1. Development and Application of a State-of-the-Science Plume-in-Grid Model CMAQ-APT Prakash Karamchandani, Christian Seigneur, Krish Vijayaraghavan and Shiang-Yuh Wu, AER, San Ramon, CA Alan Hansen and Naresh Kumar EPRI, Palo Alto, CA CMAQ Workshop, October 2002

2. Plume-in-Grid Modeling 3-D air quality models create an artificial dilution of stack emissions –lower concentrations of plume material –unrealistic concentrations upwind of stack –incorrect chemical reaction rates –incorrect representation of transport Subgrid-scale representation of plumes can remove some or all of these major limitations

3. Previous PiG Models Previous Plume-in-Grid (PiG) models include PARIS, URM, UAM-V, CAMx and CMAQ All these PiG representations had limitations due to a simplified treatment of plume dispersion (empirical or first-order diffusion), simplified chemical mechanism in some cases and no effect of turbulence on plume chemistry

4. CMAQ-APT Development of a new PiG model that uses the state- of-the-science for the host model (CMAQ) and the plume model (SCICHEM) SCICHEM includes advanced treatments for plume dispersion (second-order diffusion) and chemistry (multistage mechanism, effect of turbulence) CMAQ with Advanced Plume Treatment (APT)

5. Plume Dispersion SCICHEM uses the SCIPUFF framework to simulate plume dispersion A myriad of puffs is released from the source to represent the plume Puffs are split when they become too large so that the effect of wind shear and turbulence on plume dispersion are properly characterized Puffs that overlap are merged

6. Plume Chemistry Plume chemistry is simulated with a chemical kinetic mechanism that evolves through three stages as the plume becomes dispersed into the background air (Karamchandani et al., 2000) Effect of turbulence on plume chemistry can be simulated Crosswind plume resolution can be improved by using more puffs SCICHEM has been evaluated with plume data from SOS 95 and SOS 99

7. Evolution of Plume Chemistry Early Plume Dispersion NO/NO 2 /O 3 chemistry 1 2 Mid-range Plume Dispersion Reduced VOC/NO x /O 3 chemistry — acid formation from OH and NO 3 /N 2 O 5 chemistry Long-range Plume Dispersion 3 Full VOC/NO x /O 3 chemistry — acid and O 3 formation

8. SCICHEM/CMAQ Interface Domain, grid information Geophysical data Meteorological data Deposition velocities Models-3 CMAQ SCICHEM Emissions, IC/BC Output concentrations and deposition Output puff information Point source emissions Dump puffs chemical concentrations chemical concentrations I/O API I/O API I/O API I/O API

9. Plume Dumping Criteria Chemical criterion: the plume has become chemically mature as determined by reaching the third stage of plume chemistry and a given threshold for the plume concentration ratio of O 3 / (O 3 + NO 2 ) Physical criterion: the plume width must exceed the host model grid size

10. CMAQ-APT Application Eastern United States with two nested grid domains (12 and 4 km resolution) Episode of 11 to 15 July 1995 MM5 simulation of Seaman and Michelson (2000) Thirty largest NO x point sources simulated with APT Simulation with CMAQ and CMAQ-APT CMAQ-APT is about 1.6 times slower than CMAQ for this simulation

11. CMAQ Surface O 3 Concentrations 13 July 1995, 3 p.m. 12 km domain

12. Effect of APT PiG Treatment on Surface O 3 Concentrations 13 July 1995, 3 p.m. CMAQ-APT - CMAQ 12 km domain

13. Effect of Point Source NO x Emissions on Surface O 3 Concentrations without PiG Treatment CMAQ - Background 12 km domain

14. Effect of Point Source NO x Emissions on Surface O 3 Concentrations with APT PiG Treatment CMAQ-APT - Background 12 km domain

15. CMAQ Surface HNO 3 Concentrations 13 July 1995, 3 p.m. 12 km domain

16. Effect of APT PiG Treatment on Surface HNO 3 Concentrations 13 July 1995, 3 p.m. CMAQ-APT - CMAQ 12 km domain

17. Effect of Point Source NO x Emissions on Surface HNO 3 Concentrations without PiG Treatment CMAQ - Background 12 km domain

18. Effect of Point Source NO x Emissions on Surface HNO 3 Concentrations with APT PiG Treatment CMAQ-APT - Background 12 km domain

19. Conclusions CMAQ-APT provides an improved representation of the impact of large point sources For isolated point sources, CMAQ-APT predicts less impact on O 3 formation (up to 80 ppb less) and less impact on HNO 3 formation (up to 24 ppb less) CMAQ-APT has been subjected to a comprehensive beta-testing by three organizations It will be applied to the California San Joaquin Valley for several CCOS episodes