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Modeling and Ambient Monitoring of Air Toxics in Corpus Christi, Texas

Gary McGaughey, Elena McDonald-Buller, Yosuke Kimura, Hyun-Suk Kim, and David T. Allen The University of Texas at Austin Center for Energy and Environmental Resources Greg Yarwood , Ed Tai, and Chris Colville ENVIRON International Corporation Novato, CA

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Modeling and Ambient Monitoring of Air Toxics in Corpus Christi, Texas

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  1. Gary McGaughey, Elena McDonald-Buller, Yosuke Kimura, Hyun-Suk Kim, and David T. Allen The University of Texas at Austin Center for Energy and Environmental Resources Greg Yarwood, Ed Tai, and Chris Colville ENVIRON International Corporation Novato, CA John Nielsen-Gammon and Wenfang Lei Department of Atmospheric Sciences, Texas A&M University College Station, TX Modeling and Ambient Monitoring of Air Toxics in Corpus Christi, Texas

  2. Outline • Background • Configuration of the Corpus Christi air toxics monitoring network • Development of a conceptual model for TNMHC and benzene: meteorological conditions, emission source areas, and temporal trends (diurnal and seasonal) • AERMOD and CALPUFF results for benzene • On-going efforts including WRF/CAMx at 1km horizontal resolution

  3. Background • Neighborhood-scale monitoring and air quality modeling of air toxics is critical for human exposure and health risk assessments. • Since June 2005, The University of Texas at Austin (UT) has operated a dense monitoring network for air toxics in Corpus Christi that will continue at least several more years. • UT with ENVIRON and Texas A&M University are now developing neighborhood-scale air quality models. Population of 400,000 (2008) Currently in attainment with the NAAQS for O3 and PM2.5. Significant petroleum refining and chemical manufacturing industries.

  4. Corpus Christi Air Monitoring and Surveillance Camera Installation and Operation Project • Sulfur compounds, TNMHC, and meteorological measurements at all seven UT sites since early 2005. • Hourly auto-GC measurements and camera surveillance at two sites (Oak Park and Solar Estates in blue above). • Event triggered canisters at five sites (TNMHC > 2000 ppbC for 15 min). • Canister sampling at TCEQ CATMN sites.

  5. Locations of Industrial Property Boundaries, Terminals and Docks In Nueces County Relative to UT and TCEQ Monitoring Sites

  6. Conceptual Model Development: Identifying Key Characteristics of Air Toxics Events • Investigate meteorological conditions, emission source areas, and temporal trends associated with TNMHC, benzene and other air toxics. • Based on data collected during June 2005 – May 2008 by the UT network in additional to historical data from the TCEQ CATMN sites. • Important for selecting time periods of interest for air quality modeling, for identifying emission source areas, and for understanding and targeting conditions that lead to higher concentrations of air toxics. • This analysis will be continued during the lifetime of the network.

  7. Benzene Concentrations • TCEQ thresholds for evaluating health effects: • Reference Values (ReVs): Acute and chronic ReVs for benzene are currently 1080 ppbC and 516 ppbC. • Effects Screening Levels (ESLs): Acute and chronic ESLs for benzene are 324 ppbC and 8.4 ppbC. • Average benzene concentrations between June 2005-May 2008 range from 1.93 (Solar Estates) to 8.92 ppbC (Huisache).

  8. Benzene Concentrations • Similar to TNMHC, higher concentrations of benzene tend to occur during the night and early morning hours and during the fall/winter. • These results are generally consistent with other areas of the US. • Weekend vs. weekday comparison suggests weak trend towards lower concentrations on Sunday compared to weekdays. • Annual benzene trends at CATMN sites indicate lower concentrations recently at Huisache and Dona Park.

  9. Benzene Concentrations • A Trajectory Analysis Tool was used to identify upwind source areas during periods with higher benzene concentrations. • Consistent upwind geographic areas were identified during periods with higher benzene concentrations, suggesting site-specific emissions sources. Surface back-trajectories for all hours characterized by a benzene concentration of 30 ppb or greater at the Oak Park monitoring station during June 2005 - May 2008.

  10. Emission Inventory • TCEQ Photochemical Modeling EI (2000, 2005) • Same level of source resolution as the State of Texas submittals to EPA’s National Emission Inventory (NEI) • Used for air quality planning in Texas • Accounts for rule effectiveness (RE) • To account for reductions in control efficiency. • Applied at the SCC/SIC/abatement level by geographic regions. • Primarily affects VOC emissions from flares, equipment leak fugitives, external floating roof and internal floating roof tanks. • Results in approximately a 28% increase in VOC emissions (6600 tpy to 8500 tpy) in Nueces and San Patricio Counties. • Most detailed chemical speciation of VOC emissions • Needed for responding to regulations in the Houston area that target highly reactive VOCs and for assessment of control strategies. • Source-specific profiles originally developed by Pacific Environmental Services under contract to ENVIRON and Gabriel Cantu at the TCEQ (See Thomas et al. Emissions Modeling of Specific Highly Reactive Volatile Organic Compounds in the Houston-Galveston-Brazoria Ozone Nonattainment Area, presented at the 17th Annual International Emission Inventory Conference, Portland, OR June 2008). Profiles are updated continuously.

  11. AERMOD and CALPUFF Meteorological Processing • Chose Oct 1 – Nov 30, 2006 (based on results from the conceptual model) for initial testing and development of the AERMOD and CALPUFF models. • Used 2005 TCEQ Photochemical Modeling EI (stationary point sources only) • Does not include on-road mobile EI currently being developed by ENVIRON • AERMET was used to process the meteorological data collected at the Solar Estates and Oak Park (on-site) monitors. Surface parameters (albedo, Bowen ratio, and roughness length) were provided by the TCEQ for Nueces County. Additional surface and all upper air data were from the NWS station at Corpus Christi Airport. • CALMET was used to generate meteorological input for CALPUFF. • 8 UT/TCEQ surface stations, 10 NWS monitors, 1 upper air station (Corpus Christi Airport), 5 precipitation NWS locations, 1 NOAA buoy • CALMET sensitivity tests were performed to yield the most acceptable wind fields (subjective judgment). • CALMET options included relocation of buoy closer to grid domain, terrain kinematics, smoothing in higher layers, high resolution LULC data for coastline.

  12. AERMOD Maximum Predicted Benzene Concentrations using Solar Estates and Oak Park Meteorology Solar Estates Meteorology Max = 31.8 ppb Oak Park Meteorology Max = 43.5 ppb Distance between Oak Park and Solar Estates ~10 km, yet ~30% difference in maximum concentrations. Oak Park meteorology also predicts higher concentrations further west compared to Solar Estates meteorology.

  13. Maximum Predicted Benzene Concentrations between AERMOD (with Oak Park Meteorology) and CALPUFF AERMOD with Oak Park Meteorology Max = 43.5 ppb CALPUFF Max = 53.2 ppb, Second Max = 47.4 ppb AERMOD simulated one peak compared to two peaks for CALPUFF. CALPUFF predicts higher concentrations nearer to the emissions sources. AERMOD tended to disperse emissions further downwind.

  14. Comparison of Observed and Predicted AERMOD and CALPUFF Maximum Daily Hourly Benzene Concentrations Daily Maximum Benzene during Oct/Nov 2006 at Oak Park: Observed, AERMOD, and CALPUFF Daily Maximum Unpaired Benzene Concentrations Although the modeled values capture the range of observed concentrations, there is large variation on any given day.

  15. On-going Work: Coupling WRF/CAMx at 1km horizontal grid resolution • Two WRF simulations: (36/12/4/1 km resolution) • October 16-22, 2002 • 1 km domain • 10 minute output resolution • 44 vertical layers • Lowest 21 layers mapped to • CAMx (up to 3 km) • WRF Run 1: • ACM2 PBL scheme • Noah LSM • Monin Obukhov scheme for surface layer physics • WRF Run 2 changes: • Pleim-Xiu surface layer physics • Added analysis nudging in 36 and 12km domains above layer 10 (~700m)

  16. CAMx Sensitivity Runs with CALMET and WRF (Run 1 and Run 2) Meteorology at Solar Estates • Inert CAMx run with PiGs • Emissions from point sources only • Run 16 = CALMET • Run 19 = WRF Run 1 • Run 20 = WRF Run 2 • CAMx concentrations were extracted from 200m sampling grid over Solar Estates. • CALMET layer 1 = 18m (fixed) • WRF layer 1 =~17m • Peak observed daily benzene = 6.6 ppb on Oct 17 (8AM) • Second daily peak = 3.5 ppb on Oct 21 (10AM) • All runs under-predicted the peaks, but CAMx Run 20 (WRF Run 2) was closest • CAMx Run 19 (WRF Run 1) produced un-observed benzene spikes (Oct 18)

  17. Wind Speed Comparison over Solar Estates CALMET vs. WRF Run 1 WRF Run 1 vs. WRF Run 2 • CALMET follows observed wind speeds well due to strong obs nudging. • WRF Run 1 similar or slower than observed winds during low-wind speed periods. • WRF Run 2 wind speeds faster than WRF Run 1 and closer to observed.

  18. Wind Fields during Peak Observed Benzene at Solar Estates on October 17 CALMET WRF Run 1 WRF Run 2 • CALMET does not show a clear distinction in winds over land and water; “crop circle effects” • WRF Run 1 has a more distinguished land/water interface. • WRF Run 2 wind direction similar to Run 1, but wind speeds are relatively higher • over land and slower over water.

  19. Wind Direction at Solar Estates CALMET vs. WRF Run 1 WRF Run 1 vs. Run 2 • CALMET wind direction matches observed winds well. • WRF Run 1 wind direction tracks observed reasonably well • except during the mornings of Oct 17 and 21. • WRF Run 2 handles the nighttime rotation wind shift better, • especially on Oct 21. • Benzene higher with WRF Run 2 compared to WRF Run1.

  20. CAMx/WRF Summary: Solar EstatesOctober 16-22, 2006 • Daily peak observed benzene was 6.6 ppb on Oct 17 (8AM) and 3.5 ppb on Oct 21 (10AM). • CAMx under-predicted peaks using CALMET and WRF Run 1. • CAMx with WRF Run 2 predicted benzene comparable in magnitude to observed concentrations, but ~half a day off in time. • Meteorological conditions needed for high benzene concentrations: • Low Kv’s. • Both WRF runs and CALMET met this criteria. • Low wind speeds • Both WRF runs had comparable or slower wind speeds compared to observations, but WRF Run 2 was faster. • An industrial facility is located ENE of Solar Estates. • On October 17 and 21, WRF Run 1 failed to rotate early morning winds clockwise from north to southeast. • WRF Run 2 had a similar problem on October 17, but performed better on October 21, resulting in relatively higher benzene (3.2 ppb in Run 2 vs. 0.6 ppb in Run 1; observed = 3.5 ppb)

  21. Summary • UT is operating a dense ambient monitoring network for air toxics with a lifetime of approximately 10 years that includes hourly auto-GCs and camera surveillance, threshold triggered canister samples and meteorological data for the Corpus Christi area. • Conceptual models of meteorological conditions and associated temporal trends and emission source regions have been developed for TNMHC and benzene. • Similar to other areas, higher concentrations of benzene and TNMHC tend to occur during the night and early morning hours and during the fall/winter. • Concentration gradients in benzene exist between monitors and trajectory suggests strong associations with site-specific emissions sources. • On-going work focuses on the development and application of Gaussian and neighborhood-scale photochemical grid models. • Evaluate and compare model performance (AERMOD, CALPUFF, and CAMx). • A primary goal of our work is the development of a modeling system that predicts the three-dimensional concentrations of selected air toxics concentrations (e.g., benzene) at the neighborhood (< 1-km horizontal resolution) scale. • Model results used to: • assess the accuracy of the emission inventories and the sensitivity of predictions in the spatial patterns of air toxics. • examine whether the locations of the existing air quality monitors captures the locations of predicted maximum air toxics concentrations.

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