1. U.S. Perspective on Particulate Matter and Ozone
United Nations Economic Commission for Europe
European Monitoring and Evaluation Program (EMEP) Workshop
April 2004

2. Overview Purpose Background
Provide a view of PM and Ozone air quality problem in the U.S.
Provide approximate estimates of the contribution of different sources to fine particle (PM2.5) and ozone (O3) non-attainment issues for selected US urban areas in the eastern US
Background
No precise answers possible, but we can provide reasonable estimates through three approaches
Analyses of chemical components monitored in PM problem areas, compare with proportion of emissions from power generation
Use of statistical analyses of PM components in ‘source apportionment’ techniques
Using specialized regional air quality models that track source contributions
Third approach (modeling) is the only approach for estimating contribution to ozone
Summary and integration of analytical results
Identifying PM sources

3. Significant New Information on Sources from Urban PM 2
Significant New Information on Sources from Urban PM 2.5 Speciation Monitoring Data
The chemical composition of PM offers important clues as to major local and regional sources – the new network provides data for 2001 and later. These data can be combined with other information (e.g. emissions) to provide insights into the relative importance of major source categories+
These urban data show that the highest concentrations of PM2.5 occur across the East and in California. Rural data show the major reason for high eastern levels is elevated regional levels of ammonium sulfates, formed in the atmosphere from SO2 emissions. Nitrate particles (from NOx emissions) are high in northern states in the East.

4. Background: What chemical composition can tell us about the sources of fine particles (PM2.5)
Example: Sources of PM in Cleveland
Fine particles related to power generation
A large portion of the sulfate must come from power generation, because this sector contributes about 80% of the SO2 emissions in the surrounding region
A large portion of ammonium fraction is there only because of the power sector sulfate and nitrate contributions
A modest fraction of nitrate (from NOx emissions, only about 30% comes from the power sector)
A rough quantitative estimate can be derived by combining composition and emissions data
Based on these data, the power sector contributes about 30% to 35% of PM2.5 in Cleveland
Because these estimates omits some associated liquid mass, the estimate may reflect a lower bound
Ambient measurements at Cleveland PM Speciation Site
Sources of SOx emissions in States Surrounding Ohio
Note: EGUs are Electric Generating Units. Public utilities and other sources that sell power to the grid

5. Background: What “Source Apportionment” can tell us about sources of fine particles
Example: Sources of PM in Birmingham
Start with more detailed chemical composition data
Use statistical modeling to reveal the extent to which short-term (i.e. 24 hr) monitored data has repeated patterns among known key source-related chemical elements, e.g. Selenium with coal combustion, Vanadium with oil. Use these statistical patterns to estimate relative contribution of identifiable source categories.
Apply Power sector’s proportion of coal combustion to Source Apportionment Results
Power sector contributes about 30% to 35% of PM2.5 in Birmingham
Ambient measurements at Birmingham PM Spec. Site
Source apportionment modeling 6% 9%
33%
38% 8% 6%
Ammonium Nitrate
Coal Combustion
Crustal
Coal combustion emissions in States surrounding Alabama
Industrial
Mobile Sources
Veg. Burning
Source Apportionment Results

6. Background: What photochemical grid modeling tells us about ozone sources
Uses an analytical feature in a photochemical grid model (CAMx)
Impact is determined by using the model to determine the contribution of specific sectors to ozone problem in a given city
The model feature essentially uses mathematical ‘tracers’ to track the formation, transport, and removal of pollutants associated with initial/boundary conditions and emissions from source areas

7. Estimated Power Sector Contribution to PM 2.5 and Ozone
in Selected Cities
30 – 34% %
13%
16%
30 – 35% %
38 – 39%
13%
30 – 35%
36– 38%
12%
28 – 34%
EPA staff estimates reflect recent emissions, ambient data, and are subject to a number of measurement, analytical, and modeling uncertainties.
28 – 37%
PM Values in Blue
Ozone Values in Red

8. Particles Bronx
EPA staff estimates reflect recent emissions, ambient data, and are subject to a number of measurement, analytical, and modeling uncertainties.

9. Particles Washington, DC
EPA staff estimates reflect recent emissions, ambient data, and are subject to a number of measurement, analytical, and modeling uncertainties.

10. Particles Charlotte
EPA staff estimates reflect recent emissions, ambient data, and are subject to a number of measurement, analytical, and modeling uncertainties.

11. Particles Birmingham
EPA staff estimates reflect recent emissions, ambient data, and are subject to a number of measurement, analytical, and modeling uncertainties.

12. Particles Milwaukee
EPA staff estimates reflect recent emissions, ambient data, and are subject to a number of measurement, analytical, and modeling uncertainties.

13. Particles Indianapolis
EPA staff estimates reflect recent emissions, ambient data, and are subject to a number of measurement, analytical, and modeling uncertainties.

14. Particles St. Louis
EPA staff estimates reflect recent emissions, ambient data, and are subject to a number of measurement, analytical, and modeling uncertainties.

15. Particles Houston
EPA staff estimates reflect recent emissions, ambient data, and are subject to a number of measurement, analytical, and modeling uncertainties.

16. Key To Ozone Charts Source Sector Definitions
EGU – Electric Generating Units. Public utilities and other sources that sell power to the grid.
Non-EGU – All other large stationary sources.
Motor Vehicle – On road cars and trucks
Non Road – All other mobile sources: aircraft, marine vessels, trains, construction equipment, agricultural equipment, etc.
Stationary Area – Small stationary sources: residential, gas stations, dry cleaners, etc.

17. Power Sector Contribution to Ozone
EPA staff estimates reflect recent emissions, ambient data, and are subject to a number of measurement, analytical, and modeling uncertainties.

18. Counties Measuring Ozone and PM2.5 Air Quality Problems

19. Proposed Interstate Air Quality Rule
Together with Other Clean Air Programs Will Bring
Cleaner Air to Cities in the East