1. Regional Air Pollution Study Alissa Dickerson, M.S. Environmental Specialist Enviroscientists, Inc. Alissa Dickerson, M.S. Environmental Specialist Enviroscientists, Inc.

2. 2 Goal of Study  Western Regional Air Partnership (WRAP) http://wrapair.org  Causes of Haze Assessment (COHA)  Goal: provide assessment of Class I areas through integrated approach  www.coha.dri.edu  Western Regional Air Partnership (WRAP) http://wrapair.org  Causes of Haze Assessment (COHA)  Goal: provide assessment of Class I areas through integrated approach  www.coha.dri.edu

3. 3 Overview  Introduction  Methodology  Analysis  Results & Discussion: Case Studies  Summary  Introduction  Methodology  Analysis  Results & Discussion: Case Studies  Summary

4. 4 What is Spatial Representativeness?  Area within which pollutant concentrations are approximately constant  Quantitative and qualitative approach to investigate equivalency of measurements  Area within which pollutant concentrations are approximately constant  Quantitative and qualitative approach to investigate equivalency of measurements

5. 5 Why is it important?  Data assessments can determine dependence and elicit solutions  Comprehensive picture of a complex system  Tool to assess degree to which measured concentrations can be derived from reference points  Optimal network design  Data assessments can determine dependence and elicit solutions  Comprehensive picture of a complex system  Tool to assess degree to which measured concentrations can be derived from reference points  Optimal network design

6. 6 Why is it Important? (cont.)  Evaluation tool to help more efficiently in mediation of environmental problems  Understanding regional visibility & reduction  Evaluation tool to help more efficiently in mediation of environmental problems  Understanding regional visibility & reduction

7. 7 Introduction  Visibility reduction 1977 CAA  USEPA Regional Haze Rule, Final (40 CFR 51, 1999)  Interagency Monitoring of Protected Visual Environments = IMPROVE (1985)  5 regional organizations  Visibility reduction 1977 CAA  USEPA Regional Haze Rule, Final (40 CFR 51, 1999)  Interagency Monitoring of Protected Visual Environments = IMPROVE (1985)  5 regional organizations

8. 8 The IMPROVE Network: Objectives  Federally mandated Class I areas  National parks, monuments, wilderness areas  Identify current conditions of visibility  Determine aerosol species and sources  Document trends  Cultivate representative monitoring network  Federally mandated Class I areas  National parks, monuments, wilderness areas  Identify current conditions of visibility  Determine aerosol species and sources  Document trends  Cultivate representative monitoring network

9. 9 The IMPROVE Network  163 sites  1-in-3 day sampling  4 cyclone-based modules  Coarse mass & speciated fine aerosols

10. 10 The Improve Network b ext visibility  Light Extinction Formula  b ext = 3*f(RH)[Sulfate] + 3*f(RH)[Nitrate] + 4*[Organic Carbon] + 10*[Elemental Carbon] + 1*[ Fine Soil] + 0.6*[Coarse Mass]+ 10  Concentrations [ ] Units= μ g/m 3  Units= Mm -1, proportional to amount of light lost over distance of 1 million meters  Rayleigh Scattering= 10 Mm -1, proportional 0.0 deciviews or 400 km  Light Extinction Formula  b ext = 3*f(RH)[Sulfate] + 3*f(RH)[Nitrate] + 4*[Organic Carbon] + 10*[Elemental Carbon] + 1*[ Fine Soil] + 0.6*[Coarse Mass]+ 10  Concentrations [ ] Units= μ g/m 3  Units= Mm -1, proportional to amount of light lost over distance of 1 million meters  Rayleigh Scattering= 10 Mm -1, proportional 0.0 deciviews or 400 km

11. 11 Research Objectives  Determine spatial representativeness of IMPROVE monitors- WRAP  WA, OR, CA, NV, ID, ND, SD, CO, AZ, NM, TX  14 Physiographic Regions

12. 12 Considerations  What are most dominant chemical species during 20% worst visibility days within a region?  What are practical statistical and spatial analysis methods?  How do concentrations vary by season?  What are most dominant chemical species during 20% worst visibility days within a region?  What are practical statistical and spatial analysis methods?  How do concentrations vary by season?

13. 13 Considerations  How can expected average concentrations be determined for a region?  What is a method to test validity?  How can expected average concentrations be determined for a region?  What is a method to test validity?

14. 14 Methodology  Data  1997-2002, 54 monitors w/most complete data  Six aerosol species  Sulfates, nitrates, organic carbon (OC), elemental carbon (EC), fine soil, coarse mass (CM)  Focus: Upper 20% of calculated visibility impairment values or 20% worst visibility days  Data  1997-2002, 54 monitors w/most complete data  Six aerosol species  Sulfates, nitrates, organic carbon (OC), elemental carbon (EC), fine soil, coarse mass (CM)  Focus: Upper 20% of calculated visibility impairment values or 20% worst visibility days

15. 15 Assumptions  All elemental sulfur is from sulfate -> ammonium sulfate  All nitrate -> ammonium nitrate  Total organic carbon= C released in four steps (OC1-OC4) + pyrolized organics (OP) Thermal Optical Reflectance (TOR) analysis of quartz filter  All elemental sulfur is from sulfate -> ammonium sulfate  All nitrate -> ammonium nitrate  Total organic carbon= C released in four steps (OC1-OC4) + pyrolized organics (OP) Thermal Optical Reflectance (TOR) analysis of quartz filter

16. 16 Assumptions  Elemental carbon (light absorbing carbon) = EC fractions (EC1-EC3) – pyrolized organics (OP) TOR analysis of quartz filter  Fine soil = sum of Al, Si, K, Ca, Ti particle-induced X-ray emission (PIXE) & Fe X-ray fluorescence (XRF)  Coarse mass = total mass - fine mass  Elemental carbon (light absorbing carbon) = EC fractions (EC1-EC3) – pyrolized organics (OP) TOR analysis of quartz filter  Fine soil = sum of Al, Si, K, Ca, Ti particle-induced X-ray emission (PIXE) & Fe X-ray fluorescence (XRF)  Coarse mass = total mass - fine mass

17. 17 Analysis Procedures  1) Characterize dynamics of regions  Climate & meteorology: wind patterns & back-trajectory analysis (transport)  Graphically displays % of time an air mass spent in an area  Color coded (shading increases w/ residence)  Topography: elevation & intervening terrain  Emission sources and population centers  1) Characterize dynamics of regions  Climate & meteorology: wind patterns & back-trajectory analysis (transport)  Graphically displays % of time an air mass spent in an area  Color coded (shading increases w/ residence)  Topography: elevation & intervening terrain  Emission sources and population centers

18. 18 Analysis Procedures (cont.)  2) Regional spatial correlation analysis: correlation expected to decrease w/distance  Correlation matrix of aerosol measurements  Distance matrix (km)  Consideration  Correlation of site vs. itself = unity [Artificial]= uncertainty * random #+measurement  [Artificial] plotted at distance of 0  2) Regional spatial correlation analysis: correlation expected to decrease w/distance  Correlation matrix of aerosol measurements  Distance matrix (km)  Consideration  Correlation of site vs. itself = unity [Artificial]= uncertainty * random #+measurement  [Artificial] plotted at distance of 0

19. 19 Analysis (cont.)  3) Criteria correlation cut-off = 0.7  Rationalize association between monitoring sites  Validation of spatial representativeness  4) Seasons  Warm months: April to September  Cold months: October to March  3) Criteria correlation cut-off = 0.7  Rationalize association between monitoring sites  Validation of spatial representativeness  4) Seasons  Warm months: April to September  Cold months: October to March

20. 20 Analysis (cont.)  5) Expected average concentrations  density (like temp.) of atmosphere varies w/ altitude  [Estimated] = [aerosol]* site density density @ sea level  Put conc. into elevation ranges based on natural breaks, then averaged= regional estimated conc.  Uncertainty= standard deviation of average concentrations within elevation range (applicable only with 2 or more sites)  5) Expected average concentrations  density (like temp.) of atmosphere varies w/ altitude  [Estimated] = [aerosol]* site density density @ sea level  Put conc. into elevation ranges based on natural breaks, then averaged= regional estimated conc.  Uncertainty= standard deviation of average concentrations within elevation range (applicable only with 2 or more sites)

21. 21 Analysis (cont.)  6) Test of representativeness  Analyzed sites within each region  Calculated seasonal average concentrations  Uncertainty= average measurement uncertainty  Compared to estimated concentrations  6) Test of representativeness  Analyzed sites within each region  Calculated seasonal average concentrations  Uncertainty= average measurement uncertainty  Compared to estimated concentrations

22. 22 3.The Northern Great Plains Region  Characteristics  (E) Montana, (NE) Wyoming, & (W) portions of North and South Dakota  Terrain: mostly prairie & rolling hills, mix of forest and grassland  Badlands composed of steep buttes and pinnacles  Sparse population centers  Several coal-fired power plants, west-central ND  Characteristics  (E) Montana, (NE) Wyoming, & (W) portions of North and South Dakota  Terrain: mostly prairie & rolling hills, mix of forest and grassland  Badlands composed of steep buttes and pinnacles  Sparse population centers  Several coal-fired power plants, west-central ND

23. 23 The N. Great Plains 6-IMPROVE sites Site NameAbbreviationElevation (m) Badlands National Park BADL1 736 Lostwood Wilderness Area LOST1 692 Medicine Lake Wilderness Area MELA1 605 Theodore Roosevelt Nat'l Park THRO1 853 UL Bend Wilderness Area ULBE1 893 Wind Cave National Park WICA1 1300

24. 24 Residence Time Analysis WICA1  Warm months  Prevailing winds SE  Bring in dry air from SW U.S.  Moist warm air masses from Gulf of Mexico  Few inversions

25. 25 Residence Time Analysis MELA1  Cold months  Cold continental air flowing from N/NW from Canada  L system typical, flushes atmosphere

26. 26 Aerosol Summary

27. 27 Aerosol Summary (cont.)

28. 28 Estimated Concentration (µg/m 3 ) Elevation500-1000mUNC1000-1500mUNC SO4 WARM Months0.310.020.260.03 COLD Months0.300.030.220.00 NO3 WARM Months0.210.060.170.05 COLD Months0.710.270.340.10 OC WARM Months1.100.151.130.02 COLD Months0.520.070.440.01 EC WARM Months0.160.010.160.01 COLD Months0.130.010.110.01 Soil WARM Months0.780.100.670.03 COLD Months0.370.030.290.06 CM WARM Months7.270.614.670.12 COLD Months3.270.192.080.12

29. 29 Test Sites FOPE1 (2yr) NOCH1 (2 yr) ExpectedUNCFOPE1UNCExpectedUNCNOCH1UNC Elevation500-1000m 638m 1000-1500m 1332m SO4 WARM Months0.310.020.320.020.260.030.280.01 COLD Months0.300.030.290.010.220.000.170.01 NO3 WARM Months0.210.060.210.030.170.050.200.02 COLD Months0.710.270.900.040.340.100.210.01 OC WARM Months1.100.151.080.291.130.021.510.34 COLD Months0.520.070.540.170.440.010.330.14 EC WARM Months0.160.010.140.010.160.010.190.02 COLD Months0.130.010.100.010.110.010.070.01 Soil WARM Months0.780.100.260.020.670.030.280.02 COLD Months0.370.030.110.010.290.060.140.01 CM WARM Months7.270.616.620.204.670.124.790.15 COLD Months3.270.192.310.092.080.121.720.08 FOPE1 30m elev. difference MELA1 [NO3]=0.9 µg/m 3

30. 30 Northern Great Plains Regional Conclusions  Relatively flat terrain with good dispersion of air  Atypical stagnation alleviates regional haze problems during most days  SO 4  representative ~ 180km  Colder months show good agreement out to 700 km  Relatively flat terrain with good dispersion of air  Atypical stagnation alleviates regional haze problems during most days  SO 4  representative ~ 180km  Colder months show good agreement out to 700 km

31. 31 Northern Great Plains Regional Conclusions (cont.)  NO 3  Rep. Distance ~ 450 km, 200km warm months  Factor – chemical nature to volatilize quickly in warmer temperatures or not form at all  OC  Southerly located IMPROVE samplers recorded higher OC concentrations on worst visibility days  Forest fire episodes  Rep. distance (Southern region) ~250 km  NO 3  Rep. Distance ~ 450 km, 200km warm months  Factor – chemical nature to volatilize quickly in warmer temperatures or not form at all  OC  Southerly located IMPROVE samplers recorded higher OC concentrations on worst visibility days  Forest fire episodes  Rep. distance (Southern region) ~250 km

32. 32 Thank you Questions?