Updates of the Rider 8 Ozone Reduction Program in El Paso, Texas

1. Updates of the Rider 8 Ozone Reduction Program in El Paso, Texas Wen-Whai Li, Huiyan Yang, Rosa Fitzgerald, Kelvin Cheu, The University of Texas at El Paso Christine Ponce-Diaz, Michael Medina, Efren Meza El Paso Metropolitan Panning Organization Victor Valenzuela Texas Commission on Environmental Quality The 58th Meeting of the Joint Advisory Committee for the Improvement of Air Quality in the Ciudad Juárez, Chihuahua / El Paso, Texas / Doña Ana County, New México Air Basin Sunland Park, New Mexico September 19, 2013

2. Rider 8 Background • Air Quality Planning Program • Ozone Near Non-Attainment Areas • 81st Legislature appropriations

3. Tasks Completed • Outreach Activities Rider 8 website : rider8ep.org Ozone Precursor Emissions Calculator: cleanairforelpaso-dev.tamu.edu • Developed a conceptual model – through 2010 Conceptual model for ozone reduction in El Paso, Texas, El Paso MPO, 272 pages • Performed emission inventories improvement a. Emissions inventory review and improvement plan, El Paso MPO, 79 pages; b. Quantification of selected sources for emission inventory improvement in EL Paso, Texas, El Paso MPO, 56 pages(Presented previously in the JAC meeting) • Conducted ozone modeling for selected episode Photochemical modeling of ozone pollution in the Paso del Norte region, El Paso MPO, 231 pages) • Conducted ozone monitoring at 2 supplemental locations Supplementary ozone monitoring in the Paso del Norte region for the 2012 ozone season, El Paso MPO, 105 pages)

4. Outreach Activities • Neighborhood Association Summit – YISD • Health and Wellness Fair – El Paso International Airport • Public Participation Meetings for Current Planning Documents • 2013 EcoWise Environmental Summit • Rider 8 Website • Ozone Precursor Emissions Calculator

5. Summary of Ozone Pollution in the PdN

6. Ozone pollution has been decreasing in the past 10 years

7. NOx level has been decreasing in the past 10 years

8. High ozone at Sunland Park and Far east of El Paso

9. Transport ozone affects ozone levels in PdN

10. Ozone Monitoring

11. Two locations with windroses

12. High zone levels comparable to those measured at CAMS locations

13. 8-hr Ozone spatial distributions for two high ozone days

14. Ozone Modeling

15. Domain for Meteorological Modeling UTEP meteorology domain TCEQ meteorology domain

16. Modeling Scenarios • Set 1: Concentric UTEP grid system centered at El Paso and NEI emission inventory dataset • Poor model performance due to dated emissions inventory and low resolutions of landuse, topography, and other modeling parameters) • Set 2: TCEQ Rider 8 nested grid system with Rider 8 emission inventory dataset (by Environ Corporation) • Run 2a: TCEQ 36, 12, and 4-km CAMx grids with 4 km meteorology interpolated from TCEQ 12-km WRF outputs • Run 2b: TCEQ 36, 12, and 4-km CAMx grids with 4 km meteorology from UTEP concentric 4-km WRF outputs. • Set 3: Sensitivity Analysis • Run 3a: with new bridge emission • Runs 3.1 - 3.12: with controlled area emissions from Cd. Juarez

17. Modeling Results (Runs 2a and 2b) • Acceptable results for 1-hr ozone predictions Figure 4-4. Time series of 1-hour ozone comparing two CAMx simulations.

18. Modeling Results (Runs 2a and 2b) • Ozone map produced by Run 2a, 2b, and 2a – 2b

19. Modeling Results (Runs 3a) • Peak ozone concentrations do not increase with the added BOTA bridge emissions. Instead, ozone concentrations are actually reduced with bridge emissions without bridge emissions

20. Modeling Results (Runs 3.1 and 3.12) • Performance of all runs were acceptable

21. Modeling Results (Runs 3.1 and 3.12) • Reduction of VOC emissions from Juarez area emissions reduce 8-hr ozone level (at CAMS) in the PdN

22. Modeling Results (Runs 3.1 and 3.12) • Diurnal variation is acceptable with 4-hrs delay in ozone peak RUN 1 RUN 2 RUN 3 RUN 5 RUN 6 RUN 4

23. Modeling Results (Runs 3.1 and 3.12) • Diurnal variation is acceptable with 4-hrs delay in ozone peak RUN 7 RUN 8 RUN 9 RUN 11 RUN 12 RUN 10

24. Remarks on Ozone Modeling • The model performance was evaluated for the 2006 base case ozone episode between June 12 and June 21 • Model slightly underestimated ozone trends and over-predicted NOx on average but under-predicted events with very high NOx that occurred throughout the episode • Ozone under prediction is related to the NOx over prediction. Potential causes include overestimated NOx emissions or under estimated dispersion of NOx emissions (e.g., because of under estimated vertical dilution) • Under estimated VOC emissions could be a contributing factor to under estimated peak ozone concentrations. Sensitivity tests with alternative meteorology or modified modeling parameters should be conducted. • Reduction in Juarez area source VOC emissions by 50% would result in up to 13% reduction in peak ozone

25. Remarks on Ozone Modeling • All sensitivity runs functioned within acceptable limits for the model performance evaluation • None of the runs displayed significant improvement in the model performance over the BASELINE run • An increase of 75% area source VOC emissions with or without concurrent increase in NOx emissions will bring the predicted peak ozone to be the same as the observed peak • Variation in 50 or 75% of NOx area emissions represent only a small fraction of NOx changes in the PdN (5% and 8%) which may not be sufficient to make visible changes in the ozone predictions • On the other hand, if one reduces the Juarez area source VOC emissions by 50% through some control strategies, one would be able to reduce the peak ozone by as much as 13%

26. Questions and Answers