U.S. Perspective on Particulate Matter and Ozone

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. Identifying PM sources Overview • Purpose • 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

3. 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% Coal Combustion Crustal Ammonium Nitrate Coal combustion emissions in States surrounding Alabama Mobile Sources Veg. Burning Industrial 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% 30 - 31% 13% 16% 30 – 35% 39 - 46% 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. ParticlesBronx EPA staff estimates reflect recent emissions, ambient data, and are subject to a number of measurement, analytical, and modeling uncertainties.

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

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

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

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

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

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

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

16. Key To Ozone ChartsSource 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