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Partially Supported by Inter-RPO WG – NESCAUM Fast Aerosol Sensing Tools for Natural Event Tracking FASTNET CAPITA September 2004 Natural Aerosol Event Detection and Characterization

2004-09-21 Natural Aerosol Event Detection and Characterization

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Page 1: 2004-09-21 Natural Aerosol Event Detection and Characterization

Partially Supported by Inter-RPO WG – NESCAUMFast Aerosol Sensing Tools for Natural Event Tracking FASTNET

CAPITA

September 2004

Natural Aerosol Event Detection and Characterization

Page 2: 2004-09-21 Natural Aerosol Event Detection and Characterization

Contents• Background, Objectives and and Approach

• Direct Evidence of Natural Aerosol Events

• Event Definition: Time Series Approach

• Origin of US Dust Events

• Fine Dust Concentration Pattern

• FAST-CATT: EUS Dust Transport Events

• Regional PM25 Time Pattern AIRNOW (2003-2004)

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Background, Objectives and and Approach to the

Analysis

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Background, Objectives and and Approach to the Analysis

Background • There is considerable evidence that smoke from biomass fires and windblown dust constitutes a

significant component of the PM25 and PM10 over the US.• There is a rich pool of research on smoke and dust but the contributions are fragmented, and

uneven in spatial, temporal an compositional coverage.

Objective• Quantify the the spatio-temporal and chemical pattern of dust and smoke over the US• Identify and possibly quantify the local and origin of NAM dust and smoke

Approach • This natural aerosol analysis applies integrative analysis along several dimensions:

– Access, organize and share historical and recent aerosol-relevant data for the community– Combine surface, satellite data, relevant to emissions, transport and effects– Participate in open, collaborative projects to conduct integrative analysis

Status (Sep. 2004)• The analysis of natural aerosols over the US begun at CAPITA in 2000. Since then several funded projects have supported

aspects of the analysis. Current (2004) activities support the development of collaboration technologies (NSF), haze regulations (RPO) and the use of satellite data (NASA). The natural aerosol pattern/source analysis progressing well but the collaboration with the community has been marginal.

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Aerosol Types and their Events: Dust, Smoke and Haze

• Aerosol are composed of multiple types including urban-industrial sulfates, nitrates and organics (industrial haze), biomass smoke and windblown dust and others.

• Each type may be considered a different pollutant since it has its own class of sources, aerosol properties and it is associated with different effects.

• Current regulation lump the different aerosol species into two size classes PM2.5 and PM10, regardless of their composition in each size range.

• In this sense dust, smoke and haze aerosols (PM25 and PM10) are equivalents to an array of gaseous pollutants, such as SO2, NOx and CO

• The assessment of PM25 and PM10 aerosols can only be accomplished through a full understanding of the component species and their interaction

• This analysis assesses the dynamic, event-characteristics of sulfate, organic, dust and nitrate aerosols and their statistical interaction in producing PM25 events.

Page 6: 2004-09-21 Natural Aerosol Event Detection and Characterization

Regional Haze Rule: Nomenclature and Time Scale Schematics

Temporal ComponentsHistorical condition, pre 2000 status

Baseline condition, established in 2000-2004

Current condition, on 2000-2064 trajectory

Natural condition, absence of human aerosol

Haze ComponentsNatural haze is due to natural windblown dust, biomass smoke and other natural processes

Man-made haze is due industrial activities AND man-perturbed smoke and dust emissions

A fraction of the man-perturbed smoke and dust is assigned to natural by policy decisions

Regulatory ComponentsGoal is to attain natural conditions by 2064;

Establish baseline during 2000-2004

First SIP & Natural Cond. estimate in 2008;

SIP & Natural Cond. revisions every 10 yrs

Page 7: 2004-09-21 Natural Aerosol Event Detection and Characterization

Natural Aerosol Analysis Goals

Natural Haze (this Project, COHA)

• Spatially resolve natural (dust, smoke, other), focus on Class I areas

• Temporally resolve natural haze components for each day

Current Conditions (VIEWS, RPO Projects)

• Spatially resolved haze components, focus on Class I areas

• Temporally resolve aerosol components for each day

• Identify worst/best visibility days for total aerosol

Natural-Total Haze Apportionment (this & other RPO projects)

• Estimate the natural-manmade contribution on best/worst visibility days

• Thus, Current Conditions and the Natural Conditions need to be quantified simultaneously. Thus, coordination with other work is essential.

Page 8: 2004-09-21 Natural Aerosol Event Detection and Characterization

Observational Tools Establishing Aerosol Origin

Direct Evidence

Spatial Pattern Wind Pattern

Composition Temporal Pattern

Trajectory

Modern Methods – similar to century-old approaches but with more data

• Direct Evidence. Photographic, satellite or compelling visual evidence of origin

• Aerosol Composition. Chemical fingerprinting of different source types (speciation, traces)

• Temporal pattern. Chemical rPhysical property analysis (satellite, ASOS, PM2.5)• Spatial Pattern. Chemical

• Transport Pattern. Forward, backward trajectory, residence time analysis • Chemistry with Transport. Combining chemical fingerprinting and transport (CATT)

• Dynamic modeling. Simulation model (forward, inversion) quantifying origin/transport

Historical Methods

• Source attribution methods have been used for the past 2 centuries

• A list of methods was given my Egen, 1835. See paper and PPT

Page 9: 2004-09-21 Natural Aerosol Event Detection and Characterization

Natural Aerosol Conditions – Default Values• The Regional Haze Rule provides initial default values for the Natural Haze Conditions

• The default haze for the West is 8 deciviews while for the East is 11 deciviews

• Obtained by estimating the natural concentration of SO4, EC, OC, NO3, Fine, Coarse Soil

• Weighing each aerosol component by corresponding extinction efficiencies. (Trijonis, 1990)

Mass

West East

Regulatory objective: Fortify the natural condition estimates by the 2008 SIP call.

Page 10: 2004-09-21 Natural Aerosol Event Detection and Characterization

Regional Haze Guide on Fire and Dust

Fire• Forest and other fires can be either natural or man-induced

• Many major forest fires can be inherently classified as natural

• Other fires are intentional (prescribed) to reduce organic fuel accumulation

• Prescribed burning will likely be increasing to reduce catastrophic wildfires

• EPA considers some portion of the prescribed fire emissions as ‘natural’.

• The Western Regional Air Partnership (WRAP) is conducting interesting policy discussions on defining natural and manmade smoke

Dust• Regional Haze guide document is vague on natural dust

• A WRAP RPO study has concluded that windblown dust, not manmade fugitive (mechanically stirred up) dust dominated regional dust.

• Pitchford suggests that a working definition of natural dust could be any dust from non-disturbed soil surfaces; dust from disturbed surfaces would be manmade.

• Clearly, there is a need to begin both the scientific/technical as well as the policy discussion about natural/manmade dust.

Page 11: 2004-09-21 Natural Aerosol Event Detection and Characterization

Direct Evidence of Natural Aerosol Events

Miscellaneous Observations

Page 12: 2004-09-21 Natural Aerosol Event Detection and Characterization

Aerosol Events Catalog

• Aerosol events catalog is community-based

• Each cataloged event has location, time and type codes

• Software tools allow event submission and browsing

• Events are described in flexible user-supplied URLsDust Events

Haze Events

Smoke Events

FASTNET Aerosol Event Catalog

Page 13: 2004-09-21 Natural Aerosol Event Detection and Characterization

Example Event Catalog Entry: Texas Dust Event

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Aerosol Event Catalog: Astronaut Photos

• Astronauts routinely photograph dust and smoke events

• The images and the catalog is on the NASA JSC website

• Aerosol images are registered in the DataFed Catalog and web-accessible through standard VIEWER interface

Page 15: 2004-09-21 Natural Aerosol Event Detection and Characterization

Aerosol Event Catalog: Web pages

• Catalog of generic ‘web objects’ – pages, images, animations that relate to aerosol events

• Each ‘web object’ is cataloged by location, time and aerosol type.

Page 16: 2004-09-21 Natural Aerosol Event Detection and Characterization

Temporal Pattern Regional Speciated Analysis - VIEWS

• Aerosol species time series:– ammSO4f– OCf– ECf– SOILf– ammNO3f– RCFM

Regions of Aggregation

Page 17: 2004-09-21 Natural Aerosol Event Detection and Characterization

Dust

Seasonal + spikes

East – west events are independent

East events occur several times a year, mostly in summer

West events are lest frequent, mostly in spring

US

West

East

Page 18: 2004-09-21 Natural Aerosol Event Detection and Characterization

Dust

asgasgasfg

Northeast

Southwest

Southeast

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Dust

dfjdjdfjetyj

Northwest

S. California

Great Plaines

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Amm. Sulfate

wdthehreherh

US

West

East

Page 21: 2004-09-21 Natural Aerosol Event Detection and Characterization

Amm. Sulfate

stheherheyju

Northeast

Southwest

Southeast

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Amm. Sulfate

shheherh

Northwest

S. California

Great Plaines

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Organic Carbon

sdhdfhefheryj

US

West

East

Page 24: 2004-09-21 Natural Aerosol Event Detection and Characterization

Organic Carbon

sdheherh

Northeast

Southwest

Southeast

Page 25: 2004-09-21 Natural Aerosol Event Detection and Characterization

Organic Carbon

erheryeyj

Northwest

S. California

Great Plaines

Page 26: 2004-09-21 Natural Aerosol Event Detection and Characterization

Reconstructed Fine Mass

estrhertheryu

US

West

East

Page 27: 2004-09-21 Natural Aerosol Event Detection and Characterization

Reconstructed Fine Mass

werty3rueru

Northeast

Southwest

Southeast

Page 28: 2004-09-21 Natural Aerosol Event Detection and Characterization

Reconstructed Fine Mass

wthwrthwerhtr

Northwest

S. California

Great Plaines

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Event Definition:Time Series Approach

• Eastern US aggregate time series

Page 30: 2004-09-21 Natural Aerosol Event Detection and Characterization

Sulfate

EUS Daily Average

50%-ile, 30 day 50%-ile smoothing

Deviation from %-ile

Event – Deviation > percentile value

Median Seasonal Conc.

Mean Seasonal Conc.

Page 31: 2004-09-21 Natural Aerosol Event Detection and Characterization

Reconstructed Fine Mass RCFM

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Reconstructed Fine Mass RCFM

Page 33: 2004-09-21 Natural Aerosol Event Detection and Characterization

Organic Carbon

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Eelemental Carbon

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SOIL

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Nitrate

Page 37: 2004-09-21 Natural Aerosol Event Detection and Characterization

Eastern US PM25 Event Composition

• The largest EUS PM25 events (as RCFM) are simultaneously ‘events’ in sulfate, organics and soil!

• Some EUS PM25 events are single species events

• Some PM25 events are not events in any species; their reinforcing combination causes the PM25 event

Page 38: 2004-09-21 Natural Aerosol Event Detection and Characterization

Origin of US Dust Events

Page 39: 2004-09-21 Natural Aerosol Event Detection and Characterization

Origin of Fine Dust Events over the US

Gobi dust in springSahara in summer

Fine dust events over the US are mainly from intercontinental transport

Fine Dust Events, 1992-2003ug/m3

Page 40: 2004-09-21 Natural Aerosol Event Detection and Characterization

Daily Average Concentration over the US

Dust is seasonal with noise

Random short spikes added

Sulfate is seasonal with noiseNoise is by synoptic weather

VIEWS Aerosol Chemistry Database

Page 41: 2004-09-21 Natural Aerosol Event Detection and Characterization

Dust Event DetectionAverage Fine Soil, Measured

- 0.5

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

01/01/92 05/15/93 09/27/94 02/09/96 06/23/97 11/05/98 03/19/00 08/01/01 12/14/02

Fin

e S

oil

Co

nc.,

ug

/m3

Average Fine Soil, Events

- 0.5

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

01/ 01/ 92 05/ 15/ 93 09/ 27/ 94 02/ 09/ 96 06/ 23/ 97 11/ 05/ 98 03/ 19/ 00 08/ 01/ 01 12/ 14/ 02

Fin

e S

oil

Co

nc.

, u

g/m

3

Average Fine Soil, Events Removed

- 0.5

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

01/01/92 05/15/93 09/27/94 02/09/96 06/23/97 11/05/98 03/19/00 08/01/01 12/14/02

Fin

e S

oil

Co

nc.,

ug

/m3

Plot of the daily avg. fine SOIL

- Baseline with strong seasonality

- Events superimposed on baseline

Separate event days from baseline

- Identify spike (event) days

- Subtract baseline to get event ‘excess’

Determine concentration baseline

- Use ‘spike filter’ to remove outlier

- Declare remaining data as ‘baseline’

Page 42: 2004-09-21 Natural Aerosol Event Detection and Characterization

Seasonal Pattern of Dust Baseline and Events

• The dust baseline concentration is has a 5x seasonal amplitude from 0.2 to 1 ug/m3• The dust events (determined by the spike filter) occur in April/May and in July• The two April/May and the July peak in avg. dust is due to the events

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

01/01/92 02/20/92 04/10/92 05/30/92 07/19/92 09/07/92 10/27/92 12/16/92

EventsBaselineTotal

Page 43: 2004-09-21 Natural Aerosol Event Detection and Characterization

Fine Dust Concentration Pattern

Page 44: 2004-09-21 Natural Aerosol Event Detection and Characterization

Annual Average Fine Dust Pattern(Derived from VIEWS 1992-2002)

Page 45: 2004-09-21 Natural Aerosol Event Detection and Characterization

Seasonal Average Fine Soil (VIEWS database, 1992-2002)

• Fine soil concentration is highest in the summer over Mississippi Valley, lowest in the winter• In the spring, high concentrations also exists in the arid Southwest (Arizona and Texas)

• Evidently, the summer Mississippi Valley peak is Sahara dust while the Spring peak is from local sources

Page 46: 2004-09-21 Natural Aerosol Event Detection and Characterization

Annual Average Fine Dust Concentration (VIEWS database, 1992-2002)

• The highest annual fine dust concentration is in southern Arizona and Texas

• Elevated dust is also evident in the Mississippi Valley

Page 47: 2004-09-21 Natural Aerosol Event Detection and Characterization

TOMS and VIEWS, July

• TOMS – Dust plume from Sahara • VIEWS SOILf in July – Sahara dust plume penetrating the continent

Page 48: 2004-09-21 Natural Aerosol Event Detection and Characterization

Local Dust

• VIEWS SOILf, Spring - Local dust • TOMS local dust

Page 49: 2004-09-21 Natural Aerosol Event Detection and Characterization

Local Dust

• Dust Storm Damage, 19030-1940 Dust Bowl States (brown), most dust storm damage (red), less damage (yellow).

• Dust frequency based on visibility obs. – Sehmel (1975?)

Page 50: 2004-09-21 Natural Aerosol Event Detection and Characterization

FAST-CATT: EUS Dust Transport Events

• Sahara Dust Events over the EUS

Page 51: 2004-09-21 Natural Aerosol Event Detection and Characterization

Example high fine dust days (See console for complete list)

Asian DustApril 16, 2001

Sahara DustJuly 5, 2001

Southwestern Dust

Oct. 16, 2001

Page 52: 2004-09-21 Natural Aerosol Event Detection and Characterization
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AIRNOW PM25 Northeast, Southeast

Northeast

Southeast

2004

2004

2003

2003

Page 54: 2004-09-21 Natural Aerosol Event Detection and Characterization

AIRNOW PM25 Great Lakes, Great Plaines

Great Lakes

Great Plaines 2004

20042003

2003

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AIRNOW PM25 Northwest, Southwest

Northwest

Southwest 2004

20042003

2003

Page 56: 2004-09-21 Natural Aerosol Event Detection and Characterization

AIRNOW PM25 Northeast, Southeast

Northeast

Southeast

2004

2004

Page 57: 2004-09-21 Natural Aerosol Event Detection and Characterization

AIRNOW PM25 Great Lakes, Great Plaines

Great Lakes

Great Plaines 2004

2004

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AIRNOW PM25 Northwest, Southwest

Northwest

Southwest

2004

2004

Page 59: 2004-09-21 Natural Aerosol Event Detection and Characterization