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Airborne Observations for
Aerosol Model Assessment
Prepared by M. Kleb and G. Chen
NASA Airborne Campaign Map
from mid 1980s to present
Summary of NASA Tropospheric Airborne
Particle Measurements
Aer o so l Measu r em en t s
Missio n s
Co m p o sit io n CN N/S Dist ist r ib u t io n Op t ical Pr o p er t ies
CITE-1C & ABLE-1 ('84)
ABLE-2A ('85)
CITE-2 ('86)
ABLE-2B ('87)
ABLE-3A ('88)
CITE-3 ('89)
ABLE-3B ('90)
PEM-West A ('91)
PEM-West B ('94)
PEM-Tr o p ics A ('96)
PEM-Tr o p ics B ('99)
TRACE-P ('01)
INTEX-NA ('04)
NAMMA ('05)
INTEX-B ('06)
TC4 ('07)
ARCTAS ('08)
Other Important Airborne Campaign
for Aerosol Observations
NSF ACE‐1, 1995
NSF ACE‐2, 1997
NSF ACE‐Asia, 2001
NOAA NEAQS‐ITCT, 2004
EU AMMA, 2006
NOAA ARCPAC, 2008
TC4 Example
20
15
Boundary Layer Comparison:
Latitude (ºN)
10 Caribbean vs. Pacific
5
Pacific
Caribbean
0 Scattering (Mm-1)
-95 -90 -85 -80 -75 -70
Longitude (ºE)
SO2 & HNO3
0 100 200 300
Number Density ( x 10 1/cm3)
HNO3 (pptv)
SO2 (pptv)
0 20 40 60 80
HCN (pptv)
C3H8 (pptv)
• Both Caribbean and Pacific observations are mostly
C2H2 (pptv) consistent with typical tropical marine boundary
layer (TMBL) conditions, except elevated SO2.
Pacific
NO2 (pptv) Caribbean
• Particle scattering and number density are also
O3 (ppbv)
consistent with typical TMBL values.
• Larger particles and heavier loading are seen in the
CO (ppbv)
Caribbean observations.
0 40 80 120
CO, O3, NO2, C2H2, C3H8 & HCN
TC4 Example (cont.)
3.5
Median Concentration (µg m )
-3
Caribbean Seasalt ~65%
3.0 Pollution ~31%
2.5
Dust ~4% • Airborne aerosol observations
can be used to assess spatial
2.0
and temporal distribution.
1.5 Pacif ic • Allow detailed and direct
1.0 comparison for aerosol
0.5
volume loading, chemical
composition, number and size
0.0
Cl NO3 SO4 Na NH4 K Mg Ca distribution, and optical
Inorganic Ions properties.
120 2 • Companion gas phase
550 nm Scattering (Mm )
-1
Slope = 0.20 ± 0.03
100 2
R = 0.49
observations can be used as
0.0 0.2 0.4 0.6
ln[Na (µg m )]
1
++ -3
tracers for airmass
-3
Ca (µg m )
80
60 0 classification and source
+
40 Caribbean WS = 9 m s-1
assessment.
-1
20 Pacific WS = 6 m s-1
0 -2
0 1 2 3 4 5 6 0 2 4 6 8 10 12
+ -3 -1
Na (µg m ) Wind Speed (m s )
• Sea salt is the largest particulate component.
• Significant pollution and dust contribution.
• Sea salt loading is likely a strong function of wind speed.
The LaRC MEaSUREs Project:
Creating a Unified Airborne Database for Assessment and
Validation of Global Models of Atmospheric Composition
• The first international Tropospheric Airborne Measurement
Evaluation Panel (TAbMEP) meeting, held in Baltimore, MD August
19‐21, 2008, was sponsored by the LaRC MEaSUREs project and
received broad endorsement and participation from NASA, NOAA,
NSF, EPA, DOE and IGAC.
• TAbMEP is a group of measurement and modeling experts
representing a broad spectrum of trace gas and particle
measurement techniques/ instruments as well as global and
regional models
• TAbMEP serves as a steering committee to guide the LaRC
MEaSUREs project in achieving its overarching goal to generate
unified data products for model assessment and validation.
MEaSUREs = Making Earth System data records for Use in Research
Environments.
First TAbMEP Meeting Goals
• To objectively assess measurement uncertainties for ICARTT
airborne data.
• To objectively evaluate measurement consistency between
techniques, instruments, and platforms.
• To assess the suitability of measurements for model
assessment and validation and to identify problematic
measurements.
• To establish community‐accepted approaches for combining
data sets and creating a unified airborne database from
multiple instruments and aircraft platforms.
Particulate Phase measurements of interest for 1st TAbMEP Meeting: total
number density, submicron and total volume densities, sulfate, ammonium, nitrate
mass concentration, scattering coefficients, and absorption coefficients
TAbMEP Members
Attendees Contributions Affiliation Attendees Contributions Affiliation
Bruce Anderson Aerosol Measurements NASA LaRC Jose Jimenez Aerosol Measurements Univ. of CO
HTAP & EPA
Eric Apel Trace Gas Measurements NCAR Terry Keating EPA
Representative
Melody Avery Trace Gas Measurements NASA LaRC Mary Kleb Organizer, data analysis NASA LaRC
Global & Reg. Model: Trace Univ. of
Steve Arnold Qing Liang Global Model: Trace Gas NASA GSFC
Gas Leeds
Univ. of CA,
Don Blake Trace Gas Measurements David McCabe EPA Representative AAAS/EPA
Irvine
Chuck Brock Aerosol Measurements NOAA/ESRL Pete Parker Statistician NASA LaRC
Reg. Model: Trace Gas & Trace Gas
Greg Carmichael Univ. of IA David Parrish NOAA/ESRL
Aerosol Measurements
Margaret
Gao Chen Organizer, data analysis NASA LaRC Organizer, data analysis NASA LaRC
Pippin
Trace Gas
Mian Chin Global Model: Aerosols NASA GSFC Tom Ryerson NOAA/ESRL
Measurements
Trace Gas & Aerosol
Jack Dibb Univ. of NH Jian Wang Aerosol Measurements DOE/BNL
Measurements
Glenn Diskin Trace Gas Measurements NASA LaRC
Absent Panel
Louisa Emmons Global Model: Trace Gas NCAR
Members
Global & Reg. Model: Trace Univ. of Trace Gas
Mat Evans Greg Huey GA Tech
Gas Leeds Measurements
Arlene Fiore Global Model: Trace Gas NOAA/GFDL Trish Quinn Aerosol Measurements NOAA/PMEL
Frank Flocke Trace Gas Measurements NCAR Michael Schulz Global Model: Aerosols LSCE
Key TAbMEP Recommendations
• TAbMEP Assessment Report: Summary of TAbMEP meeting discussions and
results of the follow‐up analysis, publically available tentatively by June 2009.
• Significant and irreconcilable differences between measurements:
– Panel often recommended more than one measurement as suitable for model assessment .
– Measurements unified by increasing systematic uncertainties to encompass all measurements
within 2‐σ total uncertainty limits.
– Individual data sets will not adjusted ‐ average is unlikely to be closer to the actual ambient value.
• Internal estimate of instrument precision (IEIP):
– Panel established as useful data‐driven independent check on the PI reported uncertainties.
– IEIP analysis will be performed on all applicable data (i.e., high time resolution and continuous).
• Measurement consistency analysis for the intercomparison data: Reports
absolute or relative difference between coincident points in addition to the
orthogonal distance regression (ODR) slopes and intercepts.
The scope of the TAbMEP meeting is to evaluate the implementation of techniques,
but not to critique the techniques themselves.
Unified Airborne Database
Assessment of Integrated Volume Density and
Size Distribution Measurements
Volume Density Measurement Precision Assessment
DC-8:V(< 1 µm)* WP-3D:V(< 1 µm) WP-3D: VTotal • WP‐3D data appears to be
Date
(μm3cm-3) (μm3cm-3) (μm3cm-3) more precise, however, the
07/22/2004 4% 7% panel believes that the
07/31/2004 35% 5% 15% overall uncertainty should
08/07/2004 28% 4% 25%
quite similar for both
*Derived from OPC data only, i.e., 150 – 1000 nm
measurements at ~ 50%.
• Data collected from
• The total volume
NASA DC‐8 and NOAA measurement is less precise
WP‐3D. than that of the PM1. This
• WP‐3D data: 1 sec, reflects low coarse particle
nearly continuous number density.
data .
• The agreement between the
• DC‐8 data: slower
time resolution with integrated quantities is
gaps. significantly better than the
• WP‐3D PI reported size distributions, see next
uncertainty: ~50%. slide.
• DC‐8 total uncertainty
not specified.
Size distribution comparison
15:22:39 – 15:24:39
DC-8 3
5 6x10 DC-8 N 50
Vol(0.15 - 0.91 µm) (µm /cm )
WP-3D
3
10 Case B DC8 V
WP-3D N
5 WP-3D V 40
dV/dlogD (µm /cm )
3
4
dN/dlogD (1/cm )
3
Altitude (km)
Begin End 4
1 14:45:50 15:32:14 30
3
3
20
2
3
2
0.1
3
10
1 1
0 0
0.01 0 2 3 4 5 6 7 8 9
0.1 1
14:50 15:00 15:10 15:20 15:30 Optical Effective Diameter (µm)
Time, GMT
3
10 5
23:17:51 – 23:22:21 Begin DC-8 End
3 6 22:52:50 WP-3D
2.0x10 8 23:32:10
N(0.15 - 0.91 µm) (1/cm )
5
3
Case B 4
4
DC-8 N
DC8 V 3
Altitude (km)
dV/dlogD (µm /cm )
WP-3D N
dN/dlogD (1/cm )
1.5 6
3
WP-3D V 2 3
2
1.0 4 10 2
6
3
5
0.5 2 4 1
3
3
0.0 0
2 0
2 3 4 5 6 7 8 9
0.1 1 22:50 23:00 23:10 23:20 23:30
Optical Effective Diameter (µm) Time, GMT
Scattering and Absorption
• Panel did not have a full discussion on scattering and
absorption measurements (made only onboard NASA DC‐
8).
• Results from intercomparison analysis of INTEX‐B and
ARCTAS analysis suggests nephelometer scattering
measurement is typically more precise and highly
consistent between instruments and platforms. The
ARCTAS and INTEX‐B data will be discussed at future
TAbMEP meetings.
• Absorption measurement precision is estimated about 35%
or 0.1 Mm‐1. Typically, scattering precision is estimated
from 5‐20%. The intercomparison results are less
conclusive due to limited range reflecting weak absorption
environment.
Particulate Nitrate (07/31/04)
1.2 DC-8 PILs (< 1 µm) DC8 Filter (< 8 µm) 5
WP-3D PILs (< 1 µm) WP-3D AMS (< 1 µm?)
1.0 Begin
22:52:50 4 Aerosol Nitrate
Measurement Assessment
Nitrate (µg/m )
3
Altitude (km)
0.8
3
End
0.6 23:32:10
0.4 Nitrate (07/28/04) 8
2 DC-8 PILs (< 1 µm)
0.4 DC8 filter (< 8 µm) End 7
LOD 0.3 Begin BAE 146 17:01:20
15:49:30 BAE 146 Uncertainty
1 6
0.2
Nitrate (µg/m )
3
Altitude (km)
0.2
PILs LOD
5
0.0 0
0.1 4
22:50 23:00 23:10 23:20 23:30
Time, GMT 3
0.0
2
-0.1
Filter LOD 1
Particulate Nitrate (08/07/04)
0.4 DC-8 PILs (< 1 µm) DC8 Filter (< 8 µm) 5 -0.2 0
WP-3D PILs (< 1 µm) WP-3D AMS (< 1 µm?) 15:45 16:00 16:15 16:30 16:45 17:00
4 Time, GMT
0.3 End
The nitrate comparison is not conclusive
Nitrate (µg/m )
22:19:10
3
Altitude (km)
Begin
21:35:10 3 since most of the submicron data are near
0.2 Filter LOD
or under limit of detections.
PILs LOD 2
0.1
The internal estimate of instrument
AMS LOD 1
precision procedures can not be applied
because of long integration time and/or
0.0 0
21:30 21:40 21:50 22:00 22:10 22:20 gaps between data points.
Time, GMT
1.2 Particulate Ammonium (07/31/04) 5
DC-8 PILs (< 1 µm) DC8 Filter (< 8 µm)
WP-3D PILs (< 1 µm) WP-3D AMS (< 1 µm?)
1.0 Begin 4
Ammonium (µg/m )
End
3
22:52:50
23:32:10
Altitude (km)
0.8
3 Aerosol Ammonium
AMS LOD
0.6 Measurement Assessment
2
0.4
1
0.2
PILs LOD
0.0 0
22:50 23:00 23:10 23:20 23:30
Time, GMT
The intercomparison between 0.8 Particulate Ammonium (08/07/04)
DC-8 PILs (< 1 µm) DC8 Filter (< 8 µm)
5
DC‐8 and WP‐3D is inconclusive WP-3D PILs (< 1 µm) WP-3D AMS (< 1 µm?)
End
22:19:10
4
due to low nitrate values,
Ammonium (µg/m )
3
0.6
Altitude (km)
AMS LOD
while DC‐8 PILS appears to be Begin
21:35:10 3
systematically high. 0.4
2
The panel recommended
0.2
further comparison analysis 1
PILs LOD
between DC‐8 PILs and filter
0.0 0
measurements. 21:30 21:40 21:50 22:00 22:10 22:20
Time, GMT
Particulate Sulfate (07/31/04)
DC-8 PILs (< 1 µm) DC8 Mist Chamber (< 2.5 µm)
DC8 Filter (< 8 µm) WP-3D PILs (< 1 µm) WP-3D AMS (< 1 µm?)
6 5 Aerosol Sulfate
Begin
5 22:52:50
End
23:32:10
4
Measurement Assessment
Sulfate (µg/m )
3
Altitude (km)
4
3 4
3 PILs Sulfate Correlation
ODR fit: y = a + bx 1:1
2
a = -0.05 ± 0.07
2
DC-8 PILs (µg m )
3 b = 0.66 ± 0.05
-3
2
1 R = 0.92
1
0 0 2
22:50 23:00 23:10 23:20 23:30
Time, GMT
Particulate Sulfate (08/07/04) 1
DC-8 PILs (< 1 µm) DC8 Mist Chamber (< 2.5 µm) DC8 Filter (< 8 µm)
WP-3D PILs (< 1 µm) WP-3D (< 1 µm?)
5
1.4 Begin
21:35:10 0
1.2 4 0 1 2 3 4
-3
Sulfate (µg/m )
WP-3D PILs (µg m )
3
Altitude (km)
1.0
3
0.8
The panel believes that the
0.6 2
agreement between the
0.4
End
1 instruments and platforms is
0.2 22:19:10 about as good as one can expect.
0.0 0
21:30 21:40 21:50 22:00 22:10 22:20
Time, GMT
WP-3D Ammonium Comparison
all available data WP‐3D Comparison:
8 y = a + bx
a = 0.26 ± 0.04
b = 1.51 ± 0.04
AMS vs. PILs
2
R = 0.72
6
PILs (µg m )
WP-3D Sulfate Comparison
-3
30 all available data 1:1
y = a + bx
4 a = 0.15 ± 0.12
25 b = 0.91 ± 0.02
2
R = 0.82
PILs (µg m )
2
-3
20
0 15
0 1 2 3 4 5
-3
2.5 AMS (µg m )
10
1:1
2.0
5
PILs (µg m )
-3
1.5
0
0 5 10 15 20 25 30
-3
1.0 AMS (µg m )
WP-3D Nitrate Comparison
0.5 AMS reported 10 min. averages which is not
typical for other field campaigns. Some
0.0
panel member noted that the AMS suffered
0.0 0.5 1.0 1.5
-3
2.0 2.5 some instrument problems during this study
AMS (µg m )
