1. Development of the CMAQ-UCD Sectional Aerosol Model K. Max Zhang and Anthony S. Wexler University of California Davis University of California Davis

2. Biosketch of CMAQ-UCD 1990 1998 1999-2000 2002-2003 8:30pm (EST) Feb 9, 2005, Atlanta Tony Wexler wrote the original AIM Sun and Wexler simulated SCAQS particle size distributions Clegg, Brimblecombe and Wexler developed online AIM CMAQ-AIM in VISTAS Started CMAQ-AIM effort Started CMAQ-AIM effort Renamed to CMAQ-UCD 2004 - present CMAQ-AIM in BRACE, CRPAQS 2006 CMAQ-UCD public release

3. Uses Models-3/CMAQ as platformUses Models-3/CMAQ as platform Incoporates an aerosol module developed by Sun, Zhang and Wexler.Incoporates an aerosol module developed by Sun, Zhang and Wexler. The aerosol module is sectional, fully dynamic and computationally efficient.The aerosol module is sectional, fully dynamic and computationally efficient. CMAQ-UCD

4. Gas Chemistry Aerosol Dynamics Integration of large set of stiff ODEs  the calculation of rate of change for gas-phase species is mathematically trivial: requires partitioning between gaseous and particulate phases  requires partitioning between gaseous and particulate phases  the calculation of rate of change for particulate species needs aerosol thermodynamics computation Gas-phase chemistry vs. Aerosol dynamics

5. Dynamic Gas-to-Particle Transport UncoupledUncoupled Partitioning of each volatile species one by one Partitioning of each volatile species one by one Coupled (near pH independent)Coupled (near pH independent) NH 3 and HNO 3 and/or NH 3 and HCl condense and evaporate together to maintain near acid-neutrality NH 3 and HNO 3 and/or NH 3 and HCl condense and evaporate together to maintain near acid-neutrality Replacement (near pH independent)Replacement (near pH independent) HNO 3 condenses as HCl evaporates or vice versa in near acid-neutrality conditions HNO 3 condenses as HCl evaporates or vice versa in near acid-neutrality conditions

6. HNO 3 (g) Uncoupled Calculate vapor pressure of HNO 3 and NH 3 on particle surface NH 3 (g) NO 3 -

7. Then partition NH 3. NH 3 (g) Uncoupled NH 4 + NO 3 -

8. Uncoupled NH 4 NO 3

9. HNO 3 (g) NH 3 (g) Coupled In near acid-neutrality conditions NH 4 NO 3

10. HNO 3 (g) HCl(g) Replacement Cl - NO 3 - In near acid-neutrality conditions

11. Case Case TATATATA TNTNTNTN TCTCTCTC Mechanism(s) Mechanism(s) 1 No Aerosol Thermodynamics 2XUncoupled 3XUncoupled 4XUncoupled 5XX Coupled NH 3 and HNO 3 6XX Coupled NH 3 and HCl 7XXReplacement 8XXX Coupled NH 3 and HNO 3, NH 3 and HCl

12. Simplified Thermodynamics A rigorous approach is to minimize Gibbs free energyA rigorous approach is to minimize Gibbs free energy What we need: equilibrium vapor pressures of NH 3 /HNO 3 /HCl, and water content (requiring phase state)What we need: equilibrium vapor pressures of NH 3 /HNO 3 /HCl, and water content (requiring phase state) Strategies:Strategies:  Using phase diagrams to determine phase state  Using vapor pressure cap to determine the existence of NH 4 NO 3 (s) and NH 4 Cl(s)

13. Phase diagram of H +, NH 4 +, SO 4 2-, NO 3 -

14. Vapor Pressure Cap Constant Molality Activity Coefficient Vapor pressure

15. Numerical Integration using ATS We are developing an Asynchronous Time- Stepping (ATS) integration method.We are developing an Asynchronous Time- Stepping (ATS) integration method. Similar concepts have been applied in molecule dynamics and solid mechanics.Similar concepts have been applied in molecule dynamics and solid mechanics. With ATS, each variable is integrated based on its intrinsic time scale.With ATS, each variable is integrated based on its intrinsic time scale. CPU time can be saved by reducing number of integrations for slow variables and avoiding inversion of large Jacobian.CPU time can be saved by reducing number of integrations for slow variables and avoiding inversion of large Jacobian.

16. ε1ε1 c1c1 c2c2 c3c3. cncn t curr t new ε  2 ε  3 ε  n “pass” “scan” ……. t 1,local t 2,local t 3,local fastest slowest t n,local

17. ATS vs. GEAR for typical Tampa conditions Condensation case Evaporation case

18. ATS vs. GEAR for typical Bakersfield conditions Condensation case Evaporation case

19. ATS vs. GEAR for typical Los Angeles conditions Condensation case Evaporation case

20. ATS vs. GEAR for typical Riverside conditions Condensation case Evaporation case

21. ATS Benchmark Test Cases EPS = 0.1 EPS = 0.01 RMS CPU time (s) RMS Tampa Cond. 4.7  10 -2 0.23 8.6  10 -4 0.47 Evap. 1.7  10 -2 0.04 1.3  10 -3 0.14 Bakersfield Cond. 1.0  10 -2 0.0024 1.3  10 -3 0.013 Evap. 1.2  10 -2 0.0024 5.8  10 -4 0.019 Los Angeles Cond. 4.3  10 -3 0.03 2.9  10 -3 0.14 Evap. 5.4  10 -3 0.05 1.1  10 -3 0.18 Riverside Cond. 8.0  10 -3 0.05 2.9  10 -3 0.18 Evap. 8.0  10 -3 0.04 3.6  10 -3 0.12 SDA1.92.7

22. Summary We developed a sectional, dynamic partitioning and computationally efficient aerosol module in CMAQ- UCD.We developed a sectional, dynamic partitioning and computationally efficient aerosol module in CMAQ- UCD. CMAQ-UCD adopts three gas-to-particle partitioning schemes: Uncoupled, Coupled and Replacement.CMAQ-UCD adopts three gas-to-particle partitioning schemes: Uncoupled, Coupled and Replacement. CMAQ-UCD applies simplified thermodynamic schemes to determine the vapor pressures of volatile species and particle phase states.CMAQ-UCD applies simplified thermodynamic schemes to determine the vapor pressures of volatile species and particle phase states. CMAQ-UCD employs a novel asynchronous time- stepping (ATS) integration technique to solve stiff ODE problems in aerosol dynamics.CMAQ-UCD employs a novel asynchronous time- stepping (ATS) integration technique to solve stiff ODE problems in aerosol dynamics.

23. Acknowledgement USEPA California Air Resources Board VISTAS Dr. Robin Dennis, Dr. Ajith Kaduwela and Dr. Gail Tonnesen