentrations. How-
ever, the typical one-in-six day sam-
pling schedule for most PM10 sites
limits the number of days that PM10
can factor into the AQI determina-
tion, which may, in some places, ac-
count for the predominance of ozone.
Figure 3-3. Percent of days over 100 due to ozone.
u 95
90 91 92 93 94 95 96 97 98 99
CHAPTER 3 • CRITERIA POLLUTANTS—METROPOLITAN AREA TRENDS 73
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
References and Notes
1. Community Based Environmental
Protection (CBEP) is a relatively new
approach to environmental protection.
Traditionally, environmental protection
programs have focused on a particular
medium or problem (i.e., a "Command
and Control" approach to environmen-
tal protection). These "Command and
Control" programs have been very
effective at reducing point source pol-
lution and improving environmental
quality for more than two decades.
However, some environmental prob-
lems, such as non-point source pollu-
tion, which may involve several media
types and diffuse sources, are less
amenable to the "Command and Con-
trol" approach. Instead, a solution that
seeks to address the various causes of
the problems by focusing on the inter-
relationships between human behavior
and pollution in a specific area may be
more appropriate. CBEP supplements
and complements the traditional envi-
ronmental protection approach by
focusing on the health of an ecosystem
and the behavior of humans that live
in the ecosystem's boundaries, instead
of concentrating on a medium or par-
ticular problem. Therefore, CBEP is
place-based, and not media or
issue-based (see http://www.epa.gov/
ecocommunity/about.htm).
2. Statistical Abstracts of the United
States, 1999, U.S. Department of Com-
merce, U.S. Bureau of the Census.
3. Air Quality Index, A Guide to Air
Quality and Your Health, EPA-454/
R-00-005, U.S. Environmental Protec-
tion Agency, Office of Air Quality
Planning and Standards, Research
Triangle Park, NC, June 2000.
4. Code of Federal Regulations, 40 CFR
Part 58, Appendix G.
5. Guideline for Reporting of Daily Air
Quality—Air Quality Index (AQI), EPA-
454/R-99-010, U.S. Environmental
Protection Agency, Office of Air Quali-
ty Planning and Standards, Research
Triangle Park, NC, July 1999.
6. Note: Although the results are sum-
marized in the report for comparison
purposes, the intent of publishing
Tables A-16 through A-18 is to present
information on a localized basis, to be
used on a localized basis (i.e., one MSA
at a time). Therefore, no attempt was
made to adjust the Type I error to a
table-wide basis. All the tests for
trends were conducted at the 5-percent
significance level. No inference has
been made from the tables as a whole.
7. T. Fitz-Simons and D. Mintz, "As-
sessing Environmental Trends with
Nonparametric Regression in the SAS
Data Step," American Statistical Asso-
ciation 1995 Winter Conference, Ra-
leigh, NC, January, 1995.
8. Freas, W.P and E.A. Sieurin, "A
Nonparametric Calibration Procedure
for Multi-Source Urban Air Pollution
Dispersion Models," presented at the
Fifth Conference on Probability and
Statistics in Atmospheric Sciences,
American Meteorological Society, Las
Vegas, NV, November 1977.
9. M. Hollander and D.A. Wolfe,
Nonparametric Statistical Methods, John
Wiley and Sons, Inc., New York, NY,
1973.
74 CRITERIA POLLUTANTS—METROPOLITAN AREA TRENDS • CHAPTER 3
-------
CHAPTER 4
Criteria Pollutants —
Nonattainment Areas
114 nonattainment areas on the condensed
Worth Noting:
• As of September 2000, there were a total of
nonattainment list.
This chapter provides general infor-
mation on geographical regions
known as nonattainment areas.
When an area does not meet the air
quality standard for one of the crite-
ria pollutants the area may be subject
to the formal rule-making process
which designates the area as non-
attainment. The 1990 Clean Air Act
Amendments (CAAA) further classi-
fy ozone, carbon monoxide, and
some particulate matter nonattain-
ment areas based on the magnitude
of an area's problem. Nonattainment
classifications may be used to specify
what air pollution reduction mea-
Figure 4-1. Location of nonattainment areas for criteria pollutants, September 2000.
Note: Incomplete data, not classified, and Section 185a areas are not shown.
*Ozone nonattainment areas on map are based on the 1 -hour ozone standard.
**PMio nonattainment areas on map are based on the existing PM10 standards.
CHAPTER 4 • CRITERIA POLLUTANTS — NONATTAINMENT AREAS 75
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 4-2. Classified ozone nonattainment areas.
September 30, 2000
Classifications
¦ Extreme (LA) & Severe ¦ Serious ¦ Moderate ¦ Marginal
Note: San Francisco is classified Other / Sec 185a and nonattainment areas with incomplete data are not included.
sures an area must adopt and when
the area must reach attainment. The
technical details underlying these
classifications are discussed in the
Code of Federal Regulations, Part 81 (40
CFR 81), see http://www.epa.gov/
epacfr40.
Figure 4-1 shows the location of
the nonattainment areas for each
criteria pollutant as of September
2000. Figure 4-2 identifies the classi-
fied ozone nonattainment areas by
degree of severity. A summary of
nonattainment areas can be found in
Table A-19 in Appendix A. An area is
on the condensed list if the area is
designated nonattainment for one or
more of the criteria pollutants. Note
that Section 185a areas (formerly
known as "transitional areas") and
incomplete areas are excluded from
the counts in Table A-19. Another
source of information for areas desig-
nated as nonattainment, including
Section 185a and incomplete areas, is
the Green Book. The current Green
Book is located at http://
www.epa.gov/oar/oaqps/greenbk.
As of September 2000, there were a
total of 114 nonattainment areas on
the condensed nonattainment list.
The areas on the condensed list are
displayed alphabetically by state.
There were, as of September 2000,
approximately 101 million people
living in areas designated as non-
attainment for at least one of the
criteria pollutants. Areas redesig-
nated between September 1999 and
September 2000 are listed in Table
4-1, by pollutant. All redesignations
were to attainment.
76 CRITERIA POLLUTANTS — NONATTAINMENT AREAS • CHAPTER 4
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table 4-1. Areas Redesignated Between September 1999 and September 2000
CM
o
CO
Coshocton Co., OH; Gallia Co., OH; and Lorain Co., OH
PM10
Canon City, CO
CO
Colorado Springs, CO; Longmont, CO; and Minneapolis-
St. Paul, MN
Pb
Collin Co., TX and Marion Co. (Indianapolis), IN
o3
Cincinnati-Hamilton, OH-KY
CHAPTER 4 • CRITERIA POLLUTANTS
— NONATTAINMENT AREAS
77
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
78 CRITERIA POLLUTANTS — NONATTAINMENT AREAS • CHAPTER 4
-------
CHAPTER 5
Air Toxics
http://www.epa.gov/oar/aqtrnd99/chapter5.pdf
Worth Noting:
• For all 188 HAPs, there is a 23-percent
reduction in emissions between the
1990-1993 baseline and 1996. For the
33 urban HAPs, there is a 30-percent
reduction in air toxics emissions
between baseline and 1996. The
majority of these reductions are
attributable to two source types with
existing regulatory programs: major
sources and onroad mobile sources.
• Ambient monitoring results generally
reveal downward trends for most
monitored HAPs. The most consistent
improvements are apparent for benzene
which is predominantly emitted by
mobile sources; and for total suspended
lead. From 1994-1999, annual average
concentrations for these two HAPs
declined 40 and 47 percent respectively.
Background
Hazardous air pollutants (HAPs),
commonly referred to as air toxics or
toxic air pollutants are pollutants
known to cause or suspected of caus-
ing cancer or other serious human
health effects or ecosystem damage.
The Clean Air Act (CAA) lists 188
HAPs and directs EPA to regulate
sources emitting major amounts of
these identified pollutants.1 Examples
of HAPs include heavy metals (e.g.,
mercury and chromium), volatile
chemicals (e.g., benzene and perchlo-
roethylene), combustion byproducts
(e.g., dioxins) and solvents (e.g., car-
bon tetrachloride and methylene
chloride). In addition, EPA has recent-
ly listed diesel particulate matter plus
diesel exhaust organic gases as a
mobile source air toxic and has ad-
dressed diesel exhaust in several
regulatory actions. EPA's list of mo-
bile source air toxics also includes 20
other pollutants which are included
among the list of 188 HAPs.
Hazardous air pollutants are emit-
ted from literally thousands of
sources including large stationary
industrial facilities (such as electric
power plants), smaller area sources
(such as neighborhood dry cleaners),
mobile sources (such as automobiles),
indoor sources (such as some build-
ing materials and cleaning solvents),
and other sources (such as wildfires).
Factors such as weather, the terrain
(i.e., mountains, plains, valleys), and
the chemical and physical properties
of a pollutant determine how far it is
transported, its concentration at vari-
ous distances from the source, what
kind of physical and chemical
changes it undergoes, and whether it
will degrade, remain airborne, or
deposit to land or water. Some HAPs
(such as chromium) remain airborne
and contribute to air pollution prob-
lems far from the pollution source.
Other HAPs (such as mercury) are
released into the air and can be depos-
ited to land and water bodies through
precipitation, or by settling directly out
of the air onto land or water.
Potential Effects
of Air Toxics
Human Health
• Cancer
• Birth defects
• Developmental delays
• Reduced immunity
• Difficulty in breathing and respiratory
damage
• Headache, dizziness, and nausea
Environmental
• Reproductive effects and developmental
delays in wildlife
• Toxicity to aquatic plants and animals
• Accumulation of pollutants in the food
chain
Health and Environmental Effects
The degree to which a toxic air pol-
lutant affects a person's health de-
pends on many factors, including the
quantity of pollutant the person is
exposed to, the duration and frequen-
cy of exposures, the toxicity of the
pollutant, and the person's state of
health and susceptibility. The differ-
ent health effects that may be caused
by HAPs include cancer; neurologi-
cal, cardiovascular, and respiratory
CHAPTER 5 • AIR TOXICS 79
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
effects; effects on the liver, kidney,
immune system, and reproductive
system; and effects on fetal and child
development. The timing and severi-
ty of the effect (e.g., minor or revers-
ible vs. serious, irreversible, and
life-threatening) may vary among
HAPs and with the exposure circum-
stances. In some cases effects can be
seen immediately; in other cases the
resulting effects (e.g., liver damage or
cancer) are associated with long-term
exposures and may not appear until
years after exposure. Roughly half of
the 188 HAPs have been classified by
EPA as "known," "probable," or
"possible" human carcinogens.
Known human carcinogens are those
that have been demonstrated to cause
cancer in humans. Examples include
benzene, which has caused leukemia
in workers exposed over several
years in their workplace air, and ar-
senic, which has been associated with
elevated lung cancer rates in workers
at metal smelters. Probable and possi-
ble human carcinogens include chem-
icals that we are less certain cause
cancer in people, yet for which labo-
ratory animal testing or limited hu-
man data indicate carcinogenic
effects. For example, EPA concluded
that diesel exhaust is likely to be
carcinogenic to humans at environ-
mental levels that the public faces
(classifying it as a "probable human
carcinogen").2
Some HAPs pose particular haz-
ards to people of a certain stage in life
(e.g., young children, adolescents,
adults, or elderly people). Some
HAPs are developmental or repro-
ductive toxicants in humans. This
means that exposure before birth or
during childhood may interfere with
normal development into a healthy
adult. Other such exposures may
affect the ability to conceive or give
birth to a healthy child. Ethylene
oxide, for example, has been associ-
ated with increased miscarriages in
exposed workers and has affected
reproductive ability in both male and
female laboratory animals.
Some HAPs are of particular con-
cern because they degrade very
slowly or not at all, as in the case of
metals such as mercury or lead. These
persistent HAPs can remain in the
environment for a long time and can
be transported great distances. Per-
sistent and bioaccumulative HAPs
are of particular concern in aquatic
ecosystems because the pollutants
accumulate in sediments and may
biomagnify in tissues of animals at
the top of the food chain through
consumption or uptake to concentra-
tions many times higher than in the
water or air. In this case, exposure to
people occurs by eating contaminated
food from waters polluted from the
deposition of these HAPs. As of July
2000, for example, 40 states and the
American Samoa have issued fish
consumption advisories for mercury.
Thirteen of those states have issued
advisories for all water bodies in their
state and the other 27 states have
issued advisories for more than 1900
specific water bodies.3
Hazardous air pollutants can have
a variety of environmental impacts in
addition to the threats they pose to
human health. Like humans, animals
can experience health problems if
they are exposed to sufficient concen-
trations of HAPs over time. For ex-
ample, exposures to PCBs, dioxins,
and dibenzo-furans are suspected of
causing death and deformities to
various bird chicks.4 These pollut-
ants are also thought to have had
adverse impacts on reproduction of
lake trout.5 Mercury is also thought to
pose a significant risk to wildlife. Meth-
ylmercury levels in fish in numerous
waterbodies have been shown to ex-
ceed levels associated with adverse
effects on birds.6 These and other ob-
servations have led some scientists to
conclude that fish-eating birds and
mammals occupying a variety of habi-
tats are at risk due to high levels of
methylmercury in aquatic food webs.
National Air Toxics Control
Program
Since 1990, EPA has made consider-
able progress in reducing emissions
of air toxics through regulatory, vol-
untary, and other programs. To date,
the overall air toxics program has
focused on reducing emissions of the
188 air toxics from major stationary
sources through the implementation
of technology-based emissions stan-
dards as specified by Congress in the
1990 CAA Amendments. These ac-
tions have resulted in, or are project-
ed to result in, substantial reductions
in air toxics emissions. Additionally,
actions to address mobile sources
under other CAA programs have
achieved significant reductions in air
toxics emissions (e.g., the phase-out
of lead from gasoline). Many motor
vehicle and fuel emission control
programs of the past have reduced air
toxics. Several current EPA programs
further reduce air toxics emissions
from a wide variety of mobile sourc-
es. These include the reformulated
gasoline (RFG) program, the national
low emission vehicle (NLEV) pro-
gram, and Tier 2 motor vehicle emis-
sion standards and gasoline sulfur
control requirements. In addition, EPA
has recently issued regulations to ad-
dress emissions of toxic air pollutants
from motor vehicles and their fuels as
well as stringent standards for heavy-
duty trucks and buses and diesel fuel
that will lead to a reduction in emis-
80
AIR TOXICS • CHAPTER 5
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table 5-1. List of 33 Urban Air Toxics Strategy HAPs
VOCs
Metals
Aldehydes
SVOCs &
(Inorganic
(Carbonyl
Other HAPs
Compounds)
Compounds)
acrylonitrile
arsenic compounds
acetaldehyde
2,3,7,8-tetrachlorodi
benzo-p-dioxin (&
congeners &TCDF
congeners)
benzene
beryllium and compounds
formaldehyde
coke oven emissions
1,3-butadiene
cadmium compounds
acrolein
hexachlorobenzene
carbon tetrachloride
chromium compounds
hydrazine
chloroform
lead compounds
polycyclic organic matter
(POM)
1,2-dibromoethane
manganese compounds
polychlorinated biphenyls
(ethylene dibromide)
(PCBs)
1,3-dichloropropene
mercury compounds
quinoline
1,2-dichloropropane
nickel compounds
(propylene dichloride)
ethylene dichloride, EDC
(1,2-dichlorethane)
ethylene oxide
methylene chloride
(dichloromethane)
1,1,2,2,-tetrachloroethane
tetrachloroethylene
(perchloroethylene, PCE)
trichloroethylene, TCE
vinyl chloride
sions of diesel particulate matter by
over 90 percent between 1996 and 2020.
From 1996 (the year of the most up-to-
date emissions inventory estimates) to
2020, the existing proposed mobile
source programs are also expected to
lower onroad emissions of benzene by
61 percent, formaldehyde by 78 per-
cent, 1,3-butadiene by 60 percent, and
acetaldehyde by 73 percent from the
1996 levels. There will also be substan-
tial reductions from other gaseous
onroad HAPs and from nonroad mo-
bile sources.
EPA expects, however, that the
emission reductions that will result
from these actions may only be part
of what is necessary to protect public
health and the environment from air
toxics. In accordance with the 1990
CAA Amendments, EPA has begun to
assess the risk remaining (i.e., the
residual risk) after implementation of
technology-based standards in order
to evaluate the need for additional
stationary source standards to protect
public health and the environment.
During 2001, EPA will also begin the
process for assessing new standards
for nonroad engines such as construc-
tion and farm equipment. In addition,
after extensive study, EPA determined
mercury emissions from power plants
pose significant hazards to public
health and must be reduced. EPA will
propose regulations by 2003 and issue
final rules by 2004. By July 2003, EPA
will reassess the need for and feasibility
of controls for onroad and nonroad
sources of air toxics, and propose any
additional vehicle and fuel controls that
the Agency determines are appropriate.
This rulemaking will be finalized by
July 2004.
EPA's Integrated Urban Air Toxics
strategy identified 33 HAPs which
are judged to pose the greatest threat
to public health in urban areas.7
These 33 "urban HAPs" are a subset
of EPA's list of 188. Under EPA's
urban strategy, the Agency is devel-
oping area source regulations that
will control those sources responsible
for 90 percent of the total emissions of
the 33 HAPs in urban areas. The list
of the 33 urban HAPs is presented in
Table 5-1 and is grouped according to
chemical properties (volatile organic
compounds (VOCs), metals, alde-
hydes, and semi-volatile organic com-
pounds [SVOCs]). This grouping is the
same breakdown EPA uses for ambient
monitoring which is discussed in a
subsequent section of this chapter.
In addition to national regulatory
efforts, EPA provides leadership and
technical and financial assistance for
the development of cooperative fed-
eral, state, local, and tribal programs
to prevent and control air pollution.
EPA's risk initiatives include compre-
hensive local-scale assessments, as
well as federal and regional activities
associated with air toxics deposition
(e.g., the Great Waters program (in-
cludes the Great Lakes, Lake
Champlain, Chesapeake Bay, and
many U.S. coastal estuaries) and
Agency initiatives concerning mer-
cury and other persistent and bio-
accumulative toxics [PBTs]).
EPA also has an ongoing compre-
hensive evaluation of air toxics in the
United States which is called the
National Air Toxics Assessment
(NATA). These NATA activities help
EPA identify areas of concern, charac-
terize risks, and track progress to-
ward meeting the air toxics program
goals to reduce risk to human health
and the environment. They include
expansion of air toxics monitoring,
CHAPTER 5 • AIR TOXICS 81
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
improving and periodically updating
emissions inventories, developing
better air toxics emission factors for
nonroad sources, improving national-
and local-scale modeling, continued
research on health effects and expo-
sures to both ambient and indoor air,
and improvement of assessment tools.
For indoor air toxics, EPA's pro-
gram has relied on education and
outreach to achieve reductions. EPA's
voluntary programs that focus on
indoor air pollution have been very
successful in reducing indoor air
pollution. For example, through
EPA's voluntary Tools for Schools Pro-
gram, there have been significant reduc-
tions in children's exposure to air toxics
in 4,000 schools across the country.
EPA is also developing a specific strat-
egy for indoor air toxics that will
present an approach to evaluate infor-
mation, characterize potential indoor
exposures and risks, and identify meth-
ods to reduce air toxics indoors. Addi-
tional information about indoor air
toxics activities is available at:
www.epa.gov/iaq/pubs/index.html.
Air Toxics Emissions in 1996
The National Toxics Inventory (NTI) is
EPA's compilation of quantitative infor-
mation concerning the mass of emis-
sions of HAPs emitted into the
atmosphere (through smokestacks,
tailpipes, vents, etc.) from stationary
and mobile sources. The NTI is devel-
oped every 3 years. EPA has compiled
both a baseline period (1990-1993) as
well as 1996 emissions estimates for the
188 HAPs. As of the date of this publi-
cation, the 1996 NTI contains the most
complete, up-to-date air toxics emis-
sions estimates available. However,
EPA has not yet included the 1996
dioxin emissions in the 1996 NTI since
they are still under review. Since dioxin
emissions are relatively small, its exclu-
sion does not affect the summary infor-
mation presented for the 188 or the 33
urban HAPs. In addition, these emis-
sion summaries do not include diesel
particulate matter. For purposes of this
report, the information in the NTI has
been divided into four overarching
source types: 1) large industrial or
"major" sources; 2) "area and other
sources," which include smaller indus-
trial sources, such as small drycleaners
and gasoline stations, as well as natural
sources, such as wildfires; 3) "onroad"
Figure 5-1. National contribution of source types to 1996 NTI emissions for the 188 HAPs.
188 HAPs
(4.6M tons)
Nonroad
20%
Major
25%
Onroad
30%
Area/Other
25%
Examples of Source
Types
• Major sources: large industrial sources
such as chemical plants, oil refineries
and steel mills.
• Area and other sources: smaller
industrial sources such as drycleaners,
gas stations and landfills, as well as
natural sources like wildfires.
• Onroad mobile sources: cars, heavy-
duty trucks, buses and other highway
vehicles.
• Nonroad mobile sources: construction
and farm equipment as well as
recreational vehicles.
Figure 5-2. National contribution of source types to 1996 NTI emissions forthe urban HAPs.
33 urban HAPs
(1.1M tons)
Nonroad
23%
Major
9%
Onroad
28%
Area/ Other
40%
82
AIR TOXICS • CHAPTER 5
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 5-3. National contribution by emission source type for individual urban HAPsand diesel particulate matter, 1996.
Contributions from Major Sources, Area/Other Sources Contributions from Mobile Sources
VOCs
Metals
Aldehydes
SVOCs
and
Other
Diesel Exhaust
Acrylonitnle
Benzene
1,3-Butadiene
Carbon Tetrachlonde
Chloroform
1,2-Dichloropropane
1,3-Dichloropropene
Ethylene Dibromide
Ethylene Dichlonde
Ethylene Oxide
Methylene Chlonde
Perchloroethylene
1,1,2,2-Tetrachloroethane
mchloroethylene
Vinyl Chlonde
Arsenic Compounds
Beryllium Compounds
Cadmium Compounds
Chromium Compounds
Lead Compounds
Manganese Compounds
Mercury Compounds
Nickel Compounds
Acetaldehyde
Acrolein
Formaldehyde
Coke Oven Emissions
Hexach orobenzene
Hydrazine
Polycylic Organic Matter
POM as 7-PAH
Quinoline
Diesel Particulate Matter
100 90 80 70
50 40 30 20 10 0 10 20 30 40 50
~ Major
I Area and
Other
~ On road
Mobile
| Nonroad
Mobile
Note: For aldehyde
emissions (formaldehyde
and acetaldehyde) contri-
butions are for primary
direct emissions and do
not include secondary
aldehydes formed via
photochemical reactions.
70 80 90 100
percent of total emissions
mobile, including highway vehicles;
and 4) "nonroad" mobile sources, like
aircraft, locomotives, and lawn mowers.
Figures 5-1 and 5-2 provide a sum-
mary of the national emissions in the
1996 NTI based on source types for the
188 HAPs as well as the 33 urban
HAPs, respectively. Note that emis-
sions of the 33 urban HAPs represent
roughly a quarter (23 percent) of the
1996 emissions of the 188 HAPs. As
shown in Figure 5-1, the national emis-
sions of the 188 HAPs are relatively
equally divided between the four types
of sources. For the 33 urban HAPs,
however, area and other sources are the
largest overall contributor (40 percent),
while major sources account for less
than 10 percent of the nationwide emis-
sions and mobile sources make up the
remaining 51 percent.
Figure 5-3 provides the percent of
emissions by source type for each of
the 33 urban HAPs that have avail-
able emissions information (i.e., ex-
cluding dioxin). It also contains
information on diesel particulate
matter. Note that for each bar, the
individual contributions total to 100
percent. Also, the center vertical line
in the chart is zero so that the mobile
source contributions are shown on
the right side of the chart for ease of
display. The contributions from each
source type vary by pollutant. For
example, acetaldehyde and benzene
have mobile sources as the dominant
contributor, hydrazine and coke oven
emissions are dominated by major
sources, and perchlorethylene is pre-
dominantly from area and other
sources. Since the other 156 HAPs
are not represented here, this graph
provides a subset of information on
what source types emit which HAPs.
For example, nine of the 21 HAPs
EPA has identified as mobile source
air toxics are not included in Figure 5-
3. Table A-21 shows the 21 mobile
source air toxics, including diesel
particulate matter, and their contribu-
tions from mobile sources.
Also, note that Figure 5-3 does not
provide any information about the
relative magnitude of emissions. For
example, benzene and formaldehyde
together represent about 64 percent
CHAPTER 5 • AIR TOXICS 83
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
(roughly 32 percent each) of the total
emissions of these 32 urban HAPs.
Conversely, 23 of the urban HAPs,
including lead, chromium, and PCBs
each represent less than 1 percent of the
total emissions of the 33 urban HAPs.
Figure 5-4 provides additional
detail on the source sector emissions
from the 1996 NTI to show the rela-
tive percentages of sources that are
found in urban versus rural areas for
all 188 HAPs. Figure 5-5 shows this
same breakdown for the 33 urban
HAPs subset. For the 188 HAPs,
urban sources dominate the emis-
sions for all source types. For the 33
urban HAPs, there is one source type,
area and other sources, which has
roughly the same percentage contri-
bution of urban and rural sources.
Trends in Air Toxics Emissions
Trends in air toxics emissions are
shown in Figure 5-6 based on com-
parison of a baseline period of NTI
emissions data (1990-1993) to the
1996 NTI. The bar for each time peri-
od includes both the national total for
the 188 HAPs as well as the fraction
of the national emissions that are
associated with the urban HAPs. For
all 188 HAPs, there is a 23-percent
reduction between the baseline and
1996. For the 33 urban HAPs, there is
a 30-percent reduction between base-
line and 1996. The majority of these
reductions are attributable to two
source types with existing regulatory
programs: major sources and onroad
mobile sources. For the 188 HAPs,
major source emissions (which ac-
counted for 25 percent of the total
emissions in 1996) decreased by 58
percent and onroad mobile source
emissions (which accounted for 30
percent of the total emission in 1996)
decreased by 16 percent. Although
differences in how EPA compiled the
Figure 5-4. Urban/rural splits by source type for the 1996 national emissions of 188 HAPs.
CD
£
»
L_
CD
Q.
CO
c
c
o
0.50
0.45
0.40
0.35
0.30
0.25
0.20
0.15
0.10
0.05
0.00
~ rural
~ urban
Major
Area/ Other
Onroad
Nonroad
inventory over time could account for
some of the current estimates of
changes in emissions, EPA and state
regulations, as well as voluntary
reductions by industry, have clearly
achieved large reductions in overall
air toxic emissions.
Ambient Monitoring
Ambient measurements, which pro-
vide the concentration of a HAP at a
particular monitored location at a point
in time, are useful to characterize air
quality. These measurements are used
to derive trends in HAP concentrations
to help evaluate the effectiveness of
HAP reduction strategies. They also can
provide data to support and evaluate
dispersion and deposition models.
Unlike criteria air pollutants, such as
carbon monoxide and sulfur dioxide
(which have been monitored since the
1970s), there is no national air toxics
monitoring system. However, there are
approximately 300 monitoring sites
currently producing ambient data on
84
AIR TOXICS • CHAPTER 5
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 5-6. Change in national air toxics emissions - baseline (1990-1993) to 1996.
6.0
4.6
Baseline
(1990-1993)
1996
~ 33 urban air toxics
~ Other 155 Air Toxics
HAPs. These include sites within sev-
eral states that have long-standing air
toxics monitoring programs as well as
sites of the Interagency Monitoring of
Protected Visual Environments (IM-
PROVE) visibility network which pro-
vides historical information about HAP
trace metals in rural areas. The current
monitoring sites also include those
participating in the Urban Air Toxics
Monitoring Program which provides a
year's worth of measurements of 39
HAP VOCs and 13 carbonyl com-
pounds.8 In addition, the Agency's
Photochemical Assessment Monitoring
Stations (PAMS) program requires
routine year-round measurement of
VOCs which include nine HAPs: acetal-
dehyde, benzene, ethylbenzene, formal-
dehyde, n-hexane, styrene, toluene,
xylenes (m/p-xylene, o-xylene) and 2,2,4-
trimethlypentane. For a more detailed
discussion of the PAMS program, see the
ozone section in Chapter 2 of this re-
port. At the present time, the collection
of current state and local air toxics
monitoring data and PAMS data is
limited in its geographic scope and it
does not cover many HAPs for most
states. In addition the sites are not
necessarily at locations which represent
the highest area-wide concentrations.
Nevertheless, they can still be used to
provide useful infonnation on the trends
in ambient air' toxics at this time.
EPA is working together with state
and local air monitoring agencies to
build upon these sites to develop a
monitoring network with the follow-
ing objectives: to characterize air
toxics problems on a national scale; to
provide a means to obtain data on a
more localized basis as appropriate
and necessary (e.g., to evaluate po-
tential "hot spots" near sources), and
to help evaluate air quality models.
However, there are a significant num-
ber of the 188 HAPs for which EPA
does not yet have a monitoring
method developed. For this reason,
EPA is devoting its resources on
building up the air toxics monitoring
network by first focusing on the 33
urban HAPs. The states currently
have the capability to monitor for 28
of the 33 urban HAPs. As the moni-
toring network is enhanced, EPA will
assist the states to continue to add to
both the geographic scope of the
monitoring as well as the number of
HAPs included. The network will
represent an integration of informa-
tion from many monitoring pro-
grams, including existing state and
local air toxic monitoring sites;
PAMS, and the new urban PM2.5
chemical speciation and rural IM-
PROVE program networks. This new
national network will be developed
over the next several years.9
Trends In Ambient Concentrations
The most widely measured HAP has
been lead, which is also a criteria
pollutant. Until recently, it has been
monitored in most states, both in
metropolitan and non-metropolitan
areas. Nineteen states have moni-
tored other urban HAPs in their met-
ropolitan areas since 1994. In
addition, several VOCs, aldehydes
and metals have good data history in
metropolitan areas. Most of these
monitors, however, are concentrated
in a few states, with 36 percent of
them in California alone. Neverthe-
less, these data can be used to pro-
vide a preliminary picture of
nationwide trends in air toxics. A
good history of several trace metal
concentrations in rural areas is de-
rived from the IMPROVE program.
However, long-term monitoring in
rural areas for VOCs and aldehydes
has generally been more limited. The
locations for the urban and rural
monitors with long-term data are
shown in Figure 5-7.
Trends derived from these data are
separately presented for metropolitan
(urban) and non-metropolitan (rural)
sites. Table 5-2 presents a national
summary of these 6-year trends in
CHAPTER 5 • AIR TOXICS 85
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
ambient air toxics concentrations in
metropolitan statistical areas. Among
the 33 HAPs on the urban strategy
list, 25 pollutants have sufficient
historical data for this 6-year trends
assessment. These air contaminants
include 13 of the 15 urban VOCs, all
eight urban HAP trace metals, the
three aldehydes and several specific
polycyclic aromatic hydrocarbons
(PAHs). Also included are styrene
and toluene, which are two addi-
tional pervasive air toxics whose
monitoring sites have good nation-
wide coverage. The table presents
the number of sites with increases
and decreases in measured ambient
concentrations from 1994-1999. For
trace metals, the table includes results
representing more than one particu-
late size fraction. Similarly, trends are
shown separately for several indi-
vidual PAHs which are constituents
of polycyclic organic matter (POM).
For each of these HAPs with suffi-
cient historical data, the number of
sites with statistically significant
changes are highlighted. When most
individual locations reveal a consistent
change (and when many are statisti-
cally significant), this is more character-
istic of a national trend.
Although these ambient air toxics
data are only available for a limited
number of metropolitan areas, the
results generally reveal downward
trends for most monitored HAPs.
The most consistent improvements
are apparent for benzene which is
predominantly emitted by mobile
sources; and for total suspended lead.
From 1994-1999, annual average
concentrations for these two HAPs
declined 40 and 47 percent respec-
tively. The majority of ambient con-
centrations of lead once came from
the tail pipe of cars. Since the mid-
908, however, lead has been largely
Figure 5-7. Locations for urban and rural air toxics monitors with long-term data.
Number of sites located in an MSA (184): 0
Number of sites not located in an MSA (80): 0
removed from gasoline and almost all
of these trace elements now typically
emanate from major point sources
and aircrafts with piston engines
(e.g., small commuter aircraft). The
criteria pollutant section in Chapter 2
of this report contains more informa-
tion about particulate lead. The
change in national benzene emissions
is attributed to a combination of new
car emission standards, use of cleaner
fuels in many states as well as station-
ary source emission reductions. Am-
bient concentrations of toluene
(emitted primarily from mobile
sources) also show a consistent de-
crease over most reporting locations.
Similar to benzene, annual average
toluene concentrations dropped 48
percent. Other HAPs (including
styrene) also reveal air quality im-
provement, but the downward trends
are not significant across large numbers
of monitoring locations.
Figure 5-8 presents boxplots of the
composite urban trends for six HAPs:
benzene, 1,3-butadiene, lead,
perchlorethylene, styrene and tolu-
ene. These figures depict the concen-
tration distributions among annual
averages in metropolitan areas from
1994-1999. The accompanying map
displays the number and location of
the monitoring "trend" sites. For
comparison, the maps also show the
number of sites that produced any
measurement data during the 6-year
period. The average trend lines for
benzene, lead and toluene show more
improvement in the first few years.
The trend for toluene continues
through 1999. The benzene trend re-
veals a small increase between 1998
and 1999.
For the other HAPs in Table 5-2,
most urban locations do not reveal
predominant or consistent trends
among all monitoring areas. In addi-
tion, most observed trends for these
HAPs are not statistically significant.
This is attributed in part to few states
with long-term HAP monitoring, to
the large year-to-year variability in
computed annual average concentra-
tions for some HAPs and the large
variety of contributing emission
86
AIR TOXICS • CHAPTER 5
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table 5-2. National Summary of Ambient HAP Concentration Trends in Metropolitan Areas, 1994-1999
Number of Urban Sites by HAP
>ollutant Name
Total
Significant*
Non-Significant
No Trend
Non-Significant
Significant*
UP Trend
UP Trend
DOWN Trend
DOWN Trend
Acrylonitrile
4
4
Benzene
84
2
8
52
22
1,3-Butadiene
62
3
23
5
22
9
Carbon tetrachloride
57
1
10
6
26
14
Chloroform
76
5
24
13
34
1,2-Dibromoethane
26
3
17
3
3
1,2-Dichloropropane
30
2
11
16
1
Ethylene dichloride
58
5
26
21
6
Methylene chloride
74
19
2
39
14
1,1,2,2-Tetrachloroethane
11
4
3
4
Perchloroethylene
76
7
5
50
14
Trichloroethylene
66
2
17
8
37
2
Vinyl chloride
55
2
32
18
3
Arsenic (coarse)
9
9
Arsenic (fine)
8
1
7
Arsenic (PM10)
13
1
2
8
2
Arsenic (TSP)
64
8
37
12
7
Beryllium (PM10)
6
6
Beryllium (TSP)
25
3
20
2
Cadmium (PM10)
6
3
3
Cadmium (TSP)
58
2
12
10
30
4
Chromium (coarse)
9
1
8
Chromium (fine)
8
1
1
5
1
Chromium (PM10)
12
1
7
4
Chromium (TSP)
70
4
27
9
27
3
Chromium VI
19
9
10
Lead (coarse)
9
7
2
Lead (fine)
8
1
6
1
Lead (PM10)
26
2
3
14
5
2
Lead (TSP)
241
8
52
2
124
55
Manganese (coarse)
9
1
7
1
Manganese (fine)
8
4
4
Manganese (PM10)
12
1
11
Manganese (TSP)
63
20
1
34
8
Mercury (fine)
8
1
7
Mercury (PM10)
6
3
3
Mercury (TSP)
22
1
16
2
3
Mercury compounds
2
1
1
Nickel (coarse)
9
2
5
2
Nickel (fine)
8
1
6
1
Nickel (PM10)
12
3
9
Nickel (TSP)
69
12
3
39
15
Acetaldehyde
18
1
9
7
1
Formaldehyde
18
1
12
4
1
Acrolein
6
1
2
3
Benzo(a)pyrene
(total PMln & vapor)
18
1
13
4
Dibenz(a,h)anthracene
(total PMln & vapor)
18
3
11
4
lndeno(1,2,3-cd)pyrene
(total PMln & vapor)
18
1
13
4
Benzo(b)fluoranthene
(total PMln & vapor)
18
3
13
2
Benzo(k)fluoranthene
(total PMln & vapor)
18
3
11
4
Styrene
61
13
5
38
5
Toluene
80
1
4
42
33
""Statistically significant at the 10-percent level (See Appendix B: Methodology, Air Toxics Methodology section).
CHAPTER 5 • AIR TOXICS 87
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 5-8a. National trend in annual average benzene concentrations in metropolitan areas, 1994-1999.
6.5
6.0
co
5.5
B
$
5.0
g
4.5
•.a
£
4.0
a
u
9
3.5
R
u
3.0
a>
1
2.5
>
<
2.0
1
1.5
<
1.0
0.5
0.0
Sites Producing Data During
1994-1996
• Sufficient trend data (87)
Insufficient trend data (533)
95th percentile
75th percentile
Mean
Median
25th percentile
5th percentile
1994
1995
1996
1997
1998
1999
Year
Figure 5-8b. National trend in annual average 1,3-butadiene concentrations in metropolitan areas, 1994-1999.
2.0
1.5
1.0
0.5
0.0-
1994
1995
1996
1997
1998
1999
Year
95th percentile
-Li 75th percentile
• Mean
— Median
T25th percentile
5th percentile
Sites Producing Data During
1994-1996
• Sufficient trend data (65)
Insufficient trend data (205)
88
AIR TOXICS • CHAPTER 5
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 5-8c. National trend in annual average total suspended lead concentrations in metropolitan areas, 1990-1999.
m
l
1
CD
1
u
I
-a
g
0.55
0.50
0.45
0.40
0.35
0.30
0.25
0.20
0.15
0.10
0.05
0.00
Sites Producing Data During
1994-1996
• Sufficient trend data (241)
Insufficient trend data (215)
1994
1995
1998
1999
T
95th percentile
75th percentile
Mean
Median
25th percentile
5th percentile
1996 1997
Year
Figure 5-8d. National trend in annual average perchloroethylene concentrations in metropolitan areas, 1990-1999.
3.0-
1 2'5
£
fl
I
1
§
u
%
1
2.0
1.5
1.0
0.5
0.0:
Sites Producing Data During
1994-1996
• Sufficient trend data (79)
Insufficient trend data (283)
95th percentile
75th percentile
Mean
Median
25th percentile
5th percentile
1994
1995
1996
1997
1998
1999
Year
CHAPTER 5 • AIR TOXICS 89
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 5-8e. National trend in annual average styrene concentrations in metropolitan areas, 1994-1999.
3.0-
« 2.5
IP
d
CD
1
u
3
-a
a
2.0
1.5
1.0
0.5
0.0:
Sites Producing Data During
1994-1996
• Sufficient trend data (64)
Insufficient trend data (426)
1994
1995
1996 1997
Year
1998
1999
I
95th percentile
75th percentile
Mean
Median
25th percentile
5th percentile
Figure 5-8f. National trend in annual average toluene concentrations in metropolitan areas, 1994-1999.
Il
d
I
i
I
U
CD
1
20-
15
10
Sites Producing Data During
1994-1996
• Sufficient trend data (83)
Insufficient trend data (538)
T
95th percentile
75th percentile
Mean
Median
25th percentile
5th percentile
1994
1995
1996
1997
1998
1999
Year
90
AIR TOXICS • CHAPTER 5
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
sources for many of the air toxics. For
these pollutants, a national composite
trend may not be meaningful at this
time. Although the general direction
of change is down for most HAPs on
the urban list, several states reveal
significant 6-year increases at a few
locations. The HAPs and some of
their influencing sources are: 1,3-
butadiene (mobile sources); chro-
mium (power plants, electroplating);
lead (smelters and aircraft); and semi-
volatile particulates (various combus-
tion sources). This list also includes
carbon tetrachloride, chloroform, and
trichloroethylene whose ambient
concentrations are estimated to have
relatively high background contribu-
tions. Background concentrations are
contributions to ambient air toxics
concentrations resulting from natural
sources, persistence in the environ-
ment of past years' emissions and
long-range transport from distant
source. To illustrate a few of the
HAPs without consistent trends
among the current set of trend sites,
boxplots for 1994-1999 are presented
for 1,3-butadiene, styrene, and per-
chloroethylene. The national trend
lines for these HAPs show more year-to
year variability, but still appear to show
6-year air quality improvements.
To illustrate the behavior of se-
lected HAPs in a particular region of
the country, trends of monitoring
sites in California are presented Fig-
ure 5-9. The state of California has the
largest and longest running air toxics
monitoring network. They have over
30 sites with a 10-year history for
several VOCs and almost as many for
several trace metals. These data al-
low us to take a look at air toxics
trends over a longer period of time.
Among the HAPs discussed in this
section, notable improvements are
seen for benzene, 1,3-butadiene, lead,
perchloroethylene, styrene and tolu-
ene. The impressive air quality im-
provement for urban benzene in
California is shown in Figure 5-9a.
This figure illustrates the large de-
crease in ambient concentrations
which occurred during the early
1990s. Annual average concentrations
declined 64 and 35 percent over the
1990-1999 and 1990-1999 periods.
Ambient concentrations of perchloro-
ethylene associated with dry cleaners
is down 60 and 39 percent respec-
tively (Figure 5-9d). Toluene associ-
ated with mobile sources also showed
consistent 10-year declines which
averaged 53 percent across the state
(Figure 5-9f). Besides benzene, an-
other HAP which predominantly
comes from mobile sources is 1,3-
butadiene. Although site-specific
trends for this pollutant were mixed,
the composite trend in Figure 5-9b
shows an overall 40 percent and 28
percent decline in ambient concentra-
tions for the 10- and 6-year periods.
As was the case nationally, the
reductions in ambient concentrations
of perchloroethylene are due to better
controls on the use of solvents. The
California improvements in benzene,
1,3-butadiene and toluene are prima-
rily attributed to the reformulation of
gasoline and new-car improvements
in terms of emission controls. (For
more information about trends in
these emissions, see the ozone section
in Chapter 2.) For lead in TSP, annual
average concentrations in California
declined 46 percent over the 10 years,
but appear to have leveled off over
the most recent years. For additional
detail on the derivation of Figures 5-8a
to 5-9f, see Appendix B: Methodology.
Ambient air toxics data in rural
areas are much more limited, but the
results in Table 5-3 also indicate wide-
spread air quality improvement for
many monitored HAPs. Significant
downward trends are noted among the
few rural sites for benzene and several
other VOCs. Lead concentrations in
rural areas are also down.
While these data are useful to
describe general trends and geo-
graphic variations in annual average
concentrations, they only represent a
selected group of monitoring sites.
They do not necessarily highlight the
range of concentrations or locate air
toxics problem areas that exist nation-
wide. For example, a recent air toxics
study conducted in the Los Angeles
area has shown that higher concen-
trations of air toxics generally occur
near their emission sources. In par-
ticular, concentrations of compounds
that are emitted primarily from sta-
tionary and area sources tended to be
highest within a few kilometers from
the source location. More ubiquitous
mobile source related compounds
such as benzene and 1,3-butadiene
were shown to be generally high
throughout the South Coast Air Ba-
sin. However, the highest concentra-
tions were estimated by air quality
models to occur along freeway corri-
dors and junctions. In addition, high
levels of mobile source related com-
pounds were estimated near major
mobile source activities such as air-
ports and other areas with major
industrial activities. Also, annual
averages may tend to average out
peaks in the monitoring data. The
study showed that there were strong
seasonal variations to the levels of
toxic air contaminants, primarily with
those pollutants associated with mo-
bile sources. For example, benzene
and butadiene both had seasonal
peaks in the late fall and winter
CHAPTER 5 • AIR TOXICS 91
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 5-9a. Trend in annual average benzene concentrations for metropolitan sites in California, 1994-1999.
15
CO
l
fl
0
"¦§
1
§
u
I
1
10
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
Year
T
95th percentile
75th percentile
Mean
Median
25th percentile
5th percentile
Figure 5-9b. Trend in annual average 1,3-butadiene concentrations for metropolitan sites in California, 1994-1999.
1.5-
95th percentile
75th percentile
•
Mean
Median
"
25th percentile
5th percentile
92
AIR TOXICS • CHAPTER 5
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 5-9c. Trend in annual average total suspended lead concentrations for metropolitan sites in California, 1990-1999.
1
0.075-
0.070
0.065 H
0.060
0.055 H
0.050
0.045-
0.040
1
I
I
u 0.035
0
3
1
0.030
0.025
0.020
0.015
0.010-1
0.005
0.000
j
I
s
T
95th percentile
75th percentile
Mean
Median
25th percentile
5th percentile
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
Year
Figure 5-9d. Trend in annual average perchloroethylene concentrations for metropolitan sites in California, 1990-1999.
1
d
4.5
4.0
3.5
3 3.0
1 2.5
^ ,0
> 1.5
<3
1.0
0.5
0.0
I
95th percentile
75th percentile
Mean
Median
25th percentile
5th percentile
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
Year
CHAPTER 5 • AIR TOXICS 93
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 5-9e. Trend in annual average styrene concentrations for metropolitan sites in California, 1990-1999.
2.5
J 2.0
1
I
¦b 1.5
p
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table 5-3. National Summary of Ambient HAP Concentration Trends in Rural Areas, 1994-1999
Number of Rural Trend Sites by HAP
Pollutant Name
Total
Significant*
UP Trend
Non-Significant
UP Trend
No Trend
Non-Significant
DOWN Trend
Significant*
DOWN Trend
Benzene
6
6
1,3-Butadiene
4
1
2
1
Carbon tetrachloride
2
2
Chloroform
4
1
2
1
1,2-Dichloropropane
3
2
1
Ethylene dichloride
3
2
1
Methylene chloride
4
1
3
1,1,2,2-Tetrachloroethani
! 1
1
Perchloroethylene
5
1
1
3
Trichloroethylene
5
1
3
1
Vinyl chloride
4
1
2
1
Arsenic (coarse)
Arsenic (fine)
Arsenic (PM10)
Arsenic (TSP)
2
59
6
5
2
1
18
1
1
1
3
1
36
1
2
2
1
2
Beryllium (PM10)
Beryllium (TSP)
2
3
1
1
3
Cadmium (PM10)
Cadmium (TSP)
2
7
1
4
1
1
2
Chromium (coarse)
Chromium (fine) *
Chromium (PM10)
Chromium (TSP)
Chromium VI
2
59
6
8
1
32
1
1
22
2
3
1
1
1
4
3
4
1
Lead (coarse)
Lead (fine)
Lead (PM10)
Lead (TSP)
2
59
8
33
3
1
32
2
5
1
2
1
20
2
16
4
1
12
Manganese (coarse)
Manganese (fine)
Manganese (PM10)
Manganese (TSP)
2
59
6
7
3
1
22
2
2
1
32
3
5
2
1
Mercury (fine)
Mercury (PM10)
Mercury (TSP)
2
4
1
2
1
1
1
1
1
Nickel (coarse)
Nickel (fine)
Nickel (PM10)
Nickel (TSP)
2
59
6
8
1
12
1
1
1
1
1
32
3
6
14
1
1
Acetaldehyde
3
2
1
Formaldehyde
4
1
3
Acrolein
1
1
Styrene
6
2
3
1
Toluene
7
3
3
1
""Statistically significant at the 10-percent level (See Appendix B: Methodology, Air Toxics Methodology section).
** The apparent up trends in fine chromium concentrations may be an artifact of the detection limits for these measurements.
CHAPTER 5 • AIR TOXICS 95
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
months; their lowest levels were
observed during the spring and sum-
mer months.
National Atmospheric Deposition
Program/Mercury Deposition
Network
The purpose of the National Atmo-
spheric Deposition Program (NADP)
is to address the problem of atmo-
spheric deposition and its effects on
agricultural crops, forests, range-
lands, surface waters, and other natu-
ral resources. NADP began in 1978 as
a cooperative program between fed-
eral and state agencies, universities,
electrical utilities, and other indus-
tries to measure atmospheric deposi-
tion and determine geographical
patterns and trends in wet deposition
of sulfate, nitrate, hydrogen ion, ammo-
nium, chloride, calcium, magnesium,
and potassium. Wet deposition is at-
mospheric deposition that occurs when
rain, snow, or fog carry gases and parti-
cles to the earth's surface.
The Mercury Deposition Network
(MDN), which is a component of the
NADP, measures mercury levels in
wet deposition at over 40 NADP sites
located in 16 states and two Canadian
provinces. MDN is investigating the
importance of atmospheric deposi-
tion as a source of mercury in lakes
and streams. These MDN data enable
researchers to compile a national
database of weekly precipitation
concentrations to determine seasonal
and annual fluxes of mercury in pre-
cipitation falling on lakes, wetlands,
streams, forested watersheds, and
other sensitive ecosystems. As a
result, state and federal air regulators
can monitor progress in reducing
mercury deposition and amend
policy decisions accordingly. There
are plans to expand the network in
the near future, pending availability
of new funds. Additional informa-
tion about the network is available on
the Internet at http://
nadp.sws.uiuc.edu/mdn/.
Data from 1998 indicate that the
volume-weighted mean concentra-
tion of total mercury in precipitation
from 30 sites ranged from 3.8-23.0
ng/L and annual deposition of mer-
cury ranged from 4.0-20.3 ]Ug/m2.
Most of the monitors are in the Great
Lake states and eastern United States.
While high concentrations in precipi-
tation are found in many regions, the
highest estimated deposition is in the
southern states. In the eastern United
States, average summer mercury
concentrations are approximately
twice the winter concentrations and
average summer deposition values
are three times winter values. This
can be explained by higher concentra-
tions of mercury in the rain and higher
rainfall amounts during the summer.10
Integrated Atmospheric
Deposition Network
The Integrated Atmospheric Deposi-
tion Network (IADN) was estab-
lished in 1990 by the United States
and Canada for conducting air and
precipitation monitoring in the Great
Lakes Basin. IADN collects data that
can be useful in assessing the relative
importance of atmospheric deposi-
tion to pollutant loadings in the Great
Lakes. The first implementation plan,
signed in 1990, committed the United
States and Canada to work coopera-
tively towards the initiation of IADN.
IADN measures concentrations of
target chemicals in rain and snow
(wet deposition), airborne particles
(dry deposition), and airborne organ-
ic vapors.11 PAHs, PCBs, and orga-
nochlorine compounds (which are all
Semivolatile Organic Compounds, or
SVOCs) are measured in air and pre-
cipitation samples in the United
States and Canada. SVOCs are mea-
sured in both the gaseous and partic-
ulate phases in air. Canada also
measures trace metals in air and pre-
cipitation, as well as PM2.5 (particles
less than 2.5 microns in diameter) in
air.
Under IADN, trends in pollutant
concentrations in air and precipita-
tion are assessed and loading esti-
mates of atmospheric deposition and
volatilization of pollutants are made
every two years. The IADN network
currently consists of one master sta-
tion per Great Lake and 14 satellite
stations. Stations are located in re-
mote areas and do not assess urban
sources of pollution.
General conclusions based on
IADN data include the following:
• Levels in air and precipitation ap-
pear stable for current-use pesti-
cides such as endosulphan, but
levels for most other pesticides,
PCBs, and lead are decreasing.
• Gas absorption appears to be the
dominant deposition process for
delivering SVOCs, including PCBs
and PAHs, to lake surfaces, while
wet and dry deposition dominate
for the trace elements and higher
molecular weight PAHs.
• For some IADN substances, like
dieldrin and PCBs, the surface wa-
ters are behaving like a source
since the amount that is volatiliz-
ing from the water is greater than
the amount being deposited to the
water.
• The lakes are sensitive to the atmo-
spheric concentration of IADN
chemicals, and this points out the
fragility of these resources given
that long-range transport from
other regions may be a significant
source of toxic pollutants.
96 AIR TOXICS • CHAPTER 5
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
• Air trajectory analyses indicate
that many SVOCs are potentially
originating from outside the Great
Lakes basin, whereas trace metals
and PAHs may be associated with
local sources.
The Second Implementation Plan
for IADN (IP2), signed in 1998, out-
lines goals and plans for IADN for
the period 1998-2004. Under this
Second Implementation Plan, the
IADN will continue surveillance and
monitoring activities, related re-
search, and provision of information
for intergovernmental commitments
and agreements. Additional work to
be completed under the Second
Implementation Plan is the develop-
ment of a database for all U.S. and
Canadian data. Potential modifica-
tions will be discussed in relation to
the placement of satellite stations to
assess urban inputs and air-water gas
exchange, criteria for changes to the
IADN chemical list, coordination
with other research activities, quality
assurance and control of IADN op-
erations, and communication of
IADN results.12
References
1. This list originally included 189
chemicals. The CAA allows EPA to
modify this list if new scientific infor-
mation becomes available that indi-
cates a change should be made. Using
this authority, the Agency modified the
list to remove caprolactam in 1996,
reducing the list to 188 pollutants
(.Hazardous Air Pollutant List; Modifica-
tion, 61 FR 30816, June 18, 1996).
2. U.S. EPA. 2000. Draft Health As-
sessment Document for Diesel Ex-
haust. July 2000.
3. Federal Register, 65 FR 79827.
4. Giesy, J.P., Ludwig, J.P., and Tillitt,
D.E. 1994. Deformities in birds of the
Great Lakes region: assigning causali-
ty. Environ. Sci. Technol. 28,128A-136A.
5. Cook, P.M., Zabel, E.W., and Peter-
son, R.E. 1997. The TCDD toxicity
equivalence approach for characteriz-
ing risks for early life stage mortality
in trout. In: Chemically Induced Alter-
ations in the Functional Development and
Reproduction of Fishes, pp. 9-27. (Rolland,
R., Gilbertson, M., and Peterson R., Eds.).
SETAC Press, Pensacola, FL.
6. Scheuhammer, A.M., and Blancher,
P.J. 1994. Potential risk to common
loons (Gavia immer) from methylmer-
cury exposure in acidified lakes. Hy-
drobiol. 279,445-455.
7. "National Air Toxics Program: The
Integrated Urban Strategy," Federal
Register, 64 FR 38705, Washington,
D.C., July 19, 1999. Available on the
Internet at: http://www.epa.gov/ttn/
atw/urban/urbanpg.html
8. "1997 Urban Air Toxics Monitoring
Program (UTAMP)," EPA-454/R-99-
036. RTP, NC 27711, January 1999.
Available on the Internet at http://
www.epa.gov/ttn/amtic/airtxfil.html.
9. "Air Toxics Monitoring Concept
Paper," U.S Environmental Protection
Agency, Office of Air Quality Planning
and Standards, RTP, NC, 27711. Febru-
ary 29, 2000. Peer Review Draft. Avail-
able on the Internet at: http://
www.epa.gov/ttn/amtic/airtxfil.html.
10. Sweet, C.W., E. Prestbo, B. Bru-
nette. 1999. Atmospheric wet deposi-
tion of mercury in North America.
Proceedings of the 92nd Annual Meet-
ing of the Air and Waste Management
Association. June 21-23, 1999, St.
Louis, MO.
11. The target chemicals include PCBs,
pesticides, PAHs and metals. The
compounds included as "target chemi-
cals" were selected based on the fol-
lowing criteria: presence on List 1 of
Annex 1 of the Great Lakes Water
Quality Agreement (substances be-
lieved to be toxic and present in the
Great Lakes); established or perceived
water quality problem; presence on the
International Joint Commission's Wa-
ter Quality Board's list of criteria pol-
lutants; evidence of presence in the
atmosphere and an important deposi-
tion pathway; and feasibility of mea-
surement in a routine monitoring net-
work.
12. U.S./Canada IADN Scientific Steer-
ing Committee. 1998. Technical sum-
mary of progress under the integrated
atmospheric depositions program
1990-1996.
CHAPTER 5 • AIR TOXICS 97
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
98 AIR TOXICS • CHAPTER 5
-------
CHAPTER 6
Visibility Trends
http://www.epa.gov/oar/aqtrnd99/chapter6.pdf
Worth Noting:
The 10 eastern U.S. Class I area trend sites as an aggregate show a 15-percent improvement
in aerosol light extinction for the haziest 20 percent of days over the 1992-1999 timeframe,
with aerosol light extinction due to sulfates reaching its lowest level of the 1990s. However,
visibility on the haziest 20 percent of the days remains significantly impaired with a mean
visual range of 23 km for 1999 as compared to 84 km for the clearest days in 1999.
The 26 western U.S. Class I area trend sites as an aggregate show improvement in aerosol
light extinction for the clearest 20 percent and middle 20 percent of days over the 1990-1999
timeframe, with a 25-percent and 14-percent improvement, respectively. The conditions for
the haziest 20 percent of days degraded between 1997 and 1999 by 17 percent. However,
visibility on the haziest 20 percent of the days remains relatively unchanged over the 1990s
with the mean visual range for 1999 (80 km) nearly the same as the 1990 level (86 km).
Introduction
The Clean Air Act (CAA) authorizes
the United States Environmental
Protection Agency (EPA) to protect
visibility, or visual air quality
through a number of programs.
These programs include the National
Visibility Program under sections
169a and 169b of the Act, the Preven-
tion of Significant Deterioration Pro-
gram for the review of potential
impacts from new and modified
sources, the secondary National Am-
bient Air Quality Standards
(NAAQS) for PM10 and PM25, and
the Acid Rain Program under section
401. Since 1980, EPA issued two sets
of regulations to prevent future and
remedy existing visibility impair-
ment. In 1980, EPA issued visibility
regulations to address adverse im-
pacts from a single source or small
group of sources. In 1999, EPA issued
regulations to address regional haze,
visibility impairment caused by nu-
merous sources located across large
geographic areas.
The National Visibility Program
requires the protection of visibility in
156 mandatory federal Class I areas
across the country (primarily national
parks and wilderness areas). The
CAA established as a national visibil-
ity goal "the prevention of any fu-
ture, and the remedying of any
existing, impairment of visibility in
mandatory federal Class I areas in
which impairment results from man-
made air pollution." The Act also
calls for state programs to make "rea-
sonable progress" toward the na-
tional goal.
In 1987, the Interagency Monitoring
of Protected Visual Environments
(IMPROVE) visibility network was
established as a cooperative effort
between EPA, the National Oceanic
and Atmospheric Administration, the
National Park Service, the U.S. Forest
Service, the Bureau of Land Manage-
ment, the U.S. Fish & Wildlife Service,
and state governments. The objectives
of the network are to establish current
conditions, to track progress toward
the national visibility goal by docu-
menting long-term trends, and to pro-
vide information for determining the
types of pollutants and sources prima-
rily responsible for visibility impair-
ment. Chemical analysis of aerosol
measurements provides ambient con-
centrations and associated light extinc-
tion for PM10, PM2.5, sulfates, nitrates,
organic and elemental carbon, crustal
material, and a number of other ele-
ments. The IMPROVE program has
established protocols for aerosol, opti-
cal, and photographic monitoring
methods. The IMPROVE network has
been expanded from 30 to 110 sites to
represent all mandatory federal Class I
areas. Together with additional sites
which also used the IMPROVE moni-
toring protocol, the total number of
visibility sites now exceeds 130 nation-
wide. The analyses presented in this
chapter are based on data from the
IMPROVE network, which can be
found on the Internet at: http://
vista.cira.colostate.edu/improve/Data/
IMPROVE/improve_data.htm.
This chapter presents aerosol and
light extinction data collected between
1990 and 1999 at 36 Class I areas in the
IMPROVE network. Because the CAA
calls for the tracking of "reasonable
progress" in preventing future impair-
CHAPTER 6 • VISIBILITY TRENDS 99
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
ment and remedying existing impair-
ment, this analysis looks at trends in
visibility impairment across the entire
range of the visual air quality distribu-
tion. States are required to establish
goals to improve visibility for the 20
percent worst days and to allow no
degradation of the 20 percent best days
as discussed later in this chapter. To
facilitate this approach, visibility data
have been sorted into quintiles, or 20
percent segments, of the overall distri-
bution and average values have been
calculated for each quintile. Trends are
presented in terms of the haziest
("worst") 20 percent, typical
("middle") 20 percent, and clearest
("best") 20 percent of the annual distri-
bution of data. Figure 6-1 is a map of
the 36 Class I areas with seven or more
years of IMPROVE monitoring data
included in this analysis.
Figure 6-1. IMPROVE sites meeting data completeness requirements for sites
operating in 1999.*
/T^tount Rairyer\
Three Sisters
h Crater Lake
h Redwood /
Lassen Volcanic Jarbidge
s Yellowstone
Bridger Badlands
Moose horn
Acadia H
Point Reyes Lone Peak Mount zirte|
H Great Basin * H_ . .
. h Yosemite" "Rocky Mountain
Pinnacles x BrVce Can£>n " Canyonlands
Sequoia B a 0 Great Sand Dunes
Mesa Verde Weminuche
a . H a Bandelier
San Gorgonio Petrified Forest Upper Buffalo
Lye Brook a
Brigantine
Dolly SodsH
Shenandoah
* Jefferson
n Tonto
1 u a
0 Guadalupe Mntns
Big Bend
Mammoth Cave
B Great Smoky Mntn
Sipsey x Cape Romain
n Okefenokee
la >
Chassahowitza
b Complete for Both
~ Complete for Trends Only
x Complete for 1999 Only
*Data does not include IMPROVE sites established in 2000 and 2001.
Nature and Sources of
the Problem
Visibility impairment occurs as a
result of the scattering and absorp-
tion of light by particles and gases in
the atmosphere. It is most simply
described as the haze that obscures
the clarity, color, texture, and form of
what we see. The same particles
linked to serious health and environ-
mental effects (sulfates, nitrates, or-
ganic carbon, elemental carbon
(commonly called soot), and crustal
material) also can significantly affect
our ability to see.
Both primary emissions and sec-
ondary formation of particles contrib-
ute to visibility impairment. Primary
particles, such as elemental carbon
from diesel and wood combustion, or
dust from certain industrial activities
or natural sources, are emitted di-
rectly into the atmosphere. Second-
ary particles that are formed in the
atmosphere from primary gaseous
emissions include sulfate from sulfur
dioxide (S02) emissions, nitrates from
nitrogen oxide (NOx) emissions, and
organic carbon particles formed from
condensed hydrocarbon emissions.
In the eastern United States, reduced
visibility is mainly attributable to
secondarily formed particles, particu-
larly those less than a few microme-
ters in diameter. While secondarily
formed particles still account for a
significant amount in the West, pri-
mary emissions from sources such as
woodsmoke generally contribute a
larger percentage of the total particu-
late load than in the East. The only
primary gaseous pollutant that di-
rectly reduces visibility is nitrogen
dioxide (N02), which can sometimes
be seen in a visible plume from an
industrial facility, or in some urban
areas with high levels of motor ve-
hicle emissions.
Visibility conditions in Class I and
other rural areas vary regionally
across the United States. Rural areas
in the East generally have higher
levels of impairment than most re-
mote sites in the West. Higher east-
ern levels are generally due to higher
regional concentrations of sulfur
dioxide and other anthropogenic
emissions, higher estimated regional
background levels of fine particles,
and higher average relative humidity
levels. Humidity can significantly
increase the effect of pollution on
visibility. Some particles, such as
sulfates, accumulate water and grow
in size becoming more efficient at
scattering light. Annual average
relative humidity levels are 70-80
percent in the East as compared to
50-60 percent in many parts of the
100
VISIBILITY TRENDS • CHAPTER 6
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 6-2. Comparison of the three visibility metrics (extinction, deciview and visual image).
Extinction (MmT3) 10 30 n 4d w Wioo 200 aoo 400 too 1000
Dvtfvfvwt ldv>
Visual Range lkm>
Figure 6-2a. Images of Shenandoah National Park and Yosemite National Park.
n—
i
i I i i ii
1
1
1 1
¦Wfi
¦
11
i
14 in 19 23
1 1 1 1 II
»
1
34
1
37 39
! H
i i i i i i ii
400 200 130 J00 80 6(1 40 20 13 10 S 6 4
Condition:
Bad
Visual Range:
25 km
Deciviews:
28
Condition:
Bad
Visual Range:
16 km
Deciviews:
32
Condition:
Good
Visual Range:
180 km
Deciviews:
8
Condition:
Good
Visual Range:
200 km
Deciviews:
6.5
Shenandoah National Park Yosemite National Park
West. Poor summer visibility in the
eastern United States is primarily the
result of high sulfate particle concen-
trations combined with high humid-
ity levels.
Visibility conditions are commonly
expressed in terms of three math-
ematically related metrics: visual
range, light extinction, and deci-
views. Figure 6-2 shows the relation-
ship between these three metrics of
visibility. Figure 6-2a provides a pho-
tographic illustration of very clear
and very hazy conditions at
Shenandoah National Park in Vir-
ginia and Yosemite National Park in
California. Visual range is the metric
best known by the general public. It
is the maximum distance at which
one can identify a black object
against the horizon, and is typically
described in miles or kilometers.
Light extinction, inversely related
to visual range, is the sum of light
scattering and light absorption by
particles and gases in the atmo-
sphere. It is typically expressed in
terms of inverse megameters (Mm4),
with larger values representing
poorer visibility. Unlike visual range,
the light extinction coefficient allows
one to express the relative contribu-
tion of one particulate matter (PM)
constituent versus another to overall
visibility impairment. Using speci-
ated mass measurements collected
from the IMPROVE samplers, "recon-
structed light extinction" can be cal-
culated by multiplying the aerosol
mass for each constituent by its ap-
propriate "dry extinction coeffi-
cient," and then summing these
values for each constituent. Because
sulfates and nitrates become more
efficient at scattering light with in-
CHAPTER 6 • VISIBILITY TRENDS 101
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 6-3. Shenandoah National Park on clear and hazy days and the effect of
adding 10 |jg/m3offine particles to each.
Clean Day
' " 1
stjndartf Visual Rang* = 6D Mlfef
standard Visual Rang* = IB Mlkt
Dirty Day
Dirty Day + 10ug/rr>3
StJhdard VlfUil Rang* =¦ & Miles
SlatHftrd Visual Range 6 Miles
creasing humidity, these values are
also multiplied by a relative humidity
adjustment factor.2 Annual and sea-
sonal light extinction values devel-
oped by this approach correlate well
with optical measurements of light
extinction (by transmissometer) and
light scattering (by nephelometer).
The deciview metric was developed
because changes in visual range and
light extinction are not proportional to
human perception of visibility impair-
ment. For example, a 5-mile (8-km)
change in visual range can be either
very apparent or not perceptible, de-
pending on the base line level of ambi-
ent pollution. The deciview metric
provides a linear scale for perceived
visual changes over the entire range of
conditions, from clear to hazy, analo-
gous to the decibel scale for sound.
Under many scenic conditions, a
change of one deciview is considered to
be perceptible by the average person.
A deciview of zero represents pristine
conditions.
It is important to understand that
the same amount of pollution can have
dramatically different effects on visibil-
ity depending on existing conditions.
Most importantly, visibility in cleaner
environments is more sensitive to in-
creases in PM2.5 particle concentrations
than visibility in more polluted areas.
This principle is illustrated in Fig-
ure 6-3, which characterizes visibility at
Shenandoah National Park under a
range of conditions.3 A clear day at
Shenandoah can be represented by a
visual range of 80 miles (133 km), with
conditions approximating naturally-
occurring visibility (i.e., without pollu-
tion created by human activities). An
average day at Shenandoah is repre-
sented by a visual range of 18 miles (30
km), and is the result of an additional
10 ]Ug/m3 of fine particles in the atmo-
sphere. The two bottom scenes, with
visual ranges of eight and six miles
respectively, illustrate that the per-
ceived change in visibility due to an
additional 10 ]Ug/m3 of fine particles to
an already degraded atmosphere is
much less perceptible than adding this
amount to a clean atmosphere. Thus,
to achieve a given level of perceived
visibility improvement, a large reduc-
tion in fine particle concentrations is
needed in more polluted areas. Con-
versely, a small amount of pollution
in a clean area can dramatically de-
crease visibility.
Long-Term Trends
(1981-1995)
Visibility impairment is presented
here using visual range data collected
since 1960 by human observers at 298
monitoring stations located at prima-
rily urban and suburban airports
across the country. Trends in visibili-
ty impairment can be inferred from
these long-term records of visual
range. Figure 6-4 describes long-term
U.S. visibility impairment trends
derived from such data.4 The maps
show the amount of haze during the
summer months with each map cov-
ering five-year periods, centered at
1983, 1988, and 1993. The dark blue
color represents the best visibility
and red represents the worst visibili-
ty. Overall, these maps show that
summer visibility in the eastern Unit-
ed States improved slightly between
1980 and 1990, and continued to
improve between 1991 and 1995.
These trends follow overall trends in
emissions of sulfur oxides during
these periods.
In the early 1990s to the mid 1990s,
the National Weather Service gradu-
ally switched the method used to
collect visibility data presented in
Figure 6-4 from human observations
to automated sensors. This method
change resulted in an incompatibility
between the human observation and
the automated sensor data. Because
102
VISIBILITY TRENDS • CHAPTERS
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 6-4. Long-term trends for 75th percentile light extinction coefficient from airport 0f this method change the trends
visual data (July-September)
presented using the human observa-
tion data in Figure 6-4 end at 1995.
Recent Trends (1990-1999)
from IMPROVE Data
Visibility and aerosol light extinction
data are presented for 36 sites with at
least seven years of fine particle data
from 1990-1999 for western sites and
from 1992-1999 for eastern sites: 10
are located in the East, and 26 are
located in the West, as shown in Fig-
ure 6-2. Eastern trends start in 1992
because seven sites were added to the
existing three eastern sites in the
IMPROVE network, bringing the
total number of eastern sites to 10.
This is reflected in the eastern Class I
area plots, Figure 6-5a and Figure
6-6a to 6-6c, where the trend is based
on eight years of data, versus 10 years
of data in the western Class I area
plots. Because of the significant re-
gional variations in visibility condi-
tions, this chapter does not present
aggregate national trends, but instead
groups the data into eastern and
western regions. As noted earlier,
trends in this chapter are presented in
terms of the annual average values
for the clearest ("best") 20 percent,
middle ("typical") 20 percent, and
haziest ("worst") 20 percent of the
days monitored each year. The goals
of the regional haze program are to
improve visibility on the haziest days
and prevent degradation of visibility
on the clearest days. To date, two
24-hour aerosol samples have been
taken each week from IMPROVE
sites, resulting in a potential for 104
sampling days per year. In 2000, the
aerosol sampling schedule was
changed to one sample every three
days, consistent with the approach
used for national I'M., - aerosol moni-
toring.
CHAPTER 6 • VISIBILITY TRENDS 103
13*1-38 Qui iar i
'ZtM-iCl Qufettr 1
¦ M1-4S QufcfMr J
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
In May of 2001, the National Park
Service and other participants of the
IMPROVE program identified techni-
cal concerns about measured nitrate
concentrations at all IMPROVE sites
prior to June 1996, and about estimates
of sulfates, primarily at eastern IM-
PROVE sites prior to 1995. As a result,
the IMPROVE monitoring data used in
this year's National Air Quality and
Emissions Trends Report is interpreted
differently to correct the technical con-
cerns. At some affected IMPROVE
sites, the adjustments result in a change
in the direction or significance of the
reported visibility trend. Because of the
new usage of the IMPROVE monitor-
ing data, the results presented here are
not directly comparable with results
presented in previous Trends reports. A
discussion of the technical concerns, the
data usage, and the effect on the nitrate
and sulfate data is presented on the
IMPROVE website, http://
vista.cira.colostate.edu/IMPROVE/
Data/QA_QC/issues.htm.
Regional Visibility Trends for the
Eastern and Western United States
Figures 6-5a and 6-5b illustrate east-
ern and western trends for visibility
impairment in deciviews. The deci-
view metric used in Figures 6-5a and
6-5b best characterizes perceived
changes in visibility impairment.
Under many scenic conditions a
change in one deciview is considered
to be perceptible by the average per-
son. These figures, presented with
equivalent scales, demonstrate the
regional difference in overall levels of
rural visibility impairment. One can
see that visibility impairment for the
haziest visibility days in the West is
close to the same level of impairment
as seen for the best days in the East.
Figure 6-5a shows that in the East, the
haziest visibility days improved by
Figure 6-5a. Visibility* trends for 10 eastern U.S. Class I areas for clearest, middle,
and haziest 20 percent days in the distribution, 1992-1999.
Visibility Impairment, deciviews
35
30
25
20
15
10
5
0
92 93 94 95 96 97 98 99
Haziest 20-percent
Typical 20-percent
Clearest 20-percent
Figure 6-5b. Visibility* trends for 26 western U.S. Class I areas for clearest, middle,
and haziest 20 percent days in the distribution, 1992-1999.
Visibility Impairment, deciviews
35
30
25
20
15
10
Haziest 20-percent
Typical20-percent
Clearest 20-percent
90 91 92 93 94 95 96 97 98 99
* For Figures 6-5a and 6-5b changes in nitrate concentrations were not considered in
calculation of deciviews. A constant value based on mean 1997-1999 extinction
associated with nitrates was substituted for all years.
104
VISIBILITY TRENDS • CHAPTER 6
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Aerosol Light Extinction, Mm-1
200
150
100
50
92 93 94 95 96 97 98
Aerosol Light Extinction, Mm-1
200
99
150
100
50
92 93 94 95 96 97 98
Aerosol Light Extinction, Mm-1
200
150
100
Figure 6-6a. Aerosol light*
extinction in 10 eastern Class I
areas for the clearest 20
percent of the days in the
distribution, 1992-1999.
~ Organic Carbon
¦ Nitrate
~ Sulfate
¦ Elemental Carbon
¦ Crustal Material
Figure 6-6b. Aerosol light*
extinction in 10 eastern Class I
areas for the middle 20
percent of the days in the
distribution, 1992-1999.
99
92 93 94 95 96
Figure 6-6c. Aerosol light*
extinction in 10 eastern Class I
areas for the haziest 20
percent of the days in the
distribution, 1992-1999.
* For Figures 6-6a to 6-6c
changes in nitrate
concentrations were not
considered in calculation of
aerosol light extinction. A
constant value based on mean
1997-1999 extinction
associated with nitrates was
substituted for all years.
1.5 deciviews, or 15 percent in aerosol
light extinction, since 1992 based on
10 locations. Over the past two years
(1998-1999) impairment on the hazi-
est days in the East show improve-
ment of close to 1 deciview, or
10-percent in aerosol light extinction.
However, visibility for the haziest
days still remains significantly im-
paired with a mean visual range of 23
km compared to 84 km for the clear-
est days in 1999. Visibility impair-
ment in 1999 for the clearest 20
percent of days is approximately
equal to 1992 levels of 15 deciviews.
The typical days (or middle 20 per-
cent of the distribution) show a 1
deciview improvement, 10 percent in
aerosol light extinction, since 1992 for
the 10 sites.
In the West, there appears to be
visibility improvement for the
clearest, and the typical, days as pre-
sented in Figure 6-5b for the period
1990-1999. Visibility impairment for
the aggregate 26 western sites im-
proved by 1.5 deciviews for the
clearest days and 1 deciview for the
typical days, or 25 percent and 14
percent in aerosol light extinction,
respectively. Visibility impairment for
the haziest days in the West degraded
between 1997-1999 close to 1.5 deci-
views or 17 percent in aerosol light
extinction. However, visibility on the
haziest 20 percent of days remains
relatively unchanged over the 1990s,
with the mean visual range for 1999
(80 km) nearly the same as the 1990
level (86 km).
The Components of PM Contributing
to Trends in Visibility Impairment
The area plots in Figures 6-6a to 6-6f
show the relative contribution to
aerosol light extinction by the five
principal particulate matter constitu-
ents measured by IMPROVE at east-
CHAPTER 6 • VISIBILITY TRENDS 105
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
ern and western sites for the best,
middle, and worst 20 percent days.
Note that the scale differs for the
eastern and western figures in order
to more clearly present the relative
contribution of the five components.
By understanding the total magnitude
of each PM2.5 component, the change in
aerosol composition over time, and the
effect of these components on changing
visibility, policymakers can design
strategies to address both health and
environmental concerns.
In the East, (Figures 6-6a to 6-6c),
sulfate is clearly the largest contribu-
tor to visibility impairment, ranging
from an average of 78-82 percent of
each year's annual aerosol extinction
during the haziest days to 56-63 per-
cent on the clearest days. In 1999,
eastern aerosol light extinction due to
sulfates on the haziest days reached
its lowest level of the 1990s with a
19-percent decline over 1992-1999.
This decline in sulfates in the eastern
United States and the low 1999 level
corresponds to the reported regional
S02 emissions trends and lower aver-
age sulfate aerosol concentrations
discussed in Chapter 7 (Atmospheric
Deposition of Sulfur and Nitrogen
Compounds). Organic carbon is the
next largest contributor to visibility
impairment in the East, accounting
for 10-14 percent of annual aerosol
extinction on the best days and 8-11
percent on the most impaired days.
The third largest contributor in the
East is nitrate, which also accounts
for about 11-13 percent of annual
aerosol light extinction on the best
days and about 3-4 percent on the
haziest days.
In the West, sulfate is also the most
significant single contributor to aero-
sol light extinction on the clearest,
typical, and haziest days. Sulfate
accounts for 33-41 percent of annual
Aerosol Light Extinction, Mm-1
100
75
50
25
90 91 92 93 94 95 96 97 98 99
Aerosol Light Extinction, Mm-1
100
75
50
25
75
Figure 6-6d. Aerosol light*
extinction in 26 western Class I
areas for the clearest 20
percent of the days in the
distribution, 1990-1999.
~ Organic Carbon
¦ Nitrate
~ Sulfate
¦ Elemental Carbon
¦ Crustal Material
Figure 6-6e. Aerosol light*
extinction in 26 western Class
I areas for the middle 20
percent of the days in the
distribution, 1990-1999.
90 91 92 93 94 95 96 97 98 99
Aerosol Light Extinction, Mm-1
100
Figure 6-6f. Aerosol light*
extinction in 26 western Class I
areas for the haziest 20
percent of the days in the
distribution, 1990-1999.
* For Figures 6-6d to 6-6f
changes in nitrate
concentrations were not
considered in calculation of
aerosol light extinction. A
constant value based on mean
1997-1999 extinction
associated with nitrates was
substituted for all years.
106
VISIBILITY TRENDS • CHAPTER 6
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
An Urban Perspective - the Washington, D.C.
IMPROVE site
The only urban monitoring site with a long-term data record using the IMPROVE moni-
toring protocol is located in Washington, D.C, This monitor was one of the first to be
deployed in 1988. The figure below illustrates the trend at the Washington, D.C. site for
visibility impairment in deciviews from 1990-1999. The decrease of visibility impairment
in deciviews seen from 1993-1995 for the clearest, typical, and haziest days is attribut-
able primarily to decreases in sulfate concentrations, although nitrates and organic
carbon both had large decreases during the same time period. Nevertheless, conditions
of the haziest days are still significantly impaired with an average visual range of only 21 km.
Visibility impairment, deciviews
40
30
20
10
0
90 91 92 93 94 95 96 97 98 99
* Changes in nitrate concentrations were not considered in calculation of total
light extinction. A constant value based on mean 1997-1999 extinction
associated with nitrates was substituted for all years.
Haziest 20 percent
Typical 20 percent
Clearest 20 percent
The photos below depict a very clear day along
with a very hazy day looking across the
Potomac River at the Lincoln Memorial and the
Washington Monument.
Visual range > 150 km / 9.6 deciviews
Visual range = 8.4 km / 38.4 deciviews
Table 6-1. Summary of Class I Area Trend1 Analysis
Parameter Number of Sites With Number of Sites With
Significant2 Upward Significant2 Downward
(Deteriorating) Trends (Improving) Trends
West East West East
3Deciviews, worst 20%
4
0
1
2
3Deciviews, middle 20%
0
0
6
2
3Deciviews, best 20%
0
0
9
1
Light extinction due to sulfate, worst 20%
4
0
4
2
Light extinction due to sulfate, middle 20%
1
1
6
4
Light extinction due to sulfate, best 20%
0
1
14
0
Light extinction due to organic carbon, worst 20%
2
0
1
0
Light extinction due to organic carbon, middle 20%
0
0
3
0
Light extinction due to organic carbon, best 20%
2
0
5
0
1Based on a total of 36 monitored sites with at least 10 years of data in the West and eight years of data in the East: 26 sites in the
West, 10 sites in the East.
Statistically significant at the 5-percent level.
3For deciview trends changes in nitrate concentrations were not considered in the trend analysis. A constant value based on mean
1997-1999 extinction associated with nitrates was substituted for all years.
CHAPTER 6 • VISIBILITY TRENDS 107
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 6-7a. Class I area significant trends in deciviews for the clearest 20 percent, middle 20 percent, and haziest 20 percent days
as summarized in Table 6-1.
Significant Trends
* IMPROVE site location
Clearest 20 percent
I Upward (Deteriorating) Trend
^ Downward (Improving) Trend
^ Middle 20 percent
I Upward (Deteriorating) Trend
^ Downward (Improving) Trend
Haziest 20 percent
Upward (Deteriorating) Trend
Downward (Improving) Trend
Note: For deciview trends changes in nitrate concentrations were not considered in
the trend analysis. A constant value based on mean 1997-1999 extinction associated
with nitrates was substituted for all years.
Figure 6-7b. Class I area significant trends light extinction due to sulfate for the clearest 20 percent, middle 20 percent, and haziest
20 percent days as summarized in Table 6-1.
showed
Significant Trends
* IMPROVE site location
a. Clearest 20 percent
I Upward (Deteriorating) Trend
^ Downward (Improving) Trend
. Middle 20 percent
I Upward (Deteriorating) Trend
^ Downward (Improving) Trend
Haziest 20 percent
Upward (Deteriorating) Trend
Downward (Improving) Trend
Note: Denali National Park and Preserve in Alaska (not shown on this figure)
a downward (improving) trend for the clearest 20 percent.
108
VISIBILITY TRENDS • CHAPTER 6
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 6-7c. Class I area significant trends for light extinction due to organic carbon for the clearest 20 percent, middle 20 percent,
and haziest 20 percent days as summarized in Table 6-1.
Significant Trends
* IMPROVE site location
^ Clearest 20 percent
I Upward (Deteriorating) Trend
^ Downward (Improving) Trend
^ Middle 20 percent
U Upward (Deteriorating) Trend
^ Downward (Improving) Trend
Haziest 20 percent
Upward (Deteriorating) Trend
Downward (Improving) Trend
aerosol light extinction on the best
days, 39-43 on the typical days, and
31-42 on the haziest days. However,
organic carbon (19-30 percent),
crustal material (14-26 percent), and
nitrates (9-15 percent) play a more
significant role (as a percentage of
aerosol extinction) in western sites as
compared to eastern ones. Since
1990, western visibility (as aggre-
gated across 26 areas) has improved
slightly on the best days and typical
days. On the haziest days, light ex-
tinction generally decreased through
1997, but it increased by 22 percent
between 1997-1999. It appears that
this increase in light extinction was
primarily due to increases in organic
carbon and crustal material.
Trends in Specific Class I Areas
IMPROVE data from 36 Class I area
monitoring sites1 were analyzed for
upward or downward tends using a
nonparametric regression methodology
described in Appendix B: Methodology.
Table 6-1 summarizes the trends
analysis performed on these 36 sites for
total light extinction (expressed in
deciviews), light extinction due to
sulfates and light extinction due to
organic carbon on an area-by-area
basis. Figures 6-7a-c show the signifi-
cant trends for the Class I areas as sum-
marized in Table 6-1. A solid dot
indicates the IMPROVE monitoring
site location. The arrow is pointing up
for a deteriorating trend and down for
an improving trend. The different color
arrows represent the clearest 20 percent
of days, typical (middle) 20 percent of
days, and haziest 20 percent of days.
As shown in Figure 6-7a several sites
with improving trends show improve-
ment in more than one of the three
quintiles, especially in the West. Fig-
ures 6-7b and 6-7c show the trends
associated with aerosol light extinction
due to sulfate and organic carbon,
respectively. Trends in the individual
constituents, like sulfate and organic
carbon, often appear earlier than trends
for total aerosol light extinction.
Current Visibility
Conditions
Current annual average conditions
range from about 18^0 miles in the
rural east and about 35-90 miles in the
rural west. On an annual average
basis, natural visibility conditions have
been estimated at approximately 80-90
miles in the East and up to 140 miles in
the West.3 Natural visibility varies by
region, primarily because of slightly
higher estimated background levels of
PM2.5 in the East, and the more signifi-
cant effect of relative humidity on parti-
cle concentrations in the East than in
the West.
CHAPTER 6 • VISIBILITY TRENDS 109
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 6-8a. Aerosol light extinction in (Mm-1) for the clearest 20 percent days and contribution by individual particulate matter
constituents, based on 1997-1999 IMPROVE data.
9.8
13.3
4.9
18.3
5.0
14.1
16.2
10.5
® 5.7
,38.5
39.4
22.5
® 6.0
7.0
i® ® 8.4
7.71
'6.5
14..
6.2
31.1
57.7
9.6 ®,
13.6,
9.5
11.3®
26.9
11.9
63.4
9.8
Species
Sulfate
Nitrate
Organic Carbon
Elemental Carbon
Crustal Matter
52.5
Figure 6-8b. Aerosol light extinction in (Mm1) for the middle 20 percent days and contribution by individual particulate matter
constituents, based on 1997-1999 IMPROVE data.
35.2
29.6
12.4
>10.0
32.9
37.!
34.8,
22.0
12.0
14.1
10.6
76.8
76.1
38.4
L0.9
13.
3.7
27.1
114.)
16.7
7ILa
16.1
71.1
89.5
17.1
23.2
Species
Sulfate
Nitrate
Organic Carbon
Elemental Carbon
Crustal Matter
92.7
27.3
110 VISIBILITY TRENDS • CHAPTER 6
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 6-8c. Aerosol light extinction in (Mm-1) for the haziest 20 percent days and contribution by individual particulate matter
constituents, based on 1997-1999 IMPROVE data.
57.
24.2
25.2
94.5
78.!
124.6
20.6
49.5
43.
25.2
1198.9
180.5
78.9y \
>S> ®\
51-5\ 56.1
25.0 2i|
228.:
18Z-
125.3
26.4.
184.
27.0
31.9
44.2
Species
186.3
28.5
Sulfate
Nitrate
Organic Carbon
Elemental Carbon
Crustal Matter
54.1
143.9
Note: For Figures 6-8a to 6-8c changes in nitrate concentrations were not considered
in calculation of aerosol light extinction.
Figures 6-8a to 6-9c illustrate re-
gional visibility impairment in terms
of reconstructed aerosol light extinc-
tion based on measurements at IM-
PROVE sites between 1997 and 1999.
Maps are presented for the clearest,
typical, and haziest 20 percent of the
distribution. The pie charts show the
relative contribution of different par-
ticle constituents to visibility impair-
ment. Annual average aerosol light
extinction due to these particles is
indicated by the value next to each
pie and by the size of each pie.1 Fig-
ure 6-8 also shows that visibility im-
pairment is generally greater in the
rural east compared to most of the
West. As noted earlier, the pies show
that, for most rural eastern sites, sul-
fates account for more than 60 per-
cent of annual average light
extinction on the best days and up to
86 percent of annual average light
extinction on the haziest days. Sul-
fate particles play a particularly sig-
nificant role in the humid summer
months due to their ability to take on
moisture and become more efficient
at scattering light, most notably in the
Appalachian, northeast, and
mid-south regions. The figures also
show that organic carbon and nitrates
each account for 10-18 percent and 7-
16 percent respectively of aerosol
extinction on the clearest days while
elemental carbon only contributes 5-8
percent. On the other hand, organic
carbon contributes around 11 percent
to aerosol light extinction on the hazi-
est days while nitrates and elemental
carbon each typically contribute 1-6
percent.
In the rural west, sulfates also play
a significant role, typically account-
ing for about 30-40 percent of aerosol
light extinction on the best days and
30-45 percent on the haziest days. In
several areas of the West, however,
sulfates account for over 50 percent of
annual average aerosol extinction,
including Mt. Rainier, WA, and Red-
wood National Park, CA. In contrast,
it contributes less than 25 percent in
southern California. Organic carbon
typically makes up 25-40 percent of
aerosol light extinction in the rural
west, elemental carbon (absorption)
accounts for about 10 percent, and
crustal matter (including coarse PM)
accounts for about 15-25 percent.
Nitrates typically account for less
than 10 percent of total light extinc-
tion in western locations, except in
the southern California region where
it accounts for 30-45 percent.
Figures 6-9a to 6-9c illustrate cur-
rent levels of visibility impairment, in
terms of deciviews, for the clearest,
typical, and haziest 20 percent days
based on IMPROVE data from 1997-
1999.1 Note that the deciview scale is
more compressed than the scale for
CHAPTER 6 • VISIBILITY TRENDS 111
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 6-9a. Current visibility impairment expressed in deciviews for the clearest 20 percent days based on 1997-1999 IMPROVE
data.
8.4
10..
4.0
4.5
7.2
16.0
5.7
'18.0
14.3
5.3
19.1
8.6
6.7
15.
6.7
7.5
13.1
6.9<
7.8
19.9
8.5,
Deciview ranges at
IMPROVE sites
18.3
3.2 - 5.3
5.4 - 7.5
~
o 7.6-10.4
o 10.5-16
• 16.1-19.9
Figure 6-9b. Current visibility impairment expressed in deciviews for the middle 20 percent days based on 1997-1999 IMPROVE
data.
'15.0
13.7
14.6
6.9
15.0
15.'
7.9
8.8
,21.5
21.6
15.8
'8.7
8.6
13.5
8.6
13.;
20.9
25.2
21.1
9.6
20.9
10.9
12.0
22.9j
10.0
,13.
Deciview ranges at
IMPROVE sites
23.3
6.4 - 7.9
8-10
~
O 10.1-13.7
o 13.8-16.9
• 17-25.2
112 VISIBILITY TRENDS • CHAPTER 6
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 6-9c. Current visibility impairment expressed in deciviews for the haziest 20 percent days based on 1997-1999 IMPROVE
data.
Deciview ranges at
IMPROVE sites
. 9.9-11.4
= 11.5-14.3
o 14.4-19
o 19.1-26
• 26.1-31.7
Note: For Figures 6-9a to 6-9o changes in nitrate concentrations were not considered
in calculation of deciviews.
visual range or light extinction, with
larger values representing greater
visibility degradation. Most of the
sites in the intermountain west and
Colorado Plateau have annual aver-
age impairment of 12 deciviews or
less, with the worst days ranging up
to 17 deciviews. Several other west-
ern sites in the northwest and Califor-
nia experience levels on the order of
16-23 deciviews on the haziest 20
percent of days. Many rural loca-
tions in the East have annual average
values exceeding 21 deciviews, with
average visibility levels on the hazi-
est days up to 32 deciviews.
Programs to Improve
Visibility
In April of 1999, EPA issued the final
regional haze regulation.5 This regu-
lation addresses visibility impairment
in national parks and wilderness
areas that is caused by numerous
sources located over broad regions.
The program lays out a framework
within which states can work togeth-
er to develop implementation plans
that are designed to achieve "reason-
able progress" toward the national
visibility goal of no human-caused
impairment in the 156 mandatory Class
I federal areas across the country.
States are required to establish
goals to improve visibility on the 20
percent worst days and to allow no
degradation on the 20 percent best
days for each Class I area in the state.
In establishing any progress goal, the
state must analyze the rate of
progress for the next 10-15 year
implementation period which, if
maintained, would achieve natural
visibility conditions by 2064. The
state will need to show whether this
rate of progress or another rate is
more reasonable based on certain
factors in the Clean Air Act, including
costs and the remaining useful life of
affected sources. Along with these
goals, the state plans also must in-
clude emission reduction measures to
meet these goals (in combination
with other states' measures), require-
ments for Best Available Retrofit
Technology on certain large existing
sources (or an alternative emissions
trading program), and visibility
monitoring representative of all Class
I areas.
State regional haze plans are due
in the 2003-2008 timeframe. Because
of the common precursors and the
regional nature of the PM and re-
gional haze problems, the haze rule
includes specific provisions for states
that work together in regional plan-
ning groups to assess the nature and
sources of these problems and to
develop coordinated, regional emis-
sion reduction strategies. One provi-
CHAPTER 6 • VISIBILITY TRENDS 113
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
si on allows nine Grand Canyon Vis-
ibility Transport Commission States
(Arizona, California, Colorado, Idaho,
Nevada, New Mexico, Oregon, Utah,
and Wyoming) to submit initial plans
in 2003 to implement their past rec-
ommendations within the frame-
work of the national regional haze
program. Another provision allows
certain states until 2008 to develop
coordinated strategies for regional
haze and PM contingent upon partici-
pation in regional planning groups.
For additional information on the
regional haze program, go to EPA's
website: http/www.epa.gov/air/
visibility.
Implementation of the PM and
ozone NAAQS in conjunction with a
future regional haze program is ex-
pected to improve visibility in urban
as well as rural areas across the coun-
try. Other air quality programs are
expected to bring about emissions
reductions that will improve visibil-
ity in certain regions of the country.
The acid rain program will achieve
significant regional reductions in the
emissions of S02, which will reduce
sulfate haze particularly in the east-
ern United States. When imple-
mented, the NOx State Implementa-
tion Plan (SIP) call to reduce emis-
sions from sources of NOx to reduce
formation of ozone should also im-
prove regional visibility conditions to
some degree. In addition, visibility
impairment in Class I areas should
improve as a result of a number of
other programs, including mobile
source emissions and fuel standards,
certain air toxics standards, and
implementation of smoke manage-
ment and woodstove programs to
reduce fuel combustion and soot
emissions.
References
1. Data from IMPROVE Visibility
Monitoring Network, 1999.
2. Sisler, J. Spatial and Seasonal Patterns
and Temporal Variability of Haze and its
Constituents in the United States: Report
III. Colorado State University, Cooper-
ative Institute for Research in the At-
mosphere. Fort Collins, CO., 2000.
Also see: Sisler, J. Spatial and Seasonal
Patterns and Long-Term Variability of the
Composition of the Haze in the United
States: An Analysis of Data from the
IMPROVE Network. Colorado State
University, Cooperative Institute for
Research in the Atmosphere. Fort Col-
lins, CO, 1996.
Sisler, J., Huffman, D., and Latimer, D.
Spatial and Temporal Patterns and the
Chemical Composition of the Haze in the
United States: An Analysis of Data from
the IMPROVE Network, 1988-1991,
Colorado State University, Cooperative
Institute for Research in the Atmo-
sphere. Fort Collins, CO, 1993.
Also see (Submitted for publication)
Sisler, J., and Malm, W.C. "Interpreta-
tion of Trends of PM2 5 and Recon-
structed Visibility from the IMPROVE
Network," Journal of the Air and
Waste Management Association, 1998.
3. Irving, P.M., ed., Acid Deposition:
State of Science and Technology, Volume
III, Terrestrial, Materials, Health, and
Visibility Effects, The U.S. National Acid
Precipitation Assessment Program,
Chapter 24, page 24-76.
4. Schichtel, B.A., J.B. Husar, S.R.
Falke, and W.E. Wilson. "Haze Trends
of the United States, 1980-1995," Atmo-
spheric Environment in press.
5. The final regional haze rule was
signed on 4/22/99 and published in
the Federal Register on 7/1/99
(64FR35713).
114 VISIBILITY TRENDS • CHAPTER 6
-------
Atmospheric Deposition of
Sulfur and Nitrogen
Compounds
http://www.epa.gov/oar/aqtrnd99/chapter7.pdf
Worth Noting:
• 1990's improvements in wet sulfur
deposition, rural ambient S02, and rural
ambient sulfates followed the large
reductions in regional emissions in S02.
Most of the emissions and reductions
come from power plants.
- 10-year changes in the eastern United
States: annual average sulfates, -24
percent; annual average S02, -32
percent; regional power plant emissions,
-25 percent.
- 2-year changes in the eastern United
States: (1998-99): annual average
sulfates, -10 percent; annual average
S02, -4 percent; regional power plant
emissions, -6 percent.
• The largest sulfate improvements occur
during the third calendar quarter.
- 10-year changes: quarterly average
sulfates, -33 percent.
- 2-year changes (1998-99): quarterly
average sulfates, -17 percent.
• These regional reductions in particle
sulfates benefit visibility and PM2 5 levels.
Sulfur and nitrogen oxides are emit-
ted into the atmosphere primarily
from the burning of fossil fuels.
These emissions react in the atmo-
sphere to form compounds that are
transported long distances and are
subsequently deposited in the form
of pollutants such as particulate mat-
ter (sulfates, nitrates) and related
gases (nitrogen dioxide, sulfur diox-
ide and nitric acid). Nitrogen oxides
also will interact with volatile organic
compounds to form ozone. The ef-
fects of atmospheric deposition in-
clude acidification of lakes and
streams, nutrient enrichment of
coastal waters and large river basins,
soil nutrient depletion and decline of
sensitive forests, agricultural crop
damage, and impacts on ecosystem
biodiversity. Toxic pollutants and
metals also can be transported and
deposited through atmospheric pro-
cesses. (See Chapter 5: Air Toxics.)
Both local and long-range emis-
sion sources contribute to atmo-
spheric deposition. Total atmospheric
deposition is determined using both
wet and dry deposition measure-
ments. Wet deposition is the portion
dissolved in cloud droplets and is
deposited during rain or other forms
of precipitation. Dry deposition in-
cludes both gas and particle transfer
to surfaces during periods of no pre-
cipitation. Although the term "acid
rain" is widely recognized, the dry
deposition portion can range from
20-60 percent of total deposition.
EPA is required by several Con-
gressional and other mandates to
assess the effectiveness of air pollu-
tion control efforts. These mandates
include Title IX of the Clean Air Act
Amendments (the National Acid
Precipitation Assessment Program),
the Government Performance and
Results Act, and the U.S./Canada Air
Quality Agreement. One measure of
effectiveness of these efforts is
whether sustained reductions in the
amount of atmospheric deposition
over broad geographic regions are
occurring. However, changes in the
atmosphere happen very slowly and
trends are often obscured by the wide
variability of measurements and
climate. Numerous years of continu-
ous and consistent data are required
to overcome this variability, making
long-term monitoring networks espe-
cially critical for characterizing depo-
sition levels and identifying
relationships among emissions, at-
mospheric loadings and effects on
human health and the environment.
For wet and dry deposition, these
studies typically include measure-
CHAPTER 7 • ATMOSPHERIC DEPOSITION OF SULFUR AND NITROGEN COMPOUNDS 115
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 7-1. The National Atmospheric Deposition Program/National Trends Network.
t
¦ wumm
1
f
f
1
ment of concentration levels of key
chemical components as well as pre-
cipitation amounts. For dry deposi-
tion, analyses also must include
meteorological measurements that
are used to estimate rate of the actual
deposition, or "flux." Data represent-
ing total deposition loadings (e.g.,
total sulfate or nitrate) are what
many environmental scientists use
for integrated ecological assessments.
Primary Atmospheric
Deposition Monitoring
Networks
The National Atmospheric Deposi-
tion Program/National Trends Net-
work (NADP/NTN) and the Clean
Air Status and Trends Network
(CASTNet) were developed to moni-
tor wet and dry acid deposition,
respectively. Monitoring site loca-
tions are predominantly rural by
design to assess the relationship be-
tween regional pollution and changes
in regional patterns in deposition.
CASTNet also includes measure-
ments of rural ozone and the chemi-
cal constituents of PM2ij. Rural
monitoring sites of NADP/NTN and
CASTNet provide data where sensi-
tive ecosystems are located and pro-
vide insight into natural background
levels of pollutants where urban
influences are minimal. Scientists
and policy analysts use these data to
evaluate environmental effects, partic-
ularly those caused by regional sources
of emissions for which long-range
transport plays an important role.
Measurements from these networks
also are important for understanding
non-ecological impacts of air pollution
such as visibility impairment and dam-
age to materials, particularly those of
cultural and historical importance.
~ . Source: EPA/CAMD 04/04/01
They also provide important informa-
tion to support the NAAQS.
National Atmospheric Deposition
Network/National Trends
Network
The National Atmospheric Deposi-
tion Program/National Trends Net-
work is a cooperative program
between federal and state agencies,
universities, electric utilities and
other industries that has measured
precipitation chemistry in the United
States since 1978. As one of the
world's largest and longest running
deposition monitoring networks, it is
composed of over 200 sites and is
able to determine geographic pat-
terns and trends in precipitation
chemistry (see Figure 7-1).
The NADP/NTN analyzes the
constituents important in precipita-
tion chemistry, including those affect-
ing rainfall acidity and those that
116 ATMOSPHERIC DEPOSITION OF SULFURAND NITROGEN COMPOUNDS • CHAPTER 7
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 7-2. Annual mean sulfate deposition from precipitation, 1990-1992 vs.
1997-1999.
Source: CASTNet & NADP/NTN
Scfurce: CASTNet & NADP/NTN
Change
Scturce: CASTNet & NADP/NTN
sen"
I
r
may have ecological effects. The
Network measures sulfate, nitrate,
hydrogen ion (measure of acidity),
ammonia, chloride, and base cations
(calcium, magnesium, potassium).
To ensure comparability of results,
laboratory analyses for all samples
are conducted by NADP's Central
Analytical Lab at the Illinois State
Water Survey. A new subnetwork of
the NADP, the Mercury Deposition
Network (MDN) measures mercury in
precipitation. For more information on
the MDN, see Chapter 5: Air Toxics.
Trends Analyses for
Sulfate and Nitrogen
Concentrations in Wet
Deposition
Sulfate concentrations in precipitation
have decreased over the past two
decades.1 The reductions were rela-
tively large in the early 1980s fol-
lowed by more moderate declines
until 1995. These reductions in wet
sulfates are similar to changes in S02
emissions. In 1995 and 1996, howev-
er, concentrations of sulfates in pre-
cipitation over a large area of the
eastern United States exhibited a
dramatic and unprecedented reduc-
tion. Sulfates in rain have been esti-
mated to be 10-25 percent lower than
levels expected with a continuation
of 1983-1994 trends.2 The wet sulfate
deposition levels in the 1990-1992
and 1997-1999 time periods, together
with the absolute change are illustrat-
ed in Figure 7-2. This important re-
duction in acid precipitation is
directly related to the large regional
decreases in S02 emissions resulting
from phase I of the Acid Rain Pro-
gram (see "Trends in S02" in Chapter
2 of this report). The largest reduc-
tions in wet sulfate deposition oc-
curred along the Ohio River Valley
CHAPTER? • ATMOSPHERIC DEPOSITION OF SULFUR AND NITROGEN COMPOUNDS 117
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
and in states to the north and imme-
diately downwind of this region.
Nitrogen trends paint a different
picture. Nitrate and ammonium dep-
osition derived from NADP/NTN
measurement sites reveal 10-year
improvement in some areas, includ-
ing eastern IX, MI, PA and NY. In-
creased deposition is estimated for
the Plains States; and the western
Ohio River and Central Mississippi
River Valleys. From ammonium in
rain, increases are also noted for
eastern NC. However, most areas of
the country were not appreciably
different in either oxidized or reduced
1997-1999 nitrogen from historical
levels (see Figures 7-3 and 7-4).
Clean Air Status and Trends
Network
The Clean Air Status and Trends
Network provides atmospheric data
on the dry deposition component of
total acid deposition, ground-level
ozone and other forms of atmos-
pheric pollution. CASTNet is consid-
ered the nation's primary source for
atmospheric data to estimate dry
acidic deposition and to provide data
on rural ozone levels. Used in con-
junction with other national monitor-
ing networks, CASTNet is used to
determine the effectiveness of nation-
al emission control programs. Estab-
lished in 1987, CASTNet now
comprises 79 monitoring stations
across the United States. The longest
data records are primarily at eastern
sites. The majority of the monitoring
stations are operated by EPA's Office
of Air and Radiation; however, 27
stations are operated by the National
Park Service (NPS) in cooperation
with EPA. Of the total number of
sites, 74 measure dry-deposition, 68
measure ozone, and eight measure
aerosols for visibility assessment.
Figure 7-3. Annual mean ammonium deposition from precipitation, 1990-1992 vs.
1997-1999.
Source: CASTNet & NADP/NTN
Source: CASTNet & NADP/NTN
Change
Source: CASTNet & NADP/NTN
118 ATMOSPHERIC DEPOSITION OF SULFURAND NITROGEN COMPOUNDS • CHAPTER 7
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Each CASTNet dry deposition
station measures:
• Weekly average atmospheric
concentrations of sulfate, nitrate,
ammonium, sulfur dioxide, and
nitric acid (sulfate, nitrate and am-
monium generally exist as fine
particles).
• Hourly concentrations of ambient
ozone levels.
• Meteorological conditions required
for calculating dry deposition rates.
Dry Deposition
Dry deposition rates are calculated
using atmospheric concentrations,
meteorological data and information
on land use, vegetation, and surface
conditions. CASTNet complements
the database compiled by NADP/
NTN. Together, these two long-term
databases provide the necessary data
to estimate trends and spatial patterns
in total atmospheric deposition. NOAA
also operates a smaller dry deposition
network called Atmospheric Integrated
Assessment Monitoring Network
(AIRMoN) focused on addressing
research issues specifically related to
dry deposition measurement.
Concentration Trends Analysis
at CASTNet Sites
CASTNet ambient concentration data
in the eastern United States were
analyzed for the period 1990-1999 for
the change in ambient sulfur dioxide,
sulfates, total nitrates and ammoni-
um. First, maps are presented for a
comparison of 3-year periods at the
beginning and end of the 10-year
period based on data from all 51
eastern locations in the CASTNet
monitoring program. Then data from
a subset of 34 eastern CASTNet sites
with the most complete historical
record are examined for year to year
changes from 1990-1999.3,
Figure 7-4. Annual mean nitrate deposition from precipitation, 1990-1992 vs.
1997-1999.
SOI'
ftonoj
1
fi
.
1*
£
k
->26
Source: CASTNet & NADP/NTN
Source: dASTNet & NADP/NTN
Change
I
Source:-CASTNet & NADP/NTN
CHAPTER? • ATMOSPHERIC DEPOSITION OF SULFUR AND NITROGEN COMPOUNDS 118
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 7-5. Rural annual mean S02 concentrations from CASTNet, 1990-1992 vs. 1997-1999.
1990-1992
1997-1999
Source: CASTNet
so2
(|jg/m3)
Source: CASTNet
Source: CASTNet
SQ2.
(Mg/m3)
In the early 1990s, ambient S02
concentrations in the rural eastern
United States were highest in western
Pennsylvania, along the Ohio Valley
and in the vicinity of Chicago/Gary
Indiana. Large improvement in ambi-
ent S02 air quality can be seen in
Figure 7-5 by comparing 1990-1992
with 1997-1999. The largest decreases
in concentrations are noted in the
vicinity of Chicago and throughout
the states bordering the Ohio Valley
(IL, IN, OH, PA, KY, WV). The high-
est S02 concentrations in the rural
parts of the eastern United States are
now concentrated in southwestern PA.
Figure 7-6 shows that sulfate con-
centrations greater than 5 pg/rr#*
cover most of the eastern United
"Sulfate concentrations represent the
sulfate ion, SO4 2, and do not represent the
compounds (i.e., ammonium sulfate or
ammonium bisulfate) typically associated
with this analyte.
States in the 1990-1992 period. Re-
gions of concentrations greater than 6
]Ug/m3 are estimated to cover the
Ohio Valley States (IL, IN, OH, KY,
WV), Pennsylvania, and the other
mid-Atlantic states from New Jersey
to Virginia. The highest sulfate con-
centrations (> 7 ]ug/m3) were adja-
cent to the Ohio Valley and in
northern Alabama. These are the
locations of large electric utilities.
During the late 1990s, ambient
average sulfates lowered dramati-
cally. Although there are differences
in the measured concentrations
among these individual years, both the
size of the region with high concentra-
tions as well as the magnitude of those
concentrations have decreased.
Based on 34 CASTNet sites with
10 years of measurement data (Figure
7-7), mean rural sulfur dioxide con-
centrations were reduced by 32 per-
cent and mean rural sulfate levels
were reduced by 24 percent. The
regional distribution of annual aver-
age concentrations is presented as
box-plots in Figures 7-8 and 7-9. A
10-percent decrease in mean sulfates
and 4-percent decrease in annual
mean sulfur dioxide between 1998
and 1999 is also noted. This is a re-
versal of the 2-year increase previ-
ously reported for 1997-1998.
Levels and spatial changes in am-
bient nitrates in the rural east are
shown in Figure 7-10. No significant
change is noted in total nitrate con-
centrations. The trend in average
total nitrate concentrations (nitrates
plus nitric acid) among the 34 trend
sites was level, corresponding to the
small change in NOx emissions dur-
ing this period. The stable regional
average nitrate trend line is not
shown. The highest nitrate concentra-
tions in the East are recorded in Ohio,
Indiana, and Illinois. As shown in
120 ATMOSPHERIC DEPOSITION OF SULFUR AND NITROGEN COMPOUNDS • CHAPTER 7
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 7-6. Rural annual average sulfate concentrations from CASTNet, 1990-1992 vs. 1997-1999.
S04*:
(ng/m3)
Change
SO„2-
(ug/ms)
Source: CASTNet
1990-1992
Source: CASTNet
Figure 7-7. CASTNet and subset of 34 long-term monitoring sites used for 1990-1999 trends analysis.
34 long-term monitoring sites.
CHAPTER? • ATMOSPHERIC DEPOSITION OF SULFUR AND NITROGEN COMPOUNDS 121
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 7-10, the 10-year change in
total nitrate concentrations at indi-
vidual measurement locations has
been minimal. The ammonium maps
for the eastern United States pre-
sented in Figure 7-11 shows that the
highest ammonium concentrations
are also highest in the midwest. This
is due to the association of ammo-
nium concentrations to sulfate and
nitrate compounds. Although total
nitrates have not substantially
changed throughout this region, the
10-year decrease in ambient ammo-
nium in the Ohio Valley and elsewhere
appears to be associated with the re-
duction in sulfate concentrations.
Seasonal Trends in S02
Emissions and Related
Air Quality
Electric utilities account for 70 per-
cent of the S02 emissions in the east-
ern United States and for 75 percent
of the 10-year regional reduction in
S02 emissions. The trend in ambient
sulfates and sulfur dioxide are gener-
ally consistent with the change in
annual sulfur dioxide emissions from
electric utilities in the eastern United
States. Figure 7-12 shows that the
24-percent 10-year decline in sulfates
and 31-percent decrease in ambient
S02 correspond to the overall 25-
percent decline in power plant S02
emissions. In addition, the 1998-1999
decrease in ambient rural sulfates (10
percent) and in ambient rural S02 (4
percent) appear to follow the 6-per-
cent decrease in annual regional S02
power plant emissions.
For annual average ambient sulfur
dioxide, the long-term air quality
improvement is more substantial and
appears similar to the large drop in
regional S02 power plant emissions
which occurred between 1993 and
Figure 7-8. Trend in ambient sulfates in the rural eastern United States, based on
CASTNet monitoring data, 1990-1999.
Concentration (ug/m3)
6 -
- 90th Percentile
- Median
- 10th Percentile
34 Sites
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
Figure 7-9. Trend in ambient sulfur dioxide in the rural eastern United States, based
on CASTNet monitoring data, 1990-1999.
Concentration (ug/m3)
30 -
- 90th Percentile
34 Sites
- 10th Percentile
122 ATMOSPHERIC DEPOSITION OF SULFUR AND NITROGEN COMPOUNDS • CHAPTER 7
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 7-10. Rural annual mean ammonium concentrations from CASTNet, 1990-1992 vs. 1997-1999.
1990-1992
1997-1999
NhV
(|jg/tn«r
I
Change
1L'
(Mg/m3)
r
'
*
(Mg/m3)
L 4 J
0
hOiA
:
Source: CASTNet
Source: CASTNet
Source: CASTNet
Figure7-11. Rurai annual mean total nitrate concentrations from CASTNet, 1990-1992vs. 1997-1999.
1990-1992
1997-1999
Change
no3-
¦rd
- V- 11
/ f
nq3-
(M9/m 3)
f :
Source: CASTNet
Source: CASTNet
Source: CASTNet
CHAPTER 7 • ATMOSPHERIC DEPOSITION OF SULFUR AND NITROGEN COMPOUNDS 123
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
1995. For sulfates, the composite
average ambient concentrations de-
pict a more gradual change.
Figure 7-13 presents the trends in
ambient sulfates, ambient sulfur
dioxide, and S02 emissions by calen-
dar quarter. The largest 10-year de-
crease in quarterly average ambient
sulfates occurred during the 3rd cal-
endar quarter which is the high sul-
fate "season." This 3-month period
with its slow moving air masses, high
photochemical activity and high
seasonal S02 emissions contributes
65-70 percent to the typical annual
average concentrations of sulfates.
Sulfur dioxide on the other hand
depicts its lowest concentration levels
during the summer season, but also
reveals long term, albeit slightly
lower, rural air quality improvement
(-25 percent). This contrasts with
more significant 10-year changes of
-30 percent, -34 percent and -37 per-
cent for the 1st, 2nd, and 4th calendar
quarters respectively.
These changes in rural S02 match
the annual average results presented
for urban areas. (See the criteria
pollutants section in Chapter 2 for
more information about urban ambi-
ent S02 trends, S02 emission trends
and the acid rain program. Also see
www.epa.gov/airmarkets/.)
Figure 7-12. Trend in annual mean ambient sulfur dioxide and sulfate concentrations,
based on CASTNet monitoring data, and regional S02 emissions from electric utilities
in rural eastern United States, 1990-1999.
15
II
si
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U
(/) "So
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2 c
g 8
1§
C\J CM
OO
CO CO
10
SO2 Emissions
SO2 Concentrations
**» ^
- - - _ - - -
Sulfate concentrations
10
8
6
4
2
E
D>
CO
c
o
2
-i—»
C
0
o
c
8
CD
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90 91 92 93 94 95 96 97 98 99
Year
Figures 7-13a. and Figure 7-13b. Trend in annual mean ambient sulfur dioxide and
sulfate concentrations, based on CASTNet monitoring data, and regional S02 emissions
from electric utilities in rural eastern United States by calendar quarter, 1990-1999.
10-
CO
c
o
¦*—>
c
o
10
c
o
¦(0
to
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CD
CM
o
CO
E
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c
o
o
CM
o
CO
20
15
10
5
Quarter 1
t
SO2 Concentrations
SO2 Emissions
Sulfate concentrations
10
8
6
4
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CO
c
o
c
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0
c
8
CD
1
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90 91 92 93 94 95 96 97 98 99
Year
Sulfur and Nitrogen
Deposition
Total deposition of sulfur and nitro-
gen are derived from concentrations
of sulfur and nitrogen species in rain
combined with estimated deposition
resulting from ambient particles and
gases. As described for the spatial
patterns in measured concentrations
of wet and dry sulfur compounds, the
highest deposition of sulfur also is
estimated to occur in the eastern
10-
CO
c
c
o
CO
c
o
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CD
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20
15
10
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C
0)
o
c
o
o
CM
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CO
^S02 Emissions
Sulfate concentrations
/ ^
SO2 Concentrations
" " " m „ +*
10
8
6
4
90 91 92 93 94 95 96 97 98 99
Year
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o
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o
c
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o
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CO
124 ATMOSPHERIC DEPOSITION OF SULFUR AND NITROGEN COMPOUNDS • CHAPTER 7
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figures 7-13c. and 7-13d. Trend in annual mean ambient sulfur dioxide and sulfate
concentrations, based on CASTNet monitoring data, and regional S02 emissions from
electric utilities in rural eastern United States by calendar quarter, 1990-1999.
20
E
O)
315
CO
c
o
"210
-«—»
c
CD
O
c
8
CSJ
o
CO
Quarter 3
Sulfate concentrations
J
" \
SO2 Emissions
S02 Concentrations
—\
90 91 92 93 94 95 96 97 98 99
Year
20
E
D>
15
(/)
c
o
'•*—>
2
c
(D
O
c
o
o
CM
O
CO
10
Quarter 4
SO2 Emissions
X. SO2 Concentrations
i
/
Sulfate concentrations
90 91 92 93 94 95 96 97 98 99
Year
United States. Because of differences
in rain, terrain and ground cover
there is more spatial variability in
estimated deposition than the con-
tributing ambient concentrations.
Some of the highest estimated sulfur
deposition include areas along and to
the East of the Ohio Valley. In these
areas, generally at least half (45-65
percent) come from rain. This wet
percent ranges from 70-90 percent in
the other eastern United States areas
with lower sulfur deposition. In all
areas of the eastern United States,
most of the dry deposition is associ-
ated ambient S02 gas. In the West,
sulfur deposition is much lower.
Most western sulfur is deposited in
rain, but the other sulfur is more
evenly divided between S02 gas and
sulfate particle (see Figure 7-14).
Nitrogen deposition comes from
ammonium and nitrates in rain and
ambient particulate concentrations of
those species as well as ambient nitric
acid. Based on monitoring stations
that provide both wet and dry nitro-
gen measurements, Figure 7-15
shows that large areas of the eastern
United States have similarly high
values of estimated nitrogen deposi-
tion. The estimated deposition at
western stations is much lower. For
eastern stations, 60-70 percent is
estimated to come from rain and
most of this is associated with ammo-
nium. Almost all of the remaining
30-40 percent is associated with mea-
sured nitric acid. In the West, rain
accounts for more of the total deposi-
tion. Because dry nitrogen measure-
ments are not available for the
middle of the country, total nitrogen
deposition cannot be estimated for
this region. Data from the NADP,
however, suggest that high nitrogen
deposition would occur in this re-
gion. See Figure 7-3 which shows the
high deposition of ammonium from
precipitation in the region centered
on IA.
References
1. Lynch, J. A., J.W. Grim and V.C.
Bowersox. 1995. Trends in Precipitation
Chemistn/ in the United States: A Nation-
al Perspective, 1980-1992. Atmospheric
Environment Vol 29, No. 11.
2. Lynch, J.A., V.C. Bowersox and J.W.
Grim. 1996. Trends in Precipitation
Chemistry in the United States: An Anal-
ysis of the Effects in 1995 of Phase 1 of the
Clean Air Act Amendments of 1990, Title
IV. U.S. Geological Survey. Open-file
Report 96-0346.
3. Clean Air Status and Trends Net-
work (CASTNet), 1999 Annual Report.
http://www.epa.gov/castnet/
reports.html.
CHAPTER 7 • ATMOSPHERIC DEPOSITION OF SULFUR AND NITROGEN COMPOUNDS 125
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure 7-14. Wet and dry components of sulfur deposition, 1999.
1 t*
¥
1
u
H T # " V ^
M M
, MJtt " - M m u k
W v W WW*** #
v» M ~r mj " '~ 1
u 1 H
"Tl
« €
*NtS£N*
¦¦lov soa
Source: USEPA/CASTNet NADP/NTN 04/04/01
Figure 7-15. Wet and dry components of nitrogen deposition, 1999.
v
LvKWNOa
I Oy Pnnpu'aw wH" "
I pFf >#Ol
® Dry ^ Q ^
W Jfl
41
T*
it
JM
.4 < u ,U
«. M*| ».lo I'
i# „ Iftfllr n ;i *•* \
" § # » ^ " to ^
¥
u
u
U W
u
Source: USEPA/CASTNet NADP/NTN USEPA/CAMD 04/04/01
126 ATMOSPHERIC DEPOSITION OF SULFUR AND NITROGEN COMPOUNDS • CHAPTER 7
-------
APPENDIX A
Data Tables
http://www.epa.gov/oar/aqtrnd99/appenda.pdf
APPENDIX A • DATA TABLES 127
-------
NATIONALAIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-1a. National Air Quality Trends Statistics for Criteria Pollutants, 1980-1989
Statistic
# of Sites Units Percentile 1980
1981
1982
1983 1984 1985 1986
1987
1988 1989
Carbon Monoxide
2nd Max. 8-hr.
304
ppm
95th
15.6
14.6
14.1
14.1
13.6
12.4
12.1
11.6
11.4
11.1
2nd Max. 8-hr.
304
ppm
90th
13.9
12.6
12.7
12.4
11.9
11.0
10.7
9.6
10.0
9.6
2nd Max. 8-hr.
304
ppm
75th
10.7
10.6
10.0
9.8
9.9
8.9
8.9
8.3
7.8
7.9
2nd Max. 8-hr.
304
ppm
50th
7.9
7.7
7.5
7.3
7.3
6.5
6.8
6.3
6.0
6.0
2nd Max. 8-hr.
304
PPm
25th
5.7
6.0
5.6
5.4
5.2
4.9
5.1
4.7
4.5
4.5
2nd Max. 8-hr.
304
PPm
10th
4.4
4.2
4.4
3.9
4.2
3.7
3.9
3.7
3.5
3.6
2nd Max. 8-hr.
304
PPm
5th
3.8
3.7
3.6
3.4
3.5
3.4
3.3
3.3
3.1
2.9
2nd Max. 8-hr.
304
PPm
Arith. Mean
8.6
8.4
8.1
7.9
7.8
7.1
7.2
6.7
6.5
6.4
Lead
Max. Qtr. AM
216
|jg/m3
95th
1.63
1.28
1.12
0.87
0.74
0.63
0.36
0.30
0.22
0.21
Max. Qtr. AM
216
|jg/m3
90th
1.18
1.00
0.93
0.68
0.63
0.45
0.27
0.20
0.18
0.14
Max. Qtr. AM
216
|jg/m3
75th
0.70
0.58
0.63
0.50
0.45
0.30
0.17
0.13
0.11
0.10
Max. Qtr. AM
216
|jg/m3
50th
0.50
0.40
0.42
0.36
0.33
0.19
0.12
0.09
0.07
0.06
Max. Qtr. AM
216
|jg/m3
25th
0.35
0.29
0.28
0.24
0.22
0.14
0.08
0.06
0.05
0.04
Max. Qtr. AM
216
|jg/m3
10th
0.23
0.21
0.19
0.17
0.16
0.10
0.06
0.04
0.03
0.03
Max. Qtr. AM
216
|jg/m3
5th
0.19
0.17
0.15
0.14
0.12
0.07
0.05
0.03
0.02
0.02
Max. Qtr. AM
216
|jg/m3
Arith. Mean
0.65
0.54
0.53
0.40
0.37
0.25
0.15
0.11
0.10
0.08
Nitrogen Dioxide
Arith. Mean
156
PPm
95th
0.051
0.051
0.050
0.046
0.046
0.048
0.050
0.043
0.048
0.045
Arith. Mean
156
PPm
90th
0.040
0.041
0.039
0.038
0.038
0.038
0.035
0.038
0.037
0.036
Arith. Mean
156
PPm
75th
0.029
0.028
0.028
0.027
0.029
0.029
0.028
0.028
0.028
0.028
Arith. Mean
156
PPm
50th
0.023
0.021
0.021
0.021
0.022
0.022
0.022
0.022
0.023
0.022
Arith. Mean
156
PPm
25th
0.016
0.016
0.016
0.016
0.016
0.017
0.016
0.017
0.016
0.016
Arith. Mean
156
PPm
10th
0.007
0.009
0.009
0.008
0.009
0.009
0.009
0.011
0.009
0.009
Arith. Mean
156
PPm
5th
0.003
0.003
0.004
0.003
0.003
0.004
0.004
0.004
0.003
0.003
Arith. Mean
156
PPm
Arith. Mean
0.024
0.024
0.023
0.022
0.023
0.023
0.023
0.023
0.023
0.023
Ozone
2nd
Max. 1-hr.
441
PPm
95th
0.220
0.202
0.196
0.220
0.203
0.190
0.170
0.180
0.200
0.170
2nd
Max. 1-hr.
441
PPm
90th
0.177
0.164
0.160
0.186
0.165
0.160
0.150
0.164
0.180
0.143
2nd
Max. 1-hr.
441
PPm
75th
0.150
0.140
0.133
0.150
0.138
0.132
0.130
0.140
0.155
0.124
2nd
Max. 1-hr.
441
PPm
50th
0.122
0.115
0.115
0.130
0.113
0.112
0.112
0.118
0.130
0.108
2nd
Max. 1-hr.
441
PPm
25th
0.105
0.100
0.100
0.110
0.100
0.098
0.098
0.104
0.110
0.099
2nd
Max. 1-hr.
441
PPm
10th
0.091
0.090
0.086
0.095
0.090
0.088
0.086
0.090
0.098
0.086
2nd
Max. 1-hr.
441
PPm
5th
0.087
0.080
0.080
0.085
0.080
0.078
0.080
0.087
0.088
0.080
2nd
Max. 1-hr.
441
PPm
Arith. Mean
0.134
0.125
0.124
0.137
0.124
0.122
0.118
0.124
0.135
0.115
4th Max.
8-hr.
441
PPm
95th
0.142
0.129
0.128
0.145
0.130
0.127
0.120
0.126
0.140
0.120
4th Max.
8-hr.
441
PPm
90th
0.125
0.115
0.114
0.126
0.113
0.111
0.107
0.116
0.128
0.105
4th Max.
8-hr.
441
PPm
75th
0.106
0.101
0.098
0.110
0.099
0.097
0.095
0.102
0.115
0.093
4th Max.
8-hr.
441
PPm
50th
0.093
0.088
0.088
0.096
0.088
0.087
0.085
0.090
0.102
0.084
4th Max.
8-hr.
441
PPm
25th
0.082
0.077
0.076
0.085
0.077
0.077
0.076
0.081
0.087
0.076
4th Max.
8-hr.
441
PPm
10th
0.071
0.068
0.066
0.071
0.067
0.067
0.069
0.072
0.076
0.068
4th Max.
8-hr.
441
PPm
5th
0.065
0.060
0.061
0.063
0.062
0.062
0.062
0.067
0.067
0.063
4th Max.
8-hr.
441
PPm
Arith. Mean
0.097
0.091
0.090
0.099
0.091
0.090
0.088
0.093
0.102
0.087
128
DATA TABLES • APPENDIX A
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-1a. National Air Quality Trends Statistics for Criteria Pollutants, 1980-1989 (continued)
Statistic
# of Sites
Units
Percentile
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
Annual Avg.
—
|jg/m3
95th
—
—
—
—
—
—
—
—
—
—
Annual Avg.
—
|jg/m3
90th
—
—
—
—
—
—
—
—
—
—
Annual Avg.
—
|jg/m3
75th
—
—
—
—
—
—
—
—
—
—
Annual Avg.
—
|jg/m3
50th
—
—
—
—
—
—
—
—
—
—
Annual Avg.
—
|jg/m3
25th
—
—
—
—
—
—
—
—
—
—
Annual Avg.
—
|jg/m3
10th
—
—
—
—
—
—
—
—
—
—
Annual Avg.
—
|jg/m3
5th
—
—
—
—
—
—
—
—
—
—
Annual Avg.
—
|jg/m3
Arith. Mean
—
—
—
—
—
—
—
—
—
—
Sulfur Dioxide
Arith. Mean
438
ppm
95th
0.0232
0.0223
0.0195
0.0182
0.0184
0.0176
0.0163
0.0162
0.0170
0.0162
Arith. Mean
438
ppm
90th
0.0190
0.0177
0.0164
0.0151
0.0156
0.0150
0.0140
0.0134
0.0143
0.0141
Arith. Mean
438
ppm
75th
0.0134
0.0133
0.0119
0.0121
0.0122
0.0114
0.0114
0.0111
0.0109
0.0107
Arith. Mean
438
ppm
50th
0.0092
0.0090
0.0085
0.0085
0.0088
0.0083
0.0081
0.0078
0.0080
0.0077
Arith. Mean
438
PPm
25th
0.0057
0.0059
0.0057
0.0056
0.0054
0.0050
0.0050
0.0048
0.0048
0.0047
Arith. Mean
438
PPm
10th
0.0029
0.0029
0.0031
0.0029
0.0029
0.0026
0.0025
0.0024
0.0025
0.0023
Arith. Mean
438
PPm
5th
0.0018
0.0018
0.0016
0.0017
0.0018
0.0019
0.0016
0.0016
0.0019
0.0016
Arith. Mean
438
PPm
Arith. Mean
0.0103
0.0101
0.0094
0.0091
0.0092
0.0087
0.0085
0.0083
0.0084
0.0081
2nd Max. 24-hr.
PPm
95th
2nd Max. 24-hr.
—
PPm
90th
—
—
—
—
—
—
—
—
—
—
2nd Max. 24-hr.
—
PPm
75th
—
—
—
—
—
—
—
—
—
—
2nd Max. 24-hr.
—
PPm
50th
—
—
—
—
—
—
—
—
—
—
2nd Max. 24-hr.
—
PPm
25th
—
—
—
—
—
—
—
—
—
—
2nd Max. 24-hr.
—
PPm
10th
—
—
—
—
—
—
—
—
—
—
2nd Max. 24-hr.
PPm
5th
—
2nd Max. 24-hr.
PPm
Arith. Mean
—
APPENDIX A • DATA TABLES 129
-------
NATIONALAIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-1 b. National Air Quality Trends Statistics for Criteria Pollutants, 1990-1999
Statistic
# of Sites Units Percentile 1990
1991
1992 1993 1994 1995
1996 1997
1998 1999
Carbon Monoxide
2nd Max. 8-hr.
388
ppm
95th
10.5
9.9
8.9
8.4
8.3
7.9
7.7
6.9
7.0
6.5
2nd Max. 8-hr.
388
ppm
90th
8.9
8.9
8.0
7.4
7.7
6.7
6.7
6.1
5.8
5.6
2nd Max. 8-hr.
388
PPm
75th
7.2
7.2
6.6
6.1
6.2
5.7
5.2
5.0
4.7
4.5
2nd Max. 8-hr.
388
PPm
50th
5.5
5.3
5.0
4.8
5.0
4.3
4.0
3.8
3.6
3.6
2nd Max. 8-hr.
388
PPm
25th
4.2
4.0
3.8
3.7
3.9
3.3
3.0
2.9
2.8
2.6
2nd Max. 8-hr.
388
PPm
10th
3.1
2.9
2.8
2.8
2.7
2.5
2.3
2.1
2.1
2.0
2nd Max. 8-hr.
388
PPm
5th
2.5
2.3
2.3
2.2
2.2
2.2
2.0
1.7
1.8
1.6
2nd Max. 8-hr.
388
PPm
Arith. Mean
5.8
5.7
5.3
5.0
5.1
4.6
4.3
4.0
3.8
3.7
Lead
Max. Qtr. AM
175
|jg/m3
95th
0.40
0.25
0.19
0.18
0.15
0.16
0.14
0.12
0.13
0.10
Max. Qtr. AM
175
|jg/m3
90th
0.18
0.16
0.14
0.11
0.10
0.09
0.09
0.09
0.09
0.08
Max. Qtr. AM
175
|jg/m3
75th
0.09
0.08
0.07
0.07
0.06
0.05
0.05
0.04
0.04
0.05
Max. Qtr. AM
175
|jg/m3
50th
0.05
0.04
0.04
0.04
0.03
0.03
0.03
0.02
0.02
0.02
Max. Qtr. AM
175
|jg/m3
25th
0.03
0.03
0.02
0.02
0.02
0.02
0.01
0.01
0.01
0.01
Max. Qtr. AM
175
|jg/m3
10th
0.02
0.02
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
Max. Qtr. AM
175
|jg/m3
5th
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
Max. Qtr. AM
175
|jg/m3
Arith. Mean
0.10
0.08
0.06
0.06
0.05
0.05
0.04
0.04
0.04
0.04
Nitrogen Dioxide
Arith. Mean
230
PPm
95th
0.039
0.043
0.038
0.037
0.040
0.039
0.037
0.034
0.035
0.035
Arith. Mean
230
PPm
90th
0.033
0.032
0.032
0.031
0.032
0.031
0.031
0.030
0.031
0.030
Arith. Mean
230
PPm
75th
0.025
0.025
0.024
0.024
0.024
0.023
0.023
0.022
0.023
0.023
Arith. Mean
230
PPm
50th
0.018
0.018
0.018
0.018
0.019
0.018
0.018
0.017
0.017
0.017
Arith. Mean
230
PPm
25th
0.013
0.012
0.012
0.012
0.013
0.012
0.012
0.012
0.012
0.012
Arith. Mean
230
PPm
10th
0.007
0.007
0.007
0.007
0.007
0.007
0.007
0.007
0.006
0.007
Arith. Mean
230
PPm
5th
0.005
0.005
0.005
0.005
0.004
0.004
0.004
0.004
0.004
0.004
Arith. Mean
230
PPm
Arith. Mean
0.020
0.019
0.019
0.019
0.020
0.019
0.018
0.018
0.018
0.018
Ozone
2nd
Max. 1-hr.
703
PPm
95th
0.170
0.170
0.159
0.150
0.147
0.149
0.141
0.142
0.150
0.139
2nd
Max. 1-hr.
703
PPm
90th
0.144
0.147
0.130
0.137
0.129
0.139
0.126
0.130
0.133
0.130
2nd
Max. 1-hr.
703
PPm
75th
0.120
0.122
0.112
0.120
0.117
0.123
0.114
0.116
0.119
0.118
2nd
Max. 1-hr.
703
PPm
50th
0.107
0.107
0.099
0.104
0.104
0.110
0.103
0.103
0.109
0.107
2nd
Max. 1-hr.
703
PPm
25th
0.093
0.093
0.090
0.091
0.092
0.098
0.093
0.091
0.097
0.095
2nd
Max. 1-hr.
703
PPm
10th
0.083
0.082
0.082
0.080
0.083
0.086
0.084
0.081
0.086
0.085
2nd
Max. 1-hr.
703
PPm
5th
0.075
0.076
0.077
0.075
0.077
0.079
0.079
0.075
0.077
0.077
2nd
Max. 1-hr.
703
PPm
Arith. Mean
0.112
0.112
0.105
0.108
0.107
0.112
0.105
0.105
0.110
0.107
4th Max.
8-hr.
703
PPm
95th
0.115
0.115
0.107
0.110
0.106
0.112
0.103
0.105
0.110
0.105
4th Max.
8-hr.
703
PPm
90th
0.105
0.108
0.097
0.101
0.098
0.107
0.097
0.100
0.102
0.102
4th Max.
8-hr.
703
PPm
75th
0.093
0.096
0.087
0.090
0.090
0.096
0.090
0.091
0.095
0.095
4th Max.
8-hr.
703
PPm
50th
0.083
0.084
0.079
0.081
0.082
0.088
0.082
0.082
0.087
0.087
4th Max.
8-hr.
703
PPm
25th
0.074
0.073
0.073
0.073
0.074
0.077
0.075
0.073
0.077
0.077
4th Max.
8-hr.
703
PPm
10th
0.066
0.065
0.066
0.063
0.067
0.068
0.068
0.065
0.069
0.067
4th Max.
8-hr.
703
PPm
5th
0.060
0.059
0.061
0.059
0.061
0.062
0.062
0.059
0.060
0.061
4th Max. 8-hr.
703
ppm
Arith. Mean 0.085 0.086 0.081
0.083 0.084 0.087 0.083 0.082 0.086 0.085
130
DATA TABLES • APPENDIX A
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-1b. National Air Quality Trends Statistics for Criteria Pollutants, 1990-1999 (continued)
Statistic
# of Sites Units Percentile 1990
1991
1992 1993 1994 1995
1996 1997
1998 1999
PM„
Annual Avg.
954
|jg/m3
95th
45.9
45.5
41.7
40.5
39.4
38.4
37.4
37.5
35.5
39.7
Annual Avg.
954
|jg/m3
90th
39.6
39.8
36.3
35.8
36.2
34.6
33.0
32.2
31.7
32.7
Annual Avg.
954
|jg/m3
75th
33.9
33.5
30.9
30.1
30.3
29.0
27.6
27.1
27.5
27.6
Annual Avg.
954
|jg/m3
50th
28.1
28.0
25.7
25.2
25.4
24.2
22.9
22.9
23.4
23.0
Annual Avg.
954
|jg/m3
25th
23.2
23.4
22.0
21.0
20.9
19.7
19.3
19.3
19.2
19.1
Annual Avg.
954
|jg/m3
10th
18.8
18.3
17.7
16.9
16.7
15.6
16.1
15.6
15.2
15.0
Annual Avg.
954
|jg/m3
5th
16.1
15.2
14.7
13.5
13.4
12.6
13.2
12.7
12.9
12.9
Annual Avg.
954
|jg/m3
Arith. Mean
29.2
29.0
26.8
26.0
26.0
24.8
24.0
23.8
23.6
23.9
Sulfur Dioxide
Arith. Mean
480
ppm
95th
0.0176
0.0162
0.0154
0.0154
0.0143
0.0116
0.0113
0.0107
0.0106
0.0103
Arith. Mean
480
ppm
90th
0.0146
0.0140
0.0129
0.0126
0.0123
0.0101
0.0097
0.0091
0.0095
0.0089
Arith. Mean
480
ppm
75th
0.0108
0.0100
0.0095
0.0093
0.0091
0.0074
0.0074
0.0071
0.0070
0.0068
Arith. Mean
480
ppm
50th
0.0077
0.0075
0.0068
0.0067
0.0065
0.0051
0.0053
0.0051
0.0049
0.0048
Arith. Mean
480
PPm
25th
0.0043
0.0044
0.0042
0.0039
0.0037
0.0032
0.0032
0.0031
0.0032
0.0032
Arith. Mean
480
PPm
10th
0.0022
0.0022
0.0020
0.0022
0.0020
0.0018
0.0019
0.0018
0.0019
0.0019
Arith. Mean
480
PPm
5th
0.0014
0.0015
0.0014
0.0015
0.0015
0.0014
0.0014
0.0014
0.0014
0.0014
Arith. Mean
480
PPm
Arith. Mean
0.0081
0.0079
0.0073
0.0072
0.0069
0.0056
0.0056
0.0054
0.0053
0.0052
2nd Max. 24-hr.
481
PPm
95th
0.0870
0.0750
0.0750
0.0720
0.0720
0.0570
0.0600
0.0520
0.0520
0.0520
2nd Max. 24-hr.
481
PPm
90th
0.0660
0.0630
0.0620
0.0590
0.0620
0.0480
0.0470
0.0450
0.0440
0.0410
2nd Max. 24-hr.
481
PPm
75th
0.0480
0.0440
0.0440
0.0420
0.0450
0.0330
0.0330
0.0330
0.0310
0.0290
2nd Max. 24-hr.
481
PPm
50th
0.0330
0.0320
0.0300
0.0280
0.0330
0.0220
0.0230
0.0230
0.0220
0.0210
2nd Max. 24-hr.
481
PPm
25th
0.0200
0.0200
0.0190
0.0190
0.0190
0.0150
0.0150
0.0140
0.0140
0.0140
2nd Max. 24-hr.
481
PPm
10th
0.0100
0.0100
0.0100
0.0100
0.0090
0.0080
0.0090
0.0070
0.0070
0.0070
2nd Max. 24-hr.
481
PPm
5th
0.0060
0.0070
0.0060
0.0060
0.0050
0.0050
0.0050
0.0050
0.0050
0.0050
2nd Max. 24-hr.
481
PPm
Arith. Mean
0.0376
0.0350
0.0340
0.0328
0.0343
0.0259
0.0263
0.0251
0.0242
0.0233
APPENDIX A • DATA TABLES
131
-------
Source Category
1970 1975 1980 1985 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
Fuel Combustion
4,632
4,480
7,302
8,485
7,443
FUEL COMB. ELEC. UTIL.
237
276
322
291
321
Coal
106
134
188
207
233
Oil
41
69
48
18
26
Gas
90
73
85
56
51
Other
NA
NA
NA
NA
NA
Internal Combustion
NA
NA
NA
10
11
FUEL COMB. INDUSTRIAL
770
763
750
670
672
Coal
100
67
58
86
87
Oil
44
49
35
47
46
Gas
462
463
418
257
271
Other
164
184
239
167
173
Internal Combustion
NA
NA
NA
113
96
FUEL COMB. OTHER
3,625
3,441
6,230
7,525
6,450
Commercial/Institutional Coal
12
17
13
14
15
Commercial/Institutional Oil
27
23
21
18
17
Commercial/Institutional Gas
24
25
26
42
49
Misc. Fuel Comb. (Except Residential)NA
NA
NA
57
55
Residential Wood
2,932
3,114
5,992
7,232
6,161
fireplaces
2,932
3,114
5,992
7,232
6,161
woodstoves
NA
NA
NA
NA
NA
other
NA
NA
NA
NA
NA
Residential Other
630
262
178
162
153
Industrial Processes
16,899
10,770
9,250
7,215
7,013
CHEMICAL & ALLIED PRODUCT MFG3.397
2,204
2,151
1,845
1,925
Organic Chemical Mfg
340
483
543
251
285
ethylene dichloride
11
12
17
0
0
maleic anhydride
73
147
103
16
16
cyclohexanol
36
39
37
5
6
other
220
286
386
230
264
Inorganic Chemical Mfg
190
153
191
89
95
pigments; Ti02 chloride proc.: reactor18
22
34
77
84
other
172
131
157
12
12
Polymer & Resin Mfg
NA
NA
NA
19
18
Agricultural Chemical Mfg
NA
NA
NA
16
17
Paint, Varnish, Lacquer, Enamel Mfg NA
NA
NA
NA
NA
Pharmaceutical Mfg
NA
NA
NA
0
0
Other Chemical Mfg
2,866
1,567
1,417
1,471
1,510
carbon black mfg
2,866
1,567
1,417
1,078
1,112
carbon black furnace: fugitives
NA
NA
NA
155
180
other
NA
NA
NA
238
219
METALS PROCESSING
3,644
2,496
2,246
2,223
2,132
Nonferrous Metals Processing
652
636
842
694
677
aluminum anode baking
326
318
421
41
41
prebake aluminum cell
326
318
421
257
254
other
NA
NA
NA
396
382
5,856
6,155
5,586
5,519
5,934
6,206
5,484
5,075
5,322
349
350
363
370
372
409
423
450
445
234
236
246
247
250
251
257
242
239
19
15
16
15
10
12
14
19
18
51
51
49
53
55
79
84
97
94
NA
NA
NA
NA
NA
8
9
33
33
45
47
51
55
58
58
60
60
61
920
955
1,043
1,041
1,056
1,191
1,163
1,151
1,178
101
102
101
100
98
110
109
106
109
60
64
66
66
71
54
52
51
52
284
300
322
337
345
340
339
336
342
267
264
286
287
297
349
333
334
341
208
227
268
251
245
337
330
324
334
4,587
4,849
4,181
4,108
4,506
4,606
3,898
3,474
3,699
14
15
15
15
15
14
14
15
15
17
18
18
18
19
19
20
16
16
44
51
53
54
54
64
65
63
69
141
141
143
147
145
46
48
49
50
4,090
4,332
3,679
3,607
3,999
4,207
3,499
3,089
3,300
4,090
4,332
3,679
3,607
3,999
3,579
2,891
2,518
2,699
NA
NA
NA
NA
NA
304
293
276
290
NA
NA
NA
NA
NA
325
314
296
312
281
292
274
268
273
255
252
242
249
5,740
5,683
5,898
5,839
5,790
4,759
4,932
4,955
7,590
1,127
1,112
1,093
1,171
1,223
1,053
1,071
1,081
1,081
128
131
132
130
127
90
91
92
93
0
0
0
0
0
0
0
0
0
3
4
4
4
4
0
0
0
0
0
0
0
1
1
0
0
0
0
125
127
128
125
123
89
90
92
92
129
130
131
135
134
120
121
123
125
119
119
119
119
119
117
118
120
122
11
12
13
16
15
3
3
3
3
6
5
5
5
5
5
5
5
5
19
19
18
17
17
12
13
13
13
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
844
827
805
885
939
826
841
847
845
756
736
715
793
845
796
811
818
815
54
57
60
63
65
4
4
4
4
35
34
30
30
29
26
26
26
26
2,571
2,496
2,536
2,475
2,380
1,604
1,709
1,702
1,678
438
432
423
421
424
459
475
465
454
47
41
41
41
41
22
23
23
23
260
260
260
260
260
277
288
281
274
131
131
122
120
123
160
164
160
157
5,510
363
234
20
51
NA
57
879
105
74
226
279
195
4,269
14
18
44
149
3,781
3,781
NA
NA
262
5,852
1,183
149
0
3
0
146
133
119
14
3
44
0
0
854
798
17
39
2,640
436
41
260
135
-------
Source Category
1970
1975
1980
1985
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
Ferrous Metals Processing
2,991
1,859
1,404
1,523
1,449
2,163
2,108
2,038
2,089
2,029
1,930
1,101
1,189
1,193
1,181
basic oxygen furnace
440
125
80
694
662
594
731
767
768
677
561
268
296
301
301
carbon steel electric arc furnace
181
204
280
19
18
45
54
49
58
61
65
60
65
66
65
coke oven charging
62
53
43
9
9
14
16
17
7
7
8
4
4
4
4
gray iron cupola
1,203
649
340
302
280
124
118
114
121
128
120
111
115
111
106
iron ore sinter plant windbox
1,025
759
600
304
293
211
211
211
211
211
211
46
50
50
50
other
81
70
61
194
187
1,174
979
880
924
945
966
612
659
661
654
Metals Processing NEC
NA
NA
NA
6
6
40
25
26
25
25
25
44
46
44
43
PETROLEUM & RELATED INDUSTRIES2,179
2,211
1,723
462
436
333
345
371
371
338
348
354
367
366
366
Oil & Gas Production
NA
NA
NA
11
8
38
18
21
22
35
34
27
27
27
27
Petroleum Refineries & Related lnd.2,168
2,211
1,723
449
427
291
324
345
344
299
309
319
332
331
332
fee units
1,820
2,032
1,680
403
390
284
315
333
328
286
299
308
320
319
320
other
348
179
44
46
37
7
9
13
17
13
10
11
12
12
12
Asphalt Manufacturing
11
NA
NA
2
2
3
4
5
5
5
5
8
8
8
1
OTHER INDUSTRIAL PROCESSES
620
630
830
694
716
537
548
544
594
600
624
561
582
590
599
Agriculture, Food, & Kindred Products NA
NA
NA
0
0
3
3
3
3
2
6
4
4
4
4
Textiles, Leather, & Apparel Products NA
NA
NA
0
0
0
0
0
0
0
0
0
0
0
0
Wood, Pulp & Paper, & Pub. Prod.
610
602
798
627
655
473
461
449
453
461
484
356
370
378
388
sulfate pulping: rec. furnace/evaporatorNA
NA
NA
475
497
370
360
348
350
355
370
274
285
291
299
sulfate (kraft) pulping: lime kiln
610
602
798
140
146
87
81
75
78
76
82
50
52
53
55
other
NA
NA
NA
12
13
16
21
25
24
30
32
32
33
34
34
Rubber & Miscellaneous Plastic Prod. NA
NA
NA
0
0
0
0
0
0
0
0
0
0
0
0
Mineral Products
10
27
32
43
43
54
77
85
131
131
127
180
186
186
185
Machinery Products
NA
NA
NA
0
0
0
0
0
0
0
0
1
1
1
1
Electronic Equipment
NA
NA
NA
18
12
2
2
2
2
2
2
0
0
0
0
Transportation Equipment
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
0
0
Miscellaneous Industrial Processes
NA
NA
NA
6
5
5
5
6
4
4
4
19
19
20
20
SOLVENT UTILIZATION
NA
NA
NA
2
2
5
5
5
5
5
6
1
2
2
2
Degreasing
NA
NA
NA
1
1
0
0
0
0
0
0
0
0
0
0
Graphic Arts
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
0
0
Dry Cleaning
NA
NA
NA
NA
NA
0
0
0
0
1
1
0
0
0
0
Surface Coating
NA
NA
NA
0
1
0
1
1
1
1
1
1
1
1
1
Other Industrial
NA
NA
NA
0
0
4
4
4
4
4
4
0
0
0
0
Nonindustrial
NA
NA
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
Solvent Utilization NEC
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
0
0
0
0
STORAGE & TRANSPORT
NA
NA
NA
49
55
76
28
17
51
24
25
70
71
72
72
Bulk Terminals & Plants
NA
NA
NA
0
0
0
2
0
4
4
4
0
0
0
0
Petroleum & Petroleum Prod. Storage NA
NA
NA
0
0
0
12
0
32
4
4
0
0
0
0
Petroleum & Petroleum Prod. Trans
. NA
NA
NA
0
0
0
0
0
0
0
0
0
0
0
0
Service Stations: Stage I
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
0
0
0
0
Service Stations: Stage II
NA
NA
NA
NA
NA
NA
NA
NA
NA
0
0
0
0
0
0
Organic Chemical Storage
NA
NA
NA
42
49
74
13
13
13
13
13
68
69
70
70
Organic Chemical Transport
NA
NA
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
Inorganic Chemical Storage
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
0
0
Bulk Materials Storage
NA
NA
NA
6
5
1
1
3
2
3
3
1
1
1
1
-------
Source Category
1970
1975
1980
1985
1989
1990
WASTE DISPOSAL & RECYCLING
7,059
3,230
2,300
1,941
1,747
1,079
Incineration
2,979
1,764
1,246
958
876
372
conical wood burner
1,431
579
228
17
19
6
municipal incinerator
333
23
13
34
35
16
industrial
NA
NA
NA
9
9
9
commmercial/institutional
108
68
60
32
39
19
residential
1,107
1,094
945
865
773
294
other
NA
NA
NA
2
2
27
Open Burning
4,080
1,466
1,054
982
870
706
industrial
1,932
1,254
1,007
20
21
14
commmercial/institutional
2,148
212
47
4
5
46
residential
NA
NA
NA
958
845
509
other
NA
NA
NA
NA
NA
137
POTW
NA
NA
NA
NA
NA
0
Industrial Waste Water
NA
NA
NA
NA
NA
0
TSDF
NA
NA
NA
NA
NA
0
Landfills
NA
NA
NA
0
0
1
Other
NA
NA
NA
0
0
0
Transportation
100,004
96,243
92,538
93,386
83,829
76,635
ON-ROAD VEHICLES
88,034
83,134
78,049
77,387
66,050
58,444
Light-Duty Gas Vehicles & Motorcycles64,031
59,281
53,561
49,451
42,234
34,996
light-duty gas vehicles
63,846
59,061
53,342
49,273
42,047
34,806
motorcycles
185
220
219
178
187
190
Light-Duty Gas Trucks
16,570
15,767
16,137
18,960
15,940
17,118
light-duty gas trucks 1
10,102
9,611
10,395
11,834
9,034
9,672
light-duty gas trucks 2
6,468
6,156
5,742
7,126
6,906
7,446
Heavy-Duty Gas Vehicles
6,712
7,140
7,189
7,716
6,506
5,029
Diesels
721
945
1,161
1,261
1,369
1,301
heavy-duty diesel vehicles
721
915
1,139
1,235
1,336
1,233
light-duty diesel trucks
NA
NA
4
4
6
46
light-duty diesel vehicles
NA
30
19
22
28
22
NON-ROAD ENGINES AND VEHICLES11,970
13,109
14,489
15,999
17,779
18,191
Non-Road Gasoline
10,946
11,754
12,760
13,659
15,021
15,394
recreational
268
283
299
312
321
355
construction
358
393
527
603
603
603
industrial
535
586
709
807
740
723
lawn & garden
5,899
6,324
6,764
7,166
8,023
8,237
farm
202
267
338
372
407
416
light commercial
1,905
1,997
2,095
2,263
2,754
2,877
logging
10
23
28
31
47
50
airport service
6
8
9
10
10
10
railway maintenance
NA
NA
NA
5
6
6
recreational marine vessels
1,763
1,873
1,990
2,090
2,112
2,117
1991 1992 1993 1994 1995 1996 1997 1998 1999
1,116
1,138
1,248
1,225
1,185
1,116
1,130
1,142
3,792
392
404
497
467
432
403
408
412
416
7
6
6
6
6
2
2
2
2
17
15
14
14
15
7
7
8
8
10
10
87
48
10
9
10
10
10
20
21
21
21
21
22
23
24
24
312
324
340
347
351
330
333
337
339
26
28
29
30
29
32
32
33
33
722
731
749
755
750
706
715
723
3,369
14
15
15
15
15
15
16
16
0
48
50
52
54
52
84
88
90
0
516
523
529
533
536
506
510
515
422
144
144
153
153
147
101
101
102
2,947
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
2
2
2
2
6
6
6
6
0
0
1
1
1
0
0
0
0
81,583
80,235
81,224
82,699
75,035
79,795
78,509
77,478
75,151
62,999
61,236
61,833
62,903
54,811
54,388
53,315
52,360
49,989
35,680
33,761
33,185
33,317
29,787
29,163
28,639
28,420
27,382
35,503
33,582
32,995
33,122
29,601
28,974
28,449
28,225
27,187
177
179
190
195
187
189
191
195
195
20,622
21,536
22,795
22,614
19,434
16,873
16,949
16,948
16,115
11,606
12,065
12,647
12,428
11,029
11,221
11,296
11,315
10,766
9,016
9,471
10,148
10,186
8,405
5,652
5,652
5,634
5,349
5,369
4,586
4,483
5,523
4,103
6,260
5,549
4,782
4,262
1,327
1,353
1,370
1,449
1,487
2,093
2,178
2,210
2,230
1,292
1,317
1,333
1,411
1,447
2,074
2,162
2,197
2,217
8
9
10
10
10
7
6
5
5
27
27
28
29
29
12
10
8
8
18,585
18,999
19,391
19,796
20,224
25,407
25,194
25,118
25,162
15,738
16,081
16,424
16,765
17,112
22,012
21,773
21,657
21,717
361
366
371
374
382
1,376
1,359
1,355
1,357
602
602
602
602
602
723
688
674
667
707
690
674
657
640
864
823
793
767
8,451
8,665
8,880
9,094
9,308
11,330
11,243
11,073
11,063
424
433
442
450
459
340
343
346
349
3,000
3,123
3,246
3,369
3,491
3,992
4,061
4,138
4,187
54
58
62
66
69
1,160
1,012
1,016
1,067
10
9
9
9
9
9
9
9
9
6
6
6
6
7
7
7
7
6
2,122
2,128
2,133
2,138
2,144
2,211
2,228
2,244
2,247
-------
Source Category
1970
1975
1980
1985
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
Non-Road Diesel
430
650
829
900
1,062
1,098
1,134
1,169
1,204
1,238
1,269
1,386
1,377
1,352
1,302
recreational
1
2
2
3
3
3
3
3
3
3
3
5
5
5
5
construction
254
362
479
534
637
662
688
714
739
763
785
878
869
846
802
industrial
88
69
83
105
121
124
127
130
134
138
142
149
151
151
151
lawn & garden
6
12
13
14
26
29
32
34
37
39
42
47
50
53
53
farm
16
138
174
142
163
166
168
170
172
174
175
165
163
161
156
light commercial
20
27
28
34
44
46
48
49
51
52
54
62
64
67
72
logging
43
38
49
61
58
58
58
57
57
56
55
63
58
52
46
airport service
1
1
1
2
3
4
4
5
5
5
6
7
7
8
8
railway maintenance
UA
UA
UA
1
2
2
2
2
2
3
3
3
3
3
3
recreational marine vessels
UA
UA
UA
3
4
4
4
4
4
4
5
7
7
7
7
Aircraft
506
600
743
831
955
904
888
901
905
915
942
949
958
995
1,002
Marine Vessels
23
28
62
73
98
129
136
132
126
127
127
132
135
137
138
coal
2
2
4
5
7
4
4
4
4
5
4
4
4
4
5
diesel
21
25
57
67
90
80
83
79
75
76
77
127
129
130
131
residual oil
0
0
1
1
2
11
11
12
12
12
10
0
0
0
0
gasoline
NA
NA
NA
NA
NA
2
2
2
2
2
2
2
2
2
2
other
NA
NA
NA
NA
NA
31
36
35
33
33
34
0
0
0
0
Railroads
65
77
96
106
121
121
120
125
120
114
114
117
121
120
119
Non-Road Other
0
0
0
430
522
545
568
591
614
637
660
810
831
858
883
liquified petroleum gas
NA
NA
NA
288
376
398
420
442
464
486
508
704
724
749
773
compressed natural gas
NA
NA
NA
142
146
147
148
149
150
151
152
106
108
109
111
Miscellaneous
7,909
5,263
8,344
7,927
8,153
11,122
8,618
6,934
7,082
9,656
7,298
10,534
12,534
9,364
9,378
Agriculture & Forestry
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
0
0
0
0
Other Combustion
7,909
5,263
8,344
7,927
8,153
11,122
8,618
6,934
7,082
9,656
7,298
10,534
12,534
9,364
9,378
structural fires
101
258
217
242
242
78
80
81
82
83
84
80
78
79
85
agricultural fires
873
539
501
396
571
415
413
421
415
441
465
454
464
471
479
slash/prescribed burning
1,146
2,268
2,226
4,332
4,332
4,668
4,666
4,729
4,966
4,990
5,252
5,402
5,769
6,152
6,152
forest wildfires
5,620
2,165
5,396
2,957
3,009
5,928
3,430
1,674
1,586
4,114
1,469
4,574
6,200
2,638
2,638
other
169
34
4
NA
NA
32
28
30
34
28
28
22
23
23
24
Health Services
NA
NA
NA
NA
NA
0
NA
NA
NA
NA
NA
0
0
0
0
Cooling Towers
NA
NA
NA
NA
NA
NA
0
0
NA
0
0
0
0
0
0
Fugitive Dust
NA
NA
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
TOTAL ALL SOURCES
129,444
116,757
117,434
117,013
106,439
99,119
101,797
99,007
99,791
103,713
94,058
101,294
101,459
96,872
97,441
Note: Some columns may not sum to totals due to rounding.
-------
Source Category
1970
1975
1980
1985
1989
1990
Fuel Combustion
10,616
10,347
4,299
515
505
500
FUEL COMB. ELEC. UTIL.
327
230
129
64
67
64
Coal
300
189
95
51
46
46
bituminous
181
114
57
31
28
28
subbituminous
89
56
28
15
14
14
anthracite & lignite
30
19
9
5
4
4
Oil
28
41
34
13
21
18
residual
27
40
34
13
21
18
distillate
0
1
0
0
0
0
FUEL COMB. INDUSTRIAL
237
75
60
30
18
18
Coal
218
60
45
22
14
14
bituminous
146
40
31
15
10
10
subbituminous
45
12
10
5
3
3
anthracite & lignite
27
7
4
2
1
1
Oil
19
16
14
8
4
3
residual
17
14
14
7
3
3
distillate
1
1
1
1
1
1
FUEL COMB. OTHER
10,052
10,042
4,111
421
420
418
Commercial/Institutional Coal
1
16
12
6
4
4
bituminous
1
6
6
4
3
3
subbituminous
NA
2
2
1
1
1
anthracite, lignite
NA
7
4
1
1
0
Commercial/Institutional Oil
4
11
10
4
4
4
residual
3
10
9
3
3
3
distillate
NA
1
1
1
1
1
other
1
NA
NA
NA
NA
NA
Misc. Fuel Comb. (Except Residential)!0,000
10,000
4,080
400
400
400
Residential Other
47
16
9
11
12
10
Inustrial Processes
28,554
12,976
5,148
3,402
3,161
3,278
CHEMICAL & ALLIED PRODUCT MFG 103
120
104
118
136
136
Inorganic Chemical Mfg
103
120
104
118
136
136
lead oxide and pigments
103
120
104
118
136
136
METALS PROCESSING
24,224
9,923
3,026
2,097
2,088
2,170
Nonferrous Metals Processing
15,869
7,192
1,826
1,376
1,337
1,409
primary lead production
12,134
5,640
1,075
874
715
728
primary copper production
242
171
20
19
19
19
primary zinc production
1,019
224
24
16
9
9
secondary lead production
1,894
821
481
288
433
449
secondary copper production
374
200
116
70
37
75
lead battery manufacture
41
49
50
65
74
78
lead cable coating
127
55
37
43
50
50
other
38
32
24
3
1
1
1991 1992 1993 1994 1995 1996 1997 1998 1999
495
491
497
496
490
492
493
494
501
61
59
62
62
57
61
64
69
72
46
47
50
50
50
53
54
55
56
28
28
30
30
30
32
33
33
34
14
14
15
15
15
16
16
16
17
4
4
5
5
5
5
5
5
5
15
12
12
12
1
8
10
14
16
15
12
12
12
7
8
10
14
16
0
0
0
0
0
0
0
0
0
18
18
19
19
18
16
16
15
17
15
14
14
14
14
13
14
13
13
10
10
10
10
10
9
9
9
9
3
3
3
3
3
3
3
3
3
1
1
1
1
1
1
1
1
1
3
4
5
5
4
3
2
2
3
2
3
4
4
3
2
2
1
3
1
1
1
1
1
1
1
1
1
416
414
416
415
415
415
413
410
412
3
4
4
3
4
5
5
4
4
2
2
2
2
2
3
3
2
2
1
1
1
1
1
1
1
1
1
0
0
1
0
1
1
1
1
1
4
4
4
4
3
3
2
2
3
3
3
3
3
2
2
2
1
3
1
1
1
1
1
1
1
1
1
NA
NA
NA
NA
NA
NA
0
0
0
400
400
400
400
400
400
400
400
400
9
7
8
8
8
7
6
5
5
3,081
2,736
2,872
3,007
2,875
3,061
3,121
3,045
3,162
132
93
92
96
163
167
188
194
218
132
93
92
96
163
167
188
194
218
132
93
92
96
163
167
188
194
218
1,974
1,774
1,900
2,027
2,049
2,055
2,081
1,991
2,078
1,258
1,112
1,210
1,287
1,337
1,333
1,342
1,259
1,329
623
550
637
633
674
588
619
608
623
19
20
21
22
21
22
24
25
25
11
11
13
12
12
13
13
12
12
414
336
341
405
432
514
484
413
465
65
73
70
76
79
76
82
78
81
77
77
81
94
102
103
107
110
117
48
44
47
44
16
16
14
13
4
1
1
1
1
1
1
1
1
1
-------
Source Category
1970
1975
1980
1985
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
Ferrous Metals Processing
7,395
2,196
911
577
582
576
517
461
496
540
528
529
538
536
555
coke manufacturing
11
8
6
3
4
4
3
3
2
0
0
0
0
0
0
ferroalloy production
219
104
13
7
20
18
14
14
12
13
8
8
8
7
6
iron production
266
93
38
21
19
18
16
17
18
18
19
18
18
18
18
steel production
3,125
1,082
481
209
138
138
145
139
145
160
159
160
165
168
173
gray iron production
3,773
910
373
336
401
397
339
288
319
349
342
343
348
343
357
Metals Processing NEC
960
535
289
144
170
185
199
202
194
200
184
193
201
196
195
metal mining
353
268
207
141
169
184
198
201
193
199
183
192
200
195
194
other
606
268
82
3
1
1
1
1
1
1
1
1
1
1
1
OTHER INDUSTRIAL PROCESSES
2,028
1,337
808
316
173
169
167
56
55
54
59
51
54
54
53
Mineral Products
540
217
93
43
23
26
24
26
27
28
29
29
30
30
31
cement manufacturing
540
217
93
43
23
26
24
26
27
28
29
29
30
30
31
Miscellaneous Industrial Processes 1,488
1,120
715
273
150
143
143
30
28
26
30
22
25
23
22
WASTE DISPOSAL & RECYCLING
2,200
1,595
1,210
871
765
804
808
812
825
830
604
788
798
806
813
Incineration
2,200
1,595
1,210
871
765
804
808
812
825
830
604
788
798
806
813
municipal wasfe
581
396
161
79
45
67
70
68
69
68
70
76
76
76
77
other
1,619
1,199
1,049
792
720
738
738
744
756
762
534
712
722
729
736
Transportation
181,698
136,336
64,706
18,973
1,802
1,197
592
584
547
544
564
525
523
518
536
ON-ROAD VEHICLES
171,961
130,206
60,501
18,052
982
421
18
18
19
19
19
19
20
21
22
Light-Duty Gas Vehicles & Motorcycles142,918 106,868
47,184
13,637
733
314
13
14
14
14
14
12
13
14
14
Light-Duty Gas Trucks
22,683
19,440
11,671
4,061
232
100
4
4
5
5
5
7
7
7
7
Heavy-Duty Gas Vehicles
6,361
3,898
1,646
354
16
7
0
0
0
0
0
0
0
1
1
NON-ROAD ENGINES AND VEHICLES9J37
6,130
4,205
921
820
776
574
565
529
525
544
505
503
497
515
Non-Road Gasoline
8,340
5,012
3,320
229
166
158
0
0
0
0
0
0
0
0
0
Aircraft
1,397
1,118
885
692
655
619
574
565
528
525
544
505
503
497
515
TOTAL ALL SOURCES
220,869
159,659
74,153
22,890
5,468
4,975
4,169
3,810
3,916
4,047
3,929
4,077
4,137
4,057
4,199
Note: Some columns may not sum to totals due to rounding.
-------
Source Category
1970
1975
1980
1985
1989
1990
Fuel Combustion
10,061
10,486
11,320
10,048
10,537
10,895
FUEL COMB. ELEC. UTIL.
4,900
5,694
7,024
6,127
6,593
6,663
Coal
3,888
4,828
6,123
5,240
5,676
5,642
bituminous
2,112
2,590
3,439
4,378
4,595
4,532
subbituminous
1,041
1,276
1,694
668
837
857
anthracite & lignite
344
414
542
194
245
254
other
391
548
447
NA
NA
NA
Oil
1,012
866
901
193
285
221
residual
40
101
39
178
268
207
distillate
972
765
862
15
17
14
other
NA
NA
NA
NA
NA
0
Gas
NA
NA
NA
646
582
565
natural
NA
NA
NA
646
582
565
process
NA
NA
NA
NA
NA
NA
Other
NA
NA
NA
NA
NA
NA
Internal Combustion
NA
NA
NA
48
49
235
FUEL COMB. INDUSTRIAL
4,325
4,007
3,555
3,209
3,209
3,035
Coal
771
520
444
608
615
585
bituminous
532
359
306
430
446
399
subbituminous
164
111
94
14
14
18
anthracite & lignite
75
51
44
33
30
26
other
NA
NA
NA
131
124
141
Oil
332
354
286
309
294
265
residual
228
186
179
191
176
180
distillate
104
112
63
89
88
71
other
NA
56
44
29
29
14
Gas
3,060
2,983
2,619
1,520
1,625
1,182
natural
3,053
2,837
2,469
1,282
1,405
967
process
8
5
5
227
209
211
other
NA
140
145
11
10
3
Other
162
149
205
118
120
131
wood/bark wasfe
102
108
138
89
92
89
liquid wasfe
NA
NA
NA
12
12
8
other
60
41
67
17
16
34
Internal Combustion
NA
NA
NA
655
556
874
FUEL COMB. OTHER
836
785
741
712
736
1,196
Commercial/Institutional Coal
23
33
25
37
38
40
Commercial/Institutional Oil
210
176
155
106
106
97
Commercial/Institutional Gas
120
125
131
145
159
200
Misc. Fuel Comb. (Except Residential)NA
NA
NA
11
11
34
Residential Wood
44
39
74
88
75
46
Residential Other
439
412
356
326
347
780
distillate oil
118
113
85
75
78
209
natural gas
242
246
238
248
267
449
other
79
54
33
3
3
121
1991
1992
1993
1994
1995
1996
1997
1998
1999
10,779
10,928
11,111
11,015
10,827
10,523
10,576
10,396
10,026
6,519
6,504
6,651
6,565
6,384
6,141
6,279
6,231
5,715
5,559
5,579
5,744
5,636
5,579
5,574
5,644
5,436
4,935
4,435
4,456
4,403
4,207
3,830
3,776
3,828
3,635
3,229
874
868
1,087
1,167
1,475
1,570
1,591
1,575
1,504
250
255
255
262
273
229
225
226
202
NA
NA
NA
NA
NA
0
0
0
0
212
170
180
163
96
118
145
223
202
198
158
166
149
94
116
142
220
199
14
13
14
14
2
2
2
3
3
NA
NA
NA
NA
NA
0
0
0
0
580
579
551
591
562
285
319
381
385
580
579
551
591
562
273
306
363
367
NA
NA
NA
NA
NA
12
13
19
18
NA
NA
NA
NA
NA
6
7
27
26
168
175
176
175
148
158
165
164
167
2,979
3,071
3,151
3,147
3,144
3,157
3,102
3,051
3,136
570
574
589
602
597
543
537
524
542
387
405
413
420
412
369
364
357
370
20
21
28
38
46
46
46
44
46
26
26
26
27
26
19
19
18
18
137
122
122
117
112
109
108
105
108
237
244
245
241
247
225
216
209
214
146
154
153
149
156
141
130
126
129
73
73
75
76
73
73
74
72
73
18
17
17
17
17
11
12
11
11
1,250
1,301
1,330
1,333
1,324
1,205
1,189
1,175
1,202
1,025
1,068
1,095
1,103
1,102
993
970
958
985
222
230
233
228
220
210
216
215
214
3
3
2
2
2
3
3
3
3
129
126
124
124
123
120
115
115
118
82
82
83
83
84
83
79
80
82
11
10
11
11
11
9
8
8
8
36
34
30
30
28
29
28
27
28
793
825
863
846
854
1,064
1,045
1,028
1,059
1,281
1,353
1,308
1,303
1,298
1,225
1,195
1,114
1,175
36
38
40
40
38
34
35
37
37
88
93
93
95
103
96
97
80
80
210
225
232
237
231
247
252
243
266
32
28
31
31
30
27
28
29
28
50
53
45
44
49
51
43
38
40
865
916
867
857
847
770
740
688
723
211
210
210
210
210
193
188
172
175
469
489
513
516
519
470
437
400
433
185
218
144
131
118
108
114
117
116
2
CD
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it
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D
Q)
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D
o
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m
3
w
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o'
m
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CD
i i
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(/)
CD
O
CD
cn
CD
00
O
CD
00
cn
CD
00
CD
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CD
CD
CD
O
c
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IT
0
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i i
o
D
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§
o
Z
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>
73
O
C
>
H
>
Z
D
m
n
w
to
O
z
to
H
73
m
z
D
to
73
m
¦0
o
73
-------
Source Category 1970
1975
1980
1985
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
Industrial Processes 1,215
697
666
891
852
892
816
857
861
878
873
903
939
950
942
CHEMICAL & ALLIED PRODUCT MFG
271
221
213
262
273
168
165
163
155
160
158
125
127
129
131
Organic Chemical Mfg
70
53
54
37
42
18
22
22
19
20
20
21
21
21
21
Inorganic Chemical Mfg
201
168
159
22
18
12
12
10
5
6
7
6
6
6
6
Polymer & Resin Mfg
NA
NA
NA
22
23
6
6
6
5
5
4
3
3
3
3
Agricultural Chemical Mfg
NA
NA
NA
143
152
80
77
76
74
76
74
50
51
52
53
Paint, Varnish, Lacquer, Enamel Mfg
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
0
0
Pharmaceutical Mfg
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
0
0
Other Chemical Mfg
NA
NA
NA
38
39
52
48
50
51
54
54
45
46
47
47
METALS PROCESSING
77
73
65
87
83
97
76
81
83
91
98
83
88
88
88
Nonferrous Metals Processing
NA
NA
NA
16
15
14
15
13
12
12
12
11
12
12
12
Ferrous Metals Processing
77
73
65
58
54
78
56
62
67
75
83
66
71
71
70
Metals Processing NEC
NA
NA
NA
13
14
6
5
6
4
4
4
6
6
6
6
PETROLEUM & RELATED INDUSTRIES 240
63
72
124
97
153
121
148
123
117
110
139
143
143
143
Oil & Gas Production
NA
NA
NA
69
47
104
65
68
70
63
58
86
88
88
88
Petroleum Refineries & Related Ind.
240
63
72
55
49
47
52
76
49
49
48
47
48
48
48
Asphalt Manufacturing
NA
NA
NA
1
1
3
4
4
5
5
5
7
7
7
7
OTHER INDUSTRIAL PROCESSES
187
182
205
327
311
378
352
361
370
389
399
438
460
467
470
Agriculture, Food, & Kindred Products NA
NA
NA
5
5
3
3
3
4
3
6
5
5
5
5
Textiles, Leather, & Apparel Products
NA
NA
NA
0
0
0
0
0
0
0
0
1
1
1
1
Wood, Pulp & Paper, & Pub. Prod.
18
18
24
73
77
91
88
86
86
89
89
86
89
91
93
Rubber & Miscellaneous Plastic Prod
. NA
NA
NA
0
0
0
0
0
0
0
0
0
0
0
0
Mineral Products
169
164
181
239
220
270
249
259
267
281
287
331
350
355
356
cement mfg
97
89
98
137
124
151
131
139
143
150
153
200
212
214
213
glass mfg
48
53
60
48
45
59
59
61
64
66
67
69
74
76
78
other
24
23
23
54
51
61
59
60
60
64
66
62
64
65
65
Machinery Products
NA
NA
NA
2
2
3
2
2
3
6
7
2
3
3
3
Electronic Equipment
NA
NA
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
Transportation Equipment
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
0
0
Miscellaneous Industrial Processes
NA
NA
NA
8
7
10
10
10
9
9
10
12
12
12
12
SOLVENT UTILIZATION
NA
NA
NA
2
3
1
2
3
3
3
3
2
3
3
3
Degreasing
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
0
0
Graphic Arts
NA
NA
NA
0
0
0
1
1
1
1
1
1
1
1
1
Dry Cleaning
NA
NA
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
Surface Coating
NA
NA
NA
2
2
1
2
2
2
2
2
2
2
2
2
Other Industrial
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
0
0
Nonindustrial
NA
NA
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
Solvent Utilization NEC
NA
NA
NA
NA
NA
NA
NA
NA
NA
0
0
0
0
0
0
STORAGE & TRANSPORT
NA
NA
NA
2
2
3
6
5
5
5
6
15
16
16
16
Bulk Terminals & Plants
NA
NA
NA
NA
NA
0
1
1
1
1
1
2
2
2
2
Petroleum & Petroleum Prod. Storage NA
NA
NA
1
1
2
2
0
0
0
0
7
8
8
8
Petroleum & Petroleum Prod. Trans.
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
0
0
Service Stations: Stage I
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
0
0
0
0
Service Stations: Stage II
NA
NA
NA
NA
NA
NA
NA
NA
NA
0
0
0
0
0
0
Organic Chemical Storage
NA
NA
NA
1
1
0
2
3
3
3
4
4
4
4
4
Organic Chemical Transport
NA
NA
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
Inorganic Chemical Storage
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
0
0
Bulk Materials Storage
NA
NA
NA
0
1
0
0
0
0
0
1
2
2
2
2
-------
Source Category
1970
1975
1980
1985
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
WASTE DISPOSAL & RECYCLING
440
159
111
87
84
91
95
96
123
114
99
101
102
104
91
Incineration
110
56
37
27
31
49
51
51
74
65
53
56
56
57
58
Open Burning
330
103
74
59
52
42
43
43
44
44
44
42
42
43
30
POTW
NA
NA
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
Industrial Waste Water
NA
NA
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
TSDF
NA
NA
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
Landfills
NA
NA
NA
0
0
0
0
1
1
1
1
2
2
2
2
Other
NA
NA
NA
0
0
0
1
1
4
3
1
1
1
1
1
Transportation
9,322
11,284
12,150
11,948
12,210
12,014
12,457
12,692
12,902
13,191
13,085
14,211
14,436
14,355
14,105
ON-ROAD VEHICLES
7,390
8,645
8,621
8,089
7,682
7,210
7,557
7,759
7,960
8,176
7,956
8,793
8,924
8,816
8,590
Light-Duty Gas Vehicles & Motorcycles4,158
4,725
4,421
3,806
3,494
3,013
3,069
3,098
3,117
3,173
3,043
3,006
2,996
2,933
2,859
light-duty gas vehicles
4,156
4,722
4,416
3,797
3,483
3,002
3,058
3,086
3,105
3,161
3,031
2,994
2,983
2,920
2,846
motorcycles
2
3
5
9
11
11
11
12
12
13
12
12
12
12
13
Light-Duty Gas Trucks
1,278
1,461
1,408
1,530
1,386
1,552
1,839
2,004
2,131
2,160
1,991
1,709
1,742
1,703
1,638
light-duty gas trucks 1
725
819
864
926
803
901
1,074
1,171
1,242
1,251
1,183
1,166
1,185
1,157
1,110
light-duty gas trucks 2
553
642
544
603
584
651
766
833
888
909
809
543
557
546
529
Heavy-Duty Gas Vehicles
278
319
300
330
343
306
321
309
316
351
330
518
505
467
459
Diesels
1,676
2,141
2,493
2,423
2,458
2,340
2,328
2,347
2,397
2,492
2,591
3,560
3,680
3,713
3,635
heavy-duty diesel vehicles
1,676
2,118
2,463
2,389
2,416
2,248
2,284
2,302
2,351
2,446
2,544
3,538
3,662
3,698
3,620
light-duty diesel trucks
NA
NA
5
6
7
63
11
11
12
12
13
8
7
6
6
light-duty diesel vehicles
NA
23
25
28
35
28
33
33
33
34
34
14
11
9
8
NON-ROAD ENGINES AND VEHICLES1,931
2,638
3,529
3,859
4,528
4,804
4,900
4,934
4,942
5,015
5,128
5,418
5,512
5,539
5,515
Non-Road Gasoline
85
92
101
108
114
120
121
123
124
126
127
142
160
176
187
recreational
1
1
1
1
1
6
6
6
6
6
6
7
8
8
8
construction
2
3
4
4
4
4
4
4
4
4
4
4
5
6
6
industrial
10
10
13
14
13
12
12
12
11
11
11
14
14
14
13
lawn & garden
26
28
29
31
35
36
37
38
39
40
41
51
61
71
78
farm
3
3
5
5
5
6
6
6
6
6
6
4
4
4
4
light commercial
10
10
11
12
14
15
16
16
17
18
18
22
27
31
34
logging
0
0
0
0
0
0
0
0
0
0
0
3
4
5
5
airport service
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
railway maintenance
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
0
0
recreational marine vessels
34
36
38
40
41
41
41
41
41
41
41
37
37
37
37
Non-Road Diesel
1,109
1,666
2,125
2,155
2,472
2,513
2,552
2,595
2,640
2,687
2,739
2,746
2,760
2,751
2,707
recreational
0
2
2
2
3
3
3
3
3
3
3
5
5
5
5
construction
436
639
843
943
1,083
1,102
1,120
1,138
1,156
1,174
1,198
1,267
1,273
1,267
1,247
industrial
217
160
193
244
270
268
265
265
268
270
274
240
242
241
237
lawn & garden
9
18
19
22
40
45
50
54
59
64
69
70
76
81
83
farm
350
728
926
755
877
898
917
936
953
970
987
935
934
926
906
light commercial
31
43
44
54
72
77
82
87
91
96
101
109
114
119
123
logging
65
74
94
118
101
94
88
82
79
77
75
79
73
67
61
airport service
2
2
2
3
6
7
7
8
8
9
9
10
10
10
10
railway maintenance
UA
UA
UA
2
3
3
4
4
4
4
4
4
4
4
4
recreational marine vessels
UA
UA
UA
13
16
17
17
18
19
19
20
28
29
30
31
Aircraft
72
85
106
119
138
158
155
156
156
161
165
167
168
174
175
-------
Source Category
1970
1975
1980
1985
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
Marine Vessels
171
207
467
557
747
943
995
961
917
929
936
970
985
996
1,007
coal
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
diesel
144
175
396
469
628
630
649
621
593
604
615
960
974
984
995
residual oil
26
31
71
87
118
114
115
116
114
115
105
0
0
0
0
gasoline
NA
NA
NA
NA
NA
10
10
9
9
9
10
10
10
11
12
other
NA
NA
NA
NA
NA
190
221
214
201
201
206
0
0
0
0
Railroads
495
589
731
808
923
929
929
946
945
947
990
1,183
1,222
1,215
1,204
Non-Road Other
0
0
0
112
135
141
147
153
159
165
171
210
218
227
235
liquified petroleum gas
NA
NA
NA
75
98
103
109
115
120
126
132
183
190
199
206
compressed natural gas
NA
NA
NA
37
38
38
38
39
39
39
39
27
28
28
29
Miscellaneous
330
165
248
310
293
369
286
255
241
390
267
416
402
319
320
Agriculture and Forestry
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
0
0
0
0
agricultural livestock
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
0
0
0
0
Other Combustion
330
165
248
310
293
368
285
253
240
388
265
416
402
319
320
Health Services
NA
NA
NA
NA
NA
NA
NA
0
0
0
0
0
0
0
0
Cooling Towers
NA
NA
NA
NA
NA
NA
NA
0
NA
0
0
0
0
0
0
Fugitive Dust
NA
NA
NA
NA
NA
1
1
1
1
1
1
0
0
0
0
TOTAL ALL SOURCES
20,928
22,632
24,384
23,198
23,893
24,170
24,338
24,732
25,116
25,474
25,051
26,053
26,352
26,020
25,393
Note: Some columns may not sum to totals due to rounding.
-------
Source Category 1970 1975 1980 1985 1989 1990
Fuel Combustion
722
660
1,050
1,570
1,372
1,005
FUEL COMB. ELEC. UTIL.
30
40
45
32
37
47
Coal
18
22
31
24
27
27
Oil
7
14
9
5
7
6
Gas
5
4
5
2
2
2
Other
NA
NA
NA
NA
NA
NA
Internal Combustion
NA
NA
NA
1
1
12
FUEL COMB. INDUSTRIAL
150
150
157
134
134
182
Coal
4
3
3
7
1
1
Oil
4
5
3
17
16
12
Gas
77
71
62
57
61
58
Other
65
71
89
35
36
51
Internal Combustion
NA
NA
NA
18
15
54
FUEL COMB. OTHER
541
470
848
1,403
1,200
776
Commercial/Institutional Coal
1
1
1
1
1
1
Commercial/Institutional Oil
4
3
3
4
4
3
Commercial/Institutional Gas
6
7
7
6
7
8
Misc. Fuel Comb. (Except Residential) NA
NA
NA
4
4
8
Residential Wood
460
420
809
1,372
1,169
718
fireplaces
460
420
809
1,372
1,169
718
woodstoves
NA
NA
NA
NA
NA
NA
other
NA
NA
NA
NA
NA
NA
Residential Other
70
38
28
16
15
38
Inudstrial Processes
14,310
12,081
12,861
10,474
10,755
10,000
CHEMICAL & ALLIED PRODUCT MFG 1,341
1,351
1,595
881
980
634
Organic Chemical Mfg
629
751
884
349
387
192
ethylene oxide mfg
8
9
10
2
2
0
phenol mfg
NA
NA
NA
0
0
4
terephthalic acid mfg
29
46
60
24
27
20
ethylene mfg
70
79
111
28
33
9
charcoal mfg
48
29
40
37
45
33
socmi reactor
81
96
118
43
49
26
socmi distillation
NA
NA
NA
7
7
8
socmi air oxidation processes
NA
NA
NA
0
1
2
socmi fugitives
194
235
254
179
193
61
other
199
257
291
27
30
29
Inorganic Chemical Mfg
65
78
93
3
3
2
Polymer & Resin Mfg
271
299
384
343
389
242
polypropylene mfg
0
0
1
12
13
2
polyethylene mfg
17
18
22
51
57
39
polystyrene resins
10
11
15
6
7
4
synthetic fiber
112
149
199
217
250
144
styrene/butadiene rubber
77
68
70
45
50
15
other
55
54
77
12
13
37
Agricultural Chemical Mfg
NA
NA
NA
11
12
6
1991 1992 1993 1994 1995 1996 1997 1998 1999
1,075
1,114
993
989
44
44
45
45
27
27
29
29
5
4
4
4
2
2
2
2
NA
NA
NA
NA
10
10
10
10
196
187
186
196
6
1
6
8
11
12
12
12
60
52
51
63
51
49
51
50
68
66
66
64
835
884
762
748
1
1
1
1
3
3
3
3
8
10
11
11
8
8
9
9
776
822
698
684
776
822
698
684
NA
NA
NA
NA
NA
NA
NA
NA
39
40
40
40
10,178
10,380
10,578
10,738
710
715
701
691
216
211
215
217
1
1
1
1
4
4
4
4
23
17
19
21
11
10
10
9
33
33
33
34
30
30
32
33
9
8
8
8
2
2
2
2
67
69
70
70
38
37
36
35
3
3
2
2
268
283
269
257
2
2
2
2
44
45
46
46
5
5
5
5
161
173
157
143
15
16
17
18
41
42
42
43
7
8
7
6
1,072 935 858 904
50
52
56
56
28
29
29
29
3
4
5
5
8
8
10
9
0
0
1
1
10
11
11
11
179
175
174
178
7
7
7
1
9
8
8
8
59
59
59
60
35
34
34
35
69
68
67
69
843
708
628
670
1
1
1
1
3
3
3
3
14
14
13
15
9
9
9
10
779
645
569
608
680
549
478
512
41
39
37
39
59
57
54
57
36
35
33
34
0
8,761
8,304
7,996
387
388
394
395
131
133
136
138
0
0
0
0
2
2
2
2
11
11
11
11
5
5
5
5
30
31
31
32
27
28
28
29
4
4
4
4
1
1
1
1
40
41
42
42
12
12
12
12
3
3
3
3
128
124
126
124
2
2
2
2
16
17
17
17
5
3
3
3
78
80
82
83
11
7
7
7
16
16
16
13
8 8 8 8
1,073
44
29
3
2
NA
10
206
6
12
73
50
65
823
1
3
11
8
759
759
NA
NA
41
10,780
660
210
1
2
17
10
33
33
8
2
70
34
3
222
2
35
5
142
16
22
5
-------
Source Category 1970
1975
1980
1985
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
Paint, Varnish, Lacquer, Enamel Mfg
61
66
65
8
8
14
16
17
18
17
18
7
8
8
8
paint & varnish mfg
61
66
65
8
8
13
15
16
16
16
16
6
6
6
6
other
NA
NA
NA
0
0
1
1
1
1
1
2
2
2
2
2
Pharmaceutical Mfg
40
55
77
43
48
20
21
24
23
24
38
7
7
7
8
Other Chemical Mfg
275
102
92
125
132
158
179
169
166
168
164
104
105
106
107
carbon black mfg
275
102
92
26
26
9
17
16
16
21
24
27
28
28
28
printing ink mfg
NA
NA
NA
2
3
1
1
1
1
2
2
1
1
1
1
fugitives unclassified
NA
NA
NA
12
12
23
23
21
20
27
30
13
13
13
13
carbon black furnace: fugitives
NA
NA
NA
4
5
0
1
1
1
1
1
0
0
0
0
other
NA
NA
NA
81
87
125
136
129
127
117
107
63
64
64
65
METALS PROCESSING
394
336
273
76
74
122
123
124
124
126
125
73
78
78
77
Nonferrous Metals Processing
NA
NA
NA
18
19
18
19
17
18
20
21
19
20
20
20
Ferrous Metals Processing
394
336
273
57
54
98
99
100
98
97
96
44
47
47
46
coke oven door & topside leaks
216
187
152
12
12
19
22
27
27
26
26
5
6
6
6
coke oven by-product plants
NA
NA
NA
3
3
7
9
9
9
9
9
5
5
5
5
other
177
149
121
41
39
71
68
63
62
62
61
35
37
36
36
Metals Processing NEC
NA
NA
NA
1
1
7
6
8
8
8
8
10
11
11
10
PETROLEUM & RELATED INDUSTRIES1,194
1,342
1,440
703
639
612
640
632
649
647
642
477
487
485
424
Oil & Gas Production
411
378
379
107
68
301
301
297
310
305
299
271
274
272
271
Petroleum Refineries & Related Ind.
773
951
1,045
592
568
308
337
332
336
339
339
201
208
208
149
vaccuum distillation
24
31
32
15
13
7
7
7
7
7
6
3
3
3
3
cracking units
27
27
21
34
31
15
17
16
15
16
16
16
16
16
16_
process unit turnarounds
NA
NA
NA
15
13
11
11
11
11
10
12
2
2
2
28
petroleum refinery fugitives
NA
NA
NA
76
65
99
105
103
109
109
111
84
87
86
27 |
other
721
893
992
454
446
177
196
195
194
198
194
97
101
101
101 5
4-5
Asphalt Manufacturing
11
13
16
3
3
3
3
3
3
3
4
5
5
5
OTHER INDUSTRIAL PROCESSES
270
235
237
390
403
401
391
414
442
438
450
422
438
443
449
Agriculture, Food, & Kindred Products
208
182
191
169
175
138
130
127
146
145
147
104
108
109
111
vegetable oil mfg
59
61
81
46
49
16
18
19
19
16
16
1
1
1
1
whiskey fermentation: aging
105
77
64
24
23
24
16
12
24
24
25
15
16
16
16
bakeries
45
44
46
51
51
43
44
44
46
46
47
41
42
42
43
other
NA
NA
NA
49
52
55
52
51
58
58
60
47
49
50
51
Textiles, Leather, & Apparel Products
NA
NA
NA
10
10
20
18
19
19
19
19
10
10
10
10
Wood, Pulp & Paper, & Publishing Prod.NA
NA
NA
42
44
96
92
101
112
105
122
154
160
164
167
Rubber & Miscellaneous Plastic Prod.
60
51
44
41
46
58
59
64
62
61
60
49
51
52
52
rubber tire mfg
60
51
44
10
11
5
5
5
5
6
6
6
6
6
6
green tire spray
NA
NA
NA
5
6
3
4
3
3
3
3
2
2
2
2
other
NA
NA
NA
26
29
50
50
55
53
52
51
41
43
44
44
Mineral Products
2
2
2
15
14
18
17
27
28
30
31
31
32
32
32
Machinery Products
NA
NA
NA
4
4
7
8
10
8
11
11
11
12
12
12
Electronic Equipment
NA
NA
NA
0
0
2
2
3
3
3
2
1
1
1
1
Transportation Equipment
NA
NA
NA
1
0
2
2
2
3
3
2
3
4
4
4
Construction
NA
NA
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
Miscellaneous Industrial Processes
NA
NA
NA
108
109
59
62
62
62
62
57
58
60
60
61
-------
Source Category
1970 1975 1980 1985 1989 1990
SOLVENT UTILIZATION
Degreasing
open top
conveyorized
cold cleaning
other
Graphic Arts
letterpress
flexographic
lithographic
gravure
other
Dry Cleaning
perchloroethylene
petroleum solvent
other
Surface Coating
industrial adhesives
fabrics
paper
large appliances
magnet wire
autos & light trucks
metal cans
metal coil
wood furniture
metal furniture
flatwood products
plastic parts
large ships
aircraft
misc. metal parts
steel drums
architectural
traffic markings
maintenance coatings
railroad
auto refinishing
machinery
electronic & other electrical
general
miscellaneous
thinning solvents
other
7,174
5,651
6,584
5,699
5,964
5,750
707
448
513
756
757
744
NA
NA
NA
28
29
18
NA
NA
NA
5
4
5
NA
NA
NA
31
35
30
707
448
513
691
689
691
319
254
373
317
363
274
NA
NA
NA
2
2
4
NA
NA
NA
18
20
20
NA
NA
NA
4
4
14
NA
NA
NA
131
150
75
319
254
373
162
187
162
263
229
320
169
212
215
NA
NA
NA
85
107
110
NA
NA
NA
84
105
104
263
229
320
0
0
0
3,570
2,977
3,685
2,549
2,635
2,523
52
41
55
381
375
390
161
177
186
34
35
14
652
548
626
106
114
75
49
43
36
22
18
21
7
6
5
0
0
1
165
204
165
85
87
92
49
57
73
97
95
94
18
19
21
50
50
45
211
231
231
132
140
158
35
42
52
41
44
48
64
76
82
4
4
9
17
18
25
11
11
27
21
20
20
15
15
15
1
1
2
27
34
7
NA
NA
NA
14
14
59
NA
NA
NA
NA
NA
3
442
407
477
473
500
495
NA
NA
NA
100
106
105
108
125
106
79
80
79
5
7
9
4
3
3
83
143
186
111
132
130
39
51
62
37
28
28
NA
NA
NA
79
79
78
79
61
52
146
154
121
942
392
799
104
103
32
NA
NA
NA
90
96
96
372
309
415
306
317
297
1991 1992 1993 1994 1995 1996 1997 1998 1999 ^
>
,782
5,901
6,016
6,162
718
737
753
775
25
26
26
27
6
6
6
6
23
24
24
22
664
680
697
719
301
O
308
O
322
P
333
P
0
24
0
26
0
26
0
25
17
18
21
22
82
81
87
93
171
175
180
185
218
224
225
228
112
115
116
117
106
109
110
111
0
0
0
0
,521
2,577
2,632
2,716
374
386
400
419
14
16
16
15
64
61
59
59
20
20
21
22
1
1
1
1
90
93
92
96
91
93
96
98
49
47
49
48
154
159
171
185
47
49
52
56
10
10
11
12
22
23
22
22
14
15
15
15
7
7
7
7
87
90
92
93
3
3
3
4
500
505
510
515
106
107
108
109
76
78
81
85
3
3
3
4
132
137
140
144
26
26
27
27
75
77
80
85
127
129
133
140
37
42
39
38
97
100
94
96
295
302
310
321
5,474
5,621
5,149
4,825
602
624
372
371
8
8
4
4
4
5
2
2
22
23
10
11
567
588
356
354
287
293
300
293
6
6
6
6
19
19
20
15
12
12
13
13
50
51
52
44
200
205
210
214
154
163
166
168
58
61
63
63
89
94
96
97
7
8
8
8
2,373
2,456
2,193
2,136
351
366
147
148
10
10
10
10
48
49
50
51
23
24
23
22
2
2
2
2~
94
100
102
106 §
99
106
109
113 §
45
47
48
49 i
175
185
127
130-5
52
54
56
58
16
17
17
18
15
16
16
16
17
18
18
19
11
11
12
5
38
40
40
40
4
4
4
4
480
485
487
483
93
94
94
93
80
83
84
85
3
3
3
4
161
163
163
104
25
25
22
20
78
82
82
82
100
105
106
107
30
31
32
32
51
53
54
54
273
280
282
282
Q.
B)
3"
0
3-
1 I
o
3
B)
6,183
789
24
5
23
737
339
8
24
20
91
196
230
118
112
1
2,681
410
15
52
21
1
96
102
47
179
53
13
18
13
6
92
4
522
111
84
4
142
25
85
138
35
99
314
-------
Source Category
1970 1975 1980 1985 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
Other Industrial
640
499
690
125
131
miscellaneous
39
30
44
NA
NA
rubber & plastics mfg
309
245
327
25
29
other
292
224
319
100
102
Nonindustrial
1,674
1,243
1,002
1,783
1,867
cutback asphalt
1,045
723
323
191
199
other asphalt
NA
NA
NA
NA
NA
pesticide application
241
195
241
212
260
adhesives
NA
NA
NA
345
353
consumer solvents
NA
NA
NA
1,035
1,056
other
387
325
437
NA
NA
Other
NA
NA
NA
NA
NA
STORAGE & TRANSPORT
1,954
2,181
1,975
1,747
1,753
Bulk Terminals & Plants
599
668
517
606
651
fixed roof
14
15
12
14
15
floating roof
45
50
39
46
50
variable vapor space
1
1
1
1
1
efr with seals
NA
NA
NA
NA
NA
ifr with seals
NA
NA
NA
NA
NA
underground tanks
NA
0
0
0
0
area source: gasoline
509
569
440
512
553
other
30
33
26
32
33
Petroleum & Petroleum Product Stor.
300
315
306
223
210
fixed roof gasoline
47
52
43
26
23
fixed roof crude
135
141
148
26
21
floating roof gasoline
49
54
45
27
24
floating roof crude
32
34
36
5
5
efr / seal gasoline
3
4
3
2
2
efr / seal crude
1
2
2
0
0
ifr / seal gasoline
1
2
1
1
1
ifr/seal crude
2
2
2
0
0
variable vapor space gasoline
3
3
3
1
2
area source: crude
NA
NA
NA
NA
NA
other
25
22
23
133
132
Petroleum & Petroleum Product Trans.t 92
84
61
126
125
gasoline loading: normal / splash
3
2
0
3
3
gasoline loading: balanced / submerged20
13
2
21
22
gasoline loading: normal / submerged39
26
3
41
42
gasoline loading: clean / submerged 2
1
0
2
2
marine vessel loading: gasoline & crude26
38
50
24
22
other
2
4
6
35
35
Service Stations: Stage I
416
481
461
207
223
Service Stations: Stage II
521
602
583
485
441
Service Stations: Breathing & Emptying NA
NA
NA
49
52
Organic Chemical Storage
26
31
46
34
36
Organic Chemical Transport
NA
NA
NA
17
15
Inorganic Chemical Storage
NA
NA
NA
0
0
Inorganic Chemical Transport
NA
NA
NA
0
0
Bulk Materials Storage
NA
NA
NA
0
0
Bulk Materials Transport
NA
NA
NA
NA
NA
98
102
102
99
96
106
110
111
113
NA
NA
NA
NA
NA
NA
NA
NA
NA
28
28
29
31
31
38
40
40
40
71
74
73
68
64
68
70
71
72
1,925
1,952
1,982
2,011
2,048
1,949
1,973
2,004
1,743
202
207
214
221
227
135
140
144
147
NA
NA
NA
NA
NA
43
44
45
46
264
272
280
289
299
388
393
408
412
365
368
372
375
380
301
304
307
250
1,095
1,105
1,116
1,126
1,142
1,076
1,085
1,095
883
NA
NA
NA
NA
NA
6
6
6
5
NA
NA
0
0
0
3
3
3
2
1,532
1,583
1,600
1,629
1,652
1,289
1,327
1,327
1,240
369
384
395
403
406
208
215
214
203
11
12
13
16
16
6
6
6
6
29
30
34
29
19
11
11
11
11
2
1
1
1
0
0
0
0
0
3
3
4
4
3
2
2
2
2
2
3
5
3
3
3
3
3
3
2
2
2
2
2
2
2
2
2
281
292
292
305
322
163
167
167
157
40
42
44
43
41
21
22
22
22 _
195
204
205
194
191
181
187
187
108 o
17
17
16
16
16
14
14
14
1 !
25
26
28
24
21
25
26
25
10 i
113
25
24
24
22
22
16
16
16
7
7
8
6
6
5
6
6
2
11
13
14
14
15
9
9
9
9
3
3
3
3
2
3
3
4
3
2
2
2
2
2
3
3
3
3
0
0
0
0
0
1
1
1
1
2
5
6
3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
102
106
103
103
106
104
108
108
68
146
149
142
139
134
115
119
119
120
2
2
2
3
2
3
3
3
3
17
15
13
11
10
7
7
7
7
25
26
24
25
23
13
14
13
14
0
0
0
0
0
0
0
0
0
30
30
29
28
29
31
32
33
34
73
75
73
72
70
61
62
62
62
295
303
309
322
334
310
318
318
320
430
442
449
467
484
399
410
410
412
51
52
53
55
57
43
45
45
45
35
38
39
39
37
26
26
27
25
8
8
7
7
7
5
5
5
5
1
1
1
1
1
1
1
1
1
0
0
0
0
0
0
0
0
0
2
2
1
1
1
1
1
1
1
NA
NA
NA
NA
NA
0
0
0
0
94
NA
28
66
1,900
199
NA
258
361
1,083
NA
0
1,495
359
9
26
2
2
2
1
282
36
157
13
21
15
2
7
3
1
0
1
0
92
151
3
15
26
0
31
76
300
433
52
30
10
0
0
2
NA
-------
Source Category
1970
1975
1980
1985
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
WASTE DISPOSAL & RECYCLING
1,984
984
758
979
941
986
999
1,010
1,046
1,046
1,067
418
422
428
586
Incineration
548
453
366
64
59
48
50
51
76
65
54
50
50
51
51
Open Burning
1,424
517
372
309
274
196
200
203
207
208
208
195
198
200
356
industrial
NA
NA
NA
6
6
4
4
4
5
5
5
5
5
5
0
commmerciai/institutionai
NA
NA
NA
1
2
9
9
10
10
10
10
18
19
19
0
residential
NA
NA
NA
302
266
165
167
169
171
172
173
163
165
166
149
other
1,424
517
372
NA
NA
19
20
20
21
21
20
9
10
10
207
POTW
NA
NA
NA
10
11
49
47
48
50
52
51
48
48
49
50
Industrial Waste Water
NA
NA
NA
1
2
14
18
19
19
19
16
19
20
20
21
TSDF
NA
NA
NA
594
595
589
591
589
588
587
628
41
41
42
42
Landfills
NA
NA
NA
0
0
64
66
69
74
80
75
35
35
36
36
Other
11
14
20
0
0
26
28
31
33
35
36
29
29
30
30
Transportation
14,849
12,623
11,291
11,818
9,744
8,988
9,240
8,882
8,973
9,235
8,515
9,099
8,844
8,738
8,529
ON-ROAD VEHICLES
12,972
10,545
8,979
9,376
7,192
6,443
6,660
6,289
6,348
6,563
5,816
5,541
5,438
5,439
5,297
Light-Duty Gas Vehicles & Motorcycles9,193
7,248
5,907
5,864
4,462
3,692
3,608
3,288
3,232
3,332
3,029
2,911
2,878
2,935
2,911
light-duty gas vehicles
9,133
7,177
5,843
5,810
4,412
3,635
3,571
3,256
3,198
3,295
2,991
2,875
2,842
2,895
2,870
motorcycles
60
71
64
54
50
56
36
33
34
37
38
36
36
39
42
Light-Duty Gas Trucks
2,770
2,289
2,059
2,425
1,867
2,016
2,318
2,347
2,471
2,488
2,135
1,786
1,789
1,788
1,722
light-duty gas trucks 1
1,564
1,251
1,229
1,437
1,018
1,103
1,245
1,255
1,313
1,307
1,172
1,157
1,164
1,171
1,132
light-duty gas trucks 2
1,206
1,038
830
988
849
912
1,073
1,092
1,157
1,181
963
629
624
617
589
Heavy-Duty Gas Vehicles
743
657
611
716
517
405
416
335
327
414
325
488
439
400
375
Diesels
266
351
402
370
346
331
318
318
318
330
326
356
332
316
289 o
heavy-duty diesel vehicles
266
335
392
360
332
298
303
302
302
313
309
348
325
311
284 2.
light-duty diesel trucks
NA
NA
2
2
3
24
4
5
5
5
5
4
3
3
21
light-duty diesel vehicles
NA
15
8
8
11
9
11
11
11
12
12
5
4
3
O (D
o Q_
NON-ROAD ENGINES AND VEHICLES 1,878
2,078
2,312
2,442
2,552
2,545
2,581
2,594
2,624
2,672
2,699
3,558
3,406
3,299
3,232~
Non-Road Gasoline
1,564
1,669
1,787
1,886
1,907
1,889
1,920
1,925
1,957
1,991
2,021
2,888
2,738
2,637
2,593
recreational
138
145
151
156
160
128
130
132
133
135
138
189
186
185
185
construction
27
29
39
45
44
44
44
44
44
44
44
68
59
54
51
industrial
25
27
33
37
33
33
32
31
30
29
28
42
34
32
30
lawn & garden
511
547
583
616
682
700
718
734
752
771
789
1,047
971
888
845
farm
10
14
17
19
20
20
21
21
21
22
22
17
17
16
15
light commercial
115
121
127
137
164
171
179
185
192
200
207
233
204
182
172
logging
2
4
5
5
8
9
9
10
11
11
12
372
344
351
369
airport service
0
0
1
1
1
1
1
1
1
1
1
0
0
0
0
railway maintenance
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
0
0
recreational marine vessels
736
782
830
869
793
784
787
768
772
778
779
917
924
929
924
Non-Road Diesel
187
257
327
332
384
390
397
403
408
414
420
412
406
395
372
recreational
0
1
1
1
1
1
1
1
1
1
1
1
1
1
1
construction
94
103
135
151
176
181
185
190
194
199
204
207
205
198
185
industrial
38
23
28
36
40
40
41
41
42
42
43
41
41
41
39
lawn & garden
3
4
4
5
9
10
11
12
13
14
14
15
16
17
17
farm
39
109
138
113
127
126
126
125
124
123
121
107
104
101
94
light commercial
7
8
8
10
13
13
14
14
15
16
16
18
19
20
20
logging
6
9
11
14
14
14
15
15
15
14
14
15
13
10
8
airport service
0
0
0
1
1
1
1
2
2
2
2
2
2
2
2
railway maintenance
UA
UA
UA
1
1
1
1
1
1
1
1
1
1
1
1
recreational marine vessels
UA
UA
UA
2
3
3
3
3
3
3
3
4
4
5
5
-------
Source Category
1970
1975
1980
1985
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
Aircraft
97
116
146
165
190
180
177
179
176
176
178
177
178
183
183
Marine Vessels
7
8
19
22
30
32
34
33
32
43
32
33
33
34
34
coal
0
0
0
1
1
0
0
0
0
1
0
0
0
0
1
diesel
6
8
17
20
27
21
22
21
20
27
20
32
32
32
33
residual oil
0
1
1
1
2
3
3
3
3
4
3
0
0
0
0
gasoline
NA
NA
NA
NA
NA
1
1
1
1
1
1
1
1
1
1
other
NA
NA
NA
NA
NA
7
8
8
8
11
8
0
0
0
0
Railroads
22
27
33
37
42
52
52
54
52
49
49
48
50
50
49
Non-Road Other
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
liquified petroleum gas
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
0
0
compressed natural gas
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
0
0
Miscellaneous
1,101
716
1,134
566
642
1,059
756
486
556
720
551
753
1,192
714
716
Agriculture & Forestry
NA
NA
NA
NA
NA
5
6
6
6
6
7
7
7
7
8
Other Combustion
1,101
716
1,134
565
641
1,049
743
474
544
707
537
740
1,179
700
702
structural fires
19
47
40
44
44
14
14
15
15
15
15
14
14
15
15
agricultural fires
131
75
70
55
79
48
48
49
48
51
54
51
52
52
53
slash/prescribed burning
147
290
285
182
182
234
239
243
266
259
293
277
293
311
311
forest wildfires
770
297
739
283
335
749
439
164
212
379
171
395
817
319
319
other
34
7
1
NA
NA
3
3
3
3
3
3
3
3
3
3
Catastrophic/Accidental Releases
NA
NA
NA
NA
NA
4
4
4
4
4
4
4
5
5
5
Health Services
NA
NA
NA
0
1
1
0
1
1
1
1
0
1
1
1
Cooling Towers
NA
NA
NA
NA
NA
0
2
2
1
2
2
1
1
1
1 -o-
Fugitive Dust
NA
NA
NA
NA
NA
0
0
0
0
0
0
0
0
0
0 1
TOTAL AVAILABLE SOURCES
30,982
26,079
26,336
24,428
22,513
21,053
21,249
20,862
21,099
21,683
20,918
19,464
19,732
18,614
18,145 |
(D
Q_
Note: Some columns may not sum to totals due to rounding.
-------
Source Category
1970
1975
1980
1985
1989
1990
Fuel Combustion
2872
2247
2445
1,536
1,382
1,196
FUEL COMB. ELEC. UTIL.
1,775
1,191
879
280
271
295
Coal
1,680
1,091
796
268
255
265
bituminous
1,041
661
483
217
193
188
subbituminous
513
326
238
35
39
37
anthracite & lignite
126
104
75
16
22
41
other
NA
NA
NA
0
0
NA
Oil
89
93
76
8
12
9
residual
85
87
74
8
11
9
distillate
3
6
2
0
0
0
Gas
7
6
1
1
1
1
Other
0
0
0
0
0
0
Internal Combustion
NA
NA
NA
3
3
20
FUEL COMB. INDUSTRIAL
641
564
679
247
243
270
Coal
83
23
18
71
70
84
bituminous
52
14
12
48
49
59
subbituminous
16
4
4
1
1
5
anthracite & lignite
15
4
2
7
6
2
other
NA
NA
NA
15
14
19
Oil
89
69
67
52
48
52
residual
83
62
63
43
39
44
distillate
6
7
4
5
5
6
other
0
0
0
4
4
2
Gas
27
25
23
47
44
41
natural
24
22
20
24
24
30
process
4
3
3
22
20
11
other
NA
NA
NA
1
1
0
Other
441
447
571
75
78
87
wood/bark wasfe
415
444
566
67
71
80
liquid wasfe
NA
NA
NA
1
1
1
other
26
3
5
6
6
6
Internal Combustion
NA
NA
NA
3
3
6
FUEL COMB. OTHER
455
492
887
1,009
869
631
Commercial/Institutional Coal
13
10
8
13
13
15
Commercial/Institutional Oil
52
34
30
12
13
13
Commercial/Institutional Gas
4
4
4
4
5
5
Misc. Fuel Comb. (Except Residential)NA
NA
NA
3
3
79
Residential Wood
384
407
818
959
817
501
fireplaces
384
407
818
959
817
501
woodstoves
NA
NA
NA
NA
NA
NA
other
NA
NA
NA
NA
NA
NA
Residential Other
3
37
27
18
18
18
1991
1992
1993
1994
1995
1996
1997
1998
1999
1,147
1,183
1,124
1,113
1,179
1,160
1,076
996
1,029
257
257
279
273
268
289
294
229
225
232
234
253
246
244
264
268
197
194
169
167
185
181
174
195
196
134
131
39
43
46
44
48
51
51
47
46
23
23
22
21
21
19
21
17
17
NA
NA
NA
NA
NA
0
0
0
0
10
1
9
8
5
6
7
5
5
10
7
9
8
5
6
7
5
5
0
0
0
0
0
0
0
0
0
1
0
1
1
1
1
1
1
1
0
0
0
0
0
1
1
7
7
15
16
17
17
18
17
18
18
19
233
243
257
270
302
239
233
230
236
72
74
71
70
70
73
73
71
74
48
53
51
49
49
43
43
42
44
3
3
3
5
5
5
5
5
5
1
1
1
1
1
1
1
1
1
19
17
16
16
15
24
23
23
23
44
45
45
44
49
46
43
42
43
36
37
38
37
42
38
35
34
35
6
6
6
6
6
7
7
7
7
2
1
1
1
1
1
1
1
1
34
40
43
43
45
42
42
42
43
24
26
29
30
30
28
27
27
28
10
13
13
14
15
14
15
15
14
0
0
0
0
0
0
0
0
0
72
74
86
74
73
61
58
59
60
67
67
71
68
68
54
51
52
53
1
1
1
1
1
1
1
1
1
5
6
14
6
5
7
6
6
6
10
11
12
38
64
17
17
16
17
657
683
588
570
610
632
549
537
568
14
15
15
15
16
16
16
17
17
11
12
11
12
12
12
12
10
9
6
6
6
7
6
8
8
7
8
73
73
72
73
73
72
76
79
81
535
558
464
446
484
503
415
403
431
535
558
464
446
484
429
344
335
359
NA
NA
NA
NA
NA
38
36
34
36
NA
NA
NA
NA
NA
37
35
33
35
18
18
18
18
18
23
22
21
22
2
CD
>
i
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3
w
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D
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m
w
3'
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i i
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CD
O
CD
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00
O
CD
00
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CD
00
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CD
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D
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0
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O
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§
o
Z
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>
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D
c
>
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O
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73
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73
-------
Source Category
1970 1975 1980 1985 1989 1990
Inudstrial Processes
8,668
4,075
3,026
1339
1276
1306
CHEMICAL & ALLIED PRODUCT MFG
¦ 235
127
148
58
63
77
Organic Chemical Mfg
43
21
19
19
22
26
Inorganic Chemical Mfg
61
31
25
7
8
19
Polymer & Resin Mfg
NA
NA
NA
4
5
5
Agricultural Chemical Mfg
46
38
61
9
10
11
Paint, Varnish, Lacquer, Enamel Mfg NA
NA
NA
0
0
1
Pharmaceutical Mfg
NA
NA
NA
0
0
1
Other Chemical Mfg
86
37
42
18
18
14
METALS PROCESSING
1,316
825
622
220
211
214
Nonferrous Metals Processing
593
229
130
46
45
50
copper
343
66
32
3
3
14
lead
53
31
18
4
3
3
zinc
20
11
3
3
3
6
other
177
121
77
36
36
27
Ferrous Metals Processing
198
275
322
164
156
155
primary
31
198
271
136
129
128
secondary
167
77
51
26
26
25
other
NA
NA
NA
2
2
2
Metals Processing NEC
525
321
170
10
10
9
PETROLEUM & RELATED INDUSTRIES 286
179
138
63
58
55
Oil & Gas Production
NA
NA
NA
0
0
2
Petroleum Refineries & Related Ind
. 69
56
41
28
24
20
fluid catalytic cracking units
69
56
41
24
21
17
other
NA
NA
NA
4
3
3
Asphalt Manufacturing
217
123
97
35
34
33
OTHER INDUSTRIAL PROCESSES
5,832
2,572
1,846
611
591
583
Agriculture, Food, & Kindred Products485
429
402
68
72
73
country elevators
257
247
258
7
9
9
terminal elevators
147
111
86
6
6
6
feed mills
5
3
3
6
7
7
soybean mills
25
27
22
13
14
14
wheat mills
5
1
1
3
3
3
other grain mills
9
8
6
7
8
8
other
38
32
26
25
25
25
Textiles, Leather, & Apparel Products NA
NA
NA
0
0
0
Wood, Pulp & Paper, & Pub. Prod.
727
274
183
101
106
105
sulfate (kraft) pulping
668
228
142
71
74
73
other
59
46
41
30
33
32
Rubber & Miscellaneous Plastic Prod. NA
NA
NA
3
4
4
Mineral Products
4,620
1,869
1,261
401
374
367
cement mfg
1,731
703
417
213
193
190
surface mining
134
111
127
20
15
15
stone quarrying/processing
957
508
421
52
54
54
other
1,798
547
296
116
111
108
Machinery Products
NA
NA
NA
8
9
9
Electronic Equipment
NA
NA
NA
0
0
0
Transportation Equipment
NA
NA
NA
2
2
2
Construction
NA
NA
NA
NA
NA
0
Miscellaneous Industrial Processes
NA
NA
NA
28
23
23
1991 1992 1993 1994 1995 1996 1997 1998 1999
1264
1269
1240
1219
1231 951
977
983
1263
68
71
66
76
67
63
64
65
66
28
28
28
29
29
29
29
30
30
4
5
5
5
5
4
4
4
4
4
5
4
4
4
3
3
3
3
11
11
11
10
10
8
9
9
9
1
1
1
1
1
1
1
1
1
0
0
0
0
0
0
0
0
0
20
20
18
27
18
19
19
19
19
251
250
181
184
212
144
151
150
147
46
47
40
39
41
34
35
35
35
14
15
12
11
12
6
6
6
6
2
2
2
2
3
2
2
2
2
6
6
1
2
2
2
2
2
2
23
23
25
25
25
24
25
25
25
123
115
121
125
149
91
96
95
93
99
92
97
100
123
64
68
68
67
24
23
24
25
26
27
28
27
26
0
0
0
0
0
0
0
0
0
82
88
20
20
22
19
20
20
19
43
43
38
38
40
29
30
30
29
2
2
2
2
2
1
1
1
1
20
21
20
19
20
17
17
17
17
17
18
17
16
18
12
12
12
12
3
3
3
3
3
5
5
5
5
21
20
17
17
18
12
12
11
11
520
506
501
495
511
325
336
338
343
80
69
73
73
80
59
61
59
61
10
10
10
9
9
5
5
5
5
7
8
8
7
7
2
2
2
2
4
5
5
5
5
3
3
3
3
15
11
12
12
12
7
7
7
7
4
4
4
4
4
2
2
2
2
6
5
6
6
7
5
5
5
5
34
26
28
30
37
36
37
34
36
0
0
0
0
0
1
1
1
1
81
79
78
76
81
75
77
79
80
53
50
49
50
53
38
40
40
41
27
29
29
26
28
37
38
39
39
4
4
3
3
3
4
4
4
4
320
318
316
313
317
160
166
167
168
147
145
140
139
140
23
24
25
24
14
15
17
17
17
16
17
17
17
59
60
60
58
58
23
24
24
24
99
98
99
100
102
97
101
102
103
8
9
7
7
7
5
5
5
5
0
0
0
0
0
1
1
1
1
2
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
25
24
22
22
23
21
21
21
22
&>
2
ID
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00
O
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00
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O
C
>
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CO
O
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CO
H
73
D
CO
73
m
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73
-------
Source Category
1970 1975 1980 1985 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
SOLVENT UTILIZATION
NA
NA
NA
2
2
Degreasing
NA
NA
NA
0
0
Graphic Arts
NA
NA
NA
0
0
Dry Cleaning
NA
NA
NA
0
0
Surface Coating
NA
NA
NA
2
2
Other Industrial
NA
NA
NA
0
0
Nonindustrial
NA
NA
NA
NA
NA
Solvent Utilization NEC
NA
NA
NA
NA
NA
STORAGE & TRANSPORT
NA
NA
NA
107
101
Bulk Terminals & Plants
NA
NA
NA
0
0
Petroleum & Petroleum Prod. Storage NA
NA
NA
0
0
Petroleum & Petroleum Prod. Trans.
NA
NA
NA
0
0
Service Stations: Stage II
NA
NA
NA
NA
NA
Organic Chemical Storage
NA
NA
NA
1
1
Organic Chemical Transport
NA
NA
NA
0
0
Inorganic Chemical Storage
NA
NA
NA
0
0
Inorganic Chemical Transport
NA
NA
NA
NA
NA
Bulk Materials Storage
NA
NA
NA
105
99
storage
NA
NA
NA
33
31
transfer
NA
NA
NA
72
67
combined
NA
NA
NA
1
1
other
NA
NA
NA
NA
NA
Bulk Materials Transport
NA
NA
NA
0
0
WASTE DISPOSAL & RECYCLING
999
371
273
278
251
Incineration
229
95
75
52
50
residential
51
49
42
39
35
other
178
46
32
13
15
Open Burning
770
276
198
225
200
residential
770
276
198
221
195
other
NA
NA
NA
4
5
POTW
NA
NA
NA
NA
NA
Industrial Waste Water
NA
NA
NA
0
0
TSDF
NA
NA
NA
NA
NA
Landfills
NA
NA
NA
0
0
Other
NA
NA
NA
0
0
Transportation
786
786
786
786
844
ON-ROAD VEHICLES
443
471
397
363
367
Light-Duty Gas Vehicles & Motorcycles 225
207
120
77
65
light-duty gas vehicles
224
206
119
77
64
motorcycles
1
1
1
0
0
Light-Duty Gas Trucks
70
72
55
43
34
light-duty gas trucks 1
41
39
25
19
16
light-duty gas trucks 2
29
34
29
24
19
Heavy-Duty Gas Vehicles
13
15
15
14
11
Diesels
136
177
208
229
257
heavy-duty diesel vehicles
136
166
194
219
247
light-duty diesel trucks
NA
NA
2
1
2
light-duty diesel vehicles
NA
10
12
8
9
5
5
6
6
6
6
6
6
6
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
0
0
0
0
0
0
0
0
0
4
4
5
5
5
4
5
5
5
1
1
1
1
1
0
0
0
0
NA
NA
NA
NA
NA
0
0
0
0
NA
NA
NA
NA
NA
0
0
0
0
101
117
114
106
109
81
83
84
85
0
0
0
0
0
0
0
0
0
1
1
1
0
0
1
1
1
1
0
0
0
0
0
0
0
0
0
NA
NA
NA
0
0
0
0
0
0
1
1
1
1
1
1
1
1
1
0
0
0
0
0
0
0
0
0
1
1
1
1
1
0
0
1
1
0
0
0
0
0
0
0
0
0
99
115
111
104
107
78
80
81
82
27
30
32
31
30
26
26
27
27
71
85
79
73
76
51
53
54
54
0
0
0
0
0
0
0
0
0
0
0
NA
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
276
278
334
313
287
303
307
310
587
66
65
119
96
69
89
90
91
92
41
43
44
45
45
62
63
63
63
25
23
74
52
25
26
27
28
28
209
211
214
216
217
211
214
216
492
197
199
202
203
204
194
195
197
188
12
12
13
13
13
18
18
19
303
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
1
1
0
3
3
3
3
0
0
0
1
1
1
1
1
1
842
839
810
804
756 818
801
779
753
353
349
327
324
300
345
331
312
295
56
55
55
55
55
56
57
58
59
55
54
55
54
55
56
56
58
58
0
0
0
0
0
0
0
0
0
44
47
46
46
41
35
36
36
36
21
22
22
22
23
23
24
24
25
23
25
24
24
19
12
12
12
11
10
9
10
10
9
14
13
12
12
243
238
215
213
194
239
225
206
189
233
228
206
204
185
235
221
203
186
2
3
2
2
2
2
1
1
1
8
8
7
7
7
3
2
2
1
4
0
0
0
3
1
NA
NA
102
0
0
0
NA
1
0
1
0
100
31
69
1
NA
1
271
65
39
26
206
195
11
0
NA
0
0
0
838
349
57
57
0
37
18
19
10
245
225
13
7
-------
Source Category
1970
1975
1980
1985
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
NON-ROAD ENGINES AND VEHICLES 220
310
398
424
477
489
489
490
483
480
456
473
470
467
458
Non-Road Gasoline
12
39
42
44
46
47
47
48
48
48
49
86
87
88
89
recreational
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
construction
0
1
1
1
1
1
1
1
1
1
1
2
2
2
2
industrial
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
lawn & garden
8
8
9
9
10
11
11
11
12
12
12
21
21
20
20
farm
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
light commercial
1
1
1
1
2
2
2
2
2
2
2
2
2
2
2
logging
0
0
0
0
0
0
0
0
0
0
0
19
20
22
23
airport service
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
railway maintenance
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
0
0
recreational marine vessels (other) UA
26
28
29
30
30
30
30
30
30
30
38
38
39
39
Non-Road Diesel
154
204
263
272
302
301
299
297
296
296
296
273
268
263
253
recreational
0
0
0
1
1
1
1
1
1
1
1
1
1
1
1
construction
75
92
123
134
149
149
148
147
147
146
146
142
139
135
128
industrial
36
23
27
35
38
38
37
37
38
38
38
33
33
33
33
lawn & garden
3
3
4
4
8
8
9
10
11
11
12
11
11
12
12
farm
16
66
85
70
78
78
77
76
75
74
73
62
59
57
54
light commercial
6
7
7
9
11
12
12
12
13
13
14
13
14
14
15
logging
17
12
16
19
15
13
11
10
9
9
8
8
7
7
6
airport service
0
0
0
0
1
1
1
1
1
1
1
1
1
1
1
railway maintenance
NA
UA
UA
0
1
1
1
1
1
1
1
1
1
1
1
recreational marine vessels
NA
UA
UA
1
1
1
1
1
1
2
2
2
2
2
2
Aircraft
21
26
33
37
43
44
44
45
43
41
40
40
39
39
38
Marine Vessels
9
10
23
28
38
44
46
45
43
44
43
44
44
45
46
coal
1
1
2
2
3
3
3
3
3
3
3
3
3
3
3
diesel
5
6
15
17
23
27
28
27
26
26
26
40
41
41
42
residual oil
3
3
7
9
12
14
14
14
14
14
13
0
0
0
0
gasoline
NA
NA
NA
NA
NA
1
1
1
1
1
1
1
1
1
1
Railroads
25
30
37
41
47
53
53
54
52
50
27
29
30
30
30
Non-Road Other
0
0
0
1
1
1
1
1
1
1
1
2
2
2
2
liquified petroleum gas
NA
NA
NA
1
1
1
1
1
1
1
1
1
1
1
1
compressed natural gas
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
0
0
TOTAL ALL SOURCES
12,325
7,108
6,258
3,662
3,502
3,340
3,253
3,292
3,174
3,136
3,165
2,929
2,854
2,758
3,045
Note: Some columns may not sum to totals due to rounding.
-------
Source Category
1970
1975
1980
1985
1989
1990
Miscellaneous
839
569
852
37,736
37,461
24,541
Agriculture & Forestry
NA
NA
NA
7,108
7,320
5,292
agricultural crops
NA
NA
NA
6,833
6,923
4,745
agricultural livestock
NA
NA
NA
275
396
547
Other Combustion
839
569
852
894
912
1,181
wildfires
385
206
514
308
300
601
managed burning
390
325
315
527
553
558
other
64
37
23
59
59
22
Cooling Towers
NA
NA
NA
NA
NA
0
Fugitive Dust
NA
NA
NA
29,734
29,229
18,068
unpaved roads
NA
NA
NA
11,644
11,798
11,234
paved roads
NA
NA
NA
5,080
5,769
2,248
construction
NA
NA
NA
12,670
11,269
4,249
other
NA
NA
NA
339
392
336
TOTAL ALL SOURCES
839
569
852
37,736
37,461
24,541
1991 1992 1993 1994 1995 1996 1997 1998 1999
24,233 23,958
5,234 5,017
4,684 4,464
550 553
924 770
332 171
569 576
23 23
0 0
18,075 18,170
11,206 10,918
2,399 2,423
4,092 4,460
377 369
24,233 23,958
24,328
25,620
4,575
4,845
4,016
4,281
558
564
801
1,053
152
424
625
606
23
24
0
0
18,953
19,722
11,430
11,370
2,462
2,538
4,651
5,245
409
569
24,328 25,620
22,765 21,761
4,902 4,911
4,334 4,330
569 581
850 1,152
145 502
680 631
24 20
1 3
17,012 15,695
10,362 9,071
2,409 2,400
3,654 3,578
586 645
22,765 21,761
23,046 23,282
4,952 4,951
4,373 4,366
579 585
1,300 1,005
599 261
680 723
21 21
3 3
16,791 17,324
9,461 9,327
2,595 2,663
4,022 4,545
713 788
23,046 23,282
20,634
4,888
4,298
590
1,007
261
725
21
3
14,736
9,360
2,728
1,956
692
20,634
-------
Source Category
1970
1975
1980
1985
1989
1990
Fuel Combustion
23,456
22,661
21,391
20,021
19,924
20,290
FUEL COMB. ELEC. UTIL.
17,398
18,268
17,469
16,272
16,215
15,909
Coal
15,799
16,756
16,073
15,630
15,404
15,220
bituminous
9,574
10,161
NA
14,029
13,579
13,371
subbituminous
4,716
5,005
NA
1,292
1,422
1,415
anthracite & lignite
1,509
1,590
NA
309
404
434
Oil
1,598
1,511
1,395
612
779
639
residual
1,578
1,462
NA
604
765
629
distillate
20
49
NA
8
14
10
Gas
1
1
1
1
1
1
Other
NA
NA
NA
NA
NA
NA
Internal Combustion
NA
NA
NA
30
30
49
FUEL COMB. INDUSTRIAL
4,568
3,310
2,951
3,169
3,086
3,550
Coal
3,129
1,870
1,527
1,818
1,840
1,914
bituminous
2,171
1,297
1,058
1,347
1,384
1,050
subbituminous
669
399
326
28
29
50
anthracite & lignite
289
174
144
90
79
67
other
NA
NA
NA
353
348
746
Oil
1,229
1,139
1,065
862
812
927
residual
956
825
851
671
625
687
distillate
98
144
85
111
107
198
other
175
171
129
80
80
42
Gas
140
263
299
397
346
543
Other
70
38
60
86
82
158
Internal Combustion
NA
NA
NA
7
6
9
FUEL COMB. OTHER
1,490
1,082
971
579
624
831
Commercial/Institutional Coal
109
147
110
158
169
212
Commercial/Institutional Oil
883
638
637
239
274
425
Commercial/Institutional Gas
1
1
1
2
2
7
Misc. Fuel Comb. (Except Residential)NA
NA
NA
1
1
6
Residential Wood
6
7
13
13
11
7
Residential Other
492
290
211
167
167
175
distillate oil
212
196
157
128
132
137
bituminous/subbituminous coal
260
76
43
29
27
30
other
20
18
11
10
8
9
Industrial Processes
7,101
4,728
3,807
2,467
2,010
1,900
CHEMICAL & ALLIED PRODUCT MFG 591
367
280
456
440
297
Organic Chemical Mfg
NA
NA
NA
16
17
10
Inorganic Chemical Mfg
591
358
271
354
334
214
sulfur compounds
591
358
271
346
326
211
other
NA
NA
NA
8
8
2
Polymer & Resin Mfg
NA
NA
NA
7
7
1
Agricultural Chemical Mfg
NA
NA
NA
4
4
5
Paint, Varnish, Lacquer, Enamel Mfg NA
NA
NA
NA
NA
NA
Pharmaceutical Mfg
NA
NA
NA
0
0
0
Other Chemical Mfg
NA
8
10
76
77
67
1991 1992 1993 1994 1995 1996 1997 1998 1999
19,796
19,493
19,245
18,887
15,784
15,416
15,189
14,889
15,087
14,824
14,527
14,313
13,215
12,914
12,212
11,841
1,381
1,455
1,796
1,988
491
455
519
484
652
546
612
522
642
537
601
512
10
9
10
10
1
1
1
1
NA
NA
NA
NA
45
46
49
53
3,256
3,292
3,284
3,218
1,805
1,783
1,763
1,740
949
1,005
991
988
53
60
67
77
68
67
68
68
735
650
636
606
779
801
809
111
550
591
597
564
190
191
193
193
39
20
20
20
516
552
555
542
142
140
140
141
14
16
17
19
755
784
772
780
184
190
193
192
376
396
381
391
7
7
8
8
6
6
6
6
7
8
6
6
176
177
178
177
141
144
145
145
26
8
26
8
25
8
25
8
1,721
1,758
1,723
1,676
280
278
269
275
9
9
9
8
208
203
191
194
205
199
187
189
3
4
4
4
1
1
1
1
4
4
4
4
NA
NA
0
0
0
0
0
0
57
60
64
68
16,234 16,651 16,746 16,091
12,730
13,195
13,416
12,698
12,206
12,615
12,470
11,856
8,998
9,517
9,357
8,806
2,632
2,490
2,486
2,427
576
608
627
623
460
514
762
657
454
509
756
651
6
5
6
6
1
6
6
12
4
4
121
115
53
56
57
58
2,863
2,805
2,742
2,805
1,321
1,306
1,274
1,317
885
877
858
890
63
63
61
64
61
60
57
57
312
306
298
306
807
764
738
757
626
578
559
574
158
161
156
159
23
25
23
24
575
582
578
576
140
134
133
135
20
19
19
20
641
651
588
588
179
184
196
196
308
314
250
246
10
10
10
11
6
6
6
6
7
6
5
6
131
130
121
123
108
106
97
98
17
18
18
18
6
6
6
6
1,417 1,467 1,471 1,465
255
259
261
262
4
4
4
4
173
176
178
179
171
174
176
177
2
2
2
2
1
1
1
1
1
1
1
1
0
0
0
0
0
0
0
0
76
76
77
76
16,230
12,080
11,603
8,609
2,345
649
413
408
5
9
NA
55
3,357
1,728
1,003
81
68
576
912
701
191
20
548
147
23
793
200
397
8
5
7
176
144
24
8
1,637
286
8
199
195
4
0
5
0
0
74
-------
Source Category
1970
1975
1980
1985
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
METALS PROCESSING
4,775
2,849
1,842
1,042
695
726
612
615
603
562
530
390
407
405
401
Nonferrous Metals Processing
4,060
2,165
1,279
853
513
517
435
438
431
391
361
267
276
274
272
copper
3,507
1,946
1,080
655
327
323
234
247
250
206
177
93
99
98
97
lead
77
34
34
121
113
129
135
131
122
128
126
112
113
114
114
aluminum
80
72
95
62
60
60
61
55
53
51
53
57
59
57
56
other
396
113
71
14
13
4
5
5
6
6
6
5
5
5
5
Ferrous Metals Processing
715
684
562
172
165
186
159
158
153
153
151
107
114
114
113
Metals Processing NEC
NA
NA
NA
18
17
22
18
18
19
19
18
17
17
17
17
PETROLEUM & RELATED INDUSTRIES 881
727
734
505
429
430
378
416
383
379
369
335
344
342
341
Oil & Gas Production
111
173
157
204
156
122
98
93
98
95
89
90
90
90
90
natural gas
111
173
157
202
155
120
96
92
96
93
88
89
90
89
89
other
NA
NA
NA
2
1
2
2
2
2
2
1
1
1
1
1
Petroleum Refineries & Related Ind
. 770
554
577
300
272
304
274
315
278
276
271
238
246
245
244
fluid catalytic cracking units
480
318
330
212
195
183
182
185
183
188
188
157
163
162
162
other
290
236
247
88
77
121
92
130
95
88
83
81
83
83
82
Asphalt Manufacturing
NA
NA
NA
1
1
4
7
7
7
8
9
8
8
8
7
OTHER INDUSTRIAL PROCESSES
846
740
918
425
405
399
396
396
392
398
403
390
409
415
418
Agriculture, Food, & Kindred Products NA
NA
NA
3
3
3
3
3
3
3
3
4
4
4
5
Textiles, Leather, & Apparel Products NA
NA
NA
0
0
0
0
0
0
0
0
0
0
0
0
Wood, Pulp & Paper, & Publ. Prod.
169
168
223
131
136
116
123
119
113
109
114
101
105
107
109
Rubber & Miscellaneous Plastic Prod. NA
NA
NA
1
1
0
0
0
0
0
0
1
1
1
1
Mineral Products
677
571
694
286
261
275
267
270
272
282
282
270
285
288
288
cement mfg
618
511
630
192
172
181
165
168
170
167
171
171
181
183
183
other
59
60
64
95
89
94
102
102
102
114
111
99
103
105
106
Machinery Products
NA
NA
NA
0
0
0
0
1
0
1
1
0
0
0
0
Electronic Equipment
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
0
0
Transportation Equipment
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Miscellaneous Industrial Processes
NA
NA
NA
3
3
5
3
3
3
3
4
13
13
14
14
SOLVENT UTILIZATION
NA
NA
NA
1
1
0
0
1
1
1
1
1
1
1
1
Degreasing
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
0
0
Graphic Arts
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
0
0
Dry Cleaning
NA
NA
NA
NA
NA
NA
NA
0
NA
0
0
0
0
0
0
Surface Coating
NA
NA
NA
1
1
0
0
0
0
0
0
0
0
0
0
Other Industrial
NA
NA
NA
0
0
0
0
0
0
0
0
1
1
1
1
STORAGE & TRANSPORT
NA
NA
NA
4
5
7
10
9
5
2
2
5
5
5
5
Bulk Terminals & Plants
NA
NA
NA
NA
NA
0
1
1
0
0
0
1
1
1
1
Petroleum & Petroleum Prod. Storage NA
NA
NA
0
0
5
7
0
0
0
0
0
0
0
0
Petroleum & Petroleum Prod.t Trans. NA
NA
NA
1
1
0
0
0
0
0
0
1
1
2
2
Service Stations: Stage II
NA
NA
NA
NA
NA
NA
NA
NA
NA
0
0
0
0
0
0
Organic Chemical Storage
NA
NA
NA
1
1
0
0
0
0
0
0
0
0
0
0
Organic Chemical Transport
NA
NA
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
Inorganic Chemical Storage
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
0
0
Inorganic Chemical Transport
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
0
0
Bulk Materials Storage
NA
NA
NA
1
2
1
1
7
4
1
1
2
2
2
2
-------
Source Category
1970 1975 1980 1985 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
WASTE DISPOSAL & RECYCLING
8
46
33
34
36
42
44
44
71
60
47
41
42
42
37
Incineration
4
29
21
25
28
32
32
32
51
42
35
29
29
30
30
industrial
NA
NA
NA
10
10
5
4
5
25
17
8
6
6
7
7
other
4
29
21
15
18
26
28
27
26
26
27
22
23
23
24
Open Burning
4
17
12
9
8
11
11
11
11
11
11
11
11
11
5
industrial
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
0
0
other
4
17
12
8
7
10
10
11
11
11
11
11
11
11
5
POTW
NA
NA
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
Industrial Waste Water
NA
NA
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
TSDF
NA
NA
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
Landfills
NA
NA
NA
0
0
0
0
0
0
0
0
1
1
1
1
industrial
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
0
0
other
NA
NA
NA
0
0
0
0
0
0
0
0
0
0
0
0
Other
NA
NA
NA
0
0
0
1
1
8
6
0
0
0
0
0
Transportation
494
602
697
1,159
1,349
1,476
1,517
1,553
1,497
1,297
1,311
1,192
1,230
1,262
1,299
ON-ROAD VEHICLES
411
503
521
522
570
560
573
586
526
307
311
343
353
358
363
Light-Duty Gas Vehicles & Motorcycles 132
158
159
146
145
129
126
125
124
125
126
128
131
134
137
light-duty gas vehicles
132
158
158
145
145
128
126
125
124
124
126
128
130
134
136
motorcycles
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Light-Duty Gas Trucks
40
48
50
55
58
69
81
87
90
92
93
85
89
90
91
light-duty gas trucks 1
26
32
33
36
38
45
52
56
58
59
60
62
65
66
68
light-duty gas trucks 2
13
16
16
19
21
24
29
31
32
32
32
22
23
24
24
Heavy-Duty Gas Vehicles
8
9
10
11
11
10
10
10
11
12
11
18
18
17
17
Diesels
231
288
303
311
356
352
356
364
300
79
82
112
117
117
118
NON-ROAD ENGINES AND VEHICLES 83
99
175
637
779
916
944
968
972
990
999
849
877
904
936
Non-Road Gasoline
NA
NA
NA
20
22
22
22
22
23
23
23
28
28
28
28
Non-Road Diesel
NA
NA
NA
407
488
509
529
549
570
590
610
459
474
490
507
Aircraft
4
4
6
6
7
11
11
11
11
11
11
11
11
12
12
Marine Vessels
43
52
117
143
193
251
259
258
249
252
239
237
245
256
273
Railroads
36
43
53
59
67
122
120
125
117
113
113
111
115
114
113
Non-Road Other
NA
NA
NA
1
2
2
2
2
2
2
2
3
3
3
3
Miscellaneous
110
20
11
11
11
12
11
10
10
15
10
16
15
12
12
Agriculture & Forestry
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
0
0
0
0
Other Combustion
110
20
11
11
11
12
11
9
9
15
10
16
15
12
12
Fugitive Dust
NA
NA
NA
NA
NA
0
0
0
1
0
0
0
0
0
0
TOTAL ALL SOURCES
31,161
28,011
25,905
23,658
23,293
23,678
23,045
22,813
22,474
21,875
19,188
18,859
19,363
19,491
18,867
Note: Some columns may not sum to totals due to rounding.
-------
Source Category
1990 1991 1992 1993 1994
Fuel Combustion 909
893
927
852
841
898
FUEL COMB. ELEC. UTIL.
121
105
106
112
108
Coal
97
85
87
90
86
bituminous
59
53
53
57
54
subbituminous
14
16
18
18
17
anthracite & lignite
23
16
16
15
15
Oil
5
5
4
5
5
Gas
NA
NA
NA
NA
NA
Other
0
0
0
0
0
Internal Combustion
20
15
16
17
17
FUEL COMB. INDUSTRIAL
177
151
159
172
183
Coal
29
23
25
24
25
bituminous
23
18
20
20
19
subbituminous
2
1
1
2
3
anthracite & lignite
1
1
0
0
0
other
3
3
3
3
2
Oil
31
26
26
27
26
residual
26
22
22
23
22
distillate
4
3
3
4
4
other
1
1
1
1
1
Gas
39
34
39
41
42
natural
29
23
26
28
29
process
11
10
13
13
14
other
0
0
0
0
0
Other
73
58
59
69
60
wood/bark wasfe
68
55
54
58
55
liquid wasfe
1
0
0
1
0
other
4
3
4
10
4
Internal Combustion
5
10
10
11
29
FUEL COMB. OTHER
611
638
662
568
550
Commercial/Institutional Coal
6
6
6
6
6
Commercial/Institutional Oil
5
5
5
5
5
Commercial/Institutional Gas
5
5
6
6
6
Misc. Fuel Comb. (Except Residential)
78
73
72
72
72
Residential Wood
501
535
558
464
446
fireplaces
501
535
558
464
446
woodstoves
NA
NA
NA
NA
NA
Residential Other
15
15
15
15
15
Industrial Processes 794
812
819
788
771
749
CHEMICAL & ALLIED PRODUCT MFG
47
43
45
41
49
Organic Chemical Mfg
10
10
11
10
11
Inorganic Chemical Mfg
12
3
4
4
4
Polymer & Resin Mfg
4
3
4
3
3
Agricultural Chemical Mfg
8
8
8
8
8
Paint, Varnish, Lacquer, Enamel Mfg
0
0
0
0
0
Pharmaceutical Mfg
0
0
0
0
0
Other Chemical Mfg
13
17
17
15
23
1995
1996
1997
1998
1999
848
776
735
766
107
157
161
130
128
86
133
135
103
102
52
88
89
62
61
20
32
31
30
30
15
13
15
11
11
3
5
6
4
4
NA
1
1
1
1
H
0
0
0
3
3
fi>
D"
18
17
18
18
19
CD
203
153
149
147
151
>
i
<0
Iz:
25
23
23
23
24
19
18
18
18
18
CD
i i
3
3
3
3
3
o'
D
1
0
0
0
0
Q3_
2
28
2
26
2
24
2
24
2
24
"U
24
4
22
4
20
4
19
4
20
4
m
3
1
0
1
0
0
(/)
(/)
44
29
39
25
39
25
38
25
39
25
o'
D
(/)
15
13
14
14
14
m
CO
0
0
0
0
0
3
59
50
48
48
49
Q)
i i
(D
j/j
55
44
42
42
43
0
3
48
0
6
15
0
5
15
0
5
15
0
5
15
CD
CD
o
_l^
589
538
466
458
487
CD
CD
6
1
1
7
1
CD
5
5
5
4
4
i i
IT
6
7
7
7
7
C
(/)
CD
3
73
72
75
78
81
484
433
358
349
374
Q_
484
418
344
335
359
I-
>
73
O
C
>
H
>
Z
D
m
C/3
W
O
z
w
H
73
m
z
D
C/3
73
m
¦0
o
73
-------
Source Category
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
METALS PROCESSING
157
197
Non-Ferrous Metals Processing
31
29
copper
9
9
lead
2
2
zinc
5
5
other
14
13
Ferrous Metals Processing
121
89
primary
103
72
secondary
17
16
other
1
0
Metals Processing NEC
5
80
PETROLEUM & RELATED INDUSTRIES
27
24
Oil & Gas Production
2
2
Petroleum Refineries & Related Industries
13
14
fluid catalytic cracking units
11
12
other
2
2
Asphalt Manufacturing
12
9
OTHER INDUSTRIAL PROCESSES
284
264
Agriculture, Food, & Kindred Products
39
46
country elevators
6
6
terminal elevators
3
3
feed mills
2
2
soybean mills
5
4
wheat mills
1
1
other grain mills
4
3
other
17
26
Textiles, Leather, & Apparel Products
0
0
Wood, Pulp & Paper, & Publishing Products
77
61
sulfate (kraft) pulping
57
40
other
21
21
Rubber & Miscellaneous Plastic Products
3
3
Mineral Products
144
134
cement mfg
54
40
surface mining
6
6
stone quarrying/processing
24
28
other
61
60
Machinery Products
3
3
Electronic Equipment
0
0
Transportation Equipment
1
1
Construction
0
0
Miscellaneous Industrial Processes
16
16
SOLVENT UTILIZATION
4
4
Degreasing
0
0
Graphic Arts
0
0
Dry Cleaning
0
0
Surface Coating
3
3
Other Industrial
1
1
Nonindustrial
NA
NA
Solvent Utilization NEC
NA
NA
125
125
134
100
105
105
103
25
25
25
22
23
23
23
8
8
8
4
5
4
4
2
2
2
2
2
2
2
1
1
1
1
1
1
7
14
14
14
15
15
15
75
86
86
92
65
69
68
67
68
68
74
47
50
50
50
17
18
19
18
18
18
77
0
0
0
0
0
0
0
14
14
16
13
14
14
14
22
22
22
17
17
17
17
2
2
2
1
1
1
1
13
13
13
12
12
12
12
11
11
11
7
8
8
8
2
2
2
4
4
4
4
7
1
8
4
4
4
4
260
256
256
180
186
189
191
44
43
40
20
21
21
22
6
6
6
1
1
1
7
5
4
4
0
0
0
0
2
2
2
1
1
1
7
5
5
5
3
3
3
3
1
1
1
1
1
7
3
3
3
2
3
3
3
27
22
20
14
14
14
74
0
0
0
0
1
0
0
59
57
60
52
53
55
56
38
38
40
31
32
32
33
21
19
20
21
22
22
23
3
3
3
2
2
2
2
136
133
134
88
92
93
93
38
38
38
11
11
11
77
7
7
6
7
7
7
7
28
26
26
9
9
9
9
62
63
63
61
64
65
66
3
3
3
2
2
2
2
0
0
0
1
1
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
15
16
16
14
14
15
15
6
6
5
5
5
5
6
0
0
0
0
0
0
0
0
0
0
1
1
1
1
0
0
0
0
0
0
0
4
4
4
4
4
4
4
1
1
1
0
0
0
0
NA
NA
NA
0
0
0
0
NA
NA
NA
0
0
0
0
198
29
9
2
5
73
83
66
16
0
85
24
2
14
12
2
8
259
40
7
4
2
4
1
3
19
0
59
38
21
3
135
39
7
28
67
3
0
1
0
17
5
0
0
0
4
1
NA
NA
-------
Source Category
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
STORAGE & TRANSPORT
42
42
50
46
43
42
30
31
31
31
Bulk Terminals & Plants
0
0
0
0
0
0
0
0
0
0
Petroleum & Petroleum Product Storage
0
1
1
1
0
0
0
0
0
0
Petroleum & Petroleum Product Transport
0
0
0
0
0
0
0
0
0
0
Service Stations: Stage II
0
0
0
0
0
0
0
0
0
0
Organic Chemical Storage
0
0
0
0
0
0
1
1
1
1
Organic Chemical Transport
0
0
0
0
0
0
0
0
0
0
Inorganic Chemical Storage
0
0
0
0
0
0
0
0
0
0
Inorganic Chemical Transport
0
0
0
0
0
0
0
0
0
0
Bulk Materials Storage
41
41
48
44
41
41
28
29
29
30
storage
13
11
12
13
13
12
11
11
11
11
transfer
28
29
36
31
28
29
17
18
18
18
combined
0
0
0
0
0
0
0
0
0
0
other
NA
0
0
NA
0
0
0
0
0
0
Bulk Materials Transport
0
0
0
0
0
0
0
0
0
0
WASTE DISPOSAL & RECYCLING
234
238
239
288
271
247
234
236
238
525
Incineration
46
47
46
93
73
50
45
46
46
47
residential
27
28
30
31
31
31
30
30
30
31
other
19
18
16
62
42
19
15
15
16
16
Open Burning
187
190
192
195
196
197
186
188
190
476
residential
177
179
181
183
184
185
176
177
179
173
other
10
11
11
11
12
11
10
11
11
303
POTW
0
0
0
0
0
0
0
0
0
0
Industrial Waste Water
0
0
0
0
0
0
0
0
0
0
TSDF
0
0
0
0
0
0
0
0
0
0
Landfills
0
0
1
1
1
0
2
2
2
2
Other
0
0
0
0
1
0
0
0
0
0
Transportation 719
720
717
688
682
640
701
686
665
640
ON-ROAD VEHICLES
286
288
284
261
258
237
276
263
246
229
Light-Duty Gas Vehicles & Motorcycles
34
33
32
32
32
32
32
33
34
34
Idgv
34
33
32
32
32
32
32
33
33
34
motorcycles
0
0
0
0
0
0
0
0
0
0
Light-Duty Gas Trucks
24
28
30
30
29
26
22
22
22
22
Idgtl
12
13
14
14
14
14
14
15
15
15
Idgt2
13
15
16
16
15
12
8
8
7
7
Heavy-Duty Gas Vehicles
6
6
6
1
1
6
9
9
8
8
Diesels
221
220
216
192
190
173
212
199
181
166
hddv
204
211
207
184
182
165
208
196
179
164
Iddt
12
2
2
2
2
2
1
1
1
1
Iddv
6
7
7
6
6
6
2
2
1
1
NON-ROAD ENGINES AND VEHICLES
432
432
433
427
424
403
425
423
419
411
Non-Road Gasoline
43
43
43
44
44
45
79
80
81
82
recreational
2
3
3
3
3
3
3
3
3
3
construction
1
1
1
1
1
1
2
2
2
2
industrial
0
0
0
0
0
0
0
0
0
0
lawn & garden
10
10
10
11
11
11
19
19
19
19
farm
0
0
0
0
0
0
0
0
0
0
light commercial
1
2
2
2
2
2
2
2
2
2
-------
Source Category
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
NON-ROAD ENGINES AND VEHICLES (cont.)
logging
0
0
0
0
0
0
17
19
20
21
airport service
0
0
0
0
0
0
0
0
0
0
railway maintenance
0
0
0
0
0
0
0
0
0
0
recreational marine vessels
27
27
27
28
28
28
35
35
36
36
Non-Road Diesel
277
275
273
273
272
272
251
247
242
233
recreational
1
1
1
1
1
1
1
1
1
1
construction
137
136
136
135
134
134
130
128
124
118
industrial
35
34
34
35
35
35
30
30
30
30
lawn & garden
8
8
9
10
11
11
10
10
11
11
farm
71
71
70
69
68
67
57
55
53
50
light commercial
11
11
11
12
12
13
12
13
13
14
logging
12
10
9
8
8
8
8
7
6
5
airport service
1
1
1
1
1
1
1
1
1
1
railway maintenance
1
1
1
1
1
1
1
1
1
0
recreational marine vessels
1
1
1
1
1
1
2
2
2
2
Aircraft
31
31
32
30
29
28
28
27
27
27
Marine Vessels
32
34
33
31
32
31
39
39
40
40
coal
1
1
1
1
1
1
1
1
1
1
diesel
25
26
25
24
24
24
37
38
38
38
residual oil
6
6
6
6
6
6
0
0
0
0
gasoline
0
0
0
0
0
0
0
0
0
0
Railroads
49
48
50
48
46
25
27
28
28
27
Non-Road Other
1
1
1
1
1
1
2
2
2
2
liquified petroleum gas
1
1
1
1
1
1
1
1
1
1
compressed natural gas
0
0
0
0
0
0
0
0
0
0
Miscellaneous
5,234 5,004
4,854
4,926
5,360
4,725
4755
5186
5040
4454
Agriculture & Forestry
1,031
1,019
976
887
941
952
953
961
961
948
agricultural crops
949
937
893
803
856
867
866
875
873
860
agricultural livestock
82
83
83
84
85
85
87
87
88
89
Other Combustion
1,037
807
666
693
913
734
946
1139
871
872
wildfires
538
299
151
137
372
130
386
538
233
233
managed burning
479
488
494
535
519
583
542
582
619
620
other
20
20
21
21
21
22
18
19
19
19
Cooling Towers
0
0
0
0
0
1
2
2
3
3
Fugitive Dust
3,166
3,177
3,212
3,346
3,506
3,037
2853
3084
3206
2631
unpaved roads
1,687
1,684
1,642
1,718
1,709
1,559
1366
1427
1406
1411
paved roads
562
600
606
616
634
585
600
649
666
682
construction
850
818
892
930
1,049
777
750
857
968
391
other
67
75
73
81
113
117
136
150
165
146
TOTAL ALL SOURCES
7,655
7,430
7,317
7,254
7,654
7,012
6,909
7,267
7,065
6,773
Note: Some columns may not sum to totals due to rounding.
-------
Source Category
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
Fuel Combustion 25
25
25
26
26
26
47
47
47
48
FUEL COMB. ELEC. UTIL.
0
0
0
0
0
0
6
6
8
7
Coal
NA
NA
NA
NA
NA
NA
0
0
0
0
Oil
NA
NA
NA
NA
NA
NA
2
2
3
3
Gas
NA
NA
NA
NA
NA
NA
4
4
4
4
Other
NA
NA
NA
NA
NA
0
0
0
0
Internal Combustion
0
0
0
0
0
0
0
0
0
0
FUEL COMB. INDUSTRIAL
17
17
17
18
18
18
34
34
33
34
Coal
0
0
0
0
0
0
0
0
0
0
Oil
4
4
4
4
4
4
4
4
4
4
Gas
13
13
13
14
14
13
25
25
25
25
Other
0
0
0
0
0
0
0
0
0
0
Internal Combustion
0
0
0
0
0
0
5
5
5
5
FUEL COMB. OTHER
8
8
8
8
8
8
7
7
6
7
Commercial/Institutional Coal
0
0
0
0
0
0
0
0
0
0
Commercial/Institutional Oil
2
2
2
2
2
2
2
2
2
2
Commercial/Institutional Gas
1
1
1
1
1
1
1
1
1
1
Misc. Fuel Comb. (Except Residential)
NA
NA
NA
NA
NA
NA
0
0
0
0
Residential Other
5
5
5
5
5
5
5
5
4
4
Industrial Processes 351
355
359
364
364
365
271
277
284
289
CHEMICAL & ALLIED PRODUCT MFG
183
183
183
183
183
183
123
125
130
133
Organic Chemical Mfg
NA
NA
NA
NA
NA
NA
0
0
0
0
Inorganic Chemical Mfg
NA
NA
NA
NA
NA
NA
0
0
0
0
Polymer & Resin Mfg
NA
NA
NA
NA
NA
NA
0
0
0
0
Agricultural Chemicals
183
183
183
183
183
183
109
111
115
118
ammonium nitrate/urea mfg.
111
111
111
111
111
111
41
42
43
44
other
71
71
71
71
71
71
68
70
72
73
Other Chemical Mfg
NA
NA
NA
NA
NA
NA
13
14
14
15
METALS PROCESSING
6
6
6
6
6
6
4
5
5
5
Non-Ferrous Metals Processing
0
0
0
0
0
0
0
0
0
0
Ferrous Metals Processing
6
6
6
6
6
6
4
5
5
5
Metals Processing NEC
0
0
0
0
0
0
0
0
0
0
PETROLEUM & RELATED INDUSTRIES
43
43
43
43
43
43
16
17
17
17
Oil & Gas Production
0
0
0
0
0
0
0
0
0
0
Petroleum Refineries & Related Industries
43
43
43
43
43
43
16
17
17
17
catalytic cracking
43
43
43
43
43
43
16
17
17
17
other
0
0
0
0
0
0
0
0
0
0
OTHER INDUSTRIAL PROCESSES
38
38
39
39
40
40
43
45
45
45
Agriculture, Food, & Kindred Products
2
2
3
3
2
2
4
4
4
4
Textiles, Leather, & Apparel Products
NA
NA
NA
NA
NA
NA
0
0
0
0
Wood, Pulp & Paper, & Publishing Products
NA
NA
NA
NA
NA
NA
1
1
1
1
Rubber & Miscellaneous Plastic Products
NA
NA
NA
NA
NA
NA
0
0
0
0
Mineral Products
0
0
0
0
0
0
0
0
0
0
Machinery Products
NA
NA
NA
NA
NA
NA
0
0
0
0
Electronic Equipment
NA
NA
NA
NA
NA
NA
0
0
0
0
Miscellaneous Industrial Processes
35
35
36
37
38
38
39
40
40
40
-------
Source Category
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
SOLVENT UTILIZATION
0
0
0
0
0
0
0
0
0
0
Degreasing
NA
NA
NA
NA
NA
NA
0
0
0
0
Graphic Arts
NA
NA
NA
NA
NA
NA
0
0
0
0
Dry Cleaning
NA
NA
NA
NA
NA
NA
0
0
0
0
Surface Coating
NA
NA
NA
NA
NA
NA
0
0
0
0
Other Industrial
NA
NA
NA
NA
NA
NA
0
0
0
0
STORAGE & TRANSPORT
0
0
0
0
0
0
1
1
1
1
Bulk Terminals & Plants
NA
NA
NA
NA
NA
NA
0
0
0
0
Petroleum & Petroleum Product Storage
NA
NA
NA
NA
NA
NA
1
1
1
1
Petroleum & Petroleum Product Transport
NA
NA
NA
NA
NA
NA
0
0
0
0
Organic Chemical Storage
NA
NA
NA
NA
NA
NA
0
0
0
0
Inorganic Chemical Storage
NA
NA
NA
NA
NA
NA
0
0
0
0
Bulk Materials Storage
0
0
0
0
0
0
0
0
0
0
WASTE DISPOSAL & RECYCLING
82
86
89
93
93
93
84
84
86
88
Incineration
NA
NA
NA
NA
NA
NA
0
0
0
0
Open Burning
NA
NA
NA
NA
NA
NA
0
0
0
0
POTW
82
86
89
93
93
93
84
84
86
87
wastewater treatment
82
86
89
93
93
93
84
84
86
87
other
NA
NA
NA
NA
NA
NA
0
0
0
0
Industrial Waste Water
NA
NA
NA
NA
NA
NA
0
0
0
0
TSDF
NA
NA
NA
NA
NA
NA
0
0
0
0
Landfills
NA
NA
NA
NA
NA
NA
0
0
0
0
Other
NA
NA
NA
NA
NA
NA
0
0
0
0
Transportation 194
205
214
224
239
258
238
267
262
270
ON-ROAD VEHICLES
188
198
208
218
233
252
229
258
252
260
Light-Duty Gas Vehicles & Motorcycles
149
151
155
159
168
180
157
168
169
174
Light-Duty Gas Trucks
38
46
52
58
63
70
63
80
72
76
Heavy-Duty Gas Vehicles
0
0
1
1
1
1
4
4
4
4
Diesels
0
0
0
0
0
0
6
6
6
6
NON-ROAD ENGINES AND VEHICLES
6
7
7
7
7
7
9
9
10
10
Non-Road Gasoline
1
1
1
1
1
1
1
1
1
1
Non-Road Diesel
2
3
3
3
3
3
3
3
3
3
Aircraft
NA
NA
NA
NA
NA
NA
3
3
4
4
Marine Vessels
1
1
1
1
1
1
1
1
1
1
Railroads
2
2
2
2
2
2
1
1
1
1
NATURAL SOURCES
30
29
28
29
30
31
32
33
34
35
Biogenic
30
29
28
29
30
31
32
33
34
35
Miscellaneous 3,727
3,770
3,814
3,869
3,924
3,979
4,106
4,163
4,258
4,322
Agriculture & Forestry
3,727
3,770
3,814
3,869
3,924
3,979
4,106
4,163
4,258
4,322
livestock agriculture
3,307
3,324
3,341
3,370
3,399
3,427
3,457
3,485
3,520
3,552
fertilizer application
420
446
473
499
525
551
649
678
739
769
Fugitive Dust
0
0
0
0
0
0
0
0
0
0
TOTAL ALL SOURCES
4,327
4,383
4,440
4,512
4,583
4,658
4,694
4,787
4,885
4,964
Note:
Some columns may not sum to totals due to rounding.
-------
NATIONALAIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-11. National Long-Term Air Quality Trends, 1980-1999
CO Pb N02 Ozone PM10 S02
Year 2nd Max. 8-hr Max. Qtr. Arith. Mean 2nd Max. 1-hr Wtd. Arith. Mean Arith. Mean
ppm
[jg/m3
ppm
ppm
[jg/m3
ppm
1980-89
(304 sites)
(216 sites)
(156 sites)
(441 sites)
—
(438 sites)
1980
8.6
0.65
0.024
0.134
—
0.0103
1981
8.4
0.54
0.024
0.125
—
0.0101
1982
8.1
0.53
0.023
0.124
—
0.0094
1983
7.9
0.40
0.022
0.137
—
0.0091
1984
7.8
0.37
0.023
0.124
—
0.0092
1985
7.1
0.25
0.023
0.122
—
0.0087
1986
7.2
0.15
0.023
0.118
—
0.0085
1987
6.7
0.11
0.023
0.124
—
0.0083
1988
6.5
0.10
0.023
0.135
—
0.0084
1989
6.4
0.08
0.023
0.115
—
0.0081
1990-99
(388 sites)
(175 sites)
(230 sites)
(703 sites)
(954 sites)
(480 sites)
1990
5.8
0.10
0.020
0.112
29.2
0.0081
1991
5.7
0.08
0.019
0.112
29.0
0.0079
1992
5.3
0.06
0.019
0.105
26.8
0.0073
1993
5.0
0.06
0.019
0.108
26.0
0.0072
1994
5.1
0.05
0.020
0.107
26.0
0.0069
1995
4.6
0.05
0.019
0.112
24.8
0.0056
1996
4.3
0.04
0.018
0.105
24.0
0.0056
1997
4.0
0.04
0.018
0.105
23.8
0.0054
1998
3.8
0.04
0.018
0.110
23.6
0.0053
1999
3.7
0.04
0.018
0.107
23.9
0.0052
162 DATA TABLES • APPENDIX A
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-12a. National Air Quality Trends by Monitoring Location, 1980-1989
Statistic # of Sites
Units
Location
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
Carbon Monoxide
2nd Max. 8-hr.
3
ppm
Rural
4.7
4.9
3.8
3.3
4.1
3.8
4.5
3.8
3.5
3.2
2nd Max. 8-hr.
132
ppm
Suburban
8.0
7.8
7.5
7.5
7.3
6.6
6.6
6.4
6.1
6.1
2nd Max. 8-hr.
166
ppm
Urban
9.1
00
00
8.6
8.3
8.2
7.5
7.6
7.0
6.8
6.6
Lead
Max. Qtr.
8
|jg/m3
Rural
0.53
0.49
0.32
0.26
0.24
0.16
0.11
0.10
0.09
0.09
Max. Qtr.
89
|jg/m3
Suburban
0.68
0.56
0.50
0.41
0.36
0.25
0.15
0.11
0.09
0.08
Max. Qtr.
114
|jg/m3
Urban
0.64
0.53
0.57
0.41
0.38
0.25
0.15
0.11
0.09
0.08
Nitrogen Dioxide
Arith. Mean
23
ppm
Rural
0.008
0.009
0.009
0.009
0.009
0.009
0.009
0.009
0.009
0.009
Arith. Mean
75
PPm
Suburban
0.026
0.025
0.024
0.024
0.024
0.024
0.024
0.024
0.025
0.024
Arith. Mean
57
PPm
Urban
0.029
0.028
0.027
0.027
0.028
0.027
0.028
0.027
0.028
0.027
Ozone
2nd Max. 1-hr.
121
PPm
Rural
0.123
0.116
0.113
0.125
0.116
0.114
0.112
0.117
0.129
0.110
2nd Max. 1-hr.
215
PPm
Suburban
0.138
0.130
0.129
0.142
0.128
0.127
0.122
0.129
0.141
0.118
2nd Max. 1-hr.
96
PPm
Urban
0.137
0.126
0.124
0.140
0.126
0.122
0.119
0.125
0.133
0.116
Wtd. Arith. Mean
—
|jg/m3
Rural
—
—
—
—
—
—
—
—
—
—
Wtd. Arith. Mean
—
|jg/m3
Suburban
—
—
—
—
—
—
—
—
—
—
Wtd. Arith. Mean
—
|jg/m3
Urban
—
—
—
—
—
—
—
—
—
—
Sulfur Dioxide
Arith. Mean
117
PPm
Rural
0.0087
0.0083
0.0076
0.0074
0.0076
0.0074
0.0072
0.0070
0.0070
0.0070
Arith. Mean
180
PPm
Suburban
0.0105
0.0101
0.0093
0.0091
0.0094
0.0090
0.0087
0.0084
0.0085
0.0082
Arith. Mean
133
PPm
Urban
0.0116
0.0116
0.0109
0.0104
0.0104
0.0095
0.0096
0.0092
0.0095
0.0092
* PM10 trend data is not available for this 10-year period.
APPENDIX A • DATA TABLES 163
-------
NATIONALAIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-12b. National Air Quality Trends by Monitoring Location, 1990-1999
Statistic # of Sites
Units
Location
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
Carbon Monoxide
2nd Max. 8-hr.
13
ppm
Rural
2.5
2.6
2.3
2.0
2.2
2.3
1.9
1.8
1.7
1.6
2nd Max. 8-hr.
157
ppm
Suburban
5.6
5.4
5.0
4.9
5.0
4.3
4.1
3.9
3.8
3.7
2nd Max. 8-hr.
215
ppm
Urban
6.2
6.1
5.6
5.2
5.4
4.9
4.6
4.3
4.0
3.9
Lead
Max. Qtr.
6
|jg/m3
Rural
0.06
0.06
0.07
0.06
0.05
0.1
0.04
0.03
0.05
0.04
Max. Qtr.
86
|jg/m3
Suburban
0.08
0.06
0.05
0.05
0.04
0.04
0.03
0.03
0.03
0.03
Max. Qtr.
78
|jg/m3
Urban
0.12
0.09
0.07
0.06
0.06
0.05
0.05
0.05
0.05
0.04
Nitrogen Dioxide
Arith. Mean
43
ppm
Rural
0.009
0.009
0.008
0.008
0.008
0.008
0.008
0.008
0.007
0.008
Arith. Mean
105
PPm
Suburban
0.021
0.021
0.020
0.020
0.020
0.020
0.019
0.018
0.019
0.019
Arith. Mean
80
PPm
Urban
0.024
0.024
0.023
0.023
0.024
0.023
0.023
0.022
0.022
0.022
Ozone
2nd Max. 1-hr.
239
PPm
Rural
0.107
0.105
0.101
0.103
0.102
0.108
0.102
0.101
0.107
0.105
2nd Max. 1-hr.
325
PPm
Suburban
0.115
0.117
0.108
0.111
0.111
0.116
0.107
0.108
0.114
0.110
2nd Max. 1-hr.
121
PPm
Urban
0.110
0.110
0.105
0.104
0.106
0.109
0.105
0.102
0.104
0.103
Wtd. Arith. Mean
153
|jg/m3
Rural
23.9
23.2
21.7
20.6
20.8
19.4
19.4
19.0
19.0
19.2
Wtd. Arith. Mean
375
|jg/m3
Suburban
30.1
29.8
27.6
26.8
26.8
25.8
24.6
24.6
24.3
24.8
Wtd. Arith. Mean
408
|jg/m3
Urban
30.5
30.4
28.0
27.3
27.3
26.0
25.1
24.9
24.9
24.9
Sulfur Dioxide
Arith. Mean
123
PPm
Rural
0.0065
0.0063
0.0060
0.0061
0.0058
0.0050
0.0048
0.0046
0.0045
0.0042
Arith. Mean
215
PPm
Suburban
0.0086
0.0084
0.0078
0.0076
0.0072
0.0057
0.0059
0.0057
0.0057
0.0056
Arith. Mean
131
PPm
Urban
0.0092
0.0088
0.0080
0.0077
0.0077
0.0060
0.0059
0.0057
0.0056
0.0055
164 DATA TABLES • APPENDIX A
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-13a. National Air Quality Trends Statistics by EPA Region, 1980-1989
Statistic # of Sites
Units
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
Region 1
CO
2nd Max. 8-hr.
10
ppm
9.4
8.4
8.9
8.5
8.3
6.8
7.2
6.4
5.6
5.6
Pb
Max. Qtr.
15
|jg/m3
0.53
0.49
0.54
0.41
0.33
0.29
0.11
0.08
0.06
0.06
no2
Arith. Mean
4
ppm
0.032
0.030
0.028
0.026
0.032
0.031
0.029
0.030
0.030
0.028
°3
2nd Max. 1-hr.
21
ppm
0.161
0.141
0.151
0.169
0.155
0.139
0.123
0.133
0.160
0.130
°3
4th Max. 8-hr.
21
PPm
0.112
0.100
0.109
0.121
0.106
0.100
0.090
0.095
0.118
0.095
PM10*
Wtd. Arith. Mean
—
|jg/m3
—
—
—
—
—
—
—
—
—
—
so2
Arith. Mean
46
PPm
0.0107
0.0100
0.0099
0.0092
0.0099
0.0095
0.0101
0.0099
0.0100
0.0093
Region 2
CO
2nd Max. 8-hr.
22
PPm
8.9
9.4
8.5
7.8
8.3
6.7
7.4
6.4
6.2
6.1
Pb
Max. Qtr.
7
|jg/m3
0.61
0.62
0.63
0.47
0.53
0.38
0.12
0.08
0.08
0.05
no2
Arith. Mean
7
PPm
0.029
0.029
0.031
0.031
0.030
0.029
0.028
0.029
0.029
0.027
°3
2nd Max. 1-hr.
25
PPm
0.142
0.132
0.133
0.152
0.130
0.130
0.123
0.139
0.158
0.117
°3
4th Max. 8-hr.
25
PPm
0.106
0.098
0.098
0.111
0.096
0.098
0.095
0.104
0.120
0.091
PM10*
Wtd. Arith. Mean
—
|jg/m3
—
—
—
—
—
—
—
—
—
—
so2
Arith. Mean
31
PPm
0.0148
0.0147
0.0135
0.0126
0.0131
0.0117
0.0114
0.0109
0.0119
0.0111
Region 3
CO
2nd Max. 8-hr.
38
PPm
7.0
7.0
7.0
6.9
7.6
5.7
6.2
5.9
5.4
5.3
Pb
Max. Qtr.
29
|jg/m3
0.46
0.39
0.44
0.34
0.34
0.22
0.15
0.12
0.14
0.10
no2
Arith. Mean
36
PPm
0.024
0.023
0.023
0.023
0.024
0.023
0.024
0.024
0.023
0.023
°3
2nd Max. 1-hr.
62
PPm
0.133
0.122
0.125
0.138
0.119
0.118
0.114
0.128
0.150
0.111
O3
4th Max. 8-hr.
62
PPm
0.102
0.095
0.095
0.107
0.092
0.093
0.090
0.100
0.116
0.088
PM10*
Wtd. Arith. Mean
—
|jg/m3
—
—
—
—
—
—
—
—
—
—
so2
Arith. Mean
54
PPm
0.0141
0.0137
0.0130
0.0130
0.0133
0.0124
0.0127
0.0123
0.0130
0.0130
Region 4
CO
2nd Max. 8-hr.
47
PPm
7.9
7.8
7.3
7.4
7.7
6.2
6.1
5.9
5.6
5.9
Pb
Max. Qtr.
39
|jg/m3
0.49
0.41
0.52
0.42
0.37
0.21
0.12
0.10
0.08
0.08
no2
Arith. Mean
8
PPm
0.018
0.019
0.019
0.019
0.018
0.018
0.017
0.018
0.018
0.018
°3
2nd Max. 1-hr.
71
PPm
0.116
0.107
0.105
0.118
0.106
0.104
0.114
0.112
0.123
0.103
°3
4th Max. 8-hr.
71
PPm
0.089
0.082
0.081
0.091
0.082
0.081
0.087
0.088
0.096
0.081
PM10«
Wtd. Arith. Mean
—
|jg/m3
—
—
—
—
—
—
—
—
—
—
so2
Arith. Mean
63
PPm
0.0096
0.0088
0.0078
0.0072
0.0071
0.0071
0.0072
0.0073
0.0076
0.0071
Region 5
CO
2nd Max. 8-hr.
39
PPm
7.5
7.8
7.3
7.0
7.5
5.9
6.2
6.3
5.5
5.6
Pb
Max. Qtr.
48
|jg/m3
0.59
0.48
0.56
0.36
0.31
0.20
0.13
0.10
0.09
0.09
no2
Arith. Mean
17
PPm
0.019
0.020
0.020
0.021
0.021
0.020
0.020
0.021
0.020
0.021
O3
2nd Max. 1-hr.
90
PPm
0.119
0.114
0.112
0.129
0.109
0.106
0.108
0.119
0.131
0.107
O3
4th Max. 8-hr.
90
PPm
0.092
0.088
0.086
0.096
0.083
0.082
0.081
0.090
0.105
0.085
PM10«
Wtd. Arith. Mean
—
|jg/m3
—
—
—
—
—
—
—
—
—
—
so2
Arith. Mean
126
PPm
0.0112
0.0109
0.0102
0.0101
0.0101
0.0095
0.0090
0.0088
0.0086
0.0086
* PM10 trend data is not available for this 10-year period.
APPENDIX A • DATA TABLES 165
-------
NATIONALAIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-13a. National Air Quality Trends Statistics by EPA Region, 1980-1989 (continued)
Statistic ;
# of Sites
Units
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
Region 6
CO
2nd Max. 8-hr.
24
ppm
8.2
8.1
8.0
7.4
7.3
7.3
7.3
7.5
6.5
6.5
Pb
Max. Qtr.
16
|jg/m3
0.74
0.76
0.63
0.56
0.50
0.30
0.16
0.13
0.10
0.08
no2
Arith. Mean
12
ppm
0.017
0.017
0.017
0.017
0.017
0.016
0.017
0.017
0.017
0.015
°3
2nd Max. 1-hr.
34
ppm
0.131
0.127
0.121
0.120
0.123
0.118
0.114
0.117
0.118
0.113
°3
4th Max. 8-hr.
34
PPm
0.093
0.090
0.086
0.086
0.089
0.087
0.083
0.087
0.089
0.083
PM10*
Wtd. Arith. Mean
—
|jg/m3
—
—
—
—
—
—
—
—
—
—
so2
Arith. Mean
29
PPm
0.0066
0.0073
0.0068
0.0076
0.0068
0.0071
0.0063
0.0059
0.0056
0.0056
Region 7
CO
2nd Max. 8-hr.
13
PPm
7.7
7.4
7.3
5.8
6.1
5.2
6.0
5.7
4.9
5.3
Pb
Max. Qtr.
14
|jg/m3
0.31
0.27
0.22
0.20
0.20
0.16
0.10
0.09
0.08
0.08
no2
Arith. Mean
8
PPm
0.016
0.014
0.016
0.015
0.015
0.014
0.015
0.016
0.015
0.015
°3
2nd Max. 1-hr.
20
PPm
0.119
0.104
0.100
0.119
0.115
0.108
0.108
0.113
0.118
0.098
°3
4th Max. 8-hr.
20
PPm
0.087
0.074
0.075
0.090
0.087
0.079
0.077
0.082
0.092
0.077
PM10*
Wtd. Arith. Mean
—
|jg/m3
—
—
—
—
—
—
—
—
—
—
so2
Arith. Mean
17
PPm
0.0094
0.0085
0.0095
0.0093
0.0093
0.0082
0.0083
0.0081
0.0076
0.0079
Region 8
CO
2nd Max. 8-hr.
12
PPm
10.4
10.6
10.2
11.9
10.9
9.5
10.6
9.0
8.9
7.4
Pb
Max. Qtr.
5
|jg/m3
0.90
0.73
0.77
0.64
0.62
0.49
0.22
0.12
0.07
0.06
no2
Arith. Mean
14
PPm
0.013
0.013
0.012
0.013
0.013
0.014
0.014
0.013
0.013
0.013
°3
2nd Max. 1-hr.
13
PPm
0.102
0.101
0.103
0.110
0.104
0.102
0.109
0.097
0.104
0.103
°3
4th Max. 8-hr.
13
PPm
0.074
0.073
0.074
0.078
0.075
0.076
0.076
0.074
0.078
0.077
PM10«
Wtd. Arith. Mean
—
|jg/m3
—
—
—
—
—
—
—
—
—
—
so2
Arith. Mean
20
PPm
0.0064
0.0060
0.0055
0.0048
0.0050
0.0045
0.0043
0.0040
0.0043
0.0041
Region 9
CO
2nd Max. 8-hr.
72
PPm
00
00
8.1
7.9
7.8
7.0
7.8
7.6
6.5
7.2
7.1
Pb
Max. Qtr.
38
|jg/m3
0.84
0.61
0.57
0.44
0.41
0.25
0.19
0.13
0.10
0.09
no2
Arith. Mean
50
PPm
0.031
0.031
0.029
0.027
0.028
0.029
0.029
0.028
0.030
0.029
°3
2nd Max. 1-hr.
99
PPm
0.164
0.152
0.149
0.161
0.151
0.155
0.137
0.141
0.143
0.137
°3
4th Max. 8-hr.
99
PPm
0.109
0.102
0.099
0.107
0.103
0.104
0.097
0.098
0.099
0.095
PM10*
Wtd. Arith. Mean
—
|jg/m3
—
—
—
—
—
—
—
—
—
—
so2
Arith. Mean
47
PPm
0.0051
0.0058
0.0045
0.0041
0.0046
0.0042
0.0036
0.0032
0.0034
0.0032
Region 10
CO
2nd Max. 8-hr.
27
PPm
12.6
11.7
11.4
11.3
10.2
10.4
9.3
9.4
9.2
8.6
Pb
Max. Qtr.
8
|jg/m3
2.05
1.50
0.58
0.47
0.46
0.44
0.24
0.17
0.14
0.12
no2
Arith. Mean
—
PPm
—
—
—
—
—
—
—
—
—
—
O3
2nd Max. 1-hr.
6
PPm
0.095
0.121
0.108
0.093
0.098
0.105
0.107
0.098
0.110
0.089
O3
4th Max. 8-hr.
6
PPm
0.070
0.084
0.075
0.063
0.065
0.074
0.078
0.073
0.072
0.064
PM10«
Wtd. Arith. Mean
|jg/m3
—
—
—
—
—
—
—
—
—
—
so2
Arith. Mean
PPm
0.0120
0.0126
0.0130
0.0115
0.0137
0.0122
0.0116
0.0106
0.0086
0.0079
* PM10 trend data is not available for this 10-year period.
166 DATA TABLES • APPENDIX A
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-13b. National Air Quality Trends Statistics by EPA Region, 1990-1999
Statistic
# of Sites
Units 1990
1991
1992 1993 1994 1995
1996 1997
1998 1999
Region 1
CO
2nd Max. 8-hr.
18
Pb
Max. Qtr.
1
no2
Arith. Mean
14
°3
2nd Max. 1-hr.
42
°3
4th Max. 8-hr.
42
PM10
Wtd. Arith. Mean
69
so2
Arith. Mean
47
Region 2
CO
2nd Max. 8-hr.
28
Pb
Max. Qtr.
4
no2
Arith. Mean
12
°3
2nd Max. 1-hr.
39
°3
4th Max. 8-hr.
39
PM10
Wtd. Arith. Mean
65
so2
Arith. Mean
43
Region 3
CO
2nd Max. 8-hr.
41
Pb
Max. Qtr.
25
no2
Arith. Mean
35
°3
2nd Max. 1-hr.
74
°3
4th Max. 8-hr.
74
PM10
Wtd. Arith. Mean
71
so2
Arith. Mean
76
Region 4
CO
2nd Max. 8-hr.
61
Pb
Max. Qtr.
25
no2
Arith. Mean
29
°3
2nd Max. 1-hr.
131
°3
4th Max. 8-hr.
131
PM10
Wtd. Arith. Mean
146
so2
Arith. Mean
76
Region 5
CO
2nd Max. 8-hr.
43
Pb
Max. Qtr.
44
no2
Arith. Mean
13
°3
2nd Max. 1-hr.
135
O3
4th Max. 8-hr.
135
PM,.
Wtd. Arith. Mean
165
so2
Arith. Mean
111
ppm
6.0
5.5
5.6
4.8
5.9
5.3
4.8
4.1
3.7
3.7
|jg/m3
0.69
0.69
0.19
0.02
0.02
0.04
0.03
0.03
0.02
0.01
ppm
0.022
0.022
0.021
0.022
0.022
0.020
0.020
0.020
0.020
0.019
ppm
0.118
0.127
0.110
0.119
0.114
0.116
0.102
0.116
0.106
0.113
PPm
0.090
0.097
0.086
0.087
0.086
0.089
0.080
0.089
0.083
0.087
|jg/m3
23.0
23.8
20.9
20.4
20.9
18.9
19.5
19.9
19.7
19.4
PPm
0.0080
0.0077
0.0072
0.0069
0.0068
0.0053
0.0052
0.0050
0.0050
0.0047
PPm
5.8
5.8
5.3
4.7
5.5
4.8
4.2
3.7
3.4
3.6
|jg/m3
0.10
0.07
0.06
0.07
0.07
0.06
0.06
0.06
0.06
0.05
PPm
0.030
0.029
0.028
0.028
0.029
0.027
0.028
0.027
0.027
0.027
PPm
0.120
0.122
0.109
0.109
0.105
0.115
0.103
0.111
0.108
0.115
PPm
0.094
0.099
0.085
0.088
0.085
0.095
0.082
0.092
0.088
0.093
|jg/m3
26.5
26.9
24.3
24.4
24.8
22.2
22.9
23.5
22.8
22.4
PPm
0.0090
0.0092
0.0085
0.0078
0.0079
0.0061
0.0062
0.0056
0.0055
0.0054
PPm
5.2
4.7
4.4
4.4
4.7
4.0
3.7
3.5
3.4
3.1
|jg/m3
0.07
0.07
0.06
0.05
0.05
0.04
0.04
0.03
0.03
0.03
PPm
0.022
0.021
0.021
0.021
0.022
0.020
0.021
0.020
0.020
0.019
PPm
0.110
0.117
0.102
0.116
0.111
0.117
0.105
0.116
0.115
0.120
PPm
0.088
0.096
0.083
0.092
0.088
0.094
0.085
0.093
0.095
0.096
|jg/m3
29.4
30.2
26.5
26.6
27.3
26.1
24.9
24.9
24.7
24.0
PPm
0.0124
0.0119
0.0110
0.0111
0.0111
0.0084
0.0084
0.0088
0.0085
0.0080
PPm
5.2
4.9
4.9
5.0
4.7
4.3
3.8
4.0
3.7
3.7
|jg/m3
0.05
0.05
0.05
0.04
0.04
0.04
0.03
0.02
0.03
0.03
PPm
0.014
0.013
0.014
0.014
0.014
0.014
0.014
0.014
0.014
0.014
PPm
0.103
0.096
0.095
0.103
0.099
0.104
0.101
0.102
0.111
0.109
PPm
0.082
0.075
0.076
0.081
0.080
0.082
0.081
0.082
0.090
0.089
|jg/m3
29.3
28.2
26.4
25.7
25.4
24.8
23.8
23.7
24.4
23.8
PPm
0.0059
0.0056
0.0053
0.0054
0.0050
0.0042
0.0044
0.0044
0.0045
0.0044
PPm
5.1
4.8
4.5
4.4
5.2
4.1
3.4
3.2
3.3
3.0
|jg/m3
0.16
0.10
0.08
0.08
0.08
0.07
0.06
0.06
0.05
0.05
PPm
0.021
0.021
0.022
0.022
0.023
0.023
0.023
0.022
0.022
0.022
PPm
0.102
0.110
0.098
0.097
0.104
0.110
0.103
0.101
0.105
0.105
PPm
0.082
0.088
0.079
0.077
0.083
0.089
0.085
0.083
0.085
0.088
|jg/m3
30.4
29.7
27.5
26.2
27.8
27.0
24.5
24.6
26.0
24.8
PPm
0.0094
0.0093
0.0081
0.0083
0.0077
0.0061
0.0062
0.0059
0.0059
0.0059
APPENDIX A • DATA TABLES
167
-------
NATIONALAIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-13b. National Air Quality Trends Statistics by EPA Region, 1990-1999 (continued)
Statistic
# of Sites
Region 6
CO
2nd Max. 8-hr.
29
Pb
Max. Qtr.
17
no2
Arith. Mean
24
°3
2nd Max. 1-hr.
71
°3
4th Max. 8-hr.
71
PM10
Wtd. Arith. Mean
86
so2
Arith. Mean
27
Region 7
CO
2nd Max. 8-hr.
22
Pb
Max. Qtr.
19
no2
Arith. Mean
12
°3
2nd Max. 1-hr.
29
°3
4th Max. 8-hr.
29
PM10
Wtd. Arith. Mean
50
so2
Arith. Mean
28
Region 8
CO
2nd Max. 8-hr.
22
Pb
Max. Qtr.
8
no2
Arith. Mean
12
°3
2nd Max. 1-hr.
19
°3
4th Max. 8-hr.
19
PM10
Wtd. Arith. Mean
112
so2
Arith. Mean
27
Region 9
CO
2nd Max. 8-hr.
97
Pb
Max. Qtr.
27
no2
Arith. Mean
79
°3
2nd Max. 1-hr.
152
°3
4th Max. 8-hr.
152
PM10
Wtd. Arith. Mean
120
so2
Arith. Mean
36
Region 10
CO
2nd Max. 8-hr.
27
Pb
Max. Qtr.
5
no2
Arith. Mean
—
°3
2nd Max. 1-hr.
14
°3
4th Max. 8-hr.
14
PM,„
Wtd. Arith. Mean
70
so2
Arith. Mean
9
Units
1990
1991
1992
ppm
6.3
5.7
5.6
|jg/m3
0.14
0.13
0.10
ppm
0.014
0.014
0.015
ppm
0.121
0.113
0.109
PPm
0.086
0.080
0.079
|jg/m3
26.3
24.7
24.7
PPm
0.0067
0.0063
0.0066
PPm
4.9
5.0
4.4
|jg/m3
0.03
0.03
0.02
PPm
0.015
0.015
0.016
PPm
0.091
0.093
0.092
PPm
0.071
0.076
0.074
|jg/m3
30.3
29.6
29.0
PPm
0.0078
0.0074
0.0066
PPm
6.6
6.7
6.7
|jg/m3
0.07
0.07
0.06
PPm
0.012
0.012
0.013
PPm
0.090
0.088
0.084
PPm
0.068
0.069
0.066
|jg/m3
24.2
25.2
24.0
PPm
0.0061
0.0058
0.0064
PPm
6.1
6.0
5.1
|jg/m3
0.07
0.06
0.04
PPm
0.022
0.022
0.021
PPm
0.128
0.127
0.125
PPm
0.091
0.091
0.091
|jg/m3
37.8
36.8
32.1
PPm
0.0021
0.0021
0.0020
PPm
8.2
8.4
7.7
|jg/m3
0.06
0.06
0.04
PPm
—
—
—
PPm
0.100
0.088
0.089
PPm
0.073
0.065
0.069
|jg/m3
31.1
31.9
30.4
PPm
0.0071
0.0070
0.0073
1992 1993 1994 1995
1996 1997
1998 1999
5.6
0.10
0.014
0.111
0.080
24.0
0.0055
4.3
0.02
0.015
0.088
0.066
27.9
0.0065
5.7
0.06
0.013
0.082
0.089
22.8
0.0062
4.7
0.04
0.020
0.121
0.088
31.1
0.0018
7.1
0.05
0.081
0.058
29.9
0.0066
4.8
0.07
0.015
0.110
0.082
24.2
0.0048
4.2
0.01
0.016
0.099
0.079
28.7
0.0066
5.3
0.04
0.014
0.085
0.096
22.4
0.0055
5.1
0.03
0.021
0.117
0.087
30.2
0.0018
6.8
0.05
0.088
0.063
26.4
0.0066
4.5
0.10
0.015
0.121
0.090
25.2
0.0047
4.0
0.01
0.016
0.102
0.081
28.3
0.0054
4.9
0.04
0.013
0.085
0.066
19.6
0.0049
4.5
0.03
0.020
0.120
0.088
30.1
0.0018
6.6
0.05
0.086
0.063
23.0
0.0059
5.1
0.09
0.015
0.110
0.082
24.3
0.0049
4.1
0.02
0.016
0.094
0.076
28.3
0.0051
4.9
0.03
0.013
0.088
0.068
19.9
0.0041
4.3
0.03
0.019
0.115
0.088
28.3
0.0018
6.5
0.04
0.097
0.076
23.0
0.0051
4.5
0.05
0.015
0.114
0.083
22.7
0.0044
3.7
0.03
0.016
0.095
0.076
26.4
0.0047
4.6
0.03
0.013
0.083
0.066
19.0
0.0034
4.0
0.03
0.018
0.103
0.078
28.8
0.0018
6.1
0.05
0.076
0.058
23.2
0.0047
4.1
0.06
0.014
0.116
0.086
23.8
3.7
0.04
0.014
0.112
0.086
25.0
0.0043 0.0038
4.2
0.04
0.016
0.100
0.078
26.1
3.4
0.04
0.017
0.101
0.080
26.7
0.0045 0.0047
3.9
0.04
0.013
0.093
0.074
19.1
0.0031
3.9
0.02
0.018
0.114
0.085
26.3
3.9
0.04
0.013
0.086
0.067
18.7
0.0031
3.9
0.03
0.019
0.103
0.079
30.5
0.0018 0.0019
5.5
0.06
0.098
0.069
20.7
5.6
0.04
0.073
0.058
20.8
0.0047 0.0050
168
DATA TABLES • APPENDIX A
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-14. Maximum Air Quality Concentrations by County, 1999
CO
Pb
no2
°3
°3
PM10
PM10
S02
S02
State County
1990
8-hr
QMax
AM
1-hr
8-hr
Wtd AM
2nd Max
AM
24-hr
Population
(ppm)
(jjg/m3)
(PP"i)
(PP"i)
(PP"i)
(jjg/m3)
(jjg/m3)
(ppm)
(ppm)
AL
CALHOUN CO
116,034
ND
ND
ND
ND
ND
ND
IN
ND
ND
AL
CLAY CO
13,252
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
AL
COLBERT CO
51,666
ND
ND
ND
ND
ND
ND
IN
0.003
0.017
AL
DE KALB CO
54,651
ND
ND
ND
ND
ND
24
48
ND
ND
AL
ELMORE CO
49,210
ND
ND
ND
0.10
0.08
ND
ND
ND
ND
AL
ESCAMBIA CO
35,518
ND
ND
ND
ND
ND
25
53
ND
ND
AL
ETOWAH CO
99,840
ND
ND
ND
ND
ND
30
66
ND
ND
AL
FRANKLIN CO
27,814
ND
ND
ND
ND
ND
ND
IN
ND
ND
AL
HOUSTON CO
81,331
ND
ND
ND
ND
ND
IN
IN
ND
ND
AL
JACKSON CO
47,796
ND
ND
ND
ND
ND
ND
ND
0.005
0.026
AL
JEFFERSON CO
651,525
5
ND
ND
0.13
0.09
IN
108
IN
0.026
AL
LAWRENCE CO
31,513
ND
ND
ND
0.10
0.09
ND
ND
0.002
0.011
AL
LIMESTONE CO
54,135
ND
ND
ND
ND
ND
ND
IN
ND
ND
AL
MADISON CO
238,912
4
ND
ND
0.11
0.09
24*
54*
ND
ND
AL
MARENGO CO
23,084
ND
ND
ND
ND
ND
29
55
ND
ND
AL
MOBILE CO
378,643
ND
ND
ND
0.12
0.09
25
84
0.008
0.041
AL
MONTGOMERY CO
209,085
ND
ND
ND
0.11
0.09
24
48
ND
ND
AL
MORGAN CO
100,043
ND
ND
ND
ND
ND
IN
43
ND
ND
AL
PIKE CO
27,595
ND
0.83
ND
ND
ND
23
40
ND
ND
AL
RUSSELL CO
46,860
ND
ND
ND
ND
ND
IN
49
ND
ND
AL
SHELBY CO
99,358
ND
ND
0.010
0.12
0.10
28
57
ND
ND
AL
SUMTER CO
16,174
ND
ND
ND
0.09
0.07
ND
ND
ND
ND
AL
TALLADEGA CO
74,107
ND
ND
ND
ND
ND
26
59
ND
ND
AL
TUSCALOOSA CO
150,522
ND
ND
ND
ND
ND
28
61
ND
ND
AL
WALKER CO
67,670
ND
ND
ND
ND
ND
25
56
ND
ND
AK
ANCHORAGE BOROUGH
226,338
8
ND
ND
ND
ND
19*
73*
ND
ND
AK
FAIRBANKS NORTH STAR BOROUGH
77,720
10
ND
ND
ND
ND
IN
51
ND
ND
AK
JUNEAU BOROUGH
26,751
ND
ND
ND
ND
ND
IN
27
ND
ND
AK
MATANUSKA-SUSITNA BOROUGH
39,683
ND
ND
ND
ND
ND
16
149
ND
ND
AK
YUKON-KOYUKUK CA
8,478
ND
ND
ND
0.06
0.05
ND
ND
ND
ND
AZ
COCHISE CO
97,624
ND
ND
ND
0.08
0.07
IN
IN*
ND
ND
AZ
COCONINO CO
96,591
ND
ND
ND
0.09
0.08
IN
IN
ND
ND
AZ
GILA CO
40,216
ND
ND
ND
0.09
0.08
IN
IN
ND
ND
AZ
GRAHAM CO
26,554
ND
ND
ND
ND
ND
IN
IN*
ND
ND
AZ
MARICOPA CO
2,122,101
8
ND
0.041
0.12
0.09
60
219
0.003
0.014
AZ
NAVAJO CO
77,658
ND
ND
ND
ND
ND
IN
IN
ND
ND
AZ
PIMA CO
666,880
4
ND
0.019
0.09
0.07
49*
207*
0.002
0.005
AZ
PINAL CO
116,379
ND
ND
ND
ND
ND
ND
ND
IN
0.018
AZ
SANTA CRUZ CO
29,676
ND
ND
ND
ND
ND
IN
IN*
ND
ND
AZ
YAVAPAI CO
107,714
ND
ND
ND
0.09
0.08
IN
IN
ND
ND
AZ
YUMACO
106,895
ND
ND
ND
0.09
0.08
IN
IN*
ND
ND
AR
ARKANSAS CO
21,653
ND
ND
ND
ND
ND
IN
IN*
ND
ND
AR
ASHLEY CO
24,319
ND
ND
ND
ND
ND
IN
IN*
ND
ND
AR
CRAIGHEAD CO
68,956
ND
ND
ND
ND
ND
IN
IN*
ND
ND
AR
CRITTENDEN CO
49,939
ND
ND
ND
0.13
0.10
IN
IN*
ND
ND
AR
GARLAND CO
73,397
ND
ND
ND
ND
ND
IN
IN*
ND
ND
AR
JEFFERSON CO
85,487
ND
ND
ND
ND
ND
IN
IN*
ND
ND
AR
MARION CO
12,001
ND
ND
ND
ND
ND
IN
IN*
ND
ND
AR
MILLER CO
38,467
ND
ND
ND
ND
ND
IN
IN*
IN
0.019
AR
MONTGOMERYCO
7,841
ND
ND
ND
0.09
0.07
ND
ND
ND
ND
AR
NEWTON CO
7,666
ND
ND
ND
0.09
0.08
ND
ND
ND
ND
AR
OUACHITA CO
30,574
ND
ND
ND
ND
ND
IN
IN*
ND
ND
AR
PHILLIPS CO
28,838
ND
ND
ND
ND
ND
IN
IN*
ND
ND
AR
POLK CO
17,347
ND
ND
ND
ND
ND
IN
IN
ND
ND
AR
POPE CO
45,883
ND
ND
ND
ND
ND
IN
IN*
ND
ND
APPENDIX A • DATA TABLES
169
-------
NATIONALAIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-14. Maximum Air Quality Concentrations by County, 1999 (continued)
CO
Pb
no2
°3
°3
PM10
PM10
S02
S02
State County
1990
8-hr
QMax
AM
1-hr
8-hr
Wtd AM
2nd Max
AM
24-hr
Population
(ppm)
(jjg/m3)
(PP"i)
(PP"i)
(PP"i)
(jjg/m3)
(jjg/m3)
(ppm)
(ppm)
AR
PULASKI CO
349,660
4
ND
0.011
0.11
0.09
CM
CO
70*
0.002
0.005
AR
SEBASTIAN CO
99,590
ND
ND
ND
ND
ND
IN
IN*
ND
ND
AR
UNION CO
46,719
ND
ND
ND
ND
ND
IN
IN*
0.005
0.022
AR
WASHINGTON CO
113,409
ND
ND
ND
ND
ND
IN
IN*
ND
ND
AR
WHITE CO
54,676
ND
ND
ND
ND
ND
IN
IN*
ND
ND
CA
ALAMEDA CO
1,279,182
5
0.00
0.022
0.14
0.09
26*
CD
ND
ND
CA
AMADOR CO
30,039
1
ND
ND
0.12
0.10
ND
ND
ND
ND
CA
BUTTE CO
182,120
4
0.00
0.015
0.11
0.09
CM
CO
CD
ND
ND
CA
CALAVERAS CO
31,998
1
ND
ND
0.12
0.10
21*
^r
CD
ND
ND
CA
COLUSA CO
16,275
ND
ND
ND
0.09
0.08
30
138
ND
ND
CA
CONTRA COSTA CO
803,732
3
0.00
0.018
0.13
0.09
26*
89*
0.003
0.020
CA
DEL NORTE CO
23,460
ND
ND
ND
ND
ND
18
39
ND
ND
CA
EL DORADO CO
125,995
2
ND
0.011
0.14
0.10
21*
CM
ND
ND
CA
FRESNO CO
667,490
8
0.00
0.024
0.15
0.11
47*
o
CO
ND
ND
CA
GLENN CO
24,798
ND
ND
ND
0.10
0.08
26
121
ND
ND
CA
HUMBOLDT CO
119,118
ND
ND
ND
ND
ND
19*
51*
ND
ND
CA
IMPERIAL CO
109,303
14
0.00
0.018
0.17
0.09
85
369
0.003
0.013
CA
INYO CO
18,281
ND
ND
ND
0.09
0.08
51*
CD
OO
ND
ND
CA
KERN CO
543,477
4
0.00
0.025
0.14
0.11
61*
CM
IN
0.006
CA
KINGS CO
101,469
ND
ND
0.016
0.13
0.10
54
146
ND
ND
CA
LAKE CO
50,631
ND
ND
ND
0.09
0.07
IN
28
ND
ND
CA
LASSEN CO
27,598
ND
ND
ND
ND
ND
IN
96
ND
ND
CA
LOS ANGELES CO
8,863,164
11
0.09
0.051
0.14
0.10
56
119
0.005
0.019
CA
MADERA CO
88,090
ND
ND
0.014
0.10
0.09
ND
ND
ND
ND
CA
MARIN CO
230,096
3
ND
0.018
0.10
0.06
CM
CM
CD
CD
ND
ND
CA
MARIPOSA CO
14,302
ND
ND
ND
0.11
0.10
IN
IN
ND
ND
CA
MENDOCINO CO
80,345
4
ND
0.010
0.08
0.06
LO
CM
67*
ND
ND
CA
MERCED CO
178,403
ND
ND
0.012
0.13
0.11
IN
IN
ND
ND
CA
MODOC CO
9,678
ND
ND
ND
ND
ND
26
73
ND
ND
CA
MONO CO
9,956
ND
ND
ND
ND
ND
IN
33
ND
ND
CA
MONTEREY CO
355,660
2
ND
0.010
0.08
0.06
29
76
ND
ND
CA
NAPA CO
110,765
3
ND
0.014
0.11
0.08
19*
^r
LO
ND
ND
CA
NEVADA CO
78,510
ND
ND
ND
0.11
0.09
25
78
ND
ND
CA
ORANGE CO
2,410,556
6
ND
0.035
0.11
0.08
37
73
0.002
0.005
CA
PLACER CO
172,796
2
0.00
0.012
0.13
0.10
27*
CM
ND
ND
CA
PLUMAS CO
19,739
ND
ND
ND
0.08
0.07
27*
CO
O
ND
ND
CA
RIVERSIDE CO
1,170,413
4
0.05
0.025
0.14
0.12
72
134
0.002
0.009
CA
SACRAMENTO CO
1,041,219
6
ND
0.021
0.14
0.11
^r
CO
CO
0.004
0.012
CA
SAN BENITO CO
36,697
ND
ND
ND
0.11
0.08
CO
CM
CO
LO
ND
ND
CA
SAN BERNARDINO CO
1,418,380
4
0.05
0.039
0.16
0.13
60
108
0.002
0.009
CA
SAN DIEGO CO
2,498,016
5
0.00
0.026
0.11
0.09
52
114
0.003
0.016
CA
SAN FRANCISCO CO
723,959
5
0.00
0.021
0.07
0.05
27*
70*
0.002
0.006
CA
SAN JOAQUIN CO
480,628
6
0.00
0.024
0.13
0.09
37*
CO
CM
ND
ND
CA
SAN LUIS OBISPO CO
217,162
3
ND
0.013
0.09
0.08
27
82
0.005
0.027
CA
SAN MATEO CO
649,623
4
ND
0.019
0.08
0.05
27*
75*
ND
ND
CA
SANTA BARBARA CO
369,608
4
0.00
0.022
0.10
0.08
CM
^r
LO
0.002
0.003
CA
SANTA CLARA CO
1,497,577
6
0.00
0.026
0.12
0.08
CM
CD
ND
ND
CA
SANTA CRUZ CO
229,734
1
ND
0.005
0.08
0.07
CM
CO
75*
0.001
0.002
CA
SHASTA CO
147,036
ND
ND
ND
0.11
0.09
IN
42
ND
ND
CA
SIERRA CO
3,318
ND
ND
ND
ND
ND
25
53
ND
ND
CA
SISKIYOU CO
43,531
ND
ND
ND
0.07
0.06
17
47
ND
ND
CA
SOLANO CO
340,421
5
ND
0.014
0.12
0.09
20*
^r
CD
0.002
0.006
CA
SONOMACO
388,222
3
ND
0.014
0.10
0.08
19*
LO
CD
ND
ND
CA
STANISLAUS CO
370,522
6
0.00
0.022
0.11
0.09
43
137
ND
ND
CA
SUTTER CO
64,415
4
ND
0.014
0.11
0.08
CO
CD
CD
LO
ND
ND
170
DATA TABLES • APPENDIX A
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-14. Maximum Air Quality Concentrations by County, 1999 (continued)
CO Pb N02 03 03 PM10 PM10 S02 S02
State County 1990 8-hr QMax AM 1-hr 8-hr WtdAM 2nd Max AM 24-hr
Population (ppm) ((jg/m3) (ppm) (ppm) (ppm) (ng/m3) (ng/m3) (ppm) (ppm)
CA
TEHAMACO
49,625
ND
ND
ND
0.11
0.10
IN
IN
ND
ND
CA
TRINITY CO
13,063
ND
ND
ND
ND
ND
IN
78
ND
ND
CA
TULARE CO
311,921
4
ND
0.021
0.13
0.11
56*
137*
ND
ND
CA
TUOLUMNE CO
48,456
3
ND
ND
0.11
0.10
ND
ND
ND
ND
CA
VENTURA CO
669,016
3
0.00
0.022
0.13
0.10
32*
63*
0.002
0.005
CA
YOLO CO
141,092
1
ND
0.012
0.12
0.09
33
144
ND
ND
CO
ADAMS CO
265,038
4
0.08
0.020
0.09
0.07
37*
142*
0.003
0.012
CO
ALAMOSA CO
13,617
ND
ND
ND
ND
ND
IN
129
ND
ND
CO
ARAPAHOE CO
391,511
ND
ND
ND
0.10
0.08
ND
ND
ND
ND
CO
ARCHULETA CO
5,345
ND
ND
ND
ND
ND
IN
82
ND
ND
CO
BOULDER CO
225,339
4
ND
ND
0.10
0.08
IN
56
ND
ND
CO
DELTA CO
20,980
ND
ND
ND
ND
ND
26*
57*
ND
ND
CO
DENVER CO
467,610
5
0.02
IN
0.09
0.07
29*
83*
IN
0.014
CO
DOUGLAS CO
60,391
ND
ND
ND
0.09
0.08
IN
24
ND
ND
CO
EAGLE CO
21,928
ND
ND
ND
ND
ND
IN
36
ND
ND
CO
EL PASO CO
397,014
5
0.01
0.019
0.08
0.06
23*
80*
0.004
0.020
CO
FREMONT CO
32,273
ND
ND
ND
ND
ND
15*
41*
ND
ND
CO
GARFIELD CO
29,974
ND
ND
ND
ND
ND
IN
51
ND
ND
CO
GUNNISON CO
10,273
ND
ND
ND
ND
ND
30
111
ND
ND
CO
JEFFERSON CO
438,430
4
ND
0.010
0.11
0.08
14*
35*
ND
ND
CO
LAKE CO
6,007
ND
0.02
ND
ND
ND
ND
ND
ND
ND
CO
LA PLATA CO
32,284
ND
ND
ND
ND
ND
36
98
ND
ND
CO
LARIMER CO
186,136
5
ND
ND
0.09
0.07
16*
36*
ND
ND
CO
MESA CO
93,145
5
ND
ND
ND
ND
20
52
ND
ND
CO
MONTEZUMA CO
18,672
ND
ND
ND
0.08
0.07
ND
ND
ND
ND
CO
MONTROSE CO
24,423
ND
ND
ND
ND
ND
IN
88
ND
ND
CO
PITKIN CO
12,661
ND
ND
ND
ND
ND
31
73
ND
ND
CO
PROWERS CO
13,347
ND
ND
ND
ND
ND
29*
145*
ND
ND
CO
PUEBLO CO
123,051
ND
ND
ND
ND
ND
IN
51
ND
ND
CO
ROUTT CO
14,088
ND
ND
ND
ND
ND
IN
109
ND
ND
CO
SAN MIGUEL CO
3,653
ND
ND
ND
ND
ND
IN
66
ND
ND
CO
SUMMIT CO
12,881
ND
ND
ND
ND
ND
18*
54*
ND
ND
CO
TELLER CO
12,468
ND
ND
ND
ND
ND
IN
93
ND
ND
CO
WELD CO
131,821
3
ND
ND
0.09
0.07
18*
47*
ND
ND
CT
FAIRFIELD CO
827,645
4
ND
0.018
0.15
0.11
29*
49*
0.006
0.026
CT
HARTFORD CO
851,783
6
ND
0.018
0.13
0.09
18
81
0.004
0.019
CT
LITCHFIELD CO
174,092
ND
ND
ND
0.13
0.10
16*
41*
ND
ND
CT
MIDDLESEX CO
143,196
ND
ND
ND
0.16
0.11
ND
ND
ND
ND
CT
NEW HAVEN CO
804,219
3
0.01
0.026
0.15
0.11
27*
76*
0.007
0.027
CT
NEW LONDON CO
254,957
ND
ND
ND
0.13
0.10
17
36
IN
0.008
CT
TOLLAND CO
128,699
ND
ND
IN
0.12
0.09
ND
ND
IN
0.009
CT
WINDHAM CO
102,525
ND
ND
ND
ND
ND
ND
IN
ND
ND
DE
KENT CO
110,993
ND
ND
ND
0.12
0.10
ND
ND
ND
ND
DE
NEW CASTLE CO
441,946
3
ND
0.018
0.14
0.10
24*
49*
0.008
0.049
DE
SUSSEX CO
113,229
ND
ND
ND
0.12
0.10
ND
ND
ND
ND
DC
WASHINGTON
606,900
6
0.03
0.024
0.13
0.10
IN
IN
0.008
0.020
FL
ALACHUA CO
181,596
ND
ND
ND
0.10
0.08
22*
39*
ND
ND
FL
BAKER CO
18,486
ND
ND
ND
0.08
0.08
ND
ND
ND
ND
FL
BAY CO
126,994
ND
ND
ND
ND
ND
IN
50
ND
ND
FL
BREVARD CO
398,978
ND
ND
ND
0.09
0.08
20*
53*
ND
ND
FL
BROWARD CO
1,255,488
5
0.02
0.011
0.10
0.08
19*
34*
0.003
0.015
FL
COLLIER CO
152,099
ND
ND
ND
ND
ND
17
30
ND
ND
FL
DADE CO
1,937,094
4
ND
0.017
0.11
0.08
25*
45*
0.001
0.003
FL
DUVAL CO
672,971
4
0.02
0.016
0.10
0.08
28
53
0.004
0.020
FL
ESCAMBIA CO
262,798
ND
ND
IN
0.11
0.09
24*
57*
0.004
0.029
APPENDIX A • DATA TABLES
171
-------
NATIONALAIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-14. Maximum Air Quality Concentrations by County, 1999 (continued)
CO
Pb
no2
°3
°3
PM10
PM10
S02
S02
State County
1990
8-hr
QMax
AM
1-hr
8-hr
Wtd AM
2nd Max
AM
24-hr
Population
(ppm)
(jjg/m3)
(PP"i)
(PP"i)
(PP"i)
(jjg/m3)
(jjg/m3)
(ppm)
(ppm)
FL GULF CO
11,504
ND
ND
ND
ND
ND
IN
IN
ND
ND
FL HAMILTON CO
10,930
ND
ND
ND
ND
ND
25*
40*
0.004
0.013
FL HILLSBOROUGH CO
834,054
5
1.02
0.010
0.12
0.09
35
81
0.008
0.060
FL HOLMES CO
15,778
ND
ND
ND
0.10
0.08
ND
ND
ND
ND
FL LAKE CO
152,104
ND
ND
ND
ND
ND
19
49
ND
ND
FL LEE CO
335,113
ND
ND
ND
0.10
0.08
19
32
ND
ND
FL LEON CO
192,493
ND
ND
ND
0.09
0.08
19
55
ND
ND
FL MANATEE CO
211,707
ND
ND
0.007
0.11
0.08
24
42
0.004
0.017
FL MARION CO
194,833
ND
ND
ND
0.10
0.08
ND
ND
ND
ND
FL MONROE CO
78,024
ND
ND
ND
ND
ND
15
30
ND
ND
FL NASSAU CO
43,941
ND
ND
ND
ND
ND
28*
cn
CD
0.004
0.036
FL ORANGE CO
677,491
3
ND
0.012
0.10
0.08
27*
LO
0.002
0.007
FL OSCEOLA CO
107,728
ND
ND
ND
0.10
0.08
ND
ND
ND
ND
FL PALM BEACH CO
863,518
3
0.00
0.013
0.10
0.08
o
CM
CO
CO
0.002
0.013
FL PASCO CO
281,131
ND
ND
ND
0.09
0.08
ND
ND
ND
ND
FL PINELLAS CO
851,659
3
0.01
0.016
0.11
0.09
LO
CM
CD
0.007
0.038
FL POLK CO
405,382
ND
ND
ND
0.10
0.08
22
50
0.007
0.019
FL PUTNAM CO
65,070
ND
ND
ND
ND
ND
LO
CM
LO
0.003
0.015
FL ST LUCIE CO
150,171
ND
ND
0.010
0.08
0.07
20
39
ND
ND
FL SARASOTA CO
277,776
3
ND
ND
0.11
0.09
o
CM
CM
0.002
0.011
FL SEMINOLE CO
287,529
ND
ND
ND
0.10
0.08
IN
IN
ND
ND
FL VOLUSIA CO
370,712
ND
ND
ND
0.09
0.08
21*
57*
ND
ND
GA BARTOW CO
55,911
ND
ND
ND
ND
ND
ND
ND
0.003
0.012
GA BIBB CO
149,967
ND
ND
ND
0.13
0.11
IN
53
ND
ND
GA CHATHAM CO
216,935
ND
ND
ND
0.11
0.08
27
59
0.003
0.018
GA CHATTOOGA CO
22,242
ND
ND
ND
ND
ND
22
59
ND
ND
GA CHEROKEE CO
90,204
ND
ND
ND
0.10
IN
ND
ND
ND
ND
GA COBB CO
447,745
ND
ND
ND
0.11
ND
ND
ND
ND
ND
GA COWETACO
53,853
ND
ND
ND
0.13
0.11
ND
ND
ND
ND
GA DAWSON CO
9,429
ND
ND
ND
0.10
0.09
ND
ND
ND
ND
GA DEKALB CO
545,837
4
0.05
0.020
0.15
0.11
23
44
ND
ND
GA DOUGHERTY CO
96,311
ND
ND
ND
ND
ND
26
60
ND
ND
GA DOUGLAS CO
71,120
ND
ND
ND
0.12
0.11
IN
47
ND
ND
GA FANNIN CO
15,992
ND
ND
ND
0.10
0.08
ND
ND
0.004
0.018
GA FAYETTE CO
62,415
ND
ND
ND
0.13
0.11
ND
ND
ND
ND
GA FLOYD CO
81,251
ND
ND
ND
ND
ND
IN
IN
0.003
0.021
GA FULTON CO
648,951
3
ND
0.024
0.16
0.12
35
72
0.005
0.023
GA GLYNN CO
62,496
ND
ND
ND
0.09
0.08
26
45
ND
ND
GA GWINNETT CO
352,910
ND
ND
ND
0.13
0.10
ND
ND
ND
ND
GA HENRY CO
58,741
ND
ND
ND
0.15
0.13
ND
ND
ND
ND
GA MUSCOGEE CO
179,278
ND
1.04
ND
0.11
0.10
24
45
ND
ND
GA PAULDING CO
41,611
ND
ND
0.007
0.12
0.10
ND
ND
ND
ND
GA RICHMOND CO
189,719
ND
ND
ND
0.11
0.09
IN
49
ND
ND
GA ROCKDALE CO
54,091
ND
ND
0.007
0.16
0.12
ND
ND
ND
ND
GA SPALDING CO
54,457
ND
ND
ND
ND
ND
IN
IN
ND
ND
GA SUMTER CO
30,228
ND
ND
ND
0.10
0.08
ND
ND
ND
ND
GA WALKER CO
58,340
ND
ND
ND
ND
ND
26
57
ND
ND
GA WASHINGTON CO
19,112
ND
ND
ND
ND
ND
27
59
ND
ND
HI HONOLULU CO
836,231
2
ND
0.004
0.05
0.05
15
41
0.001
0.004
HI KAUAI CO
51,177
ND
ND
ND
ND
ND
IN
26
ND
ND
HI MAUI CO
100,374
ND
ND
ND
ND
ND
22
97
ND
ND
ID ADA CO
205,775
5
ND
0.021
ND
ND
31
106
ND
ND
ID BANNOCK CO
66,026
ND
ND
IN
ND
ND
o
CO
176*
0.007
0.046
ID BLAINE CO
13,552
ND
ND
ND
ND
ND
CD
CM
cn
CD
ND
ND
ID BONNER CO
26,622
ND
ND
ND
ND
ND
21
64
ND
ND
172
DATA TABLES • APPENDIX A
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-14. Maximum Air Quality Concentrations by County, 1999 (continued)
CO Pb N02 03 03 PM10 PM10 S02 S02
State County 1990 8-hr QMax AM 1-hr 8-hr WtdAM 2nd Max AM 24-hr
Population (ppm) ((jg/m3) (ppm) (ppm) (ppm) (ng/m3) (ng/m3) (ppm) (ppm)
ID
BONNEVILLE CO
72,207
ND
ND
ND
ND
ND
IN
IN
ND
ND
ID
BUTTE CO
2,918
ND
ND
ND
0.08
0.07
ND
ND
ND
ND
ID
CANYON CO
90,076
6
ND
ND
ND
ND
CD
CO
101*
ND
ND
ID
CARIBOU CO
6,963
ND
ND
ND
ND
ND
LO
CM
78*
0.004
0.047
ID
KOOTENAI CO
69,795
ND
ND
ND
ND
ND
CM
CM
97*
ND
ND
ID
LEMHI CO
6,899
ND
ND
ND
ND
ND
37*
CD
cn
ND
ND
ID
LEWIS CO
3,516
ND
ND
ND
ND
ND
IN
72
ND
ND
ID
MADISON CO
23,674
ND
ND
ND
ND
ND
CD
CM
74*
ND
ND
ID
MINIDOKA CO
19,361
ND
ND
ND
ND
ND
LO
CM
CO
CD
ND
ND
ID
NEZ PERCE CO
33,754
5
ND
ND
ND
ND
31*
LO
CD
ND
ND
ID
SHOSHONE CO
13,931
ND
0.05
ND
ND
ND
19
75
ND
ND
ID
TWIN FALLS CO
53,580
ND
ND
ND
ND
ND
^r
CM
^r
LO
ND
ND
IL
ADAMS CO
66,090
ND
ND
ND
0.09
0.08
21
46
0.005
0.033
IL
CHAMPAIGN CO
173,025
ND
ND
ND
0.11
0.09
23
47
0.002
0.010
IL
COOK CO
5,105,067
5
0.06
0.032
0.11
0.10
40
120
0.009
0.044
IL
DU PAGE CO
781,666
ND
ND
ND
0.09
0.08
ND
IN
0.004
0.019
IL
EFFINGHAM CO
31,704
ND
ND
ND
0.10
0.09
ND
ND
ND
ND
IL
HAMILTON CO
8,499
ND
ND
ND
0.10
0.08
ND
ND
ND
ND
IL
JACKSON CO
61,067
ND
ND
ND
ND
ND
22
55
ND
ND
IL
JERSEY CO
20,539
ND
ND
ND
0.13
0.10
ND
ND
ND
ND
IL
KANE CO
317,471
ND
ND
ND
0.09
0.08
IN
42
ND
ND
IL
LAKE CO
516,418
ND
ND
IN
0.11
0.09
ND
ND
ND
ND
IL
LA SALLE CO
106,913
ND
ND
ND
ND
ND
28
149
ND
ND
IL
MCHENRY CO
183,241
ND
ND
ND
0.10
0.09
ND
ND
ND
ND
IL
MACON CO
117,206
ND
ND
ND
0.10
0.09
ND
IN
0.006
0.027
IL
MACOUPIN CO
47,679
ND
0.03
ND
0.10
0.09
ND
IN
0.003
0.012
IL
MADISON CO
249,238
2
2.50
ND
0.12
0.09
44
120
0.009
0.059
IL
PEORIA CO
182,827
5
0.02
ND
0.10
0.08
23
52
0.007
0.036
IL
RANDOLPH CO
34,583
ND
ND
ND
0.10
0.08
ND
ND
0.005
0.065
IL
ROCK ISLAND CO
148,723
ND
ND
ND
0.09
0.07
ND
IN
0.003
0.010
IL
ST CLAIR CO
262,852
ND
0.09
0.019
0.11
0.08
32
79
0.008
0.036
IL
SANGAMON CO
178,386
2
ND
ND
0.10
0.08
20
45
0.006
0.059
IL
TAZEWELL CO
123,692
ND
ND
ND
ND
ND
ND
IN
0.005
0.035
IL
WABASH CO
13,111
ND
ND
ND
ND
ND
ND
ND
IN
0.032
IL
WILL CO
357,313
1
ND
0.010
0.10
0.09
23
52
0.005
0.023
IL
WINNEBAGO CO
252,913
4
ND
ND
0.09
0.08
ND
IN
ND
ND
IN
ALLEN CO
300,836
3
ND
ND
0.10
0.09
IN
IN
ND
ND
IN
CLARK CO
87,777
ND
ND
ND
0.11
0.09
IN
57
ND
ND
IN
DAVIESS CO
27,533
ND
ND
ND
ND
ND
ND
ND
IN
0.030
IN
DEARBORN CO
38,835
ND
ND
ND
ND
ND
ND
ND
0.008
0.030
IN
DE KALB CO
35,324
ND
ND
ND
ND
ND
IN
IN
ND
ND
IN
DELAWARE CO
119,659
ND
0.76
ND
ND
ND
ND
ND
ND
ND
IN
DUBOIS CO
36,616
ND
ND
ND
ND
ND
CD
CM
^r
LO
ND
ND
IN
ELKHART CO
156,198
ND
ND
ND
0.09
0.08
ND
ND
ND
ND
IN
FLOYD CO
64,404
ND
ND
ND
0.12
0.09
ND
ND
0.007
0.032
IN
FOUNTAIN CO
17,808
ND
ND
ND
ND
ND
ND
ND
IN
0.049
IN
GIBSON CO
31,913
ND
ND
IN
0.10
0.08
ND
ND
IN
0.057
IN
HAMILTON CO
108,936
ND
ND
ND
0.11
0.10
ND
ND
ND
ND
IN
HANCOCK CO
45,527
ND
ND
ND
0.10
0.09
ND
ND
ND
ND
IN
HENDRICKS CO
75,717
IN
ND
IN
ND
ND
IN
IN
IN
0.014
IN
JASPER CO
24,960
ND
ND
ND
ND
ND
IN
IN
0.003
0.015
IN
JEFFERSON CO
29,797
ND
ND
ND
ND
ND
ND
ND
0.007
0.023
IN
JOHNSON CO
88,109
ND
ND
ND
0.11
0.10
ND
ND
ND
ND
IN
LAKE CO
475,594
3
0.08
0.019
0.11
0.10
35
166
0.007
0.032
IN
LA PORTE CO
107,066
ND
ND
ND
0.11
0.09
ND
IN
0.004
0.014
APPENDIX A • DATA TABLES
173
-------
NATIONALAIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-14. Maximum Air Quality Concentrations by County, 1999 (continued)
CO
Pb
no2
°3
°3
PM10
PM10
S02
so2
State County
1990
8-hr
QMax
AM
1-hr
8-hr
Wtd AM
2nd Max
AM
24-hr
Population
(ppm)
(jjg/m3)
(PP"i)
(PP"i)
(PP"i)
(jjg/m3)
(jjg/m3)
(ppm)
(ppm)
IN
MADISON CO
130,669
ND
ND
ND
0.11
0.09
IN
IN
ND
ND
IN
MARION CO
797,159
3
0.12
0.018
0.11
0.10
27*
CO
LO
0.007
0.024
IN
MORGAN CO
55,920
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
IN
PERRY CO
19,107
ND
ND
ND
0.12
0.09
IN
IN
IN
0.029
IN
PIKE CO
12,509
ND
ND
ND
ND
ND
ND
ND
IN
0.037
IN
PORTER CO
128,932
ND
ND
ND
0.12
0.10
26
79
0.005
0.020
IN
POSEY CO
25,968
ND
ND
ND
0.11
0.10
ND
ND
ND
ND
IN
ST JOSEPH CO
247,052
ND
ND
IN
0.11
0.09
IN
49
ND
ND
IN
SPENCER CO
19,490
ND
ND
0.008
ND
ND
ND
IN
0.008
0.028
IN
SULLIVAN CO
18,993
ND
ND
ND
ND
ND
ND
ND
IN
0.019
IN
VANDERBURGH CO
165,058
4
ND
IN
0.11
0.10
26
60
0.007
0.022
IN
VERMILLION CO
16,773
ND
ND
ND
ND
ND
ND
IN
ND
ND
IN
VIGO CO
106,107
ND
ND
ND
0.09
0.08
IN
IN
0.006
0.025
IN
WARRICK CO
44,920
ND
ND
ND
0.11
0.10
ND
ND
IN
0.087
IN
WAYNE CO
71,951
ND
ND
ND
ND
ND
ND
ND
0.006
0.041
IA
BLACK HAWK CO
123,798
ND
ND
ND
ND
ND
IN
IN
ND
ND
IA
CERRO GORDO CO
46,733
ND
ND
ND
ND
ND
38
149
0.006
0.123
IA
CLINTON CO
51,040
ND
ND
ND
0.10
0.08
26
78
0.004
0.021
IA
DELAWARE CO
18,035
ND
ND
ND
ND
ND
IN
IN
ND
ND
IA
HARRISON CO
14,730
ND
ND
ND
0.09
0.07
ND
ND
ND
ND
IA
LEE CO
38,687
ND
ND
ND
ND
ND
ND
ND
0.002
0.020
IA
LINN CO
168,767
2
ND
ND
0.10
0.08
IN
54
0.005
0.071
IA
MUSCATINE CO
39,907
ND
ND
ND
ND
ND
IN
67
0.010
0.129
IA
PALO ALTO CO
10,669
ND
ND
ND
0.08
0.07
ND
ND
ND
ND
IA
POLK CO
327,140
4
ND
ND
0.07
0.06
IN
76
ND
ND
IA
POTTAWATTAMIE CO
82,628
ND
ND
ND
ND
ND
IN
IN
ND
ND
IA
SCOTT CO
150,979
ND
ND
ND
0.10
0.08
44
177
0.004
0.014
IA
STORY CO
74,252
ND
ND
ND
0.08
0.07
ND
ND
ND
ND
IA
VAN BUREN CO
7,676
ND
ND
ND
0.09
0.08
ND
ND
0.002
0.011
IA
WARREN CO
36,033
ND
ND
ND
0.08
0.07
ND
ND
ND
ND
IA
WOODBURY CO
98,276
ND
ND
ND
ND
ND
28
73
ND
ND
KS
CLOUD CO
11,023
ND
ND
ND
ND
ND
ND
IN
ND
ND
KS
FORD CO
27,463
ND
ND
ND
ND
ND
31
89
ND
ND
KS
GREELEY CO
1,774
ND
ND
ND
ND
ND
ND
IN
ND
ND
KS
JOHNSON CO
355,054
ND
ND
ND
ND
ND
ND
IN
ND
ND
KS
KEARNEY CO
4,027
ND
ND
ND
ND
ND
ND
IN
ND
ND
KS
LINN CO
8,254
1
ND
0.004
0.10
0.08
ND
ND
0.002
0.007
KS
MONTGOMERYCO
38,816
ND
ND
ND
ND
ND
26
68
0.007
0.046
KS
MORTON CO
3,480
ND
ND
ND
ND
ND
ND
IN
ND
ND
KS
NEOSHO CO
17,035
ND
ND
ND
ND
ND
35
98
ND
ND
KS
PAWNEE CO
7,555
ND
ND
ND
ND
ND
ND
IN
ND
ND
KS
SEDGWICK CO
403,662
5
ND
ND
0.10
0.08
31
86
ND
ND
KS
SHAWNEE CO
160,976
ND
ND
ND
ND
ND
25
74
ND
ND
KS
SHERMAN CO
6,926
ND
ND
ND
ND
ND
31
120
ND
ND
KS
SUMNER CO
25,841
IN
ND
ND
0.10
IN
ND
ND
ND
ND
KS
WYANDOTTE CO
161,993
5
ND
IN
0.09
0.08
40
118
IN
0.016
KY
BELL CO
31,506
2
ND
ND
0.11
0.08
IN
48
ND
ND
KY
BOONE CO
57,589
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
KY
BOYD CO
51,150
1
ND
0.016
0.12
0.09
39
89
0.008
0.024
KY
BULLITT CO
47,567
ND
ND
0.014
0.11
0.09
25
56
ND
ND
KY
CAMPBELL CO
83,866
ND
ND
0.017
0.10
0.09
26
46
0.006
0.025
KY
CARTER CO
24,340
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
KY
CHRISTIAN CO
68,941
ND
ND
ND
0.12
0.09
ND
ND
ND
ND
KY
DAVIESS CO
87,189
1
ND
0.011
0.10
0.09
25
63
0.006
0.024
KY
EDMONSON CO
10,357
ND
ND
ND
0.12
0.10
ND
ND
ND
ND
174 DATA TABLES • APPENDIX A
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-14. Maximum Air Quality Concentrations by County, 1999 (continued)
CO Pb N02 03 03 PM10 PM10 S02 S02
State County 1990 8-hr QMax AM 1-hr 8-hr WtdAM 2nd Max AM 24-hr
Population (ppm) ((jg/m3) (ppm) (ppm) (ppm) (ng/m3) (ng/m3) (ppm) (ppm)
KY
FAYETTE CO
225,366
2
ND
0.013
0.11
0.09
23
54
0.008
0.020
KY
FLOYD CO
43,586
ND
ND
ND
ND
ND
23
47
ND
ND
KY
GRAVES CO
33,550
ND
ND
ND
0.12
0.10
ND
ND
ND
ND
KY
GREENUP CO
36,742
ND
ND
ND
0.12
0.10
ND
ND
0.006
0.026
KY
HANCOCK CO
7,864
ND
ND
ND
0.11
0.09
ND
ND
0.006
0.031
KY
HARDIN CO
89,240
ND
ND
ND
0.11
0.09
IN
39
ND
ND
KY
HARLAN CO
36,574
ND
ND
ND
ND
ND
IN
44
ND
ND
KY
HENDERSON CO
43,044
2
ND
0.016
0.11
0.10
24
59
0.007
0.056
KY
JEFFERSON CO
664,937
5
ND
0.014
0.12
0.10
28
60
0.007
0.027
KY
JESSAMINE CO
30,508
ND
ND
ND
0.10
0.08
ND
ND
ND
ND
KY
KENTON CO
142,031
3
ND
0.017
0.11
0.09
20
52
ND
ND
KY
LAWRENCE CO
13,998
ND
ND
ND
ND
ND
IN
IN
ND
ND
KY
LIVINGSTON CO
9,062
ND
ND
ND
0.12
0.10
IN
61
0.005
0.024
KY
MC CRACKEN CO
62,879
2
ND
0.011
0.11
0.09
15
58
0.005
0.027
KY
MC LEAN CO
9,628
ND
ND
ND
0.12
0.10
ND
ND
ND
ND
KY
MADISON CO
57,508
ND
ND
ND
ND
ND
IN
46
ND
ND
KY
MARSHALL CO
27,205
ND
ND
ND
ND
ND
IN
61
ND
ND
KY
OLDHAM CO
33,263
ND
ND
ND
0.12
0.10
ND
ND
ND
ND
KY
PERRY CO
30,283
ND
ND
ND
0.10
0.07
24
45
ND
ND
KY
PIKE CO
72,583
ND
ND
ND
0.10
0.08
30
57
ND
ND
KY
PULASKI CO
49,489
ND
ND
ND
0.10
0.10
IN
45
ND
ND
KY
SCOTT CO
23,867
ND
ND
ND
0.11
0.08
ND
ND
ND
ND
KY
SIMPSON CO
15,145
ND
ND
0.009
0.12
0.10
ND
ND
ND
ND
KY
TRIGG CO
10,361
ND
ND
ND
0.12
0.10
ND
ND
ND
ND
KY
WARREN CO
76,673
ND
ND
ND
ND
ND
21
45
ND
ND
KY
WHITLEY CO
33,326
ND
ND
ND
ND
ND
IN
48
ND
ND
LA
ASCENSION PAR
58,214
ND
ND
ND
0.12
0.09
ND
ND
ND
ND
LA
BEAUREGARD PAR
30,083
ND
ND
0.007
0.10
0.08
ND
ND
ND
ND
LA
BOSSIER PAR
86,088
ND
ND
ND
0.11
0.09
ND
ND
0.002
0.006
LA
CADDO PAR
248,253
ND
ND
ND
0.10
0.09
CM
CM
41*
ND
ND
LA
CALCASIEU PAR
168,134
ND
ND
0.005
0.13
0.09
ND
ND
0.004
0.015
LA
EAST BATON ROUGE PAR
380,105
5
0.06
0.019
0.12
0.10
IN
50
0.005
0.025
LA
GRANT PAR
17,526
ND
ND
ND
0.09
0.08
ND
ND
ND
ND
LA
IBERVILLE PAR
31,049
ND
ND
0.009
0.12
0.09
ND
ND
ND
ND
LA
JEFFERSON PAR
448,306
ND
ND
0.011
0.11
0.09
ND
ND
ND
ND
LA
LAFAYETTE PAR
164,762
ND
ND
ND
0.09
0.08
ND
ND
ND
ND
LA
LAFOURCHE PAR
85,860
ND
ND
ND
0.12
0.09
ND
ND
ND
ND
LA
LIVINGSTON PAR
70,526
ND
ND
0.005
0.11
0.09
ND
ND
ND
ND
LA
ORLEANS PAR
496,938
3
0.03
0.022
0.09
0.08
LO
CM
LO
LO
ND
ND
LA
OUACHITA PAR
142,191
ND
ND
ND
0.10
0.08
ND
ND
0.003
0.010
LA
POINTE COUPEE PAR
22,540
ND
ND
0.009
0.11
0.08
ND
ND
ND
ND
LA
ST BERNARD PAR
66,631
ND
ND
ND
0.10
0.08
ND
ND
0.005
0.023
LA
ST CHARLES PAR
42,437
ND
ND
ND
0.11
0.09
27
60
ND
ND
LA
ST JAMES PAR
20,879
ND
ND
0.012
0.12
0.09
ND
ND
ND
ND
LA
ST JOHN THE BAPTIST PAR
39,996
ND
0.08
ND
0.11
0.09
ND
ND
ND
ND
LA
ST MARY PAR
58,086
ND
ND
ND
0.10
0.09
ND
ND
ND
ND
LA
WEST BATON ROUGE PAR
19,419
ND
0.02
0.015
0.11
0.09
34
79
0.006
0.019
ME
ANDROSCOGGIN CO
105,259
ND
ND
ND
ND
ND
IN
45
0.004
0.016
ME
AROOSTOOK CO
86,936
ND
ND
ND
ND
ND
31
91
ND
ND
ME
CUMBERLAND CO
243,135
ND
ND
ND
0.11
0.08
23
61
0.005
0.014
ME
FRANKLIN CO
29,008
ND
ND
ND
ND
ND
IN
27
ND
ND
ME
HANCOCK CO
46,948
ND
ND
IN
0.12
0.09
ND
IN
ND
ND
ME
KENNEBEC CO
115,904
ND
ND
ND
0.10
0.08
IN
76
ND
ND
ME
KNOX CO
36,310
ND
ND
ND
0.11
0.08
IN
47
ND
ND
ME
OXFORD CO
52,602
ND
ND
ND
0.08
0.06
IN
45
0.003
0.015
APPENDIX A • DATA TABLES
175
-------
NATIONALAIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-14. Maximum Air Quality Concentrations by County, 1999 (continued)
CO
Pb
no2
°3
°3
PM10
PM10
S02
so2
State County
1990
8-hr
QMax
AM
1-hr
8-hr
Wtd AM
2nd Max
AM
24-hr
Population
(ppm)
(jjg/m3)
(PP"i)
(PP"i)
(PP"i)
(jjg/m3)
(jjg/m3)
(ppm)
(ppm)
ME
PENOBSCOT CO
146,601
ND
ND
ND
0.09
0.08
17*
32*
ND
ND
ME
PISCATAQUIS CO
18,653
ND
ND
ND
0.08
0.07
ND
ND
ND
ND
ME
SAGADAHOC CO
33,535
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
ME
YORK CO
164,587
ND
ND
IN
0.12
0.09
ND
ND
ND
ND
MD
ALLEGANY CO
74,946
ND
ND
ND
ND
ND
ND
IN
ND
ND
MD
ANNE ARUNDEL CO
427,239
ND
ND
IN
0.14
0.11
25
53
0.006
0.020
MD
BALTIMORE CO
692,134
ND
ND
0.020
0.14
0.11
15
29
ND
ND
MD
CALVERT CO
51,372
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
MD
CARROLL CO
123,372
ND
ND
ND
0.13
0.10
ND
ND
ND
ND
MD
CECIL CO
71,347
ND
ND
ND
0.15
0.11
14
32
ND
ND
MD
CHARLES CO
101,154
ND
ND
ND
0.13
0.11
ND
ND
ND
ND
MD
FREDERICK CO
150,208
ND
ND
ND
0.11
0.10
ND
ND
ND
ND
MD
GARRETT CO
28,138
ND
ND
ND
ND
ND
ND
IN
ND
ND
MD
HARFORD CO
182,132
ND
ND
IN
0.15
0.11
ND
ND
ND
ND
MD
KENT CO
17,842
ND
ND
ND
0.13
0.10
ND
ND
ND
ND
MD
MONTGOMERY CO
757,027
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
MD
PRINCE GEORGES CO
729,268
4
ND
ND
0.13
0.10
24
58
ND
ND
MD
WASHINGTON CO
121,393
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
MD
WICOMICO CO
74,339
ND
ND
ND
ND
ND
12
31
ND
ND
MD
BALTIMORE
736,014
5
0.00
0.024
0.12
0.09
30*
61*
ND
ND
MA
BARNSTABLE CO
186,605
ND
ND
IN
0.13
0.10
ND
ND
ND
ND
MA
BERKSHIRE CO
139,352
ND
ND
ND
0.09
0.08
ND
ND
ND
ND
MA
BRISTOL CO
506,325
ND
ND
IN
0.13
0.10
ND
IN
0.004
0.021
MA
ESSEX CO
670,080
ND
ND
0.013
0.12
0.09
ND
IN
0.005
0.021
MA
HAMPDEN CO
456,310
6
ND
0.022
0.11
0.09
30
66
0.005
0.024
MA
HAMPSHIRE CO
146,568
ND
ND
0.007
0.11
0.09
14
42
0.005
0.017
MA
MIDDLESEX CO
1,398,468
4
ND
ND
0.11
0.09
ND
IN
0.007
0.040
MA
NORFOLK CO
616,087
ND
ND
ND
ND
ND
ND
IN
ND
ND
MA
SUFFOLK CO
663,906
4
0.03
0.030
0.11
0.09
30
65
0.007
0.026
MA
WORCESTER CO
709,705
3
ND
0.020
0.11
0.09
IN
65
0.004
0.013
Ml
ALLEGAN CO
90,509
ND
ND
ND
0.12
0.09
ND
ND
ND
ND
Ml
BENZIE CO
12,200
ND
ND
ND
0.11
0.10
ND
ND
ND
ND
Ml
BERRIEN CO
161,378
ND
ND
ND
0.11
0.10
ND
ND
ND
ND
Ml
CALHOUN CO
135,982
ND
ND
ND
ND
ND
IN
50
ND
ND
Ml
CASS CO
49,477
ND
ND
ND
0.11
0.10
ND
ND
ND
ND
Ml
CLINTON CO
57,883
ND
ND
ND
0.10
0.09
ND
ND
ND
ND
Ml
DELTA CO
37,780
ND
ND
ND
ND
ND
ND
ND
0.002
0.010
Ml
GENESEE CO
430,459
ND
0.01
ND
0.11
0.10
IN
IN
0.003
0.011
Ml
GRAND TRAVERSE CO
64,273
ND
ND
ND
0.09
0.08
ND
ND
ND
ND
Ml
HURON CO
34,951
ND
ND
ND
0.12
0.09
ND
ND
ND
ND
Ml
INGHAM CO
281,912
ND
ND
ND
0.10
0.09
ND
ND
ND
ND
Ml
KALAMAZOO CO
223,411
ND
ND
ND
0.10
0.09
ND
ND
ND
ND
Ml
KENT CO
500,631
4
0.00
ND
0.11
0.09
21
54
0.001
0.006
Ml
LENAWEE CO
91,476
ND
ND
ND
0.09
0.08
ND
ND
ND
ND
Ml
MACOMB CO
717,400
3
ND
ND
0.12
0.10
ND
ND
0.002
0.012
Ml
MASON CO
25,537
ND
ND
ND
0.12
0.10
ND
ND
ND
ND
Ml
MISSAUKEE CO
12,147
ND
0.00
ND
0.10
0.09
ND
ND
ND
ND
Ml
MUSKEGON CO
158,983
ND
ND
ND
0.12
0.10
ND
ND
ND
ND
Ml
OAKLAND CO
1,083,592
3
ND
ND
0.11
0.09
ND
ND
ND
ND
Ml
ONTONAGON CO
8,854
ND
ND
ND
ND
ND
IN
IN
ND
ND
Ml
OTTAWA CO
187,768
ND
ND
ND
0.11
0.09
IN
IN
ND
ND
Ml
ST CLAIR CO
145,607
ND
ND
ND
0.12
0.09
ND
ND
0.008
0.048
Ml
WASHTENAW CO
282,937
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
Ml
WAYNE CO
2,111,687
4
0.10
0.018
0.11
0.09
36
126
0.009
0.053
MN
ANOKA CO
243,641
2
ND
ND
0.09
0.07
ND
ND
ND
ND
176 DATA TABLES • APPENDIX A
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-14. Maximum Air Quality Concentrations by County, 1999 (continued)
CO Pb N02 03 03 PM10 PM10 S02 S02
State County 1990 8-hr QMax AM 1-hr 8-hr WtdAM 2nd Max AM 24-hr
Population (ppm) ((jg/m3) (ppm) (ppm) (ppm) (ng/m3) (ng/m3) (ppm) (ppm)
MN
BELTRAMI CO
34,384
ND
ND
ND
ND
ND
IN
IN
ND
ND
MN
CARLTON CO
29,259
ND
ND
ND
ND
ND
IN
32
ND
ND
MN
CLAY CO
50,422
ND
ND
ND
ND
ND
IN
IN
ND
ND
MN
DAKOTA CO
275,227
1
0.47
0.014
0.08
0.07
ND
ND
0.003
0.013
MN
FREEBORN CO
33,060
ND
ND
ND
ND
ND
IN
IN
ND
ND
MN
HENNEPIN CO
1,032,431
3
0.01
0.022
ND
ND
30
70
0.004
0.030
MN
KOOCHICHING CO
16,299
ND
ND
ND
ND
ND
ND
ND
0.001
0.003
MN
LAKE CO
10,415
ND
ND
ND
0.08
0.07
IN
IN
ND
ND
MN
MC LEODCO
32,030
ND
ND
ND
ND
ND
IN
IN
ND
ND
MN
MILLE LACS CO
18,670
ND
ND
ND
0.10
0.08
IN
26
ND
ND
MN
OLMSTED CO
106,470
ND
ND
ND
ND
ND
IN
IN
ND
ND
MN
OTTER TAIL CO
50,714
ND
ND
ND
ND
ND
IN
IN
ND
ND
MN
PINE CO
21,264
1
ND
ND
ND
ND
ND
ND
ND
ND
MN
RAMSEY CO
485,765
5
0.01
0.016
ND
ND
35
88
0.002
0.007
MN
ST LOUIS CO
198,213
2
ND
ND
0.08
0.07
25
71
ND
ND
MN
STEARNS CO
118,791
3
ND
ND
ND
ND
IN
IN
ND
ND
MN
SWIFT CO
10,724
ND
ND
ND
ND
ND
IN
IN
ND
ND
MN
WASHINGTON CO
145,896
ND
ND
ND
0.09
0.08
23
49
0.003
0.017
MN
WINONA CO
47,828
ND
ND
ND
ND
ND
IN
IN
ND
ND
MN
WRIGHT CO
68,710
ND
ND
ND
ND
ND
IN
IN
ND
ND
MS
ADAMS CO
35,356
ND
ND
ND
0.09
0.08
ND
ND
ND
ND
MS
BOLIVAR CO
41,875
ND
ND
ND
0.10
0.09
ND
ND
ND
ND
MS
COAHOMACO
31,665
ND
ND
ND
ND
ND
IN
IN
ND
ND
MS
DE SOTO CO
67,910
ND
ND
0.012
0.13
0.09
ND
ND
ND
ND
MS
HANCOCK CO
31,760
ND
ND
0.006
0.11
0.09
ND
ND
ND
ND
MS
HARRISON CO
165,365
ND
ND
ND
0.11
0.10
ND
ND
0.003
0.024
MS
HINDS CO
254,441
5
ND
ND
0.11
0.08
25
53
0.002
0.007
MS
JACKSON CO
115,243
ND
ND
ND
0.11
0.09
IN
38
0.003
0.016
MS
JONES CO
62,031
ND
ND
ND
ND
ND
IN
IN
ND
ND
MS
LAUDERDALE CO
75,555
ND
ND
ND
0.09
0.08
ND
ND
ND
ND
MS
LEE CO
65,581
ND
ND
ND
0.11
0.09
16
34
ND
ND
MS
MADISON CO
53,794
ND
ND
ND
0.10
0.08
ND
ND
ND
ND
MS
PANOLA CO
29,996
ND
ND
IN
ND
ND
IN
IN
IN
0.004
MS
WARREN CO
47,880
ND
ND
ND
0.09
0.07
ND
IN
ND
ND
MS
WASHINGTON CO
67,935
ND
ND
ND
ND
ND
IN
IN
ND
ND
MO
AUDRAIN CO
23,599
ND
ND
ND
ND
ND
ND
IN
ND
ND
MO
BUCHANAN CO
83,083
ND
ND
ND
ND
ND
IN
99
0.003
0.013
MO
CEDAR CO
12,093
ND
ND
IN
0.09
0.08
ND
ND
ND
ND
MO
CLAY CO
153,411
5
ND
0.015
0.11
0.08
ND
ND
0.002
0.011
MO
GREENE CO
207,949
3
ND
0.013
0.10
0.08
18*
34*
0.004
0.039
MO
HOLT CO
6,034
ND
0.28
ND
ND
ND
ND
ND
ND
ND
MO
IRON CO
10,726
ND
1.24
ND
ND
ND
ND
ND
0.009
0.083
MO
JACKSON CO
633,232
4
0.01
ND
0.12
0.08
28
56
0.003
0.009
MO
JASPER CO
90,465
ND
ND
ND
ND
ND
34
105
ND
ND
MO
JEFFERSON CO
171,380
ND
6.75
ND
0.12
0.10
ND
IN
0.008
0.045
MO
LINCOLN CO
28,892
ND
ND
ND
ND
ND
IN
61
ND
ND
MO
MONROE CO
9,104
ND
ND
ND
0.11
0.09
13*
34*
0.004
0.011
MO
PLATTE CO
57,867
ND
ND
0.011
0.09
0.08
ND
ND
0.002
0.008
MO
ST CHARLES CO
212,907
ND
ND
0.012
0.13
0.10
ND
ND
0.005
0.016
MO
STE GENEVIEVE CO
16,037
ND
ND
IN
0.11
0.10
ND
ND
ND
ND
MO
ST LOUIS CO
993,529
3
0.02
0.024
0.12
0.10
18
33
0.007
0.021
MO
ST LOUIS
396,685
4
ND
0.027
0.12
0.09
36
92
0.009
0.037
MT
BIG HORN CO
11,337
ND
ND
ND
ND
ND
29*
77*
ND
ND
MT
BROADWATER CO
3,318
ND
ND
ND
ND
ND
ND
IN
ND
ND
MT
CASCADE CO
77,691
4
ND
ND
ND
ND
ND
ND
0.003
0.011
APPENDIX A • DATA TABLES
177
-------
NATIONALAIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-14. Maximum Air Quality Concentrations by County, 1999 (continued)
CO
Pb
no2
°3
°3
PM10
PM10
S02
so2
State County
1990
8-hr
QMax
AM
1-hr
8-hr
Wtd AM
2nd Max
AM
24-hr
Population
(ppm)
(jjg/m3)
(PP"i)
(PP"i)
(PP"i)
(jjg/m3)
(jjg/m3)
(ppm)
(ppm)
MT
FLATHEAD CO
59,218
5
ND
ND
0.06
IN
29*
96*
ND
ND
MT
GALLATIN CO
50,463
5
ND
ND
ND
ND
IN
62
ND
ND
MT
GLACIER CO
12,121
ND
ND
ND
ND
ND
26
69
ND
ND
MT
JEFFERSON CO
7,939
ND
ND
ND
ND
ND
IN
IN
0.004
0.029
MT
LAKE CO
21,041
ND
ND
ND
ND
ND
21
118
ND
ND
MT
LEWIS AND CLARK CO
47,495
ND
1.12
ND
ND
ND
25
125
0.006
0.036
MT
LINCOLN CO
17,481
ND
ND
ND
ND
ND
26
74
ND
ND
MT
MADISON CO
5,989
ND
ND
ND
ND
ND
6*
19*
ND
ND
MT
MISSOULA CO
78,687
4
ND
ND
ND
ND
20*
56*
ND
ND
MT
PARK CO
14,562
ND
ND
ND
ND
ND
IN
IN*
ND
ND
MT
PHILLIPS CO
5,163
ND
ND
ND
ND
ND
ND
IN
ND
ND
MT
RAVALLI CO
25,010
ND
ND
ND
ND
ND
21*
67*
ND
ND
MT
ROOSEVELT CO
10,999
ND
ND
ND
ND
ND
IN
IN
ND
ND
MT
ROSEBUD CO
10,505
ND
ND
ND
ND
ND
32
107
ND
ND
MT
SANDERS CO
8,669
ND
ND
ND
ND
ND
IN
53
ND
ND
MT
SILVER BOW CO
33,941
4
ND
ND
ND
ND
21
62
ND
ND
MT
STILLWATER CO
6,536
ND
ND
ND
ND
ND
IN
IN
ND
ND
MT
YELLOWSTONE CO
113,419
6
ND
ND
ND
ND
21
69
0.007
0.037
NE
CASS CO
21,318
ND
ND
ND
ND
ND
38
131
ND
ND
NE
DAWSON CO
19,940
ND
ND
ND
ND
ND
34
116
ND
ND
NE
DOUGLAS CO
416,444
9
0.81
ND
0.09
0.08
43
102
0.001
0.006
NE
LANCASTER CO
213,641
6
ND
ND
0.06
0.05
ND
ND
ND
ND
NV
CHURCHILL CO
17,938
ND
ND
ND
ND
ND
ND
IN
ND
ND
NV
CLARK CO
741,459
8
ND
ND
0.10
0.08
56
281
ND
ND
NV
DOUGLAS CO
27,637
2
ND
ND
0.09
0.07
IN
IN
ND
ND
NV
ELKO CO
33,530
ND
ND
ND
ND
ND
29
93
ND
ND
NV
LANDER CO
6,266
ND
ND
ND
ND
ND
24
120
ND
ND
NV
PERSHING CO
4,336
ND
ND
ND
ND
ND
ND
IN
ND
ND
NV
WASHOE CO
254,667
7
ND
IN
0.10
0.08
57*
o
CM
ND
ND
NV
WHITE PINE CO
9,264
ND
ND
ND
0.08
0.07
ND
IN
ND
ND
NV
CARSON CITY
40,443
4
ND
ND
0.08
0.07
ND
IN
ND
ND
NH
BELKNAP CO
49,216
ND
ND
ND
0.09
0.08
ND
ND
ND
ND
NH
CARROLL CO
35,410
ND
ND
ND
0.09
0.07
ND
ND
ND
ND
NH
CHESHIRE CO
70,121
ND
ND
ND
0.11
0.08
22
49
0.005
0.022
NH
COOS CO
34,828
ND
ND
ND
0.10
IN
29
63
0.004
0.034
NH
GRAFTON CO
74,929
ND
ND
ND
0.09
0.07
ND
ND
ND
ND
NH
HILLSBOROUGH CO
336,073
5
ND
IN
0.10
0.09
17
41
0.005
0.025
NH
MERRIMACK CO
120,005
ND
ND
ND
0.09
0.07
17
39
0.004
0.028
NH
ROCKINGHAM CO
245,845
ND
ND
0.010
0.12
0.09
16
34
0.004
0.019
NH
STRAFFORD CO
104,233
ND
ND
ND
0.10
0.08
ND
ND
ND
ND
NH
SULLIVAN CO
38,592
ND
ND
ND
0.10
0.08
16
46
0.003
0.015
NJ
ATLANTIC CO
224,327
ND
ND
ND
0.12
0.10
22
46
0.003
0.009
NJ
BERGEN CO
825,380
4
ND
ND
ND
ND
34
75
0.005
0.020
NJ
BURLINGTON CO
395,066
4
ND
ND
ND
ND
ND
ND
0.004
0.018
NJ
CAMDEN CO
502,824
4
0.08
0.022
0.13
0.11
22
51
0.006
0.023
NJ
CUMBERLAND CO
138,053
ND
ND
ND
0.12
0.10
ND
ND
0.003
0.012
NJ
ESSEX CO
778,206
4
ND
0.033
0.12
0.10
IN
66
0.007
0.022
NJ
GLOUCESTER CO
230,082
ND
ND
ND
0.13
0.10
ND
IN
0.005
0.020
NJ
HUDSON CO
553,099
6
ND
0.026
0.14
0.11
35
56
0.008
0.030
NJ
HUNTERDON CO
107,776
ND
ND
ND
0.13
0.11
ND
ND
ND
ND
NJ
MERCER CO
325,824
ND
ND
0.017
0.15
0.11
21
48
ND
ND
NJ
MIDDLESEX CO
671,780
3
0.18
0.019
0.15
0.11
ND
ND
0.005
0.016
NJ
MONMOUTH CO
553,124
3
ND
ND
0.12
0.10
ND
ND
ND
ND
NJ
MORRIS CO
421,353
4
ND
0.011
0.12
0.10
ND
ND
0.004
0.020
NJ
OCEAN CO
433,203
ND
ND
ND
0.14
0.11
ND
ND
ND
ND
178 DATA TABLES • APPENDIX A
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-14. Maximum Air Quality Concentrations by County, 1999 (continued)
CO Pb N02 03 03 PM10 PM10 S02 S02
State County 1990 8-hr QMax AM 1-hr 8-hr WtdAM 2nd Max AM 24-hr
Population (ppm) ((jg/m3) (ppm) (ppm) (ppm) (ng/m3) (ng/m3) (ppm) (ppm)
NJ
PASSAIC CO
453,060
ND
ND
ND
0.13
0.10
ND
IN
ND
ND
NJ
UNION CO
493,819
7
ND
0.042
ND
ND
33
67
0.007
0.023
NJ
WARREN CO
91,607
ND
ND
ND
ND
ND
ND
IN
ND
ND
NM
BERNALILLO CO
480,577
5
ND
0.016
0.10
0.08
LO
CO
CO
CM
ND
ND
NM
CHAVES CO
57,849
ND
ND
ND
ND
ND
19
33
ND
ND
NM
DONAANA CO
135,510
4
ND
0.012
0.10
0.08
47*
200*
0.001
0.008
NM
EDDY CO
48,605
ND
ND
0.006
0.08
0.07
ND
ND
0.001
0.007
NM
GRANT CO
27,676
ND
ND
ND
ND
ND
CO
CM
51*
0.003
0.030
NM
HIDALGO CO
5,958
ND
ND
ND
ND
ND
IN
53
0.003
0.025
NM
LEA CO
55,765
ND
ND
ND
ND
ND
18*
31*
ND
ND
NM
LUNA CO
18,110
ND
ND
ND
ND
ND
LO
CM
112*
ND
ND
NM
OTERO CO
51,928
ND
ND
ND
ND
ND
IN
45
ND
ND
NM
SANDOVAL CO
63,319
1
ND
0.010
0.09
0.08
o
CM
CD
ND
ND
NM
SAN JUAN CO
91,605
2
ND
0.012
0.08
0.07
18*
37*
0.010
0.038
NM
SANTA FE CO
98,928
2
ND
ND
ND
ND
14*
31*
ND
ND
NM
TAOS CO
23,118
ND
ND
ND
ND
ND
IN
38
ND
ND
NM
VALENCIA CO
45,235
ND
ND
ND
0.09
0.07
ND
ND
ND
ND
NY
ALBANY CO
292,594
1
ND
IN
0.11
0.08
ND
ND
0.003
0.016
NY
BRONX CO
1,203,789
4
ND
0.033
0.14
0.10
IN
IN
0.011
0.041
NY
CHAUTAUQUA CO
141,895
ND
ND
ND
0.10
0.09
14
40
0.008
0.060
NY
CHEMUNG CO
95,195
ND
ND
ND
0.09
0.08
ND
ND
0.003
0.015
NY
DUTCHESS CO
259,462
ND
ND
ND
0.12
0.09
ND
ND
ND
ND
NY
ERIE CO
968,532
2
ND
0.022
0.10
0.09
ND
ND
0.010
0.052
NY
ESSEX CO
37,152
ND
ND
ND
0.10
0.08
10
40
0.002
0.007
NY
HAMILTON CO
5,279
ND
ND
ND
0.09
0.08
ND
ND
0.002
0.006
NY
HERKIMER CO
65,797
ND
ND
ND
0.09
0.07
IN
46
0.001
0.007
NY
JEFFERSON CO
110,943
ND
ND
ND
0.10
0.09
ND
ND
ND
ND
NY
KINGS CO
2,300,664
5
0.10
ND
ND
ND
IN
46
0.009
0.030
NY
MADISON CO
69,120
ND
ND
ND
0.09
0.08
ND
ND
0.002
0.015
NY
MONROE CO
713,968
3
ND
ND
0.10
0.09
ND
ND
0.007
0.041
NY
NASSAU CO
1,287,348
5
ND
0.024
ND
ND
16
41
0.006
0.038
NY
NEW YORK CO
1,487,536
5
ND
0.041
0.12
0.08
IN
45
0.013
0.045
NY
NIAGARA CO
220,756
3
0.02
ND
0.10
0.09
IN
48
0.005
0.020
NY
ONEIDA CO
250,836
ND
ND
ND
0.09
0.08
ND
ND
ND
ND
NY
ONONDAGACO
468,973
3
ND
ND
0.10
0.09
ND
ND
0.002
0.012
NY
ORANGE CO
307,647
ND
0.20
ND
0.12
0.09
ND
ND
ND
ND
NY
PUTNAM CO
83,941
ND
ND
ND
0.13
0.10
ND
ND
0.003
0.010
NY
QUEENS CO
1,951,598
3
ND
0.029
0.13
0.09
ND
ND
0.007
0.028
NY
RENSSELAER CO
154,429
ND
ND
ND
ND
ND
ND
ND
0.002
0.011
NY
RICHMOND CO
378,977
ND
0.02
ND
0.15
0.11
IN
43
0.006
0.022
NY
SARATOGA CO
181,276
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
NY
SCHENECTADY CO
149,285
4
ND
ND
0.11
0.08
ND
ND
0.003
0.013
NY
SUFFOLK CO
1,321,864
ND
ND
ND
0.13
0.11
ND
ND
0.007
0.025
NY
ULSTER CO
165,304
ND
ND
ND
0.10
0.08
IN
41
0.002
0.010
NY
WAYNE CO
89,123
ND
ND
ND
0.10
0.09
ND
ND
ND
ND
NY
WESTCHESTER CO
874,866
ND
ND
ND
0.14
0.11
ND
ND
ND
ND
NC
ALEXANDER CO
27,544
ND
ND
ND
0.11
0.08
ND
ND
0.005
0.007
NC
AVERY CO
14,867
ND
ND
ND
0.09
IN
ND
ND
ND
ND
NC
BEAUFORT CO
42,283
ND
ND
ND
ND
ND
ND
ND
0.006
0.015
NC
BUNCOMBE CO
174,821
ND
ND
ND
0.10
0.08
CM
CM
44*
ND
ND
NC
CABARRUS CO
98,935
ND
ND
ND
ND
ND
IN
45
ND
ND
NC
CALDWELL CO
70,709
ND
ND
ND
0.12
0.09
ND
ND
ND
ND
NC
CAMDEN CO
5,904
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
NC
CASWELL CO
20,693
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
NC
CATAWBA CO
118,412
ND
ND
ND
ND
ND
CD
CM
51*
ND
ND
APPENDIX A • DATA TABLES
179
-------
NATIONALAIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-14. Maximum Air Quality Concentrations by County, 1999 (continued)
CO
Pb
no2
°3
°3
PM10
PM10
S02
so2
State County
1990
8-hr
QMax
AM
1-hr
8-hr
Wtd AM
2nd Max
AM
24-hr
Population
(ppm)
(jjg/m3)
(PP"i)
(PP"i)
(PP"i)
(jjg/m3)
(jjg/m3)
(ppm)
(ppm)
NC CHATHAM CO
38,759
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
NC CUMBERLAND CO
274,566
5
ND
ND
0.12
0.10
25*
CO
0.005
0.007
NC DAVIDSON CO
126,677
ND
ND
ND
ND
ND
LO
CM
CD
ND
ND
NC DAVIE CO
27,859
ND
ND
ND
0.13
0.10
ND
ND
ND
ND
NC DUPLIN CO
39,995
ND
ND
ND
0.10
0.09
ND
ND
0.005
0.007
NC DURHAM CO
181,835
5
ND
ND
0.11
0.09
CO
CM
47*
ND
ND
NC EDGECOMBE CO
56,558
ND
ND
ND
0.10
0.09
IN
IN
0.005
0.007
NC FORSYTH CO
265,878
4
ND
0.016
0.12
0.10
23
58
0.005
0.020
NC FRANKLIN CO
36,414
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
NC GASTON CO
175,093
ND
ND
ND
ND
ND
23
43
ND
ND
NC GRANVILLE CO
38,345
1
ND
ND
0.09
0.08
ND
ND
ND
ND
NC GUILFORD CO
347,420
3
ND
ND
0.11
0.10
LO
CM
48*
ND
ND
NC HARNETT CO
67,822
ND
ND
ND
ND
ND
CD
CM
47*
ND
ND
NC HAYWOOD CO
46,942
ND
ND
ND
0.11
0.10
LO
CM
CM
ND
ND
NC HENDERSON CO
69,285
ND
ND
ND
ND
ND
^r
CM
44*
ND
ND
NC JACKSON CO
26,846
ND
ND
ND
0.09
0.09
ND
ND
ND
ND
NC JOHNSTON CO
81,306
ND
ND
ND
0.13
0.10
ND
ND
0.005
0.009
NC LENOIR CO
57,274
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
NC LINCOLN CO
50,319
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
NC MCDOWELL CO
35,681
ND
ND
ND
ND
ND
24
40
ND
ND
NC MARTIN CO
25,078
ND
ND
ND
0.10
0.08
ND
ND
ND
ND
NC MECKLENBURG CO
511,433
4
ND
0.018
0.13
0.10
31*
61*
0.004
0.013
NC MITCHELL CO
14,433
ND
ND
ND
ND
ND
CM
CD
ND
ND
NC NEW HANOVER CO
120,284
4
ND
ND
0.08
0.07
IN
45
0.007
0.027
NC NORTHAMPTON CO
20,798
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
NC ONSLOW CO
149,838
ND
ND
ND
ND
ND
IN
45
ND
ND
NC ORANGE CO
93,851
4
ND
ND
ND
ND
ND
ND
ND
ND
NC PASQUOTANK CO
31,298
ND
ND
ND
ND
ND
IN
43
ND
ND
NC PERSON CO
30,180
ND
ND
ND
0.12
0.10
ND
ND
ND
ND
NC PITT CO
107,924
ND
ND
ND
0.11
0.09
IN
43
ND
ND
NC ROCKINGHAM CO
86,064
ND
ND
ND
0.11
0.08
ND
ND
ND
ND
NC ROWAN CO
110,605
1
ND
ND
0.13
0.11
ND
ND
ND
ND
NC SWAIN CO
11,268
ND
ND
ND
0.09
0.08
21
41
ND
ND
NC UNION CO
84,211
ND
ND
ND
0.12
0.10
ND
ND
ND
ND
NC WAKE CO
423,380
5
ND
ND
0.13
0.11
21*
CD
ND
ND
NC WAYNE CO
104,666
ND
ND
ND
ND
ND
20
48
ND
ND
NC YANCEY CO
15,419
ND
ND
ND
0.10
0.09
ND
ND
ND
ND
ND BILLINGS CO
1,108
ND
ND
ND
0.06
0.06
ND
ND
0.001
0.004
ND BURKE CO
3,002
ND
ND
0.003
ND
ND
17
45
0.002
0.010
ND BURLEIGH CO
60,131
ND
ND
ND
ND
ND
ND
IN
ND
ND
ND CASS CO
102,874
ND
ND
0.007
0.07
0.07
21
65
0.001
0.003
ND DUNN CO
4,005
ND
ND
0.003
0.06
0.06
ND
ND
0.001
0.005
ND GRAND FORKS CO
70,683
ND
ND
ND
ND
ND
ND
IN
ND
ND
ND MCKENZIE CO
6,383
ND
ND
ND
ND
ND
6
17
0.001
0.010
ND MCLEAN CO
10,457
ND
ND
ND
ND
ND
7
17
0.002
0.009
ND MERCER CO
9,808
ND
ND
0.004
0.07
0.06
ND
IN
0.003
0.016
ND MORTON CO
23,700
ND
ND
ND
ND
ND
ND
ND
0.006
0.071
ND OLIVER CO
2,381
ND
ND
0.003
0.08
0.06
ND
ND
0.002
0.014
ND STARK CO
22,832
ND
ND
ND
ND
ND
ND
IN
ND
ND
ND STEELE CO
2,420
ND
ND
0.003
0.07
0.06
ND
IN
0.001
0.004
ND WILLIAMS CO
21,129
ND
ND
ND
ND
ND
ND
IN
0.003
0.064
OH ADAMS CO
25,371
ND
ND
ND
ND
ND
ND
ND
0.008
0.056
OH ALLEN CO
109,755
ND
ND
ND
0.11
0.09
17
32
0.003
0.013
OH ASHTABULA CO
99,821
ND
ND
ND
0.10
0.09
ND
ND
0.005
0.019
OH ATHENS CO
59,549
ND
ND
ND
ND
ND
20
38
ND
ND
180
DATA TABLES • APPENDIX A
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-14. Maximum Air Quality Concentrations by County, 1999 (continued)
CO Pb N02 03 03 PM10 PM10 S02 S02
State County 1990 8-hr QMax AM 1-hr 8-hr WtdAM 2nd Max AM 24-hr
Population (ppm) ((jg/m3) (ppm) (ppm) (ppm) (ng/m3) (ng/m3) (ppm) (ppm)
OH
BELMONT CO
71,074
ND
ND
ND
ND
ND
26
69
IN
0.030
OH
BUTLER CO
291,479
ND
0.01
ND
0.12
0.10
31
85
0.007
0.024
OH
CLARK CO
147,548
ND
ND
ND
0.11
0.09
ND
ND
0.004
0.017
OH
CLERMONT CO
150,187
ND
ND
ND
0.12
0.09
ND
ND
0.005
0.020
OH
CLINTON CO
35,415
ND
ND
ND
0.11
0.10
ND
ND
ND
ND
OH
COLUMBIANACO
108,276
ND
ND
ND
ND
ND
IN
135
IN
0.039
OH
CUYAHOGACO
1,412,140
4
0.15
0.025
0.10
0.09
42
106
0.009
0.036
OH
DELAWARE CO
66,929
ND
ND
ND
0.14
0.10
ND
ND
ND
ND
OH
ERIE CO
76,779
ND
ND
ND
ND
ND
IN
IN
ND
ND
OH
FRANKLIN CO
961,437
3
0.05
ND
0.11
0.10
27
86
0.004
0.015
OH
FULTON CO
38,498
ND
0.26
ND
ND
ND
ND
ND
ND
ND
OH
GEAUGA CO
81,129
ND
ND
ND
0.12
0.10
ND
ND
ND
ND
OH
GREENE CO
136,731
ND
ND
ND
0.10
0.09
18
39
ND
ND
OH
HAMILTON CO
866,228
3
0.01
0.022
0.12
0.09
31
60
0.006
0.028
OH
HANCOCK CO
65,536
ND
ND
ND
ND
ND
IN
31
ND
ND
OH
JEFFERSON CO
80,298
3
ND
ND
0.11
0.09
34
75
0.011
0.059
OH
KNOX CO
47,473
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
OH
LAKE CO
215,499
1
ND
ND
0.12
0.10
20
50
0.011
0.062
OH
LAWRENCE CO
61,834
ND
ND
ND
0.12
0.10
27
52
0.005
0.025
OH
LICKING CO
128,300
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
OH
LOGAN CO
42,310
ND
0.23
ND
0.10
0.08
ND
ND
ND
ND
OH
LORAIN CO
271,126
ND
ND
ND
0.12
0.09
29
76
0.006
0.027
OH
LUCAS CO
462,361
3
ND
ND
0.13
0.09
23
58
0.004
0.052
OH
MADISON CO
37,068
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
OH
MAHONING CO
264,806
ND
ND
ND
0.11
0.09
26
63
0.008
0.029
OH
MEDINA CO
122,354
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
OH
MEIGS CO
22,987
ND
ND
ND
ND
ND
ND
ND
0.006
0.034
OH
MIAMI CO
93,182
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
OH
MONROE CO
15,497
ND
ND
ND
ND
ND
25
52
ND
ND
OH
MONTGOMERY CO
573,809
3
0.01
ND
0.13
0.10
24
53
0.005
0.018
OH
MORGAN CO
14,194
ND
ND
ND
ND
ND
ND
ND
0.006
0.038
OH
OTTAWA CO
40,029
ND
ND
ND
ND
ND
25
62
ND
ND
OH
PORTAGE CO
142,585
ND
ND
ND
0.12
0.10
ND
ND
ND
ND
OH
PREBLE CO
40,113
ND
ND
ND
0.10
0.09
ND
ND
ND
ND
OH
RICHLAND CO
126,137
ND
ND
ND
ND
ND
23
53
ND
ND
OH
SANDUSKY CO
61,963
ND
ND
ND
ND
ND
26
69
ND
ND
OH
SCIOTO CO
80,327
ND
ND
ND
ND
ND
32
64
0.007
0.032
OH
SENECA CO
59,733
ND
ND
ND
ND
ND
IN
69
ND
ND
OH
STARK CO
367,585
2
ND
ND
0.11
0.09
24
57
0.007
0.028
OH
SUMMIT CO
514,990
3
0.01
ND
0.11
0.10
23
69
0.011
0.065
OH
TRUMBULL CO
227,813
ND
ND
ND
0.11
0.10
22
59
ND
ND
OH
TUSCARAWAS CO
84,090
ND
ND
ND
ND
ND
ND
ND
0.006
0.028
OH
UNION CO
31,969
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
OH
WARREN CO
113,909
ND
ND
ND
0.11
0.10
ND
ND
ND
ND
OH
WASHINGTON CO
62,254
ND
ND
ND
0.12
0.10
28
72
ND
ND
OH
WOOD CO
113,269
ND
ND
ND
0.10
0.09
ND
ND
ND
ND
OH
WYANDOT CO
22,254
ND
ND
ND
ND
ND
22
63
ND
ND
OK
CLEVELAND CO
174,253
2
ND
0.012
0.09
0.08
ND
IN
ND
ND
OK
COMANCHE CO
111,486
2
ND
ND
0.09
0.08
ND
IN
ND
ND
OK
CUSTER CO
26,897
ND
ND
ND
ND
ND
ND
IN
ND
ND
OK
GARFIELD CO
56,735
ND
ND
0.008
ND
ND
ND
IN
ND
ND
OK
JEFFERSON CO
7,010
ND
ND
ND
0.10
0.08
ND
ND
ND
ND
OK
KAY CO
48,056
ND
ND
ND
ND
ND
IN
IN*
0.004
0.019
OK
LATIMER CO
10,333
ND
ND
ND
0.10
0.07
ND
ND
ND
ND
OK
LOVE CO
8,157
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
APPENDIX A • DATA TABLES
181
-------
NATIONALAIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-14. Maximum Air Quality Concentrations by County, 1999 (continued)
CO
Pb
no2
°3
°3
PM10
PM10
S02
so2
State County
1990
8-hr
QMax
AM
1-hr
8-hr
Wtd AM
2nd Max
AM
24-hr
Population
(ppm)
(jjg/m3)
(PP"i)
(PP"i)
(PP"i)
(jjg/m3)
(jjg/m3)
(ppm)
(ppm)
OK
MCCLAIN CO
22,795
ND
ND
ND
0.10
0.08
ND
ND
ND
ND
OK
MARSHALL CO
10,829
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
OK
MAYES CO
33,366
ND
ND
0.007
ND
ND
ND
IN
ND
ND
OK
MUSKOGEE CO
68,078
ND
ND
0.008
ND
ND
32*
88*
0.003
0.017
OK
OKLAHOMA CO
599,611
4
ND
0.014
0.10
0.08
IN
IN*
0.004
0.009
OK
PITTSBURG CO
40,581
ND
ND
ND
ND
ND
ND
IN
ND
ND
OK
TULSA CO
503,341
4
ND
0.017
0.12
0.09
22*
44*
0.011
0.083
OR
CLACKAMAS CO
278,850
ND
ND
ND
0.09
0.07
IN
IN
ND
ND
OR
COLUMBIA CO
37,557
ND
ND
ND
0.07
0.05
ND
ND
ND
ND
OR
DESCHUTES CO
74,958
5
ND
ND
ND
ND
IN
75
ND
ND
OR
JACKSON CO
146,389
6
0.00
ND
0.08
IN
IN
93
ND
ND
OR
JOSEPHINE CO
62,649
5
ND
ND
ND
ND
IN
39
ND
ND
OR
KLAMATH CO
57,702
5
ND
ND
ND
ND
IN
82
ND
ND
OR
LAKE CO
7,186
ND
ND
ND
ND
ND
IN
94
ND
ND
OR
LANE CO
282,912
5
0.02
ND
0.08
0.07
IN
IN*
ND
ND
OR
MARION CO
228,483
6
ND
ND
0.08
0.07
ND
ND
ND
ND
OR
MULTNOMAH CO
583,887
6
0.00
IN
ND
ND
IN
63
ND
ND
OR
UMATILLA CO
59,249
ND
ND
ND
ND
ND
IN
53
ND
ND
OR
UNION CO
23,598
ND
ND
ND
ND
ND
IN
89
ND
ND
OR
YAMHILL CO
65,551
ND
0.18
ND
ND
ND
ND
ND
ND
ND
PA
ADAMS CO
78,274
1
ND
0.005
ND
ND
ND
ND
ND
ND
PA
ALLEGHENY CO
1,336,449
4
0.06
0.029
0.13
0.10
37
121
0.012
0.089
PA
ARMSTRONG CO
73,478
ND
ND
ND
0.12
0.10
ND
ND
ND
ND
PA
BEAVER CO
186,093
2
0.08
0.019
0.13
0.10
IN
IN
0.015
0.070
PA
BERKS CO
336,523
3
0.84
0.021
0.13
0.10
IN
IN*
0.008
0.027
PA
BLAIR CO
130,542
2
ND
0.013
0.11
0.09
IN
IN*
0.007
0.030
PA
BUCKS CO
541,174
4
ND
0.018
0.15
0.11
IN
IN*
0.005
0.020
PA
CAMBRIA CO
163,029
3
0.09
0.015
0.11
0.09
IN
IN
0.009
0.025
PA
CARBON CO
56,846
ND
0.07
ND
ND
ND
ND
ND
ND
ND
PA
CENTRE CO
123,786
ND
ND
ND
0.10
0.09
ND
ND
ND
ND
PA
CHESTER CO
376,396
ND
ND
ND
ND
ND
ND
IN
ND
ND
PA
CLEARFIELD CO
78,097
ND
ND
ND
0.09
0.08
ND
ND
ND
ND
PA
DAUPHIN CO
237,813
4
ND
0.018
0.13
0.10
IN
IN*
0.005
0.021
PA
DELAWARE CO
547,651
ND
0.05
0.017
0.13
0.10
IN
IN*
0.010
0.034
PA
ERIE CO
275,572
6
ND
0.015
0.11
0.10
IN
IN*
0.010
0.043
PA
FRANKLIN CO
121,082
ND
ND
ND
0.12
0.10
ND
ND
ND
ND
PA
GREENE CO
39,550
2
ND
0.003
0.12
0.10
ND
ND
0.009
0.022
PA
LACKAWANNA CO
219,039
2
ND
0.014
0.12
0.10
IN
IN
0.005
0.021
PA
LANCASTER CO
422,822
2
ND
0.015
0.13
0.10
IN
IN
0.005
0.021
PA
LAWRENCE CO
96,246
3
ND
0.020
0.11
0.09
IN
IN*
0.008
0.035
PA
LEHIGH CO
291,130
3
ND
0.015
0.13
0.11
IN
IN*
0.007
0.030
PA
LUZERNE CO
328,149
3
ND
0.015
0.11
0.09
IN
IN
0.007
0.023
PA
LYCOMING CO
118,710
ND
ND
ND
0.09
0.08
IN
IN
0.005
0.021
PA
MERCER CO
121,003
ND
ND
ND
0.11
0.09
ND
IN
0.007
0.039
PA
MONROE CO
95,709
0
ND
ND
0.12
0.10
ND
ND
0.003
0.006
PA
MONTGOMERYCO
678,111
2
ND
0.016
0.13
0.10
IN
IN*
0.006
0.020
PA
NORTHAMPTON CO
247,105
3
ND
0.017
0.13
0.11
IN
IN
0.009
0.037
PA
PERRY CO
41,172
ND
ND
0.006
0.11
0.09
ND
IN
0.003
0.012
PA
PHILADELPHIA CO
1,585,577
5
0.84
0.032
0.12
0.10
IN
IN
0.006
0.028
PA
SCHUYLKILL CO
152,585
2
ND
ND
ND
ND
ND
ND
0.007
0.038
PA
TIOGA CO
41,126
ND
ND
ND
0.09
0.08
ND
ND
ND
ND
PA
WARREN CO
45,050
ND
ND
ND
ND
ND
ND
ND
0.015
0.097
PA
WASHINGTON CO
204,584
2
ND
0.016
0.12
0.10
IN
IN
0.010
0.036
PA
WESTMORELAND CO
370,321
2
0.04
0.018
0.13
0.10
IN
IN
0.011
0.037
PA
YORK CO
339,574
2
ND
0.019
0.12
0.09
IN
IN
0.007
0.019
182
DATA TABLES • APPENDIX A
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-14. Maximum Air Quality Concentrations by County, 1999 (continued)
CO Pb N02 03 03 PM10 PM10 S02 S02
State County 1990 8-hr QMax AM 1-hr 8-hr WtdAM 2nd Max AM 24-hr
Population (ppm) ((jg/m3) (ppm) (ppm) (ppm) (ng/m3) (ng/m3) (ppm) (ppm)
Rl
KENT CO
161,135
ND
ND
IN
0.12
0.09
14
37
ND
ND
Rl
PROVIDENCE CO
596,270
4
ND
0.024
0.11
0.08
29
61
0.007
0.026
Rl
WASHINGTON CO
110,006
ND
ND
ND
0.13
0.09
ND
ND
ND
ND
SC
ABBEVILLE CO
23,862
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
sc
AIKEN CO
120,940
ND
0.00
0.005
0.11
0.08
IN
44
IN
0.007
SC
ANDERSON CO
145,196
ND
ND
ND
0.12
0.10
ND
ND
ND
ND
sc
BARNWELL CO
20,293
ND
ND
IN
0.10
0.09
19*
CO
0.002
0.004
SC
BEAUFORT CO
86,425
ND
0.00
ND
ND
ND
ND
ND
ND
ND
sc
BERKELEY CO
128,776
ND
ND
ND
0.10
0.08
ND
ND
ND
ND
sc
CHARLESTON CO
295,039
4
0.01
0.010
0.10
0.08
21
47
0.002
0.011
sc
CHEROKEE CO
44,506
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
sc
CHESTER CO
32,170
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
sc
COLLETON CO
34,377
ND
ND
ND
0.09
0.08
ND
ND
ND
ND
sc
DARLINGTON CO
61,851
ND
ND
ND
0.10
0.09
ND
ND
ND
ND
sc
DILLON CO
29,114
ND
0.01
ND
ND
ND
ND
ND
ND
ND
sc
EDGEFIELD CO
18,375
ND
ND
ND
0.10
0.09
ND
ND
ND
ND
sc
FAIRFIELD CO
22,295
ND
ND
ND
ND
ND
^r
CM
LO
ND
ND
sc
FLORENCE CO
114,344
ND
0.01
ND
ND
ND
ND
ND
ND
ND
sc
GEORGETOWN CO
46,302
ND
0.02
ND
ND
ND
32
77
IN
0.015
sc
GREENVILLE CO
320,167
5
0.01
0.017
ND
ND
IN
52
0.003
0.009
sc
GREENWOOD CO
59,567
ND
0.02
ND
ND
ND
ND
ND
ND
ND
sc
HAMPTON CO
18,191
ND
0.01
ND
ND
ND
ND
ND
ND
ND
sc
HORRY CO
144,053
ND
0.01
ND
ND
ND
ND
ND
ND
ND
sc
KERSHAW CO
43,599
ND
0.01
ND
ND
ND
ND
ND
ND
ND
sc
LEXINGTON CO
167,611
ND
0.04
ND
ND
ND
IN
148
0.004
0.017
sc
OCONEE CO
57,494
ND
ND
ND
0.10
0.09
ND
ND
0.002
0.006
sc
PICKENS CO
93,894
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
sc
RICHLAND CO
285,720
4
0.01
0.014
0.12
0.09
^r
CM
122*
0.003
0.010
sc
SPARTANBURG CO
226,800
ND
0.01
ND
0.12
0.10
26
46
ND
ND
sc
UNION CO
30,337
ND
ND
ND
0.10
0.09
ND
ND
ND
ND
sc
WILLIAMSBURG CO
36,815
ND
ND
ND
0.09
0.08
ND
ND
ND
ND
sc
YORK CO
131,497
ND
0.02
ND
0.11
0.09
26
49
ND
ND
SD
BROOKINGS CO
25,207
ND
ND
ND
ND
ND
24
71
ND
ND
SD
MINNEHAHA CO
123,809
ND
ND
ND
0.07
IN
CM
CM
44*
ND
ND
SD
PENNINGTON CO
81,343
ND
ND
ND
ND
ND
31*
108*
ND
ND
TN
ANDERSON CO
68,250
ND
ND
ND
0.12
0.09
ND
ND
0.004
0.028
TN
BLOUNT CO
85,969
1
ND
0.003
0.12
0.11
ND
IN
0.009
0.056
TN
BRADLEY CO
73,712
ND
ND
0.015
ND
ND
28*
CM
LO
0.008
0.034
TN
COFFEE CO
40,339
ND
ND
IN
ND
ND
ND
ND
IN
0.005
TN
DAVIDSON CO
510,784
5
ND
0.019
0.12
0.10
32
75
0.005
0.022
TN
DICKSON CO
35,061
ND
ND
IN
0.11
0.10
ND
IN
0.003
0.011
TN
GREENE CO
55,853
ND
ND
ND
ND
ND
IN
50
ND
ND
TN
HAMBLEN CO
50,480
ND
ND
ND
ND
ND
ND
IN
ND
ND
TN
HAMILTON CO
285,536
ND
ND
ND
0.12
0.10
29
49
ND
ND
TN
HAWKINS CO
44,565
ND
ND
ND
ND
ND
ND
ND
0.008
0.044
TN
HAYWOOD CO
19,437
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
TN
HUMPHREYS CO
15,795
ND
ND
ND
ND
ND
ND
ND
0.004
0.026
TN
JEFFERSON CO
33,016
ND
ND
ND
0.13
0.10
ND
ND
ND
ND
TN
KNOX CO
335,749
4
0.00
ND
0.13
0.10
30
61
ND
ND
TN
LAWRENCE CO
35,303
ND
ND
ND
0.12
0.10
ND
IN
ND
ND
TN
MCMINN CO
42,383
ND
ND
0.016
ND
ND
CO
CD
69*
0.008
0.027
TN
MADISON CO
77,982
ND
ND
ND
ND
ND
IN
43
ND
ND
TN
MAURY CO
54,812
ND
ND
ND
ND
ND
ND
IN
ND
ND
TN
MONTGOMERY CO
100,498
ND
ND
ND
ND
ND
23
39
0.005
0.016
TN
POLK CO
13,643
ND
ND
ND
ND
ND
ND
ND
0.007
0.021
APPENDIX A • DATA TABLES
183
-------
NATIONALAIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-14. Maximum Air Quality Concentrations by County, 1999 (continued)
CO
Pb
no2
°3
°3
PM10
PM10
S02
so2
State County
1990
8-hr
QMax
AM
1-hr
8-hr
Wtd AM
2nd Max
AM
24-hr
Population
(ppm)
(jjg/m3)
(PP"i)
(PP"i)
(PP"i)
(jjg/m3)
(jjg/m3)
(ppm)
(ppm)
TN
PUTNAM CO
51,373
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
TN
ROANE CO
47,227
ND
ND
IN
0.12
0.09
26
44
0.003
0.019
TN
RUTHERFORD CO
118,570
ND
ND
ND
0.12
0.10
ND
ND
ND
ND
TN
SEVIER CO
51,043
ND
ND
ND
0.11
0.10
ND
ND
ND
ND
TN
SHELBY CO
826,330
5
0.65
0.025
0.13
0.10
27
64
0.006
0.028
TN
STEWART CO
9,479
ND
ND
ND
ND
ND
ND
ND
0.003
0.011
TN
SULLIVAN CO
143,596
3
0.12
0.016
0.11
0.09
ND
IN
0.010
0.039
TN
SUMNER CO
103,281
IN
ND
IN
0.12
0.10
ND
IN
0.004
0.035
TN
UNION CO
13,694
ND
ND
ND
ND
ND
43
148
ND
ND
TN
WASHINGTON CO
92,315
ND
ND
ND
ND
ND
ND
IN
ND
ND
TN
WILLIAMSON CO
81,021
ND
1.02
ND
0.11
0.10
ND
ND
ND
ND
TN
WILSON CO
67,675
ND
ND
ND
0.12
0.09
ND
ND
ND
ND
TX
BEXAR CO
1,185,394
4
ND
0.025
0.11
0.09
IN
IN*
ND
ND
TX
BOWIE CO
81,665
ND
ND
ND
ND
ND
ND
ND
IN
0.007
TX
BRAZORIA CO
191,707
ND
ND
ND
0.16
0.11
ND
ND
ND
ND
TX
BREWSTER CO
8,681
ND
ND
0.000
0.08
0.06
ND
ND
0.001
0.001
TX
CAMERON CO
260,120
3
0.01
ND
0.08
0.07
CM
CM
cn
CD
0.002
0.004
TX
CASS CO
29,982
ND
ND
ND
ND
ND
ND
ND
IN
0.008
TX
COLLIN CO
264,036
ND
0.82
ND
0.14
0.10
IN
IN*
ND
ND
TX
DALLAS CO
1,852,810
3
0.00
0.021
0.13
0.10
CM
CO
61*
0.002
0.007
TX
DENTON CO
273,525
ND
ND
0.008
0.14
0.11
ND
ND
ND
ND
TX
ELLIS CO
85,167
ND
ND
ND
0.12
0.10
LO
CM
CM
LO
0.004
0.033
TX
EL PASO CO
591,610
8
0.15
0.028
0.11
0.07
63
303
0.003
0.016
TX
GALVESTON CO
217,399
ND
ND
0.005
0.18
0.12
CO
CM
CO
0.007
0.040
TX
GREGG CO
104,948
ND
ND
0.007
0.13
0.11
ND
ND
0.002
0.011
TX
HARRIS CO
2,818,199
4
0.02
0.024
0.20
0.12
LO
116*
0.005
0.019
TX
HIDALGO CO
383,545
ND
ND
ND
0.09
0.08
ND
IN
ND
ND
TX
JEFFERSON CO
239,397
ND
ND
0.011
0.10
0.08
ND
ND
0.007
0.051
TX
LUBBOCK CO
222,636
ND
ND
ND
ND
ND
18*
CM
ND
ND
TX
MARION CO
9,984
ND
ND
0.005
0.12
0.09
ND
ND
ND
ND
TX
MONTGOMERYCO
182,201
ND
ND
IN
0.12
ND
ND
ND
ND
ND
TX
NUECES CO
291,145
ND
ND
ND
0.10
0.09
LO
CO
88*
0.002
0.019
TX
ORANGE CO
80,509
ND
ND
0.009
0.09
0.06
ND
ND
ND
ND
TX
SMITH CO
151,309
ND
ND
0.007
0.12
0.10
ND
ND
ND
ND
TX
TARRANT CO
1,170,103
3
ND
0.017
0.15
0.10
CM
CM
44*
ND
ND
TX
TRAVIS CO
576,407
1
ND
0.006
0.11
0.10
IN
IN
ND
ND
TX
VICTORIA CO
74,361
ND
ND
ND
0.10
0.09
ND
ND
ND
ND
TX
WEBB CO
133,239
4
0.02
ND
0.08
0.07
IN
IN
ND
ND
UT
CACHE CO
70,183
IN
ND
ND
0.08
0.07
IN
65
ND
ND
UT
DAVIS CO
187,941
3
ND
0.020
0.11
0.08
ND
ND
0.002
0.006
UT
GRAND CO
6,620
ND
ND
ND
ND
ND
IN
57
ND
ND
UT
SALT LAKE CO
725,956
6
0.08
0.028
0.11
0.08
CD
113*
0.004
0.010
UT
SAN JUAN CO
12,621
ND
ND
ND
0.08
0.07
ND
ND
ND
ND
UT
UTAH CO
263,590
6
ND
0.024
0.11
0.08
CO
CO
91*
ND
ND
UT
WASHINGTON CO
48,560
ND
ND
ND
ND
ND
ND
IN
ND
ND
UT
WEBER CO
158,330
6
ND
0.026
0.10
0.07
CM
70*
ND
ND
VT
BENNINGTON CO
35,845
ND
ND
ND
0.11
0.08
ND
ND
ND
ND
VT
CHITTENDEN CO
131,761
2
ND
0.017
0.09
0.08
ND
IN
0.002
0.008
VT
RUTLAND CO
62,142
2
ND
0.012
ND
ND
ND
IN
0.005
0.022
VT
WASHINGTON CO
54,928
ND
ND
ND
ND
ND
ND
IN
ND
ND
VA
ARLINGTON CO
170,936
4
ND
0.025
0.13
0.10
ND
ND
ND
ND
VA
CAROLINE CO
19,217
ND
ND
IN
0.11
0.09
ND
ND
ND
ND
VA
CARROLL CO
26,594
ND
ND
ND
ND
ND
19
39
ND
ND
VA
CHARLES CITY CO
6,282
ND
ND
0.011
0.13
0.10
ND
ND
0.005
0.017
VA
CHESTERFIELD CO
209,274
ND
ND
ND
0.12
0.09
ND
ND
ND
ND
184
DATA TABLES • APPENDIX A
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-14. Maximum Air Quality Concentrations by County, 1999 (continued)
CO Pb N02 03 03 PM10 PM10 S02 S02
State County 1990 8-hr QMax AM 1-hr 8-hr WtdAM 2nd Max AM 24-hr
Population (ppm) ((jg/m3) (ppm) (ppm) (ppm) (ng/m3) (ng/m3) (ppm) (ppm)
VA
CULPEPERCO
27,791
ND
ND
ND
ND
ND
18
40
ND
ND
VA
FAIRFAX CO
818,584
3
ND
0.023
0.12
0.10
20
56
0.009
0.026
VA
FAUQUIER CO
48,741
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
VA
FREDERICK CO
45,723
ND
ND
ND
0.10
0.09
ND
ND
ND
ND
VA
HANOVER CO
63,306
ND
ND
ND
0.13
0.10
ND
ND
ND
ND
VA
HENRICO CO
217,881
ND
ND
ND
0.12
0.10
ND
ND
ND
ND
VA
KING WILLIAM CO
10,913
ND
ND
ND
ND
ND
18
45
ND
ND
VA
LOUDOUN CO
86,129
ND
ND
0.014
0.11
0.09
ND
ND
ND
ND
VA
MADISON CO
11,949
ND
ND
ND
0.11
0.09
ND
ND
IN
0.010
VA
NORTHUMBERLAND CO
10,524
ND
ND
ND
ND
ND
19
53
ND
ND
VA
PAGE CO
21,690
ND
ND
ND
0.09
0.09
ND
ND
ND
ND
VA
PRINCE WILLIAM CO
215,686
ND
ND
0.012
0.11
0.09
IN
IN
ND
ND
VA
ROANOKE CO
79,332
ND
ND
0.012
0.11
0.09
ND
ND
0.003
0.010
VA
ROCKBRIDGE CO
18,350
ND
ND
ND
0.10
0.08
ND
ND
ND
ND
VA
ROCKINGHAM CO
57,482
ND
ND
ND
ND
ND
25
41
0.003
0.013
VA
STAFFORD CO
61,236
ND
ND
ND
0.12
0.09
ND
ND
ND
ND
VA
TAZEWELL CO
45,960
ND
ND
ND
ND
ND
IN
IN
ND
ND
VA
WARREN CO
26,142
ND
ND
ND
ND
ND
20
40
ND
ND
VA
WISE CO
39,573
ND
ND
ND
ND
ND
21
39
ND
ND
VA
WYTHE CO
25,466
ND
ND
ND
0.10
0.09
ND
ND
ND
ND
VA
ALEXANDRIA
111,183
4
ND
0.025
0.12
0.10
ND
ND
0.005
0.024
VA
CHARLOTTESVILLE
40,341
ND
ND
ND
ND
ND
IN
37
ND
ND
VA
CHESAPEAKE
151,976
ND
ND
ND
ND
ND
IN
44
ND
ND
VA
FREDERICKSBURG
19,027
ND
ND
ND
ND
ND
18
37
ND
ND
VA
HAMPTON
133,793
3
ND
ND
0.14
0.10
19
50
0.004
0.014
VA
NEWPORT NEWS
170,045
2
ND
ND
ND
ND
ND
ND
ND
ND
VA
NORFOLK
261,229
5
ND
0.017
ND
ND
19
46
0.007
0.022
VA
RICHMOND
203,056
2
ND
0.020
ND
ND
19
36
0.005
0.017
VA
ROANOKE
96,397
4
ND
ND
ND
ND
IN
64
ND
ND
VA
SUFFOLK
52,141
ND
ND
ND
0.13
0.09
ND
ND
ND
ND
VA
WINCHESTER
21,947
ND
ND
ND
ND
ND
22
46
ND
ND
WA
ASOTIN CO
17,605
ND
ND
ND
ND
ND
31
82
ND
ND
WA
BENTON CO
112,560
ND
ND
ND
ND
ND
IN
86
ND
ND
WA
CHELAN CO
52,250
ND
ND
ND
ND
ND
IN
44
ND
ND
WA
CLALLAM CO
56,464
ND
ND
ND
0.05
0.04
ND
IN
0.002
0.007
WA
CLARK CO
238,053
7
ND
ND
0.07
0.06
16*
34*
ND
ND
WA
COWLITZ CO
82,119
ND
ND
ND
0.07
0.05
20*
38*
ND
ND
WA
KING CO
1,507,319
6
0.05
0.019
0.09
0.07
IN
50
IN
0.018
WA
KITSAP CO
189,731
ND
ND
ND
ND
ND
15*
34*
ND
ND
WA
KITTITAS CO
26,725
ND
ND
ND
ND
ND
IN
46
ND
ND
WA
KLICKITAT CO
16,616
ND
ND
ND
0.08
0.06
ND
ND
ND
ND
WA
LEWIS CO
59,358
ND
ND
ND
0.06
IN
ND
ND
ND
ND
WA
PIERCE CO
586,203
7
ND
ND
0.09
0.07
17*
56*
IN
0.020
WA
SKAGIT CO
79,555
ND
ND
ND
0.06
0.05
ND
ND
IN
0.025
WA
SNOHOMISH CO
465,642
5
ND
ND
ND
ND
16*
35*
IN
0.011
WA
SPOKANE CO
361,364
6
ND
ND
0.07
0.07
26*
86*
ND
ND
WA
STEVENS CO
30,948
ND
ND
ND
ND
ND
IN
60
ND
ND
WA
THURSTON CO
161,238
5
ND
ND
0.08
0.06
IN
35
ND
ND
WA
WALLA WALLA CO
48,439
ND
ND
ND
ND
ND
40*
92*
ND
ND
WA
WHATCOM CO
127,780
ND
ND
ND
0.06
0.05
14
26
IN
0.016
WA
YAKIMA CO
188,823
5
ND
ND
ND
ND
25*
82*
ND
ND
WV
BERKELEY CO
59,253
ND
ND
ND
ND
ND
22
57
ND
ND
WV
BROOKE CO
26,992
ND
ND
ND
ND
ND
28
61
0.012
0.065
WV
CABELL CO
96,827
ND
ND
ND
0.12
0.10
IN
45
0.005
0.019
WV
FAYETTE CO
47,952
ND
ND
ND
ND
ND
IN
IN
ND
ND
APPENDIX A • DATA TABLES
185
-------
NATIONALAIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-14. Maximum Air Quality Concentrations by County, 1999 (continued)
CO
Pb
no2
°3
°3
PM10
PM10
S02
S02
State County
1990
8-hr
QMax
AM
1-hr
8-hr
Wtd AM
2nd Max
AM
24-hr
Population
(ppm)
(jjg/m3)
(PP"i)
(PP"i)
(PP"i)
(jjg/m3)
(jjg/m3)
(ppm)
(ppm)
VW GREENBRIER CO
34,693
ND
ND
ND
0.10
0.08
ND
ND
ND
ND
VW HANCOCK CO
35,233
5
ND
ND
0.11
0.09
31
98
0.016
0.065
VW HARRISON CO
69,371
ND
ND
ND
ND
ND
18
45
ND
ND
VW KANAWHA CO
207,619
IN
ND
ND
0.13
0.10
IN
45
0.010
0.046
VW MARSHALL CO
37,356
ND
ND
ND
ND
ND
IN
59
0.015
0.060
VW MONONGALIA CO
75,509
ND
ND
ND
ND
ND
21
58
0.010
0.049
VW OHIO CO
50,871
3
ND
ND
0.10
0.09
25
50
0.010
0.034
VW PUTNAM CO
42,835
ND
ND
ND
ND
ND
IN
IN
ND
ND
VW RALEIGH CO
76,819
ND
ND
ND
ND
ND
IN
39
ND
ND
VW SUMMERS CO
14,204
ND
ND
ND
ND
ND
IN
37
ND
ND
VW WAYNE CO
41,636
ND
ND
IN
ND
ND
IN
IN
0.009
0.042
WV WOOD CO
86,915
ND
ND
ND
0.12
0.10
25
63
0.013
0.058
Wl BROWN CO
194,594
ND
ND
ND
0.10
0.09
ND
ND
0.003
0.011
Wl COLUMBIA CO
45,088
ND
ND
ND
0.10
0.09
ND
ND
ND
ND
Wl DANE CO
367,085
2
ND
ND
0.10
0.09
21*
CD
IN
0.008
Wl DODGE CO
76,559
ND
ND
ND
0.10
0.09
ND
ND
ND
ND
Wl DOOR CO
25,690
ND
ND
ND
0.11
0.10
ND
ND
ND
ND
Wl DOUGLAS CO
41,758
ND
ND
ND
ND
ND
19
44
ND
ND
Wl FLORENCE CO
4,590
ND
ND
ND
0.10
0.09
ND
ND
ND
ND
Wl FOND DU LAC CO
90,083
ND
ND
ND
0.10
0.09
ND
ND
ND
ND
Wl JEFFERSON CO
67,783
ND
ND
ND
0.11
0.10
ND
ND
ND
ND
Wl KENOSHA CO
128,181
ND
ND
ND
0.13
0.10
ND
ND
ND
ND
Wl KEWAUNEE CO
18,878
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
Wl MANITOWOC CO
80,421
ND
ND
ND
0.12
0.10
ND
ND
ND
ND
Wl MARATHON CO
115,400
ND
ND
ND
0.10
0.08
IN
64
0.003
0.040
Wl MILWAUKEE CO
959,275
2
ND
0.022
0.12
0.10
27
60
0.004
0.024
Wl ONEIDA CO
31,679
ND
ND
ND
0.09
0.08
ND
ND
0.006
0.065
Wl OUTAGAMIE CO
140,510
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
Wl OZAUKEE CO
72,831
ND
ND
IN
0.12
0.10
ND
ND
ND
ND
Wl POLK CO
34,773
IN
ND
ND
ND
ND
ND
ND
ND
ND
Wl RACINE CO
175,034
3
ND
ND
0.11
0.09
ND
ND
ND
ND
Wl ROCK CO
139,510
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
Wl ST CROIX CO
50,251
ND
ND
ND
0.08
0.07
ND
ND
ND
ND
Wl SAUK CO
46,975
ND
ND
0.004
0.10
0.09
ND
ND
ND
ND
Wl SHEBOYGAN CO
103,877
ND
ND
ND
0.13
0.09
ND
ND
ND
ND
Wl VERNON CO
25,617
ND
ND
ND
0.08
0.08
IN
IN
ND
ND
Wl VILAS CO
17,707
ND
ND
ND
0.09
0.08
11*
LO
ND
ND
Wl WALWORTH CO
75,000
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
Wl WASHINGTON CO
95,328
ND
ND
ND
0.10
0.09
ND
ND
ND
ND
Wl WAUKESHA CO
304,715
2
ND
ND
0.11
0.10
23
57
ND
ND
Wl WINNEBAGO CO
140,320
ND
ND
ND
0.10
0.09
ND
ND
ND
ND
Wl WOOD CO
73,605
ND
ND
ND
ND
ND
ND
ND
0.003
0.042
WY ALBANY CO
30,797
ND
ND
ND
ND
ND
IN
50
ND
ND
WY CAMPBELL CO
29,370
ND
ND
ND
ND
ND
39
CM
CO
ND
ND
WY CARBON CO
16,659
ND
ND
ND
ND
ND
ND
IN
ND
ND
WY CONVERSE CO
11,128
ND
ND
ND
ND
ND
28
78
ND
ND
WY FREMONT CO
33,662
ND
ND
ND
ND
ND
IN
63
ND
ND
WY LARAMIE CO
73,142
ND
ND
ND
ND
ND
15
30
ND
ND
WY LINCOLN CO
12,625
ND
ND
ND
ND
ND
IN
IN
ND
ND
WY NATRONA CO
61,226
ND
ND
ND
ND
ND
IN
52
ND
ND
WY PARK CO
23,178
ND
ND
ND
ND
ND
IN
40
ND
ND
WY SHERIDAN CO
23,562
ND
ND
ND
ND
ND
31*
117*
ND
ND
WY SWEETWATER CO
38,823
ND
ND
ND
ND
ND
LO
CM
72*
ND
ND
WY TETON CO
11,172
ND
ND
ND
0.08
0.07
IN
39
ND
ND
PR BARCELONETA CO
18,942
ND
ND
ND
ND
ND
IN
49
IN
0.014
186
DATA TABLES • APPENDIX A
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
CO Pb no2 o3 o3 pm10 pm10 S02 S02
State County 1990 8-hr QMax AM 1-hr 8-hr WtdAM 2nd Max AM 24-hr
Population (ppm) ((jg/m3) (ppm) (ppm) (ppm) (ng/m3) (ng/m3) (ppm) (ppm)
PR
BAYAMON CO
196,206
ND
ND
ND
ND
ND
IN
55
0.003
0.021
PR
CAROLINA CO
165,954
ND
ND
ND
ND
ND
IN
IN
ND
ND
PR
CATANO CO
26,243
ND
ND
IN
0.08
0.05
IN
IN
IN
0.017
PR
FAJARDO CO
32,087
ND
ND
ND
ND
ND
IN
73
ND
ND
PR
GUAYAMACO
40,183
ND
ND
ND
ND
ND
27
61
ND
ND
PR
GUAYNABO CO
80,742
ND
ND
ND
ND
ND
38
84
ND
ND
PR
HUMACAO CO
46,134
ND
ND
ND
ND
ND
IN
60
ND
ND
PR
MANATI CO
36,562
ND
ND
ND
ND
ND
25
58
ND
ND
PR
PONCE CO
189,046
ND
ND
ND
ND
ND
39
86
ND
ND
PR
RIO GRANDE CO
34,283
ND
ND
ND
ND
ND
IN
IN
ND
ND
PR
SAN JUAN CO
434,849
8
0.02
ND
ND
ND
IN
60
ND
ND
CO - Highest second maximum non-overlapping 8-hour concentration (Applicable NAAQS is 9 ppm)
Pb - Highest quarterly maximum concentration (Applicable NAAQS is 1.5 pg/m3)
N02 - Highest arithmetic mean concentration (Applicable NAAQS is 0.053 ppm)
03 (1-hr) - Highest second daily maximum 1-hour concentration (Applicable NAAQS is 0.12 ppm)
03 (8-hr) - Highest fourth daily maximum 8-hour concentration (Applicable NAAQS is 0.08 ppm)
PM10 - Highest weighted annual mean concentration (Applicable NAAQS is 50 pg/m3)
- Highest second maximum 24-hour concentration (Applicable NAAQS is 150 pg/m3)
S02 - Highest annual mean concentration (Applicable NAAQS is 0.03 ppm)
- Highest second maximum 24-hour concentration (Applicable NAAQS is 0.14 ppm)
ND - Indicates data not available
IN - Indicates insufficient data to calculate summary statistic
Wtd - Weighted
AM - Annual mean
|jg/m3 - Units are micrograms per cubic meter
PPM - Units are parts per million
Data from exceptional events not included.
(*) - These PM10 statistics were converted from local temperature and pressure to standard temperature and pressure to ensure all PM10 data
in this table reflect standard conditions.
Note: The reader is cautioned that this summary is not adequate in itself to numerically rank MSAs according to their air quality. The monitoring
data represent the quality of air in the vicinity of the monitoring site but may not necessarily represent urban-wide air quality.
APPENDIX A • DATA TABLES
187
-------
NATIONALAIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-15. Maximum Air Quality Concentrations by Metropolitan Statistical Area, 1999
CO
Pb
no2
°3
°3
PM10
PM10
S02
so2
Metropolitan Statistical Area
1990
8-hr
QMax
AM
1-hr
8-hr
Wtd AM
2nd Max
AM
24-hr
Population
(ppm)
(jjg/m3)
(PP"i)
(PP"i)
(PP"i)
(jjg/m3)
(jjg/m3)
(ppm)
(ppm)
AKRON, OH
657,575
3
0.01
ND
0.12
0.10
23
69
0.011
0.065
ALBANY, GA
112,561
ND
ND
ND
ND
ND
26
60
ND
ND
ALBANY-SCHENECTADY-TROY, NY
861,424
4
ND
IN
0.11
0.09
ND
ND
0.003
0.016
ALBUQUERQUE, NM
589,131
5
ND
0.016
0.10
0.08
35*
123*
ND
ND
ALLENTOWN-BETHLEHEM-EASTON, PA
595,081
3
0.07
0.017
0.13
0.11
ND
36*
0.009
0.037
ALTOONA, PA
130,542
2
ND
0.013
0.11
0.09
ND
ND
0.007
0.030
ANCHORAGE, AK
226,338
8
ND
ND
ND
ND
15
73
ND
ND
ANN ARBOR, Ml
490,058
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
APPLETON-OSHKOSH-NEENAH, Wl
315,121
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
ASHEVILLE, NC
191,774
ND
ND
ND
0.10
0.08
21
41
ND
ND
ATLANTA, GA
2,959,950
4
0.05
0.024
0.16
0.13
35
72
0.005
0.023
ATLANTIC-CAPE MAY, NJ
319,416
ND
ND
ND
0.12
0.10
22
46
0.003
0.009
AUGUSTA-AIKEN, GA-SC
415,184
ND
0.00
0.005
0.11
0.09
IN
49
IN
IN
AUSTIN-SAN MARCOS, TX
846,227
1
ND
0.006
0.11
0.10
ND
ND
ND
ND
BAKERSFIELD, CA
543,477
4
0.00
0.025
0.14
0.11
59
141
IN
IN
BALTIMORE, MD
2,382,172
5
0.00
0.024
0.15
0.11
29
61
0.006
0.020
BANGOR, ME
91,629
ND
ND
ND
0.09
0.08
17
32
ND
ND
BATON ROUGE, LA
528,264
5
0.06a
0.019
0.12
0.10
34
78
0.006
0.025
BEAUMONT-PORT ARTHUR, TX
361,226
ND
ND
0.011
0.10
0.08
ND
ND
0.007
0.051
BELLINGHAM, WA
127,780
ND
ND
ND
0.06
0.05
14
26
IN
IN
BENTON HARBOR, Ml
161,378
ND
ND
ND
0.11
0.10
ND
ND
ND
ND
BERGEN-PASSAIC, NJ
1,278,440
4
ND
ND
0.13
0.10
34
73
0.005
0.020
BILLINGS, MT
113,419
6
ND
ND
ND
ND
21
69
0.007
0.037
BILOXI-GULFPORT-PASCAGOULA, MS
312,368
ND
ND
0.006
0.11
0.10
IN
38
0.003
0.024
BIRMINGHAM, AL
840,140
5
ND
0.010
0.13
0.10
28
108
IN
IN
BISMARCK, ND
83,831
ND
ND
ND
ND
ND
ND
ND
0.006
0.071
BOISE CITY, ID
295,851
6
ND
0.021
ND
ND
36
101
ND
ND
BOSTON, MA-NH
3,227,707
4
0.03
0.030
0.12
0.09
30
65
0.007
0.040
BOULDER-LONGMONT, CO
225,339
4
ND
ND
0.10
0.08
IN
56
ND
ND
BRAZORIA, TX
191,707
ND
ND
ND
0.16
0.11
ND
ND
ND
ND
BREMERTON, WA
189,731
ND
ND
ND
ND
ND
15
33
ND
ND
BRIDGEPORT, CT
443,722
3
ND
0.018
0.14
0.11
19
41
0.006
0.023
BROCKTON, MA
236,409
ND
ND
IN
0.10
0.08
ND
ND
ND
ND
BROWNSVILLE-HARLINGEN-SAN BENITO, TX
260,120
3
0.01
ND
0.08
0.07
22*
59*
0.002
0.004
BUFFALO-NIAGARA FALLS, NY
1,189,288
3
0.02
0.022
0.10
0.09
IN
48
0.010
0.052
BURLINGTON, VT
151,506
2
ND
0.017
ND
ND
ND
ND
0.002
0.008
CANTON-MASSILLON, OH
394,106
2
ND
ND
0.11
0.09
24
57
0.007
0.028
CASPER, WY
61,226
ND
ND
ND
ND
ND
IN
52
ND
ND
CEDAR RAPIDS, IA
168,767
2
ND
ND
0.10
0.08
IN
54
0.005
0.071
CHAMPAIGN-URBANA, IL
173,025
ND
ND
ND
0.11
0.09
23
47
0.002
0.010
CHARLESTON-NORTH CHARLESTON, SC
506,875
4
0.01
0.010
0.10
0.08
21
47
0.002
0.011
CHARLESTON, VW
250,454
IN
ND
ND
0.13
0.10
IN
45
0.010
0.046
CHARLOTTE-GASTONIA-ROCK HILL, NC-SC
1,162,093
4
0.02
0.018
0.13
0.11
30
60
0.004
0.013
CHARLOTTESVILLE, VA
131,107
ND
ND
ND
ND
ND
IN
37
ND
ND
CHATTANOOGA, TN-GA
424,347
ND
ND
ND
0.12
0.10
29
57
ND
ND
CHEYENNE, WY
73,142
ND
ND
ND
ND
ND
15
30
ND
ND
CHICAGO, IL
7,410,858
5
0.06
0.032
0.11
0.10
40
120
0.009
0.044
CHICO-PARADISE, CA
182,120
4
0.00
0.015
0.11
0.09
29
139
ND
ND
CINCINNATI, OH-KY-IN
1,526,092
3
0.01
0.022
0.12
0.10
31
60
0.008
0.030
CLARKSVILLE-HOPKINSVILLE, TN-KY
169,439
ND
ND
ND
0.12
0.09
23
39
0.005
0.016
CLEVELAND-LORAIN-ELYRIA, OH
2,202,069
4
0.15b
0.025
0.12
0.10
42
106
0.011
0.062
COLORADO SPRINGS, CO
397,014
5
0.01
0.019
0.08
0.06
22
80
0.004
0.020
COLUMBIA, SC
453,331
4
0.04
0.014
0.12
0.09
24
148
0.004
0.017
188
DATA TABLES • APPENDIX A
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-15. Maximum Air Quality Concentrations by Metropolitan Statistical Area, 1999 (continued)
CO
Pb
no2
°3
°3
PM10
PM10
S02
so2
Metropolitan Statistical Area
1990
8-hr
QMax
AM
1-hr
8-hr
Wtd AM
2nd Max
AM
24-hr
Population
(ppm)
(jjg/m3)
(PP"i)
(PP"i)
(PP"i)
(jjg/m3)
(jjg/m3)
(ppm)
(ppm)
COLUMBUS, GA-AL
260,860
ND
1.04c
ND
0.11
0.10
24
49
ND
ND
COLUMBUS, OH
1,345,450
3
0.05d
ND
0.14
0.10
27
86
0.004
0.015
CORPUS CHRISTI, TX
349,894
ND
ND
ND
0.10
0.09
35*
88*
0.002
0.019
DALLAS, TX
2,676,248
3
0.82e
0.021
0.14
0.11
32*
61*
0.004
0.033
DANBURY, CT
193,597
ND
ND
ND
0.15
0.11
ND
ND
0.004
0.024
DAVENPORT-MOLINE-ROCK ISLAND, IA-IL
350,861
ND
ND
ND
0.10
0.08
44
177
0.004
0.014
DAYTON-SPRINGFIELD, OH
951,270
3
0.01
ND
0.13
0.10
24
53
0.005
0.018
DAYTONA BEACH, FL
399,413
ND
ND
ND
0.09
0.08
21
56
ND
ND
DECATUR, AL
131,556
ND
ND
ND
0.10
0.09
IN
43
0.002
0.011
DECATUR, IL
117,206
ND
ND
ND
0.10
0.09
ND
ND
0.006
0.027
DENVER, CO
1,622,980
5
0.08
0.02
0.11
0.08
37
141
0.003
0.012
DES MOINES, IA
392,928
4
ND
ND
0.08
0.07
IN
76
ND
ND
DETROIT, Ml
4,266,654
4
0.10
0.018
0.12
0.10
36
126
0.009
0.053
DOTHAN, AL
130,964
ND
ND
ND
ND
ND
IN
IN
ND
ND
DOVER, DE
110,993
ND
ND
ND
0.12
0.10
ND
ND
ND
ND
DULUTH-SUPERIOR, MN-WI
239,971
2
ND
ND
0.08
0.07
25
71
ND
ND
DUTCHESS COUNTY, NY
259,462
ND
ND
ND
0.12
0.09
ND
ND
ND
ND
EL PASO, TX
591,610
8
0.15
0.028
0.11
0.07
63
129
0.003
0.016
ELKHART-GOSHEN, IN
156,198
ND
ND
ND
0.09
0.08
ND
ND
ND
ND
ELMIRA, NY
95,195
ND
ND
ND
0.09
0.08
ND
ND
0.003
0.015
ENID, OK
56,735
ND
ND
0.008
ND
ND
ND
ND
ND
ND
ERIE, PA
275,572
6
ND
0.015
0.11
0.10
ND
54*
0.010
0.043
EUGENE-SPRINGFIELD, OR
282,912
5
0.02
ND
0.08
0.07
ND
ND
ND
ND
EVANSVILLE-HENDERSON, IN-KY
278,990
4
ND
0.016
0.11
0.10
26
60
0.007
0.056
FARGO-MOORHEAD, ND-MN
153,296
ND
ND
0.007
0.07
0.07
21
65
0.001
0.003
FAYETTEVILLE, NC
274,566
5
ND
ND
0.12
0.10
24
42
0.005
0.007
FLAGSTAFF, AZ-UT
101,760
ND
ND
ND
0.09
0.08
ND
ND
ND
ND
FLINT, Ml
430,459
ND
0.01
ND
0.11
0.10
IN
IN
0.003
0.011
FLORENCE, AL
131,327
ND
ND
ND
ND
ND
ND
ND
0.003
0.017
FLORENCE, SC
114,344
ND
0.01
ND
ND
ND
ND
ND
ND
ND
FORT COLLINS-LOVELAND, CO
186,136
5
ND
ND
0.09
0.07
16
36
ND
ND
FORT LAUDERDALE, FL
1,255,488
5
0.02
0.011
0.10
0.08
19
33
0.003
0.015
FORT MYERS-CAPE CORAL, FL
335,113
ND
ND
ND
0.10
0.08
19
32
ND
ND
FORT PIERCE-PORT ST. LUCIE, FL
251,071
ND
ND
0.010
0.08
0.07
20
39
ND
ND
FORT WAYNE, IN
456,281
3
ND
ND
0.10
0.09
IN
IN
ND
ND
FORT WORTH-ARLINGTON, TX
1,361,034
3
ND
0.017
0.15
0.10
22*
44*
ND
ND
FRESNO, CA
755,580
8
0.00
0.024
0.15
0.11
47
130
ND
ND
GADSDEN, AL
99,840
ND
ND
ND
ND
ND
30
66
ND
ND
GAINESVILLE, FL
181,596
ND
ND
ND
0.10
0.08
21
38
ND
ND
GALVESTON-TEXAS CITY, TX
217,399
ND
ND
0.005
0.18
0.12
23*
43*
0.007
0.040
GARY, IN
604,526
3
0.08
0.019
0.12
0.10
35
166
0.007
0.032
GOLDSBORO, NC
104,666
ND
ND
ND
ND
ND
20
48
ND
ND
GRAND JUNCTION, CO
93,145
5
ND
ND
ND
ND
20
52
ND
ND
GRAND RAPIDS-MUSKEGON-HOLLAND, Ml
937,891
4
0.00
ND
0.12
0.10
21
54
0.001
0.006
GREAT FALLS, MT
77,691
4
ND
ND
ND
ND
ND
ND
0.003
0.011
GREELEY, CO
131,821
3
ND
ND
0.09
0.07
18
47
ND
ND
GREEN BAY, Wl
194,594
ND
ND
ND
0.10
0.09
ND
ND
0.003
0.011
GREENSBORO—WINSTON-SALEM—HIGH POINT
1,050,304
4
ND
0.016
0.13
0.10
25
57
0.005
0.020
GREENVILLE, NC
107,924
ND
ND
ND
0.11
0.09
IN
43
ND
ND
GREENVILLE-SPARTANBURG-ANDERSON, SC
830,563
5
0.01
0.017
0.12
0.10
26
52
0.003
0.009
HAGERSTOWN, MD
121,393
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
HAMILTON-MIDDLETOWN, OH
291,479
ND
0.01
ND
0.12
0.10
31
85
0.007
0.024
APPENDIX A • DATA TABLES
189
-------
NATIONALAIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-15. Maximum Air Quality Concentrations by Metropolitan Statistical Area, 1999 (continued)
CO
Pb
no2
°3
°3
PM10
PM10
S02
so2
Metropolitan Statistical Area
1990
8-hr
QMax
AM
1-hr
8-hr
Wtd AM
2nd Max
AM
24-hr
Population
(ppm)
(jjg/m3)
(PP"i)
(PP"i)
(PP"i)
(jjg/m3)
(jjg/m3)
(ppm)
(ppm)
HARRISBURG-LEBANON-CARLISLE, PA
587,986
4
ND
0.018
0.13
0.10
ND
ND
0.005
0.021
HARTFORD, CT
1,157,585
6
ND
0.018
0.16
0.11
18
81
0.004
0.019
HICKORY-MORGANTON-LENOIR, NC
292,409
ND
ND
ND
0.12
0.09
25
49
0.005
0.007
HONOLULU, HI
836,231
2
ND
0.004
0.05
0.05
15
41
0.001
0.004
HOUMA, LA
182,842
ND
ND
ND
0.12
0.09
ND
ND
ND
ND
HOUSTON, TX
3,322,025
4
0.02
0.024
0.20
0.12
45*
116*
0.005
0.019
HUNTINGTON-ASHLAND, WV-KY-OH
312,529
1
ND
0.016
0.12
0.10
39
89
0.009
0.026
HUNTSVILLE, AL
293,047
4
ND
ND
0.11
0.09
24
52
ND
ND
INDIANAPOLIS, IN
1,380,491
3
0.12f
0.018
0.11
0.10
27
53
0.007
0.024
JACKSON, MS
395,396
5
ND
ND
0.11
0.08
25
53
0.002
0.007
JACKSON, TN
90,801
ND
ND
ND
ND
ND
IN
43
ND
ND
JACKSONVILLE, FL
906,727
4
0.02
0.016
0.10
0.08
28
59
0.004
0.036
JACKSONVILLE, NC
149,838
ND
ND
ND
ND
ND
IN
45
ND
ND
JAMESTOWN, NY
141,895
ND
ND
ND
0.10
0.09
14
40
0.008
0.060
JANESVILLE-BELOIT, Wl
139,510
ND
ND
ND
0.11
0.09
ND
ND
ND
ND
JERSEY CITY, NJ
553,099
6
ND
0.026
0.14
0.11
35
56
0.008
0.030
JOHNSON CITY-KINGSPORT-BRISTOL, TN-VA
436,047
3
0.12
0.016
0.11
0.09
ND
ND
0.010
0.044
JOHNSTOWN, PA
241,247
3
0.09
0.015
0.11
0.09
ND
ND
0.009
0.025
JOPLIN, MO
134,910
ND
ND
ND
ND
ND
34
105
ND
ND
KALAMAZOO-BATTLE CREEK, Ml
429,453
ND
ND
ND
0.10
0.09
IN
50
ND
ND
KANSAS CITY, MO-KS
1,582,875
5
0.01
0.015
0.12
0.08
40
118
0.003
0.011
KENOSHA, Wl
128,181
ND
ND
ND
0.13
0.10
ND
ND
ND
ND
KNOXVILLE, TN
585,960
4
0.00
0.003
0.13
0.11
43
148
0.009
0.056
LAFAYETTE, LA
344,853
ND
ND
ND
0.09
0.08
ND
ND
ND
ND
LAKE CHARLES, LA
168,134
ND
ND
0.005
0.13
0.09
ND
ND
0.004
0.015
LAKELAND-WINTER HAVEN, FL
405,382
ND
ND
ND
0.10
0.08
22
50
0.007
0.019
LANCASTER, PA
422,822
2
ND
0.015
0.13
0.10
ND
ND
0.005
0.021
LANSING-EAST LANSING, Ml
432,674
ND
ND
ND
0.10
0.09
ND
ND
ND
ND
LAREDO, TX
133,239
4
0.02
ND
0.08
0.07
ND
ND
ND
ND
LAS CRUCES, NM
135,510
4
ND
0.012
0.10
0.08
45
88
0.001
0.008
LAS VEGAS, NV-AZ
852,737
8
ND
ND
0.10
0.08
56
281
ND
ND
LAWRENCE, MA-NH
353,232
ND
ND
ND
0.09
0.07
ND
ND
0.005
0.021
LAWTON, OK
111,486
2
ND
ND
0.09
0.08
ND
ND
ND
ND
LEWISTON-AUBURN, ME
93,679
ND
ND
ND
ND
ND
IN
45
0.004
0.016
LEXINGTON, KY
405,936
2
ND
0.013
0.11
0.09
23
54
0.008
0.020
LIMA, OH
154,340
ND
ND
ND
0.11
0.09
17
32
0.003
0.013
LINCOLN, NE
213,641
6
ND
ND
0.06
0.05
ND
ND
ND
ND
LITTLE ROCK-NORTH LITTLE ROCK, AR
513,117
4
ND
0.011
0.11
0.09
32*
70*
0.002
0.005
LONGVIEW-MARSHALL, TX
193,801
ND
ND
0.007
0.13
0.11
ND
ND
0.002
0.011
LOS ANGELES-LONG BEACH, CA
8,863,164
11
0.09
0.051
0.14
0.10
56
119
0.005
0.019
LOUISVILLE, KY-IN
948,829
5
ND
0.014
0.12
0.10
28
60
0.007
0.032
LOWELL, MA-NH
280,578
4
ND
ND
ND
ND
ND
ND
ND
ND
LUBBOCK, TX
222,636
ND
ND
ND
ND
ND
18*
42*
ND
ND
MACON, GA
290,909
ND
ND
ND
0.13
0.11
IN
53
ND
ND
MADISON, Wl
367,085
2
ND
ND
0.10
0.09
21
48
IN
IN
MANCHESTER, NH
50,000
ND
ND
IN
ND
ND
16
41
IN
IN
MANSFIELD, OH
174,007
ND
ND
ND
ND
ND
23
53
ND
ND
MCALLEN-EDINBURG-MISSION, TX
383,545
ND
ND
ND
0.09
0.08
ND
ND
ND
ND
MEDFORD-ASHLAND, OR
146,389
6
0.00
ND
0.08
IN
IN
93
ND
ND
MELBOURNE-TITUSVILLE-PALM BAY, FL
398,978
ND
ND
ND
0.09
0.08
19
52
ND
ND
MEMPHIS, TN-AR-MS
1,007,306
5
0.659
0.025
0.13
0.10
27
64
0.006
0.028
MERCED, CA
178,403
ND
ND
0.012
0.13
0.11
IN
IN
ND
ND
MIAMI, FL
1,937,094
4
ND
0.017
0.11
0.08
24
44
0.001
0.003
190 DATA TABLES • APPENDIX A
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-15. Maximum Air Quality Concentrations by Metropolitan Statistical Area, 1999 (continued)
CO
Pb
no2
°3
°3
PM10
PM10
S02
S02
Metropolitan Statistical Area
1990
8-hr
QMax
AM
1-hr
8-hr
Wtd AM
2nd Max
AM
24-hr
Population
(ppm)
(jjg/m3)
(PP"i)
(PP"i)
(PP"i)
(jjg/m3)
(jjg/m3)
(ppm)
(ppm)
MIDDLESEX-SOMERSET-HUNTERDON, NJ
1,019,835
3
0.18h
0.019
0.15
0.11
ND
ND
0.005
0.016
MILWAUKEE-WAUKESHA, Wl
1,432,149
2
ND
0.022
0.12
0.10
27
60
0.004
0.024
MINNEAPOLIS-ST. PAUL, MN-WI
2,538,834
5
0.47'
0.022
0.09
0.08
35
88
0.004
0.030
MOBILE, AL
476,923
ND
ND
ND
0.12
0.09
25
84
0.008
0.041
MODESTO, CA
370,522
6
0.00
0.022
0.11
0.09
43
137
ND
ND
MONMOUTH-OCEAN, NJ
986,327
3
ND
ND
0.14
0.11
ND
ND
ND
ND
MONROE, LA
142,191
ND
ND
ND
0.10
0.08
ND
ND
0.003
0.010
MONTGOMERY, AL
292,517
ND
ND
ND
0.11
0.09
24
48
ND
ND
MUNCIE, IN
119,659
ND
0.76'
ND
ND
ND
ND
ND
ND
ND
MYRTLE BEACH, SC
144,053
ND
0.01
ND
ND
ND
ND
ND
ND
ND
NAPLES, FL
152,099
ND
ND
ND
ND
ND
17
30
ND
ND
NASHUA, NH
168,233
5
ND
IN
0.10
0.09
17
40
0.005
0.016
NASHVILLE, TN
985,026
5
1.02k
0.019
0.12
0.10
32
74
0.005
0.035
NASSAU-SUFFOLK, NY
2,609,212
5
ND
0.024
0.13
0.11
16
41
0.007
0.038
NEW BEDFORD, MA
175,641
ND
ND
ND
0.13
0.10
ND
ND
ND
ND
NEW HAVEN-MERIDEN, CT
530,180
3
ND
0.026
0.15
0.11
20
76
0.007
0.027
NEW LONDON-NORWICH, CT-RI
290,734
ND
ND
ND
0.13
0.10
17
36
IN
IN
NEW ORLEANS, LA
1,285,270
3
0.08
0.022
0.12
0.09
27
60
0.005
0.023
NEW YORK, NY
8,546,846
5
0.10
0.041
0.15
0.11
IN
46
0.013
0.045
NEWARK, NJ
1,915,928
7
ND
0.042
0.12
0.10
33
67
0.007
0.023
NEWBURGH, NY-PA
335,613
ND
0.20'
ND
0.12
0.09
ND
ND
ND
ND
NORFOLK-VIRGINIA BEACH-NEWPORT NEWS.V
1,443,244
5
ND
0.017
0.14
0.10
19
50
0.007
0.022
OAKLAND, CA
2,082,914
5
0.00
0.022
0.14
0.09
26
94
0.003
0.020
OCALA, FL
194,833
ND
ND
ND
0.10
0.08
ND
ND
ND
ND
OKLAHOMA CITY, OK
958,839
4
ND
0.014
0.10
0.08
ND
ND
0.004
0.009
OLYMPIA, WA
161,238
5
ND
ND
0.08
0.06
IN
35
ND
ND
OMAHA, NE-IA
639,580
9
0.81m
ND
0.09
0.08
43
131
0.001
0.003
ORANGE COUNTY, CA
2,410,556
6
ND
0.035
0.11
0.08
37
73
0.002
0.005
ORLANDO, FL
1,224,852
3
ND
0.012
0.10
0.08
26
49
0.002
0.007
OWENSBORO, KY
87,189
1
ND
0.011
0.10
0.09
25
63
0.006
0.024
PANAMA CITY, FL
126,994
ND
ND
ND
ND
ND
IN
50
ND
ND
PARKERSBURG-MARIETTA, WV-OH
149,169
ND
ND
ND
0.12
0.10
28
72
0.013
0.058
PENSACOLA, FL
344,406
ND
ND
IN
0.11
0.09
23
56
0.004
0.029
PEORIA-PEKIN, IL
339,172
5
0.02
ND
0.10
0.08
23
52
0.007
0.036
PHILADELPHIA, PA-NJ
4,922,175
5
0.84"
0.032
0.15
0.11
22
59*
0.010
0.034
PHOENIX-MESA, AZ
2,238,480
8
ND
0.041
0.12
0.09
60
219
0.003
0.012
PITTSBURGH, PA
2,384,811
4
0.08
0.029
0.13
0.10
37
121
0.015
0.089
PITTSFIELD, MA
88,695
ND
ND
ND
0.09
0.08
ND
ND
ND
ND
POCATELLO, ID
66,026
ND
ND
IN
ND
ND
30
168
0.007
0.046
PONCE, PR
3,442,660
ND
ND
ND
ND
ND
39
86
ND
ND
PORTLAND, ME
221,095
ND
ND
ND
0.11
0.08
23
61
0.005
0.014
PORTLAND-VANCOUVER, OR-WA
1,515,452
7
0.18
IN
0.09
0.07
16
63
ND
ND
PORTSMOUTH-ROCHESTER, NH-ME
223,271
ND
ND
0.010
0.12
0.09
16
34
0.004
0.019
PROVIDENCE-FALL RIVER-WARWICK, RI-MA
1,134,350
4
ND
0.024
0.13
0.09
29
61
0.007
0.026
PROVO-OREM, UT
263,590
6
ND
0.024
0.11
0.08
32
91
ND
ND
PUEBLO, CO
123,051
ND
ND
ND
ND
ND
IN
51
ND
ND
RACINE, Wl
175,034
3
ND
ND
0.11
0.09
ND
ND
ND
ND
RALEIGH-DURHAM-CHAPEL HILL, NC
855,545
5
ND
ND
0.13
0.11
23
49
0.005
0.009
RAPID CITY, SD
81,343
ND
ND
ND
ND
ND
28
108
ND
ND
READING, PA
336,523
3
0.84°
0.021
0.13
0.10
ND
55*
0.008
0.027
REDDING, CA
147,036
ND
ND
ND
0.11
0.09
IN
42
ND
ND
RENO, NV
254,667
7
ND
IN
0.10
0.08
55
116
ND
ND
RICHLAND-KENNEWICK-PASCO, WA
150,033
ND
ND
ND
ND
ND
IN
86
ND
ND
APPENDIX A • DATA TABLES
191
-------
NATIONALAIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-15. Maximum Air Quality Concentrations by Metropolitan Statistical Area, 1999 (continued)
CO
Pb
no2
°3
°3
PM10
PM10
S02
so2
Metropolitan Statistical Area
1990
8-hr
QMax
AM
1-hr
8-hr
Wtd AM
2nd Max
AM
24-hr
Population
(ppm)
(jjg/m3)
(PP"i)
(PP"i)
(PP"i)
(jjg/m3)
(jjg/m3)
(ppm)
(ppm)
RICHMOND-PETERSBURG, VA
865,640
2
ND
0.02
0.13
0.10
19
36
0.005
0.017
RIVERSIDE-SAN BERNARDINO, CA
2,588,793
4
0.05
0.039
0.16
0.13
72
134
0.002
0.009
ROANOKE, VA
224,477
4
ND
0.012
0.11
0.09
IN
64
0.003
0.010
ROCHESTER, MN
106,470
ND
ND
ND
ND
ND
IN
IN
ND
ND
ROCHESTER, NY
1,062,470
3
ND
ND
0.10
0.09
ND
ND
0.007
0.041
ROCKFORD, IL
329,676
4
ND
ND
0.09
0.08
ND
ND
ND
ND
ROCKY MOUNT, NC
133,235
ND
ND
ND
0.10
0.09
IN
IN
0.005
0.007
SACRAMENTO, CA
1,340,010
6
0.00
0.021
0.14
0.11
33
143
0.004
0.012
ST. CLOUD, MN
190,921
3
ND
ND
ND
ND
IN
IN
ND
ND
ST. JOSEPH, MO
83,083
ND
ND
ND
ND
ND
IN
99
0.003
0.013
ST. LOUIS, MO-IL
1,836,302
4
6.75P
0.027
0.13
0.10
44
117
0.009
0.059
SALEM, OR
278,024
6
ND
ND
0.08
0.07
ND
ND
ND
ND
SALINAS, CA
355,660
2
ND
0.010
0.08
0.06
29
76
ND
ND
SALT LAKE CITY-OGDEN, UT
1,072,227
6
0.08
0.028
0.11
0.08
45
113
0.004
0.010
SAN ANTONIO, TX
1,324,749
4
ND
0.025
0.11
0.09
ND
46*
ND
ND
SAN DIEGO, CA
2,498,016
5
0.00
0.026
0.11
0.09
52
112
0.003
0.016
SAN FRANCISCO, CA
1,603,678
5
0.00
0.021
0.10
0.06
26
69
0.002
0.006
SAN JOSE, CA
1,497,577
6
0.00
0.026
0.12
0.08
29
94
ND
ND
SAN JUAN-BAYAMON, PR
1,836,302
8
0.02
IN
0.08
0.05
38
84
0.003
0.015
SAN LUIS OBISPO-ATASCADERO-PASO ROBLE
217,162
3
ND
0.013
0.09
0.08
27
82
0.005
0.027
SANTA BARBARA-SANTA MARIA-LOMPOC, CA
369,608
4
0.00
0.022
0.10
0.08
29
54
0.002
0.003
SANTACRUZ-WATSONVILLE, CA
229,734
1
ND
0.005
0.08
0.07
31
75
0.001
0.002
SANTA FE, NM
117,043
2
ND
ND
ND
ND
13
31
ND
ND
SANTA ROSA, CA
388,222
3
ND
0.014
0.10
0.08
18
64
ND
ND
SARASOTA-BRADENTON, FL
489,483
3
ND
0.007
0.11
0.09
24
42
0.004
0.017
SAVANNAH, GA
258,060
ND
ND
ND
0.11
0.08
27
59
0.003
0.018
SCRANTON—WILKES-BARRE—HAZLETON, PA
638,466
3
ND
0.015
0.12
0.10
ND
ND
0.007
0.023
SEATTLE-BELLEVUE-EVERETT, WA
2,033,156
6
0.05q
0.019
0.09
0.07
16
50
IN
IN
SHARON, PA
121,003
ND
ND
ND
0.11
0.09
ND
ND
0.007
0.039
SHEBOYGAN, Wl
103,877
ND
ND
ND
0.13
0.09
ND
ND
ND
ND
SHREVEPORT-BOSSIER CITY, LA
376,330
ND
ND
ND
0.11
0.09
IN
41
0.002
0.006
SIOUX CITY, IA-NE
115,018
ND
ND
ND
ND
ND
28
73
ND
ND
SIOUX FALLS, SD
139,236
ND
ND
ND
0.07
IN
22
44
ND
ND
SOUTH BEND, IN
247,052
ND
ND
IN
0.11
0.09
IN
49
ND
ND
SPOKANE, WA
361,364
6
ND
ND
0.07
0.07
26
86
ND
ND
SPRINGFIELD, IL
189,550
2
ND
ND
0.10
0.08
20
45
0.006
0.059
SPRINGFIELD, MO
264,346
3
ND
0.013
0.10
0.08
18
34
0.004
0.039
SPRINGFIELD, MA
587,884
6
ND
0.022
0.11
0.09
30
66
0.005
0.024
STAMFORD-NORWALK, CT
329,935
4
ND
ND
0.14
0.11
29
49
0.006
0.026
STATE COLLEGE, PA
123,786
ND
ND
ND
0.10
0.09
ND
ND
ND
ND
STEUBENVILLE-WEIRTON, OH-WV
142,523
5
ND
ND
0.11
0.09
34
98
0.016
0.065
STOCKTON-LODI, CA
480,628
6
0.00
0.024
0.13
0.09
36
123
ND
ND
SYRACUSE, NY
742,177
3
ND
ND
0.10
0.09
ND
ND
0.002
0.015
TACOMA, WA
586,203
7
ND
ND
0.09
0.07
17
56
IN
IN
TALLAHASSEE, FL
233,598
ND
ND
ND
0.09
0.08
19
55
ND
ND
TAMPA-ST. PETERSBURG-CLEARWATER, FL
2,067,959
5
1.02r
0.016
0.12
0.09
35
81
0.008
0.060
TERRE HAUTE, IN
147,585
ND
ND
ND
0.09
0.08
IN
IN
0.006
0.025
TEXARKANA, TX-TEXARKANA, AR
120,132
ND
ND
ND
ND
ND
ND
ND
IN
IN
TOLEDO, OH
614,128
3
0.26
ND
0.13
0.09
23
58
0.004
0.018
TOPEKA, KS
160,976
ND
ND
ND
ND
ND
25
74
ND
ND
TRENTON, NJ
325,824
ND
ND
0.017
0.15
0.11
21
48
ND
ND
TUSCON, AZ
666,880
4
ND
0.019
0.09
0.07
48
207
0.002
0.005
192 DATA TABLES • APPENDIX A
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-15. Maximum Air Quality Concentrations by Metropolitan Statistical Area, 1999 (continued)
CO
Pb
no2
o,
o,
PM10
PM10
SO,
S02
Metropolitan Statistical Area
1990
8-hr
QMax
AM
1-hr
8-hr
Wtd AM
2nd Max
AM
24-hr
Population
(PP"i)
(jjg/m3)
(PP"i)
(PP"i)
(ppm)
(jjg/m3)
(jjg/m3)
(ppm)
(ppm)
TULSA, OK
708,954
4
ND
0.017
0.12
0.09
CM
CM
LO
CD
0.011
0.083
TUSCALOOSA, AL
150,522
ND
ND
ND
ND
ND
28
61
ND
ND
TYLER, TX
151,309
ND
ND
0.007
0.12
0.10
ND
ND
ND
ND
UTICA-ROME, NY
316,633
ND
ND
ND
0.09
0.08
IN
46
0.001
0.007
VALLEJO-FAIRFIELD-NAPA, CA
451,186
5
ND
0.014
0.12
0.09
20
62
0.002
0.006
VENTURA, CA
669,016
3
0.00
0.022
0.13
0.10
31
63
0.002
0.005
VICTORIA, TX
74,361
ND
ND
ND
0.10
0.09
ND
ND
ND
ND
VINELAND-MILLVILLE-BRIDGETON, NJ
138,053
ND
ND
ND
0.12
0.10
ND
ND
0.003
0.012
VISALIA-TULARE-PORTERVILLE, CA
311,921
4
ND
0.021
0.13
0.11
55
137
ND
ND
WASHINGTON, DC-MD-VA-WV
4,223,485
6
0.03
0.025
0.13
0.11
24
57
0.009
0.026
WATERBURY, CT
221,629
ND
0.01
ND
ND
ND
20
47
0.005
0.020
WATERLOO-CEDAR FALLS, IA
123,798
ND
ND
ND
ND
ND
IN
IN
ND
ND
WAUSAU, Wl
115,400
ND
ND
ND
0.10
0.08
IN
64
0.003
0.040
WEST PALM BEACH-BOCA RATON, FL
863,518
3
0.00
0.013
0.10
0.08
20
33
0.002
0.013
WHEELING, WV-OH
159,301
3
ND
ND
0.10
0.09
26
69
0.015
0.060
WICHITA, KS
485,270
5
ND
ND
0.10
0.08
31
86
ND
ND
WILLIAMSPORT, PA
118,710
ND
ND
ND
0.09
0.08
ND
ND
0.005
0.021
WILMINGTON-NEWARK, DE-MD
513,293
3
ND
0.018
0.15
0.11
^r
CM
CD
0.008
0.049
WILMINGTON, NC
171,269
4
ND
ND
0.08
0.07
IN
45
0.007
0.027
WORCESTER, MA-CT
478,384
3
ND
0.020
0.11
0.09
IN
65
0.004
0.013
YAKIMA, WA
188,823
5
ND
ND
ND
ND
25
82
ND
ND
YOLO, CA
141,092
1
ND
0.012
0.12
0.09
33
144
ND
ND
YORK, PA
339,574
2
ND
0.019
0.12
0.09
ND
ND
0.007
0.019
YOUNGSTOWN-WARREN, OH
600,859
ND
ND
ND
0.11
0.10
26
135
0.008
0.029
YUBA CITY, CA
122,643
4
ND
0.014
0.11
0.08
38
156
ND
ND
YUMA, AZ
106,895
ND
ND
ND
0.09
0.08
ND
ND
ND
ND
CO - Highest second maximum non-overlapping 8-hour concentration (Applicable NAAQS is 9 ppm)
Pb - Highest quarterly maximum concentration (Applicable NAAQS is 1.5/jg/m3)
N02 - Highest arithmetic mean concentration (Applicable NAAQS is 0.053 ppm)
03 (1-hr) - Highest second daily maximum 1-hour concentration (Applicable NAAQS is 0.12 ppm)
03 (8-hr) - Highest fourth daily maximum 8-hour concentration (Applicable NAAQS is 0.08 ppm)
PM10 - Highest weighted annual mean concentration (Applicable NAAQS is 50/jg/m3)
- Highest second maximum 24-hour concentration (Applicable NAAQS is 150 /jg/m3)
S02 - Highest annual mean concentration (Applicable NAAQS is 0.03 ppm)
- Highest second maximum 24-hour concentration (Applicable NAAQS is 0.14 ppm)
ND - Indicates data not available
IN - Indicates insufficient data to calculate summary statistic
Wtd - Weighted
AM - Annual mean
|jg/m3 - Units are micrograms per cubic meter
PPM - Units are parts per million
APPENDIX A • DATA TABLES
193
-------
NATIONALAIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
TableA-16. Metropolitan Statistical Area Air Quality Trends, 1990-1999
Metropolitan Statistical Area
Trend
#Trend
Sites
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
AKRON, OH
CO 2nd max 8-hour
03 4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
S02 arithmetic mean
2nd max 24-hour
ALBANY-SCHENECTADY-TROY, NY
CO 2nd max 8-hour
Pb max quarterly mean
03 4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
S02 arithmetic mean
2nd max 24-hour
ALBUQUERQUE, NM
CO 2nd max 8-hour
N02 arithmetic mean
03 4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
ALEXANDRIA, LA
PM10 90th percentile
weighted annual mean
ALLENTOWN-BETHLEHEM-EASTON, PA
CO 2nd max 8-hour
Pb max quarterly mean
N02 arithmetic mean
03 4th max 8-hour
2nd daily max 1-hour
S02 arithmetic mean
2nd max 24-hour
ALTOONA, PA
CO
no2
o3
2nd max 8-hour
arithmetic mean
4th max 8-hour
2nd daily max 1-hour
S02 arithmetic mean
2nd max 24-hour
ANCHORAGE, AK
PM„
ANNISTON, AL
PMin
ASHEVILLE,
o3
PM„
90th percentile
weighted annual mean
90th percentile
weighted annual mean
NC
ATLANTA, GA
CO
no2
o3
4th max 8-hour
2nd daily max 1-hour
90th percentile
weighted annual mean
2nd max 8-hour
arithmetic mean
4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
S02 arithmetic mean
2nd max 24-hour
ATLANTIC-CAPE MAY, NJ
03 4th max 8-hour
2nd daily max 1-hour
S02 arithmetic mean
2nd max 24-hour
AUGUSTA-AIKEN, GA-SC
Pb
o3
PM„
SO,
max quarterly mean
4th max 8-hour
2nd daily max 1-hour
90th percentile
weighted annual mean
arithmetic mean
2nd max 24-hour
Down
NS
NS
Down
Down
Down
NS
Down
Down
NS
NS
NS
NS
Down
Down
Down
NS
NS
NS
Down
Down
Down
NS
Down
Down
NS
NS
NS
NS
NS
NS
Down
NS
up
Down
Down
Down
Down
NS
NS
up
up
NS
Down
Down
NS
NS
NS
NS
Down
Down
Down
NS
NS
Down
NS
Down
NS
NS
NS
NS
NS
Down
5.7
0.09
0.111
49
25.9
0.015
0.061
6.2
0.133
0.084
0.105
36.4
20.98
0.006
3.3
0.101
0.12
51
28.4
0.015
0.051
5.4
0.037
0.084
0.099
35.6
21.3
0.007
4.1
0.087
0.108
44
27.1
0.013
0.064
4.7
0.033
0.086
0.098
33.6
21.46
0.006
3.1
0.093
0.108
49
25
0.015
0.056
3.8
0.033
0.081
0.099
34.2
19.74
0.006
5.3
0.086
0.1
51
27.6
0.012
0.042
5.2
0.043
0.077
0.1
40
21.4
0.006
3.3
0.092
0.117
48
26.1
0.009
0.046
4.3
0.041
0.079
0.101
31.8
18.22
0.005
3.4
0.091
0.105
35
24.7
0.01
0.042
3.7
0.032
0.074
0.094
28.8
19.08
0.005
3.2
0.087
0.103
39
23.8
0.012
0.072
4.5
0.031
0.079
0.097
32
19.52
0.004
2.6
0.097
0.112
39
23.8
0.01
0.044
4.4
0.032
0.075
0.096
36
19.64
0.003
2.5
0.097
0.115
39
23.8
0.011
0.065
4.2
0.032
0.085
0.106
36
19.64
0.003
0.028 0.03 0.022 0.026 0.027 0.016 0.021 0.017 0.013 0.013
5.967
0.018
0.069
0.088
5.433 5.017 5.117
0.004 0.021 0.024
0.065 0.066 0.063
0.084 0.086 0.081
38.875 37.125 33.75 35.5
4.933 4.983
0.023 0.018
0.067 0.065
0.083 0.083
35.5 39.375
4.333 3.7 3.667 4.067
0.022 0.019 0.016 0.016
0.068 0.066 0.07 0.071
0.084 0.082 0.086 0.09
37.5 32.625 32 31.75
23.95 22.488 22.788 23.45 22.25 23.75 23.925 20.788 20.575 20.538
38
22.8
5.8
0.4
0.017
0.093
0.11
0.008
0.037
1.7
0.015
0.081
0.097
0.011
0.062
37
21.9
6.5
0.461
0.018
0.101
0.119
0.008
0.037
1.7
0.015
0.092
0.106
0.011
0.044
40
24.7
3.9
0.283
0.018
0.081
0.096
0.007
0.032
2.8
0.014
0.079
0.095
0.009
0.046
36
21.3
3.5
0.181
0.02
0.084
0.107
0.006
0.029
2
0.015
0.086
0.1
0.009
0.052
38 37 27 32 32 32
23.2 21.4 18.6 23.2 23.2 23.2
4.7
0.131
0.021
0.082
0.105
0.008
0.047
2.4
0.015
0.092
0.106
0.01
0.058
4.8
0.074
0.018
0.094
0.109
0.006
0.027
1.7
0.013
0.091
0.112
0.008
0.037
3.2 2.7 2.9 3.2
0.083 0.093 0.12 0.071
0.018 0.016 0.016 0.015
0.089 0.097 0.092 0.102
0.107 0.116 0.109 0.12
0.006 0.009 0.009 0.007
0.028 0.029 0.032 0.034
1.9
0.013
0.083
0.101
0.008
0.033
1.5
0.014
0.096
0.114
0.01
0.046
1.2
0.013
0.098
0.114
0.008
0.032
1.6
0.013
0.091
0.111
0.007
0.03
63.333 57.333 61.333 55.333 50.333 50.667
30.933 29.633 31.267 27.567 26.6 26.033
48 51.333 37.333 32.667
24.8 24.5 20.067 21.2
46 46 37 38
28 29.2 24.6 25
0.073 0.063 0.064 0.066
0.091 0.079 0.083 0.079
41 41 40 43
25.1 24 22.8 22.3
5.4 6.5 5.1 4.9
0.021 0.02 0.02 0.02
0.107 0.093 0.091 0.112
0.137 0.124 0.127 0.148
68.333 53.333 45.667 47
38.9 32.067 28.067 28.567
0.006 0.006 0.006 0.006
0.025 0.029 0.026 0.032
0.109 0.111 0.094 0.093
0.157 0.136 0.119 0.115
0.004 0.004 0.003 0.003
0.012 0.011 0.016 0.014
40 40
23.7 22.8
27
18.7
42
23.1
41
26
41
26
0.069
0.084
30
19
5.3
0.018
0.093
0.12
0.076
0.085
28
18.4
4.5
0.017
0.112
0.143
43.333 45.333
26.867 28.267
0.004 0.004
0.022 0.018
0.083
0.099
0.003
0.019
0.1
0.116
0.003
0.011
0.074 0.075 0.09 0.084
0.084 0.09 0.114 0.099
29 38 36 36
18.8 20.7 20.1 20.5
3.7 4.3 4.1 4.1
0.021 0.02 0.021 0.022
0.103 0.102 0.117 0.12
0.129 0.132 0.144 0.152
41 48.667 49.667 46
26.8 27.967 28.067 26.833
0.004 0.004 0.003 0.003
0.019 0.021 0.016 0.017
0.095 0.106 0.091 0.095
0.108 0.131 0.118 0.118
0.003 0.003 0.003 0.003
0.014 0.011 0.01 0.009
0.017 0.013 0.011 0.01 0.009 0.007
0.085
0.103
36
22.2
0.002
0.072
0.095
35
22.7
0.002
0.074
0.09
32
21.9
0.002
0.084
0.101
35
22.1
0.002
0.08
0.093
35
21.3
0.002
0.079
0.1
29
18.7
0.002
0.009 0.01 0.009 0.009 0.008 0.009
0.004
0.083
0.099
29
18.7
0.002
0.007
0.008
0.084
0.105
31
21.4
0.002
0.008
0.019
0.096
0.116
38
22.4
0.002
0.007
0.002
0.087
0.106
35
21.1
0.002
0.007
194
DATA TABLES • APPENDIX A
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-16. Metropolitan Statistical Area Air Quality Trends, 1990-1999 (continued)
Metropolitan Statistical Area Trend #Trend 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
Sites
AUSTIN-SAN MARCOS, TX
03 4th max 8-hour
2nd daily max 1-hour
BAKERSFIELD, CA
NO,
o3
PM„
BALTIMORE.
CO
Pb
no2
o3
PM10
so2
BANGOR, ME
PMin
arithmetic mean
4th max 8-hour
2nd daily max 1-hour
90th percentile
weighted annual mean
MD
2nd max 8-hour
max quarterly mean
arithmetic mean
4th max 8-hour
2nd daily max 1-hour
90th percentile
weighted annual mean
arithmetic mean
2nd max 24-hour
90th percentile
weighted annual mean
BATON ROUGE, LA
Pb max quarterly mean
N02 arithmetic mean
03 4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
S02 arithmetic mean
2nd max 24-hour
BEAUMONT-PORT ARTHUR, TX
N02 arithmetic mean
03 4th max 8-hour
2nd daily max 1-hour
S02 arithmetic mean
2nd max 24-hour
BELLINGHAM, WA
03 4th max 8-hour
2nd daily max 1-hour
S02 arithmetic mean
2nd max 24-hour
BERGEN-PASSAIC, NJ
CO
no2
o3
PM10
so2
BILLINGS, MT
so2
2nd max 8-hour
arithmetic mean
4th max 8-hour
2nd daily max 1-hour
90th percentile
weighted annual mean
arithmetic mean
2nd max 24-hour
arithmetic mean
2nd max 24-hour
BILOXI-GULFPORT-PASCAGOULA, MS
03 4th max 8-hour
2nd daily max 1-hour
S02 arithmetic mean
2nd max 24-hour
BIRMINGHAM, AL
CO
o3
PM„
so2
BOISE CITY, ID
PMin
2nd max 8-hour
4th max 8-hour
2nd daily max 1-hour
90th percentile
weighted annual mean
arithmetic mean
2nd max 24-hour
90th percentile
weighted annual mean
NS
NS
Down
NS
NS
Down
Down
Down
Down
Down
NS
NS
Down
Down
Down
Down
NS
Down
NS
NS
NS
NS
NS
NS
NS
NS
NS
NS
NS
Down
Down
NS
Down
NS
Down
Down
Down
NS
NS
Down
Down
Down
Down
Down
Down
NS
NS
Down
NS
Down
NS
NS
Down
Down
NS
NS
Down
Down
0.088 0.083 0.081
0.11 0.1 0.099
0.017
0.103
0.13
89.25
47.15
7.1
0.058
0.034
0.098
0.126
51.8
32.72
0.008
0.03
33
20.5
0.051
0.01
0.107
0.154
42.5
28.15
0.005
0.022
0.009
0.087
0.12
0.009
0.042
0.061
0.082
0.007
0.028
6.8
0.031
0.096
0.129
59
36.933
0.01
0.041
0.017
0.105
0.13
90.5
53.775
6.367
0.036
0.033
0.108
0.136
57.6
35.64
0.009
0.03
41
25.1
0.03
0.01
0.093
0.132
48.5
27.6
0.009
0.036
0.08
0.091
0.015
0.105
0.128
60
0.016
0.099
0.122
61.75
38.4 33.188 30.1 32.825
0.085
0.102
0.015
0.104
0.13
47.25
0.089
0.105
0.013
0.109
0.13
62
0.08 0.075 0.088 0.087
0.098 0.089 0.115 0.102
5.5
0.043
0.031
0.092
0.117
47
30.26
0.009
0.027
32
21.9
0.104
0.01
0.084
0.107
37
26.7
0.008
0.033
5.433
0.035
0.033
0.106
0.132
50.6
29.44
0.008
0.026
34
22.2
0.027
0.01
0.08
0.111
34.5
22.2
0.006
0.021
5.833
0.032
0.032
0.096
0.128
53.4
30.46
0.009
0.03
35
21.9
0.038
0.011
0.082
0.115
40.5
26.3
0.008
0.025
4.667
0.029
0.026
0.104
0.137
47.8
28.78
0.006
0.022
32
20
0.049
0.01
0.093
0.123
37.5
24.35
0.006
0.034
0.01 0.011 0.009
0.097 0.094 0.088
0.13 0.13 0.115
0.008 0.006 0.006
0.059 0.044 0.047
0.058 0.056 0.058
0.073 0.069 0.08
0.006 0.007 0.006
0.021 0.022 0.017
6.6 4.45 5.15
0.031 0.03 0.029
0.1 0.075 0.082
0.137 0.104 0.111
61.667 50.333 51
39.333 32.967 31.167
0.01 0.009 0.008
0.035 0.04 0.026
0.01 0.01
0.08 0.098
0.113 0.134
0.006 0.005
0.039 0.025
0.059 0.054
0.082 0.079
0.007 0.006
0.019 0.018
6.15 4.9
0.031 0.029
0.088 0.104
0.114 0.122
57.333 49.333
35.167 30.633
0.007 0.005
0.037 0.027
0.013
0.113
0.138
47
28.425
3.633
0.027
0.027
0.091
0.119
43.4
27.1
0.007
0.026
27
18.8
0.032
0.01
0.088
0.114
34.5
24.45
0.006
0.024
0.01
0.013
0.096
0.118
45
0.013 0.014
0.114 0.105
0.134 0.122
45.5 55.5
27.9 25.175 29.925
4.6
0.005
0.026
0.105
0.137
46.4
28.12
0.008
0.025
33
21.1
4.133
0.005
0.026
0.098
0.123
47.8
28.56
0.007
0.021
34
17.5
4.567
0.005
0.024
0.106
0.138
45
28.02
0.007
0.02
24
16.7
0.043
0.01
0.093
0.115
47
30.7
0.006
0.019
0.01 0.008 0.01
0.082 0.092 0.085 0.072
0.117 0.137 0.117 0.099
0.005 0.006 0.005 0.005
0.041 0.037 0.033 0.032
0.062 0.052 0.056 0.05
0.078 0.07 0.07 0.062
0.005 0.005 0.005 0.007
0.013 0.012 0.015 0.016
0.041 0.045
0.01 0.01
0.086 0.091
0.119 0.127
43.5 45.25
27.35 29.025
0.006 0.007
0.027 0.036
3.75
0.028
0.083
0.106
4.85
0.028
0.096
0.12
47.667 48.833
30.533 31.183
0.006 0.005
0.022 0.021
3.7
0.028
0.096
0.12
46
28.5
0.005
0.021
0.079
0.115
0.007
0.037
6.8
0.093
0.119
58.2
34.64
0.008
0.079 0.087 0.076
0.115 0.108 0.098
0.006 0.006 0.004
0.034 0.02 0.029
0.075
0.1
55.2
31.88
0.007
7.45
0.083
0.108
45.2
28.78
0.007
7.3
0.082
0.11
43.2
27.34
0.009
0.093 0.087
0.117 0.111
0.003 0.003
0.022 0.024
6.7 6.55
0.077
0.097
38.8
25.24
0.007
0.096
0.125
41.8
26.48
0.006
5.3
0.093
0.128
38.8
24.62
0.004
0.083
0.11
47.2
26.1
0.006
4.1
0.028
0.096
0.12
44
26.9
0.005
0.022
0.016 0.016 0.02 0.021 0.015 0.013 0.009 0.007 0.006 0.005
0.066 0.069 0.081 0.104 0.066 0.059 0.056 0.032 0.025 0.022
0.076 0.078 0.089 0.091
0.104 0.092 0.108 0.107
0.003 0.002 0.003 0.003
0.043 0.025 0.022 0.024
4.4 4.55
0.097
0.121
40.4
27.34
0.007
0.09
0.121
36.8
24.82
0.007
0.025 0.02 0.027 0.05 0.037 0.016 0.015 0.018 0.032 0.026
53.5 68 55.75 62 59.5 50 48.5 44.75 39.75 48.25
29.275 33.675 33.2 35.45 34.025 29.65 28.175 28.025 22.65 26.05
APPENDIX A • DATA TABLES
195
-------
NATIONALAIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-16. Metropolitan Statistical Area Air Quality Trends, 1990-1999 (continued)
Metropolitan Statistical Area
Trend
#Trend
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
Sites
BOSTON, MA-NH
CO
2nd max 8-hour
Down
4
5.6
4.05
4.725
3.95
4.85
3.55
3.6
3.775
2.875
3.425
no2
arithmetic mean
Down
3
0.029
0.031
0.029
0.03
0.03
0.027
0.028
0.026
0.027
0.026
o3
4th max 8-hour
NS
4
0.08
0.093
0.088
0.085
0.084
0.086
0.073
0.082
0.085
0.083
2nd daily max 1-hour
NS
4
0.101
0.126
0.109
0.113
0.109
0.108
0.092
0.102
0.101
0.102
PM10
90th percentile
NS
8
41.375
40
36.125
36
39.25
35.125
40.25
34.75
41.875
38.375
weighted annual mean
NS
8
25.913
24.775
22.775
22.325
23.05
21.938
23.625
22.013
24.413
24.2
so2
arithmetic mean
Down
10
0.009
0.009
0.009
0.009
0.008
0.006
0.006
0.006
0.006
0.006
2nd max 24-hour
Down
10
0.038
0.03
0.037
0.031
0.032
0.024
0.025
0.03
0.023
0.025
BOULDER-LONGMONT, CO
CO
2nd max 8-hour
Down
2
5.7
5.7
5.85
5.25
4.45
4.2
4
4.35
3.4
2.9
o3
4th max 8-hour
NS
1
0.074
0.077
0.07
0.073
0.071
0.072
0.072
0.071
0.08
0.08
2nd daily max 1-hour
NS
1
0.096
0.102
0.092
0.096
0.091
0.095
0.092
0.092
0.1
0.1
PM10
90th percentile
Down
2
39
43.5
34.5
43.5
28.5
27
27
24
26
26.5
weighted annual mean
Down
2
22.9
23.2
22.6
24.25
18.95
16.2
17.2
16.6
16.9
18.15
BRAZORIA, TX
o3
4th max 8-hour
NS
1
0.1
0.091
0.097
0.092
0.085
0.113
0.079
0.085
0.09
0.112
2nd daily max 1-hour
NS
1
0.15
0.13
0.129
0.132
0.112
0.148
0.11
0.137
0.111
0.161
BREMERTON, WA
PM10
90th percentile
Down
1
41
41
41
47
36
33
24
27
21
23
weighted annual mean
Down
1
22.6
22.6
22.6
23.4
19.7
20.6
16.9
17.3
12.9
15
BRIDGEPORT, CT
CO
2nd max 8-hour
Down
1
5
5.5
4.7
3.7
5.8
4.9
3
4
2.8
3.2
NO,
arithmetic mean
Down
1
0.026
0.025
0.024
0.024
0.026
0.024
0.024
0.023
0.023
0.023
o3
4th max 8-hour
NS
2
0.098
0.108
0.084
0.098
0.088
0.101
0.088
0.096
0.093
0.093
2nd daily max 1-hour
NS
2
0.145
0.147
0.119
0.157
0.152
0.131
0.114
0.132
0.132
0.135
PM10
90th percentile
Down
1
41
49
37
43
44
37
32
34
33
30
weighted annual mean
Down
1
25.2
27.7
22.4
20.8
25.7
21.8
20.6
21.4
20.8
19.4
so2
arithmetic mean
Down
1
0.013
0.012
0.011
0.01
0.01
0.007
0.006
0.007
0.007
0.006
2nd max 24-hour
Down
1
0.05
0.044
0.04
0.035
0.049
0.028
0.023
0.031
0.024
0.023
BROWNSVILLE-HARLINGEN-SAN BENITO, TX
PM10
90th percentile
NS
1
36
36
36
45
36
35
28
36
36
36
weighted annual mean
Down
1
21.7
23.9
23.7
22.4
22.5
21.4
18.9
20.6
20.6
20.6
BUFFALO-NIAGARA FALLS, NY
CO
2nd max 8-hour
Down
3
3.367
3.1
4.633
3.433
3.2
2.567
2.933
2.167
2.167
1.833
Pb
max quarterly mean
NS
1
0.029
0.031
0.034
0.047
0.046
0.033
0.034
0.042
0.036
0.036
no2
arithmetic mean
NS
2
0.02
0.018
0.018
0.017
0.019
0.019
0.019
0.018
0.017
0.019
o3
4th max 8-hour
NS
2
0.089
0.094
0.08
0.077
0.082
0.088
0.077
0.077
0.092
0.089
2nd daily max 1-hour
NS
2
0.106
0.106
0.109
0.089
0.092
0.103
0.095
0.091
0.106
0.101
PM10
90th percentile
NS
11
35.364
49
33.364
34.545
34
34.364
29
33.909
38.364
38.364
weighted annual mean
NS
11
19.391
24.845
21.236
19.145
18.664
18.364
19.127
18.7
19.845
19.845
so2
arithmetic mean
Down
4
0.011
0.012
0.011
0.01
0.01
0.008
0.007
0.007
0.007
0.007
2nd max 24-hour
Down
4
0.054
0.062
0.058
0.042
0.039
0.04
0.035
0.041
0.029
0.03
BURLINGTON, VT
CO
2nd max 8-hour
Down
1
4.6
3.8
3.9
3.9
3.9
2.5
3.3
2
2.4
1.5
no2
arithmetic mean
NS
1
0.018
0.017
0.016
0.017
0.017
0.017
0.017
0.017
0.018
0.017
PM10
90th percentile
Down
2
37.5
36.5
38.5
36
34.5
34.5
29
29.5
29.5
29.5
weighted annual mean
Down
2
24.25
23.2
22.7
20.5
21.1
20.1
20.3
20.05
20.6
20.6
so2
arithmetic mean
Down
1
0.008
0.008
0.003
0.003
0.003
0.002
0.002
0.002
0.002
0.002
2nd max 24-hour
Down
1
0.021
0.022
0.013
0.011
0.013
0.006
0.014
0.012
0.008
0.008
CANTON-MASSILLON, OH
o3
4th max 8-hour
NS
4
0.086
0.089
0.081
0.091
0.084
0.091
0.086
0.083
0.096
0.09
2nd daily max 1-hour
NS
4
0.103
0.106
0.094
0.105
0.097
0.11
0.096
0.097
0.113
0.104
PM10
90th percentile
Down
2
52
50
45
45
50
51.5
35.5
44
43
36
weighted annual mean
Down
2
29.55
31.2
27.65
26.25
28.45
28.75
25
25.6
25.05
23.45
so2
arithmetic mean
Down
1
0.011
0.01
0.01
0.01
0.009
0.006
0.006
0.007
0.007
0.007
2nd max 24-hour
Down
1
0.036
0.037
0.04
0.046
0.052
0.033
0.032
0.025
0.029
0.028
CASPER, WY
PM10
90th percentile
Down
1
38
38
38
27
34
32
33
29
31
29
weighted annual mean
NS
1
21.3
21.3
21.3
17.7
17.3
19.4
19.1
15.7
17.2
19.7
CEDAR RAPIDS, IA
CO
2nd max 8-hour
NS
1
3.5
4.1
4.9
3.2
4.2
2.6
7.8
2.4
2.5
2
o3
4th max 8-hour
NS
1
0.054
0.065
0.071
0.058
0.063
0.065
0.061
0.06
0.059
0.059
2nd daily max 1-hour
NS
1
0.065
0.081
0.081
0.067
0.07
0.075
0.073
0.071
0.068
0.068
PM10
90th percentile
NS
2
41.5
43.5
43.5
34
34
39
36
40.5
39.5
30.5
weighted annual mean
NS
2
27.3
28.45
26.1
21.55
22.8
23.55
23.55
24.25
25.35
22.2
so2
arithmetic mean
NS
2
0.004
0.004
0.005
0.003
0.003
0.003
0.002
0.003
0.003
0.003
2nd max 24-hour
Down
2
0.031
0.025
0.024
0.017
0.016
0.013
0.011
0.012
0.01
0.016
196 DATA TABLES • APPENDIX A
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-16. Metropolitan Statistical Area Air Quality Trends, 1990-1999 (continued)
Metropolitan Statistical Area Trend #Trend 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
Sites
CHAMPAIGN-URBANA, IL
o3
4th max 8-hour
up
1
0.076
0.072
0.071
0.066
0.083
0.084
0.085
0.076
0.083
0.094
2nd daily max 1-hour
up
1
0.087
0.08
0.085
0.074
0.094
0.095
0.094
0.088
0.105
0.108
PM10
90th percentile
Down
1
46
47
47
41
44
44
31
35
39
35
weighted annual mean
NS
1
28.2
30.4
31.4
22
24.9
22.3
19.2
22.5
24.3
22.7
so2
arithmetic mean
Down
1
0.004
0.005
0.004
0.004
0.004
0.003
0.003
0.004
0.003
0.002
2nd max 24-hour
NS
1
0.03
0.038
0.018
0.015
0.024
0.011
0.013
0.018
0.019
0.01
CHARLESTON-NORTH CHARLESTON, SC
CO
2nd max 8-hour
NS
1
4.7
4.9
5.2
5.8
4
6.4
4.7
3.9
2.9
4
Pb
max quarterly mean
NS
1
0.039
0.039
0.01
0.007
0.012
0.01
0.01
0.011
0.026
0.008
no2
arithmetic mean
Down
2
0.008
0.008
0.008
0.008
0.007
0.007
0.007
0.007
0.007
0.007
o3
4th max 8-hour
up
3
0.071
0.068
0.071
0.075
0.073
0.071
0.074
0.072
0.08
0.082
2nd daily max 1-hour
NS
3
0.089
0.085
0.09
0.1
0.088
0.089
0.097
0.089
0.097
0.099
PM10
90th percentile
Down
4
44
40
35.5
35.75
33.5
29
29.5
29.25
36.75
30
weighted annual mean
Down
4
20.175
18.5
17.05
16.1
15.35
13.875
14.2 14.375
15.425
14.25
so2
arithmetic mean
Down
2
0.002
0.003
0.003
0.002
0.002
0.002
0.002
0.002
0.002
0.002
2nd max 24-hour
Down
2
0.016
0.017
0.021
0.014
0.021
0.012
0.014
0.014
0.01
0.009
CHARLESTON, WV
CO 2nd max 8-hour
Pb max quarterly mean
03 4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
S02 arithmetic mean
2nd max 24-hour
CHARLOTTE-GASTONIA-ROCK HILL, NC-SC
CO 2nd max 8-hour
Pb max quarterly mean
N02 arithmetic mean
03 4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
CHARLOTTESVILLE, VA
PM10 90th percentile
weighted annual mean
CHATTANOOGA, TN-GA
03 4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
CHEYENNE, WY
PM„
CHICAGO, IL
CO
Pb
no2
O,
90th percentile
weighted annual mean
2nd max 8-hour
max quarterly mean
arithmetic mean
4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
S02 arithmetic mean
2nd max 24-hour
CHICO-PARADISE, CA
CO 2nd max 8-hour
N02 arithmetic mean
03 4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
CINCINNATI, OH-KY-IN
CO 2nd max 8-hour
N02 arithmetic mean
03 4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
S02 arithmetic mean
2nd max 24-hour
Down
Down
NS
NS
Down
Down
NS
NS
Down
NS
NS
up
NS
NS
Down
NS
Down
NS
NS
Down
Down
Down
Down
Down
Down
NS
NS
NS
NS
NS
Down
NS
NS
NS
NS
NS
Down
NS
Down
NS
NS
NS
Down
Down
Down
Down
1
3
1
1
1
1
2
2
5
1
1
3
3
4
4
1
1
2
2
2
2
1
1
6
9
5
17
17
13
13
9
9
2.8
0.035
0.079
0.118
58
36
0.012
0.056
7.06
0.038
0.017
0.095
0.117
47.75
3.05
0.022
0.09
0.119
47
29.3
0.009
0.036
6.3 6
0.014 0.077
0.016 0.016
0.091 0.085
0.115 0.104
47.5 46
3.3
0.027
0.055
0.067
44
27.6
0.009
0.032
2.2
0.018
0.063
0.075
52
29.2
0.009
0.034
5.56
0.015
0.017
0.097
0.13
41
3.5
0.026
0.075
0.099
49
28.1
0.01
0.037
2.4
0.02
0.091
0.111
40
26
0.007
0.023
2.3
0.016
0.078
0.104
41
24
0.008
0.031
1.9
0.01
0.075
0.103
32
21.1
0.009
0.031
2
0.01
0.091
0.115
35
21.4
0.009
0.031
2
0.01
0.104
0.13
37
21.9
0.009
0.036
5.78 4.68
0.032
0.016
0.089
0.111
42
0.012
0.016
0.092
0.113
40
4.36 4.84
0.009
0.016
0.099
0.126
41.5
4.2 3.82
0.007 0.021 0.019
0.018 0.018 0.018
0.1 0.105 0.102
0.117 0.13 0.125
41.75 47 42.25
31.3 29.875 29.375 27.35 27.875 26.425 28.225 27.4 28.125 26.775
44
26.9
0.092
0.116
61
37.85
30
19.4
4.817
0.072
0.022
0.071
0.092
60.154
35.1
0.007
0.039
3.9
0.015
0.078
0.12
67
28
4.233
0.022
0.088
0.107
64
36.043
0.012
0.054
47
28.4
32
21.6
0.08 0.079
0.098 0.094
63 51.5
37.65 34.45
30
19.4
4.183
0.056
0.022
0.084
0.113
50.538
32.777
0.009
0.042
25
16.6
4.533
0.065
0.025
0.075
0.102
53.538
32.577
0.006
0.029
40
23.7
0.088
0.104
51.5
31.75
24
15.5
4.85
0.063
0.026
0.068
0.085
50.846
31.238
0.006
0.032
5.6 4.6 3.9
0.016 0.016 0.016
0.073 0.077 0.076
0.09 0.09
67 67
28 28
0.09
60
27.2
33
21.5
0.088
0.114
50.5
32.7
28
17.8
6.283
0.054
0.028
0.075
0.097
56.231
35.123
0.006
0.033
4.1
0.015
0.082
0.097
55
33.3
41
22.5
0.09
0.108
49
32.05
26
14.6
3.633
0.054
0.028
0.088
0.114
55.308
32.315
0.005
0.024
3.5
0.014
0.076
0.091
52
26.3
35
21.3
0.088
0.113
52.5
32.3
25
15.1
3.383
0.044
0.028
0.076
0.095
45.077
29.6
0.005
0.022
36
20.9
33
22.7
32
19.9
0.088 0.1 0.096
0.107 0.129 0.117
45 45 42.5
27.2 27.95 27.85
20
12.9
3.45
0.04
0.028
0.079
0.098
45.769
29.631
0.005
0.024
22
13.9
3.55
0.04
0.027
0.074
0.094
50.308
32.554
0.005
0.025
23
14.9
3.417
0.034
0.027
0.083
0.098
51.615
32.077
0.006
0.027
4.2 4.467 4.667
0.022 0.021 0.022
0.092 0.074 0.081
0.112 0.09 0.102
57.143 49 58.286
32.086 30.129 30.543
0.012 0.011 0.011
0.044 0.045 0.044
4.267 3.4
0.022 0.021
0.091 0.093
0.112 0.114
50.714 54.429
30.4 31.3
0.009 0.006
0.044 0.025
3.4 3.5 3.8 4
0.013 0.013 0.013 0.015
0.074 0.066 0.078 0.087
0.096 0.074 0.103 0.11
40 40 37 50
25 25.9 22.3 28.6
2.933 2.733 3.167 2.633
0.022 0.023 0.022 0.019
0.088 0.085 0.088 0.089
0.107 0.11 0.114 0.108
42.429 49.286 46.357 43.714
27.914 28.886 28.236 26.671
0.009 0.009 0.009 0.008
0.035 0.037 0.038 0.033
APPENDIX A • DATA TABLES
197
-------
NATIONALAIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-16. Metropolitan Statistical Area Air Quality Trends, 1990-1999 (continued)
Metropolitan Statistical Area
Trend
#Trend
Sites
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
CLARKSVILLE-HOPKINSVILLE, TN-KY
S02 arithmetic mean
2nd max 24-hour
CLEVELAND-LORAIN-ELYRIA, OH
CO 2nd max 8-hour
03 4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
S02 arithmetic mean
2nd max 24-hour
COLORADO SPRINGS, CO
CO 2nd max 8-hour
Pb max quarterly mean
N02 arithmetic mean
03 4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
S02 arithmetic mean
2nd max 24-hour
COLUMBIA, SC
CO
Pb
no2
O,
2nd max 8-hour
max quarterly mean
arithmetic mean
4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
S02 arithmetic mean
2nd max 24-hour
COLUMBUS, GA-AL
03 4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
COLUMBUS, OH
CO 2nd max 8-hour
03 4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
S02 arithmetic mean
2nd max 24-hour
CORPUS CHRISTI, TX
03 4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
S02 arithmetic mean
2nd max 24-hour
CUMBERLAND, MD-WV
so2
DALLAS, TX
CO
Pb
no2
o3
PM10
DANBURY, CT
o3
PM„
SO,
arithmetic mean
2nd max 24-hour
2nd max 8-hour
max quarterly mean
arithmetic mean
4th max 8-hour
2nd daily max 1-hour
90th percentile
weighted annual mean
4th max 8-hour
2nd daily max 1-hour
90th percentile
weighted annual mean
arithmetic mean
2nd max 24-hour
NS
Down
NS
NS
NS
NS
NS
Down
NS
Down
Down
NS
Down
Down
Down
Down
NS
NS
Down
Down
NS
NS
NS
Down
Down
NS
NS
up
up
NS
NS
Down
NS
NS
NS
NS
Down
Down
NS
NS
NS
NS
NS
NS
NS
NS
NS
Down
up
NS
NS
NS
NS
NS
NS
Down
Down
Down
Down
1
1
3
6
6
10
10
0.007 0.006 0.009 0.01 0.007 0.006 0.006 0.005 0.006 0.005
0.038 0.029 0.036 0.058 0.037 0.019 0.023 0.026 0.02 0.016
5.3
0.084
0.105
54
32.09
0.01
0.041
5.2
0.027
0.016
0.06
0.073
34.667
22.056
0.003
0.011
5.8
0.034
0.013
0.092
0.114
57.143
21.571
0.002
0.012
0.073
0.099
46
28.6
4.133
0.087
0.112
57.5
30.7
0.008
0.038
0.081
0.1
43
29.8
0.002
0.013
0.01
0.031
4.7
0.215
0.012
0.095
0.137
43.2
27.88
0.105
0.149
38
22.1
0.007
0.033
5.433
0.09
0.111
57.3
33.17
0.01
0.04
5.5
0.083
0.103
48.2
29.25
0.009
0.039
4.267
0.088
0.106
50.9
27.97
0.009
0.041
4.825
0.026
0.016
0.065
0.081
39.444
4.4
0.016
0.016
0.059
0.068
33 36.222
24.322 21.722 22.056
0.003 0.004 0.003
0.011 0.013 0.011
4.1
0.015
0.015
0.055
0.064
6
0.043
0.009
0.071
0.095
6.3
0.031
0.011
0.075
0.095
5.6
0.017
0.013
0.082
0.106
55.571 51.286 50.571
19.157 20.071
0.002 0.002
0.013 0.013
18.7
0.002
0.011
0.07 0.079 0.077
0.093 0.095 0.096
40 43
26.9 25.8
37
25.4
4.767
0.095
0.114
52.5
29.65
0.007
0.033
0.073
0.105
45
32.9
0.003
0.027
0.009
0.028
3.8
0.163
0.013
0.071
0.11
39.4
26.12
0.101
0.136
44
25.6
0.008
0.032
4.933
0.079
0.093
43.5
26.15
0.006
0.03
0.079
0.094
41
29.9
0.003
0.018
0.006
0.024
5.6
0.178
0.015
0.089
0.124
39.8
26.26
0.082
0.121
38
22.4
0.007
0.027
3.933
0.084
0.1
48
26.65
0.007
0.034
0.081
0.116
51
30.6
0.003
0.024
0.008
0.027
5.4
0.187
0.014
0.096
0.129
41
26.88
0.096
0.14
40
18.9
0.006
0.024
6.767
0.085
0.105
52
32.31
0.008
0.043
3.625
0.016
0.017
0.055
0.066
34
20.678
0.004
0.018
4.7
0.015
0.011
0.077
0.095
46.786
17.5
0.002
0.011
0.076
0.101
44
26.5
4.467
0.087
0.102
46.5
26.65
0.007
0.041
0.079
0.106
48
31.3
0.002
0.012
0.01
0.037
5.3
0.114
0.016
0.092
0.118
41.2
26.24
0.093
0.125
37
26
0.006
0.037
6.033
0.09
0.108
53.4
31.09
0.006
0.025
4.05
0.012
0.017
0.056
0.07
31
19
0.004
0.015
4
0.011
0.013
0.079
0.101
43.286
14.014
0.002
0.008
0.085
0.106
44
28.2
3.833
0.089
0.11
51.5
29.15
0.004
0.019
0.089
0.119
47
31.1
0.002
0.016
0.005
0.015
5.9
0.129
0.019
0.109
0.137
48.8
30.3
0.093
0.134
34
22
0.004
0.02
5.867
0.088
0.106
44.5
29.24
0.007
0.03
3.625
0.007
0.016
0.059
0.072
4.667
0.085
0.101
46
28.72
0.006
0.03
3.8
0.007
0.015
0.054
0.063
4.5
0.093
0.113
48
30.04
0.006
0.027
3.125
0.012
0.015
0.054
0.063
31
3.567
0.089
0.109
49.1
28.52
0.006
0.031
3.425
0.01
0.014
0.054
0.063
28
30.889 28.222
19.211 18.022 19.322 18.022
0.003 0.003 0.003 0.003
0.01 0.007 0.009 0.014
3.4
0.01
0.013
0.077
0.095
42.714
15.829
0.002
0.013
2.9
0.009
0.011
0.078
0.101
46.143
16.343
0.002
0.012
3.7
0.011
0.014
0.091
0.112
52.429
17.286
0.003
0.011
3.7
0.009
0.014
0.089
0.112
48.714
16.171
0.003
0.011
0.082 0.081 0.09 0.093
0.094 0.096 0.111 0.109
33 39 45 40
22.2 26.4 30.1 26.5
2.467
0.09
0.107
36
24.45
0.004
0.021
0.08
0.101
37
25.1
0.002
0.013
2.433
0.087
0.101
52
27.35
0.004
0.025
0.074
0.092
50
30.5
0.002
0.012
3
0.095
0.111
51
30.25
0.005
0.019
0.079
0.102
50
30.5
0.002
0.017
2.367
0.094
0.111
48.5
27.9
0.004
0.015
0.085
0.1
50
30.5
0.002
0.01
0.003 0.006 0.006 0.006
0.019 0.02 0.02 0.02
5.5
0.08
0.019
0.094
0.115
49.4
30.12
0.081
0.11
36
21.6
0.005
0.02
3.7
0.07
0.018
0.093
0.124
41.4
26.3
0.105
0.138
35
21.3
0.005
0.024
2.7
0.075
0.016
0.094
0.114
41.4
26.3
0.092
0.115
30
20.2
0.004
0.02
2.7
0.086
0.016
0.102
0.13
41.4
26.3
0.106
0.151
30
20.2
0.004
0.024
198
DATA TABLES • APPENDIX A
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-16. Metropolitan Statistical Area Air Quality Trends, 1990-1999 (continued)
Metropolitan Statistical Area Trend #Trend 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
Sites
DAVENPORT-MOLINE-ROCK ISLAND, IA-IL
Pb max quarterly mean
03 4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
S02 arithmetic mean
2nd max 24-hour
DAYTON-SPRINGFIELD, OH
CO 2nd max 8-hour
03 4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
S02 arithmetic mean
2nd max 24-hour
DAYTONA BEACH, FL
03 4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
DECATUR, AL
o3
PM10
DECATUR, IL
Pb
o3
PM10
so2
DENVER, CO
CO
Pb
no2
o3
PMin
so2
4th max 8-hour
2nd daily max 1-hour
90th percentile
weighted annual mean
max quarterly mean
4th max 8-hour
2nd daily max 1-hour
90th percentile
weighted annual mean
arithmetic mean
2nd max 24-hour
2nd max 8-hour
max quarterly mean
arithmetic mean
4th max 8-hour
2nd daily max 1-hour
90th percentile
weighted annual mean
arithmetic mean
2nd max 24-hour
DES MOINES, IA
CO
o3
PM10
DETROIT, Ml
CO
no2
o3
PM10
so2
DOTHAN, AL
PMin
2nd max 8-hour
4th max 8-hour
2nd daily max 1-hour
90th percentile
weighted annual mean
2nd max 8-hour
arithmetic mean
4th max 8-hour
2nd daily max 1-hour
90th percentile
weighted annual mean
arithmetic mean
2nd max 24-hour
90th percentile
weighted annual mean
DULUTH-SUPERIOR, MN-WI
CO 2nd max 8-hour
PM10 90th percentile
weighted annual mean
DUTCHESS COUNTY, NY
03 4th max 8-hour
2nd daily max 1-hour
NS
1
0.031
0.013
0.019
NS
2
0.067
0.08
0.076
NS
2
0.084
0.092
0.096
NS
5
59.4
55.4
59.8
NS
5
35.26
34.48
33.68
Down
3
0.005
0.004
0.004
Down
3
0.022
0.02
0.019
Down
2
3.2
3.45
3.6
NS
3
0.091
0.094
0.077
NS
3
0.114
0.111
0.097
NS
3
47.667
43.333
41
Down
3
26.033
28.2
25.233
NS
2
0.006
0.005
0.005
NS
2
0.023
0.022
0.02
NS
2
0.073
0.073
0.073
NS
2
0.082
0.082
0.082
NS
1
29
29
29
NS
1
19.2
19.2
19.2
up
1
0.069
0.069
0.069
up
1
0.08
0.08
0.08
NS
1
42
54
41
NS
1
24.7
28.1
24.9
NS
1
0.026
0.031
0.03
NS
1
0.076
0.087
0.078
NS
1
0.088
0.095
0.086
NS
1
56
54
63
NS
1
33.9
36.3
38.4
NS
1
0.008
0.007
0.005
Down
1
0.06
0.039
0.023
Down
6
7.217
7
8.3
Down
4
0.072
0.07
0.071
NS
1
0.024
0.024
0.024
NS
6
0.072
0.072
0.068
NS
6
0.101
0.094
0.092
Down
12
44.333
46.667
41.167
NS
12
23.35
23.833
23.575
Down
2
0.006
0.006
0.007
NS
2
0.02
0.026
0.038
NS
3
4.567
4.6
3.933
NS
1
0.037
0.033
0.071
NS
1
0.06
0.048
0.079
NS
3
56
48
55.333
NS
3
32.133
28.533
28
Down
5
4.12
4.5
4.08
NS
2
0.021
0.02
0.02
NS
8
0.084
0.094
0.078
NS
8
0.101
0.119
0.098
NS
6
64.167
59
46.5
NS
6
36.333
33.467
28.15
Down
10
0.01
0.008
0.007
NS
10
0.038
0.033
0.03
NS
1
64
44
43
NS
1
30.6
27.6
24.7
NS
1
4.4
5.2
4
Down
6
40.833
37.167
33.667
NS
6
22.433
23.133
20.417
NS
1
0.101
0.101
0.092
NS
1
0.126
0.126
0.112
0.016 0.015 0.013
0.067 0.073 0.077
0.082 0.087 0.093
50.6 59.333 63.867
0.019 0.015 0.014 0.014
0.076 0.069 0.072 0.076
0.086 0.084 0.092 0.093
58.2 57.2 58 58.6
33.92 33.84 33.32 33.4
3.55
0.087
0.109
45.667
24.6
0.006
0.032
32
19.6
0.08
0.091
44
24.8
0.026
0.065
0.077
46
27.5
0.006
6.6
3.35 2.95
0.091 0.091
0.114 0.116
39.667 43.667
24.433 25.633
0.006 0.004
0.032 0.016
0.072 0.068
0.084 0.083
28 34
20.2 20.9
2.35
0.097
0.113
38
22.733
0.005
0.027
2.95 2.8
0.089 0.096
0.107 0.117
41 42.333
24 24.633
0.005 0.005
0.027 0.019
2.25
0.093
0.116
43
23.8
0.005
0.018
0.066 0.072 0.079 0.075
0.079 0.086 0.094 0.087
28 28 30 26
20.2 19.3 20 18.6
0.077
0.092
35
22.4
0.046
0.079
0.095
53
28.9
0.007
0.083
0.098
40
25
0.028
0.08
0.097
56
29.5
0.005
0.086
0.096
32
20.5
0.023
0.094
0.1
43
27.9
0.005
0.076 0.085 0.092
0.09 0.102 0.103
41 41 41
22.5 24.5 24.5
0.027
0.077
0.087
41
27.1
0.006
0.024
0.078
0.094
49
31.5
0.005
0.024
0.087
0.102
49
31.5
0.006
0.03 0.024 0.022 0.021 0.02 0.027
4.533
0.041
0.08
49
28.7
4.26
0.021
0.079
0.104
55.333
32.8
0.007
0.03
52
26.4
4.1
31.5
18.9
0.099
0.139
6.1
0.048
0.028
0.069
0.09
43.417
22.183
0.006
0.025
3.933
0.052
0.073
52.333
5.567
0.048
0.023
0.067
0.09
35.583
19.025
0.004
0.016
3.967
0.071
0.081
54
4.833
0.037
0.022
0.07
0.092
35.833
19.783
0.005
0.02
4.733
0.024
0.023
0.067
0.086
39.833
20.242
0.005
0.021
3.883
0.045
0.023
0.08
0.1
38.833
20.292
0.004
0.018
4.05
0.04
0.02
0.069
0.089
36.917
19.892
0.004
0.018
30.067 29.867
3.2 2.967 5.733 2.767
0.064 0.063 0.056 0.059
0.082 0.075 0.065 0.069
53 58.667 44.667 48.667
31.3 32.133 25.967 25.6
5.8
0.022
0.089
0.124
4.3
0.02
0.087
0.117
60.667 58.833
37.65 34.517
0.007 0.006
0.032 0.03
47 46
27.8 28.1
4.3 4.5
30.5 32
18.733 18.817
3.74
0.021
0.084
0.1
49.5
3.04
0.02
0.084
0.108
45
2.98 3.08
0.021 0.021
0.089 0.089
0.11 0.11
53 52.167
0.087
0.117
0.093
0.115
30.933 27.733 29.467 29.933
0.006 0.006 0.007 0.006
0.034 0.028 0.032 0.031
36 45 41 43
22.3 24.9 27.3 28.8
4.5 3.2 3.7 2.3
31.5 30.833 30.333 35.333
19.117 18.483 19.65 20.567
0.089 0.089 0.089 0.093
0.109 0.111 0.108 0.12
APPENDIX A • DATA TABLES
199
-------
NATIONALAIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-16. Metropolitan Statistical Area Air Quality Trends, 1990-1999 (continued)
Metropolitan Statistical Area
Trend
#Trend
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
Sites
EL PASO, TX
CO
2nd max 8-hour
Down
6
10.033
8.55
7.533
7.383
6.167
6.3
7.767
6.35
6.083
4.633
Pb
max quarterly mean
Down
4
0.267
0.274
0.187
0.179
0.117
0.135
0.203
0.092
0.112
0.1
NO,
arithmetic mean
NS
2
0.022
0.023
0.026
0.026
0.029
0.029
0.029
0.027
0.025
0.023
o3
4th max 8-hour
NS
4
0.076
0.068
0.073
0.068
0.081
0.078
0.078
0.07
0.077
0.062
2nd daily max 1-hour
Down
4
0.121
0.119
0.119
0.108
0.127
0.117
0.118
0.113
0.11
0.088
PM10
90th percentile
NS
8
62.625
52.75
49.75 42.875
47.375
50.75
50.5 44.875
44.25
56.25
weighted annual mean
NS
8
32.475
27.8
27.725 24.488
24.863
27.813
26.588 22.775
23.45
29.313
so2
arithmetic mean
Down
2
0.011
0.009
0.012
0.009
0.007
0.008
0.008
0.007
0.006
0.004
2nd max 24-hour
Down
2
0.057
0.047
0.055
0.056
0.028
0.044
0.035
0.026
0.022
0.017
ELKHART-GOSHEN, IN
o3
4th max 8-hour
NS
1
0.078
0.078
0.078
0.078
0.083
0.09
0.091
0.089
0.082
0.077
2nd daily max 1-hour
NS
1
0.092
0.092
0.092
0.09
0.095
0.102
0.115
0.108
0.106
0.085
ELMIRA, NY
o3
4th max 8-hour
NS
1
0.079
0.091
0.066
0.08
0.074
0.076
0.072
0.073
0.082
0.082
2nd daily max 1-hour
NS
1
0.096
0.101
0.085
0.09
0.084
0.088
0.088
0.081
0.094
0.092
so2
arithmetic mean
Down
1
0.005
0.005
0.005
0.005
0.004
0.004
0.004
0.003
0.003
0.003
2nd max 24-hour
Down
1
0.021
0.022
0.021
0.019
0.023
0.014
0.016
0.015
0.011
0.015
ERIE, PA
NO,
arithmetic mean
NS
1
0.015
0.013
0.014
0.014
0.015
0.015
0.015
0.015
0.014
0.015
o3
4th max 8-hour
NS
1
0.084
0.091
0.084
0.081
0.09
0.088
0.083
0.087
0.098
0.096
2nd daily max 1-hour
NS
1
0.1
0.113
0.098
0.107
0.101
0.105
0.1
0.103
0.122
0.112
so2
arithmetic mean
NS
1
0.014
0.01
0.011
0.011
0.01
0.009
0.011
0.009
0.01
0.01
2nd max 24-hour
NS
1
0.057
0.044
0.056
0.072
0.076
0.05
0.066
0.035
0.068
0.043
EUGENE-SPRINGFIELD, OR
CO
2nd max 8-hour
NS
2
4.9
5.2
6.2
5.3
5.85
5.2
5.15
4.95
4.25
4.45
o3
4th max 8-hour
NS
2
0.068
0.069
0.074
0.054
0.069
0.062
0.086
0.058
0.076
0.062
2nd daily max 1-hour
NS
2
0.09
0.091
0.095
0.077
0.086
0.082
0.108
0.072
0.098
0.076
PM10
90th percentile
Down
5
55.6
65
55.8
62.6
45.6
43.6
37.4
36.8
33.8
33.8
weighted annual mean
Down
5
28.4
31.86
28.48
28.68
24.58
22.86
19.94
20.98
18.14
18.14
EVANSVILLE-HENDERSON, IN-KY
CO
2nd max 8-hour
NS
2
3.7
3.45
3.6
4.35
4.05
3.2
3.05
3.65
3.05
3.1
no2
arithmetic mean
Down
1
0.018
0.021
0.018
0.017
0.018
0.017
0.017
0.016
0.018
0.016
o3
4th max 8-hour
NS
6
0.086
0.087
0.076
0.082
0.092
0.092
0.089
0.088
0.088
0.091
2nd daily max 1-hour
NS
6
0.103
0.104
0.091
0.103
0.108
0.112
0.105
0.103
0.111
0.109
PM10
90th percentile
NS
4
49.75
47
48.5
49.25
50.75
52
40
43.5
43.5
43.75
weighted annual mean
Down
4
30.85
32.25
29.175
29.1
31.425
30.775
25.225
26.15
27.425
25.775
so2
arithmetic mean
Down
5
0.014
0.013
0.012
0.012
0.012
0.009
0.01
0.01
0.011
0.008
2nd max 24-hour
Down
5
0.066
0.064
0.071
0.055
0.049
0.043
0.052
0.052
0.05
0.046
FAYETTEVILLE, NC
o3
4th max 8-hour
NS
1
0.087
0.078
0.079
0.093
0.084
0.081
0.086
0.085
0.093
0.1
2nd daily max 1-hour
NS
1
0.1
0.101
0.092
0.115
0.098
0.1
0.099
0.098
0.112
0.12
PM10
90th percentile
NS
1
50
45
39
41
40
35
39
41
41
39
weighted annual mean
Down
1
31.4
26.9
26.2
27.3
25.1
23.3
25.3
24.8
26.5
24.4
FAYETTEVILLE-SPRINGDALE-ROGERS, AR
PM10
90th percentile
NS
1
38
38
30
39
40
36
36
31
31
31
weighted annual mean
NS
1
23.2
23.6
21.5
23.9
24.8
24.2
22.5
20.4
20.4
20.4
FLAGSTAFF, AZ-UT
o3
4th max 8-hour
NS
1
0.072
0.073
0.074
0.066
0.073
0.069
0.073
0.072
0.072
0.076
2nd daily max 1-hour
NS
1
0.082
0.079
0.079
0.07
0.081
0.075
0.082
0.076
0.076
0.086
FLINT, Ml
o3
4th max 8-hour
up
2
0.076
0.08
0.07
0.07
0.075
0.081
0.087
0.083
0.089
0.092
2nd daily max 1-hour
NS
2
0.095
0.099
0.091
0.105
0.089
0.094
0.106
0.097
0.109
0.109
SO,
2nd max 24-hour
NS
1
0.014
0.014
0.014
0.017
0.017
0.016
0.012
0.012
0.014
0.011
FLORENCE, AL
PM10
90th percentile
NS
1
39
41
34
37
34
37
29
32
35
35
weighted annual mean
NS
1
23.5
23.7
21.3
22.6
20.1
22
17.8
18.7
22.2
22.2
so2
arithmetic mean
Down
1
0.005
0.004
0.004
0.004
0.003
0.003
0.003
0.003
0.003
0.003
2nd max 24-hour
Down
1
0.027
0.025
0.019
0.022
0.022
0.018
0.019
0.02
0.019
0.017
FORT COLLINS-LOVE LAND, CO
CO
2nd max 8-hour
Down
1
7
9.8
6.9
6.6
6
5.2
5.1
5.2
4.1
5.1
o3
4th max 8-hour
NS
2
0.066
0.074
0.069
0.068
0.072
0.072
0.069
0.07
0.076
0.069
2nd daily max 1-hour
NS
2
0.083
0.09
0.091
0.091
0.095
0.089
0.092
0.088
0.092
0.085
PM10
90th percentile
Down
1
39
50
35
36
34
41
33
24
26
26
weighted annual mean
Down
1
23.4
25.1
22.6
22.4
21.6
22.3
20.4
15.7
16.2
16
200 DATA TABLES • APPENDIX A
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-16. Metropolitan Statistical Area Air Quality Trends, 1990-1999 (continued)
Metropolitan Statistical Area
Trend
#Trend
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
Sites
FORT LAUDERDALE, FL
CO
2nd max 8-hour
Down
6
4.333
4.467
4.567
3.95
4.05
4.333
3.417
3.483
2.7
3.417
Pb
max quarterly mean
up
1
0.013
0.021
0.037
0.027
0.029
0.019
0.047
0.037
0.037
0.037
NO,
arithmetic mean
NS
1
0.009
0.009
0.009
0.01
0.009
0.011
0.01
0.01
0.01
0.011
o3
4th max 8-hour
NS
3
0.07
0.063
0.077
0.078
0.07
0.065
0.065
0.07
0.074
0.071
2nd daily max 1-hour
NS
3
0.092
0.093
0.098
0.098
0.092
0.093
0.094
0.089
0.095
0.097
PM10
90th percentile
NS
5
26
26
26
28.2
22
22.2
24
23
29
21.4
weighted annual mean
NS
5
17.78
17.78
17.78
18.34
16.22
15.34
16.26
16.28
18.68
15.84
so2
arithmetic mean
up
1
0.002
0.002
0.002
0.002
0.002
0.002
0.002
0.002
0.003
0.003
2nd max 24-hour
up
1
0.006
0.006
0.006
0.011
0.013
0.008
0.008
0.011
0.017
0.015
FORT MYERS-CAPE CORAL, FL
o3
4th max 8-hour
NS
1
0.069
0.064
0.073
0.069
0.076
0.066
0.062
0.067
0.092
0.077
2nd daily max 1-hour
NS
1
0.08
0.082
0.082
0.078
0.09
0.086
0.072
0.076
0.109
0.096
FORT SMITH, AR-OK
PM10
90th percentile
NS
1
38
37
36
39
38
44
36
39
39
39
weighted annual mean
NS
1
25.7
24.7
23.5
24.9
23.8
25.7
25.3
22.3
22.3
22.3
FORT WAYNE, IN
o3
4th max 8-hour
NS
2
0.086
0.088
0.088
0.081
0.094
0.094
0.091
0.087
0.089
0.089
2nd daily max 1-hour
NS
2
0.094
0.1
0.095
0.093
0.113
0.109
0.1
0.095
0.103
0.1
PM10
90th percentile
Down
1
53
44
38
36
43
44
28
28
39
31
weighted annual mean
NS
1
27.2
27.2
22.7
22.9
23.5
23.9
17.2
19.6
23.7
17
FORT WORTH-ARLINGTON, TX
CO
2nd max 8-hour
Down
1
3.6
3.4
3.8
3.5
2.7
3.3
2.8
2.8
2.5
2.6
NO,
arithmetic mean
NS
1
0.012
0.014
0.015
0.013
0.017
0.017
0.015
0.016
0.013
0.017
o3
4th max 8-hour
NS
2
0.099
0.108
0.084
0.093
0.101
0.104
0.094
0.092
0.099
0.102
2nd daily max 1-hour
NS
2
0.135
0.145
0.122
0.113
0.133
0.141
0.129
0.123
0.126
0.145
PM10
90th percentile
NS
2
40
32
29
32
32.5
36
39
30
30
30
weighted annual mean
NS
2
23.65
21.55
19.85
19.7
19.55
22.45
22.95
19.75
19.75
19.75
FRESNO, CA
CO
2nd max 8-hour
Down
4
5.725
6.125
4.575
4.175
4.925
4.225
4.15
3.5
3.5
3.4
Pb
max quarterly mean
Down
1
0.065
0.037
0.035
0.025
0.02
0.015
0.008
0.011
0.013
0.013
NO,
arithmetic mean
Down
4
0.021
0.021
0.02
0.021
0.02
0.02
0.019
0.018
0.018
0.021
o3
4th max 8-hour
NS
5
0.1
0.105
0.105
0.106
0.096
0.103
0.108
0.102
0.116
0.103
2nd daily max 1-hour
NS
5
0.138
0.146
0.142
0.14
0.128
0.134
0.142
0.128
0.154
0.132
PM10
90th percentile
NS
5
106.6
100.4
72.6
85.6
63
80
59.2
76.8
61.8
81.2
weighted annual mean
Down
5
54.96
53.76
45.22
43.18
40.24
41.04
35.14
40.38
34.42
42.38
GADSDEN, AL
PM10
90th percentile
NS
2
54.5
56
52
57.5
46
42.5
35.5
47
50
46.5
weighted annual mean
Down
2
32.8
32.2
31.35
33.2
30.3
29.6
23.4
26.25
30.95
28.25
GALVESTON-TEXAS CITY, TX
o3
4th max 8-hour
NS
1
0.09
0.091
0.067
0.114
0.088
0.14
0.08
0.097
0.095
0.108
2nd daily max 1-hour
NS
1
0.15
0.15
0.097
0.176
0.125
0.198
0.107
0.175
0.146
0.172
PM10
90th percentile
NS
2
43.5
37.5
36.5
42
39
45.5
31
38
38
38
weighted annual mean
NS
2
25.7
22.3
23.2
23.15
24.15
27.8
21.1
23.25
23.25
23.25
so2
arithmetic mean
NS
1
0.007
0.007
0.005
0.005
0.006
0.006
0.014
0.006
0.004
0.007
2nd max 24-hour
NS
1
0.063
0.05
0.039
0.056
0.052
0.089
0.067
0.053
0.039
0.04
GARY, IN
CO
2nd max 8-hour
NS
2
4.15
4.05
4.35
4.7
5.55
3.85
3.25
3.65
3.85
3.8
Pb
max quarterly mean
NS
3
0.21
0.098
0.1
0.074
0.181
0.093
0.127
0.088
0.085
0.103
o3
4th max 8-hour
NS
2
0.08
0.086
0.084
0.072
0.084
0.101
0.095
0.093
0.086
0.098
2nd daily max 1-hour
NS
2
0.097
0.11
0.118
0.087
0.111
0.122
0.121
0.116
0.117
0.115
PM10
90th percentile
Down
7
50.571
43.429 42.286 38.571
41.571
40.857
32.286 31.429 35.429 29.857
weighted annual mean
Down
7
32.443
28.329
25.4 22.886
25.414 24.129
20.4 20.993 22.571
20.486
so2
arithmetic mean
Down
4
0.01
0.008
0.008
0.008
0.007
0.005
0.005
0.006
0.006
0.005
2nd max 24-hour
Down
4
0.052
0.029
0.031
0.034
0.034
0.024
0.025
0.026
0.03
0.021
GOLDSBORO, NC
PM10
90th percentile
NS
1
46
46
36
36
33
30
33
36
34
34
weighted annual mean
Down
1
26.8
26.8
24.3
23.8
21
20.2
22.6
23.1
21.9
21.9
GRAND JUNCTION, CO
CO
2nd max 8-hour
Down
1
6.7
6.7
6.7
6.1
6
5.4
5.8
5.4
5.3
4.7
PM10
90th percentile
Down
4
39.5
49.25
41.5
32.5
36
30.75
30.25
29.5
30.5
33
weighted annual mean
Down
4
18.925
20.95
18.45
17.35
17.15
15.2
14.875
14.5
15.3
15.325
GRAND RAPIDS-MUSKEGON-HOLLAND, Ml
CO
2nd max 8-hour
NS
1
3.5
4
3.2
3.2
4
4.6
3.3
2.4
2.9
3.5
Pb
max quarterly mean
Down
3
0.023
0.016
0.019
0.014
0.013
0.01
0.012
0.012
0.012
0.012
o3
4th max 8-hour
NS
4
0.101
0.099
0.082
0.082
0.086
0.098
0.089
0.083
0.086
0.092
2nd daily max 1-hour
NS
4
0.129
0.13
0.108
0.099
0.11
0.122
0.122
0.103
0.105
0.108
PM10
90th percentile
Down
2
55
40.5
54
39
46
40
34.5
32
37.5
36
weighted annual mean
Down
2
30
25.65
34.8
21.7
26.85
20.95
20.25
18.65
21.25
18.9
so2
arithmetic mean
Down
1
0.004
0.004
0.003
0.003
0.003
0.002
0.002
0.002
0.002
0.001
2nd max 24-hour
Down
1
0.012
0.014
0.015
0.012
0.013
0.011
0.011
0.008
0.008
0.006
APPENDIX A • DATA TABLES
201
-------
NATIONALAIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-16. Metropolitan Statistical Area Air Quality Trends, 1990-1999 (continued)
Metropolitan
Statistical Area
Trend
#Trend
1990
1991
1992
1993
1994
1995
Sites
GREAT FALLS,
MT
CO
2nd max 8-hour
NS
1
5.6
6.6
5.8
6.9
4.8
6.2
PM10
90th percentile
Down
1
39
44
40
40
34
30
weighted annual mean
Down
1
23.7
21.1
21.4
21.4
20.8
17.9
GREELEY, CO
CO
2nd max 8-hour
Down
1
7.1
7.8
7.5
5.8
5.2
5.3
o3
4th max 8-hour
NS
1
0.076
0.077
0.064
0.063
0.071
0.072
2nd daily max 1-hour
NS
1
0.109
0.096
0.084
0.087
0.087
0.093
PM10
90th percentile
Down
1
43
51
43
39
37
34
weighted annual mean
Down
1
24.7
25.9
25.4
22.6
23.1
19.9
GREEN BAY, Wl
so2
arithmetic mean
Down
1
0.005
0.005
0.004
0.003
0.003
0.004
2nd max 24-hour
Down
1
0.02
0.042
0.021
0.018
0.015
0.017
GREENSBORO
-WINSTON-SALEM—HIGH POINT, N
CO
2nd max 8-hour
Down
1
6.8
6.6
5.7
5.5
6
6.2
NO,
arithmetic mean
NS
1
0.017
0.016
0.015
0.017
0.017
0.016
o3
4th max 8-hour
up
2
0.091
0.084
0.08
0.091
0.087
0.088
2nd daily max 1-hour
NS
2
0.112
0.102
0.1
0.118
0.108
0.11
PM10
90th percentile
Down
3
49.333
47.667
41
44.667
35.333
39
weighted annual mean
Down
3
30.967
30.9
26.9
27.4
24.8
25.9
so2
arithmetic mean
NS
1
0.008
0.007
0.006
0.006
0.007
0.007
2nd max 24-hour
NS
1
0.023
0.027
0.019
0.022
0.021
0.025
GREENVILLE, NC
o3
4th max 8-hour
NS
1
0.082
0.082
0.078
0.091
0.077
0.082
2nd daily max 1-hour
up
1
0.091
0.091
0.095
0.108
0.086
0.098
GREENVILLE-SPARTANBURG-ANDERSON, SC
Pb
max quarterly mean
Down
3
0.04
0.035
0.018
0.022
0.019
0.016
NO,
arithmetic mean
Down
1
0.019
0.019
0.019
0.018
0.018
0.017
o3
4th max 8-hour
up
4
0.075
0.079
0.079
0.087
0.082
0.087
2nd daily max 1-hour
up
4
0.094
0.098
0.094
0.113
0.099
0.112
so2
arithmetic mean
NS
1
0.002
0.003
0.003
0.003
0.003
0.001
2nd max 24-hour
NS
1
0.011
0.017
0.013
0.012
0.016
0.007
HAMILTON-MIDDLETOWN, OH
o3
4th max 8-hour
NS
2
0.099
0.094
0.071
0.091
0.091
0.092
2nd daily max 1-hour
NS
2
0.122
0.111
0.097
0.121
0.113
0.127
PM10
90th percentile
NS
4
59.5
61.25
50.75
62.75
53.25
57.75
weighted annual mean
NS
4
34.275
35.55
30.075
31.125
30.375
33.8
so2
arithmetic mean
Down
2
0.01
0.009
0.007
0.008
0.008
0.005
2nd max 24-hour
Down
2
0.037
0.04
0.033
0.035
0.038
0.019
HARRISBURG-LEBANON-CARLISLE, PA
Pb
max quarterly mean
NS
1
0.039
0.039
0.039
0.041
0.041
0.041
no2
arithmetic mean
NS
2
0.013
0.014
0.013
0.011
0.015
0.014
o3
4th max 8-hour
NS
3
0.091
0.096
0.077
0.094
0.089
0.086
2nd daily max 1-hour
NS
3
0.11
0.109
0.093
0.113
0.115
0.105
PM10
90th percentile
NS
1
35
39
27
30
44
32
weighted annual mean
NS
1
18.5
22
17.8
20.7
22.3
20.7
so2
arithmetic mean
Down
2
0.005
0.006
0.005
0.006
0.007
0.005
2nd max 24-hour
NS
2
0.021
0.021
0.022
0.021
0.035
0.017
HARTFORD, CT
CO
2nd max 8-hour
Down
2
6.45
6.1
6.05
5.55
6.35
5.75
no2
arithmetic mean
NS
1
0.019
0.02
0.017
0.018
0.02
0.017
o3
4th max 8-hour
Down
3
0.103
0.108
0.093
0.1
0.099
0.097
2nd daily max 1-hour
NS
3
0.149
0.157
0.123
0.146
0.133
0.134
PM10
90th percentile
Down
6
34.667
38.167
33.667
30.833
34.667
28.5
weighted annual mean
NS
6
19.9
23
19.917
17.783
20.017 16.417
so2
arithmetic mean
Down
4
0.007
0.007
0.006
0.005
0.006
0.004
2nd max 24-hour
Down
4
0.03
0.03
0.027
0.019
0.027
0.019
HONOLULU, HI
CO
2nd max 8-hour
Down
4
1.95
1.775
1.875
2
1.85
1.7
o3
4th max 8-hour
NS
1
0.034
0.041
0.047
0.049
0.052
0.051
2nd daily max 1-hour
NS
1
0.053
0.05
0.059
0.055
0.055
0.056
PM10
90th percentile
NS
3
21.667
22.333
21.333
21
23
21
weighted annual mean
NS
3
10.167
10.533
10.567
11.167
12.167
10.5
so2
arithmetic mean
NS
3
0.001
0.001
0.002
0.002
0.001
0.001
2nd max 24-hour
NS
3
0.006
0.006
0.006
0.009
0.006
0.005
HOUMA, LA
o3
4th max 8-hour
NS
1
0.083
0.076
0.07
0.075
0.086
0.101
2nd daily max 1-hour
NS
1
0.115
0.097
0.091
0.096
0.103
0.141
5.4
35
19.1
7
0.07
0.097
30
17.7
6.4
32
20.3
4.8
0.069
0.095
30
17.8
4.5
32
20.3
4.4
0.075
0.102
30
16.5
3.5
32
20.3
3.4
0.069
0.092
29
17.5
0.003 0.003 0.003 0.003
0.011 0.017 0.011 0.011
4.3
0.016
0.088
0.114
4.7 5.4 3.6
0.017 0.017 0.016
0.088 0.096 0.096
0.11 0.119 0.112
35.333 36.667 38.667 37.667
24.033 23.933 24.4 23.767
0.007 0.007 0.006 0.005
0.026 0.023 0.023 0.02
0.086 0.097 0.089 0.093
0.097 0.122 0.109 0.109
0.009 0.01 0.015 0.011
0.016 0.017 0.017 0.017
0.085 0.087 0.098 0.097
0.105 0.102 0.116 0.115
0.002 0.003 0.003 0.003
0.012 0.014 0.015 0.009
0.093 0.09 0.091 0.096
0.111 0.111 0.114 0.118
44.5 53.75 53.25 49.75
29.325 30.425 30.45 28.25
0.007 0.007 0.006 0.006
0.025 0.034 0.021 0.023
0.04
0.015
0.08
0.097
31
18.8
0.005
0.021
0.039
0.013
0.089
0.11
33
21.9
0.005
0.022
0.036
0.012
0.092
0.112
33
21.9
0.005
0.017
0.036
0.012
0.096
0.115
33
21.9
0.004
0.017
4.975 4.8
0.016 0.018
0.082 0.099
0.098 0.143
30 33.167
17.383
0.004
5.4
0.02
0.09
0.12
31 29.833
18.45 17.983 17.417
0.004 0.004 0.004
0.019 0.019
4.35
0.018
0.097
0.138
0.018 0.021
1.575 1.525 1.45 1.2
0.041 0.047 0.049 0.048
0.047 0.053 0.056 0.054
22.667 19 21.667 21
11.467 11.633 12.2 10.067
0.001 0.002 0.002 0.001
0.007 0.005 0.007 0.003
0.075 0.079 0.089 0.087
0.094 0.103 0.11 0.115
202
DATA TABLES • APPENDIX A
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-16. Metropolitan Statistical Area Air Quality Trends, 1990-1999 (continued)
Metropolitan Statistical Area Trend #Trend 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
Sites
HOUSTON, TX
CO
2nd max 8-hour
Down
4
6.775
6.025
6.775
5.6
4.9
4.025
5.25
4.275
3.8
3.35
no2
arithmetic mean
Down
4
0.023
0.022
0.022
0.019
0.021
0.021
0.02
0.021
0.019
0.02
o3
4th max 8-hour
NS
9
0.116
0.098
0.102
0.095
0.097
0.114
0.097
0.107
0.109
0.102
2nd daily max 1-hour
NS
9
0.192
0.167
0.162
0.161
0.147
0.168
0.154
0.171
0.174
0.159
PM-io
90th percentile
Down
5
50.2
48.2
48
50.4
50.2
48
39
47.8
47.8
47.8
weighted annual mean
Down
5
31.4
31.4
30.22
30.36
30.96
29.54
26
29.42
29.42
29.42
so2
arithmetic mean
Down
5
0.005
0.006
0.005
0.005
0.004
0.004
0.004
0.003
0.003
0.003
2nd max 24-hour
Down
5
0.025
0.027
0.024
0.022
0.02
0.025
0.023
0.017
0.018
0.015
HUNTINGTON-ASHLAND, WV-KY-OH
Pb
max quarterly mean
NS
1
0.048
0.028
0.033
0.022
0.03
0.036
0.049
0.023
0.023
0.023
o3
4th max 8-hour
NS
3
0.093
0.096
0.078
0.09
0.092
0.089
0.077
0.081
0.097
0.094
2nd daily max 1-hour
NS
3
0.114
0.131
0.097
0.11
0.126
0.117
0.097
0.112
0.127
0.116
PM-io
90th percentile
Down
5
53.8
50.4
46
52.2
51.6
48.2
39
45.2
44
47
weighted annual mean
Down
5
33.82
32.44
29.18
28.46
30.68
29.86
26.46
28.4
26.48
27.9
so2
arithmetic mean
Down
8
0.012
0.012
0.01
0.011
0.01
0.009
0.008
0.008
0.008
0.008
2nd max 24-hour
Down
8
0.07
0.05
0.043
0.052
0.049
0.034
0.028
0.031
0.033
0.03
HUNTSVILLE, AL
CO
2nd max 8-hour
NS
1
4.2
4.1
4.2
4
3.5
3.6
3
3.1
3.3
4.3
o3
4th max 8-hour
NS
1
0.079
0.082
0.087
0.087
0.075
0.08
0.081
0.086
0.092
0.093
2nd daily max 1-hour
NS
1
0.087
0.106
0.114
0.112
0.107
0.102
0.096
0.096
0.118
0.106
PM-io
90th percentile
Down
3
47.333
49.333
43
40
35.5
34.333
31.333
37.333
34.667
35.667
weighted annual mean
Down
3
29.5
27.3
25.967
23.6
22.667
22.567
20.767
20.8
22.033
22.867
INDIANAPOLIS, IN
CO
2nd max 8-hour
Down
2
3.95
5.15
3.5
4
3.45
3.85
2.75
3.15
2.65
2.4
Pb
max quarterly mean
Down
4
1.11
0.738
0.596
0.654
1.003
0.299
0.073
0.054
0.059
0.095
no2
arithmetic mean
NS
1
0.018
0.018
0.018
0.018
0.019
0.02
0.018
0.015
0.019
0.018
o3
4th max 8-hour
up
6
0.085
0.086
0.082
0.083
0.093
0.094
0.096
0.088
0.094
0.094
2nd daily max 1-hour
NS
6
0.102
0.1
0.094
0.098
0.11
0.111
0.116
0.104
0.113
0.107
PM-io
90th percentile
Down
13
54.308
49.077
43
51.231
46.462
46.077
34.308
36.308
38.923
37
weighted annual mean
Down
13
32.8
30.562
27.608
27.677
28.254
28.115
22.508
22.523
23.9
21.838
so2
arithmetic mean
Down
6
0.009
0.008
0.007
0.008
0.007
0.005
0.005
0.005
0.005
0.005
2nd max 24-hour
Down
6
0.033
0.03
0.028
0.037
0.038
0.021
0.024
0.023
0.021
0.02
JACKSON, MS
CO
2nd max 8-hour
NS
1
4.3
4.3
4.3
6.2
5.1
4.4
4.8
3.8
3.7
5
o3
4th max 8-hour
up
2
0.08
0.072
0.071
0.073
0.073
0.076
0.077
0.077
0.084
0.083
2nd daily max 1-hour
up
2
0.1
0.085
0.083
0.089
0.086
0.09
0.093
0.095
0.105
0.103
PM10
90th percentile
Down
1
44
44
43
38
32
34
34
36
32
32
weighted annual mean
Down
1
25.7
25.7
27
23.3
20.9
22.8
21.5
24
19.9
19.9
so2
arithmetic mean
NS
1
0.005
0.005
0.005
0.003
0.002
0.002
0.002
0.002
0.002
0.002
2nd max 24-hour
Down
1
0.013
0.013
0.013
0.01
0.008
0.007
0.008
0.007
0.008
0.007
JACKSON, TN
PM-io
90th percentile
NS
2
44
39
41
37
31.5
42.5
33.5
34
34
34
weighted annual mean
Down
2
27.7
26.9
27.4
23.35
22.6
25.1
22.1
22.55
23.3
23.3
JACKSONVILLE, FL
CO
2nd max 8-hour
Down
4
4.05
3.6
4.15
4.075
3.85
3.6
3.075
2.5
2.675
3.375
Pb
max quarterly mean
Down
2
0.038
0.025
0.024
0.048
0.02
0.028
0.022
0.017
0.018
0.018
no2
arithmetic mean
NS
1
0.015
0.014
0.014
0.015
0.014
0.016
0.015
0.014
0.015
0.016
o3
4th max 8-hour
NS
2
0.081
0.072
0.079
0.081
0.074
0.074
0.075
0.08
0.082
0.079
2nd daily max 1-hour
NS
2
0.11
0.089
0.102
0.11
0.099
0.112
0.091
0.101
0.101
0.099
PM-io
90th percentile
NS
2
45
46.5
41.5
38.5
39.5
39
34.5
38.5
43
41.5
weighted annual mean
NS
2
33.75
33.15
27
27.6
26.55
25.9
25.25
25.5
29
28.2
so2
arithmetic mean
NS
6
0.004
0.003
0.003
0.003
0.003
0.003
0.003
0.003
0.003
0.003
2nd max 24-hour
Down
6
0.034
0.022
0.022
0.026
0.031
0.018
0.019
0.016
0.021
0.019
JACKSONVILLE, NC
PM10
90th percentile
NS
1
39
39
35
35
28
29
32
32
37
37
weighted annual mean
NS
1
23.9
23.9
22.9
22.9
20.4
19.8
21.9
20.2
22.1
22.1
JAMESTOWN, NY
o3
4th max 8-hour
up
1
0.076
0.076
0.083
0.081
0.08
0.089
0.081
0.087
0.095
0.087
2nd daily max 1-hour
NS
1
0.098
0.098
0.098
0.104
0.094
0.104
0.097
0.105
0.111
0.101
PM-io
90th percentile
NS
2
38.5
38.5
29
31.5
32.5
30
27.5
33.5
37
35.5
weighted annual mean
NS
2
20.5
20.5
17.75
16.15
15.8
16.4
16.6
16.85
18.7
17.3
so2
arithmetic mean
Down
2
0.01
0.01
0.009
0.009
0.008
0.007
0.007
0.006
0.006
0.006
2nd max 24-hour
Down
2
0.047
0.039
0.039
0.041
0.053
0.039
0.033
0.029
0.026
0.03
JANESVILLE-BELOIT, Wl
o3
4th max 8-hour
NS
1
0.076
0.076
0.076
0.063
0.076
0.083
0.082
0.075
0.077
0.08
2nd daily max 1-hour
NS
1
0.091
0.091
0.091
0.083
0.092
0.095
0.101
0.088
0.087
0.095
APPENDIX A • DATA TABLES
203
-------
NATIONALAIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-16. Metropolitan Statistical Area Air Quality Trends, 1990-1999 (continued)
Metropolitan Statistical Area
Trend
#Trend
1990
1991
1992
1993
1994
1995
Sites
JERSEY CITY, NJ
CO
2nd max 8-hour
Down
2
8.45
8.6
7.85
6.6
8.3
7.15
no2
arithmetic mean
Down
1
0.03
0.028
0.028
0.027
0.026
0.026
o3
4th max 8-hour
NS
1
0.106
0.115
0.092
0.103
0.095
0.104
2nd daily max 1-hour
NS
1
0.175
0.136
0.112
0.131
0.118
0.125
PM-io
90th percentile
Down
2
51.5
55
44.5
46.5
56.5
42
weighted annual mean
Down
2
31.2
32.35
26.8
29.05
34
26.5
so2
arithmetic mean
Down
2
0.013
0.012
0.01
0.009
0.009
0.007
2nd max 24-hour
Down
2
0.043
0.035
0.041
0.03
0.036
0.026
JOHNSON CITY-KINGSPORT-BRISTOL, TN-VA
CO
2nd max 8-hour
NS
1
3.4
3.3
3
6.5
3.4
3
no2
arithmetic mean
Down
1
0.019
0.019
0.018
0.017
0.017
0.018
o3
4th max 8-hour
NS
1
0.1
0.078
0.082
0.088
0.083
0.091
2nd daily max 1-hour
NS
1
0.117
0.115
0.103
0.125
0.103
0.114
PM-io
90th percentile
Down
1
44
48
38
46
38
40
weighted annual mean
Down
1
29.3
30.5
24.9
25.2
25
24.7
so2
arithmetic mean
NS
3
0.009
0.009
0.009
0.008
0.009
0.008
2nd max 24-hour
NS
3
0.044
0.044
0.039
0.042
0.045
0.039
JOHNSTOWN, PA
CO
2nd max 8-hour
Down
1
3.7
4.8
4.4
4.2
4.1
3.5
no2
arithmetic mean
Down
1
0.018
0.019
0.018
0.017
0.018
0.015
o3
4th max 8-hour
NS
1
0.08
0.096
0.074
0.083
0.083
0.09
2nd daily max 1-hour
NS
1
0.103
0.113
0.089
0.099
0.094
0.101
so2
arithmetic mean
Down
1
0.014
0.015
0.013
0.015
0.014
0.012
2nd max 24-hour
Down
1
0.046
0.043
0.052
0.049
0.08
0.042
JONESBORO, AR
PM10
90th percentile
NS
1
47
47
41
46
50
50
weighted annual mean
Down
1
26.8
26.7
25.3
25.2
28
27.6
KALAMAZOO-BATTLE CREEK, Ml
PM-io
90th percentile
NS
1
58
56
42
39
44
50
weighted annual mean
Down
1
28.1
29.3
27.1
24
25.9
26
KANSAS CITY, MO-KS
CO
2nd max 8-hour
NS
3
4.433
4
3.9
4.167
4.333
3.333
Pb
max quarterly mean
NS
5
0.03
0.027
0.023
0.02
0.017
0.018
no2
arithmetic mean
NS
3
0.011
0.01
0.01
0.009
0.01
0.01
o3
4th max 8-hour
up
6
0.073
0.079
0.075
0.074
0.079
0.09
2nd daily max 1-hour
up
6
0.097
0.1
0.094
0.097
0.097
0.119
PM10
90th percentile
NS
7
51
51.286
47.143
48.143
46.714
43.714
weighted annual mean
NS
7
31.343
31.614
30.186
30.186
29.886
24.429
so2
arithmetic mean
NS
5
0.003
0.003
0.003
0.003
0.003
0.003
2nd max 24-hour
NS
5
0.022
0.017
0.016
0.02
0.025
0.018
KENOSHA, Wl
o3
4th max 8-hour
NS
2
0.084
0.108
0.085
0.085
0.088
0.103
2nd daily max 1-hour
sl
NS
2
0.106
0.135
0.112
0.114
0.119
0.119
KNOXVILLE, Tl
CO
2nd max 8-hour
Down
1
5.1
4.5
4.5
4.6
4.3
4.1
o3
4th max 8-hour
up
5
0.092
0.083
0.081
0.09
0.088
0.094
2nd daily max 1-hour
up
5
0.11
0.101
0.096
0.11
0.109
0.116
PM-io
90th percentile
Down
8
52.5
52.25
46.75
48.375
48.75
48.75
weighted annual mean
Down
8
31.963
34.225
30.45
30.15
31.725
31.188
so2
arithmetic mean
NS
3
0.006
0.006
0.006
0.006
0.006
0.007
2nd max 24-hour
NS
3
0.03
0.034
0.034
0.037
0.034
0.034
LAKE CHARLES, LA
o3
4th max 8-hour
NS
1
0.085
0.087
0.073
0.077
0.075
0.084
2nd daily max 1-hour
NS
1
0.11
0.121
0.105
0.103
0.095
0.113
LAKELAND-WINTER HAVEN, FL
o3
4th max 8-hour
NS
2
0.072
0.072
0.072
0.082
0.072
0.073
2nd daily max 1-hour
NS
2
0.095
0.095
0.095
0.103
0.088
0.089
so2
arithmetic mean
NS
2
0.004
0.004
0.004
0.004
0.004
0.004
2nd max 24-hour
NS
2
0.018
0.015
0.015
0.019
0.016
0.013
LANCASTER, PA
CO
2nd max 8-hour
NS
1
3.4
2.6
2.6
3
3.8
2.4
Pb
max quarterly mean
NS
1
0.058
0.043
0.038
0.038
0.042
0.04
no2
arithmetic mean
NS
1
0.017
0.018
0.015
0.015
0.019
0.016
o3
4th max 8-hour
NS
1
0.087
0.099
0.086
0.095
0.093
0.102
2nd daily max 1-hour
NS
1
0.101
0.119
0.106
0.118
0.111
0.124
PM-io
90th percentile
NS
1
52
45
41
54
61
55
weighted annual mean
up
1
30.6
29.6
27
30.6
37.5
33.1
so2
arithmetic mean
NS
1
0.006
0.006
0.006
0.007
0.006
0.006
2nd max 24-hour
NS
1
0.028
0.023
0.023
0.026
0.03
0.018
5.8
0.027
0.087
0.12
43
28.35
0.008
0.027
3
0.018
0.083
0.099
37
22.7
0.009
0.044
4.8
0.018
0.083
0.098
0.011
0.034
5.5
0.026
0.105
0.119
42.5
26.75
0.008
0.025
3.5
0.018
0.082
0.111
37
20.8
0.009
0.05
2.7
0.016
0.092
0.104
0.009
0.03
4.85
0.027
0.089
0.118
36
22.85
0.007
0.022
3.4
0.017
0.096
0.115
30
20.7
0.009
0.043
3.1
0.015
0.098
0.124
0.008
0.027
5
0.026
0.106
0.139
36.5
23.3
0.007
0.024
2.8
0.016
0.086
0.106
30
20.7
0.009
0.038
2.8
0.015
0.09
0.107
0.009
0.025
42 40 40 40
25.6 23.7 23.7 23.7
33 38 47 44
22 22.6 26.7 22.5
3.2 3.233 3.7 3.733
0.028 0.1 0.1 0.1
0.012 0.01 0.012 0.012
0.08 0.086 0.087 0.081
0.101 0.107 0.117 0.106
56.429 39.714 44.143 50
33 26.143 27.114 28.657
0.004 0.004 0.003 0.003
0.024 0.013 0.01 0.011
0.084 0.087 0.09 0.097
0.13 0.111 0.121 0.121
3.3
0.091
0.108
48.75
4.8 3.9
0.093 0.104
0.113 0.124
44 41.25
3.8
0.1
0.122
40.75
30.513 26.438 26.075 26.925
0.006 0.006 0.005 0.005
0.037 0.033 0.028 0.035
0.077 0.085 0.09 0.073
0.092 0.114 0.123 0.085
0.07 0.078 0.087 0.078
0.089 0.101 0.104 0.097
0.005 0.005 0.006 0.005
0.019 0.016 0.022 0.016
2.6
0.041
0.017
0.085
0.101
46
30.9
0.005
0.021
3.3
0.041
0.016
0.102
0.133
50
33.6
0.007
0.023
1.9
0.04
0.015
0.101
0.119
50
33.6
0.006
0.02
2.1
0.04
0.015
0.102
0.127
50
33.6
0.005
0.021
204
DATA TABLES • APPENDIX A
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-16. Metropolitan Statistical Area Air Quality Trends, 1990-1999 (continued)
Metropolitan Statistical Area Trend #Trend 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
Sites
LANSING-EAST LANSING, Ml
03 4th max 8-hour
2nd daily max 1-hour
LAS CRUCES, NM
CO 2nd max 8-hour
Pb max quarterly mean
03 4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
S02 arithmetic mean
2nd max 24-hour
LAS VEGAS, NV-AZ
CO 2nd max 8-hour
03 4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
LAWRENCE, MA-NH
03 4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
S02 arithmetic mean
2nd max 24-hour
LAWTON, OK
PM10 90th percentile
weighted annual mean
LEWISTON-AUBURN, ME
PM10 90th percentile
weighted annual mean
S02 arithmetic mean
2nd max 24-hour
LEXINGTON, KY
CO
no2
o3
PM10
so2
LIMA, OH
o3
SO,
2nd max 8-hour
arithmetic mean
4th max 8-hour
2nd daily max 1-hour
90th percentile
weighted annual mean
arithmetic mean
2nd max 24-hour
4th max 8-hour
2nd daily max 1-hour
arithmetic mean
2nd max 24-hour
LINCOLN, NE
CO
o3
2nd max 8-hour
4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
LITTLE ROCK-NORTH LITTLE ROCK, AR
N02 arithmetic mean
03 4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
S02 arithmetic mean
2nd max 24-hour
LONGVIEW-MARSHALL, TX
03 4th max 8-hour
2nd daily max 1-hour
LOS ANGELES-LONG BEACH, CA
CO 2nd max 8-hour
Pb max quarterly mean
N02 arithmetic mean
03 4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
S02 arithmetic mean
2nd max 24-hour
NS
NS
Down
Down
NS
NS
NS
NS
Down
Down
Down
NS
Down
NS
NS
NS
NS
NS
Down
Down
Down
NS
NS
Down
Down
Down
Down
NS
Down
NS
up
Down
Down
NS
NS
NS
NS
Down
Down
NS
NS
NS
NS
NS
NS
NS
NS
NS
Down
Down
Down
up
NS
Down
Down
Down
Down
Down
Down
Down
Down
NS
2
2
1
2
3
3
3
3
2
2
1
3
3
1
1
1
1
1
1
2
2
1
1
1
1
1
1
1
1
3
3
3
3
1
1
1
1
1
1
2
1
1
2
2
1
2
2
4
4
1
1
1
1
13
6
13
14
14
9
9
4
4
0.08 0.083
0.095 0.11
0.08 0.079
0.091 0.096
6.3
0.167
0.07
0.098
60
35.233
0.011
0.056
7.7
0.073
0.101
127
69
0.073
0.091
32
20.6
0.008
6.5 4.9 8.7
0.147 0.126 0.117
0.071 0.07 0.073
0.096 0.099 0.107
52 56.667 47
31.167 31.467 29.767
0.01
0.055
6.9
0.065
0.09
88
58.8
0.086
0.119
30
18.3
0.007
0.009
0.052
6.1
0.076
0.093
76
48.3
0.074
0.086
32
19.1
0.008
0.006
0.055
7.2
0.075
0.096
75
43.1
0.076
0.1
36
18.3
0.008
0.079
0.093
5
0.054
0.074
0.104
55 55.333
32.6 34.267
0.004 0.004
0.023 0.021
0.082
0.096
4.4
0.086
0.074
0.105
0.076 0.078 0.08 0.088
0.087 0.088 0.1 0.1
4.3 4.8 4.2 3.8
0.071 0.075 0.075 0.075
0.075 0.067 0.072 0.074
0.104 0.09 0.1 0.092
50.333 43.333 42 57.667
33.3 26.8 26.767 34.833
0.004 0.003 0.003 0.001
0.03 0.014 0.012 0.005
6.9
0.077
0.091
67
47.4
0.082
0.101
32
15.9
0.006
6.4
0.073
0.088
77
46.7
0.069
0.081
24
13.4
0.006
6.6
0.08
0.094
82
52.5
0.079
0.092
22
14.3
0.005
5.5
0.074
0.088
90
59.7
0.078
0.097
25
14.8
0.005
6.2
0.077
0.087
84
52.4
0.076
0.096
28
15.2
0.006
5.6
0.073
0.086
78
45.1
0.068
0.09
28
15.2
0.005
0.029 0.026 0.027 0.026 0.027 0.025 0.019 0.02 0.021 0.021
51
29.9
41
24.7
0.007
0.027
3.7
0.017
0.078
0.097
48.333
29.4
0.006
0.02
0.084
0.096
0.005
0.026
6.15
0.057
0.067
49
28.65
0.009
0.08
0.099
48.75
28.5
0.003
0.014
0.088
0.13
8.962
0.093
0.041
0.119
0.185
78
48.667
0.003
0.012
43
27.1
41
25.5
35
27
43
27.7
44
25.3
43 49
24 24.3
0.006 0.005 0.007
0.023 0.02 0.025
50
28.5
4.9
0.016
0.074
0.088
46.333
29.133
0.008
0.025
3.8 6.5
0.016 0.017
0.065 0.079
0.08 0.099
40 42
24.9 24.033
0.007 0.007
0.03 0.026
0.09 0.082
0.102
0.09
0.1 0.099
0.006 0.004 0.005
0.021 0.02 0.023
35 37
20.2 19.8
0.006 0.004
0.025 0.02
4.2 3
0.016 0.017
0.088 0.085
0.104 0.103
45.667 40.333
27.933 24.7
0.008 0.006
0.037 0.016
0.089 0.092
0.102 0.106
0.004 0.003
0.036 0.015
44 48 48 48
27.8 26.2 26.2 26.2
31 35 31 31
20 20.6 18.2 18.6
0.004 0.004 0.004 0.004
0.018 0.017 0.019 0.016
3.1 5.2 5.2 5.2
0.014 0.014 0.011 0.013
0.079 0.079 0.087 0.087
0.088 0.096 0.105 0.107
39 37.333 39.333 40
24.033 22.433 23.333 23.033
0.006 0.006 0.006 0.008
0.02 0.016 0.023 0.02
0.092 0.083 0.089 0.093
0.11 0.091 0.102 0.107
0.003 0.003 0.003 0.003
0.015 0.016 0.017 0.013
7.4
0.06
0.067
52.5
29.85
4.45
0.067
0.074
42
25.2
4.25
0.049
0.057
38
26.05
3.95
0.062
0.075
45.5
27.8
4.85
0.06
0.07
44.5
24.75
3.35
0.054
0.06
44
28.15
5
0.054
0.061
38.5
24.25
4.25
0.058
0.068
40
26.1
4.1
0.053
0.062
40
26.1
0.009 0.012 0.009
0.078 0.076 0.076
0.098 0.089 0.096
42.5 47.25 44.25
25.1 27.9 26.925
0.003 0.005 0.006
0.012 0.012 0.017
0.081 0.079 0.093
0.11 0.101 0.114
0.011 0.011
0.076 0.086
0.09 0.106
46.5 50
27.225 29.225
0.003 0.002
0.009 0.008
0.081 0.102
0.104 0.145
0.011 0.01 0.011 0.011
0.077 0.077 0.078 0.083
0.096 0.099 0.097 0.104
40.5 42.25 42.25 42.25
26.2 24.525 24.525 24.525
0.002 0.002 0.002 0.002
0.009 0.006 0.006 0.005
0.082 0.091 0.104 0.105
0.106 0.124 0.129 0.134
0.102
0.041
0.125
0.194
79.556
52.522
0.003
0.013
7.815
0.079
0.038
0.129
0.2
64.111
41.078
0.004
0.015
6.808
0.064
0.036
0.117
0.174
65.333
40.467
0.003
0.011
8.015
0.061
0.039
0.113
0.169
59.111
39.144
0.003
0.008
7.469
0.049
0.038
0.105
0.152
63.556
39.156
0.003
0.008
6.846
0.046
0.035
0.101
0.142
60.667
37.967
0.003
0.008
6.562
0.052
0.033
0.091
0.124
56.556
38.556
0.003
0.007
6.069 5.8
0.038 0.061
0.033 0.035
0.098 0.077
0.147 0.111
54.778 60.333
33.411 39.1
0.003 0.003
0.009 0.01
APPENDIX A • DATA TABLES
205
-------
NATIONALAIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-16. Metropolitan Statistical Area Air Quality Trends, 1990-1999 (continued)
Metropolitan Statistical Area
Trend
#Trend
1990
1991
1992
1993
1994
1995
1996
1997
1998 1999
Sites
LOUISVILLE, KY-IN
CO
2nd max 8-hour
Down
4
5.85
5.85
5.15
5.35
5.875
4.4
3.9
4.95
4.375
3.925
no2
arithmetic mean
NS
1
0.012
0.012
0.012
0.013
0.014
0.012
0.013
0.013
0.012
0.014
o3
4th max 8-hour
up
5
0.079
0.086
0.071
0.091
0.092
0.09
0.087
0.089
0.096
0.094
2nd daily max 1-hour
NS
5
0.107
0.108
0.091
0.123
0.116
0.116
0.109
0.12
0.121
0.112
PM-io
90th percentile
Down
6
54.667
49.833
47.5
50.833
47 46.167
43.667
48.167
41.833
42.5
weighted annual mean
Down
6
32.767
32.25
30.3
29.117
30.283
28.65
26.483
28.717
26.333
25
so2
arithmetic mean
Down
4
0.01
0.01
0.009
0.01
0.01
0.008
0.007
0.007
0.007
0.008
2nd max 24-hour
Down
4
0.041
0.037
0.034
0.035
0.04
0.028
0.031
0.031
0.033
0.026
LOWELL, MA-NH
CO
2nd max 8-hour
Down
1
7.3
5.8
5.9
5.1
6.5
7.8
4.5
3.6
3.4
4.2
LUBBOCK, TX
PM-io
90th percentile
Down
1
36
39
34
30
33
34
34
27
27
27
weighted annual mean
Down
1
23.8
25.3
22.1
19.9
23
20.8
21.7
16.6
16.6
16.6
LYNCHBURG, VA
PM10
90th percentile
NS
1
43
41
39
44
33
49
36
37
33
33
weighted annual mean
Down
1
24.3
27.5
23.5
25.5
23.2
23.8
22.5
23
20.8
20.8
MADISON, Wl
o3
4th max 8-hour
NS
1
0.079
0.079
0.079
0.066
0.071
0.08
0.079
0.079
0.076
0.085
2nd daily max 1-hour
NS
1
0.094
0.094
0.094
0.079
0.082
0.1
0.094
0.088
0.089
0.098
PM-io
90th percentile
NS
2
37
38
35
36.5
32.5
42
30.5
33.5
36.5
37
weighted annual mean
NS
2
22.95
23.75
22
20.15
21.3
22.15
20.05
20.15
23.35
20.55
MANCHESTER, NH
PM10
90th percentile
Down
2
33.5
37.5
31
36.5
33.5
26
28
28.5
26.5
27
weighted annual mean
Down
2
19.55
19.9
18.2
17.95
15.25
14.25
16
18.55
15.05
15.6
MANSFIELD, OH
PM10
90th percentile
NS
1
42
40
39
44
49
42
40
39
41
39
weighted annual mean
Down
1
27.1
26.7
26.4
27.7
29.2
24.7
24.3
23.3
23.8
22.6
MEDFORD-ASHLAND, OR
CO
2nd max 8-hour
Down
1
8.2
8.1
6.4
6.9
6.2
5.3
6.4
5.7
5.2
5.7
o3
4th max 8-hour
NS
1
0.081
0.081
0.081
0.066
0.068
0.071
0.075
0.063
0.085
0.065
2nd daily max 1-hour
NS
1
0.112
0.112
0.112
0.082
0.087
0.091
0.101
0.074
0.117
0.077
PM-io
90th percentile
Down
4
66.75
62.25
51.75
52.5
46.75
36
35
36.25
32.5
46.75
weighted annual mean
Down
4
35.35
34.35
30.675
29.725
27.95
21.75
20.975
22.775
20.925
23.575
MELBOURNE-TITUSVILLE-PALM BAY, FL
o3
4th max 8-hour
NS
2
0.074
0.068
0.075
0.073
0.073
0.066
0.068
0.073
0.081
0.074
2nd daily max 1-hour
NS
2
0.084
0.085
0.084
0.087
0.088
0.08
0.087
0.086
0.092
0.087
PM-io
90th percentile
NS
2
29.5
29.5
29.5
27
23.5
23
25
27.5
32
27
weighted annual mean
NS
2
16.55
16.55
16.55
17.65
16.5
15.15
16.85
17.6
18.2
17.6
MEMPHIS, TN-AR-MS
CO
2nd max 8-hour
Down
5
7.46
6.14
7.66
7.64
7.28
5.96
5.28
4.96
4.86
4.68
Pb
max quarterly mean
NS
4
1.041
0.785
1.003
1.045
1.033
0.646
1.044
0.593
0.933
0.249
no2
arithmetic mean
up
1
0.023
0.024
0.026
0.026
0.027
0.027
0.024
0.028
0.029
0.025
o3
4th max 8-hour
up
4
0.088
0.085
0.08
0.084
0.085
0.095
0.094
0.087
0.093
0.097
2nd daily max 1-hour
up
4
0.113
0.108
0.102
0.108
0.108
0.125
0.124
0.118
0.116
0.127
PM10
90th percentile
Down
2
50
45
43.5
49
43
44.5
40
43.5
40.5
40
weighted annual mean
Down
2
30.6
26.95
28.4
28.5
26.65
27.45
27.45
26
24.65
24.35
so2
arithmetic mean
Down
1
0.009
0.008
0.009
0.007
0.005
0.005
0.004
0.004
0.004
0.004
2nd max 24-hour
Down
1
0.027
0.024
0.03
0.031
0.025
0.019
0.012
0.012
0.012
0.012
MERCED, CA
no2
arithmetic mean
Down
1
0.015
0.015
0.015
0.015
0.013
0.012
0.012
0.013
0.011
0.012
o3
4th max 8-hour
NS
1
0.102
0.102
0.102
0.096
0.097
0.107
0.102
0.074
0.112
0.105
2nd daily max 1-hour
NS
1
0.12
0.12
0.12
0.12
0.119
0.13
0.124
0.09
0.14
0.125
MIAMI, FL
CO
2nd max 8-hour
Down
2
5.95
7.2
6.2
5.25
4.4
4.9
4.45
3.8
3.1
3.95
no2
arithmetic mean
NS
2
0.011
0.011
0.011
0.012
0.01
0.011
0.011
0.012
0.011
0.012
o3
4th max 8-hour
NS
4
0.067
0.06
0.071
0.075
0.07
0.07
0.069
0.072
0.08
0.074
2nd daily max 1-hour
NS
4
0.098
0.091
0.095
0.101
0.093
0.094
0.092
0.098
0.099
0.101
PM-io
90th percentile
Down
4
38
38
39.5
36.25
34.75
33.75
38.25
30.25
35.25
31.75
weighted annual mean
Down
4
27
25.725
25.95
26.85
25.075
25.05
25.7
23
25.75
23.1
so2
arithmetic mean
NS
1
0.001
0.001
0.001
0.001
0.001
0.002
0.002
0.001
0.001
0.001
2nd max 24-hour
NS
1
0.003
0.003
0.005
0.004
0.004
0.004
0.005
0.004
0.004
0.003
MIDDLESEX-SOMERSET-HUNTERDON, NJ
CO
2nd max 8-hour
Down
1
5.4
4.2
3.9
3.7
4.3
5.3
3.3
3.8
3
3.2
Pb
max quarterly mean
NS
1
0.302
1.148
1.215
0.333
0.123
0.067
0.061
0.079
0.08
0.182
o3
4th max 8-hour
NS
1
0.11
0.109
0.094
0.102
0.094
0.102
0.089
0.103
0.096
0.109
2nd daily max 1-hour
NS
1
0.136
0.122
0.119
0.118
0.112
0.115
0.108
0.12
0.118
0.133
so2
arithmetic mean
Down
1
0.007
0.007
0.006
0.005
0.005
0.004
0.005
0.005
0.005
0.005
2nd max 24-hour
Down
1
0.032
0.025
0.026
0.018
0.028
0.018
0.024
0.019
0.018
0.016
206 DATA TABLES • APPENDIX A
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-16. Metropolitan Statistical Area Air Quality Trends, 1990-1999 (continued)
Metropolitan Statistical Area Trend #Trend 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
Sites
MILWAUKEE-WAUKESHA, Wl
CO
2nd max 8-hour
Down
5
4.48
3.72
3.24
Pb
max quarterly mean
Down
1
0.081
0.055
0.047
NO,
arithmetic mean
Down
1
0.019
0.018
0.018
o3
4th max 8-hour
NS
8
0.084
0.094
0.078
2nd daily max 1-hour
NS
8
0.113
0.136
0.096
PM-io
90th percentile
Down
4
57.25
48.75
41
weighted annual mean
Down
4
33.2
29.3
25.775
so2
arithmetic mean
NS
1
0.006
0.005
0.004
2nd max 24-hour
NS
1
0.04
0.029
0.023
MINNEAPOLIS-ST. PAUL, MN-WI
CO
2nd max 8-hour
Down
3
6.533
7.167
5.867
Pb
max quarterly mean
Down
4
0.588
0.246
0.197
no2
arithmetic mean
NS
1
0.017
0.016
0.016
o3
4th max 8-hour
NS
4
0.068
0.07
0.074
2nd daily max 1-hour
NS
4
0.087
0.081
0.086
PM-io
90th percentile
NS
7
43.429
42.286
37.286
weighted annual mean
NS
7
27.871
26.443
22.843
so2
arithmetic mean
Down
6
0.004
0.005
0.004
2nd max 24-hour
Down
6
0.025
0.027
0.025
MOBILE, AL
o3
4th max 8-hour
NS
2
0.081
0.054
0.075
2nd daily max 1-hour
NS
2
0.105
0.075
0.098
PM10
90th percentile
Down
4
49.5
48.5
51.25
weighted annual mean
Down
4
30.65
31.85
33.7
so2
arithmetic mean
NS
1
0.008
0.009
0.01
2nd max 24-hour
NS
1
0.038
0.05
0.054
MODESTO, CA
CO
2nd max 8-hour
Down
2
7.3
6.75
5
Pb
max quarterly mean
Down
1
0.036
0.036
0.019
no2
arithmetic mean
Down
2
0.023
0.023
0.021
o3
4th max 8-hour
NS
2
0.096
0.091
0.089
2nd daily max 1-hour
NS
2
0.115
0.11
0.11
PM-io
90th percentile
Down
2
85
101
68.5
weighted annual mean
Down
2
43.85
48.4
39.45
MONMOUTH-OCEAN, NJ
CO
2nd max 8-hour
Down
2
5.7
5.45
4.65
o3
4th max 8-hour
NS
2
0.098
0.101
0.09
2nd daily max 1-hour
NS
2
0.134
0.14
0.133
MONTGOMERY, AL
o3
4th max 8-hour
NS
1
0.078
0.067
0.076
2nd daily max 1-hour
NS
1
0.097
0.088
0.095
PM-io
90th percentile
NS
1
41
44
39
weighted annual mean
NS
1
26.9
25.8
24.2
MYRTLE BEACH, SC
Pb
max quarterly mean
NS
1
0.013
0.013
0.011
NASHUA, NH
CO
2nd max 8-hour
Down
2
7.05
6.85
6.8
no2
arithmetic mean
NS
1
0.016
0.016
0.015
o3
4th max 8-hour
NS
2
0.08
0.089
0.084
2nd daily max 1-hour
NS
2
0.096
0.103
0.098
PM10
90th percentile
Down
3
32
34
29
weighted annual mean
Down
3
17.7
19.067
16.867
so2
arithmetic mean
NS
3
0.007
0.005
0.006
2nd max 24-hour
Down
3
0.036
0.024
0.025
NASHVILLE, TN
CO
2nd max 8-hour
Down
3
5.933
5
5.533
Pb
max quarterly mean
Down
5
1.257
1.064
0.989
no2
arithmetic mean
NS
1
0.012
0.01
0.014
o3
4th max 8-hour
up
6
0.089
0.08
0.075
2nd daily max 1-hour
up
6
0.113
0.099
0.098
PM-io
90th percentile
Down
6
56.833
51.667
47.833
weighted annual mean
Down
6
36.367
34.75
30.55
so2
arithmetic mean
Down
2
0.013
0.012
0.008
2nd max 24-hour
NS
2
0.08
0.078
0.028
NASSAU-SUFFOLK, NY
CO
2nd max 8-hour
Down
1
7.2
6.6
5.6
no2
arithmetic mean
Down
1
0.028
0.029
0.026
o3
4th max 8-hour
NS
2
0.1
0.1
0.09
2nd daily max 1-hour
NS
2
0.132
0.147
0.123
PM-io
90th percentile
Down
2
53.5
53.5
38
weighted annual mean
Down
2
26.85
26.85
22.25
so2
arithmetic mean
Down
2
0.009
0.009
0.008
2nd max 24-hour
Down
2
0.045
0.039
0.039
4.04 4.5 3.04
0.035 0.032 0.048
0.017 0.017 0.017
0.076 0.081 0.096
0.097 0.117 0.114
44.5 42.25 49
26.1 27.525 26.55
0.003 0.004 0.004
0.018 0.032 0.025
5.233
0.093
0.018
0.058
0.074
34.571
22.057
0.003
0.02
0.071
0.09
51.25
32.4
0.01
0.066
4.65
0.018
0.02
0.093
0.12
72
40.15
5.3
0.099
0.129
0.085
0.113
34
22.8
6.4
0.052
0.019
0.07
0.08
35.286
21.829
0.003
0.017
0.071
0.088
51
31.4
0.011
0.052
5.1
0.019
0.02
0.09
0.112
54
37
4.9
0.092
0.117
0.078
0.101
36
25
5.967
0.181
0.017
0.076
0.101
39.571
22.886
0.003
0.015
0.077
0.108
42.75
28.8
0.009
0.053
4.2
0.012
0.019
0.099
0.125
68
34.3
3.75
0.115
0.148
0.088
0.102
43
26.1
1.9
0.032
0.017
0.083
0.105
37.5
25
0.004
0.028
5.133
0.092
0.019
0.068
0.086
35.857
22.6
0.003
0.016
0.077
0.102
39.75
24.6
0.009
0.07
4.3
0.01
0.019
0.096
0.124
40.5
28.35
4.4
0.095
0.121
0.076
0.102
37
22.5
1.98
0.03
0.016
0.083
0.117
38.25
24.275
0.004
0.028
4.5
0.072
0.017
0.073
0.085
34.286
22.271
0.003
0.015
2.08
0.03
0.016
0.082
0.109
41.25
26.85
0.004
0.022
4.933
0.05
0.018
0.071
0.089
39.429
23.843
0.002
0.013
0.088
0.107
46.75
26.35 29.975
0.008 0.009
0.049 0.073
0.076
0.107
44.5
1.94
0.03
0.016
0.091
0.111
40.5
24.05
0.004
0.024
4.033
0.127
0.016
0.073
0.083
39.429
24.257
0.002
0.014
0.082
0.107
38
24.5
0.008
0.041
3.7
0.011
0.019
0.086
0.11
47.5
29.6
3.65
0.104
0.141
0.07
0.087
40
23.9
4.3 4.85
0.019
0.103
0.14
37.5
22.55
3
0.099
0.132
0.091
0.116
39
27.8
0.02
0.089
0.109
37.5
22.55
3.3
0.1
0.127
0.077
0.096
38
23.9
0.007 0.005 0.007 0.003 0.006 0.01 0.009
5.15
0.016
0.085
0.113
0.006
0.022
6.4
0.01
5.6
0.026
0.097
0.13
41.5
23.05
0.008
0.033
7.45
0.015
0.081
0.099
31
14.133
0.006
0.028
5.433
0.933
0.02
0.083
0.103
51
30.217
0.007
0.041
5.4
0.028
0.09
0.121
38.5
22.65
0.007
0.037
6.75
0.014
0.083
0.102
25
13.467
0.005
0.023
4.833
1.784
0.014
0.086
0.103
50
30.733
0.005
0.025
5
0.025
0.109
0.141
32.5
19.1
0.005
0.03
7.7
0.019
0.083
0.101
28.667
15.733
0.005
0.021
3.867
0.574
0.012
0.087
0.108
43.167
28.383
0.006
0.049
4.9
0.026
0.089
0.118
28.5
18.05
0.007
0.028
4.65
0.016
0.088
0.109
29
17.267
0.006
0.025
4.733
0.633
0.012
0.09
0.112
46.667
28.183
0.006
0.059
4.7
0.025
0.102
0.133
33.5
20.25
0.006
0.029
4.45
0.015
0.073
0.089
27.333
15.667
0.005
0.019
4.367
0.74
0.011
0.091
0.113
44.833
28.067
0.005
0.035
4
0.022
0.093
0.126
30
18.4
0.006
0.028
4.4
0.015
0.076
0.089
26.333
15.533
0.005
0.019
4.433
0.502
0.019
0.095
0.119
44
27.217
0.004
0.029
4.5
0.024
0.099
0.13
28
17.3
0.007
0.032
APPENDIX A • DATA TABLES
207
-------
NATIONALAIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-16. Metropolitan Statistical Area Air Quality Trends, 1990-1999 (continued)
Metropolitan Statistical Area
Trend
#Trend
Sites
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
NEW BEDFORD, MA
o3
4th max 8-hour
NS
2nd daily max 1-hour
NS
PM10
90th percentile
NS
weighted annual mean
Down
NEW HAVEN-MERIDEN, CT
no2
arithmetic mean
NS
o3
4th max 8-hour
NS
2nd daily max 1-hour
NS
PM-io
90th percentile
Down
weighted annual mean
Down
so2
arithmetic mean
Down
2nd max 24-hour
Down
NEW LONDON-NORWICH, CT-RI
o3
4th max 8-hour
NS
2nd daily max 1-hour
NS
PM-io
90th percentile
Down
weighted annual mean
Down
so2
arithmetic mean
Down
2nd max 24-hour
Down
NEW ORLEANS, LA
CO
2nd max 8-hour
Down
Pb
max quarterly mean
NS
no2
arithmetic mean
NS
o3
4th max 8-hour
up
2nd daily max 1-hour
NS
PM-io
90th percentile
Down
weighted annual mean
NS
so2
arithmetic mean
NS
2nd max 24-hour
NS
NEW YORK, NY
CO
2nd max 8-hour
Down
Pb
max quarterly mean
NS
no2
arithmetic mean
Down
o3
4th max 8-hour
NS
2nd daily max 1-hour
NS
PM-io
90th percentile
NS
weighted annual mean
Down
so2
arithmetic mean
Down
2nd max 24-hour
Down
NEWARK, NJ
CO
2nd max 8-hour
Down
no2
arithmetic mean
NS
o3
4th max 8-hour
NS
2nd daily max 1-hour
NS
PM-io
90th percentile
NS
weighted annual mean
NS
so2
arithmetic mean
Down
2nd max 24-hour
Down
NEWBURGH, NY-PA
Pb
max quarterly mean
Down
NORFOLK-VIRGINIA BEACH-NEWPORT NEWS,VA-N
CO
2nd max 8-hour
NS
no2
arithmetic mean
NS
o3
4th max 8-hour
NS
2nd daily max 1-hour
NS
PM-io
90th percentile
NS
weighted annual mean
NS
so2
arithmetic mean
Down
2nd max 24-hour
Down
OAKLAND, CA
CO
2nd max 8-hour
Down
Pb
max quarterly mean
Down
no2
arithmetic mean
Down
o3
4th max 8-hour
NS
2nd daily max 1-hour
NS
PM-io
90th percentile
Down
weighted annual mean
Down
so2
arithmetic mean
NS
2nd max 24-hour
NS
1
1
1
1
1
2
2
6
6
2
2
1
1
2
2
1
1
2
1
2
6
6
1
1
1
1
5
1
2
5
5
12
12
7
7
3
4
2
2
3
3
4
4
0.099
0.126
34
23
0.027
0.1
0.129
48.833
30.033
0.01
0.045
0.105
0.158
34.5
20.65
0.008
0.029
4.85
0.049
0.016
0.079
0.104
44
27.2
0.003
0.013
7.1
0.164
0.043
0.098
0.13
51.917
30.6
0.014
0.054
7.1
0.029
0.096
0.127
55
30.633
0.01
0.04
0.101 0.087
0.132 0.109
35 29
20.4 17.4
0.073
0.088
24
16.8
0.028 0.025 0.027
0.116 0.084 0.094
0.161 0.115 0.137
57.667 46 51.167
33.483 26.733 28.583
0.01 0.009 0.008
0.055 0.042 0.038
0.107
0.135
40
23.55
0.007
0.027
4.15
0.049
0.015
0.072
0.1
48
26.3
0.005
0.028
6.7
0.124
0.043
0.105
0.141
46.167
29.225
0.014
0.048
0.088
0.12
32
19.75
0.006
0.025
5.35
0.049
0.017
0.077
0.101
39
26.6
0.005
0.019
6.1
0.106
0.037
0.078
0.116
40.5
26.25 25.433
0.013 0.012
0.051 0.039
0.099
0.126
30.5
18.25
0.006
0.019
5.1
0.073
0.016
0.079
0.104
42
24.7
0.006
0.025
5.26
0.163
0.04
0.087
0.115
41
8.333
0.028
0.105
0.125
52.333
5.633
0.03
0.085
0.105
44
29.9 28.733 30.133
0.01 0.009 0.007
0.035 0.04 0.025
4.933
0.028
0.092
0.115
52
0.077
0.096
37
19.1
0.03
0.088
0.137
51.833
0.107
0.138
21
14.3
0.025
0.105
0.144
40.5
29.067 23.617
0.008 0.006
0.049 0.031
0.093
0.118
38.5
22.1
0.005
0.029
4.6
0.12
0.015
0.082
0.11
40
25.3
0.008
0.027
5.94
0.14
0.042
0.092
0.12
46.583
27.925
0.013
0.054
7.667
0.03
0.09
0.114
57.333
34.567 27.833
0.008 0.006
0.033 0.025
0.092
0.118
27
16.1
0.092
0.123
29
17.8
0.083
0.101
25
16
0.024 0.027
0.099 0.088
0.136 0.124
36.167 35.667 36.167
22.217 22.567 23.117
0.005 0.005
0.028 0.028
0.026
0.085
0.113
0.006
0.027
0.101
0.14
28.5
17.2
0.005
0.017
3.55
0.411
0.016
0.083
0.11
37
24.3
0.007
0.022
6.52
0.124
0.039
0.096
0.122
40.583
25.325
0.01
0.038
6.033
0.028
0.105
0.12
46
0.095
0.121
30.5
18.8
0.005
0.016
0.104
0.15
28.5
18.3
0.004
0.022
3.95 3.25
0.093 0.053
0.015 0.014
0.08 0.078
0.103
31
22.3
0.1
36
25.2
0.006 0.005
0.035 0.017
4.56
0.156
0.039
0.088
0.117
39.583
26.133
0.01
0.04
3.64
0.155
0.038
0.103
0.131
40.833
25.933
0.009
0.033
0.083
0.116
27.5
17.35
0.004
0.018
3.15
0.114
0.016
0.081
0.108
36
25.2
0.004
0.026
3.72
0.137
0.038
0.09
0.116
41.417
25.125
0.008
0.03
0.098
0.125
25
16
0.026
0.098
0.136
37
22.8
0.006
0.026
0.096
0.127
25
16.1
0.004
0.018
3.2
0.077
0.017
0.085
0.105
36
25.2
0.005
0.023
4.12
0.095
0.037
0.101
0.134
40.417
23.85
0.009
0.032
4.6 3.667
0.028 0.029
0.097 0.092
0.11 0.116
48.667 48.667 44.667 47.333
31.4 30.933 27.8 29.6
0.006 0.006
0.023 0.021
5.067
0.029
0.087
0.115
0.006
0.027
4.867
0.029
0.1
0.121
0.006
0.021
1.01 0.655 0.577 0.344 0.081 0.079 0.059 0.198 0.1 0.198
4.533
0.019
0.085
0.104
37.5
24.5
0.007
0.025
4.92
0.073
0.021
0.062
0.097
58.667
32.267
0.002
0.011
5.133
0.02
0.083
0.103
43
25.15
0.007
0.022
4.333 4.967
0.02 0.021
0.086 0.094
0.125 0.119
36 41
21.6 23.45
0.006 0.007
0.024 0.026
4.98 4.14 3.54
0.061 0.022 0.024
0.022 0.02 0.02
0.065 0.067 0.069
0.1 0.097 0.106
64.667 41.333 39
34.1 26.767 23.733
0.002 0.002 0.002
0.01 0.009 0.01
5.367
0.019
0.081
0.101
30.5
19.8
0.007
0.024
3.72
0.017
0.02
0.065
0.099
38
23.8
0.002
0.007
4.267
0.018
0.083
0.105
34
19.7
0.006
0.022
2.82
0.028
0.019
0.082
0.133
36.667
21.167
0.002
0.007
4.3
0.018
0.077
0.094
33
20.8
0.006
0.022
2.96
0.012
0.018
0.073
0.107
34.667
21.967
0.002
0.007
4.033
0.019
0.092
0.111
35.5
21.6
0.006
0.025
3
0.008
0.017
0.06
0.094
32.667
21.733
0.002
0.008
4.633
0.019
0.088
0.103
36
21.85
0.006
0.02
2.98
0.008
0.018
0.069
0.104
28.667
19.033
0.002
0.009
3.767
0.017
0.094
0.125
33.5
20.45
0.006
0.018
3.2
0.008
0.019
0.073
0.106
32.667
21.267
0.002
0.013
208
DATA TABLES • APPENDIX A
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-16. Metropolitan Statistical Area Air Quality Trends, 1990-1999 (continued)
Metropolitan Statistical Area Trend #Trend 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
Sites
OKLAHOMA CITY, OK
CO
Pb
no2
o3
PM10
OLYMPIA, WA
2nd max 8-hour
max quarterly mean
arithmetic mean
4th max 8-hour
2nd daily max 1-hour
90th percentile
weighted annual mean
Down
Down
NS
up
NS
NS
NS
4.5
0.036
0.012
0.075
0.098
36
21.525
3.9
0.039
0.011
0.078
0.099
34.5
22.2
4.3
0.029
0.011
0.073
0.093
34
5.15
0.017
0.011
0.071
0.092
34.25
4.25
3.8 3.95
3.35 3.35
0.013 0.017 0.008 0.001 0.001 0.001
0.012 0.012 0.012 0.013 0.012 0.012
0.078 0.085 0.078 0.08 0.086 0.081
0.093 0.11 0.094 0.098 0.107 0.092
33.75 37.5 39 38.5 38.5 38.5
21.65 20.875 21.05 21.425 24.225 21.85 21.85 21.85
PM10
90th percentile
Down
1
44
43
42
49
30
35
30
36
22
25
weighted annual mean
Down
1
23.6
25
23.8
23.8
17.4
17.2
15.6
16.4
14.2
14.4
OMAHA, NE-IA
CO
2nd max 8-hour
NS
2
5.15
5.8
5.9
5.3
3.95
5.5
4.85
4.2
5.3
5.75
Pb
max quarterly mean
NS
6
0.841
0.752
1.329
1.29
1.684
1.032
1.003
0.348
0.046
0.101
o3
4th max 8-hour
NS
3
0.06
0.064
0.063
0.05
0.06
0.063
0.056
0.062
0.064
0.072
2nd daily max 1-hour
NS
3
0.069
0.077
0.076
0.059
0.073
0.077
0.068
0.072
0.077
0.088
PM10
90th percentile
NS
7
63.286
58.571
62.429
47.857
51.857
51.857
49.143
51.571
60.429
71
weighted annual mean
NS
7
37.157
36.357 35.529
31
32.957
29.586
32.7
32.714
34.486 39.029
ORANGE COUNTY, CA
CO
2nd max 8-hour
Down
4
8.275
6.95
7.475
5.8
7.325
5.725
5.75
4.775
5
4.65
no2
arithmetic mean
Down
3
0.039
0.038
0.034
0.032
0.034
0.033
0.029
0.028
0.029
0.029
o3
4th max 8-hour
Down
4
0.106
0.099
0.105
0.094
0.097
0.084
0.082
0.073
0.084
0.069
2nd daily max 1-hour
Down
4
0.173
0.18
0.17
0.15
0.155
0.12
0.12
0.108
0.138
0.111
PM10
90th percentile
NS
2
75
67.5
53
57
53.5
68
46.5
50
52
69
weighted annual mean
NS
2
45.45
41.25
37.2
36.3
35.6
40.55
32.65
37
33.3
40.5
so2
arithmetic mean
NS
1
0.002
0.002
0.002
0.002
0.002
0.003
0.001
0.001
0.002
0.002
2nd max 24-hour
Down
1
0.008
0.007
0.008
0.006
0.005
0.005
0.004
0.006
0.005
0.005
ORLANDO, FL
CO
2nd max 8-hour
Down
2
4.45
3.55
3.85
3.8
3.6
3.3
3.25
3.55
2.95
2.75
no2
arithmetic mean
NS
1
0.012
0.012
0.011
0.012
0.011
0.01
0.013
0.013
0.011
0.012
o3
4th max 8-hour
NS
3
0.081
0.07
0.081
0.081
0.079
0.075
0.074
0.078
0.087
0.081
2nd daily max 1-hour
NS
3
0.112
0.093
0.1
0.098
0.098
0.097
0.097
0.1
0.106
0.1
PM10
90th percentile
NS
5
35.2
33.8
34.6
31.2
29.4
30
31.8
30.8
34.4
32.4
weighted annual mean
NS
5
24.5
24.56
22.8
21.68
21.08
20.14
21.36
21.84
22.98
22.22
so2
arithmetic mean
NS
1
0.002
0.002
0.002
0.002
0.002
0.002
0.002
0.002
0.002
0.002
2nd max 24-hour
NS
1
0.011
0.007
0.007
0.011
0.012
0.006
0.008
0.006
0.007
0.007
OWENSBORO, KY
no2
arithmetic mean
NS
1
0.011
0.011
0.012
0.012
0.012
0.013
0.011
0.012
0.013
0.011
o3
4th max 8-hour
NS
1
0.086
0.075
0.075
0.081
0.092
0.088
0.086
0.087
0.086
0.09
2nd daily max 1-hour
NS
1
0.11
0.09
0.085
0.106
0.107
0.109
0.107
0.108
0.11
0.102
PM10
90th percentile
NS
3
45.333
44.667
45
44.667
44.667
48.333
41.333
42
43.333
43
weighted annual mean
Down
3
29.033
29.233
26.7
25.1
28.7
27
24.167
24.267
24.633
24.3
so2
arithmetic mean
Down
1
0.009
0.009
0.009
0.009
0.009
0.007
0.007
0.007
0.007
0.006
2nd max 24-hour
Down
1
0.038
0.044
0.053
0.05
0.035
0.028
0.02
0.027
0.023
0.024
PARKERSBURG-MARIETTA, WV-OH
Pb
max quarterly mean
NS
1
0.019
0.015
0.024
0.017
0.014
0.019
0.023
0.011
0.011
0.011
o3
4th max 8-hour
NS
2
0.084
0.102
0.08
0.092
0.095
0.097
0.088
0.085
0.093
0.096
2nd daily max 1-hour
NS
2
0.113
0.12
0.156
0.114
0.113
0.117
0.107
0.106
0.113
0.121
PM10
90th percentile
NS
1
46
46
46
51
51
40
34
39
44
36
weighted annual mean
Down
1
27.2
27.2
27.2
29.2
27.3
25.3
22.7
23.1
23.1
20.5
so2
arithmetic mean
NS
1
0.014
0.014
0.014
0.014
0.017
0.01
0.01
0.01
0.013
0.013
2nd max 24-hour
NS
1
0.064
0.06
0.059
0.065
0.084
0.041
0.046
0.052
0.089
0.058
PENSACOLA, FL
o3
4th max 8-hour
NS
2
0.088
0.075
0.087
0.08
0.085
0.083
0.079
0.085
0.095
0.084
2nd daily max 1-hour
NS
2
0.112
0.103
0.104
0.102
0.108
0.117
0.098
0.11
0.121
0.102
so2
arithmetic mean
Down
2
0.008
0.007
0.008
0.006
0.005
0.003
0.004
0.004
0.004
0.004
2nd max 24-hour
Down
2
0.074
0.063
0.063
0.047
0.045
0.023
0.024
0.031
0.023
0.024
PEORIA-PEKIN, IL
CO
2nd max 8-hour
Down
1
7.4
6.3
7.2
7.3
5.7
5.6
4.6
4.7
5.8
4.6
Pb
max quarterly mean
Down
1
0.035
0.021
0.024
0.032
0.019
0.026
0.024
0.019
0.017
0.017
o3
4th max 8-hour
NS
2
0.071
0.079
0.075
0.064
0.075
0.082
0.081
0.072
0.076
0.082
2nd daily max 1-hour
NS
2
0.084
0.096
0.09
0.079
0.089
0.094
0.089
0.086
0.085
0.098
PM10
90th percentile
Down
2
45
42.5
44.5
36.5
40.5
40
33.5
40
40.5
39.5
weighted annual mean
NS
2
27.45
26.35
28.25
21.55
23.3
21.55
22.35
26.45
25.9
24.65
so2
arithmetic mean
NS
2
0.007
0.008
0.007
0.007
0.007
0.007
0.007
0.007
0.007
0.006
2nd max 24-hour
Down
2
0.055
0.065
0.043
0.039
0.05
0.084
0.045
0.042
0.041
0.036
APPENDIX A • DATA TABLES
209
-------
NATIONALAIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-16. Metropolitan Statistical Area Air Quality Trends, 1990-1999 (continued)
Metropolitan Statistical Area
Trend
#Trend
Sites
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
PHILADELPHIA, PA-NJ
CO 2nd max 8-hour
Pb max quarterly mean
N02 arithmetic mean
03 4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
S02 arithmetic mean
2nd max 24-hour
PHOENIX-MESA, AZ
CO 2nd max 8-hour
Pb max quarterly mean
03 4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
S02 arithmetic mean
2nd max 24-hour
PINE BLUFF, AR
PM10 90th percentile
weighted annual mean
PITTSBURGH, PA
CO 2nd max 8-hour
Pb max quarterly mean
N02 arithmetic mean
03 4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
S02 arithmetic mean
2nd max 24-hour
PITTSFIELD, MA
POCATELLO, ID
PMin
4th max 8-hour
2nd daily max 1-hour
PONCE, PR
PM10
90th percentile
weighted annual mean
90th percentile
weighted annual mean
PORTLAND, ME
03 4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
S02 arithmetic mean
2nd max 24-hour
PORTLAND-VANCOUVER, OR-WA
CO 2nd max 8-hour
03 4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
PORTSMOUTH-ROCHESTER, NH-ME
N02 arithmetic mean
03 4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
S02 arithmetic mean
2nd max 24-hour
PROVIDENCE-FALL RIVER-WARWICK, RI-MA
CO 2nd max 8-hour
N02 arithmetic mean
03 4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
S02 arithmetic mean
2nd max 24-hour
Down
NS
NS
NS
NS
Down
Down
Down
Down
Down
Down
NS
NS
NS
NS
NS
NS
up
up
Down
Down
Down
NS
up
Down
Down
Down
Down
Down
NS
Down
Down
NS
NS
NS
NS
NS
NS
Down
NS
Down
NS
NS
Down
Down
Down
NS
NS
Down
Down
Down
Down
Down
NS
NS
NS
Down
Down
Down
Down
9
10
7
7
7
13
13
19
19
16
16
1
1
4
4
1
1
1
1
2
2
1
1
2
4
4
6
6
1
2
2
2
2
1
1
1
1
2
2
3
3
3
3
4.933
0.535
0.025
0.103
0.132
54.143
31.286
0.01
0.039
6.65
0.085
0.079
0.109
67
42.925
0.003
0.011
39
20.9
5.56
0.088
0.023
0.081
0.1
60.842
20.174
0.016
0.071
0.092
0.105
54
32.825
47
29.7
0.092
0.125
39
25.05
0.01
0.034
8.45
0.082
0.116
42
25.1
0.015
0.081
0.111
33
19.8
0.007
0.025
7.3
0.024
0.095
0.131
44.333
29.167
0.01
0.037
4.578
0.354
0.025
0.109
0.135
56.714
33.9
0.009
0.034
4.722
0.563
0.025
0.09
0.113
44
28.629
0.008
0.034
4.689
0.856
0.025
0.099
0.127
50.143
29.543
0.008
0.031
30
19.1
38
21.9
0.092
0.103
47
29.7
0.109
0.141
43.5
26.15
0.009
0.032
49
29.4
0.097
0.118
38
23.45
0.008
0.029
0.015
0.101
0.141
35.5
19.45
0.007
0.021
0.013
0.087
0.112
31.5
18.9
0.006
0.027
5.222
0.537
0.026
0.091
0.117
55.714
32.714
0.009
0.04
4.089
0.694
0.025
0.106
0.13
51.286
29.914
0.007
0.028
6.225 6.463 5.988
0.105 0.058 0.054
0.074 0.081 0.081
0.101 0.113 0.111
66.375 63.125 60.875
43.05 40.4 41.138
0.005 0.004 0.003
0.013 0.01 0.009
39
23.4
4.26 4.8 3.76
0.087 0.067 0.066
0.023 0.022 0.022
0.092 0.074 0.088
0.11 0.091 0.11
59.211 54.605 54.368
20.132 18.121 17.489
0.015 0.015 0.015
0.058 0.072 0.061
39
24.7
4.26
0.084
0.023
0.093
0.114
62.263
19.495
0.015
0.073
0.087 0.083
0.109 0.112
61 61.5 54.75
34.15 41.675 36.975
49.25
29.45
53
29.9
0.089
0.112
44
25.2
0.009
0.032
0.088
0.122
42.5
23.8
0.008
0.043
9.1 6.95 6.3
0.064 0.073 0.058
0.095 0.097 0.087
43.333 39.167 42.5
25.633 22.683 24.85
0.014
0.089
0.107
29.5
18.2
0.006
0.019
7.4 6.3 5.4
0.025 0.023 0.022
0.104 0.083 0.086
0.138 0.114 0.109
48 40 43
29.833 24.433 26.433
0.01 0.009 0.008
0.036 0.042 0.033
4.189
0.921
0.026
0.093
0.12
46.857
29.471
0.007
0.026
3.322
0.769
0.025
0.103
0.125
50.571
29.471
0.007
0.027
3.1
0.273
0.025
0.097
0.118
45.429
27.329
0.006
0.024
3.422
0.475
0.023
0.101
0.127
42.429
24.557
0.006
0.023
6.263 6.15
0.047 0.059
0.08 0.087
0.111 0.119
62 64.875
40.213 41.275
0.003 0.002
0.009 0.008
5.65 5.1 5.3
0.044 0.023 0.023
0.086 0.08 0.081
0.109 0.102 0.104
61.375 69.875 63.063 70.875
41.288 46.075 37.794 44.213
0.003 0.004 0.004
0.017 0.009 0.011
5.113
0.023
0.081
0.105
0.003
0.012
56
26.4
3.82
0.061
0.021
0.099
0.123
54.579
17.105
0.011
0.044
0.074 0.072
0.085 0.086
39
23.3
3.26
0.042
0.021
0.089
0.105
48.947
16.521
0.011
0.043
0.081
0.108
41
24.5
2.52
0.049
0.02
0.093
0.117
51.105
16.737
0.011
0.046
41
24.5
2.56
0.044
0.022
0.097
0.114
48.368
16.174
0.011
0.042
41
24.5
2.4
0.046
0.021
0.092
0.121
48.632
16.174
0.01
0.037
0.078 0.071 0.075
0.087 0.078 0.092
40.5 44.25 37.25
23.85 25.125 23.125
35.75
22.4
38 33
26.8 24.1
0.096
0.116
50
27.5
0.006
0.022
35
24.3
0.083
0.1
36
23.75
0.005
0.021
47 51
28.7 27.5
0.103
0.13
42.5
26.05
0.005
0.023
0.089
0.12
38.5
22.55
0.005
0.025
41
23.9
51
27.5
0.076
0.105
32.5
20.65
0.005
0.025
7 5.65
0.064 0.066
0.087 0.097
36.833 31.333
22.75 19.583
0.013 0.012
0.092 0.092
0.113 0.124
27 26
14.2 14.9
0.006 0.004
0.022 0.017
6.7 7
0.022 0.022
0.087 0.098
0.118 0.127
49 37.667
28.867 23.867
0.008 0.005
0.033 0.023
6.05 5.35 5.05 6.1
0.085 0.056 0.069 0.057
0.115 0.081 0.106 0.079
33 31.833 30.5 31.833
20.067 21.367 18.833 18.617
0.013 0.013 0.012 0.01
0.083 0.096 0.085 0.087
0.103 0.129 0.113 0.117
26.5 29 25.5 27
16.3 17.05 15.85 15.75
0.004 0.004 0.004 0.004
0.015 0.018 0.016 0.019
4.4 5.6 4.7
0.025 0.025 0.025
0.074 0.092 0.086
0.1 0.112 0.109
40.667 38.333 36.333 36.333
26.7 25.467 22.933 23.767
0.006 0.006 0.006
0.028 0.029 0.027
3.9
0.024
0.088
0.116
0.005
0.026
210
DATA TABLES • APPENDIX A
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-16. Metropolitan Statistical Area Air Quality Trends, 1990-1999 (continued)
Metropolitan Statistical Area Trend #Trend 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
Sites
PROVO-OREM, UT
no2
arithmetic mean
NS
1
0.019
0.019
0.019
0.026
0.024
0.023
0.024
0.023
0.024
0.024
o3
4th max 8-hour
NS
1
0.07
0.067
0.071
0.068
0.069
0.068
0.078
0.07
0.083
0.073
2nd daily max 1-hour
NS
1
0.093
0.084
0.089
0.084
0.084
0.083
0.097
0.08
0.102
0.096
PM10
90th percentile
Down
3
54.667
90.667
68.333
70.667
55.667
49.333
57.333
50
46.667
51.667
weighted annual mean
Down
3
32.2
42.433
37
38.233
33.7
29
33.7
29.967
27.467
29.7
PUEBLO, CO
PM10
90th percentile
Down
1
43
46
46
38
45
45
42
41
33
33
weighted annual mean
Down
1
26.3
29.7
26.3
26.1
29.6
26.2
25.8
26.8
21.7
21.7
RACINE, Wl
CO
2nd max 8-hour
Down
1
5.5
5.7
4.9
4.1
4.3
4.3
3
3.1
3
2.7
o3
4th max 8-hour
NS
1
0.086
0.099
0.08
0.08
0.088
0.096
0.083
0.098
0.084
0.093
2nd daily max 1-hour
NS
1
0.11
0.135
0.102
0.103
0.114
0.113
0.129
0.117
0.124
0.114
RALEIGH-DURHAM-CHAPEL HILL, NC
CO
2nd max 8-hour
Down
2
7.15
7.2
6.45
6.25
6.3
6
5.5
6.75
5.3
5.05
o3
4th max 8-hour
NS
1
0.093
0.085
0.082
0.095
0.083
0.081
0.082
0.097
0.099
0.108
2nd daily max 1-hour
NS
1
0.12
0.107
0.099
0.113
0.107
0.096
0.093
0.112
0.124
0.134
PM10
90th percentile
NS
2
44.5
40.5
35.5
39
31
33.5
39
39
40
36.5
weighted annual mean
)
NS
2
28.6
25.55
24
24.75
21.8
23.3
25.1
24.6
24.4
22.15
RAPID CITY, SC
PM10
90th percentile
Down
3
50.667
52.333
47.667
45
55.333
45.333
42.667
51.667
42.333
38
weighted annual mean
NS
3
30.367
31.233
28.8
26.233
32.733
26.667
27.1
29.8
26.7
23.833
READING, PA
CO
Pb
no2
o3
so2
REDDING, CA
o3
PMin
RENO, NV
CO
o3
2nd max 8-hour
max quarterly mean
arithmetic mean
4th max 8-hour
2nd daily max 1-hour
arithmetic mean
2nd max 24-hour
4th max 8-hour
2nd daily max 1-hour
90th percentile
weighted annual mean
2nd max 8-hour
4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
RICHMOND-PETERSBURG, VA
CO 2nd max 8-hour
N02 arithmetic mean
03 4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
S02 arithmetic mean
2nd max 24-hour
RIVERSIDE-SAN BERNARDINO, CA
CO 2nd max 8-hour
Pb max quarterly mean
N02 arithmetic mean
03 4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
S02 arithmetic mean
2nd max 24-hour
ROANOKE, VA
no2
o3
arithmetic mean
4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
S02 arithmetic mean
2nd max 24-hour
ROCHESTER, MN
PM10 90th percentile
weighted annual mean
Down
Down
NS
NS
NS
NS
Down
NS
NS
Down
Down
NS
NS
NS
Down
Down
NS
Down
NS
NS
NS
Down
NS
NS
Down
NS
Down
Down
Down
Down
Down
NS
NS
NS
up
NS
NS
Down
NS
Down
Down
NS
1
12
1
2
2
2
2
1
1
1
1
5
4
4
6
6
2
1
4
4
3
3
2
2
6
4
8
15
15
11
11
4
4
1
1
1
2
2
1
1
1
1
6.4
0.59
0.022
0.092
0.111
0.01
0.035
0.078
0.092
42
25
7.02
0.074
0.107
92
43.75
4.4
0.023
0.083
0.109
39.667
24.867
0.006
0.027
4.683
0.051
0.028
0.145
0.214
90.818
57.955
0.002
0.007
0.013
0.075
0.086
58
36.45
0.004
0.018
48
27.7
4.6 4.6
0.64 0.558
3.8
0.47
0.02 0.021
0.022
0.104 0.086 0.088
0.121 0.099 0.108
0.01 0.009 0.009
0.034 0.033 0.033
0.066 0.069 0.064
0.077 0.08 0.072
56 45
28.7 24.6
37
20.1
7.48 5.86
0.07 0.07
0.09 0.084
72.833
35.833
4.98
0.062
0.085
63.5 71.333
36.3 40.25
3.65 2.5 3.9
0.024 0.023 0.024
0.085 0.086 0.098
0.109 0.115 0.124
45 35.667 42.667
26.233 22 23.267
0.006 0.005 0.007
0.024 0.022 0.028
5.667
0.056
0.029
0.148
0.207
83.727
53.918
0.002
0.008
4.017
0.033
0.027
0.141
0.197
70.591
44.5
0.002
0.009
5.4 3.9
0.485 0.343
0.023 0.021
0.084 0.093
0.104 0.112
0.011 0.009
0.04 0.033
0.078 0.074
0.09 0.089
39 34
24.4 19.6
5.96 4.38
0.07 0.07
0.086 0.082
65.333 51.667
36.3 31.567
3.4 2.55
0.024 0.022
0.085 0.09
0.11 0.115
33 38.333
20.5 23.2
0.006 0.005
0.023 0.02
3.9
0.038
0.028
0.134
0.181
72.909
43.545
0.002
0.007
3.833
0.037
0.028
0.135
0.186
65.273
42.191
0.002
0.004
0.014 0.013 0.014
0.077 0.072 0.084
0.1 0.089 0.103
50.5 47.5 56
32.5 31.65 34.85
0.004 0.004 0.004
0.019 0.016 0.018
3.4 3 3 3
0.327 0.368 0.412 0.48
0.022 0.021 0.021 0.021
0.086 0.092 0.091 0.101
0.105 0.115 0.105 0.126
0.009 0.009 0.009 0.009
0.036 0.03 0.024 0.026
0.073 0.067 0.078 0.084
0.083 0.079 0.089 0.108
32
18.7
5.16
0.072
0.09
30
16.9
5.02
0.065
0.077
30
17.6
4.72
0.072
0.087
35
20
5.34
0.071
0.087
51.5 52.167 53.5 53.667
29.35 31.733 30.717 34.517
2.85 3.2 2.8 2.9
0.022 0.021 0.021 0.021
0.083 0.097 0.095 0.097
0.103 0.12 0.12 0.126
37 37 37.333 33.667
23.733 22.433 21.867 20.267
0.006 0.005 0.005 0.005
0.025 0.021 0.022 0.021
3.75
0.04
0.028
0.126
0.177
68.318
42.532
0.002
0.005
3.233
0.038
0.026
0.122
0.166
62
40.245
0.001
0.004
3.4
0.04
0.024
0.102
0.147
3.167
0.039
0.023
0.124
0.166
60.636 60.909
39.4 37.091
0.001
0.004
0.002
0.007
2.85
0.047
0.025
0.101
0.128
65.364
43.473
0.002
0.007
0.013 0.013
0.084 0.079
0.102 0.093
55 54
35.55 34.35
0.004 0.003
0.011 0.01
0.013 0.013 0.014 0.012
0.073 0.084 0.099 0.089
0.084 0.102 0.126 0.105
58 51.5 48.5 48.5
33.05 29.85 29.2 29.9
0.003 0.003 0.003 0.003
0.014 0.013 0.009 0.01
37
22.7
37
21.2
31
20.4
33
20.8
32
20.2
34
19.4
31
20
31
21.2
31
21.2
APPENDIX A • DATA TABLES
211
-------
NATIONALAIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-16. Metropolitan Statistical Area Air Quality Trends, 1990-1999 (continued)
Metropolitan Statistical Area
Trend
#Trend
1990
1991
1992
1993
1994
1995
Sites
ROCHESTER, NY
CO
2nd max 8-hour
NS
2
3.45
3.25
3.5
3.15
4.5
3.15
o3
4th max 8-hour
NS
2
0.087
0.098
0.076
0.078
0.079
0.093
2nd daily max 1-hour
NS
2
0.108
0.111
0.09
0.094
0.094
0.107
PM10
90th percentile
NS
2
37.5
48.5
37.5
39.5
33
37
weighted annual mean
Down
2
21.3
25.85
22.4
22.8
20.05
20.8
so2
arithmetic mean
Down
2
0.012
0.011
0.011
0.01
0.011
0.01
2nd max 24-hour
NS
2
0.04
0.043
0.039
0.041
0.043
0.038
ROCKFORD, IL
CO
2nd max 8-hour
Down
1
6.5
5.1
4.6
4.3
4
4.5
Pb
max quarterly mean
NS
1
0.085
0.044
0.059
0.034
0.039
0.027
o3
4th max 8-hour
NS
2
0.068
0.077
0.082
0.067
0.079
0.085
2nd daily max 1-hour
NS
2
0.085
0.091
0.093
0.077
0.102
0.101
PM10
90th percentile
NS
1
45
35
31
26
36
39
weighted annual mean
NS
1
25.2
22.2
21.4
16.3
18.8
18.9
SACRAMENTO, CA
CO
2nd max 8-hour
Down
7
7.786
7.2
5.486
5.657
5.471
4.586
Pb
max quarterly mean
Down
2
0.105
0.04
0.022
0.049
0.019
0.021
no2
arithmetic mean
Down
3
0.02
0.017
0.018
0.018
0.016
0.017
o3
4th max 8-hour
NS
8
0.093
0.095
0.094
0.09
0.091
0.097
2nd daily max 1-hour
NS
8
0.13
0.128
0.124
0.116
0.113
0.128
PM10
90th percentile
Down
3
54.333
54.333
42
38
37.667
47
weighted annual mean
Down
3
31.233
31.233
27.633
22.667
23.8
22.9
so2
arithmetic mean
NS
2
0.004
0.002
0.002
0.001
0.001
0.002
2nd max 24-hour
NS
2
0.011
0.011
0.01
0.004
0.005
0.005
ST. JOSEPH, MO
PM10
90th percentile
Down
1
71
79
70
56
62
67
weighted annual mean
Down
1
40.2
44
38.6
31.5
33.7
33.3
ST. LOUIS, MO-IL
CO
2nd max 8-hour
Down
8
4.25
4.313
3.45
3.538
3.763
3.313
Pb
max quarterly mean
Down
13
0.76
0.68
0.697
0.573
0.66
0.677
NO,
arithmetic mean
NS
9
0.018
0.018
0.019
0.018
0.019
0.019
o3
4th max 8-hour
NS
16
0.081
0.086
0.08
0.074
0.09
0.09
2nd daily max 1-hour
NS
16
0.108
0.108
0.1
0.108
0.117
0.116
PM10
90th percentile
NS
15
54.467
48.2
50.533
46.333
49.533
51.467
weighted annual mean
Down
15
32.96
31.807
32.047
28.187
31.12
30.773
so2
arithmetic mean
Down
16
0.011
0.01
0.009
0.009
0.009
0.008
2nd max 24-hour
Down
16
0.042
0.041
0.038
0.04
0.04
0.037
SALINAS, CA
CO
2nd max 8-hour
Down
1
2.5
2.1
2.3
2.1
2
1.7
no2
arithmetic mean
Down
1
0.012
0.012
0.012
0.012
0.012
0.011
o3
4th max 8-hour
NS
4
0.062
0.062
0.061
0.065
0.057
0.057
2nd daily max 1-hour
Down
4
0.08
0.078
0.075
0.083
0.08
0.071
PM10
90th percentile
NS
2
40
37
33.5
33
29
37.75
weighted annual mean
NS
2
23.45
23.9
21.45
19.7
18.15
19
SALT LAKE CITY-OGDEN, UT
CO
2nd max 8-hour
Down
1
6.8
7.5
6.5
6.4
5.9
4.5
Pb
max quarterly mean
NS
2
0.083
0.079
0.049
0.07
0.049
0.051
no2
arithmetic mean
NS
2
0.019
0.02
0.02
0.024
0.023
0.022
o3
4th max 8-hour
NS
2
0.08
0.079
0.074
0.079
0.081
0.083
2nd daily max 1-hour
NS
2
0.113
0.108
0.097
0.104
0.109
0.115
PM10
90th percentile
Down
6
56.333
89
73.667
68.333
52.5
49.333
weighted annual mean
Down
6
33.267
41.183
35.85
36.717
32.033
28.867
so2
arithmetic mean
Down
3
0.009
0.01
0.009
0.007
0.004
0.003
2nd max 24-hour
Down
3
0.039
0.051
0.046
0.043
0.013
0.013
SAN ANTONIO, TX
CO
2nd max 8-hour
Down
1
5.2
5.2
5.2
5
3.3
4.3
o3
4th max 8-hour
NS
2
0.084
0.08
0.072
0.081
0.088
0.092
2nd daily max 1-hour
NS
2
0.1
0.105
0.096
0.11
0.105
0.117
PM10
90th percentile
Down
1
47
42
46
38
39
35
weighted annual mean
Down
1
28.3
29.1
28.6
22.7
23.4
22
SAN DIEGO, CA
CO
2nd max 8-hour
Down
8
5.588
5.25
4.95
4.413
4.738
4.213
Pb
max quarterly mean
Down
3
0.094
0.044
0.03
0.033
0.016
0.025
no2
arithmetic mean
Down
7
0.025
0.025
0.024
0.02
0.021
0.021
o3
4th max 8-hour
Down
9
0.105
0.099
0.094
0.09
0.082
0.082
2nd daily max 1-hour
Down
9
0.154
0.147
0.139
0.132
0.109
0.116
PM10
90th percentile
Down
3
54.333
54
44
46
42
46
weighted annual mean
Down
3
34.233
37.133
31.5
30.033
30.667
32.167
so2
arithmetic mean
NS
3
0.004
0.003
0.004
0.002
0.003
0.003
2nd max 24-hour
NS
3
0.015
0.017
0.017
0.009
0.013
0.012
3.7
0.069
0.085
35
21.45
0.009
0.033
3.2
0.049
0.078
0.089
29
17.6
4.271
0.014
0.017
0.094
0.116
33.667
20
0.002
0.004
52
32.4
3.425
0.671
0.019
0.084
0.108
42.533
27.327
0.008
0.038
2.4
0.011
0.063
0.079
35
19
6.2
0.028
0.023
0.085
0.114
61
33.167
0.003
0.014
4.5
0.081
0.118
28
19.7
4.288
0.019
0.019
0.083
0.104
38
27.7
0.004
0.015
1.9
0.085
0.099
33
19.9
0.008
0.038
3.7
0.029
0.072
0.082
42
25.6
3.929
0.012
0.015
0.081
0.101
31.333 31.333
20.167 18.8
0.002 0.002
0.005 0.01
2.7
0.081
0.096
36
19.8
0.009
0.053
3.6
0.043
0.072
0.084
39
24.1
3.957
0.009
0.016
0.094
0.126
57
31.4
3.238
0.535
0.018
0.083
0.108
44.8
27.553
0.007
0.034
1.7
0.01
0.056
0.071
32
20.85
5.4
0.07
0.022
0.077
0.102
49
28.95
0.003
0.008
4.4
0.083
0.102
32
20.7
3.838
0.019
0.019
0.078
0.112
38
26.8
0.003
0.012
47
25.8
3.4
0.433
0.019
0.085
0.112
48.6
30.033
0.006
0.034
1.9
0.01
0.056
0.07
30.5
17.35
4.9
0.063
0.022
0.094
0.122
45.667
26.717
0.003
0.008
4.6
0.082
0.1
32
20.7
3.525
0.013
0.018
0.079
0.106
36
22.867
0.003
0.011
2.5
0.089
0.099
36
19.8
0.006
0.03
3.8
0.043
0.08
0.09
39
24.1
3.986
0.009
0.017
0.091
0.117
45
23.967
0.003
0.008
47
25.8
2.513
0.482
0.02
0.089
0.115
43.733
27.007
0.006
0.029
1.6
0.01
0.059
0.071
34.5
21.3
5
0.057
0.023
0.08
0.107
54.667
30.117
0.003
0.008
4.2
0.083
0.101
32
20.7
3.713
0.013
0.021
0.071
0.097
40.667
28
0.003
0.012
212
DATA TABLES • APPENDIX A
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-16. Metropolitan Statistical Area Air Quality Trends, 1990-1999 (continued)
Metropolitan Statistical Area Trend #Trend 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
Sites
SAN FRANCISCO, CA
CO
2nd max 8-hour
Down
4
5.7
6.15
4.825
4.6
Pb
max quarterly mean
Down
1
0.044
0.04
0.02
0.026
NO,
arithmetic mean
Down
1
0.021
0.024
0.022
0.024
o3
4th max 8-hour
NS
3
0.044
0.046
0.045
0.048
2nd daily max 1-hour
NS
3
0.06
0.063
0.063
0.083
PM10
90th percentile
Down
1
59
66
56
39
weighted annual mean
Down
1
28.3
32.1
28.5
26.5
so2
arithmetic mean
NS
1
0.002
0.002
0.003
0.002
2nd max 24-hour
NS
1
0.01
0.013
0.012
0.01
SAN JOSE, CA
CO
2nd max 8-hour
Down
2
10.75
10.15
7.25
6.4
Pb
max quarterly mean
Down
2
0.075
0.037
0.029
0.023
o3
4th max 8-hour
NS
4
0.071
0.073
0.07
0.073
2nd daily max 1-hour
NS
4
0.105
0.11
0.108
0.105
PM10
90th percentile
Down
4
72
63.75
54.75
45.5
weighted annual mean
Down
4
35.75
33.775
29.7
25.825
SAN JUAN-BAYAMON, PR
CO
2nd max 8-hour
Down
2
5.3
5.25
5.3
4.45
PM10
90th percentile
NS
7
59.286
47.143
44.429
54.429
weighted annual mean
NS
7
33.429
29.157
27.714
31.443
so2
arithmetic mean
Down
2
0.007
0.01
0.009
0.008
2nd max 24-hour
Down
2
0.056
0.062
0.069
0.038
SAN LUIS OBISPO-ATASCADERO-PASO ROBLES,C
CO
2nd max 8-hour
Down
1
3.9
3.3
3
3.1
no2
arithmetic mean
Down
3
0.013
0.013
0.012
0.012
o3
4th max 8-hour
NS
5
0.069
0.066
0.065
0.064
2nd daily max 1-hour
NS
5
0.086
0.084
0.082
0.081
PM10
90th percentile
Down
3
38
39.667
32
41.667
weighted annual mean
Down
3
23.133
24.367
21.233
22.4
so2
arithmetic mean
NS
1
0.002
0.001
0.001
0.001
2nd max 24-hour
NS
1
0.006
0.005
0.004
0.004
SANTA BARBARA-SANTA MARIA-LOMPOC, CA
CO
2nd max 8-hour
Down
4
2.35
2.325
2.25
2.15
Pb
max quarterly mean
Down
1
0.032
0.027
0.012
0.015
no2
arithmetic mean
Down
15
0.007
0.007
0.007
0.006
o3
4th max 8-hour
Down
16
0.079
0.074
0.079
0.076
2nd daily max 1-hour
Down
16
0.105
0.103
0.104
0.099
PM10
90th percentile
NS
10
35.3
35.7
32.3
37.8
weighted annual mean
NS
10
23.17
22.17
21.5
22.58
so2
arithmetic mean
NS
11
0.001
0.001
0.001
0.001
2nd max 24-hour
Down
11
0.003
0.003
0.003
0.004
SANTA CRUZ-WATSONVILLE, CA
CO
2nd max 8-hour
Down
1
1
1
1
1
no2
arithmetic mean
Down
1
0.008
0.01
0.007
0.006
o3
4th max 8-hour
NS
1
0.06
0.055
0.061
0.061
2nd daily max 1-hour
NS
1
0.07
0.07
0.07
0.07
so2
arithmetic mean
NS
1
0.001
0.001
0.001
0.001
2nd max 24-hour
NS
1
0.003
0.002
0.006
0.006
SANTA FE, NM
CO
2nd max 8-hour
Down
1
3.5
3.9
3.7
3.4
PM10
90th percentile
Down
2
23.5
21.5
23
22.5
weighted annual mean
Down
2
16.6
14.35
16.15
14.85
SANTA ROSA, CA
CO
2nd max 8-hour
Down
1
4.3
3.8
3.5
3.8
no2
arithmetic mean
NS
1
0.015
0.015
0.016
0.016
o3
4th max 8-hour
up
2
0.056
0.059
0.057
0.061
2nd daily max 1-hour
up
2
0.075
0.08
0.075
0.085
PM10
90th percentile
Down
3
37.333
46
33
33.667
weighted annual mean
Down
3
20.067
23.433
18.4
19.133
SARASOTA-BRADENTON, FL
CO
2nd max 8-hour
NS
1
6.2
6.9
5.6
6.5
o3
4th max 8-hour
NS
3
0.077
0.074
0.077
0.075
2nd daily max 1-hour
NS
4
0.096
0.095
0.092
0.097
PM10
90th percentile
Down
3
42.667
42.333
41.333
38.667
weighted annual mean
Down
3
27.967
25.1
26.533
26.533
so2
arithmetic mean
Down
1
0.002
0.003
0.003
0.003
2nd max 24-hour
NS
1
0.016
0.035
0.021
0.018
SAVANNAH, GA
so2
arithmetic mean
NS
1
0.002
0.002
0.002
0.003
2nd max 24-hour
NS
1
0.008
0.009
0.008
0.011
4.25
0.019
0.022
0.049
0.072
47
24.8
0.001
0.005
7.35
0.017
0.067
0.096
46.75
3.65
0.027
0.021
0.061
0.094
34
21
0.002
0.005
5.6
0.016
0.083
0.118
38.5
3.9
0.014
0.022
0.055
0.082
32
21.1
0.002
0.007
5.65
0.013
0.081
0.109
30.75
3.35
0.02
0.02
0.048
0.074
33
23.9
0.002
0.006
3.5
0.013
0.02
0.045
0.063
34
22.4
0.002
0.006
5.35 6.05
0.011 0.013
0.062 0.073
0.084 0.111
31.75 33
3.625
0.013
0.021
0.052
0.082
36
24.5
0.002
0.006
6
0.013
0.072
0.11
36.5
4.8 4.85
45.429 36.714
28.886 25.071
0.008 0.006
0.048 0.039
3.95 3.9 3.75 3.5
39.286 50.286 47.429 50.143
26.486 30.4 28.043 28.729
0.005 0.004 0.003 0.004
0.021 0.017 0.013 0.018
3.1 2.4 2.3 2.3 2 2.9
0.012 0.011 0.011 0.011 0.01 0.011
0.064 0.064 0.069 0.062 0.067 0.065
0.078 0.081 0.086 0.073 0.081 0.08
33 35.667 31.667 30.333 23.333 27.333
21.167 21.2 18.333 19.967 15.433 17.333
0.002 0.002 0.002 0.001 0.001 0.001
0.005 0.004 0.004 0.004 0.004 0.004
2.5
0.01
0.007
0.073
0.095
35.6
22.96
0.001
0.003
1.2
0.006
0.053
0.068
0.002
0.006
2.7
21
13.75
3.2
0.015
0.06
0.085
2.1
0.009
0.006
0.074
0.101
33.1
21.71
0.001
0.004
0.8
0.005
0.051
0.06
0.001
0.008
2.3
18.5
12.75
2.4
0.015
0.065
0.089
28.333 28.667
1.85
0.007
0.006
0.079
0.107
33.1
20.96
0.001
0.003
0.7
0.005
0.049
0.069
0.002
0.003
2.2
21
13.95
3
0.014
0.062
0.08
26.667
1.625
0.008
0.006
0.069
0.087
34.7
22.5
0.001
0.002
0.7
0.004
0.051
0.063
0.001
0.002
1.675
0.008
0.006
0.064
0.087
33.3
21.12
0.001
0.002
0.8
0.004
0.049
0.055
0.001
0.003
1.675
0.008
0.006
0.064
0.082
32.6
21.59
0.001
0.002
0.7
0.005
0.06
0.072
0.001
0.002
2.1 2 1.7
19.5 20 18.5
13.55 13.6 12.85
3.1 3
0.013 0.015
0.064 0.063
0.089 0.084
3.3
0.014
0.072
0.096
23 23.333 28.667
17.9 15.7 15.667 14.933 13.967 17.2
5.3
0.079
0.095
5.9
0.077
0.095
35 33.667
22.867 21.367
0.003
0.017
0.002
0.01
5.3 5.6
0.077 0.084
0.101 0.119
28.667 29.667 31.333 32.667
20.033 20.533 20.967 20.9
0.002 0.002
0.009 0.019
5.1
0.073
0.092
0.002
0.018
5.6
0.085
0.114
0.002
0.019
0.003 0.004
0.015 0.013
0.004 0.003 0.003 0.003
0.019 0.013 0.01 0.01
APPENDIX A • DATA TABLES
213
-------
NATIONALAIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-16. Metropolitan Statistical Area Air Quality Trends, 1990-1999 (continued)
Metropolitan Statistical Area
Trend
#Trend
1990
Sites
SCRANTON—WILKES-BARRE—HAZLETON, PA
CO
2nd max 8-hour
Down
2
4.5
no2
arithmetic mean
Down
2
0.018
o3
4th max 8-hour
NS
4
0.091
2nd daily max 1-hour
NS
4
0.106
PM-io
90th percentile
Down
3
46
weighted annual mean
NS
3
25.367
so2
arithmetic mean
Down
2
0.01
2nd max 24-hour
Down
2
0.049
SEATTLE-BELLEVUE-EVERETT, WA
CO
2nd max 8-hour
Down
6
7.617
Pb
max quarterly mean
NS
1
0.641
o3
4th max 8-hour
NS
2
0.088
2nd daily max 1-hour
NS
2
0.127
PM-io
90th percentile
Down
8
48.75
weighted annual mean
Down
8
28.55
so2
arithmetic mean
Down
2
0.008
2nd max 24-hour
Down
2
0.023
SHARON, PA
Pb
max quarterly mean
Down
1
0.087
o3
4th max 8-hour
NS
1
0.087
2nd daily max 1-hour
NS
1
0.103
PM-io
90th percentile
Down
1
52
weighted annual mean
NS
1
29.9
so2
arithmetic mean
Down
1
0.01
2nd max 24-hour
NS
1
0.036
SHREVEPORT-BOSSIER CITY, LA
o3
4th max 8-hour
NS
2
0.088
2nd daily max 1-hour
NS
2
0.112
PM-io
90th percentile
NS
1
33
weighted annual mean
NS
1
23.3
so2
arithmetic mean
NS
1
0.002
2nd max 24-hour
NS
1
0.006
SIOUX CITY, IA-NE
PM10
90th percentile
NS
1
46
weighted annual mean
NS
1
27.7
SIOUX FALLS, SD
PM-io
90th percentile
NS
2
41.5
weighted annual mean
NS
2
23.2
SOUTH BEND, IN
o3
4th max 8-hour
NS
3
0.082
2nd daily max 1-hour
up
3
0.097
PM-io
90th percentile
Down
2
52.5
weighted annual mean
Down
2
30.8
SPOKANE, WA
CO
2nd max 8-hour
Down
3
9.1
o3
4th max 8-hour
up
1
0.057
2nd daily max 1-hour
NS
1
0.071
PM-io
90th percentile
Down
4
62.5
weighted annual mean
Down
4
37.125
SPRINGFIELD, IL
CO
2nd max 8-hour
Down
1
4.4
o3
4th max 8-hour
Down
1
0.081
2nd daily max 1-hour
NS
1
0.098
so2
arithmetic mean
NS
1
0.007
2nd max 24-hour
NS
1
0.054
SPRINGFIELD, MO
CO
2nd max 8-hour
Down
1
7.2
no2
arithmetic mean
up
1
0.008
o3
4th max 8-hour
up
2
0.058
2nd daily max 1-hour
up
2
0.075
PM-io
90th percentile
NS
3
36.333
weighted annual mean
NS
3
21.6
so2
arithmetic mean
NS
2
0.006
2nd max 24-hour
NS
2
0.057
SPRINGFIELD, MA
CO
2nd max 8-hour
NS
2
6.7
no2
arithmetic mean
Down
2
0.018
o3
4th max 8-hour
NS
4
0.093
2nd daily max 1-hour
NS
4
0.121
PM-io
90th percentile
NS
5
39.2
weighted annual mean
NS
5
23.06
so2
arithmetic mean
Down
3
0.008
2nd max 24-hour
Down
3
0.033
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
4.15 3.75 2.9
0.017 0.016 0.018
0.098 0.081 0.088
0.118 0.095 0.11
48.667 40.667 45.667
28.933 25.067 26.233
0.009 0.008 0.007
0.039 0.033 0.026
7.7 7.783 5.783
0.561 0.4 0.368
0.074 0.078 0.066
0.105 0.098 0.098
49.75 47.875 50.125
29.3 28.838 27.613
0.008 0.008 0.008
0.023 0.02 0.02
0.087
0.093
0.107
59
36
0.009
0.032
0.081
0.1
48
28.4
0.002
0.009
51
27.9
39.5
22.6
0.073
0.088
0.1
42
26.6
0.008
0.03
0.083
0.1
36
23.8
0.004
0.013
45
25.4
39.5
22.8
0.086 0.081 0.076
0.1 0.094 0.09
49 38 36
29.65 23.05 23.75
9.333
0.061
0.077
58.5
8.133
0.063
0.083
57
33.1 34.125
4.3
0.083
0.102
0.008
0.048
4.5
0.077
0.091
0.006
0.043
0.06
0.069
60.75
32.15
3.9
0.081
0.106
0.006
0.04
6.9 6.2 5.3
0.008 0.01 0.011
0.063 0.058 0.069
0.073 0.085 0.075
27.333 30 29.667
18.233 18.933 17.4
0.003 0.004 0.006
0.033 0.034 0.04
6.3
0.017
0.097
0.126
42.2
23.4
0.008
0.031
7.1
0.016
0.09
0.117
34.4
21.5
0.007
0.034
6.1
0.016
0.095
0.129
39.6
22.2
0.006
0.023
3.55
0.018
0.081
0.098
49
2.8
0.016
0.088
0.105
45
28.433 25.467
0.007 0.005
0.035 0.036
5.683
0.607
0.064
0.12
38.25
5.55
0.513
0.067
0.093
37
22.513 21.725
0.006 0.005
0.022 0.017
0.047
0.083
0.105
47
28.1
0.008
0.029
0.088
0.113
37
21.8
0.004
0.011
40
22.5
27.5
17
0.054
0.09
0.111
51
29.8
0.008
0.047
0.08
0.094
36
23.6
0.002
0.008
38
23.3
6.4
0.068
0.085
52
30.375
3.1
0.081
0.101
0.006
0.05
7.5
0.019
0.093
0.125
40.4
24.44
0.006
0.048
3.8
0.018
0.081
0.103
37.667
23.533
0.006
0.028
3.05
0.016
0.087
0.101
39
25.7
0.007
0.029
2.5
0.015
0.087
0.103
39
25.7
0.006
0.024
2.15
0.015
0.092
0.109
39
25.7
0.006
0.022
5.333 5.6 4.65 4.717
0.658 0.874 2.033 0.046
0.082 0.065 0.071 0.06
0.108 0.084 0.12 0.078
32 36.75 31.625 30
20.288 22.025 18.675 18.888
0.004 0.004 0.005 0.005
0.017 0.011 0.013 0.015
0.049
0.095
0.113
49
27.7
0.008
0.032
0.081
0.097
43
23.7
0.001
0.004
55
26.4
0.067
0.09
0.103
37
29
0.007
0.029
0.079
0.098
29
21.9
0.002
0.004
38.5 39.5
22.7 21.65
0.086 0.094
0.099 0.112
39 42
27.1 21.7
6.933
0.065
0.08
44
24.45
3.2
0.08
0.1
0.006
0.062
5.9 4.1
0.013 0.012
0.072 0.079
0.093 0.098
28 27.667
17.4 16.633
0.008 0.003
0.067 0.021
7.9
0.015
0.092
0.124
36.2
20.7
0.005
0.023
0.044
0.092
0.111
42
28.2
0.007
0.032
0.084
0.101
35
22.5
0.002
0.007
0.042
0.106
0.121
42
28.2
0.007
0.029
0.089
0.109
35
22.5
0.002
0.01
72 54 45
32.5 28.3 28
31.5
20.55
0.09
0.107
34.5
20.1
6.833
0.067
0.079
43.5
26.65
3
0.079
0.098
0.006
0.061
3.3
0.011
0.074
0.086
26
17.9
0.005
0.044
7.1
0.016
0.083
0.104
35.4
22.22
0.005
0.024
35
21.2
35
21.6
0.042
0.091
0.108
42
28.2
0.007
0.039
0.091
0.104
35
22.5
0.002
0.006
48
27.9
35.5
21.6
0.089 0.091 0.088
0.11 0.115 0.102
29.5 36.5 34
17.2 20.65 20.3
5.133 5.133
0.068 0.07
0.083 0.082
40.75 43
24.45 24.525
2.1
0.071
0.085
0.006
0.043
1.9
0.078
0.093
0.007
0.061
4.567
0.065
0.073
41.75
23.7
2.4
0.075
0.099
0.006
0.059
4.6 4 3.1
0.011 0.012 0.013
0.066 0.071 0.078
0.08 0.09 0.094
24 30.667 30.333
15.7 17.967 17.967
0.002 0.004 0.004
0.022 0.021 0.021
5.1
0.015
0.094
0.122
34.2
22.08
0.005
0.021
4.1
0.013
0.087
0.109
38.8
21.28
0.005
0.02
4.8
0.014
0.087
0.108
38.4
23.4
0.005
0.02
214
DATA TABLES • APPENDIX A
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-16. Metropolitan Statistical Area Air Quality Trends, 1990-1999 (continued)
Metropolitan Statistical Area Trend #Trend 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
Sites
STAMFORD-NORWALK, CT
CO 2nd max 8-hour
03 4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
S02 arithmetic mean
2nd max 24-hour
STEUBENVILLE-WEIRTON, OH-WV
CO 2nd max 8-hour
Pb max quarterly mean
N02 arithmetic mean
03 4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
S02 arithmetic mean
2nd max 24-hour
STOCKTON-LODI, CA
CO
Pb
no2
o3
PM-io
SYRACUSE,
CO
o3
PM-io
so2
NY
2nd max 8-hour
max quarterly mean
arithmetic mean
4th max 8-hour
2nd daily max 1-hour
90th percentile
weighted annual mean
f
2nd max 8-hour
4th max 8-hour
2nd daily max 1-hour
90th percentile
weighted annual mean
arithmetic mean
2nd max 24-hour
TACOMA, WA
CO
o3
2nd max 8-hour
4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
S02 arithmetic mean
2nd max 24-hour
TAMPA-ST. PETERSBURG-CLEARWATER, FL
CO 2nd max 8-hour
Pb max quarterly mean
N02 arithmetic mean
03 4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
S02 arithmetic mean
2nd max 24-hour
TERRE HAUTE, IN
03 4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
S02 arithmetic mean
2nd max 24-hour
TEXARKANA, TX-TEXARKANA, AR
PM1C
TOLEDO, OH
o3
so2
TOPEKA, KS
Pb
PMin
90th percentile
weighted annual mean
4th max 8-hour
2nd daily max 1-hour
arithmetic mean
2nd max 24-hour
max quarterly mean
90th percentile
weighted annual mean
Down
NS
NS
NS
NS
Down
NS
Down
Down
NS
NS
NS
Down
Down
Down
NS
Down
Down
NS
NS
NS
Down
Down
Down
NS
Down
NS
NS
NS
NS
NS
NS
NS
Down
Down
Down
Down
Down
Down
NS
up
NS
NS
NS
NS
Down
NS
NS
Down
Down
NS
Down
NS
NS
NS
NS
NS
NS
Down
NS
NS
6.3
0.108
0.144
48.667
30.1
0.005
0.024
11.467
0.065
0.02
0.075
0.092
67.778
24.544
0.024
0.085
10.85
0.042
0.026
0.086
0.115
75.5
45.25
6.8
0.092
0.103
48.5
28.05
0.003
0.014
6 5.5
0.11 0.082
0.147 0.111
51 36.667
32 24.067
0.006 0.005
0.025 0.022
0.087
0.127
55.75
30.575
0.008
0.026
3.817
0.763
0.013
0.08
0.106
40.2
27.26
0.006
0.03
0.087
0.105
54.8
32.82
0.011
0.038
36
24.3
0.085
0.1
0.006
0.033
0.012
58
32.5
9.267
0.083
0.021
0.091
0.114
69.556
26.6
0.022
0.08
9.65
0.039
0.025
0.087
0.11
93.5
48.6
8.4
0.092
0.103
50.5
29.25
0.003
0.014
8.7
0.077
0.094
52.25
31.025
0.008
0.023
6.933
0.148
0.019
0.076
0.089
63.889
23.822
0.018
0.076
5.85
0.024
0.024
0.085
0.11
60
39.35
7.5
0.083
0.096
46.5
27.25
0.003
0.012
8.9
0.081
0.097
54.5
5.2
0.101
0.145
35
23.3
0.005
0.02
7.233
0.067
0.017
0.081
0.101
62.111
22.778
0.019
0.083
5.8
0.026
0.024
0.083
0.11
74.5
36.35
5.6
0.083
0.097
41
24.05
0.003
0.018
5.9
0.068
0.1
50.75
39
22.4
37
23.3
6.2 5.4
0.107 0.102
0.155 0.136
50 41.333
28.133 24.733
0.006 0.004
0.028 0.023
32.6 28.025
0.009 0.009
0.03 0.025
2.85 2.867 2.583
0.756 0.45 0.23
0.012 0.011 0.011
0.07 0.074 0.071
0.097 0.094 0.091
41.4 41.6 39
27.74 26.72 27.52
0.005 0.005 0.005
0.029 0.027 0.029
0.088 0.069 0.074
0.088
45
0.1 0.081
50 43.4
29.58 26.08 25.48
0.011 0.007 0.009
0.037 0.033 0.039
35
21.9
0.086 0.079 0.083
0.108 0.091 0.108
0.006 0.006 0.007
0.022 0.029 0.028
0.011 0.009 0.009
39 47 40
28.3 27.1
25.5
8.667
0.082
0.02
0.083
0.103
65.667
23.133
0.017
0.088
6.95
0.016
0.024
0.086
0.12
59
35
6.5
0.077
0.095
40.5
22.05
0.003
0.02
6
0.073
0.112
39.75
23.125
0.007
0.021
2.2
0.296
0.01
0.075
0.093
39
25.96
0.005
0.031
0.094
0.106
40.2
25.14
0.01
0.039
36
22.9
0.088
0.109
0.007
0.047
0.008
46
29.2
4.1 5.1 3.8 3.8
0.093 0.101 0.089 0.107
0.121 0.142 0.113 0.143
39.333 39.333 35.333 36.667
24.5 25.733 23.833 24.2
0.005 0.004 0.004 0.004
0.019 0.025 0.025 0.025
5.867
0.055
0.02
0.094
0.112
60.556
22.756
0.011
0.047
4.8
0.015
0.022
0.087
0.125
51
31.25
3.3
0.086
0.1
35.5
21
0.003
0.016
6.3
0.074
0.089
38.5
22.7
0.006
0.02
2.75
0.254
0.011
0.074
0.096
38
25.28
0.004
0.025
0.085
0.099
48.2
26.86
0.007
0.029
45
25.7
0.088
0.107
0.004
0.025
0.009
54
34.1
5
0.05
0.02
0.08
0.097
4.8
0.029
0.017
0.081
0.093
6.7
0.029
0.017
0.083
0.094
55.222 48.667 53.778
3.033
0.029
0.017
0.085
0.098
49
21.133
0.011
0.048
18.3 19.322 19.133
0.011 0.011 0.011
0.051 0.047 0.05
6 3.65 5.25 5.25
0.023 0.014 0.014 0.014
0.023 0.022 0.023 0.024
0.079 0.073 0.085 0.083
0.101 0.094 0.108
37.5 45.5 54.5
26.05 28.7 28.05
3.9
0.073
0.085
32
22.05
0.003
0.014
6.3
40.25
2.533
0.246
0.011
0.074
0.098
40.4
26.86
0.005
0.024
36.6
39
23.4
0.12
59.5
31.7
41
27.1
4
3
3.1
0.077
0.082
0.084
0.096
0.093
0.092
38
42
42
21.65
24.15
24.15
0.002
0.002
0.002
0.017
0.01
0.014
6.8
5.8
6.6
0.066
0.085
0.065
0.083
0.126
0.079
45
32.75
32.75
23.35
18.65
19.7
0.006
0.006
0.005
0.023
0.019
0.019
2.4
2.467
2.5
0.214
0.175
0.343
0.011
0.011
0.013
0.08
0.089
0.084
0.099
0.111
0.108
42.6
40.4
42.6
27.44
27.4
26.46
0.005
0.005
0.005
0.026
0.027
0.023
0.083
0.084
0.082
0.096
0.099
0.093
39
37.8
38.2
23.12
23.36
23
0.006
0.007
0.008
0.023
0.027
0.029
34
34
34
22.4
22.4
22.4
0.083
0.083
0.083
0.099
0.1
0.109
0.004
0.004
0.007
0.019
0.019
0.035
0.008
0.008
0.008
44
44
44
28
28
28
APPENDIX A • DATA TABLES
215
-------
NATIONALAIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-16. Metropolitan Statistical Area Air Quality Trends, 1990-1999 (continued)
Metropolitan Statistical Area
Trend
#Trend
Sites
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
TRENTON, NJ
o3
PM10
TUSCON, AZ
CO
no2
o3
PM-io
SO,
4th max 8-hour
2nd daily max 1-hour
90th percentile
weighted annual mean
2nd max 8-hour
arithmetic mean
4th max 8-hour
2nd daily max 1-hour
90th percentile
weighted annual mean
arithmetic mean
2nd max 24-hour
TULSA,OK
CO
Pb
no2
o3
2nd max 8-hour
max quarterly mean
arithmetic mean
4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
S02 arithmetic mean
2nd max 24-hour
TUSCALOOSA, AL
PM10 90th percentile
weighted annual mean
UTICA-ROME, NY
03 4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
S02 arithmetic mean
2nd max 24-hour
VALLEJO-FAIRFIELD-NAPA, CA
CO 2nd max 8-hour
03 4th max 8-hour
2nd daily max 1-hour
PM10 90th percentile
weighted annual mean
2nd max 8-hour
max quarterly mean
arithmetic mean
4th max 8-hour
2nd daily max 1-hour
90th percentile
weighted annual mean
VENTURA, CA
CO
Pb
no2
o3
PM-io
VICTORIA, TX
o3
4th max 8-hour
2nd daily max 1-hour
VINELAND-MILLVILLE-BRIDGETON, NJ
03 4th max 8-hour
2nd daily max 1-hour
S02 arithmetic mean
2nd max 24-hour
VISALIA-TULARE-PORTERVILLE, CA
CO
no2
o3
PM10
WASHINGTON.
CO
Pb
no2
o3
PM10
SO,
2nd max 8-hour
arithmetic mean
4th max 8-hour
2nd daily max 1-hour
90th percentile
weighted annual mean
DC-MD-VA-WV
2nd max 8-hour
max quarterly mean
arithmetic mean
4th max 8-hour
2nd daily max 1-hour
90th percentile
weighted annual mean
arithmetic mean
2nd max 24-hour
NS
Down
Down
Down
Down
NS
NS
NS
NS
NS
NS
Down
NS
Down
NS
NS
NS
NS
NS
NS
NS
NS
NS
NS
NS
Down
NS
NS
NS
Down
NS
NS
Down
Down
Down
Down
Down
Down
Down
Down
Down
NS
NS
NS
NS
Down
Down
Down
NS
NS
NS
Down
Down
Down
Down
Down
NS
NS
Down
Down
Down
NS
1
1
1
1
4
1
5
5
10
10
1
1
2
1
2
3
3
5
5
1
1
1
1
2
2
2
2
1
1
2
3
3
1
1
2
1
4
6
6
5
5
5
7
13
13
14
14
5
5
0.105
0.142
51
29.2
4.55
0.019
0.073
0.093
49.8
32.55
0.002
0.007
4.7
0.108
0.011
0.09
0.116
42
23.9
0.012
0.056
61
31.8
0.08
0.097
35
20.65
0.001
0.006
6.85
0.067
0.093
53
26.6
3.25
0.02
0.016
0.098
0.128
55.8
34.44
0.058
0.099
0.11
0.125
0.007
0.024
5
0.021
0.099
0.116
128.5
68.5
4.7
0.049
0.024
0.089
0.114
40.857
25.45
0.007
0.026
0.122
0.153
50
31.1
4.5
0.018
0.072
0.084
38.8
25.91
0.002
0.007
4.6
0.214
0.013
0.086
0.111
41.4
25.02
0.01
0.047
47
27.5
0.082
0.096
35
20.65
0.001
0.006
6.6
0.067
0.103
69
40.6
0.11
0.151
43
25.6
4.725
0.016
0.07
0.087
36.4
24.05
0.002
0.006
5.1
0.102
0.013
0.077
0.095
38.6
23.52
0.011
0.053
38
26
0.078
0.092
32
18.9
0.001
0.006
5.55
0.065
0.093
48
24.4
5.3
0.022
0.098
0.116
106.5
61
0.102
0.135
43
26.6
4.638
0.018
0.075
0.09
32.8
22.26
0.002
0.005
3.85
0.203
0.013
0.075
0.108
40
25.9
0.006
0.026
43
26
0.067
0.085
30
16.3
0.002
0.012
5.55
0.071
0.1
36
22.5
3.05 2.3
0.032 0.014
2.45
0.01
0.015 0.014 0.014
0.104 0.099 0.089
0.136 0.128 0.123
55.6 48.6
35.9
46.8
31.2 27.36
0.086 0.078 0.081
0.099 0.099 0.098
0.107 0.087 0.103
0.124 0.103 0.121
0.007 0.006 0.006
0.023 0.021 0.019
4.3
0.02
0.1
0.125
82.5
50.75
3.5
0.023
0.107
0.138
89.5
48.7
4.6 4.088 4.675
0.032 0.019 0.019
0.024 0.024 0.024
0.097 0.086 0.096
0.122 0.107 0.12
40.214 36.286 37.214
25.55 23.086 22.35
0.007 0.008 0.008
0.026 0.029 0.026
0.103
0.14
52
29.1
4.575
0.019
0.073
0.088
32.7
22.12
0.002
0.004
3.85
0.098
0.013
0.086
0.111
42
25.58
0.004
0.025
41
25.9
0.072
0.085
28.5
16.25
0.002
0.012
5.2
0.068
0.096
32
21.2
2.75
0.01
0.014
0.095
0.126
46.6
30.02
0.107
0.132
38
23.9
4.375
0.019
0.077
0.094
40.9
26.22
0.002
0.004
3.35
0.091
0.01
0.095
0.119
44.2
26.24
0.008
0.034
48
27.4
0.077
0.092
26
15.05
0.002
0.008
4.2
0.079
0.108
32
19
3.15
0.01
0.014
0.095
0.126
48.6
28.12
0.075 0.087
0.094 0.104
0.086 0.091
0.102 0.126
0.005 0.004
0.032 0.016
4
0.023
0.108
0.137
62.5
42.1
4.15
0.019
0.023
0.088
0.116
38.786
21.236
0.007
0.029
4.2
0.023
0.1
0.118
72
44.3
4.163
0.021
0.021
0.095
0.12
36.214
21.707
0.006
0.019
0.09
0.121
40
26.7
4.075
0.018
0.073
0.086
36.1
25.35
0.001
0.004
5.25
0.114
0.012
0.086
0.11
40
26.22
0.008
0.042
41
26.2
0.063
0.075
27.5
15.95
0.002
0.009
4.15
0.074
0.104
25
17.3
2.35
0.008
0.013
0.099
0.127
43.8
27.52
0.106
0.126
40
27
3.7
0.018
0.071
0.085
38.3
25.79
0.002
0.004
5.65
0.015
0.012
0.08
0.106
37.8
24.18
0.008
0.028
41
25.2
0.073
0.085
26
15.1
0.002
0.006
4.4
0.06
0.082
22
16.1
2.35
0.008
0.012
0.085
0.11
48.2
30.22
0.095
0.113
35
23.9
3.325
0.017
0.071
0.088
39.4
25.88
0.002
0.004
3.9
0.015
0.012
0.089
0.11
37.8
24.18
0.01
0.034
44
28.3
0.073
0.088
29.5
16.6
0.001
0.005
4.2
0.071
0.106
33
17.2
2.25
0.006
0.011
0.087
0.116
40.6
23.24
3.9
0.018
0.104
0.131
70
40.25
3.725
0.013
0.021
0.083
0.106
33.5
20.336
0.007
0.031
3.5
0.019
0.096
0.114
63
40.4
3.788
0.01
0.021
0.091
0.116
33.071
20.207
0.007
0.022
0.113
0.149
36
20.6
3.1
0.018
0.069
0.084
49.3
31.3
0.002
0.005
3.3
0.015
0.014
0.088
0.112
37.8
24.18
0.008
0.051
51
28.1
0.076
0.087
29.5
16.35
0.001
0.007
4.15
0.078
0.108
40
19.6
1.9
0.006
0.013
0.079
0.099
47.6
29.28
0.071 0.078 0.073 0.086
0.087 0.092 0.093 0.102
0.086 0.104 0.098 0.096
0.105 0.115 0.117 0.117
0.005 0.004 0.004 0.003
0.016 0.018 0.012 0.012
3.6
0.017
0.102
0.13
63.5
38.3
3.113
0.013
0.022
0.099
0.119
35.5
20.893
0.007
0.02
3.9
0.021
0.099
0.116
82.5
45.8
3.3
0.013
0.021
0.096
0.118
34.286
20.614
0.007
0.02
216
DATA TABLES • APPENDIX A
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-16. Metropolitan Statistical Area Air Quality Trends, 1990-1999 (continued)
Metropolitan Statistical Area Trend #Trend 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
Sites
WATERBURY, CT
PM10
90th percentile
Down
2
56.5
48.5
43.5
44.5
weighted annual mean
Down
2
34
29.7
23.15
23.55
so2
arithmetic mean
Down
1
0.01
0.009
0.007
0.006
2nd max 24-hour
Down
1
0.042
0.038
0.029
0.021
WATERLOO-CEDAR FALLS, IA
PM10
90th percentile
Down
1
57
57
63
48
weighted annual mean
Down
1
34.7
34.7
34.3
31.2
WAUSAU, Wl
o3
4th max 8-hour
NS
1
0.081
0.081
0.081
0.06
2nd daily max 1-hour
NS
1
0.086
0.086
0.086
0.081
so2
arithmetic mean
Down
1
0.004
0.004
0.004
0.004
2nd max 24-hour
NS
1
0.03
0.03
0.024
0.039
WEST PALM BEACH-BOCA RATON, FL
CO
2nd max 8-hour
NS
1
2.7
3.1
3.7
3.1
NO,
arithmetic mean
NS
1
0.014
0.012
0.011
0.013
o3
4th max 8-hour
NS
2
0.066
0.062
0.048
0.077
2nd daily max 1-hour
NS
2
0.092
0.081
0.067
0.117
PM10
90th percentile
NS
2
27
27.5
30
29
weighted annual mean
NS
2
18.95
18.45
19.9
18.85
so2
arithmetic mean
Down
1
0.002
0.002
0.003
0.004
2nd max 24-hour
NS
1
0.007
0.012
0.01
0.028
WHEELING, WV-OH
CO
2nd max 8-hour
Down
1
7.1
5.6
5.6
4.1
o3
4th max 8-hour
NS
1
0.08
0.089
0.075
0.077
2nd daily max 1-hour
NS
1
0.111
0.108
0.096
0.11
PM10
90th percentile
Down
2
50
52.5
51.5
51
weighted annual mean
Down
2
29.5
30.65
30.4
29.35
so2
arithmetic mean
Down
3
0.02
0.02
0.018
0.018
2nd max 24-hour
Down
3
0.064
0.074
0.077
0.075
WICHITA, KS
CO
2nd max 8-hour
Down
3
5.933
5.917
5.633
5
Pb
max quarterly mean
Down
5
0.017
0.02
0.012
0.014
o3
4th max 8-hour
NS
2
0.079
0.076
0.067
0.06
2nd daily max 1-hour
NS
2
0.095
0.09
0.078
0.075
PM10
90th percentile
NS
4
48.75
51
52.5
55.5
weighted annual mean
Down
4
27.7
31.35
32.25
31.425
WILLIAMSPORT, PA
o3
4th max 8-hour
NS
1
0.071
0.081
0.073
0.075
2nd daily max 1-hour
NS
1
0.088
0.101
0.092
0.088
PM10
90th percentile
NS
1
50
60
36
47
weighted annual mean
NS
1
26
30.7
23.8
23.9
so2
arithmetic mean
NS
1
0.006
0.007
0.007
0.006
2nd max 24-hour
NS
1
0.025
0.025
0.029
0.025
WILMINGTON-NEWARK, DE-MD
CO
2nd max 8-hour
NS
1
5.4
4
4.1
3.8
no2
arithmetic mean
NS
1
0.017
0.017
0.017
0.019
o3
4th max 8-hour
NS
3
0.098
0.1
0.094
0.101
2nd daily max 1-hour
NS
3
0.123
0.121
0.118
0.141
PM10
90th percentile
Down
2
47.5
44.75
39
42.5
weighted annual mean
Down
2
30.05
27.65
24.45
24.8
so2
arithmetic mean
Down
3
0.014
0.013
0.014
0.013
2nd max 24-hour
Down
3
0.053
0.046
0.054
0.047
WORCESTER, MA-CT
CO
2nd max 8-hour
Down
1
6
7.2
8
6.1
no2
arithmetic mean
Down
1
0.022
0.023
0.024
0.028
o3
4th max 8-hour
NS
1
0.097
0.097
0.097
0.092
2nd daily max 1-hour
Down
1
0.125
0.125
0.125
0.155
PM10
90th percentile
Down
2
41
37.667 34.333
37
weighted annual mean
NS
2
22.95
21.267 19.583
19.5
so2
arithmetic mean
Down
1
0.008
0.009
0.007
0.007
2nd max 24-hour
Down
1
0.034
0.029
0.033
0.025
YAKIMA, WA
PM10
90th percentile
Down
2
61.5
80.5
59.5
63
weighted annual mean
Down
2
33.1
40.15
32.45
34.85
YOLO, CA
o3
4th max 8-hour
NS
1
0.082
0.073
0.085
0.076
2nd daily max 1-hour
NS
1
0.1
0.105
0.11
0.09
PM10
90th percentile
Down
1
81
81
63
62
weighted annual mean
Down
1
46.4
46.4
34.7
29.2
43
26.15
0.007
0.03
45
28.7
40
24.1
0.005
0.019
52
35.5
2.8
0.012
0.071
0.084
24.5
18.1
0.003
0.016
4.6
0.078
0.095
49
27.7
0.015
0.065
4.933
0.008
0.07
0.085
49.75
26.4
52
27.8
4.3
0.019
0.094
0.119
52
29.45
0.012
0.048
5.9
0.025
0.097
0.125
36
19.9
0.008
0.024
54.5
29.1
0.076
0.097
46
29.8
46.5
25.95
0.005
0.022
48
31.8
0.064 0.075
0.077 0.088
0.004 0.003
0.024 0.022
2.8
0.012
0.064
0.082
24.5
17.6
0.002
0.019
5
0.089
0.104
45.5
28.25
0.01
0.055
5.233
0.01
0.073
0.095
50.75
27.1
0.069 0.073
0.079 0.091
49
27.6
0.006 0.006
0.042 0.027
4.6
0.017
0.112
0.142
44.5
27.8
0.011
0.057
4.2
0.021
0.096
0.118
31.5
19.45
0.006
0.023
0.083
0.108
61
30.1
37.5
23.65
0.005
0.02
47
31.3
32.5
22
0.006
0.021
47
29.9
2.5
0.012
0.064
0.088
27.5
18.45
0.002
0.014
3.5
0.087
0.105
42
27.6
0.011
0.058
5.8
0.011
0.071
0.093
42.5
24.85
3.6
0.012
0.064
0.082
29
19.8
0.002
0.013
3.1
0.082
0.11
40.5
23.75
0.01
0.043
4.8
0.009
0.079
0.093
40
22.45
36
25.1
40
25.6
3.6
0.019
0.088
0.111
41.5
25.4
0.01
0.045
5.3
0.019
0.074
0.091
33.5
20.25
0.005
0.021
45.5 58.5
23.55 30.375
0.087
0.113
40
24.3
4.5
0.018
0.104
0.136
42.5
25.4
0.008
0.041
3.4
0.019
0.092
0.106
31.5
19.55
0.004
0.021
59
31.6
0.068
0.092
37
24.6
32
19.7
0.005
0.02
44
24.1
0.07 0.069 0.077 0.084
0.079 0.08 0.098 0.095
0.003 0.002 0.003 0.003
0.015 0.013 0.031 0.04
2.5
0.012
0.077
0.096
31
20.35
0.001
0.004
3.5
0.087
0.104
46
24.9
0.011
0.045
4.833
0.009
0.081
0.096
40.5
24.2
2.8
0.013
0.061
0.08
29
19.6
0.002
0.013
3
0.088
0.1
46.5
25.65
0.01
0.042
4.167
0.009
0.078
0.093
49.25
25.7
0.07 0.076 0.073 0.075
0.082 0.086 0.097 0.087
40
25.6
40
25.6
0.006 0.008 0.005 0.005
0.028 0.028 0.021 0.021
3.1
0.016
0.095
0.122
40.5
24
0.008
0.032
3.5
0.019
0.097
0.124
32.5
19.2
0.005
0.017
42.5
25.75
0.087
0.109
42
21.7
3.1
0.018
0.102
0.139
38.5
22.95
0.007
0.035
3.3
0.02
0.093
0.113
36
20.5
0.004
0.013
38.5
22.4
0.088
0.115
65
30.6
APPENDIX A • DATA TABLES
217
-------
NATIONALAIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-16. Metropolitan Statistical Area Air Quality Trends, 1990-1999 (continued)
Metropolitan Statistical Area
Trend
#Trend
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
Sites
YORK, PA
CO
2nd max 8-hour
Down
1
4.4
3.7
3.6
3.3
3.9
2.7
2.8
3.4
2.4
2.4
Pb
max quarterly mean
NS
1
0.051
0.051
0.046
0.044
0.042
0.04
0.065
0.044
0.049
0.049
NO,
arithmetic mean
Down
1
0.022
0.021
0.02
0.022
0.024
0.021
0.021
0.019
0.019
0.019
o3
4th max 8-hour
NS
1
0.097
0.1
0.079
0.09
0.082
0.086
0.081
0.094
0.095
0.094
2nd daily max 1-hour
NS
1
0.121
0.114
0.101
0.112
0.115
0.097
0.098
0.109
0.112
0.121
PM10
90th percentile
NS
1
56
60
44
52
51
56
46
49
49
49
weighted annual mean
NS
1
29.7
32.2
27
30.5
31.7
29.7
28.4
31.2
31.2
31.2
so2
arithmetic mean
NS
1
0.007
0.008
0.007
0.008
0.009
0.006
0.007
0.009
0.008
0.007
2nd max 24-hour
NS
1
0.023
0.02
0.034
0.032
0.041
0.02
0.022
0.026
0.023
0.019
YOUNGSTOWN-WARREN, OH
o3
4th max 8-hour
NS
3
0.09
0.096
0.092
0.085
0.083
0.096
0.09
0.089
0.099
0.094
2nd daily max 1-hour
NS
3
0.105
0.111
0.106
0.106
0.096
0.11
0.104
0.105
0.115
0.108
PM10
90th percentile
Down
9
53
54.889
48.556
49.333
49
48.222
39.333
42.778
46.667
44
weighted annual mean
Down
9
31.267
33.022
28.544
27.389
29.033
28.089
26.011
25.389
27.267
25.867
so2
arithmetic mean
Down
2
0.016
0.016
0.013
0.011
0.011
0.01
0.009
0.008
0.008
0.008
2nd max 24-hour
Down
2
0.053
0.048
0.056
0.064
0.051
0.038
0.044
0.037
0.03
0.034
YUBA CITY, CA
CO
2nd max 8-hour
Down
1
5.8
5.8
5.8
5
5.6
4.1
4.1
3.9
3.9
4.2
NO,
arithmetic mean
Down
1
0.017
0.017
0.017
0.018
0.016
0.014
0.012
0.014
0.013
0.014
o3
4th max 8-hour
NS
2
0.076
0.079
0.088
0.081
0.082
0.087
0.086
0.073
0.087
0.084
2nd daily max 1-hour
NS
2
0.1
0.1
0.11
0.11
0.099
0.107
0.105
0.093
0.103
0.105
PM10
90th percentile
NS
1
60
73
57
59
51
68
50
48
44
68
weighted annual mean
Down
1
38.5
38.5
34.3
30.4
34.1
32.5
29.2
28.6
23.1
38.4
CO = Highest second maximum non-overlapping 8-hour concentration (Applicable NAAQS is 9 ppm)
Pb = Highest quarterly maximum concentration (Applicable NAAQS is 1.5 pg/m3)
N02 = Highest arithmetic mean concentration (Applicable NAAQS is 0.053 ppm)
03 (1-hr) = Highest second daily maximum 1-hour concentration (Applicable NAAQS is 0.12 ppm)
03 (8-hr) = Highest fourth daily maximum 8-hour concentration (Applicable NAAQS is 0.08 ppm)
PM10 = Highest second maximum 24-hour concentration (Applicable NAAQS is 150 pg/m3)
S02 = Highest second maximum 24-hour concentration (Applicable NAAQS is 0.14 ppm)
ppm = Units are parts per million
|jg/m3 = Units are micrograms per cubic meter
218
DATA TABLES • APPENDIX A
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-17. Number of Days with AQI Values Greater Than 100 at Trend Sites, 1990-1999,
and All Sites in 1999
#of
Total
AQI
Metropolitan Statistical Area
Trend
#of
> 10C
Sites
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
Sites
1999
AKRON, OH
5
9
30
8
10
8
12
11
6
14
20
6
20
ALBANY-SCHENECTADY-TROY, NY
10
4
9
5
5
6
3
4
3
2
6
10
6
ALBUQUERQUE, NM
21
8
5
0
0
1
0
0
0
0
1
21
2
ALLENTOWN-BETHLEHEM-EASTON, PA
5
10
14
3
6
3
9
6
13
18
20
9
23
ATLANTA, GA
10
42
23
20
36
15
35
25
31
50
61
18
69
AUSTIN-SAN MARCOS, TX
1
4
3
1
2
4
10
0
0
5
8
3
19
BAKERSFIELD, CA
8
99
113
100
97
98
105
109
55
76
88
14
94
BALTIMORE, MD
17
29
50
23
48
41
36
28
30
51
40
20
40
BATON ROUGE, LA
7
28
11
5
6
7
15
7
8
14
17
10
26
BERGEN-PASSAIC, NJ
7
8
11
2
3
5
11
3
5
0
0
7
0
BIRMINGHAM,AL
14
28
5
12
10
6
32
15
8
23
27
14
27
BOSTON, MA-NH
24
7
13
9
6
10
8
2
8
7
5
24
9
BUFFALO-NIAGARA FALLS, NY
20
7
9
3
1
4
6
3
1
13
8
20
8
CHARLESTON-NORTH CHARLESTON, SC
9
1
2
0
2
2
1
3
3
3
5
9
5
CHARLOTTE-GASTONIA-ROCK HILL, NC-SC
12
31
12
11
23
9
13
18
26
48
34
24
42
CHICAGO, IL
45
4
22
4
3
8
21
6
9
7
12
51
12
CINCINNATI, OH-KY-IN
19
12
19
1
6
16
19
10
11
14
12
23
27
CLEVELAND-LORAIN-ELYRIA, OH
27
10
23
11
13
23
24
18
11
20
18
40
23
COLUMBUS, OH
9
4
17
5
7
10
15
16
8
19
20
12
25
DALLAS, TX
9
24
2
12
14
27
36
12
20
28
23
9
35
DAYTON-SPRINGFIELD, OH
10
13
12
2
11
14
11
18
9
19
19
13
20
DENVER,CO
22
9
6
11
3
1
2
0
0
5
1
28
5
DETROIT, Ml
29
11
28
8
5
11
14
13
12
17
15
29
15
EL PASO, TX
19
19
7
10
7
11
8
7
4
6
6
24
7
FORT LAUDERDALE, FL
15
1
0
2
4
1
1
1
0
1
1
18
1
FORT WORTH-ARLINGTON, TX
5
16
20
7
9
31
28
14
14
17
19
5
19
FRESNO, CA
12
62
83
69
59
55
61
70
75
67
81
15
83
GARY, IN
15
2
8
5
0
6
17
11
12
9
10
18
12
GRAND RAPIDS-MUSKEGON-HOLLAND, Ml
8
10
26
6
3
12
17
7
8
13
20
9
21
GREENSBORO—WINSTON-SALEM—HIGH POINT, NC
9
12
5
2
20
7
6
6
13
25
20
15
29
GREENVILLE-SPARTANBURG-ANDERSON, SC 5
2
3
5
9
5
8
7
10
28
19
7
19
HARRISBURG-LEBANON-CARLISLE, PA
6
10
21
1
15
12
13
3
9
22
17
6
17
HARTFORD,CT
15
13
23
15
14
18
14
5
16
10
18
15
18
HONOLULU, HI
10
0
0
0
0
0
0
0
0
0
0
14
0
HOUSTON, TX
23
51
36
32
28
38
66
26
47
38
50
23
54
INDIANAPOLIS, IN
27
9
12
7
9
22
19
13
12
19
21
32
26
JACKSONVILLE, FL
14
3
0
2
3
2
1
1
4
10
3
14
3
JERSEY CITY, NJ
7
15
26
11
19
17
18
5
9
7
17
7
17
KANSAS CITY, MO-KS
21
2
11
1
4
10
22
10
18
15
5
21
5
KNOXVILLE, TN
15
23
10
7
25
16
24
20
36
54
59
18
62
LAS VEGAS, NV-AZ
5
4
0
1
2
2
0
2
0
0
0
26
7
LITTLE ROCK-NORTH LITTLE ROCK, AR
7
1
3
0
2
2
7
1
1
2
6
7
6
LOS ANGELES-LONG BEACH, CA
38
173
168
175
134
139
113
94
60
56
27
38
27
LOUISVILLE, KY-IN
20
10
15
2
23
27
22
11
14
27
40
26
44
MEMPHIS, TN-AR-MS
12
24
9
14
15
10
21
19
17
27
36
14
36
MIAMI, FL
12
1
1
3
6
1
2
1
3
8
5
12
5
MIDDLESEX-SOMERSET-HUNTERDON, NJ
3
24
24
8
13
9
16
8
18
21
23
5
26
MILWAUKEE-WAUKESHA, Wl
18
8
24
3
4
9
14
5
4
10
13
22
18
APPENDIX A • DATA TABLES
219
-------
NATIONALAIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-17. Number of Days with AQI Values Greater Than 100 at Trend Sites, 1990-1999,
and All Sites in 1999 (continued)
#
of
Total
AQI
Metropolitan Statistical Area Trend
#of
> 100
Sites
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
Sites
1999
MINNEAPOLIS-ST. PAUL, MN-WI
20
4
2
1
0
2
5
0
0
1
0
36
0
MONMOUTH-OCEAN, NJ
4
21
20
11
24
13
20
17
21
31
27
4
27
NASHVILLE, TN
16
29
12
6
18
21
26
22
20
30
33
21
45
NASSAU-SUFFOLK, NY
7
20
25
7
17
15
10
8
12
11
18
7
18
NEWHAVEN-MERIDEN, CT
9
17
29
10
17
14
14
8
19
10
16
9
16
NEWORLEANS, LA
10
6
2
5
6
8
20
8
7
7
18
10
18
NEW YORK, NY
29
36
49
10
19
21
19
15
23
17
24
30
27
NEWARK, NJ
12
23
35
10
13
13
20
12
13
23
21
12
21
NORFOLK-VIRGINIA BEACH-NEWPORT NEWS,VA-NC
10
8
7
8
19
6
6
4
17
15
16
12
16
OAKLAND, CA
18
4
4
3
4
3
12
11
0
11
5
29
6
OKLAHOMA CITY, OK
10
4
4
2
2
5
13
2
4
7
6
10
6
OMAHA, NE-IA
9
1
0
0
1
1
1
1
0
5
5
12
5
ORANGE COUNTY, CA
11
45
35
35
25
15
9
9
3
6
1
12
1
ORLANDO, FL
11
4
1
4
4
3
1
1
4
11
4
13
4
PHILADELPHIA, PA-NJ
36
39
49
24
51
26
30
22
32
37
32
44
32
PHOENIX-MESA, AZ
25
12
11
13
16
10
22
17
12
17
12
51
37
PITTSBURGH, PA
42
19
21
9
13
19
25
11
21
39
23
42
26
PONCE, PR
1
0
0
0
0
0
0
0
0
0
0
1
0
PORTLAND-VANCOUVER, OR-WA
15
11
9
6
0
2
2
6
0
3
2
15
2
PROVIDENCE-FALL RIVER-WARWICK, RI-MA
9
13
20
5
7
7
11
4
10
4
7
12
13
RALEIGH-DURHAM-CHAPEL HILL, NC
5
15
5
0
11
2
1
1
13
21
26
17
29
RICHMOND-PETERSBURG, VA
11
6
18
8
30
13
19
5
21
28
25
11
25
RIVERSIDE-SAN BERNARDINO, CA
36
159
154
174
168
149
124
119
105
95
93
47
97
ROCHESTER, NY
8
5
16
2
0
1
6
0
6
4
9
8
9
SACRAMENTO, CA
20
61
46
51
20
36
41
42
15
27
38
33
48
ST. LOUIS, MO-IL
55
23
32
15
9
32
34
20
15
23
29
55
29
SALT LAKE CITY-OGDEN, UT
13
5
20
9
5
12
4
8
1
12
2
24
5
SAN ANTON IO, TX
4
4
3
1
3
4
18
3
3
6
9
4
9
SAN DIEGO, CA
23
96
67
66
58
46
48
31
14
33
16
27
17
SAN FRANCISCO, CA
9
0
0
0
0
0
2
0
0
0
0
11
0
SAN JOSE, CA
8
7
11
3
4
2
10
7
0
5
2
9
4
SAN JUAN-BAYAMON, PR
11
0
0
0
0
0
0
1
2
1
1
21
3
SCRANTON-WILKES-BARRE-HAZLETON, PA
11
9
17
3
10
7
12
4
11
7
12
11
12
SEATTLE-BELLEVUE-EVERETT, WA
17
9
4
3
0
3
0
6
1
3
1
24
1
SPRINGFIELD, MA
13
13
15
12
13
12
9
5
10
7
10
13
10
SYRACUSE, NY
7
1
12
2
4
1
5
0
2
3
4
7
4
TACOMA, WA
8
5
1
2
0
2
0
1
0
4
0
9
0
TAMPA-ST. PETERSBURG-CLEARWATER, FL
26
6
1
2
1
3
2
3
4
11
9
40
9
TOLEDO,OH
5
3
6
2
7
9
9
11
4
5
4
6
9
TUSCON, AZ
20
1
0
1
1
0
3
0
1
0
2
21
2
TULSA, OK
11
16
12
1
4
12
21
14
7
9
14
11
14
VENTURA, CA
12
70
87
54
43
63
66
62
45
29
22
15
23
WASHINGTON, DC-MD-VA-WV
40
25
48
14
52
20
29
18
29
47
39
42
39
WEST PALM BEACH-BOCA RATON, FL
6
0
0
0
3
0
0
0
0
2
1
7
1
WILMINGTON-NEWARK, DE-MD
9
9
12
12
29
24
27
13
21
24
21
10
21
YOUNGSTOWN-WARREN, OH
14
3
14
10
10
5
12
8
10
22
12
15
13
220
DATA TABLES • APPENDIX A
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-18. (Ozone only) Number of Days with AQI Values Greater Than 100 at Trend Sites, 1990-1999,
and All Sites in 1999
#of
Total
AQI
Metropolitan Statistical Area
Trend
#of
> 100
Sites
1988
1989
1990
1993
1993
1993
1998
1998
1998
1999
Sites
1999
AKRON, OH
2
9
30
8
10
8
12
11
6
14
20
2
20
ALBANY-SCHENECTADY-TROY, NY
3
4
9
5
5
6
3
4
3
2
6
3
6
ALBUQUERQUE, NM
7
2
0
0
0
1
0
0
0
0
1
9
2
ALLENTOWN-BETHLEHEM-EASTON, PA
2
10
14
3
6
3
9
6
13
18
20
3
23
ATLANTA, GA
3
42
23
20
36
15
35
25
31
50
61
7
69
AUSTIN-SAN MARCOS, TX
1
4
3
1
2
4
10
0
0
5
8
2
19
BAKERSFIELD, CA
5
95
107
100
97
98
104
109
55
75
87
6
92
BALTIMORE, MD
7
28
50
23
48
40
36
28
30
51
40
8
40
BATON ROUGE, LA
3
28
11
5
5
7
15
7
8
14
17
7
26
BERGEN-PASSAIC, NJ
1
8
11
2
3
5
11
3
5
0
0
1
0
BIRMINGHAM, AL
6
28
5
12
10
6
32
15
8
23
27
6
27
BOSTON, MA-NH
4
7
13
9
6
10
8
2
8
7
5
4
9
BUFFALO-NIAGARA FALLS, NY
2
7
9
3
1
4
6
3
1
13
8
2
8
CHARLESTON-NORTH CHARLESTON, SC
3
1
1
0
2
2
1
3
3
3
5
3
5
CHARLOTTE-GASTONIA-ROCK HILL, NC-SC
3
29
12
11
23
9
13
18
26
48
34
7
42
CHICAGO, IL
17
3
22
4
3
7
21
6
9
7
12
22
12
CINCINNATI, OH-KY-IN
6
12
19
1
6
16
19
10
11
14
12
7
27
CLEVELAND-LORAIN-ELYRIA, OH
6
10
23
10
12
22
21
17
11
19
17
9
22
COLUMBUS, OH
3
4
17
5
7
10
15
16
8
19
20
5
25
DALLAS, TX
3
24
2
12
14
27
36
12
20
28
23
5
35
DAYTON-SPRINGFIELD, OH
3
13
12
2
11
14
11
18
9
19
19
5
20
DENVER,CO
6
4
0
4
0
0
0
0
0
5
0
8
3
DETROIT, Ml
8
11
28
7
5
11
12
12
12
17
14
8
14
EL PASO, TX
4
6
1
3
3
7
7
2
1
6
1
4
1
FORT LAUDERDALE, FL
3
1
0
2
4
1
1
1
0
1
1
3
1
FORT WORTH-ARLINGTON, TX
2
16
20
7
9
31
28
14
14
17
19
2
19
FRESNO, CA
5
56
81
69
59
55
61
70
75
67
81
7
83
GARY, IN
2
2
8
5
0
6
17
11
11
9
10
4
12
GRAND RAPIDS-MUSKEGON-HOLLAND, Ml
4
10
26
6
3
12
17
7
8
13
20
4
21
GREENSBORO—WINSTON-SALEM—HIGH POINT, NC
2
12
5
2
20
7
6
6
13
25
20
6
29
GREENVILLE-SPARTANBURG-ANDERSON, SC 4
2
3
5
9
5
8
7
10
28
19
4
19
HARRIS BURG-LEBANON-CAR LISLE, PA
3
10
21
1
15
12
13
3
9
22
17
3
17
HARTFORD,CT
3
13
21
14
14
18
13
5
16
10
18
3
18
HONOLULU, HI
1
0
0
0
0
0
0
0
0
0
0
1
0
HOUSTON, TX
9
51
36
32
28
38
66
26
47
38
50
11
54
INDIANAPOLIS, IN
6
9
11
6
9
22
19
13
12
19
21
9
26
JACKSONVILLE, FL
2
3
0
2
3
2
1
1
4
10
3
2
3
JERSEY CITY, NJ
1
15
25
9
19
12
16
5
9
7
17
1
17
KANSAS CITY, MO-KS
6
2
11
1
3
10
22
9
18
15
5
6
5
KNOXVILLE, TN
5
23
10
7
25
16
24
20
36
54
59
7
62
LAS VEGAS, NV-AZ
3
2
0
1
2
2
0
2
0
0
0
4
0
LITTLE ROCK-NORTH LITTLE ROCK, AR
2
1
3
0
2
2
7
1
1
2
6
2
6
LOS ANGELES-LONG BEACH, CA
14
130
126
140
112
117
97
74
45
46
19
14
19
LOUISVILLE, KY-IN
5
10
15
2
22
27
22
11
14
27
40
7
44
MEMPHIS, TN-AR-MS
4
22
9
13
13
10
21
18
17
27
36
4
36
MIAMI, FL
4
1
1
3
6
1
2
1
3
8
5
4
5
MIDDLESEX-SOMERSET-HUNTERDON, NJ
1
24
24
8
13
9
16
8
18
21
23
2
26
MILWAUKEE-WAUKESHA, Wl
8
8
24
3
4
9
14
5
4
10
12
9
17
APPENDIX A • DATA TABLES
221
-------
NATIONALAIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-18. (Ozone only) Number of Days with AQI Values Greater Than 100 at Trend Sites, 1990-1999,
and All Sites in 1999 (continued)
#of
Total
AQI
Metropolitan Statistical Area Trend
#of
> 100
Sites
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
Sites
1999
MINNEAPOLIS-ST. PAUL, MN-WI
4
1
0
1
0
0
3
0
0
1
0
5
0
MONMOUTH-OCEAN, NJ
2
21
20
11
24
13
20
17
21
31
27
2
27
NASHVILLE, TN
6
29
12
6
18
21
26
22
20
30
33
8
45
NASSAU-SUFFOLK, NY
2
20
25
7
17
15
10
8
12
11
18
2
18
NEWHAVEN-MERIDEN, CT
2
15
28
10
13
13
14
8
19
10
16
2
16
NEWORLEANS, LA
6
6
2
5
6
8
20
8
7
7
18
6
18
NEW YORK, NY
5
33
47
10
19
21
18
15
23
17
24
8
27
NEWARK, NJ
2
22
32
10
13
12
20
12
13
23
21
2
21
NORFOLK-VIRGINIA BEACH-NEWPORT NEWS,VA-NC
3
8
7
8
19
6
6
4
17
15
16
3
16
OAKLAND, CA
7
4
3
3
4
3
12
11
0
11
5
9
6
OKLAHOMA CITY, OK
4
4
4
2
2
5
13
2
4
7
6
4
6
OMAHA, NE-IA
3
1
0
0
0
0
0
0
0
0
2
3
2
ORANGE COUNTY, CA
4
38
35
35
25
15
8
9
3
6
1
4
1
ORLANDO, FL
3
4
1
4
4
3
1
1
4
11
4
4
4
PHILADELPHIA, PA-NJ
8
39
49
24
51
25
30
22
32
37
32
10
32
PHOENIX-MESA, AZ
8
7
7
11
16
7
19
17
10
17
12
18
27
PITTSBURGH, PA
8
11
20
8
13
19
24
11
20
39
23
12
26
PONCE, PR
0
0
0
0
0
0
0
0
0
0
0
0
0
PORTLAND-VANCOUVER, OR-WA
4
8
3
6
0
1
2
6
0
3
0
4
0
PROVIDENCE-FALL RIVER-WARWICK, RI-MA
2
13
20
5
7
7
11
4
10
4
7
3
13
RALEIGH-DURHAM-CHAPEL HILL, NC
1
15
5
0
11
2
1
1
13
21
26
8
29
RICHMOND-PETERSBURG, VA
4
6
18
8
30
13
19
5
21
28
25
4
25
RIVERSIDE-SAN BERNARDINO, CA
15
153
152
172
167
148
119
116
102
94
93
18
97
ROCHESTER, NY
2
5
16
2
0
1
6
0
6
4
9
2
9
SACRAMENTO, CA
8
42
36
50
20
36
41
42
15
27
38
13
48
ST. LOUIS, MO-IL
16
23
32
15
9
31
34
20
14
23
29
16
29
SALT LAKE CITY-OGDEN, UT
2
5
3
0
2
4
4
6
1
12
2
7
5
SAN ANTON IO, TX
2
4
3
1
3
4
18
3
3
6
9
2
9
SAN DIEGO, CA
9
96
67
66
58
46
48
31
14
33
16
10
17
SAN FRANCISCO, CA
3
0
0
0
0
0
2
0
0
0
0
3
0
SAN JOSE, CA
4
4
5
3
4
2
10
7
0
5
2
6
4
SAN JUAN-BAYAMON, PR
0
0
0
0
0
0
0
0
0
0
0
1
0
SCRANTON-WILKES-BARRE-HAZLETON, PA
4
9
17
3
10
7
12
4
11
7
12
4
12
SEATTLE-BELLEVUE-EVERETT, WA
2
7
3
3
0
3
0
6
1
3
1
3
1
SPRINGFIELD, MA
4
13
15
12
13
12
9
4
10
7
10
4
10
SYRACUSE, NY
2
0
12
2
4
1
5
0
2
3
4
2
4
TACOMA, WA
1
4
0
2
0
2
0
1
0
4
0
2
0
TAMPA-ST. PETERSBURG-CLEARWATER, FL
7
6
1
2
1
3
2
3
4
11
9
7
9
TOLEDO,OH
3
3
6
2
7
9
9
11
4
5
4
3
9
TUSCON, AZ
5
1
0
1
1
0
3
0
1
0
1
6
1
TULSA, OK
3
16
12
1
4
12
21
14
7
9
14
3
14
VENTURA, CA
6
70
87
54
43
63
66
62
44
29
22
7
23
WASHINGTON, DC-MD-VA-WV
13
25
48
14
52
20
29
18
29
47
39
17
39
WEST PALM BEACH-BOCA RATON, FL
2
0
0
0
3
0
0
0
0
2
1
2
1
WILMINGTON-NEWARK, DE-MD
3
9
12
12
29
24
27
13
21
24
21
4
21
YOUNGSTOWN-WARREN, OH
3
3
14
10
10
5
12
8
10
22
12
3
12
222 DATA TABLES • APPENDIX A
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
TableA-19. Condensed Nonattainment Areas List(a)
State
Area Name(b)
Pollutant(c)
CO SO,
pmh,
Pb NO,
Population (x 1000) (d)
CO SO, PMh
Pb All
AK
AK
AK
AL
AZ
AZ
AZ
8 AZ
9 AZ
10 AZ
11 AZ
12 AZ
13 AZ
14 AZ
15 AZ
16 AZ
17 CA
18 CA
19 CA
20 CA
21 CA
22 CA
23 CA
24 CA
25 CA
26 CA
27 CA
28 CA
29 CO
30 CO
31 CO
32 CO
33 CO
34 CO
35 CO
36 CT
37 DC-MD-VA
38 GA
39 GU
40 GU
41 ID
42 ID
43 ID
44 ID
45 IL-IN
46 KY
47 KY-IN
48 LA
49 MA
50 MD
51 MD
Anchorage
Fairbanks
Juneau
Birmingham
Ajo
Bullhead City
Douglas
Miami-Hayden
Morenci
Nogales
Paul Spur
Payson
Phoenix 1
Rillito
San Manuel
Yuma
Imperial Valley
Los Angeles-South Coast Air Basin 1
Mono Basin (in Mono Co.)
Owens Valley
Sacramento Metro 1
San Diego 1
San Francisco-Oakland-San Jose 1
San Joaquin Valley 1
Santa Barbara-Santa Maria-Lompoc 1
Searles Valley
Southeast Desert Modified AQMA 1
Ventura Co. 1
Aspen
Denver-Boulder
Fort Collins
Lamar
Pagosa Springs
Steamboat Springs
Telluride
Greater Connecticut 1
Washington 1
Atlanta 1
Piti Power Plant
Tanguisson Power Plant
Bonner Co.(Sandpoint)
Fort Hall I.R.
Portneuf Valley
Shoshone Co.
Chicago-Gary-Lake County
Boyd Co. (Ashland)
Louisville
Baton Rouge
Springfield (W. Mass)
Baltimore
Kent and Queen Anne Cos.
222
30
751
13
3
2,092 2,006
13,000 13,000
1,639
2,498
5,815
2,742
370
384
669
1,800
106
2,470
3,923
2,653
7,887
834
559
812
2,348
52
475
51
170
12
6
5
13
3
19
1
8
2,122
0
54
92
13,000
0
18
1,041
2,742
30
349
5
1,836
1
6
1
126
26
1
74
13
625
APPENDIX A • DATA TABLES
223
-------
NATIONALAIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-19. Condensed Nonattainment Areas List(a) (continued)
State
Area Name(b)
°3
Pollutant(c)
CO S02 PM10
Pb N02
°3
CO
Population (x 1000) (d)
S02 PM10 Pb All
52
MN
Minneapolis-St. Paul
1
272
272
53
MN
Olmsted Co. (Rochester)
1
71
71
54
MO
Dent
1
3
3
55
MO
Liberty-Arcadia
1
2
2
56
MO-IL
St. Louis
1
1
2,390
2
2,390
57
MT
Butte
1
33
33
58
MT
Columbia Falls
1
3
3
59
MT
Kalispell
1
12
12
60
MT
Lame Deer
1
1
1
61
MT
Lewis & Clark (E. Helena)
1
1
2
2
2
62
MT
Libby
1
3
3
63
MT
Missoula
1
1
43
43
43
64
MT
Poison
1
3
3
65
MT
Ronan
1
2
2
66
MT
Thompson Falls
1
1
1
67
MT
Whitefish
1
3
3
68
MT
Yellowstone Co. (Laurel)
1
5
5
69
NE
Douglas Co. (Omaha)
1
1
1
70
NM
Anthony
1
2
2
71
NM
Grant Co.
1
28
28
72
NM
Sunland Park
1
8
8
73
NV
Central Steptoe Valley
1
2
2
74
NV
Las Vegas
1
1
258
741
741
75
NV
Reno
1
1
134
254
254
76
NY-NJ-CT
NewYork-N. New Jersey-Long Island
1
1
1
17,943
12,338
1,488
17,943
77
OH
Cleveland-Akron-Lorain
1
1
1,412
1,412
1,412
78
OH
Jefferson Co. (Steubenville)
1
4
4
79
OH
Lucas Co. (Toledo)
1
462
462
80
OR
Grants Pass
1
1
17
17
17
81
OR
Klamath Falls
1
1
18
18
18
82
OR
LaGrande
1
12
12
83
OR
Lakeview
1
3
3
84
OR
Medford
1
1
62
63
63
85
OR
Oakridge
1
3
3
86
OR
Springfield-Eugene
1
157
157
87
PA
Lancaster
1
423
423
88
PA
Pittsburgh-Beaver Valley
1
2
1
2,468
446
75
2,468
89
PA
Warren Co
2
22
22
90
PA-DE-NJ-MDPhiladelphia-Wilmington-Trenton
1
6,010
6,010
91
PA-NJ
Allentown-Bethlehem
1
91
91
92
PR
Guaynabo Co.
1
85
85
93
TN
Shelby Co. (Memphis)
1
826
826
94
TX
Beaumont-Port Arthur
1
361
361
95
TX
Dallas-Fort Worth
1
3,561
3,561
96
TX
El Paso
1
1
1
592
54
515
592
97
TX
Houston-Galveston-Brazoria
1
3,731
3,731
98
UT
Ogden
1
1
63
63
63
99
UT
Salt Lake City
1
1
725
725
725
100
UT
Tooele Co.
1
26
26
101
UT
Utah Co. (Provo)
1
1
85
263
263
102
WA
Olympia-Tumwater-Lacey
1
63
63
224 DATA TABLES • APPENDIX A
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-19. Condensed Nonattainment Areas List(a) (continued)
Pollutant(c) Population (x 1000) (d)
State
Area Name(b)
°3
CO
so2
PMi.
Pb N02
°3
CO
so2
PMi.
Pb All
103
WA
Seattle-Tacoma
3
""730
730
104
WA
Spokane
1
1
279
177
279
105
WA
Wallula
1
47
47
106
WA
Yakima
1
54
54
107
Wl
Manitowoc Co.
1
80
80
108
Wl
Marathon Co. (Wausau)
1
115
115
109
Wl
M ilwau kee-Racine
1
1,735
1,735
110
Wl
Oneida Co. (Rhinelander)
1
31
31
111
WV
Follansbee
1
3
3
112
WV
New Manchester Gr. (in Hancock Co)
1
10
10
113
WV
Wier.-Butler-Clay (in Hancock Co)
1
1
25
22
25
114
WY
Sheridan
1
13
13
31 17 28 76 6 0 90,800 30,515 4,034 29,792 836 100,593
Notes:
(a) This is a simplified listing of Classified Nonattainment areas. Unclassified and Section 185a nonattainment areas are not included. In certain cases,
footnotes are used to clarify the areas involved. For example, the lead nonattainment area listed within the Dallas-Fort Worth ozone nonattainment area is
in Frisco, Texas, which is not in Dallas county, but is within the designated boundaries of the ozone nonattainment area. Readers interested in more
detailed information should use the official Federal Regf/sfercitation (40 CFR 81).
(b) Names of nonattainment areas are listed alphabetically within each state. The largest city determines which state is listed first in the case of multiple-city
nonattainment areas. When a larger nonattainment area, such as ozone, contains 1 or more smaller nonattainment areas, such as PM10 or lead, the
common name for the larger nonattainment area is used. Note that several smaller nonattainment areas may be inside one larger nonattainment area, as
is the case in Figure A-1. For the purpose of this table, these are considered one nonattainment area and are listed on one line. Occasionally, two
nonattainment areas may only partially overlap, as in Figure A-2. These are counted as two distinct nonattainment areas and are listed on separate lines.
(c) The number of nonattainment areas for each of the criteria pollutants is listed.
(d) Population figures were obtained from 1990 census data. For nonattainment areas defined as only partial counties, population figures for just the
nonattainment area were used when these were available. Otherwise, whole county population figures were used. When a larger nonattainment area
encompasses a smaller one, double-counting the population in the "AN" column is avoided by only counting the population of the larger nonattainment area.
(e) Lead nonattainment area is a portion of Franklin township, Marion county, Indiana.
(f) Sulfur dioxide nonattainment area is a portion of Boyd county.
(g) Lead nonattainment area is Herculaneum, Missouri in Jefferson county.
(h) Lead nonattainment area is a portion of Lewis and Clark county, Montana.
(i) Ozone nonattainment area is a portion of Dona Ana county, New Mexico.
(j) Lead nonattainment area is a portion of Shelby county, Tennessee.
(k) Lead nonattainment area is Frisco, Texas, in Collin county.
APPENDIX A • DATA TABLES
225
-------
NATIONALAIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure A-1. (Multiple NA areas within a larger NA
area) Two S02 areas inside the Pittsburgh-Beaver
Valley ozone NA. Counted as one NAarea.
Figure A-2. (Overlapping NA areas) Searles Valley
PM-io NA partially overlaps the San Joaquin Valley
ozone NA. Counted as two NA areas.
u NA for 03
NA for S02
NAfor 03
NAfor PM-10
226
DATA TABLES • APPENDIX A
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-20. Trend in 8-hr ozone concentrations (ppm) exceedances at National Park and National Monument sites, 1990-1999
National Park
Trend
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
Acadia NP
NS
0.089
0.095
0.080
0.080
0.075
0.092
0.073
0.077
0.088
0.092
4
7
1
3
0
5
2
1
4
5
Big Bend NP
UP
nd
0.057
0.061
0.063
0.069
0.065
0.073
0.063
0.070
0.064
nd
0
0
0
0
0
0
0
0
0
Brigantine
NS
0.109
0.111
0.094
0.093
0.083
0.100
0.095
0.106
0.091
0.095
17
34
8
13
2
10
13
18
22
19
Cape Cod NS
NS
0.097
0.111
0.096
0.088
0.088
0.105
0.096
0.100
0.084
0.101
9
16
6
4
4
9
8
17
2
12
Cape Romain
UP
nd
0.060
0.072
0.069
0.067
0.075
0.071
0.082
0.076
0.080
nd
0
0
0
0
1
1
3
0
2
Chiricahua NM
NS
0.069
0.071
0.065
0.068
0.071
0.059
0.072
0.065
0.067
0.072
0
0
0
0
0
0
0
0
0
0
Congaree Swamp
UP
nd
0.059
0.067
0.063
0.064
0.076
0.074
0.065
0.081
0.080
nd
0
0
0
0
1
0
0
0
0
Cowpens NB
UP
0.074
0.078
0.086
0.082
0.083
0.084
0.080
0.091
0.096
0.094
0
1
4
3
2
3
2
6
15
7
Denali NP
UP
0.048
0.049
0.050
0.048
0.049
0.053
0.053
0.051
0.054
0.054
0
0
0
0
0
0
0
0
0
0
Everglades NP
NS
0.060
0.060
0.061
0.064
0.064
0.058
0.063
0.066
0.072
0.067
0
0
0
0
0
0
0
0
0
0
Glacier NP
NS
0.050
0.051
0.051
0.044
0.055
nd
0.057
0.04
0.053
0.048
0
0
0
0
0
nd
0
0
0
0
Grand Canyon NP
NS
0.072
0.073
0.074
0.066
0.073
nd
0.073
0.072
0.072
0.076
0
0
0
0
0
nd
0
0
0
0
Great Smoky Mtn
UP
0.092
0.079
0.088
0.088
0.093
0.099
0.088
0.098
0.110
0.106
5
2
5
4
10
11
8
19
35
25
Great Smoky Mtn
UP
0.087
0.082
0.075
0.089
0.088
0.093
0.092
0.095
0.106
0.101
4
1
0
7
6
12
12
20
34
26
Lassen Volcanic
NS
0.078
0.066
0.069
0.064
0.078
0.074
0.073
0.067
0.078
0.084
1
0
0
0
1
0
1
0
1
2
Mammoth Cave NP
NS
0.083
0.078
0.073
0.072
0.075
0.088
0.082
0.078
0.092
0.098
2
0
0
0
1
5
2
3
12
13
Olympic NP
NS
0.046
0.043
0.046
0.042
0.042
0.049
0.046
0.045
0.041
0.043
0
0
0
0
0
0
0
0
0
0
Pinnacles NM
NS
0.083
0.084
0.084
0.060
0.078
0.083
0.094
0.076
0.088
0.082
3
3
3
0
0
3
9
1
5
0
Rocky Mountain
UP
0.057
0.076
0.071
0.071
0.076
0.076
0.072
0.070
0.080
0.074
0
0
0
1
0
0
0
0
1
1
Saguaro NM
NS
0.075
0.073
0.074
0.082
0.080
0.083
0.076
0.079
0.077
0.069
0
0
1
1
0
2
0
0
0
1
Sequoia/Kings C
NS
0.096
0.097
0.102
0.106
0.106
0.095
0.105
0.097
0.094
0.097
27
34
50
48
58
18
50
26
27
23
Shenandoah NP
UP
0.086
0.083
0.077
0.083
0.083
0.087
0.081
0.089
0.107
0.093
4
3
1
2
2
7
1
6
22
15
Theodore Roosevelt
NS
0.062
0.060
0.057
0.055
0.057
0.058
0.059
0.071
0.056
0.058
0
0
0
0
0
0
0
0
0
0
Yosemite NP
NS
0.094
0.080
0.084
0.078
0.077
0.084
0.081
nd
nd
nd
19
1
3
0
0
2
1
nd
nd
nd
Yellowstone
NS
0.054
0.057
0.063
0.053
0.061
0.060
0.061
0.061
0.066
0.077
0
0
0
0
0
0
0
0
0
0
Notes:
1. The trends statistic is the annual fourth highest daily maximum 8-hour ozone concentration (ppm). The number of exceedances of the level of the 8-hour
ozone NAAQS is shown below the concentration value.
2. "nd" indicates no data available for that year.
3. "inc" indicates less than 90 days of monitoring data available for that year.
4. "NS" indicates no statistically significant trend (at the 0.05 level).
5. "UP" indicates a statistically significant upward trend in ozone concentrations.
APPENDIX A • DATA TABLES 227
-------
NATIONALAIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Table A-21. Onroad and Nonroad Emissions of 21 Mobile Source Air Toxics, 1996
Onroad
Nonroad
Mobile Sources
Percent of
Percent of
Percent of
Total
Total
Total
Compound
National
National
National
Tons
Emissions
Tons
Emissions
Tons
Emissions
1,3-Butadiene*
23,500
42%
9,900
18%
33,400
60%
Acetaldehyde*
28,700
29%
40,800
41%
69,500
70%
Acrolein*
5,000
16%
7,400
23%
12,400
39%
Arsenic Compounds*
0.25
0.06%
2.01
0.51%
2.26
0.57%
Benzene*
168,200
48%
98,700
28%
266,900
76%
Chromium Compounds*
14
1.2%
35
3%
49
4.2%
Dioxins/Furans*1
NA
NA
NA
NA
NA
NA
Ethylbenzene
80,800
47%
62,200
37%
143,000
84%
Formaldehyde*
83,000
24%
86,400
25%
169,400
49%
Lead Compounds*
19
0.8%
546
21.8%
565
22.6%
Manganese Compounds*
5.8
0.2%
35.5
1.3%
41.3
1.5%
Mercury Compounds*
0.2
0.1%
6.6
4.1%
6.8
4.2%
MTBE
65,100
47%
53,900
39%
119,000
86%
n-Hexane
63,300
26%
43,600
18%
106,600
44%
Naphthalene2
NA
NA
NA
NA
NA
NA
Nickel Compounds*
10.7
0.9%
92.8
7.6%
103.5
8.5%
POM (as sum of 7 PAH)*
42.0
4%
19.3
2%
61.3
6%
Styrene
16,300
33%
3,500
7%
19,800
40%
Toluene
549,900
51%
252,200
23%
802,100
74%
Xylene
311,000
43%
258,400
36%
569,400
79%
Diesel Particulate Matter
182,000
34%
341,000
65%
523,000
99%
*On the urban HAPs list for the Integrated Urban Air Toxics Strategy
1Dioxin/Furans emission estimates are still under review
2Naphthalene emission estimates are currently included in POM. This will be corrected in the 1999 NTI.
228
DATA TABLES • APPENDIX A
-------
APPENDIX B
Methodology
http://www.epa.gov/oar/aqtrnd99/appendb.pdf
AIRS Methodology
The ambient air quality data present-
ed in Chapters 2 and 3 of this report
are based on data retrieved from AIRS
on July 20,2000. These are direct mea-
surements of pollutant concentrations
at monitoring stations operated by
state and local governments through-
out the nation. The monitoring sta-
tions are generally located in larger
urban areas. EPA and other federal
agencies also operate some air quali-
ty monitoring sites on a temporary
basis as a part of air pollution re-
search studies. The national monitor-
ing network conforms to uniform
criteria for monitor siting, instrumenta-
tion, and quality assurance.1'2
Emission estimation methods used
for historical years prior to 1985 are
considered "top-down approaches,"
e.g., pollutant emissions were esti-
mated by using national average
emission characterization techniques
(for NOx, VOC, CO, Pb, and PM10).
Emission estimates for the years
1985-present represent an evolution
in methods for significant categories
resulting in a "bottom-up approach"
including data submitted directly by
state/local agencies (for all criteria
pollutants, PM2.5 and NH3).
In 1999,4,184 monitoring sites
reported air quality data for one or
more of the six NAAQS pollutants to
AIRS, as seen in Table B-l. The geo-
graphic locations of these monitoring
sites are displayed in Figures B-l to
B-6. The sites are identified as Na-
tional Air Monitoring Stations
Table B-1. Number of Ambient Monitors
Reporting Data to AIRS
Pollutant
# of Sites
Reporting
Data to
AIRS in 1999
#of
Trend Sites
1990-1999
CO
531
388
Pb
265
175
mo2
424
230
Os
1,086
703
PM,0
1,214
954
so2
637
480
Total
4,184
2,930
(NAMS), State and Local Air Moni-
toring Stations (SLAMS), or "other."
NAMS were established to ensure a
long-term national network for urban
area-oriented ambient monitoring
and to provide a systematic, consis-
tent data base for air quality compari-
sons and trends analysis. SLAMS
allow state or local governments to
develop networks tailored for their
immediate monitoring needs.
"Other" monitors may be Special
Purpose Monitors, industrial moni-
tors, tribal monitors, etc.
Air quality monitoring sites are
selected as national trends sites if
they have complete data for at least
eight of the 10 years between 1990 and
1999. The annual data completeness
criteria are specific to each pollutant
and measurement methodology.
Table B-l displays the number of
sites meeting the 10-year trend com-
pleteness criteria. Because of the
annual turnover of monitoring sites,
the use of a moving 10-year window
maximizes the number of sites avail-
able for trends and yields a data base
that is consistent with the current
monitoring network.
The air quality data are divided
into two major groupings: daily
(24-hour) measurements and continu-
ous (1-hour) measurements. The
daily measurements are obtained
from monitoring instruments that
produce one measurement per
24-hour period and typically operate
on a systematic sampling schedule of
once every six days, or 61 samples
per year. Such instruments are used
to measure PM10 and lead. More
frequent sampling of PM10 (every
other day or every day) also is com-
mon. Only PM10 weighted (for each
quarter to account for seasonality)
annual arithmetic means that meet
the AIRS annual summary criteria are
selected as valid means for trends
purposes.3 Beginning in 1998, some
sites began reporting PM10 data
based on local conditions, instead of
APPENDIX B • AIRS METHODOLOGY 229
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure B-1. Carbon monoxide monitoring network, 1999.
NAMS
SLAMS
+¦ Other
Figure B-2. Lead monitoring network, 1999.
NAMS
SLAMS
Other
230 AIRS METHODOLOGY • APPENDIX B
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure B-3. Nitrogen dioxide monitoring network, 1999.
NAMS
SLAMS
+- Other
Figure B-4. Ozone monitoring network, 1999.
9- o(
+ ^
NAMS
SLAMS
Other
APPENDIX B • AIRS METHODOLOGY 231
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Figure B-5. PM10 monitoring network, 1999.
SLAMS
+- Other
Figure B-6. Sulfur dioxide monitoring network, 1999
NAMS
SLAMS
+¦ Other
232 AIRS METHODOLOGY • APPENDIX B
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
standard, or "reference," conditions.
For these sites, PM10 statistics were
converted from local conditions to
standard conditions to ensure all
PM10 data in this report are consistent
and reflect standard conditions.4
Only lead sites with at least six
samples per quarter in three of the
four calendar quarters qualify as
trends sites. Monthly composite lead
data are used if at least two monthly
samples are available for at least
three of the four calendar quarters.
Monitoring instruments that oper-
ate continuously produce a measure-
ment every hour for a possible total
of 8,760 hourly measurements in a
year. For hourly data, only annual
averages based on at least 4,380
hourly observations are considered
as trends statistics. The S02
standard-related daily statistics re-
quire at least 183 daily values to be
included in the analysis. Ozone sites
meet the annual trends data com-
pleteness requirement if they have at
least 50 percent of the daily data
available for the ozone season, which
varies by state, but typically runs
from May through September.5
Air Quality Trend Statistics
The air quality statistics presented in
this report relate to the pollutant-
specific NAAQS and comply with the
recommendations of the Intra-Agen-
cy Task Force on Air Quality Indica-
tors.6 A composite average of each
trend statistic is used in the graphical
presentations throughout this report.
All sites were weighted equally in
calculating the composite average
trend statistic. Missing annual sum-
mary statistics for the second through
ninth years for a site are estimated by
linear interpolation from the sur-
rounding years. Missing end points
are replaced with the nearest valid
year of data. The resulting data sets
are statistically balanced, allowing
simple statistical procedures and
graphics to be easily applied. This
procedure is conservative since end-
point rates of change are dampened
by the interpolated estimates.
Emissions Estimates
Methodology
Trends are presented for annual na-
tionwide emissions of CO, lead, NOx,
VOC, PM10, and S02. These trends
are estimates of the amount and
kinds of pollution being emitted by
automobiles, factories, and other
sources based upon best available
engineering calculations. Because of
recent changes in the methodology
used to obtain these emissions esti-
mates the estimates have been recom-
puted for each year. Thus,
comparisons of the estimates for a
given year in this report to the same
year in previous reports may not be
appropriate.
The emissions estimates presented
in this report reflect several major
changes in methodologies that were
instituted mainly in 1996. First, state-
derived emissions estimates were
included primarily for nonutility
point and area sources. Also, 1985-
1994 NOx emission rates derived
from test data from the Acid Rain
Division, U.S. EPA, were utilized.
The MOBILE5b model was run in-
stead of MOBILE5a for the years 1995
through 1999. For 1985-1999, the
Office of Transportation and Air
Quality, U.S. EPA, provided new
estimates from the beta version of the
nonroad model for most nonroad
diesel and gasoline equipment cat-
egories. Finally, additional improve-
ments were made to the particulate
matter fugitive dust categories.
In addition to the changes in meth-
odology affecting most source catego-
ries and pollutants, other changes
were made to the emissions for spe-
cific pollutants, source categories,
and/or individual sources. Activity
data and correction parameters for
agricultural crops and paved roads
were included. A change in method-
ology occurred starting in 1996 for
calculating PM10 emissions from
unpaved roads and in 1999 for calcu-
lating emissions from construction.
This has led to lower PM10 emissions
than would have been predicted
using the previous methods. The
development of new emission estima-
tion methodologies have added emis-
sions for open burning of residential
yard waste and land-clearing debris
burning. Starting in 1999, these esti-
mates contributed to a significant
increase in industrial category emis-
sions for CO, PM10 and PM2.5 be-
tween 1998 and 1999. State-supplied
MOBILE model inputs for 1990,1995,
and 1996 were used, as well as state-
supplied VMT data for 1990. In addi-
tion, there were VMT methodology
changes starting in 1995 that affected
the allocation of state or metropolitan
area VMT to counties. Rule effective-
ness from pre-1990 chemical and
allied product emissions was re-
moved. Lead content of unleaded
and leaded gasoline for the onroad
and nonroad engine lead emission
estimates was revised, and Alaska
and Hawaii nonutility point and area
source emissions from several sources
were added. Also, this report incor-
porates data from CEMs collected
between 1994 and 1999 for NOx and
SO; emissions at major electric utilities.
APPENDIX B • AIRS METHODOLOGY 233
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
All of these changes are part of a
broad effort to update and improve
emissions estimates. Additional
emissions estimates and a more de-
tailed description of the estimation
methodology are available from EPA's
Emission Factor and Inventory Group.
IMPROVE Methodology
Data collected from the Interagency
Monitoring of Protected Visual Envi-
ronments (IMPROVE) network is
summarized in Chapters 2 (PM2.5
section) and 6 of this report. The
completeness criteria and averaging
method used to summarize the IM-
PROVE data are slightly different
from those used for the criteria pol-
lutants. (Data handling guidance is
currently being developed for the
IMPROVE network. Future summa-
ries will be based on this guidance.)
The source data sets were obtained
from Dr. James Sisler of Colorado
State University.
The annual average statistics in
these files were used to assess trends
in this report. The IMPROVE data
are not reported in terms of a calen-
dar year. The IMPROVE year runs
from March to February of the fol-
lowing year. It follows that the four
seasons are: March to May (spring),
June to August (summer), September
to November (autumn), and December
to the following February (winter). The
network samplers monitor on
Wednesdays and Saturdays through-
out the year, yielding 104 samples per
year and 26 samples per season. To be
included in this analysis, sites were
required to have data at least 50 per-
cent of the scheduled samples (13
days) for every calendar quarter.
IMPROVE monitoring sites are
selected as trends sites if they have
complete data for at least eight of the
Figure B-7. Class I Areas in the IMPROVE Network meeting data completeness
criteria.
Pif
a Glacier
Mount Rainier
Three Sisters
a Crater Lake
a Redwood
Lassen Volcanic Jarbidge
, Yellowstone
Bridger Badlands
Acadia13
i r\r
Point Reyes LonexPeak Mount Zirke|
"ft-* Great Basin
a Yosemite
Lye Brook a
Brigantine
vE
Rocky Mountain
Pinnacles K BrVce Cannon a Canyoniands
Sequoia ¦> ¦ a Great Sand Dunes
\( Mesa Verde Weminuche
h Bandelier
San Gorgonio Petrified Forest
n Tonto
Chiricahua
Upper Buffalo
Dolly SoosY/^
Shenandoah
Mammoth Cave * Jeffejhspn
B Great Smoky Mntn
Sipsey
< Cape Romain
B Guadalupe Mntns
Big Bend
"?'S!
a Okefenokee
Chassahowitza
Y
Complete for Both
Complete for Trends Only
Complete for 1999 Only
10 years between 1990 and 1999 or
(six of eight years for those who be-
gan monitoring in 1992). A year is
valid only if there are at least 13
samples (50 percent complete) per
season for both measured and recon-
structed PM2.5. The same linear inter-
polation applied to the criteria
pollutants is applied here. The IM-
PROVE sites meeting the data com-
pleteness criteria are shown in Figure
B-7.
For consistency, the same sites are
used in both the PM2.5 section and the
Visibility chapter. The exceptions are
Washington D.C. and South Lake
Tahoe, which are not included in the
visibility trends analysis because they
are urban sites.
Air Toxics Methodology
Database
The 1990-1999 ambient air quality
data presented in Chapter 5 of this
report are based on air toxics data
retrieved from AIRS in July, 2000,
data retrieved from the IMPROVE
network in June, 2000, and data
voluntarily submitted to EPA by state
and local monitoring agencies and
received by June 30,2000. For more
details about the database, see Rosen-
baum et al, 1999.7 All statistical sum-
maries are based on annual average
concentrations. Measurements for
hazardous air pollutants (HAPs) are
frequently reported as non-detectable
concentrations. To calculate annual
average concentrations, one-half of
the actual or plausible detection limit
is used to substitute values for non-
detects (or if the reported value is
zero). The plausible detection limit,
used for cases where the MDL is
missing, is the lowest of the mea-
sured concentrations and MDLs for
the given monitor and HAP.
234 AIRS METHODOLOGY • APPENDIX B
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
Separate summaries are presented
for sites in an MSA/PMSA, exclud-
ing the (primarily rural) sites from
the IMPROVE network, and for other
sites. Areas (one or more counties) are
either assigned to a MSA, to a CMS A
(consolidated MSA) consisting of two
or more PMSAs (primary MSAs), or
are just assigned to a county. Each
non-IMPROVE site in an MSA or
CMS A was assigned either to its MSA
or PMSA. Some analyses allocated
MSA/PMSAs to states. If the MSA/
PMSA crosses state boundaries, the
state containing the largest portion of
that MSA/PMSA was used.
Completeness
All calculations are based on the
average of calculated or measured
24-hour values. For each HAP, a se-
ries of completeness rules are applied
sequentially starting with using the
raw hourly data to determine daily
completeness. Multiple records for
the same HAP, monitoring site, day,
and time period are averaged togeth-
er. A day is complete if the total num-
ber of hours monitored for that day is
18 or more (i.e., 75 percent of 24
hours). For example, 18 hourly aver-
ages, three 6-hour averages, or three
8-hour averages will satisfy the daily
completeness criteria. Once daily
completeness is satisfied, quarterly
completeness is determined. Calen-
dar quarters are 1. (Late winter) Janu-
ary-March, 2. (Early summer)
April-June, 3. (Late summer) July-
September, 4. (Early winter) October-
December. A calendar quarter is
complete if it has 75 percent or more
complete days out of the expected
number of daily samples for that
quarter, and if there are at least five
complete days in the quarter. To de-
termine the expected number of daily
samples, the most frequently occur-
ring sampling interval (days from one
sample to the next sample) was used;
in cases of ties, the minimum sam-
pling interval was applied. A calen-
dar year is complete if both the
summer and winter six month sea-
sons have at least one complete quar-
ter, i.e., if a) quarter 1 or quarter 4 or
both quarters 1 and 4 are complete,
and b) quarter 2 or quarter 3 or both
quarters 2 and 3 are complete.
In some cases, co-located samples
for the same HAP and location were
collected. For AIRS data, co-located
monitors are identified by having the
same 9-digit AIRS ID number but a
different POC number. The higher
POC numbers are generally used for
quality assurance monitoring data
that are not as complete as the pri-
mary sampling data. Therefore, if
multiple AIRS monitors at the same
location meet the above completeness
requirements, then only the data
from the monitor with the lowest
POC number was used for these
analyses. For data not reported to
AIRS, co-located monitors can have
very different monitor identifiers. If
multiple monitors at the same lati-
tude and longitude location for a
given sampling program and HAP
meet the completeness requirements,
then only the data from the monitor
with the highest monitoring fre-
quency was used for these analyses.
In case of tied highest monitoring
frequencies, the monitor with the
most daily average records (from
complete quarters in the trend pe-
riod) was used.
National Analyses
Based on the available years of moni-
toring data across the nation, the
national analyses were restricted to
the six-year period 1994-1999. A site
was included for a particular HAP if,
and only if, there were four or more
complete years for that period.
California Analyses
A similar, but longer term trend anal-
ysis was performed on metropolitan
sites located only in California using
1990-1999 data. A site was included
for a given HAP if there was at least
one period of five years or longer
such that a) at least 75 percent of
those years are complete, and b) the
period ends in 1997 or later. Only the
data from the most recent of the long-
est such periods was used.
Trend Analysis
Annual averages for years with four
complete quarters were computed by
averaging the four quarterly averag-
es. If a year had one or more missing
or incomplete quarters, then those
missing or incomplete quarterly aver-
ages were filled in (if possible) using
the General Linear Model (GLM) fill-
in methodology described below and
the annual average was computed by
first averaging the quarterly averages
(actual or filled-in) for a season and
then averaging across the two sea-
sons.8 Filled-in quarterly averages
were used for incomplete quarters
even if there was some data for that
quarter. Data from incomplete quar-
ters was not used in the analyses.
Sometimes, the filled in quarterly
average can be negative and occa-
sionally this leads to a negative annu-
al average. To deal with this case,
negative or zero filled-in quarterly
averages were used to compute the
annual average (this avoids biasing
the results), but any resulting nega-
tive annual averages were reset to
zero. In the summary analyses, aver-
ages across multiple sites were com-
puted as trimmed means rather than
APPENDIX B • AIRS METHODOLOGY 235
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
simple arithmetic means in order to
reduce the influence of the most ex-
treme monitor averages on the trend
line. If there were nine sites or less,
then no trimming was performed, so
the trimmed mean is the arithmetic
mean of all the site averages. If there
were between 10 and 40 sites, inclu-
sive, the trimmed mean is the arith-
metic mean of all the site averages
except for the highest and lowest
averages. If there were 41 sites or
more, the trimmed mean is the arith-
metic mean of all the site averages
except for the highest 2.5 percent and
the lowest 2.5 percent of the averag-
es. The reported numbers of sites and
percentiles are based on all sites
meeting the completeness criteria,
i.e., including the sites that were
excluded for the trimmed mean cal-
culation.
The overall slope (trend) was esti-
mated non-parametrically as the
median of the ratios of the difference
in the annual average to the differ-
ence in calendar year, for all pairs of
calendar years. The significance level
of the trend was computed using the
associated non-parametric Theil test,
based on the number of pairs of years
where the annual averages increased.
The p-values are calculated for a two-
sided test for whether or not the an-
nual averages have a trend (which
may be increasing or decreasing). The
trend is reported as "Significant Up
Trend" or "Significant Down Trend"
if the corresponding one-sided test is
significant at the five percent signifi-
cance level; otherwise the result is
reported as "Non-significant Up
Trend," "no trend," or "Non-signifi-
cant Down Trend."
For the tables summarizing the
annual average trends by monitor,
the GLM fill-in method was not used.
Instead, those monitor annual aver-
ages were computed by averaging all
complete daily averages for each
complete quarter, then averaging the
complete quarterly averages for each
season, and then, finally, averaging
over the two seasons. All other analy-
ses used the filled-in quarterly aver-
ages as described above.
GLM Fill-in Methodology
The general linear model (GLM) fill-
in methodology and software used to
fill in missing quarterly averages was
based on the report by Cohen and
Pollack (1990),9 which can be con-
sulted for more details. The method
was modified to apply to the se-
quence of quarterly averages (24
values for the six year 1994-1999
period) instead of five annual means.
The method was also modified to use
a fitted statistical model with six year
effects and four quarterly adjust-
ments, instead of having 24 indepen-
dent year/quarter effects. In other
words, the fitted model assumes that
the seasonal (quarterly) variation is
the same for every site and year.
Initially, each site is allocated to a
region, which for these analyses was
the MSA/PMSA for sites within an
MSA or PMSA, or else was the coun-
ty. Suppose that for each of the four
quarters there is at least one site in
the region with complete data for
that quarter in at least one year. Sup-
pose also that for each of the six years
there is at least one site in the region
with complete data for at least one
quarter in that year. If these two con-
ditions apply, then the missing quar-
terly averages for all sites in that
region are computed by fitting a
general linear model such that the
expected value for a given site and
quarter q is the sum of the site aver-
age, a yearly adjustment term, and a
quarterly adjustment term. The year-
ly adjustment term is the fixed effect
of the y'th year, 1 <= y <= 6, assumed
to be the same value for all sites in
the region. The quarterly adjustment
term is the fixed effect of the q'th
quarter, 1 <= q <= 4, assumed to be
the same value for all sites in the
region and all years. If a region does
not meet these two conditions, then
the region is expanded to become a
larger, augmented region with some
site data for every quarter, and some
site data for every year, and the GLM
approach is applied to the augment-
ed region. Candidates for the aug-
mented region are selected by finding
the nearest site(s) in the same state
that have complete data for the miss-
ing quarter(s) and year(s). The select-
ed augmented region is the region
giving the lowest mean square error
for the GLM model.
Although the GLM methodology
filled in most missing quarters, there
were some states, HAPs and years
that had no complete quarters for any
site in the state, and in those cases the
missing quarters were not filled in by
the GLM approach (which restricts
the augmented regions to sites in the
same state). For the national analyses
of distributions across sites in differ-
ent states, the missing site-years were
then filled in using the same EPA
extrapolation and interpolation
method used elsewhere in the Trends
report: If the site annual average for
1994 was missing, it was filled in
with the 1995 annual average; if the
1995 annual average was also miss-
ing, then the 1994 and 1995 annual
averages were filled in with the 1996
annual average. If the site annual
average for 1999 was missing, it was
filled in with the 1998 annual aver-
age; if the 1998 annual average was
also missing, then the 1999 and 1998
annual averages were filled in with
236 AIRS METHODOLOGY • APPENDIX B
-------
NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
the 1997 annual average. Otherwise,
any missing annual averages were
filled in using simple linear interpola-
tion from the two surrounding an-
nual averages.
References
1. Clean Air Act Amendments of
1990, U.S. Code, volume 42, section
7403 (c)(2), 1990.
2. Ambient Air Quality Surveillance,
44 CFR 27558, May 10, 1979.
3. Aerometric Information Retrieval
System (AIRS), Volume 2, U.S. Envi-
ronmental Protection Agency, Office of
Air Quality Planning and Standards,
Research Triangle Park, NC, October,
1993.
4. Falke, S. and Husar, R. (1998) Cor-
rection of Particulate Matter Concen-
trations to Reference Temperature and
Pressure Conditions, Paper Number
98-A920, Air & Waste Management
Association Annual Meeting, San Di-
ego, CA, June 1998.
5. Ambient Air Quality Surveillance,
51 FR 9597, March 19, 1986.
6. U.S. Environmental Protection
Agency Intra-Agency Task Force Re-
port on Air Quality Indicators,
EPA-450/4-81-015, U.S. Environmental
Protection Agency, Office of Air Quali-
ty Planning and Standards, Research
Triangle Park, NC, February 1981.
7. Rosenbaum, A. S., Stiefer, M. P.,
and Iwamiya, R. K. November, 1999.
Air Toxics Data Archive and AIRS Com-
bined Dataset: Contents Summary Report.
SYSAPP-99/26d. Systems Applications
International, San Rafael, CA.
8. In all cases analyzed, four non-
missing quarterly means were avail-
able after applying the GLM method,
so that the resulting annual mean is
the arithmetic mean of the four quar-
terly averages.
9. Cohen, J.P and A. K. Pollack. 1990.
General Linear Models Approach to Esti-
mating National Air Quality Trends As-
suming Different Regional Trends.
SYSAPP-90/102. Systems Applications
International, San Rafael, CA.
APPENDIX B • AIRS METHODOLOGY 237
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NATIONAL AIR QUALITY AND EMISSIONS TRENDS REPORT, 1999
238 AIRS METHODOLOGY • APPENDIX B
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