Transcript The Great Midwestern PM2.5 Episode of February 2005 Compiled by Donna Kenski

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.
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
Combined Aerosol Trajectory Tool
(CATT)
Example: Airmass origin for high (2.5*average) nitrate
Boundary Waters
Doly Sods
Lye Brook
Smoky Mtn.
Triangulation indicates nitrate source in the corn belt
FASTNET:
Inter-RPO pilot project,
through NESCAUM, 2004
Web-based data, tools for
community use
Built on DataFed infrastructure, NSF, NASA
Project fate depends on
sponsor, user evaluation
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
GASP
TOMS
SEAW_US
AOT, Idea Project
Reflectance, AOT
Absorption Indx, Refl.
Reflectance, AOT
Model Output
NAAPS Dust, Smoke, Sulfate, AOT
WRF
Sulfate
Fire Data
HMS_Fire
MODIS_Fire
Fire Pixels
Fire Pixels
Surface Meteorology
RADAR NEXTRAD
SURF_MET
SURF_WIND
ATAD
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Data are accessed from autonomous, distributed providers
DataFed ‘wrappers’ provide uniform geo-time referencing
Tools allow space/time overlay, comparisons and fusion
Temp, Dewp, Humidity…
Wind vectors
Trajectory, VIEWS locs.
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
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Data Catalog
Data Browser
PlumeSim, Animator
Combined Aerosol Trajectory Tool (CATT)
CATT: Combined Aerosol Trajectory
Tool for the browsing backtrajectories
for specified chemical conditions
Midwest HazeCam Image Console
Image Archive and Browser
Select date and time
Set image size and time
Other FASTNET
Consoles
MW HazeCam Console
Midwest HazeCam Image Browser
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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/consoles/MWH_WebCams.asp?image_width=400&image_height=300&datetime=2005-01-31T13:00:00
URL for a site and day: http://webapps.datafed.net/datasets/webcam/cincinnati/20050131-13mwhcincinnati.jpg
URLs can be embedded as links into emails, bookmarks, web pages, PPT and PDF files.
Midwest HazeCam Images
Jan 27-Feb 3, 2005
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The images were part of the Midwest HazeCam Console of FASTNET project.
PM25, RHBext, Temperature Pattern
From Rudy Husar
Jan.24, 2005
Jan.25, 2005
Jan.28, 2005
Feb. 1, 2005
Feb. 5, 2005
AIRNOW
Jan.26, 2005
Jan.27, 2005
Jan.29, 2005
Jan.30, 2005
Jan.31, 2005
Feb. 2, 2005
Feb. 3, 2005
Feb. 4, 2005
Feb. 6, 2005
Regional Average PM25 Concentration Pattern
0502 PM Event
Based on AIRNOW
PM Event
Midwest Region
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Compared to past PM25 events, since 2003 the 0502 event was
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Lower peak concentration (40 ug/m3 avg) than the yearly July 4 spikes (>55 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
Regional Average PM25 Concentration Pattern
Based on AIRNOW
0502 PM Event
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Time pattern of the 0502 Event
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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)
NOAA GASP
GOES Satellite Aerosol Optical Thickness
Feb 03 2005
Feb 04 2005
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Feb 07 2005
Feb 05 2005
MODIS Satellite AOD – IDEA Project
Jan 28-Feb 9
WRF PM25 Model
050201
050202
050203
050204
050209
NRL NAAPS Aerosol Forecast Model
Nitrate?
Aerosol Bext Data
NRL model
Surface Bext
Overlay
Problem: humidity correction
NAAPS SO4 Model
NAPS SO4 Model, AIRNOW PM25, ASOS RHBext
Jan 30, 2005
Jan 31, 2005
Feb 1, 2005
Feb 2, 2005
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?
Real-time Surface Meteorology provided a rich met context.
Link to the Animation of the period Feb 19-21
Monthly Nitrate, VIEWS 2000-2003
JAN
MAY
SEP
FEB
JUN
OCT
MAR
JUL
NOV
APR
AUG
DEC
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
Secondary MP25 Peak in February-March
Feb-Mar peak,
of unknown
origin
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Sulfate-driven
Jul-Aug peak
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
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
FRM PM25 Monthly Concentration
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EPA AIRS 1999-2002
JAN
FEB
MAR
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
APR
Satellite Data: POLDER Aerosol Polarization
Index
Dauze et. al, 2001
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The (short-lived, Nov 96-Jun97) POLDER
satellite sensor measured the of aerosol
polarization, which is sensitive to fine particles, <
1 mm
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For Jan-Mar the data show a strong aerosol
signal over the Upper Midwest and adjacent
Canada
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Skeptics have attributed the ‘anomalous’ aerosol
zone to interferences such as snowy ground
reflectance
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In light of the recent ground-based PM25
monitoring data, the early (1997) POLDER
results deserve full attention
Seasonal Pattern of Dust Baseline and Events
1.6
Events
Baseline
Total
1.4
1.2
1
0.8
0.6
0.4
0.2
0
01/01/92
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02/20/92
04/10/92
05/30/92
07/19/92
09/07/92
10/27/92
12/16/92
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
Seasonal Average Fine Soil
(VIEWS database, 1992-2002)
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Fine soil concentration is highest in the summer over Mississippi Valley, lowest in the
winter
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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
TOMS and VIEWS, July
• TOMS – Dust plume from
Sahara
• VIEWS SOILf in July – Sahara dust
plume penetrating the continent
Origin of Fine Dust Events over the US
Gobi dust in spring
Sahara in summer
ug/m3
Fine dust events over the
US are mainly from
intercontinental
transport
Fine Dust Events, 1992-2003
PM Event Detection from Time
Series
Event : Deviation > x*percentile
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
Temporal Analysis
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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
1. Seasonal component with stable periodic pattern
2. Random variation with ‘white noise’ pattern
3. 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
Temporal Signal
Decomposition and
Event Detection
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First, the median and average is
obtained over a region for each
hour/day (thin blue line)
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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.
EUS Daily Average
50%-ile, 30 day
50%-ile smoothing
Event : Deviation > x*percentile
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
MeanMedian
Seasonal
Conc.
Median Seasonal
Conc.
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
Application of Automatic Event Detection:
A 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
Analysts Consoles for
Event Characterization
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Analysts consoles deliver the state of the
aerosol, meteorology etc., automatically from
real-time monitoring data
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Dozens of maps depict the spatial pattern
using dozens of surface and satellitedetected parameters
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The temporal pattern are presented on time
series for the regional average and for
individual stations
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The following pages illustrate the 2004 EUS
events, through a subset of the monitored
parameters.
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The event-presentation includes limited
interpretative comments; the full
interpretation of this rich context is left to
subsequent communal analysis
Spatial Console
Temporal Console
Feb 19 2004:
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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
Mar 25
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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
Apr 18
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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
Jun 6-8
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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 IllinoisNew York .
• Possible causes: sulfate
episode
Jul 21-23
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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
Aug 18
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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(?)
Sep 4
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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
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.
CATT Software Components and Data Flow
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1.
2.
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.
Average Concentration of Different
Species -DKenski Metric
you guess the species 
OCf Concentration Field (DKenski Metric)
Avg. 98 Percentile
Avg. 95 Percentile
Avg. 90 Percentile
Average, All Data
Avg. 80 Percentile
Sulfate Transport Pattern on 2004-07-20
All Data
SO4 > 5
SO4 > 15
Sulfate Transport to BIBE, GRSM and LYBR
All Data
Big
Bend,
TX
Great
Smoky,
TN
Lynbrook,
VT
80-100 Percentile
0-20 Percentile
Incremental Transport Probability
Seasonal Incremental Probability
Year
DJF
MAM
JJA
SON
Secular Changes: 1988-94; 19952000
1988-2000
1994-2000
1988-1994