1. Ozone Transport Analysis Using Back-Trajectories and CAMx Probing Tools
Sue Kemball-Cook, Greg Yarwood, Bonyoung Koo and Jeremiah Johnson, ENVIRON
Jim Price and Mark Estes, TCEQ
2010 CMAS Conference, October 11-13, 2010
Chapel Hill, North Carolina

2. Background
Lowering the 8-hour standard increases the importance of background ozone and transport
Simulation of ozone transport in photochemical models will be critical for development of ozone control strategies
CAMx probing tools can be used to quantify background ozone

3. Objectives Investigate ozone transport into Texas
Which source regions contribute to high ozone in Texas?
What effect do emissions changes in those source regions have on Texas ozone?
Use a suite of independent tools to analyze ozone transport
HYSPLIT back trajectories
Show pathways for air arriving at Texas monitors on high ozone days
New MM5CAMx-to-ARL tool reformats CAMx winds for input to HYSPLIT and calculates vertical velocities using CAMx algorithm
CAMx probing tools
APCA (Anthropogenic Precursor Culpability Assessment)
HDDM (Higher order Decoupled Direct Method)

4. Using APCA and HDDM to Study Modeled Transport
CAMx APCA and HDDM probing tools provide complementary information for transport analysis
APCA
Can quantify contributions by source region and source category to ozone at a given receptor and time
Does not give information about how such a contribution may change if emissions change
HDDM
Can provide estimates of model response to changes in emissions

5. APCA/HDDM Source Region Maps
APCA emissions source regions shown in red
HDDM emissions source regions shaded
Ohio and Tennessee Valleys (blue)
Southeastern U.S. (pink)
3 emissions source categories
Elevated anthropogenic emissions
Biogenic emissions
All other emissions
Buffer around Texas, roughly corresponding to 12 km Texas domain

6. Episode Selection
Modeled three Texas high ozone episodes during
Episode selection based on monitoring network and model performance evaluation results
More rural ozone monitors in Texas during 2006 than 2005
Focus on periods of high diagnosed and modeled transport from Ohio and Tennessee Valleys and Southeastern U.S.
June 13-15, 2006
Good model performance in both 12 km grid and in source regions in 36 km grid; transport from OH-TN Valleys and SE diagnosed using HYSPLIT back trajectories

7. June 13-15, 2006 Transport Episode
Back trajectories from TCEQ analysis using EDAS meteorological inputs to HYSPLIT
Transport from OH-TN Valleys and SE into Texas

8. June 9-15, 2006: MPE for Source Regions
Ohio/Tennessee
Valleys
Southeast
Transport
Good model performance with small positive bias

9. Monitors Used in APCA/HDDM Analysis
Used rural monitors sited upwind of non-attainment areas
Selected monitors based on location and MPE
During transport episodes, evaluated source contributions with APCA at these receptors at the time of daily max 8-hour average ozone (DM8)

10. San Augustine, TX: June 14, 2006
Largest contributions from Louisiana, Tennessee, BCs, other states in OH-TN Valley source region
APCA and HYSPLIT back trajectories are consistent in assessment of source regions

11. Ozone Sensitivity to Change in Elevated Anthro NOx Emissions in the Source Regions
Sensitivity of DM8 to elevated anthropogenic NOx (eaNOx) emissions in the OH-TN and SE source regions when > 60 ppb
For eaNOx only,  calculate sensitivities
S1OH-TN~∂O3 _____, S1SE ~ ∂O3_____,
∂(eaNOxOH-TN) ∂(eaNOxSE)
S2 OH-TN~ ∂2O3________, S2SE ~ ∂2O3 ____,
∂(eaNOxOH-TN) ∂(eaNOxSE)2
where OT=Ohio and Tennessee Valleys, SE=Southeastern U.S.
How sensitive is East Texas ozone to emissions in these source regions?

12. June 13-15, 2006: Average S1OT and S2OT
S1OT generally positive and largest in source regions
Emissions increase generally would increase ozone; emissions reduction would decrease ozone
S1OT negative near large NOx sources; i.e. NOx reduction increases ozone (NOx disbenefit)
East-west S1OT gradient across Texas, 1-4 ppb on average over episode in East TX
S2OT largest in vicinity of large coal-fired power plants along the Ohio River

13. Sensitivity of Texas Ozone to Reductions in Source Region eaNOx
For a given monitor, calculate ozone change from emissions perturbation Δε using Taylor series expansion about unperturbed state, C(0)
C=ozone concentration, S(i) are sensitivities
Where Δε=-0.20 for 20% emissions reduction in the source region, for example, and C(0)=DM8 at the monitor in the unperturbed case
Neglecting higher order terms Rn+1
Plot emissions change Δε versus change in ozone C(Δε)-C(0) at the monitor (next slide)

14. Change in Texas Ozone from Emissions Reduction in OH-TN Valley Source Region
Shows change in DM8 at rural TX monitors that would result from reducing eaNOx in OH-TN source region
NEWT and SAGA show largest ozone reductions

15. Zero-Out Contribution
HDDM coefficients can be used to estimate effect on ozone of removing (zeroing out) one or more emissions sources
For 2 emitters j and k, zero out contribution (ZOC) is calculated
For the OH-TN and SE source regions, ZOC is given by
ZOC(OT+SE)=(S(1)OT-½S(2)OT,OT)+ (S(1)SE-½S(2)SE,SE)- S(2)OT,SE
Here, we calculate components of ZOC for OH-TN and SE eaNOx emissions and present them separately, as cross term was negligible

16. Comparison of APCA and HDDM ZOC Estimates for eaNOx
APCA/HDDM
HYSPLIT Back Trajectories
The APCA and HDDM tools agree on the relative importance of these two source regions in contributing to high ozone in Texas
APCA and HDDM consistent with the HYSPLIT back trajectories

17. Conclusions
HYSPLIT, APCA and HDDM provide complementary information on
model winds that define transport pathways from source regions to receptor regions
ozone source apportionment
sensitivity of receptors to emissions changes in the source regions
Because their formulations are independent of one another, each of these tools can serve as a way to evaluate information provided by the others
Used in combination, these tools can provide a valuable resource for control strategy development.

18. Questions?