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

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

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)

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

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

Episode Selection Modeled three Texas high ozone episodes during 2005-6 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

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

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

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)

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

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)2 ∂(eaNOxSE)2 where OT=Ohio and Tennessee Valleys, SE=Southeastern U.S. How sensitive is East Texas ozone to emissions in these source regions?

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

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)

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

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

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

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.

Questions?