Causes Haze Assessment Green

7/30/2019 Causes Haze Assessment Green

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Causes of Haze Assessment

Mark Green

Desert Research Institute

Marc Pitchford, Chair

Ambient Monitoring & Reporting Forum


2/31


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


3/31


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


4/31

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


5/31

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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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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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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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?


10/31


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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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.


18/31

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?


25/31

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


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


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

Documents

Causes Haze Assessment Green