Intro 1

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Intro 1
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
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Primary influence of BC on Spectral Albedo was
first characterized by Warren and Wiscombe
1980.(i) visible wavelengths(ii) grain radius
0.5ppm
0.05ppm
5 ppm
Snow Albedo
0.05 ppm
0.5 ppm
5 ppm
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Where and when does this matter (?)

• 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

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Pioneering Effort 1983/4 Survey
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Clarke Noone Sites

Soot in snow 1983-4 (Clarke Noone) Most amounts
are 5-50 parts per billion.
1983
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Expected magnitude of albedo reduction
Warren Wiscombe (1985) Warren
Clarke (1986) Soot contents from Clarke
Noone (1985)
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Difficulties with remote sensing
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 near-surface 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).
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Our Sites
Our 4-year project (begun in spring 2006) a
comprehensive surface-based survey of BC in
Arctic snow, to repeat and extend Clarke
Noonessurvey from 1983/4.
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Sampling Profiles
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Filter Apparatus deployed in the field
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Filters
Filters are compared to standard calibration
filters. They will be scanned with a
spectrophotometer to quantify BC, dust, other
components different spectral absorption curves.
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Greenland Sector
BC in snow (ppb) Median values K. Steffen
automatic weather stations
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Canada Sector
BC in Snow (ppb) M. Sturm (CRREL)
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Russian Sector
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.
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Representative Profile - Khatanga
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IPY News Information Bulletin June 2007
Stephen Hudson (left), a graduate student at the
University of Washington, traveling up the
Khatanga River
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Table of Results

strong haze event
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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.
?(albedo) changes from -0.01 to -0.03 for 35 ngC/g
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Spectral albedo of snow observed at selected
sites for closure - soot observations, RT
modeling, and spectral albedo. Svalbard, March
2007
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New Snow Loading and Scavenging Experiments -
Tony Clarke
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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)
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Thanks to
Jim Hansen for inspiring us to take on this
project Clean Air Task Force and NSF Arctic
Program for support
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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.
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Part 2. Source Attribution of Black Carbon in
Arctic SnowDean Hegg, Tom Grenfell, Steve
WarrenU. of Washington, Seattle, WA
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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)
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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.
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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.
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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.
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Preliminary Interpretation

• Both factors had appreciable levoglucosan,
  suggesting a strong biomass component to the
  BC

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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

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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.

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Further Analysis

• Analysis of non-filtered snow melt
• Chemical analysis of snow filters for insoluble
  tracers.
• In particular, analysis of filter deposits for
  PAHs (polycyclic aromatic hydrocarbons).
• More elaborate receptor modeling