Variability of black carbon deposition to the East Antarctic Plateau ...

Atmos Chem Phys 12 3799ndash3808 2012wwwatmos-chem-physnet1237992012doi105194acp-12-3799-2012copy Author(s) 2012 CC Attribution 30 License

AtmosphericChemistry

and Physics

Variability of black carbon deposition to the East Antarctic Plateau1800ndash2000 AD

M M Bisiaux1 R Edwards12 J R McConnell1 M R Albert 3 H Anschutz4 T A Neumann5 E Isaksson4 andJ E Penner6

1Desert Research Institute Division of Hydrologic Sciences Reno NV USA2Curtin University Imaging and Applied Physics Perth WA Australia3Thayer School of Engineering Dartmouth College Hanover NH 03755-8000 USA4Norwegian Polar Institute Tromsoslash Norway5NASA Goddard Space Flight Center Greenbelt MD USA6University Michigan Ann Arbor MI USA now at Norwegian Geotechnical Institute Oslo Norway

Correspondence toM M Bisiaux (marionmabisiauxgmailcom)

Received 14 November 2011 ndash Published in Atmos Chem Phys Discuss 22 November 2011Revised 15 March 2012 ndash Accepted 21 March 2012 ndash Published 26 April 2012

Abstract Refractory black carbon aerosols (rBC) frombiomass burning and fossil fuel combustion are depositedto the Antarctic ice sheet and preserve a history of emis-sions and long-range transport from low- and mid-latitudesAntarctic ice core rBC records may thus provide informa-tion with respect to past combustion aerosol emissions andatmospheric circulation Here we present six East Antarc-tic ice core records of rBC concentrations and fluxes cov-ering the last two centuries with approximately annual res-olution (cal yr 1800 to 2000) The ice cores were drilledin disparate regions of the high East Antarctic ice sheetat different elevations and net snow accumulation ratesAnnual rBC concentrations were log-normally distributedand geometric means of annual concentrations ranged from010 to 018 microg kgminus1 Average rBC fluxes were deter-mined over the time periods 1800 to 2000 and 1963 to2000 and ranged from 34 to 155 microg mminus2 aminus1 and 36 to218 microg mminus2 aminus1 respectively Geometric mean concentra-tions spanning 1800 to 2000 increased linearly with eleva-tion at a rate of 0025 microg kgminus1500 m Spectral analysis of therecords revealed significant decadal-scale variability whichat several sites was comparable to decadal ENSO variability

1 Introduction

Nanoparticles of refractory black carbon (rBC soot) aerosolsare emitted to the atmosphere during fires and fossil fuelcombustion and transported over long distances at thehemisphere-scale (Seiler and Crutzen 1980 Andreae et al2005 Crutzen and Andreae 1990) Because of their stronglight absorption properties rBC nanoparticles alter air tem-perature snow albedo and impact climate (Moosmuller etal 2009 Ramanathan and Carmichael 2008 Ramanathanet al 2001 Jacobson 2001 Flanner et al 2007 Penner etal 2002) The incorporation of future emissions scenarios istherefore a key parameter for global climate modellers (Ra-manathan and Carmichael 2008)

However even if surveys of rBC atmospheric concentra-tions and fire occurrence are being constructed for the lastfew decades thanks to the development of new satellite tools(Ito and Penner 2004 Chung et al 2005) the history of rBCfire emissions over last two centuries is incomplete (Mouillotand Field 2005) Indeed a detailed fire history over periodscovering the pre-industrial time to the modern era is lackingnotably because common fire proxies such as charcoal de-posits or gas emissions reconstructions from ice cores cannotreconstruct large spatial variability at inter-annual time scales(Marlon et al 2008 Wang et al 2010) Nonetheless fireregimes are likely to have been modified by anthropogenic

Published by Copernicus Publications on behalf of the European Geosciences Union

3800 M M Bisiaux et al Variability of black carbon deposition to the East Antarctic Plateau

activities such as tropical deforestation land-clearing prac-tices or through natural changes in precipitation and tem-perature patterns with the changing climate (Dube 2009Nitschke and Innes 2008 Bowman et al 2009)

Recently several studies have directly used rBC from icecores to estimate emissions from past combustion spanningthe transition from the pre-industrial to the modern era In theNorthern Hemisphere ice cores from Greenland and the Hi-malayas have shown the impact of coal combustion on rBCsnow concentrations (McConnell et al 2007 McConnell2010 Kaspari et al 2011) In the Southern Hemisphere(SH) two high resolution rBC records from Antarctica haverecently been used to investigate the evolution of forest andgrass fires (Bisiaux et al 2012) The records from the WestAntarctic Ice Sheet (WAIS) and Law Dome spanned the timeperiod 1850ndash2001 and showed large-scale changes in rBCdeposition linked to climatic oscillations such as El NinoSouthern Oscillation (ENSO) and the anthropogenic modi-fication of fire regimes

However the contribution of each continent to AntarcticrBC deposition remains unknown as well as the influenceof atmospheric transport to sites located in the Atlantic sec-tor of Antarctica Ice core sites located at high elevation onthe East Antarctic Plateau in East Antarctica may record dif-ferent variability than the sites previously studied on coastalEast Antarctica and the West Antarctic Ice Sheet (Bisiaux etal 2012) The present study uses rBC paleorecords from theAtlantic sector to investigate spatial and temporal variabilityof rBC deposition and the link with emissions sources Weuse six ice core records from Dronning Maud Land (Fig 1)and focus on the cal yr period 1800ndash2000 covering pre-industrial and modern eras These sites have much lowerannual snow accumulation rates (20ndash60 kg mminus2 aminus1) com-pared to the sites investigated by Bisiaux et al (2012) (150ndash200 kg mminus2 aminus1) and have a lower temporal resolution (an-nual to multi-annual) We use accumulation calculationsfrom Anschutz et al (2011) to estimate rBC fluxes at thesesites and the importance of precipitation on rBC concentra-tions Periodic oscillations in the rBC records are investi-gated through spectral and multiple regression analysis andcompared to sodium (Na) records (measured simultaneously)to evaluate the influence of transport in the observed rBCvariability

2 Drilling sites and methods

21 Drilling site locations and characteristics

The sites are all located on the East Antarctic Plateau (el-evationgt 2500 m) in Dronning Maud Land (Fig 1) Thecores were drilled during two exploratory traverses by aNorwegian-American team (NUS) in the summer of 2007(cores ldquo07-Xrdquo) and in the summer of 2008 (cores ldquo08-Xrsquo)Latitudes longitudes and elevations are compiled in Table 1

Figure 1 NUS07-1

NUS07-2

NUS07-5

NUS08-5

NUS08-4

NUS07-7

WAIS

Law Dome

Fig 1 Map of the traverse route 20072008 (black line) and20082009 (blue line) with drill described in this study sites fromboth legs indicated (NUS07-X and NUS08-X) Relevant stations inthe area of investigation are shown as well Elevation contour linesare in 100 m intervals The map was compiled by K Langley andS Tronstad (Norwegian Polar Institute) and adapted by Anschutz etal (2011) for this study The locations of the WAIS and Law Domedrilling sites are shown on the inset as red dots

Cores NUS08-4 and NUS08-5 were drilled in adjacent loca-tions and onlysim17 km apart All cores are firn cores of totallength under 90 m of which we present the top part downto a depth corresponding to cal yr 1800 (Table 1) How-ever the top dates are not common to all cores (due largelyto fragile near-surface firn sections) and range from cal yr1989 for NUS 07-5 to cal yr 2008 for NUS 07-7(Table 1)

22 Ice core analysis

Longitudinal sections of the NUS ice cores were analysedfrom 2008 to 2010 at the Desert Research Institute on an ice-core melter continuous flow analysis system with in-line rBCmeasurements The inner 1 cm2 of the sections were used for

Atmos Chem Phys 12 3799ndash3808 2012 wwwatmos-chem-physnet1237992012

M M Bisiaux et al Variability of black carbon deposition to the East Antarctic Plateau 3801

Table 1 Sites coordinates rBC concentrations and fluxes annual accumulation for this study and previous study by Bisiaux et al (2012)for two periods of time (since 1800 and since 1963)

This study Bisiaux et al (2012)

NUS07-1 NUS07-2 NUS07-5 NUS07-7 NUS08-4 NUS08-5 WAIS (WDC06A) Law Dome (DSSW19K)

Lat ndash long 7343prime Sndash 7604prime Sndash 7839prime Sndash 8204prime Sndash 8249prime Sndash 8238prime Sndash 7946prime Sndash 6673prime Sndash0759prime E 2228prime E 3538prime E 5453prime E 1854prime E 1752prime E 11208prime W 11283prime E

Elevation (in m asl) 3174 3582 3619 3725 2552 2544 1766 1390Depth of yr 1800 for this 222305 164904 126895 146906 180530 17592 ndash ndashStudytotal core depth (in m)Period covered 1800ndash2006 1800ndash1993 1800ndash1989 1800ndash2008 1800ndash2004 1800ndash19931850ndash2001 1850ndash2001Number of data points 2154 1501 1111 1308 1672 1616 4860 2883

Annual rBC conc (geometric since 1800 016 012 014 018 010 011 008 009mean) in microg kgminus1 range (2σ)a 009 to 026 007 to 019 008 to 026 012 to 027 006 to 018 007 to 018005 to 012 005 to 02

since 1963 014 014 018 019 015 012 008 007 range (2σ)a 008 to 027 008 to 024 014 to 024 013 to 029 008 to 026 008 to 020005 to 012 004 to 015

Annual accumulationb since 1815 520plusmn 20 330plusmn 07 240plusmn 05 294plusmn 06 367plusmn 09 350plusmn 08 200plusmn 34 150plusmn 31in kg mminus2 aminus1 since 1963 559plusmn 39 280plusmn 20 201plusmn 14 261plusmn 19 361plusmn 21 376plusmn 23 ndash ndash

Annual rBC fluxes (geometric since 1800c 83 39 34 53 37 39 16 135mean) in microg mminus2 aminus1 range (2σ) 46 to 142 25 to 62 18 to 63 35 to 80 21 to 69 22 to 65 98 to 244 73 to 306

since 1963 78 39 362 5 54 45 ndash ndash range (2σ) 40 to 158 24 to 73 26 to 52 31 to 80 27 to 100 27 to 80 ndash ndash

a Multiplicative standard deviationb From Anschutz et al 2011c We assume same accumulation rate for the 1800ndash1815 periods

the rBC analysis according to the method previously usedin McConnell et al (2007) and McConnell (2010) and de-scribed in detail by Bisiaux et al (2012) The rBC analy-sis consisted of an ultrasonic nebulizerdesolvation system(CETAC UT5000) coupled to a Single Particle Soot Pho-tometer (SP2 Droplet Measurement Technologies BoulderColorado) In this system ice core meltwater was nebulizedand desolvated to form a dry aerosol The aerosol then passedinto the SP2 where individual particles in the diameter rangesim70ndash400 nm were heated up to incandescence by an Nd-YAG laser (1064 nm) and the emitted radiation was mea-sured by optical detectors (photomultiplier tubes) Individualparticle masses were determined using calibration data gen-erated from the introduction of rBC particles of known massdirectly into the SP2 Additional calibrations of the SP2 cou-pled to the ultrasonic nebulizer (USN) were performed dailyusing rBC colloids These calibrations were used to accountfor rBC losses in the USN Depth resolution of the analyticalsystem was estimated at 1 cm

23 Ice core dating

Annual layer counting was not possible for these NUS coresand dating was based on the identification and mapping be-tween ice cores of a number of chemical markers correspond-ing to explosive volcanic eruptions Specifically we usedcontinuous high-depth-resolution measurements of non-sea-salt sulphur (nssS) in the WAIS Divide (WDC06A) and NUSice cores to identify layers with significant volcanic sulphurconcentrations Dating of the volcanic horizons was per-formed using annual layer counting in the WAIS Divide icecore (Bisiaux et al 2012) The WAIS core volcanic chronol-ogy was then applied to the NUS coresrsquo volcanic horizons

(Table 1) Although well-known large volcanic events (egTambora Krakatoa Agung) were included in the chronol-ogy smaller less-known volcanic events were used to fill inthe depth-age relationships where possible (a total of seventie points cal years 1810 1816 1837 18634 1884 196519912) Dating between the volcanic horizons assumed uni-form accumulation between horizons Snow accumulationrates (net) at each site (Table 1) were based on these depth-age relationships and ice-core depthdensity profiles (An-schutz et al 2009 2011) and restricted to average rates be-tween the dating horizons (which included the ice cap sur-face)

The number of rBC data points varied from 6 to 10 peryear However the dating uncertainty is likely on the or-der of several years due to the low annual snow accumula-tion rates and physical processes such as the redistributionof snow by wind Overall the dating uncertainty may be aslarge asplusmn5 yr between the dating horizons The depth-agerelationship of the NUS 07-1 core benefited from previouslypublished accumulation rate data (Isaksson et al 1999) andwas used as the basis of further refinement of the 08-5 and08-4 depth-age relationship using decadal trends in the rBCrecords The refinement process consisted of warping the08-4 and 08-5 rBC non-linear trend (described in Sect 24)peaks and troughs to the 07-1 non-linear rBC trend (withinthe constraints of the volcanic chronology) using the Anal-yseries software (Paillard et al 1996) lineage tool The re-fined depth-age relationships resulted in coherent non-lineartrends between the 08-4 and 08-5 records which were drilledin the same region (separated by 17 km)

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3802 M M Bisiaux et al Variability of black carbon deposition to the East Antarctic Plateau

24 Data analysis

241 Period studied

The study focused on two time periods including 1800 to1990ndash2003 (time period depending on the ice core consid-ered) and 1963 to 1990ndash2003 These time periods were se-lected to coincide with the snow accumulation calculationsby Anschutz et al (2011) For the purpose of this study thesnow accumulation rate from the time period 1809 to 1815was assumed to extend to 1800

242 Concentrations

The frequency distributions of the ice core rBC concentra-tions were determined to be lognormal Statistics such asthe average and standard deviation and mathematical op-erations such as re-sampling smoothing trend and spec-tral analysis etc were therefore performed in log-space(Limpert et al 2001) to give ldquorobustrdquo geometric rather thanarithmetic statistics Note that here the geometric standarddeviation is the multiplicative standard deviation (Limpertet al 2001) which covers 683 of the variability cor-responding toσminconc = geometric meanmiddot geometric stan-dard deviation andσmaxconc = geometric meangeometricstandard deviation Prior to spectral analysis the concentra-tion data were re-sampled to an annual time scale using theldquorobustrdquo piecewise linear interpolation method described byPaillard et al (1996) A 21-yr smoothing window was usedto capture decadal-scale variability and was performed usingthe non-parametric Nadaraya-Watson kernel density regres-sion method (Watson 1964 Nadaraya 1965) The time win-dow used for the smoothing represents a trade-off betweenthe temporal resolution of the different records and the timespan of the records and variability in the later half of the 20thcentury Monotonic trends were estimated using the nonpara-metric Thiel-Sen approach (Gilbert 1987Onoz and Bayazit2003) while non-linear trends were calculated with singu-lar spectrum analysis (SSA) using Kspectra software (Ghil etal 2002) at a 95 Kendall level of confidence Significantnon-linear trends were reconstructed using the Kspectra SSAtool which partially reconstructs the time series based on alinear combination of trend principal components (Ghil et al2002) The non-linear trend data were then back-transformedfrom log-space and normalized (Z-scores calculated usingthe arithmetic mean and standard deviation of the completetrend reconstruction) for easier comparison of variability be-tween records

243 Deposition fluxes

Flux calculations were based on longer-term average snowaccumulation estimates obtained by Anschutz et al (2011)from the volcanic chronology Atmospheric fluxes ofrBC were estimated by multiplying annual rBC concen-trations and accumulation rates corresponding to the two

time periods chosen Fluxes uncertainties were esti-mated asσminflux = σminconcmiddot accumulationminusσminaccu)

andσmaxflux = σmaxconcmiddot (accumulation +σmaxaccu)

244 Spectral analysis

Spectral analysis was conducted using Analyseries software(Paillard et al 1996) Significant periodic oscillations in therBC and Na ice core records and their spectral coherencewere investigated using the Blackman-Tukey method with aBartlett window In this study we define coherence as thefraction of common variance between two time seriesx andy through a linear relation considering non-zero when co-efficients reach valuesgt038 (Paillard et al 1996) Herewe use raw data re-sampled to a 04 yr step with piecewiselinear interpolation to perform the calculations in order to re-move lower frequencies but to keep the eventual annual cy-cles Coherence coefficients are given with 3 levels of con-fidence (low medium and high) of which we only presentthe medium level and only for coefficientsgt038 in Fig 6Principal components 1 extracted from records are calcu-lated with an embedding dimension of 20 and theory fromVautard and Ghil (1989)

3 Results and discussion

31 Concentrations and fluxes

Concentrations of rBC were found to be log-normally dis-tributed with geometric means of annual concentrationsranging from 010 to 018 microg kgminus1 since 1800 and from 012to 019microg kgminus1 since 1963(Table 1) Overall the NUS icecore geometric mean rBC concentrations were higher thanthe concentrations previously determined at lower elevationsites for the same time periods at WAIS (WDC06A) and LawDome (DSSW19K) (Bisiaux et al 2012) We attribute thisdifference to the very low annual snow accumulation rates onthe plateau (Table 1) and thus to a low rBC dilution by snowsuggesting a significant fraction of dry versus wet depositedrBC However annual rBC fluxes estimates since 1800 arestill lower (34 to 83microg mminus2 aminus1) than those determined forthe WDC06A and DSSW19K (Table 1)

The time series of annual and 21-yr smoothed rBC con-centrations at all NUS sites are shown in Fig 2 Signif-icant monotonic trends with superimposed decadal vari-ability (for the whole period 1800 ndash onwards Mann-Kendall test double-sided p-valueslt00001) were foundin annual rBC concentrations at sites 07-5 08-4 and 08-5(Fig 3a) The trends at these sites represented an increase ofsim003plusmn 001microg kgminus1100 yr Comparison of the records atannual resolution revealed no significant cross-correlationsincluding for sites 08-4 and 08-5 which were within 17 kmof each other We conclude that surface processes (accu-mulation rate variability sastrugi blowing snow and snowsublimation) prevent the analysis of rBC signal at annual

Atmos Chem Phys 12 3799ndash3808 2012 wwwatmos-chem-physnet1237992012

M M Bisiaux et al Variability of black carbon deposition to the East Antarctic Plateau 3803

Figure 2 rB

C c

on

cen

trat

ion

s (micro

gk

g)

rBC

co

nce

ntr

atio

ns

(microg

kg

)

Cal years

NUS 07-1

NUS 07-5

NUS 08-4

NUS 07-7

NUS 07-2

NUS 08-5

Fig 2 Time series of rBC concentrations Black line is annual(piece-wise linear integration interpolation of log raw data) and redline is 21 yr k-smooth on annual (calculated in log space) The pe-riods of relatively low values (1890ndash1910) and high values (1920ndash1940) as described in Fig 3 are indicated as shaded areas

time scales and restrain the resolution to interannualdecadal-scales (Pomeroy et al 1999)

Decadal-scale variability was investigated using singularspectrum analysis non-linear trend reconstruction (Ghil etal 2002) Significant non-linear trends over the entire pe-riod (1800 ndash onwardsp lt 005 Mann-Kendall trend test)are shown in Fig 3bndashc (normalized as Z-scores) Non-linear trends from sites 08-4 and 08-5 (which were indepen-dently mapped to the 07-1 time scale) were highly correlated(r = 064r2

= 041n = 195p lt 001) Correlation coeffi-cients for the other records were insignificant but with somecommon features Comparison of these non-linear trends cfFig 3bndashc revealed a period of low concentrations from calyr 1890 tosim1915 common to observations made at WAISand Law Dome (Bisiaux et al 2012) Here however thisdrop is followed by a period of relatively high concentra-tions until sim1940 and peaking locally in the 1930s Whilethis peak was detected in the high resolution record fromLaw Dome (Bisiaux et al 2012) it was absent from theWAIS record With the exception of site 07-2 (Fig 3bndashc)

Figure 3

a

b

c

d

Fig 3 (a)Monotonic trends for sites 07-5 08-4 and 08-5 (Kendallsignificance = 99 ) (b c d) Non-linear trends normalized asZ-scores (Kspectra software Kendall significance = 95 ) for thesix NUS rBC records as a function of time Corresponding frac-tion of record variability is indicated next to record name ()(b)Comparison of twin sites 08-4 and 08-5 re-scaled from 07-1 dating(plain curve) Original dating is shown as dotted line(c) Otherthree records 07-2 07-5 and 07-7 Shaded areas highlight specif-ically common features andor trends(d) Comparison of trends(Z-scores) from sites 07-1 08-4 08-5 with NADA variance (ENSOlong term variability) in dotted line scale inverted

the NUS rBC records also lacked the period of low variancefrom sim1940 tosim1980 found in the WAIS and Law Domerecords Finally the last 20 yr (1980ndash2000) show an increas-ing trend for the coresrsquo recording this period which was alsonoted by Bisiaux et al (2012) for WAIS and Law Dome

32 Effect of elevation

The geometric average of the annual rBC concentrations ateach site was found to increase linearly with elevation cf Ta-ble 1 for site elevation Linear correlation coefficient (r) was081 when concentrations were averaged since 1800 (r2

=

067 n = 8 p = 001) and 092 when concentrations wereaveraged since 1963 (r2

= 086 n = 8 p lt 001) (Fig 4a)The slope of this linear regression corresponds to an increaseof 0015 and 0025 microg for an elevation gain of 500 m respec-tively

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3804 M M Bisiaux et al Variability of black carbon deposition to the East Antarctic PlateauFigure 4

Fig 4 Geometric mean rBC(a) and Na(b) concentrationssimsince cal yr 1800 (top) and 1963 (bottom) as a function of site altitude For Naregression line was calculated without the maritime site ldquoLaw Domerdquo(c) Geometric mean rBC concentrations as a function of accumulationafter cal yr 1800 (top) and 1963 (bottom) (Anschutz et al 2011) Uncertainty bars refer to Table 1 Regression lines and coefficients arebased on geometric mean valuesr2 indicates the coefficient of determinationlowast Values for Law Dome and WAIS from Bisiaux et al (2012)

The increase of rBC with elevation was previously ob-served in the southern latitude atmospheres by Schwarzet al (2010) and modelled for Arctic snow by Skeie etal (2011) Stohl (2006) also modelled increased atmosphericloading in the southern latitudes and attributed this increaseto rBC transport from lower latitudes towards the ice capalong isentropic trajectories that may not reach the surface ofthe region lower than the plateau and remain at higher eleva-tions

To investigate whether rBC transport to the plateau is mod-ulated by the intrusion of marine air masses the variabil-ity of Na concentrations (geometric means) with elevationwas also investigated In this case no significant relationshipwas found (r2

= 005 n = 7 p gt 005)(Fig 4b) This con-firms observations previously made by Bertler et al (2005)showing no link between increased elevation and Na con-centrations for altitudes above 2000 m We hypothesize thatthis absence of correlation with elevation for Na and pres-ence of correlation for rBC are due to both a difference inthe sources of Na and rBC aerosols and to a difference inatmospheric transport Indeed the main sources of Na aremarine aerosols which are transported to the East AntarcticPlateau by low pressure systems (Sneed et al 2011) and drydeposited (Fischer et al 2007) Transport processes associ-ated with rBC therefore appear to be different from thoseassociated with Na This suggests that rBC inputs to theatmosphere of the East Antarctic Plateau are not controlledby the intrusion of marine air masses and that transport inthe upper troposphere may be important Vertical profiles of

rBC in the near Antarctic atmosphere reported by Schwarzet al (2010) who found that rBC increased with altitudeHere wet removal processes limit the lifetime of rBC nearthe boundary layer while dry air in the upper atmosphereincreases the rBC residence time

Snow water accumulation rates on the contrary do showa significant inverse trend with rBC concentrations butonly from 1963 onwards (r2

= 074 r = 085 n = 8 p lt

001)(Fig 4c) However this correlation is determinedmainly by the WAIS and Law Dome data points with NUSsites clustering around the same values (Fig 4c) Uncertain-ties inherent in the net snow accumulation rate must also beconsidered Acknowledging these caveats the slope of thelinear regression of 0030 microg in rBC for a 50mm decrease inaccumulation can be compared with the increase of 0025 microgrBC estimated for every 500 m in elevation for the time pe-riod from 1800 to the present (Fig 4a top) Thus for thetwo time periods shown in Fig 4 the change in elevationmay explainsim80 of the difference in rBC geometric meanconcentrations Therefore we suggest that the main processcontrolling the spatial differences in geometric rBC snowconcentrations between the sites of the Antarctic Plateau isthe decrease in accumulation and corresponding increase inrBC dry deposition inducing less dilution of the particlesThis relationship may explain the monotonic trend found forthe record 07-5 (Sect 31) which exhibits a decrease in ac-cumulation rate from the period 1815 ndash onwards to the period1963 ndash onwards (Anschutz et al 2011 Isaksson et al 1999)cf Table 1 However it is not as clear for the two other sites

Atmos Chem Phys 12 3799ndash3808 2012 wwwatmos-chem-physnet1237992012

M M Bisiaux et al Variability of black carbon deposition to the East Antarctic Plateau 3805

Figure 5

Fig 5 Cross correlation coefficients between Na and rBC from thesame record Na leads rBC for delaysgt0 and rBC leads Na fordelayslt0

displaying significant increasing monotonic trends 08-4 and08-5 but no strong trend in accumulations(Table 1)

33 Influence of transport

For the sites 07-1 08-4 and 08-5 cross-correlations of theannual rBC and Na suggest common high frequency vari-ability between the rBC and Na species at each site withoutleads or lags (Fig 5) These data suggest a transport compo-nent linked to some of the high frequency variability Non-linear low frequency trends similar to those found in the rBCrecords (Fig 3bndashc) were not found in the Na records Ac-cording to Sodemann and Stohl (2009) precipitation in thishigh-altitude region of the Eastern Antarctic originates fromsources located much further north than for the coastal re-gions The lack of a correlation between the annual rBC dataat the remaining sites and the non-linear trends at 08-4 08-5and 07-1 suggests that the low frequency rBC variability maybe linked to emission variability or site specific atmospherictransport

To test this hypothesis the spectral coherence for Na andrBC was investigated (Fig 6) This analysis determined thecoherence between periodic signals in the rBC and Na timeseries A high coefficient for a given frequency suggests thatthe two periodic signals have coherent variability Sites 08-4 and 08-5 exhibit coherence coefficients higher than 038(black line) for a large portion of the bandwidth Notableexceptions are the ENSO band fromsim4 to 7 yr and at lowerdecadal frequencies For sites 07-2 and 07-7 coherence ismuch lower and oftenlt038 confirming observations madeon cross-correlations between Na and rBC (Fig 5) Coher-ences between Na and rBC for sites 07-1 and 07-5 were sim-ilar to 08-4 and 08-5 with less coherence at low frequencies(lt02 cycles per year)

The spectral power of rBC time series is shown as a redline in Fig 6 Peaks of high power designate frequenciesexplaining some variability of the signal If these power

Figure 6

Fig 6 Spectral power (red) of rBC NUS records and coherencecoefficients (black) between rBC and Na investigated for the wholeperiod (since 1800) Non-zero coherence is above 038 Red lettersldquoNTrdquo stand for ldquoNon Transportrdquo They indicate periodic signals inthe rBC records that are not coherent to Na (no black peak) andthat are likely related to rBC emissions rather than regional to longrange atmospheric transport The red numbers below ldquoNTrdquo showthe corresponding periodicity (in years)

peaks do not correspond to a peak in coherence between Naand rBC (black line) they indicate an oscillation that is notlinked to common atmospheric transport (NT) A periodicityof sim45 to 7 yr (sim017 to 02) is found common to sites 07-207-5 07-7 08-4 and 08-5 This period window suggests theinfluence of ENSO However even if an ENSO ldquosignaturerdquois present none of the rBC records is statistically correlatedto the ENSO index which may be explained by two reasonsFirst the records do not have the temporal resolution to ade-quately resolve the signal from noise Second ENSO has bynature a dual effect on fire potential by inducing drought onone side of the Pacific and floods on the other side renderinga potential ENSO-fire signal very disparate (Krawchuk andMoritz 2011)

However a NT periodic oscillation ofsim15 to 40 yr(005plusmn 0024 cycles per year) is found in records 07-1 07-207-5 07-7 and 08-4 (Fig 6) This long-term periodicity inrBC which is not related to Na suggests a link to fire emis-sion variability or long-range upper atmospheric transport

wwwatmos-chem-physnet1237992012 Atmos Chem Phys 12 3799ndash3808 2012

3806 M M Bisiaux et al Variability of black carbon deposition to the East Antarctic Plateau

However both may be linked to ENSO Indeed this periodic-ity is found to correspond to an ENSO reconstruction derivedfrom the North American Drought Atlas (NADA) (Li et al2011) which is anti-correlated to the large-scale rBC vari-ability observed in Fig 3d (scale inverted) Here higher rBCconcentrations are associated with low variance periods (LaNina colder) and lower concentrations during high varianceperiods (El Nino warmer) This suggests that increased rBCemissions from fire drive higher rBC loading of the Antarc-tic atmosphere during decadal time periods dominated by LaNina

4 Conclusions

Concentrations of rBC found in the NUS ice cores revealboth spatial and temporal variability during the 1800ndash2000time period Spatial variability was primarily associated withchanges in elevation and is likely linked to increased atmo-spheric loading in rBC andor decreased accumulation withaltitude Relatively stable net snow accumulations rates atthe NUS sites (Anschutz et al 2011) suggest that decadalvariability is related to changes in the rBC aerosol in theoverlying air On the other hand the absence of strong cor-relations between the records may suggest that site-specificatmospheric transport and surface processes influence rBCconcentrations at these sites This is confirmed by highcorrelation and coherence coefficients between Na and rBCfor some of the sites This observation is different fromthe results obtained at WAIS and Law Dome by Bisiauxat al (2012) Indeed at those low elevation sites it wasshown that most of the recorded rBC variability was inde-pendent from atmospheric transport which modulates the Narecord However spectral analysis revealed the existence ofnon-transport oscillatory signals common to almost all therecords Common features in the recordsrsquo non-linear trendsshowing relatively low concentrations from 1890 to 1910high concentrations until 1930 and an increasing trend at theend of the 21st century confirm the presence of a variabilitylinked to rBC sources only Nevertheless while large-scalechanges in rBC deposition at WAIS and Law Dome werefound to correspond to a change in anthropogenic activitiesmeasurements from the East Antarctic Plateau suggest a linkwith ENSO long-term emissions In any case global climateand aerosols models may enlighten the variability of rBC de-position to Antarctica and the apportionment between thevarious continental sources

AcknowledgementsThis research is based upon work supported bythe National Science Foundation under Grant Numbers 07330890538185 0538416 0538595 and has been carried out under theumbrella of TASTE-IDEA within the framework of IPY projectno 152 jointly funded by the US National Science Foundation theNorwegian Polar Institute and the Research Council of NorwayThe project is part of the Trans-Antarctic Scientific TraverseExpeditions ndash Ice Divide of East Antarctica (TASTE-IDEA) and

the International Partners in Ice Coring Sciences (IPICS) under theISCU-WMO endorsement for the International Polar Year 2007-08and 2008-09 We gratefully acknowledge the NUS traverse fieldteams the National Science Foundation the Norwegian PolarInstitute and the DRI ice core analysis team Logistic support inAntarctica was provided by Raytheon Polar Services in Antarcticaand the 109th New York Air National Guard The National IceCore Laboratory which archived the ice cores and preformed coreprocessing is funded by the National Science Foundation

Edited by P Quinn

References

Andreae M O Jones C D and Cox P M Strong present-dayaerosol cooling implies a hot future Nature 435 1187ndash11902005

Anschutz H Muller K Isaksson E McConnell J R FischerH Miller H Albert M and Winther J G Revisiting sites ofthe South Pole Queen Maud Land Traverses in East AntarcticaAccumulation data from shallow firn cores J Geophys Res114 D24106doi1010292009jd012204 2009

Anschutz H Sinisalo A Isaksson E McConnell J R Ham-ran S-E Bisiaux M M Pasteris D Neumann T A andWinther J-G Variation of accumulation rates over the lasteight centuries on the East Antarctic Plateau derived from vol-canic signals in ice cores J Geophys Res 116 D20103doi1010292011JD015753 2011

Bertler N Mayewski P A Aristarain A Barrett P BecagliS Bernardo R Bo S Xiao C Curran M Qin D DixonD Ferron F Fischer H Frey M Frezzotti M Fundel FGenthon C Gragnani R Hamilton G Handley M HongS Isaksson E Kang J Ren J Kamiyama K KanamoriS Karkas E Karlof L Kaspari S Kreutz K Kurbatov AMeyerson E Ming Y Zhang M Motoyama H MulvaneyR Oerter H Osterberg E Proposito M Pyne A Ruth USimoes J Smith B Sneed S Teinila K Traufetter F UdistiR Virkkula A Watanabe O Williamson B Winther J GLi Y Wolff E Li Z and Zielinski A Snow chemistry acrossAntarctica Ann Glaciol 41 167ndash179 2005

Bisiaux M M Edwards R McConnell J R Curran M A JVan Ommen T D Smith A M Neumann T A Pasteris DR Penner J E and Taylor K Changes in black carbon de-position to Antarctica from two high-resolution ice core recordsAD 1850ndash2000 Atmos Chem Phys accepted 2012

Bowman D M J S Balch J K Artaxo P Bond W J CarlsonJ M Cochrane M A DrsquoAntonio C M DeFries R S DoyleJ C Harrison S P Johnston F H Keeley J E KrawchukM A Kull C A Marston J B Moritz M A Prentice I CRoos C I Scott A C Swetnam T W van der Werf G Rand Pyne S J Fire in the Earth System Science 324 481ndash484doi101126science1163886 2009

Chung C E Ramanathan V Kim D and Podgorny I A Globalanthropogenic aerosol direct forcing derived from satellite andground-based observations J Geophys Res 110 D24207doi1010292005jd006356 2005

Crutzen P J and Andreae M O Biomass burning in the tropicsImpact on atmospheric chemistry and biogeochemical cycles

Atmos Chem Phys 12 3799ndash3808 2012 wwwatmos-chem-physnet1237992012

M M Bisiaux et al Variability of black carbon deposition to the East Antarctic Plateau 3807

Science 250 1669ndash1678doi101126science250498816691990

Dube O P Linking fire and climate interactions with land usevegetation and soil Current Opinion in Environmental Sustain-ability 1 161ndash169 2009

Fischer H Siggaard-Andersen M-L Ruth U Rothlisberger Rand Wolff E Glacialinterglacial changes in mineral dust andsea-salt records in polar ice cores Sources transport and depo-sition Rev Geophys 45 RG1002doi1010292005rg0001922007

Flanner M G Zender C S Randerson J T and RaschP J Present-day climate forcing and response from blackcarbon in snow J Geophys Res-Atmos 112 D11202doi1010292006jd008003 2007

Ghil M Allen M R Dettinger M D Ide K Kondrashov DMann M E Robertson A W Saunders A Tian Y VaradiF and Yiou P Advanced spectral methods for climatic time se-ries Rev Geophys 40 1003doi1010292000rg000092 2002

Gilbert R O 65 Senrsquos Nonparametric Estimator of Slope in Sta-tistical Methods for Environmental Pollution Monitoring JohnWiley and Sons 217ndash219 1987

Isaksson E van den Broeke M Winther J-G Karlof LPinglot J and Gundestrup N Accumulation and proxy-temperature variability in Dronning Maud Land Antarctica de-termined from shallow firn cores Ann Glaciol 29 17ndash22 1999

Ito A and Penner J E Global estimates of biomass burning emis-sions based on satellite imagery for the year 2000 J GeophysRes 109 D14S05doi1010292003jd004423 2004

Jacobson M Z Strong radiative heating due to the mixing stateof black carbon in atmospheric aerosols Nature 409 695ndash6972001

Kaspari S D Schwikowski M Gysel M Flanner M GKang S Hou S and Mayewski P A Recent increasein black carbon concentrations from a Mt Everest ice corespanning 1860ndash2000 AD Geophys Res Lett 38 L04703doi1010292010gl046096 2011

Krawchuk M A and Moritz M A Constraints on global fireactivity vary across a resource gradient Ecology 92 121ndash132doi10189009-18431 2011

Li J Xie S-P Cook E R Huang G DrsquoArrigo R Liu FMa J and Zheng X-T Interdecadal modulation of El Ninoamplitude during the past millennium Nature Climate Change1 114ndash118 2011

Limpert E Stahel W A and Abbt M Log-normal Distributionsacross the Sciences Keys and Clues BioScience 51 341ndash352doi1016410006-3568(2001)051[0341LNDATS]20CO22001

Marlon J R Bartlein P J Carcaillet C Gavin D G Har-rison S P Higuera P E Joos F Power M J and Pren-tice I C Climate and human influences on global biomassburning over the past two millennia Nat Geosci 1 697ndash702doi101038ngeo313 2008

McConnell J R New Directions Historical black carbon andother ice core aerosol records in the Arctic for GCM evaluationAtmos Environ 44 2665ndash2666 2010

McConnell J R Edwards R Kok G L Flanner M G ZenderC S Saltzman E S Banta J R Pasteris D R Carter M Mand Kahl J D W 20th-century industrial black carbon emis-sions altered arctic climate forcing Science 317 1381ndash1384

doi101126science1144856 2007Moosmuller H Chakrabarty R K and Arnott W P Aerosol

light absorption and its measurement A review J Quant Spec-trosc Ra 110 844ndash878 2009

Mouillot F and Field C B Fire history and the global car-bon budget a 1times1 fire history reconstruction for the 20thcentury Glob Change Biol 11 398ndash420doi101111j1365-2486200500920x 2005

Nadaraya E A On Non-Parametric Estimates of Density Func-tions and Regression Curves Theory Probab Appl 10 186ndash190doi1011371110024 1965

Nitschke C R and Innes J L Climatic change and fire potentialin South-Central British Columbia Canada Glob Change Biol14 841ndash855doi101111j1365-2486200701517x 2008

Onoz B and Bayazit M The Power of Statistical Tests for TrendDetection Turkish J Eng Env Sci 27 247ndash251 2003

Paillard D Labeyrie L and Yiou P Macintosh program per-forms time-series analysis Eos Trans AGU 77 379ndash379 1996

Penner J E Zhang S Y Chin M CC Chuang J Feichter YFeng IV Geogdzhayev P Ginoux M Herzog A Higurashi DKoch C Land U Lohmann M Mishchenko T Nakajima GPitari B Soden I Tegen and Stowe L A comparison of model-and satellite-derived aerosol optical depth and reflectivity J At-mos Sci 59 441ndash460 2002

Pomeroy J W Davies T D Jones H G Marsh PPeters N E and Tranter M Transformations of snowchemistry in the boreal forest accumulation and volatiliza-tion Hydrol Process 13 2257ndash2273doi101002(sici)1099-1085(199910)131415lt2257aid-hyp874gt30co2-g 1999

Ramanathan V and Carmichael G Global and regional cli-mate changes due to black carbon Nat Geosci 1 221ndash227doi101038ngeo156 2008

Ramanathan V Crutzen P J Kiehl J T and Rosenfeld D At-mosphere - Aerosols climate and the hydrological cycle Sci-ence 294 2119ndash2124 2001

Schwarz J P Spackman J R Gao R S Watts L A StierP Schulz M Davis S M Wofsy S C and Fahey D WGlobal-scale black carbon profiles observed in the remote at-mosphere and compared to models Geophys Res Lett 37L18812doi1010292010gl044372 2010

Seiler W and Crutzen P J Estimates of gross and net fluxes ofcarbon between the biosphere and the atmosphere from biomassburning Clim Change 2 207ndash247 1980

Skeie R B Berntsen T Myhre G Pedersen C A Strom JGerland S and Ogren J A Black carbon in the atmosphereand snow from pre-industrial times until present Atmos ChemPhys 11 6809ndash6836doi105194acp-11-6809-2011 2011

Sneed S B Mayewski P A and Dixon D A An emerging tech-nique multi-ice-core multi-parameter correlations with Antarc-tic sea-ice extent Ann Glaciol 52 347ndash354 2011

Sodemann H and Stohl A Asymmetries in the moisture ori-gin of Antarctic precipitation Geophys Res Lett 36 L22803doi1010292009gl040242 2009

Stohl A Characteristics of atmospheric transport intothe Arctic troposphere J Geophys Res 111 D11306doi1010292005jd006888 2006

Vautard R and Ghil M Singular spectrum analysis in nonlineardynamics with applications to paleoclimatic time series PhysicaD Nonlinear Phenomena 35 395ndash424 1989

wwwatmos-chem-physnet1237992012 Atmos Chem Phys 12 3799ndash3808 2012

3808 M M Bisiaux et al Variability of black carbon deposition to the East Antarctic Plateau

Wang Z Chappellaz J Park K and Mak J E Large Variationsin Southern Hemisphere Biomass Burning During the Last 650Years Science 330 1663ndash1666doi101126science11972572010

Watson G S Smooth Regression Analysis Sankhya The IndianJournal of Statistics Series A (1961ndash2002) 26 359ndash372 1964

Atmos Chem Phys 12 3799ndash3808 2012 wwwatmos-chem-physnet1237992012