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Impacts of Meteorological Variations on RRFs (Relative Response Factors) in the Demonstration of Attainment of the National Ambient Air Quality for 8-hr O 3 and PM 2.5 Yunhee Kim, Joshua S. Fu, and Terry L. Miller University of Tennessee, Knoxville Department of Civil & Environmental Engineering
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2 Outline Background and ObjectiveBackground and Objective Model Configurations and DescriptionsModel Configurations and Descriptions Sensitivity to PBL (Planetary Boundary Layer) SchemesSensitivity to PBL (Planetary Boundary Layer) Schemes Sensitivity to RRF (Relative Response Factors)Sensitivity to RRF (Relative Response Factors) ConclusionsConclusions
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3 8-hr O 3 and PM 2.5 Nonattainment Areas Demonstrate the ozone & PM 2.5 attainment in these nonattainment areas by SIPs (State Implementation Plans). SIPs are submitted using model.
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4 Background New NAAQS for 8-hr O3 was revised from 85 ppb to 75 ppb as May 27, 2008 1 and EPA has strengthen the level of 24-hour PM2.5 standard from 1997 level of 65 g/m³ to 35 g/m³ (effective December 17, 2006). The RRFs (Relative Response Factors) at a site are calculated by modeling results as a ratio of future year predictions divided by base year predictions. Some studies have examined the calculation for the RRFs on various photochemical grid models. ² However, none has reported the sensitivity of the RRFs to the various PBL schemes in MM5 model. Optimal PBL schemes in MM5 model will give higher confidence in control strategies designed based on the modeled response to emission change. 1. US EPA, 2007 2. Pun et al 2008; Sistla et al., 2004; Jones et al., 2005; Arunachalam et al., 2006
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5 Objective To examine the sensitivity of MM5 PBL Schemes with CMAQ simulations to quantify the effects of RRFs (Relative Response Factors) on O 3, annual and 24-hour PM 2.5 SIPs
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6 MM5 Configurations and Descriptions Horizontal Grid Resolution: 36-km/12-km/4-kmHorizontal Grid Resolution: 36-km/12-km/4-km Vertical Grid Resolution: 34 layersVertical Grid Resolution: 34 layers Simulation Period: May 15– September 15, 2002 for baseSimulation Period: May 15– September 15, 2002 for base year and 2009 for future year year and 2009 for future year MM5 (v.3.7) Options:MM5 (v.3.7) Options: PX, Eta M-Y (Mellor-Yamada), –PBL: PX, Eta M-Y (Mellor-Yamada), MRF (Medium Range Forecast), Blackadar (BK), Gayno-seaman (G-S) –LSM: PX, NOAH, 5-layer soil model –Cumulus: KF2 (Kain and Fritsch) –Moisture: Mixed phase –Radiation: RRTM (rapid radiative transfer model)
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7 CMAQ Configurations and Descriptions Model Domain Descriptions:Model Domain Descriptions: –Nestdown from VISTAS’s 12km –121 x 114 grids, 19 layers –CMAQ 4.5 with CBIV mechanism –Initial & Boundary Condition: VISTAS 12-km obtained from VISTAS VISTAS 12-km obtained from VISTAS CON US 36-km VISTAS 12-km ETN 4-km
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8 Simulation Descriptions :Descriptions: : –Emissions: Typical 2002 and 2009 BaseG Emissions obtained from VISTAS Typical 2002 and 2009 BaseG Emissions obtained from VISTAS –SMOKE2.1 used –For Base case : Area, Nonroad, Mobile, Point, Fire and Biogenic emissions –For Sensitivity : Mobile, Point, and Biogenic emissions to rerun
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9 O3 and PM2.5 Observation Sites for Valley and Mountain Areas Valley Sites Mountain Sites For Valley Sites; Mildred, Rutledge, Jefferson, and Anderson For Mountain Sites; Clingmans Dome, Look Rock, and Cove Mtn For PM2.5; Mildred and Look Rock sites are selected as valley and mountain sites, respectively
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10 Methodology 4-km PBL and LSM Schemes Sensitivity Simulations 1.Step – 4-km PBL and LSM Schemes Sensitivity Simulations Baseline: PXBaseline: PX PBL Sensitivity: Eta_N, MRF_N, Eta_5, MRF_5, BK, and G-SPBL Sensitivity: Eta_N, MRF_N, Eta_5, MRF_5, BK, and G-S
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11 Methodology 2. Step – Attainment Test with RRFs for O 3, Annual PM 2.5 and 24-hour PM 2.5 RRFs = mean FVs / mean BVs Where FVs : Future Values modeled for 2009 BVs :Base year Values modeled for 2002 DVFs = DVCs x RRFs Where DVCs : Current Design Values DVFs : Future Design Values
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12 Methodology To demonstrate future attainment of 8-hr O 3 NAAQS and Annual and 24-hr NAAQS for PM 2.5, - If DVFs 0.08 ppm, then it is set to be in attainment of 8-hr O 3 - If DVFs 15 g/m³, then it is set to be in attainment of annual PM 2.5 - If DVFs 65 g/m³, then it is set to be in attainment of 24-hr PM 2.5
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13 Sensitivity to PBL Statistics for Meteorology
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14 Sensitivity to PBL Statistics of Max 8-hr O3
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15 RRFs for 8-hr Ozone PX, MRF_5, and G-S showed the lower RRFs at valley sites while PX and MRF_N presented the highest RRFs at mountain sites. Overall, G-S showed the lowest RRFs at valley and mountain sites.
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16 DVFs for 8-hr Ozone Eta_N and Eta_5 showed larger errors at valley site predicted higher DVFs whereas PX and MRF_N showed larger errors at mountain site presented higher DVFs. Overall, G-S showed the lowest DVFs at valley and mountain sites. It appears that meteorological variations predicted from each PBL scheme has strong relationships with daily maximum 8-hr ozone formation and affects the RRFs.
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17 PM2.5 major Components Sulfate > OC > Ammonium > Crustal Material > Nitrate, EC ValleyMountain Total PM2.5 = SO4 + NO3 + NH4 +OC + EC + Crustal Material
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18 Statistics of each component of PM2.5
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19 Statistics of each component of PM2.5
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20 RRFs for Annual PM 2.5 Valley Mountain
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21 RRFs for 24-hour PM2.5 Valley Mountain
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22 Summary- PM2.5 Valley Annual24-hour OC, Nitrate, and Crustal material are greatly affected by meteorological variations.
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23 Summary- PM2.5 Mountain Annual24-hour The much larger difference in OC RRFs for annual and 24- hr PM2.5 is shown at mountain sites than at valley sites.
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25 Conclusion The model performance of meteorology and air quality had impacts on the estimating RRFs. The differences of 8-hr O3 in RRFs and DVFs are 1-7 % and 1-6 ppb from observed monitoring sites, computed from seven sensitivity tests. This result may lead to a significant outcome in determining attainment or nonattainment status. The differences of PM 2.5 in RRFs are larger at valley site than mountain site whereas the difference of 8-hr ozone is shown in larger RRFs at mountain site than valley site. It appears that there is a relationship between model performance on PBL schemes associated with LSMs and RRFs uncertainties.
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26 Conclusion Large uncertainties are seen for the OC, Nitrate, and Crustal material RRFs whereas smaller uncertainties are seen for the sulfate and ammonium RRFs, which is consistent with good model performance for sulfate and ammonium than OC, Nitrate, and Crustal material. Larger uncertainties for 24-hr PM2.5 RRFs are seen than annual PM2.5 RRFs. Based on our results, PX scheme is the optimal scheme for PM 2.5 and G-S PBL scheme for 8-hr O 3. It may be desirable to apply more than one PBL schemes associated with LSMs to improve the confidence before making a decision for the design of effective emission control strategies for ozone and PM2.5 reductions
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27 Acknowledgements Observed Data for Great Smoky Mountain National Park:Observed Data for Great Smoky Mountain National Park: Jim Renfro, Air Quality Program Manager Great Smoky Mountains National Park Resource Management & Science Division Obtained Data for ICs and BCs and Meteorological Data for VISTAS 12- km:Obtained Data for ICs and BCs and Meteorological Data for VISTAS 12- km: VISTAS (Visibility Improvement State and Tribal Association of the Southeast) Funding:Funding: TDEC (Tennessee Department of Environment and Conservation)
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28 Thank you !
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