1. Emerging Science EPA’s ORD Supports Regional Haze Program
RPO National Technical Meeting
June 9-10, 2005
Denver, CO
Fred Dimmick, Chief
Process Modeling Research Branch
Human Exposure and Atmospheric Sciences Division
Fred Dimmick, Acting Chief
Process Modeling Research Branch
Human Exposure and Atmospheric Sciences Division

2. Agenda Quick overview of ORD atmospheric sciences activities
Related to regional haze
Only a portion of research
Introduce “posters” from EPA’s BOSC review and Science Forum
Take questions now (or afterwards)

3. Receptor models estimate contribution of different source types to ambient PM concentrations
Sample Screens from EPA PMF and EPA Unmix

4. Receptor models estimate contribution of different source types to ambient PM concentrations
Recent Enhancements
Focused on approaches for guiding decisions in applying models and interpreting results.
Include development of statistics summarizing uncertainty in modeled solutions.
Future Directions
Enhancement of receptor models through EPA STAR grants.
developing the next generation of receptor models
assessing the accuracy and precision of the existing models.
Enhancements are being folded into a suite of multivariate receptor models that EPA is freely distributing to the user community.

5. PM Supersites Program
Sampling and analysis methods to measure the chemical and physical characteristics of PM and important precursor species,
Enhanced temporal and compositional characterization that complements routine ambient air monitoring networks, and
Insights into policy relevant phenomena that corroborate current policies, cause rethinking and modification, and provide direction for future policy formulation.
Baltimore
Fresno
Los Angeles
New York
Houston
Atlanta
St. Louis
Pittsburgh

6. Policy Relevant Synthesis of Research
PM Supersites Program
Policy Relevant Synthesis of Research
-- 17 Science/Policy Relevant Questions --
Methods (Qs 1-3)
Characterization (Qs 4- 8)
Receptor-Based Models and Emissions-Based Chemical Transport Models (Qs 9-11)
Atmospheric Processes (Qs 12 – 15)
Emissions Estimates (Q 16)

7. CMAQ
Research Goals …
Identify PM components that contribute to model performance strengths and weaknesses for total PM2.5.
Target and diagnose sources of error for PM component predictions with the highest level of uncertainty
Determine role of input sources of error (e.g., emissions, meteorology) versus uncertainties in modeled processes
Evaluate model responses and sensitivities to emission changes.

8. Secondary Organic Aerosol (SOA) EXPERIMENTAL ATMOSPHERIC CHAMBER
Objectives
Identify the major SOA precursors
Identify tracer compounds for the major SOA precursors
Determine reaction mechanisms for SOA formation
Improve treatment of SOA in CMAQ
Use the smog chamber to generate atmospherically relevant air mixtures for exposure studies

9. SOA Tracer Compounds from Laboratory and Field Samples

10. Secondary Organic Aerosol (SOA) - Experimental Chamber
Future Directions
Continue comparing chamber concentrations and compositions of SOA formed with atmospherically relevant individual and mixtures hydrocarbons irradiated in the presence of NOx and SO2 with model results for proposed SOA formation mechanisms.
Identify SOA tracer compounds for sesquiterpenes.
Continue measuring and refining values for l for SOA precursors and use them to estimate contributions of SOA precursors to ambient PM2.5 concentrations.
Assess whether SOA yields in complex hydrocarbon mixtures are additive.
Work with modelers to develop the CMAQ version of the PM chemistry model.

11. Human Exposure and Atmospheric Sciences Division
Linda Sheldon, Director
Tim Watkins, Deputy Director
Source attribution and apportionment
Shelly Eberly
Gary Norris
PM Supersites and Ambient PM Methods
Paul Solomon
Bob Vanderpool
CMAQ
Alice Gilliland
Atmospheric chamber
Ed Edney and Tad Kleindienst
Fred Dimmick
Although this work was reviewed by EPA and approved for publication, it may not necessarily reflect official Agency policy.