Inventory Issues and Modeling- Some Examples

1. Inventory Issues and Modeling- Some Examples Brian Timin USEPA/OAQPS October 21, 2002

2. Purpose • Show examples of how certain inventory issues affect modeling results • Will focus on: • Ammonia • Crustal/fugitive • Fires • PM2.5 speciation profiles

3. Ammonia • Particulate nitrate is generally overpredicted in CMAQ • Ammonia emissions play a key role in the nitrate overpredictions • ORD has completed ammonia “inverse modeling” based on measurements of ammonium wet deposition • 1990 ammonia inventory appears to be overestimated • Reduced ammonia emissions from livestock by 20-60% in our 1996 modeling inventory for each month (from previous seasonal profiles) in our latest model runs • We have found that nitrate is still overpredicted with reduced ammonia emissions

4. CMAQ Ammonia Sensitivity Runs- 50% NH3 Reduction- January Basecase Nitrate Nitrate with 50% Ammonia Reduction

5. Crustal/Fugitive Emissions and Speciation Profiles • Crustal/other primary PM2.5 • SCC specific speciation profiles are used to speciate the primary PM2.5 emissions into organic carbon, elemental carbon, primary nitrate, primary sulfate, and “unspeciated PM2.5”. • Many of the profiles have a large percentage of unspeciated PM2.5 • The unspeciated mass is tracked in the model as other/crustal (PMFINE in REMSAD and A25 in CMAQ) • In urban areas, the annual average modeled unspeciated PM2.5 concentrations can be as high as 5-10 ug/m3.

6. Crustal/Fugitive Emissions and Speciation Profiles • The measured “other PM” in urban areas is generally < 1 ug/m3 • What is unspeciated PM? Does it really belong in another category? • Why is there so much of it predicted in urban areas? • Largest sources are paved roads, construction, and open burning • Updates to speciation profiles may reduce unspeciated portion of PM2.5 and may lead to improved primary carbon inventories • The largest contributors to “other PM2.5” should be closely examined to see where estimation improvements can be made

7. January Average Crustal/Other PM2.5

8. Fire Emissions • Burning emissions • Separate SCC’s for wildfires, prescribed burning, agricultural burning, slash burning, and open burning • Wildfires- we removed them from our modeling • We do not know when and where wildfires occurred in 1996 • WRAP has a new inventory for 1996 that we may be able to use • Lack of wildfires is likely contributing to an underestimate in organic carbon (especially in the West) • Prescribed burning- included in current modeling • Relatively large amount of prescribed burning emissions in certain parts of the country • Some States have large prescribed burning emissions (based on State submitted data), some States have none (based on the lack of State submitted data)

9. Modeling/Inventory Issues Burning Emissions • Seasonal factors for prescribed burning need to be examined • We are currently allocating 65% of the prescribed burning to the spring • Seasonal factors should probably vary by region • This creates unrealistic model results when transitioning between seasons

10. Effect of Prescribed Burning on Primary Organics

11. Link Between Emissions Modeling and Meteorology • Emissions of many species are strongly linked with meteorology • Currently incorporate meteorological variables into biogenic and mobile models • All of the previous examples are influenced by meteorology • Ammonia • Temperature, wind speed • Fugitive dust • Moisture, wind speed • Fires • Winds, mixing • In the long term, many of these emissions types may need to be incorporated into models which account for meteorology

12. Summary • There are many existing uncertainties in inventory categories that can have large impacts on the modeling results • The inventory community is beginning to address many of these “issues” • New emissions models that incorporate meteorological variables may be necessary to adequately characterize spatial and temporal emissions patterns • The modeling community can help identify and prioritize issues as they impact modeling