Part 1. Black Carbon in Arctic snow:
concentrations and effect on surface albedo
Tom Grenfell & Steve Warren
University of Washington
Tony Clarke (University of Hawaii)
Vladimir Radionov (AARI, St. Petersburg)
Other UW participants:
Dean Hegg, Richard Brandt,
Sarah Doherty, Steve Hudson,
Mike Town, Hyun-Seung Kim,
Lora Koenig, Ron Sletten (ESS)
Jamie Morison, Andy Heiberg, Mike Steele (APL)
Project website: www.atmos.washington.edu/sootinsnow
Intro 1
0.5ppm
0.05ppm
5 ppm
Snow Albedo
Primary influence of
BC on Spectral
Albedo was first
characterized by
Warren and
Wiscombe 1980.
(i) visible
wavelengths
(ii) grain radius
0.05 ppm
0.5 ppm
5 ppm
Where and when does variation of snow albedo matter for climate?
Whenever large areas of snow are exposed to significant solar energy
Arctic snow
- Tundra in spring
- Sea ice in spring (covered with snow)
- Greenland Ice Sheet in spring (cold snow)
- Greenland Ice Sheet in summer (melting snow)
Glacier ice and sea ice:
- Ablation zone of Greenland Ice Sheet in summer
- Arctic sea ice in summer
Non-Arctic snow
- Great Plains of North America
- Steppes of Asia: Kazakhstan, Mongolia, Xinjiang, Tibet
Where and when does this matter (?)
Pioneering Effort – 1983/4 Survey
Soot in snow 1983-4 (Clarke & Noone) Most amounts are 5-50 parts per billion.
1983
Clarke & Noone Sites
Expected magnitude of albedo
reduction
Warren &
Wiscombe
(1985);
Warren &
Clarke
(1986)
Soot
contents
from Clarke
& Noone
(1985)
Difficulties in the use of remote sensing to determine BC's effect on snow albedo
1. It's hard to distinguish snow from clouds-over-snow, which hide the surface. Thin nearsurface layers of atmospheric ice crystals ("diamond-dust") are common in the Arctic.
2. The bidirectional reflectance (BRDF) is affected by:
a. small-scale surface roughness: ripples, sastrugi, suncups, pressure-ridges. (The effects of
sastrugi on BRDF are different at different wavelengths, because they depend on the ratio
of sastrugi width to flux-penetration depth.)
b. when thin surface-fog (or diamond-dust layer) covers the rough snow, the forward peak is
enhanced and the nadir view is darker. This darkening at nadir could be mistaken for BC
contamination.
c. Grain shape
3. Albedo reduction by BC in snow can be mimicked by:
- thin snow. Sooty snow has the same spectral signature as thin snow.
- increase of grain size with depth (common situation) preferentially reduces visible albedo
- sub-grid-scale leads in the Arctic Ocean.
- BC in the atmosphere above the snow (Arctic haze).
Difficulties with remote sensing
Our 4-year project (begun
in spring 2006): a
comprehensive surfacebased survey
of BC in Arctic snow,
to repeat and extend
Clarke & Noone’s
survey from 1983/4.
Yakutsk
Vorkuta
Noril'sk
Nar'y an Mar
Khatanga
Dikson
Magadan
Tiksi
Chersky
Pevek

90
80  N
N
70  N
60  N
50  N
Anady r
Uelen
SGW-NE
NASA-E
Petermann
Petermann ELA
Summit
GITS
Thule
Yukon River
NASA-SE
Dy e-2
Kugluktuk
Saddle
South D
Baker Lake
Our Sites
Sampling Profiles
Filter Apparatus deployed in the field
Filters are compared to standard calibration filters. They will be
scanned with a spectrophotometer to quantify BC, dust, & other
components – different spectral absorption curves.
Filters
90
BC in snow (ppb)
Median values
K. Steffen automatic
weather stations +
80

N
10

N
2
2
Peterm ann
1
2
Peterm ann ELA
SGW-NE
GITS
4 Thule
6
NASA-E
1
70

N
Sum m it
2
Dy e-2
NASA-SE
3->9 1
1
Saddle
60

N
South D
7

10
70
W

W

20
60  W
50  W

40 W
W

30 W
Greenland Sector
N
5 2
3
2
9
80

N
3
4,6
BC in Snow (ppb)
M. Sturm (CRREL) 70 
N
+
5
7
Yukon River
15
7
60 
25
Kugluktuk
N
10
67
57
5
12
3
70
15
6
Baker Lake
8
1225
54 4
23 8 9
6 11
17 5 10
15
0
6

W

14
0
7
W
130 
Canada Sector
70
 W
80
W
120  W
110 W

100 W

90 W
W

80 N

70
N
60
Uelen

N
Nar'y an Mar
Pevek
10
Vorkuta

50
220
Dikson
Anady r
9
N
Noril'sk
Chersky
Khatanga
30
Tiksi

45
E
Yakutsk
Magadan

75
5
16

E
E
105  E

135
E
T. Grenfell and Steve Hudson, Western Arctic Russia March-May 2007
Permissions were granted to enter restricted border areas;
International Polar Year (IPY) has prominence in Russia.
Russian Sector
Representative Profile - Khatanga
Новости МПГ
IPY News Information
Bulletin June 2007
Stephen Hudson (left), a
graduate student at the
University of
Washington, traveling
up the Khatanga River
*
*strong haze event
Table of Results
Enhancements
(1) Do particles collect at the surface as the snow melts?
Greenland (Dye-2) August 2007, melting snow:
surface 9 ppb, subsurface 3 ppb
(2) Snow grain size increases markedly with spring melt onset
magnifying the effect of a given soot load – accelerating
melt. Δ(albedo) changes from -0.01 to -0.03 for 35 ngC/g
Spectral albedo of snow observed at selected sites for closure - soot
observations, RT modeling, and spectral albedo. Svalbard, March 2007
New Snow Loading and Scavenging
Experiments - Tony Clarke
Plans for 2008
January: Artificial snowpack to quantify effect of soot on snow albedo with
homogeneous grain size and known BC loading - (Rich Brandt, Steve Warren –
Adirondacks)
March-May: Snow sampling in Eastern Siberia (Grenfell & Warren)
April: Albedo & BC intercomparison with Norwegian Polar Institute
(Gerland, Brandt)
April-May: Redistribution of BC during melt (Sanja Forsstrøm at Tromsø)
July: Greenland melting-snow zone: redistribution study - fine vertical BC sampling
of top 20 cm; spectral albedo (Brandt & Warren)
Calibrate new spectrophotometer; quantify BC, dust, other components (Sarah Doherty,
Tom Grenfell); further comparisons with SP2 (Joe McConnell, Tony Clarke)
Scanning Electron Microscope and chemical analysis of samples to investigate source
signatures (Hegg, Grenfell, Warren)
Thanks to:
Jim Hansen
for inspiring us to take on this project
Clean Air Task Force and NSF Arctic Program
for support
International Polar Year Collaborations
This project has benefited from the increased scientific activity in the Arctic, 2007-9.
Collaborations:
Norwegian Polar Institute (Svalbard) Sebastian Gerland
Danish Polar Center (Northeast Greenland) Carl-Egede Bøggild
Arctic and Antarctic Research Institute (Russia) Vladimir Radionov
Volunteers who have collected snow for this project in 2007:
Konrad Steffen & Thomas Phillips (Univ. Colorado). Automatic weather stations in
Greenland
Matthew Sturm (U.S. Army Cold Regions Lab, Fairbanks, Alaska).
Snowmobile traverse of Arctic Alaska and Canada
Jacqueline Richter-Menge (U.S. Army Cold Regions Lab, Hanover, NH).
Snow on sea ice in the Beaufort Sea
Jamie Morison, Andy Heiberg & Mike Steele (UW Applied Physics Lab).
North Pole Environmental Observatory and Switchyard Expt, Arctic Ocean.
Matt Nolan (Univ. Alaska). McCall Glacier, northern Alaska
Von Walden (Univ. Idaho). Ellesmere Island, Canada
Shawn Marshall (Univ. Calgary). Devon Island Ice Cap, Canada.
Part 2. Source Attribution of Black Carbon in Arctic Snow
Dean Hegg, Tom Grenfell, Steve Warren
U. of Washington, Seattle, WA
Yakutsk
Noril'sk
Vorkuta
Nar'y an Mar
Khatanga
Dikson
Magadan
Tiksi
Chersky
Pevek

90
80  N
N
70  N
60  N
50  N
Anady r
Uelen
SGW-NE
NASA-E
Petermann
Petermann ELA
Summit
GITS
Yukon River
NASA-SE
Dy e-2
Kugluktuk
Saddle
South D
Baker Lake
Current Data Base
• 36 sites - Canada, Greenland, Russia, North Pole
• BC estimates from filter samples
• 26 soluble co-analytes from filtered, melted snow
a. Anions – ion chromatography
b. Hydrocarbons – liquid chromatography, mass spectrometer detection
c. Elements – ICP-OES (inductively coupled plasma with optical emission spectroscopy)
BC concentration, 3 most highly correlated analytes,
and a biomass fire tracer (Levoglucosan)
Levoglucosan is not simply correlated with BC but is identified by the factor analysis.
PMF (Positive matrix factorization) model results (tentative) for available
data base. The five most significant factors explained 90% of variance.
90 % of the mass of BC is associated with this and the next factor.
PMF Results continued. Factor shown had next highest BC
loading. These two factors accounted for over 90% of the BC
90 % of the mass of BC is associated with this and the previous factor.
Preliminary Interpretation
•Both factors had appreciable levoglucosan, suggesting
a strong biomass component to the BC
Preliminary Interpretation
•Both factors had appreciable levoglucosan, suggesting
a strong biomass component to the BC
•The 1st factor was associated primarily with the
Russian sites, the 2nd with the Canadian sites
Preliminary Interpretation
•Both factors had appreciable levoglucosan, suggesting
a strong biomass component to the BC
•The 1st factor was associated primarily with the
Russian sites, the 2nd with the Canadian sites
•Both factors also indicated a pollution component of
different composition for the two locales. This is
expected and may be a geographic discriminator.
• More species are needed to explore the attribution in
detail.
Further Analysis
• Analysis of non-filtered snow melt
• Chemical analysis of snow filters for insoluble
tracers.
• In particular, analysis of filter deposits for
PAH’s (polycyclic aromatic hydrocarbons).
• More elaborate receptor modeling