regional air pollution study alissa dickerson, m.s. environmental specialist enviroscientists, inc....
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Regional Air Pollution Study
Alissa Dickerson, M.S.Environmental Specialist
Enviroscientists, Inc.
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Goal of StudyGoal 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
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OverviewOverview
IntroductionMethodologyAnalysisResults & Discussion: Case StudiesSummary
IntroductionMethodologyAnalysisResults & Discussion: Case StudiesSummary
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What is Spatial Representativeness?
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
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Why is it important?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
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Why is it Important? (cont.)
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
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IntroductionIntroduction
Visibility reduction 1977 CAAUSEPA Regional Haze Rule, Final
(40 CFR 51, 1999)
Interagency Monitoring of Protected
Visual Environments = IMPROVE (1985)
5 regional organizations
Visibility reduction 1977 CAAUSEPA Regional Haze Rule, Final
(40 CFR 51, 1999)
Interagency Monitoring of Protected
Visual Environments = IMPROVE (1985)
5 regional organizations
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The IMPROVE Network: Objectives
The IMPROVE Network: Objectives
Federally mandated Class I areasNational parks, monuments, wilderness
areasIdentify current conditions of visibilityDetermine aerosol species and sourcesDocument trendsCultivate representative monitoring
network
Federally mandated Class I areasNational parks, monuments, wilderness
areasIdentify current conditions of visibilityDetermine aerosol species and sourcesDocument trendsCultivate representative monitoring
network
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The IMPROVE NetworkThe IMPROVE Network
163 sites 1-in-3 day
sampling 4 cyclone-based
modules Coarse mass &
speciated fine aerosols
163 sites 1-in-3 day
sampling 4 cyclone-based
modules Coarse mass &
speciated fine aerosols
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The Improve Network bext
visibility The Improve Network bext
visibility Light Extinction Formulabext= 3*f(RH)[Sulfate] + 3*f(RH)[Nitrate] +
4*[Organic Carbon] + 10*[Elemental Carbon] + 1*[ Fine Soil] + 0.6*[Coarse Mass]+ 10
Concentrations [ ] Units=μg/m3
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 Formulabext= 3*f(RH)[Sulfate] + 3*f(RH)[Nitrate] +
4*[Organic Carbon] + 10*[Elemental Carbon] + 1*[ Fine Soil] + 0.6*[Coarse Mass]+ 10
Concentrations [ ] Units=μg/m3
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
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Research ObjectivesResearch ObjectivesDetermine spatial
representativeness of IMPROVE monitors- WRAP
WA, OR, CA, NV, ID, ND, SD, CO, AZ, NM, TX
14 Physiographic Regions
Determine spatial representativeness of IMPROVE monitors- WRAP
WA, OR, CA, NV, ID, ND, SD, CO, AZ, NM, TX
14 Physiographic Regions
Great Basin
Great Plains
Northern Great Plains
Southern Great Plains
Columbia Plateau
Central Rocky Mountains
North Central Lowland Plains
Colorado Plateau
Mexican Highlands
Central Lowland Plains
West Gulf Coastal and Mississippi Alluvial Plains
Southwest Deserts
Southern Rocky Mountains
Cascade Range
Ouachita and Ozark PlateauSierra Nevada Range
Superior Upland
California Central ValleysCalifornia Coast Ranges
Southern Pacific Rainforests
Klamath Mountains
Southern California Ranges
Great Basin
Great Plains
Northern Great Plains
Southern Great Plains
Columbia Plateau
Central Rocky Mountains
North Central Lowland Plains
Colorado Plateau
Mexican Highlands
Central Lowland Plains
West Gulf Coastal and Mississippi Alluvial Plains
Southwest Deserts
Southern Rocky Mountains
Cascade Range
Ouachita and Ozark PlateauSierra Nevada Range
Superior Upland
California Central ValleysCalifornia Coast Ranges
Southern Pacific Rainforests
Klamath Mountains
Southern California Ranges
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ConsiderationsConsiderations
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?
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ConsiderationsConsiderations
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?
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MethodologyMethodology
Data1997-2002, 54 monitors w/most complete dataSix 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
Data1997-2002, 54 monitors w/most complete dataSix 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
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AssumptionsAssumptions
All elemental sulfur is from sulfate -> ammonium sulfate
All nitrate -> ammonium nitrateTotal 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 nitrateTotal organic carbon= C released in four
steps (OC1-OC4) + pyrolized organics (OP)
Thermal Optical Reflectance (TOR) analysis of quartz filter
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AssumptionsAssumptions
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
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Analysis ProceduresAnalysis Procedures1) 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 regionsClimate & 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
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Analysis Procedures (cont.)
Analysis Procedures (cont.)
2) Regional spatial correlation analysis: correlation expected to decrease w/distanceCorrelation matrix of aerosol measurementsDistance matrix (km)
ConsiderationCorrelation 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/distanceCorrelation matrix of aerosol measurementsDistance matrix (km)
ConsiderationCorrelation of site vs. itself = unity[Artificial]= uncertainty * random #+measurement
[Artificial] plotted at distance of 0
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Analysis (cont.)Analysis (cont.)
3) Criteria correlation cut-off = 0.7Rationalize association between
monitoring sites Validation of spatial representativeness
4) SeasonsWarm months: April to SeptemberCold months: October to March
3) Criteria correlation cut-off = 0.7Rationalize association between
monitoring sites Validation of spatial representativeness
4) SeasonsWarm months: April to SeptemberCold months: October to March
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Analysis (cont.)Analysis (cont.)
5) Expected average concentrations density (like temp.) of atmosphere varies w/
altitude [Estimated] = [aerosol]* site density density @ sea levelPut 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 levelPut 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)
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Analysis (cont.)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
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3.The Northern Great Plains Region
3.The Northern Great Plains Region
Characteristics(E) Montana, (NE) Wyoming, & (W) portions of
North and South DakotaTerrain: mostly prairie & rolling hills, mix of
forest and grasslandBadlands composed of steep buttes and
pinnaclesSparse population centers Several coal-fired power plants, west-central ND
Characteristics(E) Montana, (NE) Wyoming, & (W) portions of
North and South DakotaTerrain: mostly prairie & rolling hills, mix of
forest and grasslandBadlands composed of steep buttes and
pinnaclesSparse population centers Several coal-fired power plants, west-central ND
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The N. Great Plains 6-IMPROVE sites
The N. Great Plains 6-IMPROVE sites
Site Name Abbreviation Elevation (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
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Residence Time Analysis WICA1
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
Warm months Prevailing winds
SE Bring in dry air
from SW U.S. Moist warm air
masses from Gulf of Mexico
Few inversions
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Residence Time Analysis MELA1
Residence Time Analysis MELA1
Cold monthsCold
continental air flowing from N/NW from Canada
L system typical, flushes atmosphere
Cold monthsCold
continental air flowing from N/NW from Canada
L system typical, flushes atmosphere
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Aerosol SummaryAerosol Summary
Average Aerosol Concentration During the 20% Worst Visibility Days
0
2
4
6
8
10
12
14
16
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BADL1 LOST1 MELA1 THRO1 ULBE1 WICA1
Average Concentration (ug/m3)
CM
Soil
LAC
OMC
Nitrate
Sulfate
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Aerosol Summary (cont.)Aerosol Summary (cont.)
Average Contribution to Light Extinction During the 20% Worst Visibility Days
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
BADL1 LOST1 MELA1 THRO1 ULBE1 WICA1
Contribution to Bext (1/Mm)
CM
Soil
LAC
OMC
Nitrate
Sulfate
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Estimated Concentration (µg/m3)
Estimated Concentration (µg/m3)
Elevation 500-1000m UNC 1000-1500m UNC
SO4
WARM Months 0.31 0.02 0.26 0.03
COLD Months 0.30 0.03 0.22 0.00
NO3
WARM Months 0.21 0.06 0.17 0.05
COLD Months 0.71 0.27 0.34 0.10
OC
WARM Months 1.10 0.15 1.13 0.02
COLD Months 0.52 0.07 0.44 0.01
EC
WARM Months 0.16 0.01 0.16 0.01
COLD Months 0.13 0.01 0.11 0.01
Soil
WARM Months 0.78 0.10 0.67 0.03
COLD Months 0.37 0.03 0.29 0.06
CM
WARM Months 7.27 0.61 4.67 0.12
COLD Months 3.27 0.19 2.08 0.12
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Test SitesFOPE1 (2yr) NOCH1 (2 yr)
Test SitesFOPE1 (2yr) NOCH1 (2 yr)
Expected UNC FOPE1 UNC Expected UNC NOCH1 UNC
Elevation 500-1000m 638m 1000-1500m 1332m
SO4
WARM Months 0.31 0.02 0.32 0.02 0.26 0.03 0.28 0.01
COLD Months 0.30 0.03 0.29 0.01 0.22 0.00 0.17 0.01
NO3
WARM Months 0.21 0.06 0.21 0.03 0.17 0.05 0.20 0.02
COLD Months 0.71 0.27 0.90 0.04 0.34 0.10 0.21 0.01
OC
WARM Months 1.10 0.15 1.08 0.29 1.13 0.02 1.51 0.34
COLD Months 0.52 0.07 0.54 0.17 0.44 0.01 0.33 0.14
EC
WARM Months 0.16 0.01 0.14 0.01 0.16 0.01 0.19 0.02
COLD Months 0.13 0.01 0.10 0.01 0.11 0.01 0.07 0.01
Soil
WARM Months 0.78 0.10 0.26 0.02 0.67 0.03 0.28 0.02
COLD Months 0.37 0.03 0.11 0.01 0.29 0.06 0.14 0.01
CM
WARM Months 7.27 0.61 6.62 0.20 4.67 0.12 4.79 0.15
COLD Months 3.27 0.19 2.31 0.09 2.08 0.12 1.72 0.08
FOPE1 30m elev.
difference MELA1[NO3]=0.9 µg/m3
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Northern Great Plains Regional Conclusions
Northern Great Plains Regional Conclusions
Relatively flat terrain with good dispersion of air
Atypical stagnation alleviates regional haze problems during most days
SO4 representative ~ 180kmColder 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
SO4 representative ~ 180kmColder months show good agreement out
to 700 km
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Northern Great Plains Regional Conclusions (cont.)
Northern Great Plains Regional Conclusions (cont.)
NO3
Rep. Distance ~ 450 km, 200km warm monthsFactor – chemical nature to volatilize quickly in
warmer temperatures or not form at all
OCSoutherly located IMPROVE samplers recorded
higher OC concentrations on worst visibility days
Forest fire episodes Rep. distance (Southern region) ~250 km
NO3
Rep. Distance ~ 450 km, 200km warm monthsFactor – chemical nature to volatilize quickly in
warmer temperatures or not form at all
OCSoutherly located IMPROVE samplers recorded
higher OC concentrations on worst visibility days
Forest fire episodes Rep. distance (Southern region) ~250 km
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Thank youThank you
Questions?Questions?