1. Uma Shankar 1 and Prakash Bhave 2 Sixth Annual CMAS Conference October 1-3, 2007 1 UNC Institute for the Environment 2 Atmospheric Modeling Division, NOAA (in partnership with EPA-NERL) Box Model Tests of Two Mass Transfer Methods for Volatile Aerosol Species in CMAQ

2. Overview Treatment of Coarse PM in CMAQ Mass Transfer Theory Approach: Box Model Development Results  Fine-particle Equilibrium  Fully Dynamic Approaches (4 schemes) Next Steps

3. NO 3 - NH 4 + SO 4 = H 2 O POA SOA a SOA b EC Other SVOCs HNO 3 NH 3 H2OH2O Sea Salt Soil, Other COARSE MODE2 FINE MODES Coarse-Mode Chemistry in CMAQ H 2 SO 4 Prior to CMAQv4.5: Coarse mode is inert. Fine mode species equilibrate instantaneously w/ inorganic gases

4. NO 3 - NH 4 + SO 4 = Na + Cl - H 2 O POA SOA a SOA b EC Other SVOCs HNO 3 NH 3 H2OH2O SO 4 2- Na + Cl - Soil, Other COARSE MODE2 FINE MODES Coarse-Mode Chemistry in CMAQ H 2 SO 4 HCl CMAQv4.6 (current) treatment: Coarse mode is inert. New species shown in RED. Fine mode species equilibrate instantaneously w/ inorganic gases

5. NO 3 - NH 4 + SO 4 = Na + Cl - H 2 O POA SOA a SOA b EC Other SVOCs HNO 3 NH 3 H2OH2O NO 3 - NH 4 + SO 4 2- Na + Cl - H 2 O Soil, Other COARSE MODE2 FINE MODES Coarse-Mode Chemistry in CMAQ H 2 SO 4 HCl Next CMAQ release: Coarse mode will interact with inorganic gases New species and interactions are shown in RED

6. Time Scale for Mass Transfer D p = 0.2 μm D p = 3.0 μm Reference: Z. Meng & J.H. Seinfeld, Atmos. Environ., 30:2889-2900 (1996). Coarse PM takes ~10h to reach equilibrium with surrounding gases, so instantaneous equilibrium approach is not applicable. “Dynamic” approach needed for gas-particle mass transfer

7. Mass Transfer Rate, J Size-dependent term proportional to surface area for small particles, proportional to diameter for large particles Composition-dependent term concentration at the particle’s surface (c s ) is determined by gas/particle equilibrium positive gradient  condensation negative gradient  evaporation Most implementations of dynamic mass transfer to date have been done in sectional models (e.g., PMCAMx, CMAQ-MADRID). One exception: Modal Aerosol Module in Polyphemus (Sartelet et al., 2006).

8. Approach Adapt aerosol code from CMAQ v4.6 to develop a stand-alone box model for aerosol microphysics Extend the box model to treat gas-particle transfer with all 3 modes dynamically Add some simplifying assumptions to maintain computational efficiency Resulting module will be implemented in next release of CMAQ.

9. Approach Adapt aerosol code from CMAQ v4.6 to develop a stand-alone box model for aerosol microphysics Extend the box model to treat gas-particle transfer with all 3 modes dynamically Add some simplifying assumptions to maintain computational efficiency Resulting module will be implemented in next release of CMAQ. Test case. Mimics the transport of a marine air mass into a polluted urban area such as Los Angeles

10. Box-Model Test Conditions Reference: Pilinis et al., Aerosol Sci. Technol., 32:482-502 (2000). Developed by Pandis et al. 38-hour scenario to test different gas-to-particle mass transfer schemes over a range of RH, particle acidity, and pollution concentrations. Used previously in development/testing of sectional aerosol models in CMAQ-MADRID and PM- CAMx Large plumes of NH 3 provide a realistic challenge for dynamic- transfer module.

11. Box-Model Test Conditions Initial conditions  NH 3 0.3 μg m -3  HNO 3 4.0 μg m -3  Marine particle distribution Convert to tri-modal distribution, for compatibility with CMAQ Reference: J. Lu and F.M. Bowman, Aerosol Sci. Technol., 38:391-399 (2004).

12. Box-Model Test Results First, compare the fine particle equilibrium approach of CMAQ v4.6 with a “reference” model: a multi-component aerosol dynamics module (MADM) run with 10 sections Focus of comparisons is total PM concentrations of inorganic species predicted by different models as a function of time.

13. Box-Model Test Results Reference curve is from a state-of-the-science multi-component aerosol dynamics module (MADM) run with 10 sections. Sulfate matches very well, because SO 4 2- a non-volatile condensing species.

14. Box-Model Test Results CMAQv4.6 NH 4 + also matches reference very well. Jim Kelly discovered an error in reference case past hour 30 and thus we excluded these data from subsequent comparisons.

15. Box-Model Test Results In CMAQv4.6, nitrate is underpredicted throughout the simulation because  During first 16 hours, coarse-mode NaNO 3 is not formed.  After NH 3 is emitted on Hour 16, NH 4 NO 3 formation is restricted to the fine modes.

16. Box-Model Test Results In CMAQv4.6, Cl - is constant because  Initial mass of Cl - is entirely in coarse mode  There is no coarse- mode chemistry In reference case  In first 12 hours, Cl - in coarse PM is gradually replaced by NO 3 -.  On Hour 16, large NH 3 plume leads to NH 4 Cl formation.

17. Box-Model Test Results Next, we implemented a dynamic mass transfer scheme with a uniform 10 s time step.  Fluxes of volatile acids and NH 3 are calculated independently of each other – “uncoupled transfer”  Call ISORROPIA in reverse mode w/ particle-phase concentrations as input. Output is the equilibrium concentration, C s, at particle surface. Focus on Hours 0 – 16, when marine aerosol is reacting gradually with HNO 3, before encountering large NH 3 emissions.  Does the model capture the replacement of Cl - by NO 3 ?

18. Box-Model Test Results In dynamic model, loss of Cl - from coarse mode is captured quite accurately! In dynamic model, NaNO 3 reaches the correct endpoint, but temporal evolution needs further study. What happens in dynamic model after Hour 16?

19. Box-Model Test Results After encountering the NH 3 plume on Hour 16, dynamic model becomes unstable. Abrupt transition of coarse mode from acidic to alkaline, causes rapid NH 3 evaporation, and the system never recovers... So we investigated the use of special mass transfer schemes when particle composition approaches neutral pH

20. Treatment Near pH-Neutrality 3 approaches in literature (all sectional models)  Sun & Wexler, Atmos. Environ. 1998 “Coupled Transport” – Transfer acids and bases in equimolar quantities such that H + remains stable near pH-neutrality.  Pilinis et al., Aerosol Sci. Technol. 2000 Restrain the transfer of all volatile gases to allow only small changes in acidity during each time step.  Jacobson, Aerosol Sci. Technol. 2005 Uncoupled dynamic transfer of acids followed by instantaneous equilibrium transfer of NH 3.

21. Treatment Near pH-Neutrality 3 approaches in literature (all sectional models)  Sun & Wexler, Atmos. Environ. 1998 “Coupled Transport” – Transfer acids and bases in equimolar quantities such that H + remains stable near pH-neutrality.  Pilinis et al., Aerosol Sci. Technol. 2000 Restrain the transfer of all volatile gases to allow only small changes in acidity during each time step.  Jacobson, Aerosol Sci. Technol. 2005 Uncoupled dynamic transfer of acids followed by instantaneous equilibrium transfer of NH 3. Implement and test each scheme in box model.

22. Box-Model Test Results If acids and base are both condensing or both evaporating, coupled transfer when near pH- neutral: Oscillatory behavior persists but trend improves substantially. Same as purple curve, but turned off transfer when flux gradients for acids and base had opposite signs: Periods of no transport exhibit step-like behavior in time series Jacobson-like scheme: Reproduces magnitude of reference case, but some oscillations exist

23. Box-Model Test Results Jacobson-like scheme: Best agreement with reference case

24. Box-Model Test Results Jacobson-like scheme: Oscillations appear more pronounced due to scale of the plot. Under- prediction after hr 16 matches overprediction in NH 4 +

25. Next Steps Implement and test the Pilinis et al. mass transfer scheme in our modal model Develop a computationally-efficient solution for modal model  “Hybrid” scheme (fine particles at equilibrium w/ gas phase, dynamic transfer of coarse particle mass)  Tabulate C s on coarse mode or treat as an irreversible heterogeneous reaction (e.g., Hodzic et al., 2006) Benchmark our results  against sectional implementation by Pilinis et al.  against modal implementation by Sartelet et al.  Compare size-resolved output to multiple reference cases Apply our fully-dynamic and computationally-efficient schemes in CMAQ simulations Incorporate into next year’s CMAQ release

26. Acknowledgements Bill Benjey (EPA-ORD) Frank Binkowski (UNC) Frank Bowman (UND) Adel Hanna (UNC) Jim Kelly (EPA-ORD) Bonyoung Koo (ENVIRON) Spyros Pandis (CMU) Christian Seigneur (AER) Shaocai Yu (STC) Disclaimer The research presented here was performed under the Memorandum of Understanding between the U.S. Environmental Protection Agency (EPA) and the U.S. Department of Commerce's National Oceanic and Atmospheric Administration (NOAA) and under agreement number DW13921548. This work constitutes a contribution to the NOAA Air Quality Program. Although it has been reviewed by EPA and NOAA and approved for publication, it does not necessarily reflect their policies or views.