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Natural Haze Sensitivity Study “Final” Update Ivar Tombach RPO Monitoring/Data Analysis Workgroup Call 8 May 2006.

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Presentation on theme: "Natural Haze Sensitivity Study “Final” Update Ivar Tombach RPO Monitoring/Data Analysis Workgroup Call 8 May 2006."— Presentation transcript:

1 Natural Haze Sensitivity Study “Final” Update Ivar Tombach RPO Monitoring/Data Analysis Workgroup Call 8 May 2006

2 2 Previous Presentations Described project approach Evaluated uncertainties in default concentration estimates Showed weaknesses in current method for estimating haziest 20% days Demonstrated division of country into natural conditions sensitivity zones Demonstrated prototype Sensitivity Calculator In separate work for VISTAS (published in JAWMA), evaluated effects of possible refinements to default natural conditions for the VISTAS region

3 3 Today’s Topics Sea salt concentrations and their impacts on natural conditions and glide paths Seasonal variation of current haziest and best 20% days in each sensitivity zone Outline for final report Left out at last moment -- ranges of estimates of natural concentrations in each sensitivity zone

4 4 Natural Conditions Sensitivity Zones

5 5 Sea Salt

6 6 How Does Sea Salt Fit In? Red -- Largest valueBlue -- Smallest value

7 7 Average Sea Salt Impacts on Extinction Average impact > 5 Mm -1 : Point Reyes W, CA Redwood NP, CA Simeonof W, AK Average impact between 4 and 5 Mm -1 Virgin Islands NP Average impact between 1 & 2 Mm -1 Brigantine W, NJ Cape Romain W, SC Everglades NP, FL Haleakala NP, HI Hawaii Volcanoes NP, HI Kalmiopsis W, OR Olympic NP, WA Pinnacles NM and Ventana W, CA

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10 10 Seasonality of Current Haziest and Clearest Conditions

11 11 Annual Distribution of Best and Worst 20% Days in 1999-2003 by Sensitivity Zone On the next plots, each red data point is the monthly average of the frequencies of occurrence of the worst 20% days over IMPROVE sites in a zone during (variously) 1 to 5 years. Blue points indicate corresponding best 20% frequencies. Best/worst counts were taken from the extinction statistics matrix on the VIEWS web. Not all IMPROVE sites are in that matrix; the number of sites considered is indicated on each panel. The f(RH) values are averages of climatological monthly averages for the corresponding IMPROVE sites.

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16 16 Report Outline

17 17 1. Brief Overview of 1st Stage Regional Haze Planning Process Determine current (baseline) haze index for 20% haziest days Estimate natural haze index for 20% haziest days –Issue of transboundary transport Difference between current and natural HI defines uniform reasonable progress (URP) Set 20% clearest baseline days as future upper limit for clear days Develop control strategy to achieve reasonable progress by 2018 –Provide plot showing URP in terms of b ext (relates better to amount of control) Describe purpose of this report

18 18 2. Current Baseline Concentrations and Haze Index (HI) Calculate average annual, 20% haziest, and 20% clearest conditions –Map b ext and HI over US 1999-2003 with old IMPROVE algorithm May also have 2000-2004 with new IMPROVE algorithm Preview of natural conditions sensitivity zones –Refer to Sec. 6.2 for full description –Show map –Show plots of monthly frequencies of occurrence of clearest and haziest 20% days in 1999-2003, plus RH

19 19 3. Determining Default Natural Haze Conditions Determine default annual natural concentrations Limitations of default estimates –Only 2 regions for whole country –Large error factors –Neglects sea salt –Annual average doesn’t reflect episodic/seasonal events such as fires and intercontinental dust Calculate b ext and HI using current IMPROVE algorithm –Show map over US –Discuss implications of uncertainties

20 20 Estimate 20% haziest/clearest natural conditions (Ames & Malm method) –Reduce current sulfate and nitrate (but not others) Make consistent with default concentrations on average –Calculate SD of average natural HI Show plots from Ames & Malm –Assume normal distribution of HI –Use 90th %ile to represent haziest 20% Show maps of resulting 20% clearest and haziest natural HI Critique of method Errors in EPA’s guidance –Wichita Mountains assigned conditions for East, but located in default West –20% haziest & clearest days counted inconsistently (unsymmetrical), so frequencies are not equal

21 21 4. Evolving Refinements New IMPROVE algorithm –Includes sea salt lower bound estimate –Rayleigh coefficient varies with altitude –Changed multiplier for deducing POM from OC –Bimodal sulfate, nitrate, and organics scattering efficiencies –Based on analysis of current data Issues about appropriateness of algorithm for natural conditions New approach for estimating 20% haziest natural days –Does not assume natural HI distribution is normal –Does not assume 90th %ile represents haziest 20% –Results differ from those of original method

22 22 5. Determining Glide Path Establish baseline HI for haziest days Subtract haziest 20% natural conditions HI estimate to get required improvement by 2064 Inconsistency: natural HI values in EPA’s guidance are at centroid of Class I area, while baseline HI are determined at IMPROVE sampler, which is sometimes far away. –Implications of this inconsistency for tracking progress

23 23 6. Potential Refinements to Natural Concentrations Estimates Summarize important natural PM components –Comment on seasonal variations Introduce natural conditions sensitivity zones –Show map (again) –Explain rationale and give basis for choices of boundaries –Show matrices illustrating how various quantities vary between the zones

24 24 Summarize rough ranges of annual average natural concentrations, and their uncertainties –Lower bound of sea salt from new IMPROVE calculations –Other ranges from literature, when feasible –Indicate when uncertainties are too large for useful estimates –Discuss seasonal variations Assess implications of the refinements versus default estimates –Options -- (1) Already included; (2) add to default; (3) decrease default; and (4) too uncertain to use Provide table of ranges of potential adjustments for each sensitivity zone

25 25 Assess implications of adjustment ranges on glide paths –Which annual average component adjustments are likely to be most important in each zone In terms of relative (%) reduction in emissions In terms of absolute (∆b ext ) reduction in emissions Consider implications of uncertainties –Summarize in table or plot –How do seasonal variations affect the conclusions above? Ideas on how to use seasonally-varying conditions

26 26 7. The Natural Conditions Sensitivity Calculator Purpose and concept –Calculate effects of user-defined natural conditions changes at any Class I area Assumptions, formulas used, and limitations How to use the calculator

27 27 8. Summary of Key Findings and Their Implications Principal findings Implications for the first stage of the regional haze planning process Recommendations concerning the planning approach Recommendations concerning natural conditions refinements by the States

28 28 9. References Appendices Plots, whenever there are too many to fit comfortably in the body of the report

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