1. Simulation of Houston-Galveston Airshed Ozone Episode with EPA’s CMAQ Daewon Byun: PI Soontae Kim, Beata Czader, Seungbum Kim Emissions input Chemical Mechanisms Vertical Mixing

2. Benefits Comparative evaluation of two models provides tremendous insights on the validity of model inputs, model configurations and results Help identify strengths/shortcomings of the many components in the system Can provide “weight of evidence” information for the present SIP modeling Objectives – Evaluation of modeled HRVOC effects with an alternative modeling tool Air quality models based on first-principle description of nature are extremely complex and depends on various inputs and model assumptions TCEQ – utilizes Environ’s CAMx (Comprehensive Air quality Model– Extended) Model being compared: EPA’s CMAQ (Community Multiscale Air Quality) model

3. Emissions Inventory Standard vs. imputed (base5b/psito2n2) HRVOC emissions –CB-IV mechanism –SAPRC mechanism CAMx and CMAQ both use the same emissions EI but some minor differences –Different plume rise methods cause different vertical distributions of elevated source emissions. –Some chemical species for CAMx are not used in CMAQ. Ex) MEOH, ETOH Institute for Multi-dimensional Air Quality Studies

4. Transport Algorithms Used in CMAQ and CAMx ProcessUH CMAQTCEQ CAMx Horizontal advectionPPM (Piecewise Parabolic Method) PPM Vertical advectionPPMSemi-implicit (Crank- Nicholson) Horizontal diffusionK-theory, constantK-theory, variable Vertical diffusionK-theory with PBL similarity method for Kv calculation K-theory with O'Brien (1970) scheme for Kz calculation Mass adjustmentYes

5. X22: CAMX CAMx 4.03 TAMU&ATMET Base5b regular C_a01, TCEQ Q22: CMAQ CMAQ4.2.2 TAMU (M_a02) Base5b regular C_a01, TCEQ Supersite: LaPorte with base Texas Emissions Two models are quite comparable

6. X20: CAMX CAMx 4.03 TAMU&ATMET Base5b psito2n2 C_a01, TCEQ Q20: CMAQ CMAQ4.2.2 TAMU (M_a02) Base5b psito2n2 C_a01, TCEQ Supersite: LaPorte with Imputed HRVOC (ETH, OLE) CAMx responds to the imputed data much more

7. X22: CAMX CAMx 4.03 TAMU&ATMET Base5b regular C_a01, TCEQ Q22: CMAQ CMAQ4.2.2 TAMU (M_a02) Base5b regular C_a01, TCEQ Supersites: LaPorte/Clinton with Base Texas Emissions Some missing peaks with base emissions Not much bias

8. X20: CAMX CAMx 4.03 TAMU&ATMET Base5b psito2n2 C_a01, TCEQ Q20: CMAQ CMAQ4.2.2 TAMU (M_a02) Base5b psito2n2 C_a01, TCEQ Supersites: LaPorte/Clinton with Imputed HRVOC emissions Some improvement here Often overpredicted Mostly overpredicted

9. Aug. 28 th Comparison with NOAA Aircraft CMAQ/CB-4 with imputed HRVOC Good correlation with observation; (model prediction somewhat lower)

10. X20: CAMX CAMx 4.03 TAMU&ATMET Base5b psito2n2 C_a01, TCEQ Q22: CMAQ CMAQ4.2.2 TAMU (M_a02) Base5b psito2n2 C_a01, TCEQ Comparison with NCAR Aircraft with Imputed HRVOC (ETH, OLE) Still significant underprediction In ETH conc. Is there any other way to predict High ozone productivity in the model? Problem in the vertical distribution of the imputed HRVOC emissions? Different vertical mixing? Different chemical mechanism?

11. Regular EI: includes Area/Nonroad, Mobile, Point and Biogenic emissions Imputed EI: Regular + Additional VOC emissions OSD (Ozone Season Day) emissions: ~ 130 tons/day Hourly emissions: 30 ~ 70 tons/day Most of the imputed HRVOC emissions are treated as fugitives and thus ends up in the lower model layers Vertical re-distribution of imputed HRVOC emissions

12. Speciated OSD emissions mapped into the CB-4 species

13. Stack parameters Species # of Stacks Emissions (tons/day) Mean Ht. (H>0.5m) Mean Dia. (D>0.01m) Mean Temp (T>293K) Mean Velo. (V>0.0001m/s) ETHYLENE PENTENE (1) BUTENE PROPYLENE BUTENE (1) BUTADIENE BUTENE (3-METHYL-1) BUTENE (2-METHYL-1) ISOPRENE HEXENE DECENE,1- PENTADIENE (E-1,3) BUTADIENE, 1,2- PROPADIENE Average 3131 1343 76 3623 1266 338 415 538 463 522 1 10 1 51.881 3.343 3.120 52.831 7.213 6.433 0.321 1.107 2.018 2.733 0.000 0.315 0.014 0.018 12.4 10.5 20.7 14.2 13.6 11.9 11.1 11.3 12.0 15.2 12.6 68.6 1.5 12.9 0.7 0.9 0.1 0.8 0.7 0.9 1.8 1.5 0.1 - 0.8 449.7 342.5 572.2 430.2 417.9 481.0 311.8 313.5 371.7 346.6 417.0 486.2 1089.0 294.0 411.0 4.992 1.222 0.005 4.957 2.464 6.659 0.076 0.080 1.140 0.967 8.232 1.251 0.001 3.56

14. He = Hs + a * F**b / U F = 0.25*g * ( Ts-T )/T * V * D**2

16. Vertical re-allocation

17. Ozone concentrations predicted Surprisingly not much difference…..

18. But improves ETH

19. CMAQ Kz Sensitivity Experiments With CMAQ Eddy scheme CAMx Kz scheme (Louis79 & OB70) Holtslag and Boville (1993)

20. CAMx Aug. 28 th Comparison with NOAA Aircraft CMAQ Peaks matches wellMissing peaks in plumes CO shows serious mixing problemCO compares quite well

21. Column (21, 34) in East Houston and just north of Ship Channel CMAQ Eddy scheme CAMx Kz scheme (Louis79 & OB70) Holtslag and Boville (1993)

22. O3 against NOAA AL aircraft data 08/25 08/30 CMAQCAMxKzHB93

23. CB-4 vs. SAPRC mechanisms Lumped VOC emissions in raw EI need to be speciated into individual model species prior to input to AQMs. Ex) CB4, SAPRC99, RADM2 As an alternative chemical mechanism, SAPRC99 includes more explicit chemical species than CB4, but still cooperates with grouped VOC species. It may not be enough to explain the roles of a variety of VOC species in petrochemical plant plumes over the HGA during the high ozone formations.  Extended SAPRC Institute for Multi-dimensional Air Quality Studies

24. CB-4 mechanism SAPRC mechanism Effects of chemical mechanism

25. Still missing some plume peaks; but the correlations are quite good (ozone) CMAQ/SAPRC

26. CMAQ/SAPRC shows promising results for NOy

27. Conclusive Remarks Ozone reactivities in the air quality models are significantly affected by –HRVOC emissions –Vertical mixing –Chemical representation –Meteorological inputs (not shown today) –Model configuration (not shown today) Uncertainties in the HRVOC emissions data must be evaluated in conjunction with all other key modeling factors