black carbon & other light- absorbing particles in snow in ......snow cover in 2013 was not...
TRANSCRIPT
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ashington A USA
A USA
Black carbon & other light-absorbing particles in snow in
Central North America
Sarah Doherty JISAO, Univ. of W
Seattle, W
Stephen Warren, Dean Hegg & Cheng Dang Dept. of Atmos. Science, Univ. of Washington, Seattle, W
Rudong Zhang, Xin Wang & Jianping Huang Lanzhou University, Lanzhou, CHINA
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Goals � Constrain amount and sources of BC & other light-absorbing
particles in snow: focus on N. American Great Plains
� Comparison of light-absorbing particles in snow in N. American & N. China Great Plains
� Study relative roles of deposition and in-snow processes in surface snow light-absorbing particle mixing ratios / types
� Methods comparison for measuring BC in snow
� Use 2013 N American survey and earlier Canadian Arctic surveys to assess north-south gradients (for indication of N American contributions to Arctic)
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Bond et al., 2013 Figure 7.3
Climate forcing
by BC in snow
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Bond et al., 2013 Figure 7.3
Climate forcing
by BC in snow
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Bond et al., 2013 Figure 7.3
Climate forcing
by BC in snow
(mostly) strong
positive feedbacks to initial positive forcing
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Fig. 5
Arctic)
Motivation Flanner et al., 2007
• Focus has mostly been on BC in snow in the Arctic, BUT: • The highest concentrations of BC in snow are at lower latitudes
• The open plains regions of the northern mid-latitudes are where the snowpack is not masked by vegetation
• Warming due to BC in snow at lower latitudes may contribute significantly to Arctic warming (increased heat advection into
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Motivation Qian et al., 2009
Regional model study of Western U.S. (Qian et al., 2009):
• decreases in snow accumulation rate
• increased runoff in February; decreased runoff March onward
• affects on mountain snowpack & snowpack in agricultural regions
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Fig. 5
., China
Motivation Flanner et al., 2007
• Large-area surveys of three regions: • Arctic (mostly 2007-2010) previous work under NSF • N. China Great Plains (2010 & 2012) with Lanzhou Univ
• N. America Great Plains (2013 & 2014)
� All using the same sampling & analysis technique
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Arctic Survey (mostly 2007-2010)
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orea
orea
ussia
N. China survey 2010 : 46 sites {Lanzhou Univ. & Univ. of Washington collaboration}
Mongolia
China
Beijing N K
S K
R
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N. American survey 2013 : 67 sites + 3 process study sites in 2014
2013 sites
Canada
U.S.
2013
Site 1: 10 Jan
Sites 2-67: 28 Jan – 21 Mar
>500 snow samples
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N. American survey 2013 : 67 sites + 3 process study sites in 2014
2013 sites 2014 sites
Canada
U.S.
2013
Site 1: 10 Jan
Sites 2-67: 28 Jan – 21 Mar
>500 snow samples
2014
Sites 68-70: 27 Jan – 24 Mar
>360 snow samples
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MODIS Snow Cover (%) Feb 2013
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FIELD SAMPLING
• ~2-5cm vertical resolution • 3 parallel profiles • collect soil at each site
• melt/filter every ~3 days • re-freeze snow water for
chemical analysis
• nuclepore filters 0.4μm pore size ~95% capture efficiency
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ISSW analysis of filters
...extrapolate down to 300nm
, τ a
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ISSW analysis of filters
...extrapolate down to 300nm
calculate Åabs for λ=450, λo=600
τ a,λ τ a,λo
= λ λo
⎛ ⎝⎜ ⎞ ⎠⎟
− Åabs , τ
a
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ISSW analysis of filters
Assume: Åabs=1.1 for BC Åabs site-specific for non-BC
Partition absorption to get estimated BC via calibration curves (absorption � mass)
est BCCCBC
max
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ISSW analysis of filters
Scale by downwelling solar radiation
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ISSW analysis of filters
fraction of 300-750nm light absorption due to non-BC
constituents (organic carbon, soil, mineral dust)
est nonBCf
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er
Derived Parameters:
(ng/g) = maximum possible BC concentration � assumes all 650-700nm absorption is due to BC � assumes MAE of calib. standards matches that of BC on filt
(ng/g) = estimated BC concentration � derived using assumption of Åabs=1.1 for BC;
Åabs= site-specific for non-BC light absorbers
(ng/g) = amount of BC needed to account for all light
absorption 300-750nm (solar spectrum weighted)
(%) = fraction of 300-750nm solar absorption due to non-BC � derived using assumption of Åabs=1.1 for BC;
Åabs= site-specific for non-BC light absorbers
[450:600nm]
ma x BCC
est BCC
equiv BCC
est nonBCf
Åtot
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er
Derived Parameters:
(ng/g) = maximum possible BC concentration � assumes all 650-700nm absorption is due to BC � assumes MAE of calib. standards matches that of BC on filt
(ng/g) = estimated BC concentration � derived using assumption of Åabs=1.1 for BC;
Åabs= site-specific for non-BC light absorbers
(ng/g) = amount of BC needed to account for all light
absorption 300-750nm (solar spectrum weighted)
(%) = fraction of 300-750nm solar absorption due to non-BC � derived using assumption of Åabs=1.1 for BC;
Åabs= site-specific for non-BC light absorbers
[450:600nm]
ma x BCC
est BCC
equiv BCC
est nonBCf
Åtot
** NOT ESTIMATED IF
>0.85
est nonBCf
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Analysis for organics’ contribution to absorption via serial extractions � organics serially extracted from filters using four organic
solvents (methanol, dichloromethane, hexane and sodium hydroxide) [Dang and Hegg, 2014].
� Particulate spectral absorption measured with ISSW before extraction and after each extraction step
� Thus is a measurement of spectral absorption in snow due to different organic groups.
� OCabs = absorption due to all extracted organics
� Note: OCabs includes both “BrC” (light-absorbing combustion organics) & soil organics (e.g. HULIS)
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)
Chemical & PMF analysis � analyze for a suite of ions, carbohydrates & elements
� Use chemical data, optical data ( ) and OCabs (from serial extractions) as input to PMF analysis
� PMF : Positive Matrix Factorization
� generates factor profiles for orthogonal factors that contribute to the variance in an independent variable (e.g.
� provides chemical “fingerprints” of each factor, which are then interpreted for source type (can be a mix)
� provides the fractional contributions of each factor to the variance in an independent variable
� source “fingerprints” are not assumed a priori
ma x BCC
ma x BCC
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) results of ISSW/SP-2 comparison (ongoing; collaboration with J.P. Schwarz, NOAA
� First tests comparing BC mixing ratio for samples with: � fullerene (synthetic BC) � dust standard � fullerene + dust standard � PSL (non-absorbing spheres)
� Tested both against gravimetric determinations of BC and dust mixing ratio in the solutions
� SP2 and ISSW both agreed well with grav mixing ratios for pure fullerene
� small bias in SP2 for fullerene+dust
� significant high bias (up to factor of 2-3) in ISSW BC mixing ratios for fullerene/dust mixes
[Schwarz et al., 2012]
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Baaken Oil Fields
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CBCest
1
5
10
15
25
50
75100
150200250
120°W 110
° W 100° W 90
° W
40 °N
50 °N
60 °N
est BCC
Surface-most snow samples : BC mixing ratio
(ng/g)
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CBCequiv
× fNBCest
1
5
10
15
25
50
75100
150200250
BC mixing
120°W 110
° W 100° W 90
° W
40 °N
50 °N
60 °N
Surface-most snow samples : equivalent ratio needed to account for non-BC absorbers
equiv BCC est
nonBCfx
(ng/g)
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Åtot
1
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120°W 110
° W 100° W 90
° W
40 °N
50 °N
60 °N
Surface-most snow samples : Absorption Ångström exponent
Åtot
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CBCest
1
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75100
150200250
120°W 110
° W 100° W 90
° W
40 °N
50 °N
60 °N
est BCC
(ng/g)
Surface-most snow samples : BC
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CBCest
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150200250
120°W 110
° W 100° W 90
° W
40 °N
50 °N
60 °N
est BCC
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Snow column average : BC
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Biomass Pollution Soil
PMF Analysis : Factor contributions to 650-700nm absorption – Surface snow samples
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90° W 125 °
W 120°W 115
° W 110° W 105
° W 100° W 95
° W
40 °N
45 °N
50 °N
55 °N
Biomass Pollution Soil
PMF Analysis : Factor contributions to 650-700nm absorption – Surface snow samples
Baaken Oil Fields
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90° W 125 °
W 120°W 115
° W 110° W 105
° W 100° W 95
° W
40 °N
45 °N
50 °N
55 °N
Biomass Pollution Soil
PMF Analysis : Factor contributions to 650-700nm absorption – Surface snow samples
Baaken Oil Fields
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. In
A note regarding the relative roles of soil vs. BC in lower US Great Plains snow albedo � Great Plains soil contribution is higher in sub-surface
samples � likely because this corresponds to shallower snowpack, so more exposed soil to contribute
� Snow cover in 2013 was not anomalous – but there are years with more extensive and persistent snow cover these years, the relative role of BC (vs. soil) in lowering snow albedo will likely be higher
� i.e., BC likely only dominates snow albedo reduction in years with higher snowpack – when retention of the snow is less critical for water resources
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Why so much soil in Sern Great Plains snow?
(“snirt”) • Almost the entire area is
agricultural = disturbed soil
• It’s windy (!!!) in the winter
• Snow is often thin / patchy
• Snow cover is intermittent, especially to the S and W
� Dirt mixes in with snow as it’s falling, right near the surface. Regional/global models will not capture this.
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Why so much soil in Sern Great Plains snow?
(“snirt”) • Almost the entire area is
agricultural = disturbed soil
• It’s windy (!!!) in the winter
• Snow is often thin / patchy
• Snow cover is intermittent, especially to the S and W
� Dirt mixes in with snow as it’s falling, right near the surface. Regional/global models will not capture this.
un-tilled field
field tilled in the fall Farming practices may affect the color of snow at least as much as BC emissions in
much of the southern Great Plains
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Bakken Oil fieldsIncreased soil disturbance • clearing for oil platforms • much more driving on
dirt / farm roads • areas cleared for housing
Increased BC emissions • diesel trucks • oil flaring (significant?) • wood stoves in temporary housing?
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Quick-look comparison : Snow BC mixing ratios
ARCTIC [Doherty et al., 2010]
< 10 ng/g regional medians all regions other than Norway (~20 ng/g) and Russia (~30–40 ng/g)
N. CHINA [Wang et al., 2013]
~300–400 ng/g in north-central China >100 ng/g near the N border of NE China >900 ng/g in the industrial northeast
N. AMERICA [Doherty et al., 2014]
~ 5-40 ng/g : Pacific Northwest ~ 10-50 ng/g : Intramountain NW ~ 15-70 ng/g typical, but many >100 ng/g : U.S. Great Plains ~ 5-25 ng/g : Canada
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Quick-look comparison : Sources of light-absorbing particles in snow
ARCTIC [Hegg et al., 2009; Hegg et al., 2010]
� mostly biomass/biofuel burning � pollution in some locations/seasons (NW Russia, N. Pole, Greenland summer)
N. CHINA [Zhang et al., 2013] � NW (desert) & N-central (great plains) : dominated by soil & mineral
dust ; remainder is biomass/biofuel burning � NE : mix of biomass/biofuel burning & industrial/urban pollution
N. AMERICA [Doherty et al., 2014] � Pacific NW : mostly biomass/biofuel; remainder (~25%) fossil fuel
Intramountain NW : mix of soil, fossil fuel & biomass/biofuel U.S. Great Plains : dominated by soil in many locations; remainder
a variable mix of biomass/biofuel & fossil fuel � Canada : variable – mix of fossil fuel, soil & biomass � biomass:fossil fuel ratio increases later in winter season
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2009 Canadian Arctic survey
2007 Canadian sub-Arctic traverse
2013 N. Amer. Great Plains survey
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75 80
0
20
40
60
BC
est (
ng/g
)
50 55 60 65 70 1.0
1.5
2.0
2.5
latitude (oN)
Åto
t
est BCC
Åtot
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N. American survey 2013 : 67 sites + 3 process study sites in 2014
2013 sites 2014 sites
Canada
U.S.
2013
Site 1: 10 Jan
Sites 2-67: 28 Jan – 21 Mar
>500 snow samples
2014
Sites 68-70: 27 Jan – 24 Mar
>360 snow samples
Vernal, Utah sampling by colleagues at NOAA-PMEL (J. Johnson & T. Quinn)
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rnal, Utah
central/south Idaho 3 sites ~ 2 months sampling every ~3 days
Ve 1 site ~ 1 month sampling at least 1x/day
2014 field measurements
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1.0
1.4
1.8
2.2
2.6
3.0
3.4
3.8
Å tot
Some quick initial results from 2014 field measurements ...
0
10
20
30
40
50
60
70
80
90
100
1/24/14 2/3/14 2/13/14 2/23/14 3/5/14 3/15/14
(ng/
g) &
ne
w s
now
(%
)
% new snow
BCequiv
AAE
Idaho Site 68
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3.8
Å t
ot
Some quick initial results from 2014 field measurements ...
1.0
1.4
1.8
2.2
2.6
3.0
3.4
0
200
400
600
800
1000
1200
1400
1600
1800
2000
1/29/14 2/3/14 2/8/14 2/13/14 2/18/14 2/23/14 2/28/14 3/5/14
(ng/
g) &
ne
w s
now
(%
*10) % new snow
BCequiv
AAE
Idaho Site 69
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0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
Å tot
Some quick initial results from 2014 field measurements ...
0
200
400
600
800
1000
1200
1400
1600
1800
1/15/14 1/25/14 2/4/14 2/14/14
(ng/
g)
BCequiv
AAE
new
sno
wfa
ll
trac
e ne
w
Vernal, Utah
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~2-30 ng/g BC
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~1100ng/g BC~2-30 ng/g BC
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~1100ng/g BC~2-30 ng/g BC
???? ng/g BC dust/soil? algae?
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ma x BCC
Doherty et al. 2013
Greenland (Dye-2 site) vertical profile through 4 yrs melt layers
summer 2010
summer 2009
summer 2008
summer 2007
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new
The importance of post-wetdeposition processes
� Most of the variability in snow particulate light absorption is driven by what’s happening between snowfall events
� Dust & soil play a very strong role (dominate?) incidences of high snow particulate light absorption at: � US Great Plains sites � 2 Idaho mountain valley sites � near Vernal, Utah � for the US GP & Idaho sites this is mostly very loca.ly
transported soil, so will not be captured by regional/global models
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TBD
� finalize analysis / publication of 2014 field samples
� ongoing collaboration with DOE-PNNL to improve regional (WRF-Chem) and global (CESM) modeling of BC and dust in snow
� comparisons ISSW / SP2 of BC in snow from field samples
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A. E. Perring, R.
Atmos.,
, accepted,
Publications: Schwarz, J. P., S. J. Doherty, G. L. Kok, F. Li, S. T. Ruggiero, C. E. Tanner, S. Gao and D. W. Fahey, Assessing Single Particle Soot Photometer and Integrating Sphere/ Integrating Sandwich Spectrophotometer measurement techniques for quantifying black carbon concentration in snow, Aerosol Meas. Tech., 5, 2581-2592, doi:10.5194/ amt-5-2581-2012, 2012.
Doherty, S. J., T. C. Grenfell, S. Forsström, D. L. Hegg, S. G. Warren and R. Brandt, Observed vertical redistribution of black carbon and other light-absorbing particles in melting snow, J. Geophys. Res., 118(11), 5553-5569, doi:10.1002/jgrd.50235, 2013.
Wang, X., S. J. Doherty and J. Huang, Black carbon and other light-absorbing impurities in snow across Northern China, J. Geophys. Res., 118 (3), 1471-1492, doi: 10.1029/2012JD018291, 2013.
Dang, C., and D. A. Hegg (2014), Quantifying light absorption by organic carbon in western North American snow by serial chemical extractions, J. Geophys. Res. 19, 10,247–10,261, doi:10.1002/2014JD022156.
Doherty, S. J., C. Dang, D. A. Hegg, R. Zhang and S. G. Warren, Black carbon and other light-absorbing particles in snow of central North America, J. Geophys. Res. 2014.
(results from 2014 field samples in preparation)