causes haze assessment green
TRANSCRIPT
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Causes of Haze Assessment
Mark Green
Desert Research Institute
Marc Pitchford, Chair
Ambient Monitoring & Reporting Forum
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Causes of Haze Assessment
Goals & ObjectivesAssess causes of haze for all WRAP Federal Class I
Areas on a periodic basis every five years
Encourage broad-based stakeholder participationthroughout the assessment process
Enhance the utility and accessibility of the results for
SIP & TIP development,
Regional air quality model evaluation & interpretation,Identification of monitoring gaps,
Improved methodology for setting natural haze levels, &
Tracking effectiveness of emission control programs
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Causes of Haze Assessment
Approach Data analysis methods are selected to respond to a series
of questions concerning the causes of haze
Will require numerous methods applied to ambient
monitoring data, but not regional air quality models
As they become available, AMRF reviews draft responses
to each question & posts final responses to a web site
Results are designed for computer searches, with internallinks and directories for an easily navigated virtual report
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Causes of Haze Assessment Process
WRAP/AMRFCauses of Haze Questions
Contractor
Data Analyses
WRAP/AMRF
Review Draft Results
WRAP/AMRF
Post Final Results on Web
Separate Review &
Posting for Each
Analysis & Question
Each Analysis Method
Addresses 1 or More
of the Questions
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Grand
Canyon
Mount
Rainier
Lost
Wood
etc.
Question 1a
Question 1b
Question 1c
Question 1d
Question 2a
etc.
Each Question is Addressed at Each Class I Areas
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Method 1 Method 2 Method 3 etc.
Question 1a
Question 1b
Question 1c
Question 1d
Question 2a
etc.
Each Analysis Method Addresses One or More Questions
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Causes of Haze Assessment
Questions
What aerosol components are responsible for haze?
What are the major components for best, worst &
average days & how do they compare?How variable are they episodically, seasonally,interannually?
What site characteristics best group sites with similar
patterns of major components?How do the relative concentration of the majorcomponents compare with the relative emission ratesnearby & regionally?
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Causes of Haze Assessment
Questions - continued
What is meteorologys role in the causes of haze?How do meteorological conditions differ for best, worst and typicalhaze conditions?
What empirical relationships are their between meteorologicalconditions and haziness?
How well can haze conditions be predicted solely usingmeteorological factors?
What site characteristics best group sites with similar relationshipsbetween meteorological conditions and haze?
How well can interannual variations in haze be accounted for byvariations in meteorological conditions?
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Causes of Haze Assessment
Questions - continued What are the emission sources responsible for haze?
What geographic areas are associated with transported air that
arrives at sites on best, typical & worst haze days?
Are the emission characteristics of the transport areas consistentwith the aerosol components responsible for haze?
What do the aerosol characteristics on best, typical and worst
days indicate about the sources?
What does the spatial & temporal pattern analysis indicate aboutthe locations and time periods associated with sources
responsible for haze?
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Causes of Haze Assessment
Questions - continued What are the emission sources responsible for haze?
- continued -
What evidence is there for urban impacts on haze & what is the
magnitude & frequency when evident?
What connections can be made between sample periods with
unusual species concentrations & activity of highly sporadic
sources (e.g. major fires & dust storms)?
What can be inferred about impacts from sources in other states,other RPOs & other countries?
What refinements to default natural haze levels can be made
using ambient monitoring and emission data?
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Causes of Haze Assessment
Questions - continued
Are there detectable &/or statistically significant
multi-year trends in the causes of haze?
Are the aerosol components responsible for hazechanging?
Where changes are seen, are they the result of
meteorological or emissions changes?Where emissions are known to have changed, are
there corresponding changes in haze levels?
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Assessment Approach
Start with basics, sequentially increase complexity
Most effort for 35 sites with 7 or more years data
Reduced set of analyses for remaining 44 sites with
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2 Meteorology& Haze
Descriptive Trajectory Episode Cluster Factor Receptor
Modeling
Statistical
Tests
2a.
Meteorology
for best,
middle, worstdays
Climatology of
haze
mesoscale,
synoptic scalefactors
Residence
time,
conditional
probability
Meteorology
2b. Empirical
relationships
between
meteorology
and haze
Wind
speed/direction,
RH,
precipitation
and haze
Similar Days
(wind fields,
trajectories)
Wind
fields
-2c. Explain
best & worstdays by
meteorological
factors
Extinction rose Frequency of
clusters
2d. Site
characteristics
& relationship
betweenmeteorology
& haze
Site
meteorology
Meteorological
based site
clustering
2e. Interannual
variation in
haze &
meteorology
Year-to-
year
Residence
time
variation
Year-to-year
variation in
met. cluster
frequency
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Period of record for IMPROVE/protocol sites in WRAP region 119 of 156 visibility protected Class I areas in WRAP
region
78 have IMPROVE sampler in or nearby Class I area
3 Class I areas (Brand Canyon, Saguaro, andYellowstone) have 2 IMPROVE monitoring sites
37 of sites with relatively long-term data, startingbetween 1988 and 1994
28 sites >10 years data, 9 sites 7-9 years data Remaining sites started between 1999 and 2002 ,0-3
years data
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Prepare emissions density maps
Help in interpreting the aerosol component data;
Determine relationship of sources to the Class I
areas;
Interpreting results of backtrajectory analysis;
To examine relationships between mesoscale
meteorological transport and efforts of the
sources upon Class I areas
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Describe monitoring sites
Their representation of the Class I area and
nearby Class I areas;
Relationship to terrain features, bodies of water,etc.;
Proximity to major point sources, cities, etc.
Information from the emissions compilationdescribed above will be quite useful.
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Assess meteorological setting of sites
Expected mesoscale flow patterns of interest
(sea/land breeze, mountain/valley winds,
convergence zones,etc.);Orographic precipitation patterns (i.e. favored for
precipitation, or in rain-shadow);
Inversion layers;Potential for transport from cities and other
significant sources/source areas.
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Aerosol data analysis
Descriptive statistics and interpretation for aerosol data-individual components and reconstructed extinction
Document, interpret component spatial and seasonalpatterns- Best 20%, middle 60%, worst 20% reconstructedextinction days and seasonal patterns by site
Compile, describe spatial and seasonal patterns ofaerosol components frequency distributions.
Interpret aerosol component data in light of emissionssources, monitoring site settings, backtrajectories
Cluster analysis to group sites with similar patterns inaerosol component contributions to haze
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Backtrajectory analysis
Gather backtrajectory endpoint data
Compute and map backtrajectory summary statisticsresidence time by season, best 20% and worst 20%reconstructed extinction and aerosol components for all
sites with 5 years or more of data. Prepare conditional probability maps for high and low
extinction and aerosol components.
Interpret maps using emissions density, location
information, site setting information Mesoscale meteorological analysis needed for
many sitesbacktrajectories will be misleading
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Phase 1 conceptual model and
virtual report
Develop preliminary conceptual modelsregarding the sources of haze at every Class I
area in the WRAP region;Note uncertainties and limitations of the
conceptual models;
Suggest methodologies to refine conceptualmodels in next phase of study
Make information available over Internet asvirtual report
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Subsequent phases
Compile additional meteorological, gaseous,
aerosol, emissions, and source profile data as
needed to complete remaining tasksEpisode analysis -Use combination of
backtrajectory, synoptic, mesoscale meteorological
analysis, aerosol and emissions data toconceptually understand regional or sub-regional
episodes of high aerosol component concentrations
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In-depth meteorological analysis
Mesoscale flow patterns affecting sites
Cluster analysis to group days with similar
patterns and examine aerosol components foreach cluster
Interannual variability of meteorological patterns
Diurnal variations in flow patterns, comparison
with diurnal variation in optical data.
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Emissions changes and receptor
modeling
Evaluation of changes in emissions since 1988 and
relationship to aerosol component concentration changes
Source profile analysis- compile source profiles- note
changes over time since 1988
Establish chemical abundances against which enrichment
factors can be evaluated
Use carbon fractions from TOR analysiscancontributions of different carbon sources be
distinguished?
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Emissions changes and receptor
modeling -continued
Apply Chemical MassBalance (CMB) model
Apply Positive Matrix Factorization (PMF) at
sites with sufficient periods of record of aerosoldata
Apply UnMix model to aerosol data for each site
with sufficient data
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Trends and comprehensive
assessment
Statistical significance tests to determine
significance of trends in component concentrations
Interpret trends in light of trends in emissions andinterannual variability of meteorological patterns-
Trend due to emissions or meteorological changes?
Comprehensive assessment of causes of haze- allClass I areas-formulation of refined conceptual
models applicable to all WRAP Class I areas
Web-based virtual report
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QUESTION Descriptive Trajectory Episode Cluster Factor ReceptorModeling
Statistical
Tests
1 AerosolComponents of
Haze
1a.Components
for best,
middle, worst
days
Aerosol
1b. Temporalvariations of
components
Temporalpatterns
1c. Sitecharacteristics& components
Sites,spatialpatterns
Sites
1d. Componentcontributionsvs. emiss ions
near & reg ional
EmissionsSpatialemiss ions &
aerosol
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2 Meteorology& Haze
Descriptive Trajectory Episode Cluster Factor Receptor
Modeling
Statistical
Tests
2a.
Meteorology
for best,
middle, worstdays
Climatology of
haze
mesoscale,
synoptic scalefactors
Residence
time,
conditional
probability
Meteorology
2b. Empirical
relationships
between
meteorology
and haze
Wind
speed/direction,
RH,
precipitation
and haze
Similar Days
(wind fields,
trajectories)
Wind
fields
-2c. Explain
best & worstdays by
meteorological
factors
Extinction rose Frequency of
clusters
2d. Site
characteristics
& relationship
betweenmeteorology
& haze
Site
meteorology
Meteorological
based site
clustering
2e. Interannual
variation in
haze &
meteorology
Year-to-
year
Residence
time
variation
Year-to-year
variation in
met. cluster
frequency
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3 Emissions
sourcesresponsible
for haze
Descriptive Trajectory Episode Cluster Factor Receptor
Modeling
Statistical
Tests
3a. Transport
patterns best,middle, worst
days
Trajectory
Spatialanalysis
Residence
time,conditional
probability
3b. Emissions
characteristics
for hazy
transport
patterns
Emissions,
Source
profiles,
aerosols
3c. Aerosol
characteristics
and emiss ions
best, middle,worst days
Aerosol Chemical
abundances
Extreme
events
CMB
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3d. Spatial &
temporal
pattern
analysis re:sources
responsible
for haze
EOF
(e.g.
PCA)
CMB,
UnMix,
PMF
Time series
analysis
3e. Urban
source effects
Aerosol
composition,
optical
Mesoscale
transport
Chemical
abundances,
transport
CMB,
UnMix,
PMF
3f. Sporadic
emissionssources &
haze
Emissions,
Transport,aerosol
composition
3g. Emissions
outside US
and haze
Emissions Residence
time,
conditional
probability
3h.Refinement of
natural
visibility
conditions
Temporal &spatial
patterns
Time seriesanalysis-
aerosol
components
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4 Trends incauses ofhaze
Descriptive Trajectory Episode Cluster Factor ReceptorModeling
StatisticalTests
4a. Aerosol
components
changing?
Aerosol Significance
tests
4b. Changes
frommeteorology
or emiss ions?
Frequency of
meteorologicalclusters
Time series
analysis-aerosol,
emissions
4c.
Emissions
changes lead
to changes in
haze?
Emissions,
aerosol
components