The Great Midwestern PM2.5 Episode of February 2005

1
The Great Midwestern PM2.5 Episode of February
2005

• A compendium of data from the LADCO ftp site
• Compiled by Donna Kenski
• from data contributed by
• Rudy Husar, Wash. Univ Matthew Harrell, Ill
  EPA Neal Conatser, Mich. DEQ Bob Swinford, Ill.
  EPA and Jay Turner, Wash. Univ.

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Combined Aerosol Trajectory Tool CATT

• Indicates the origin of air masses for specific
  aerosol condition
• MANE-VU MRPO

Fast Aerosol Sensing Tools for Natural Event
Tracking FASTNET
Demonstration of tools and procedures for natural
event characterization NESCAUM
Tools in support of Inter-RPO Data Analysis
Workgroup
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Combined Aerosol Trajectory Tool (CATT)

• Example Airmass origin for high (2.5average)
  nitrate

Boundary Waters
Doly Sods
Lye Brook
Smoky Mtn.
Triangulation indicates nitrate source in the
corn belt
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FASTNETInter-RPO pilot project, through
NESCAUM, 2004Web-based data, tools for
community useBuilt on DataFed infra-structure,
NSF, NASAProject fate depends on sponsor, user
evaluation
5
Datasets Used in FASTNET
Near Real Time Data Integration Delayed Data
Integration Surface Air Quality AIRNOW O3,
PM25 ASOS_STI Visibility, 300
sites METAR Visibility, 1200 sites VIEWS_OL 40
Aerosol Parameters Satellite MODIS_AOT AOT, Idea
Project GASP Reflectance, AOT TOMS Absorption
Indx, Refl. SEAW_US Reflectance, AOT Model
Output NAAPS Dust, Smoke, Sulfate,
AOT WRF Sulfate Fire Data HMS_Fire Fire
Pixels MODIS_Fire Fire Pixels Surface
Meteorology RADAR NEXTRAD SURF_MET Temp, Dewp,
Humidity SURF_WIND Wind vectors ATAD Trajector
y, VIEWS locs.

• Data are accessed from autonomous, distributed
  providers
• DataFed wrappers provide uniform geo-time
  referencing
• Tools allow space/time overlay, comparisons and
  fusion

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Some of the Tools Used in FASTNET
Consoles Data from diverse sources are displayed
to create a rich context for exploration and
analysis
Viewer General purpose spatio-temporal data
browser and view editor applicable for all
DataFed datasets
CATT Combined Aerosol Trajectory Tool for the
browsing backtrajectories for specified chemical
conditions

• Data Catalog
• Data Browser
• PlumeSim, Animator
• Combined Aerosol Trajectory Tool (CATT)

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Midwest HazeCam Image ConsoleImage Archive and
Browser
Other FASTNET Consoles
Select date and time
Set image size and time
MW HazeCam Console
Midwest HazeCam Image Browser

• Hourly Midwest HazeCam Images are archived by
  DataFed data access system
• Archived images for all cameras can be browsed
  through this console
• HazeCam URL for a day http//www.datafed.net/cons
  oles/MWH_WebCams.asp?image_width400image_height
  300datetime2005-01-31T130000
• URL for a site and day http//webapps.datafed.net
  /datasets/webcam/cincinnati/20050131-13mwhcincinna
  ti.jpg
• URLs can be embedded as links into emails,
  bookmarks, web pages, PPT and PDF files.

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Midwest HazeCam ImagesJan 27-Feb 3, 2005

• The images were part of the Midwest HazeCam
  Console of FASTNET project.

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PM25, RHBext, Temperature Pattern
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AIRNOW
From Rudy Husar
Jan.24, 2005
Jan.25, 2005
Jan.26, 2005
Jan.27, 2005
Jan.28, 2005
Jan.29, 2005
Jan.30, 2005
Jan.31, 2005
Feb. 1, 2005
Feb. 2, 2005
Feb. 3, 2005
Feb. 4, 2005
Feb. 5, 2005
Feb. 6, 2005
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Regional Average PM25 Concentration
PatternBased on AIRNOW
0502 PM Event
Midwest Region

• Compared to past PM25 events, since 2003 the 0502
  event was
• Lower peak concentration (40 ug/m3 avg) than the
  yearly July 4 spikes (gt55 ug/m3 avg)
• Much longer (10 days) than the July 4 spikes (2-3
  hours)
• The event time integral was 2x higher than the
  largest summer events

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Regional Average PM25 Concentration
PatternBased on AIRNOW
0502 PM Event

• Time pattern of the 0502 Event
• The overall event lasted about 10 days, Jan
  28-February 7
• The Upper Midwest peaked first (Jan 31-Feb 2)
  Industrial MW later (Feb 3 6)
• The Industrial MW region show more diurnal
  variation (lowest in the mid-afternoon)

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NOAA GASP GOES Satellite Aerosol Optical
Thickness
Feb 04 2005
Feb 05 2005
Feb 03 2005

Feb 07 2005
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MODIS Satellite AOD IDEA ProjectJan 28-Feb 9
15
WRF PM25 Model
050201
050203
050202
050204
050209
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NRL NAAPS Aerosol Forecast Model
Nitrate?
NAAPS SO4 Model
Aerosol Bext Data

• NRL model
• Surface Bext
• Overlay
• Problem humidity correction

17
NAPS SO4 Model, AIRNOW PM25, ASOS RHBext
Feb 2, 2005
Jan 30, 2005
Jan 31, 2005
Feb 1, 2005
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Over the Upper Midwest, between Feb. 15-19, the
dew point temperature increased from 20 to 30
F Similarly, the temperature rose from 10 to
40 F. the over four days, causing a rapid taw
through out the region
Interestingly, the rise in aerosol Bext during
Feb 16-19 coincided with the rising temperatures
and humidity. Is there a causality?? Possible
nitrate release?
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Real-time Surface Meteorology provided a rich met
context.Link to the Animation of the period Feb
19-21
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Monthly Nitrate, VIEWS 2000-2003
FEB
MAR
APR
JUN
JUL
MAY
AUG
DEC
OCT
NOV
SEP
22
FASTNET Report 0409FebMystHaze
Mystery Winter Haze Natural? Nitrate/Sulfate?
Stagnation?
AIRNOW PM25 - February
Contributed by the FASNET Community, Sep.
2004 Correspondence to R Husar , R Poirot
Coordination Support by Inter-RPO WG Fast
Aerosol Sensing Tools for Natural Event Tracking,
FASTNET NSF Collaboration Support for Aerosol
Event Analysis NASA REASON Coop EPA -OAQPS
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Secondary MP25 Peak in February-March
Sulfate-driven Jul-Aug peak
Feb-Mar peak, of unknown origin

• The AIRNOW PM25 data are available real-time for
  300 stations since July 2002.
• The 30-day smoothing of the average hourly data
  shows the Eastern US PM25 seasonality
• The seasonal pattern shows the summertime sulfate
  peak and a second Feb/Mar peak
• The the existence, characteristics and origin of
  this regional peak is not known
• The objective of effort is to characterize this
  mysterious phenomenon over the EUS
• The approach is to seek out the community as a
  resource for collaborative analysis

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Seasonal PM25 by Region

• The 30-day smoothing average shows the
  seasonality by region
• The Feb/Mar PM25 peak is evident for the
  Northeast, Great Lakes and Great Plains
• This secondary peak is absent in the South and
  West

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FRM PM25 Monthly Concentration
EPA AIRS 1999-2002
MAR
APR
JAN
FEB
MAY
JUN
JUL
AUG
SEP
OCT
NOV
DEC

• Monthly average FRM PM25 are shown as circle and
  contour (Blue 0 Red 25 mg/m3)
• The Feb/Mar peak is clearly evident in the
  Midwest region also in January
• Hence, there is some deviation in peak location
  and time among the networks

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Satellite Data POLDER Aerosol Polarization Index
Dauze et. al, 2001

• The (short-lived, Nov 96-Jun97) POLDER satellite
  sensor measured the of aerosol polarization,
  which is sensitive to fine particles, lt 1 mm
• For Jan-Mar the data show a strong aerosol signal
  over the Upper Midwest and adjacent Canada
• Skeptics have attributed the anomalous aerosol
  zone to interferences such as snowy ground
  reflectance
• In light of the recent ground-based PM25
  monitoring data, the early (1997) POLDER results
  deserve full attention

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(No Transcript)
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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

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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

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TOMS and VIEWS, July

• TOMS Dust plume from Sahara

• VIEWS SOILf in July Sahara dust plume
  penetrating the continent

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Origin of Fine Dust Events over the US
Gobi dust in spring Sahara in summer
Fine Dust Events, 1992-2003
ug/m3
Fine dust events over the US are mainly from
intercontinental transport
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PM Event Detection from Time Series
Event Deviation gt xpercentile

• Contributed by the FASNET Community, Sep. 2004
• Correspondence to R Husar , R Poirot
• Coordination Support by
• Inter-RPO WG Fast Aerosol Sensing Tools for
  Natural Event Tracking, FASTNET
• NSF Collaboration Support for Aerosol Event
  Analysis
• NASA REASON Coop
• EPA -OAQPS

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Temporal Analysis

• The time series for typical monitoring data are
  messy the signal variation occurs at various
  scales and the time pattern at each scale is
  different
• Inherently, aerosol events are spikes in the time
  series of monitoring data but extracting the
  spikes from the noisy data is a challenging
  endeavor

Typical time series of daily AIRNOW PM25 over the
Northeastern US

• The temporal signal can be meaningfully
  decomposed into a
• Seasonal component with stable periodic pattern
• Random variation with white noise pattern
• Spikes or events that are more random in
  frequency and magnitude
• Each signal component is caused by different
  combination of the key processes emission,
  transport, transformations and removal

35
Temporal Signal Decomposition and Event Detection
EUS Daily Average
50-ile, 30 day 50-ile smoothing

• First, the median and average is obtained over a
  region for each hour/day (thin blue line)
• Next, the data are temporally smoothed by a 30
  day moving window (spatial median - red line
  spatial mean heavy blue line). These determine
  the seasonal pattern.

Event Deviation gt xpercentile
Deviation from -ile
Average

• Finally, the hourly/daily deviation from the the
  smooth median is used to determine the noise
  (blue) and event (red) components

Mean Seasonal Conc.
Median
Median Seasonal Conc.
36
Causes of Temporal Variation by Region

• The temporal signal variation is decomposable
  into seasonal, meteorological noise and events
• Assuming statistical independence, the three
  components are additive
• V2Total V2Season V2MetNoise V2Event
• The signal components have been determined for
  each region to assess the differences

Northeast exhibits the largest coeff. variation
(56) seasonal, noise and events each at
30 Southeast is the least variable region (35),
with virtually no contribution from
events Southwest, Northwest, S. Cal. and Great
Lakes/Plains show 40-50 coeff. variation mostly,
due to seasonal and meteorological
noise. Interestingly, the noise is about 30 in
all regions, while the events vary much more,
5-30
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Composition of Eastern US Events

• The bar-graph shows the various combinations of
  species-events that produce Reconstructed Fine
  Mass (RCFM) events
• Composition is defined in terms of
  co-occurrence of multi-species events (not by
  average mass composition)
• The largest EUS RCFM events are simultaneously
  events (spikes) in sulfate, organics and soil!
• Some EUS RCFM events are events in single
  species, e.g. 7-Jul-97 (OC), 21-Jun-97 (Soil)

Based on VIEWS data
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Application of Automatic Event DetectionA
Trigger and Screening Tool

• The algorithmic aerosol detection and
  characterization provides only limited
  information about events
• However, it can be used to trigger further action
  during real-time monitoring of events
• Also, automatic event quantification can be used
  as a screening tool for the further analysis of
  qualified events, e.g. the selection of natural
  events from the total event pool

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Analysts Consoles for Event Characterization

• Analysts consoles deliver the state of the
  aerosol, meteorology etc., automatically from
  real-time monitoring data
• Dozens of maps depict the spatial pattern using
  dozens of surface and satellite-detected
  parameters
• The temporal pattern are presented on time series
  for the regional average and for individual
  stations
• The following pages illustrate the 2004 EUS
  events, through a subset of the monitored
  parameters.
• The event-presentation includes limited
  interpretative comments the full interpretation
  of this rich context is left to subsequent
  communal analysis

Spatial Console
Temporal Console
40
Feb 19 2004

• Isolated high PM25 occurs over the Midwest,
  Northeast and Texas
• The aerosol patches are evident in AIRNOWPM25,
  ASOS and Fbext maps
• The absence of TOMS signal indicates the lack of
  smoke or dust at high elevation
• The high surface wind speed over Texas, hints on
  possible dust storm activity

• The NAAPS model shows high sulfate over the
  Great Lakes, but no biomass smoke
• Possible event causes nitrate in the Upper
  Midwest and Northeast, sulfate around the Great
  Lakes and dust over Texas

41
Mar 25

• Broad, contiguous AIRNOW PM25 belt covers the
  upper Midwest and the Northeast
• The ASOS is moderate throughout, while the
  surface FBExt is high over the U. Midwest
• The absence of TOMS signal indicates the lack of
  smoke or dust at high elevation
• The surface winds indicates war air transport
  from the Gulf to the U Midwest

• NAAPS shows high sulfate over the Great Lakes,
  but no biomass smoke or dust
• Possible causes nitrate in the Upper Midwest
  and sulfate around the Great Lakes

42
Apr 18

• This modest episode stretches from Wisconsin over
  Pennsylvania to the Mid-Atlantic States
• The ASOS is high over the Great Lakes and the
  surface FBExt is high over the U. Midwest
• TOMS shows smoke(?) over Mexico MODIS AOT is
  moderate over the Mid-Atlantic
• The surface winds indicate air transport from the
  Gulf to the Upper Midwest

• NAAPS model indicates high sulfate over
  Pennsylvania and smoke over the Midwest
• Possible causes nitrate and smoke over the
  Midwest, in the and sulfate around the Great Lakes

43
Jun 6-8

• This intensive 3-day episode covers much of the
  Eastern US
• The AIRNOW, ASOS and Visibility FBext are all
  elevated
• TOMS shows smoke(?) over the Gulf and Mexico
  MODIS AOT over the Northeast
• The surface winds indicate stagnation over the EUS

• NAAPS model shows intense sulfate accumulation
  over the industrial Illinois-New York .
• Possible causes sulfate episode

44
Jul 21-23

• This intensive 3-day episode covers much of the
  Eastern US
• The AIRNOW, ASOS and Visibility FBext are all
  elevated
• Extremely high MODIS AOT and GASP AOT values
  cover the East Coast and Gulf Coast
• The surface winds indicate stagnation over much
  of the East Coast

• NAAPS model predicts elevated sulfate throughout
  the Eastern US.
• Possible causes sulfate episode

45
Aug 18

• This episode has an intensive region in the
  Northeast and another in the Southeastern US
• The AIRNOW, ASOS and Visibility all show similar
  location of elevated aerosol
• Highest MODIS AOT and GASP AOT values occur over
  the Northeast
• The surface winds indicate stagnation over the
  southeastern EUS

• NAAPS model predicts high sulfate in the
  Northeast and biomass smoke over the Southeast
• Possible causes sulfate episode in the
  Northeast, smoke and sulfate in the Southeast(?)

46
Sep 4

• A single strong aerosol blob cover the Midwest
• The AIRNOW PM25, ASOS and Fbext maps all show a
  consistent spatial pattern
• The MODIS AOT confirms the Midwestern haze the
  GASP AOT peaks further south
• The surface winds are low over much of the EUS

• NAAPS model also predicts a sulfate blob over
  the Midwest without significant smoke or dust
• Possible causes sulfate episode from stagnation
  over the source region

47
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.

48
CATT Software Components and Data Flow

• The CATT software consists of two rather
  independent components
• Chemical filter component. This component is
  accomplished through queries to chemical data
  sets. The output of this step is a list of
  qualified dates for a specific receptor
  location.
• Trajectory aggregator component. This
  component receives the list of dates for a
  specific location and performs the trajectory
  aggregation, residence time calculation and other
  spatial operations to yield a transport pattern
  for specific receptor location and chemical
  conditions.

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Average Concentration of Different Species
-DKenski Metricyou guess the species ?
50
OCf Concentration Field (DKenski Metric)
Avg. 98 Percentile
Avg. 95 Percentile
Avg. 90 Percentile
Avg. 80 Percentile
Average, All Data
51
Sulfate Transport Pattern on 2004-07-20
All Data
SO4 gt 15
SO4 gt 5
52
Sulfate Transport to BIBE, GRSM and LYBR
All Data
80-100 Percentile
0-20 Percentile
Big Bend, TX
Great Smoky, TN
Lynbrook, VT
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Incremental Transport Probability
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Seasonal Incremental Probability
Year
MAM
DJF
SON
JJA
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Secular Changes 1988-94 1995-2000
1988-2000
1994-2000
1988-1994