Modeling Air Quality in Houston, Texas

1. Modeling Air Quality in Houston, Texas Byeong-Uk Kim November 17, 2004 Department of Environmental Sciences and Engineering University of North Carolina at Chapel Hill

2. Content • Background • Uniqueness of Houston • Air Quality Modeling for Houston • Dissertation

3. Background • Is ozone bad or good? • Ozone formation science • Non-attainment area and State Implementation Plan (SIP) • Difficulties in developing control strategy • Non-linearity • Ozone transport • Photochemical Air Quality Modeling (PAQM) system

4. Is ozone bad or good? http://www.epa.gov/oar/oaqps/gooduphigh/

5. Ozone formation science Jeffries, 1993

6. Ozone formation science • Where do we get the precursors? • NOx (=NO+NO2) • Automobiles • Power plants • VOCs (Volatile Organic Compounds) • Automobiles • Refineries • Trees • Other area sources

7. Non-attainment and SIP • Non-attainment area • NAAQS for ozone: daily maximum one hour average concentration < 0.12 ppm • fourth highest reading in 3 years => 125 ppb is a violation at that monitor • highest violation in 3 years is the “design value” for control • State Implementation Plan (SIP) • Control strategy development • Attainment demonstration NAAQS: National Ambient Air Quality Standards

8. Difficulties in developing control strategy: Non-linearity Philadelphia Chicago Blanchard and Reynolds, 2002

9. Difficulties in developing control strategy: Ozone transport ~100km Travel in 6 hrs ~100km between New York City- Philadelphia

10. Formulation of PAQM Jeffries, 1993

11. Operation of PAQM

12. Operation of PAQM

13. Operation of PAQM TCEQ developed 9114 new emission point speciation profiles From Byun, UH

14. Reported EI • Normal Non-EGU VOC EI with Special EI additions • hg_02km.tx_negu_si4a Total Point Source CB−IV HC Emissions, 08/25/2000 Base inventory of 240 T/D Nearly constant emissions TCEQ Cantu, 2002

15. SIP modeling Base case – explain current ozone with current inventory Future case – predict ozone with growth and existing regulations. Future controlled case – predict ozone with growth, existing regulations, and newly proposed regulations. All three cases use the same episodic meteorology. From Byun, UH

16. Uniqueness of Houston • Transient High Ozone Events (THOEs) • Large variability of VOC emissions • Different Modeling Approach Needed • Complex meteorological conditions

17. Transient High Ozone Event in Houston Jeffries, 2004

18. >10,000 lbs/hr ethylene release at La Porte, (6700 lbs between 11:00 AM and 11:25 AM) 3/27/2002

19. Short term ozone enhancements of up to 100 ppb

20. Large Variability of VOC Emissions • Permitted emission components • Nearly Constant • Routinely Variable • Allowable Episodic • Off-permit event emission releases • Start-up, shut-down, maintenance operations, accidents, emergencies • Subject to RQ value Webster, 2003

21. Different Modeling Approach Needed • Typical conceptual model • New conceptual model Jeffries, 2003

22. Complex Meteorological Conditions http://www.islandnet.com/~see/weather/elements/seabrz.htm

23. Complex Meteorological Conditions GOES: Geostationary Operational Environmental Satellites

24. Complex Meteorological Conditions August 31, 2000 Estimated Mixing Height by Kv profile 10:00 AM 02:00 PM 06:00 PM Land/sea breeze does not happen clearly all the time. The synoptic weather pattern plays a key role.

25. Air Quality Modeling for Houston • Modeling Domain • General Description • Base case results • Future case results

26. Air Quality Modeling for Houston

27. Air Quality Modeling for Houston • UNC Beowulf servers • More than 150 nodes, MPI support • CAMx (Comprehensive Air quality Model with eXtensions Ver. 4.x) • Serial/OpenMP • Modeling period • August 22, 2000 ~ September 6, 2000 • Run statistics • About 4 hours clock time for an episodic day on an Intel 2.8GHz CPU node • About 2 GB size of outputs per episodic day

28. Base case results Imputed base Not imputed (max 112 ppb) + Event

29. Base case results

30. Future case results Without Event + Imputed future With Event + Imputed future

31. Dissertation • Does this model show or have all necessary components to produce the phenomena that we can expect from the current best perceptual/conceptual model? • Can this model distinguish what precursor to control for ozone reduction? • Does it estimate the control requirement unambiguously? • What are the possible biases in the prediction and its impact on the policy choice? The answers to these questions may vary spatially over the modeling domain and temporally during the modeling period.

32. Why do we care those questions? • The current SIP framework requires the use of PAQM for the control strategy developments. • Once developed, the control strategies will influence our daily life. Some of them are also very expensive to implement. • Highway speed limit change • Restriction of the construction equipments • Installation of NOx control device • It may consume all important material for the device that is available in the USA to make the demanded amount of devices for a region. • What if these are not the primary reason for the ozone violation in your area?

33. Lots of analysis and tools • Model performance analysis • Potential reliability of the modeling results for the policy use • Area of influence analysis • Source-receptor relationships • Uncertainty/Sensitivity analysis • Identification of the important process/parameter/input • Process analysis • Model’s internal ozone concentration by process contributions