the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 12 May 2020
Refractory black carbon (rBC) variability in a 47-year West Antarctic snow and firn core
Black carbon (BC) is an important climate-forcing agentthat affects snow albedo. In this work, we present a record of refractoryblack carbon (rBC) variability, measured from a 20 m deep snow and firncore drilled in West Antarctica (79∘55′34.6′′ S, 94∘21′13.3′′ W, 2122 m above sea level) during the 2014–2015 austral summer. Thisis the highest elevation rBC record from West Antarctica. The core wasanalyzed using the Single Particle Soot Photometer (SP2) coupled to a CETACMarin-5 nebulizer. Results show a well-defined seasonality with geometricmean concentrations of 0.015 µg L−1 for the wet season(austral summer–fall) and 0.057 µg L−1 for the dry season(austral winter–spring). The core was dated to 47 years (1968–2015) usingrBC seasonality as the main parameter, along with sodium (Na), sulfur (S)and strontium (Sr) variations. The annual rBC concentration geometric meanwas 0.03 µg L−1, the lowest of all rBC cores in Antarcticareferenced in this work, while the annual rBC flux was 6.25 µg m−2 a−1, the lowest flux in West Antarctica rBCrecords. No long-term trend was observed. Snow albedo reductions at the sitedue to BC were simulated using SNICAR online and found to be insignificant(−0.48 %) compared to clean snow. Fire spot inventory and BC emissionestimates from the Southern Hemisphere suggest Australia and SouthernHemisphere South America as the most probable emission sources of BC to thedrilling site, whereas HYSPLIT model particle transport simulations from1968 to 2015 support Australia and New Zealand as rBC sources, with limitedcontributions from South America. Spectral analysis (REDFIT method) of theBC record showed cycles related to the Antarctic Oscillation (AAO) and to ElNiño–Southern Oscillation (ENSO), but cycles in common with the AmundsenSea Low (ASL) were not detected. Correlation of rBC records in Antarcticawith snow accumulation, elevation and distance to the sea suggests rBCtransport to East Antarctica is different from transport to West Antarctica.
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Black carbon (BC) is a carbonaceous aerosol formed during incompletecombustion of biomass and fossil fuels, characterized by strong absorptionof visible light and resistance to chemical transformation(Petzold et al., 2013), and it plays animportant role in the climatic system by being able to alter the planetaryalbedo (McConnell etal., 2007; Ni et al., 2014).
BC-containing aerosols are the species most commonly identified as beingshort-lived climate forcers, along with methane and ozone (AMAP,2015). BC particles stay in the atmosphere for just 1 week to 10 d(Bondet al., 2013; Ni et al., 2014), but during that time they change the directradiative forcing at the top of the atmosphere by absorbing and scatteringsunlight, with high spatial and temporal variability on regional scales(Bondet al., 2013). In some parts of the globe, the impact of BC on the climatecan be even higher than greenhouse gases (Bice et al., 2009).Globally BC is estimated to be second only toCO2 in its contributionto climate forcing, with+1.1 W m−2 for the industrial era(1750–2005)(Bondet al., 2013; Ramanathan and Carmichael, 2008)
Increases in BC concentrations in the cryosphere since the industrialrevolution have been observed, with most studies focusing on the Arctic, theHimalayas and European glaciers as these ice caps are close to large urbancenters and consequently are influenced by these. Antarctica is a pristineenvironment far from the rest of the world, but BC can still be found in itsatmosphere, snow and ice, as shown by early studies(Chýlek et al., 1987, 1992;Warren and Clarke, 1990). Although there are local emissions of BC due toscientific and touristic activities(Caseyet al., 2017; Stohl and Sodemann, 2010), Antarctic ice also records SouthernHemisphere (SH) emissions and long-range transport of BC from low andmidlatitudes(Bisiauxet al., 2012a, b; Pasteris et al., 2014), with BC concentrations inAntarctica being linked to biomass burning from South America, Africa andAustralia(Arienzoet al., 2017; Koch et al., 2007; Stohl and Sodemann, 2010). Even tropicallatitude emissions have a measurable influence on the continent(Fiebig et al., 2009).
Although there are several records of SH paleo-biomass burning, there areonly a few publications on BC variability in ice cores from Antarctica. Someof those are focused on centennial–millennial timescales(Arienzoet al., 2017; Chýlek et al., 1992) and others on annual to decadalscales(Bisiauxet al., 2012a, b; Pasteris et al., 2014). More ice core records areneeded to understand the spatial variability of BC transport and depositionto Antarctica, as well as to improve general circulation models(Bisiaux et al.,2012b). In this work we present a new West Antarctichigh-temporal-resolution rBC snow and firn core record. This record is thehighest West Antarctic rBC record produced to date and contributes to theunderstanding of BC temporal and spatial variability in Antarctica.
The core (TT07) was drilled in the 2014–2015 austral summer on the PineIsland Glacier (West Antarctica) at 79∘55′34.6′′ S, 94∘21′13.3′′ W (elevation 2122 m above sea level – a.s.l.), near the Mount Johnsnunatak (located 70 km NE of the drilling site) (Fig. 1) and close to theInstitute–Pine Island ice divide. The drilling site was chosen due to itsrelatively high accumulation rate, which ensures seasonally preservedstratigraphic resolution (Schwanck et al., 2016b; Thoen et al., 2018), anddue to the region's interesting pattern of atmospheric circulation,originating from the confluence of air masses from the Weddell, Amundsen andBellingshausen seas (Parish and Bromwich, 2007; Thoenet al., 2018).
Figure 1Drilling location for the snow and firn core analyzed in this work(TT07) and other points of interest mentioned in the text. Base map from theQuantarctica project (Matsuoka et al., 2018).
The West Antarctic Ice Sheet (WAIS) has a lower elevation and lower coastalslopes than the East Antarctic Ice Sheet (EAIS), which facilitates theintrusion of moisture-rich cyclones to the interior of the continent and thetransport of aerosols inland (Neff andBertler, 2015; Nicolas and Bromwich, 2011). Katabatic winds are not asstrong in the drilling site region as they are in most of West Antarctica,due to the higher site elevation compared to the surroundings(Parish and Bromwich, 2007). Seasonal differences inatmospheric transport have been reported for the TT07 drilling site, withparticle trajectories during the austral summer being slow moving and morelocally influenced, while, during the winter, air trajectories are influencedby oceanic air masses due to strong westerlies. The majority of air massesarrive from the Amundsen Sea and, secondarily, from across the AntarcticPeninsula and Weddell Sea (Schwanck etal., 2017). These are also the preferred pathway for dust particles(Neff and Bertler, 2015).
We used a Mark III auger (Kovacs Enterprises, Inc.) coupled with anelectrical drive powered by a generator (kept downwind at a minimum of 30 m away) to retrieve the core. The Mark III auger recovers cylinders of7.25 cm diameter and up to 1 m long. All sections of the core wereweighed in the field, packed in polyethylene bags and then stored inhigh-density styrofoam boxes. These boxes were sent by air to Punta Arenas(Chile), then to a deposit in Bangor (ME, US) for storing and finally to theCentral Washington University Ice Core Laboratory (Ellensburg, WA), where they were kept at−1 ∘C in a clean cold room until subsampling andanalysis.
3.1 rBC analytical method
We used an extended-range Single Particle Soot Photometer (SP2, DropletMeasurement Technologies, Boulder, CO, USA) at the Department of GeologicalSciences, Central Washington University (CWU – WA, USA) to analyze oursamples. The particle size range detected by the SP2 at CWU is 80–2000 nmmass-equivalent diameter for the incandescent signal, assuming a void-freeBC density of 1.8 g cm−3(Moteki and Kondo, 2010).
The SP2 measures the number and size of rBC particles using laser-inducedincandescence and was used in a variety of studies for BC in snow and ice(Bisiauxet al., 2012a, b; Casey et al., 2017; Kaspari et al., 2014, 2015, 2011;McConnell et al., 2007; Osmont et al., 2018, 2019). In this work we usethe recommended terminology by Petzoldet al. (2013) and present results from the SP2 as refractory black carbon(rBC).
As the SP2 was initially designed to analyze rBC from the atmosphere (dryaerosol), a necessary step to run liquid samples is their nebulizationbefore being coupled to the sample inlet of the SP2. For this, we used aCETAC Marin-5, described in detail by Mori et al. (2016).The authors found a good nebulizing efficiency of50.0±4.4 % andno size dependency in the diameter range of 200–2000 nm.Katich et al. (2017) managed to obtainnebulization efficiencies near 100 % with their equipment setup. Wecalculated the CWU Marin-5 nebulization efficiency to be68.3±5.9 % (1σ) based on the external calibration carried out everyworking day using Aquadag standards (Marquetto et al., 2020).We found a decrease in nebulization efficiency during the laboratory workperiod (−0.31 % per working day or−13.3 % over the 43 working days),but we assume the nebulization efficiency to remain stable between themeasurement of the standard and the samples measured for the day, followingKatich et al. (2017). We attributethis decrease to the Marin-5 but do not see any apparent cause. Liquid pumpflow rates were kept constant at0.14±0.02 mL min−1 duringanalysis.
For details of the CWU SP2 internal and external calibration, refer toMarquetto et al. (2020).
3.2 Laboratory and vial cleaning
Regular intensive cleaning was carried out inside the cold room for allsurfaces, parts and equipment in contact with the core using ethanol andlaboratory-grade paper tissues. Tyvek suits (DuPont, Wilmington, DE, USA)and sterile plastic gloves were used at all times in the cold room duringthe core processing.
Vials used to store the samples (50 mL polypropylene vials) were soaked inMilli-Q water for 24 h and rinsed three times. This process was repeatedtwo more times, in a total of 3 d with the samples soaked in Milli-Q water and rinsed a total of nine times. The vials were left to dry, covered from direct contact, in thelaboratory.
3.3 Sample preparation
The sample preparation process consists of removing the outer layers of thecore, as these are prone to contamination during drilling, handling andtransport of the core (Tao et al.,2001). In the cold room, we partitioned the 21 sections of the corelongitudinally, using a bandsaw with a meat-grade, stainless-steelblade. For every cutting session, a Milli-Q (MQ) ice stick, previouslyprepared, was cut at the beginning, to guarantee a clean blade for the snowand firn core. After cutting the core with the bandsaw, we hand-scraped theresulting snow and firn sticks with a ceramic knife in a laminar flow hood(still in the cold room) and cut them in 2–2.5 cm samples with the sameknife (resulting in∼40 samples per section). We stored thesamples in the pre-cleaned 50 mL polypropylene vials and kept them frozenuntil analysis. Samples were melted at room temperature or in a tepid bathnot exceeding 25 ∘C, sonicated for 15 min and then analyzed (inless than 1 h after melting). The resulting rBC concentrations using thissubsampling method were compared to subsampling using a continuous meltersystem for the first 8 m of the core, and results for both methods werestatistically the same (Marquetto et al., 2020).
From all steps of the sample preparation, the bandsaw cutting in the coldroom proved to be the most prone to contaminating samples. An intensivedecontamination process was carried out for a month, before we couldstart working with the core itself. In order to reach acceptable backgroundlevels for this step (around 0.02 µg L−1), we replaced andmodified some components of the bandsaw. We replaced the rubber tires forurethane ones; the carbon blade for a meat-grade, stainless-steel blade; and theoriginal plastic blade guides for ceramic ones, and we manufactured an acrylicblade guard, as the original plastic guard was chipping. Before using thenew blade, we burned it using a blowtorch and MAP/Pro gas (propylene with<0.5 % propane) to remove any residues or oils present; then we cleanedit with ethanol. For detachable parts, a detergent was used, followed byethanol and MQ water. For parts inside the cold room, ethanol was used. Wealso prepared ice sticks of MQ water to cut in the bandsaw and help cleanthe blade.
3.4 Whole-system setup
The setup for the system in use at CWU is as it follows. The melted sampleis dispensed to the Marin-5 nebulizer by a Reglo Digital peristaltic pump(ISMATEC, Wertheim, Germany) at0.14±0.02 mL min−1 andmonitored by a TruFlo sample monitor (Glass Expansion, Port Melbourne,Australia). The Marin-5 nebulizer receives standard laboratory air at 1000 sccm (1000 L min−1), regulated by an Alicat flow controller (AlicatScientific, Tucson, AZ, USA) connected to a Drierite gas purifier, whichremoves any moisture or particulates from the air. The nebulizer heating andcooling temperatures are set to 110 and 5 ∘C,respectively, following Mori et al. (2016). We used TygonLFL tubing i.d. 1.02 mm (Saint-Gobain Performance Plastics, France) for sample-to-nebulizer connection. The SP2 flow is maintained at 120 volumetric cm3 min−1 (vccm). YAG laser power for this projectstayed constant above 5.0 V.
Samples were analyzed for 5 min each. Procedural blanks (MQ water) wererun at the beginning and end of every working day and also every 15–20 samples. Background levels were kept at 0–0.5 particles cm−3(translating to less than 0.01 µg L−1 rBC concentration), and a5 % HNO3 solution was used for cleaning the tubing and nebulizer whenneeded. For the SP2 to go back to background levels, only MQ water was used.Peristaltic pump tubing replacement was necessary only once during theprocess. The limit of detection (LOD) of the method was estimated to be1.61×10–3 µg L−1 based on procedural blanks measured tocharacterize the instrument detection limit (mean+3σ,n=30).
Data processing was performed with the SP2 Toolkit 4.200 developed by theLaboratory of Atmospheric Chemistry at the Paul Scherrer Institute (PSI) and wasused on the scientific data analysis software IGOR Pro version 6.3.
3.5 Fire spots and BC emission database
To help define the dating of the core and to investigate potential emissionsource regions, we compared our results with two different datasets: BCemission estimates from the Global Fire Emission Database version 4s (GFED4s– vanDer Werf et al., 2017) for the SH (SH South America, SH Africa, Australiaand Equatorial Asia) and the Australian and Brazilian satellite programs,which count the fire spots (number of active fires) in Oceania and SouthAmerica, respectively.
The GFED4s (https://www.globalfiredata.org/data.html, last access: 13 June 2019) is based on theCarnegie Ames Stanford Approach biogeochemical model(Giglio et al.,2013) and has several improvements compared with the earlier version,including burned area and emissions from small fires as these could besubstantial at a global scale(Randerson et al.,2012). BC emission estimates are given in 109 g and separated by regionof the globe with a spatial resolution of 0.25∘ latitude by 0.25∘ longitude. For the Southern Hemisphere, four regions are identified:Southern Hemisphere Africa (SHAF), Southern Hemisphere South America (SHSA),Australia and New Zealand (AUS), and equatorial Asia (EQAS).
Sentinel Hotspots(https://www.ga.gov.au/scientific-topics/earth-obs/case-studies/mapping-bushfires, last access: 13 June 2019)and the Programa Queimadas (http://www.inpe.br/queimadas/, last access: 13 June 2019) are firemonitoring programs run by the government of Australia (GeoscienceAustralia) and Brazil (Instituto Nacional de Pesquisas Espaciais – INPE),respectively. Both programs use Moderate Resolution ImagingSpectroradiometer (MODIS), Advanced Very High-Resolution Radiometer (AVHRR)and Visible Infrared Radiometer Suite (VIIRS) sensors to detect areas ofelevated infrared radiation. The Sentinel Hotspots holds data from 2002 topresent, while Programa Queimadas has a record of fire spots since 1998.The parameter “fire spot” used in both Australian and Brazilian firemonitoring programs does not translate directly to the dimension and intensityof the biomass burning events, but it holds a correlation with burned area(Andela et al., 2017) andthus can be used to help date the core and investigate potential emissionsources.
3.6 Core dating
Antarctic ice core rBC records from other sites show a well-definedseasonality, with peak concentrations in austral winter–spring (dry season)due to increased biomass burning activity in the SH during this time of theyear(Bisiauxet al., 2012b; Pasteris et al., 2014; Sand et al., 2017; Winstrup et al.,2019). Sodium (Na) and strontium (Sr) also peak in the austral dry season(during winter) due to intense atmospheric circulation and transport(Legrandand Mayewski, 1997; Schwanck et al., 2017). Increased marine biogenicactivity reflects an increase in sulfur (S) in late austral summer(Schwancket al., 2017; Sigl et al., 2016). Also, the maxima in the ratio of non-sea-saltsulfur to sodium (nssS ∕ Na) is a robust seasonal indicator and peaksaround the New Year (Arienzo et al., 2017). This parameter helps in theidentification of the annual layers more than the Na and S records alone.Non-sea-salt sulfur was calculated using Eqs. (3) to (6) from Schwanck et al. (2017) and references therein.
The core was dated by multiparameter manual layer counting primarily drivenby rBC seasonal variability, as this is a reliable parameter for dating inAntarctica(Siglet al., 2016; Winstrup et al., 2019), and a well-defined seasonality hasalready been observed for Pine Island Glacier (Pasteris etal., 2014). We used S, Sr, Na and nssS ∕ Na records from a core drilled 1 m away as additional parameters to the main counting. The trace elementrecords goes down only to∼6.5 m, so below 6.5 m the ice coreis dated using the rBC record. The trace elements were analyzed by the Climate Change Institute (CCI)Thermo Scientific ELEMENT 2 inductively coupled plasma sector field mass spectrometer (ICP-SFMS) coupled to an ESI model SC-4autosampler; working conditions and measurement parameters are described inSchwanck et al. (2016b, 2017).
We considered the New Year to match the end of what we define as the australdry season, as this is a reliable tie point in the record due to the abruptdrop in rBC concentrations. Previous studies have demonstrated that rBCdeposition occurs in winter–spring, mostly September to December. Forexample, Arienzo et al. (2017) observed rBC concentrations to peak inSeptember in the WAIS Divide ice core; Winstrup et al. (2019) used annualvariations in rBC as the most reliable annual tracer for the RooseveltIsland Climate Evolution (RICE) ice core, stating that rBC tends to peakearlier in the year than 1 January. Pasteris et al. (2014) alsocorroborates rBC to peak in October and drop after for the Pine Island andThwaites glaciers, with the lowest values from February to June. Bisiaux et al. (2012b) state that subannual rBC concentrations are highly seasonal in theWAIS Divide ice core for the period spanning 1850–2000 – low austral wetseason and high austral dry season concentrations – and presented annualpicks in the drop in rBC concentrations, as in this work. This is alsoconsistent with the BC emission estimates from GFED4s and the fire spotdatabases from Australia and South America.
3.7 Snow accumulation, rBC concentrations and fluxes
To account for imperfections in the core geometry (and consequentlyimprecise density measurements), we averaged the core's density profile withthe density profile from Schwanck et al. (2016b) for a 45 m deep core drilled in the same region of West Antarctica,850 m away from TT07. We then fitted a quadratic trend line in the averagecurve and used this trend line instead of the field measurements tocalculate the annual snow accumulation, water equivalent (w.e.) and rBCfluxes. rBC fluxes were calculated by multiplying annual rBC means by annualsnow accumulation.
We consider that the frequency distributions of the core rBC concentrationsare lognormal, and so we present geometric means and geometric standarddeviations as these are more appropriate than arithmetic calculations(Bisiauxet al., 2012a; Limpert et al., 2001). The geometric standard deviation isthe multiplicative standard deviation (σ*), so the 68.3 % intervalof confidence is calculated asσ minconc= geometric mean × geometric standard deviation andσ maxconc= geometric mean/geometric standard deviation(Limpert et al., 2001). Also,correlation analysis was carried out using Mann–Kendall's test; we choose itas opposed to Spearman's test as confidence intervals are more reliable inthe former (Kendall and Gibbons, 1990; Newson, 2002).
We present our data as austral summer–fall (wet season: January to June)concentrations and austral winter–spring (dry season: July to December)concentrations. Wet–dry season concentrations and annual concentrationgeometric means and standard deviations were calculated in the raw rBCmeasurements using the dating carried out to separate years and rBCconcentration variations to pinpoint the changes from dry season to wetseason and vice versa. Monthly mean concentrations were calculated byapplying a linear interpolation in the raw measurements, resampling thedataset to 12 values per year.
3.8 rBC impact on snow albedo
To investigate BC impact on snow albedo, we used the Snow, Ice, and AerosolRadiation (SNICAR) online model(Flanner etal., 2007). We ran the model using the parameters presented in Table 1 withvarying rBC concentrations. We used the wet and dry season geomeans toanalyze variations for both seasons and the highest seasonal geomean foundin the core, which occurred in the dry season. As our focus in this paper isBC, we simulated albedo changes considering only the particulate anddisregarding any dust or volcanic ash influence. Snow grain size used was basedon Gay et al. (2002).
Table 1Parameters used to calculate albedo changes in snow for the TT07site.
3.9 Spectral analysis
In order to investigate periodic oscillations (cycles) in the TT07 core andBC atmospheric transport to the drilling site, we conducted a spectralanalysis in the rBC record using the REDFIT procedure described in detail inSchulz and Mudelsee (2002) in the “PAST –Paleontological Statistics” software version 3.25. The spectral analysis ismotivated by the observation that the most predictable (regular) behavior ofa time series is to be periodic (Ghil et al.,2002). The REDFIT method is a more advanced version of the simple Lombperiodogram and can be used for evenly and unevenly sampled data. The modelis fit to an AR(1) red noise model, the bandwidth is the spectral resolutiongiven as the width between the−6 dB points, and confidence levels of 90 %, 95 %and 99 % are presented (based on chi2) (Hammer, 2019).
We chose this approach instead of estimation techniques for evenly spaceddata (such as the multitaper method) because interpolation in the timedomain inevitably causes bias and alters the estimated spectrum of a timeseries (Schulz and Mudelsee, 2002). This way, weused the rBC raw measurements (not resampled, only dated by year andseparated by dry–wet season).
We compared the rBC spectrum with the El Niño–Southern Oscillation(ENSO), the Antarctic Oscillation (AAO) and the Amundsen Sea Low (ASL)spectra to observe the possible influence of these in the rBC variability. WhileENSO and AAO are well-known climate drivers, recent studies have shown theASL has a profound effect on the West Antarctic climate(Hoskinget al., 2013, 2016; Turner et al., 2013). We also compared the core recordswith the GFED4s BC emission estimates and the satellite fire spot databaseto look for similarities between the datasets which could suggest BCemission sources to the drilling site. Table 2 shows the dataset used forthe spectral analysis.
Table 2Datasets used for the REDFIT spectral analysis.
a Not resampled, only dated by year and separated by dry–wet season.b Here we use the Southern Oscillation index – SOI as the ENSOindicator.c http://www.bom.gov.au/climate/current/soihtm1.shtml, last access: 15 June 2019.d https://www.cpc.ncep.noaa.gov/products/precip/CWlink/, last access: 15 June 2019.e https://legacy.bas.ac.uk/data/absl/, last access: 15 June 2019.
3.10 Particle trajectory simulations
In order to simulate rBC particle trajectories from source areas to the TT07drilling site, we used the Hybrid Single Particle Lagrangian IntegratedTrajectory v4 model (HYSPLIT– Draxler andRolph, 2003; Stein et al., 2015), from NOAA. HYSPLIT is a complete systemfor computing simple or complex transport and deposition simulations(Stein et al., 2015) that has beenused in Antarctica for several studies(Dixonet al., 2011; Markle et al., 2012; Marquetto et al., 2015; Schwanck et al.,2016a, 2017; Sinclair et al., 2010).
We used global reanalysis data from the National Centers for EnvironmentalPrediction (NCEP) and the National Center for Atmospheric Research (NCAR) –the NCEP/NCAR dataset – and ran 10 d (240 h) back trajectories, every 5 d, from 1968 to 2015, at an initial height of 1000 m. We consider 10 dto be an appropriate simulation time as this is the estimated maximumlifetime of BC in the troposphere (IPCC et al.,2013). An initial height of 1000 m was used in order to minimize disturbancefrom the underlying terrain, but still maintaining a link with the surfacewind field (Sinclair et al., 2010). Toidentify main airflow patterns at the TT07 drilling site, the individualtrajectories were separated into dry and wet seasons (depending on day andmonth of each run) and simulations from each season were grouped into fiveclusters using the HYSPLIT model's cluster analysis algorithm.
4.1 Dating
The core was dated to 47 years (1968–2015), and details are presented inFig. 2. We consider this dating to have±2 years uncertainty. Thefirst uncertain year is located at 6.18 m (between 2003 and 2002, Fig. 2a), where S and nssS ∕ Na peak, but no full cycle is observed in the rBCrecord. We did not consider this to be a year, as rBC does not present afull cycle. The second uncertain year is located at 18.14 m (year 1973,Fig. 2b) where there is no clear rBC peak but snow accumulation would beanomalously high if considered to be only 1 year instead of 2. We considerthis to be an annual peak and consequently 2 years, as there is noevidence of higher-than-normal snow accumulation in the region for thisperiod (Kaspari et al., 2004).
Figure 2(a) Dating of the snow and firn core based on rBC andusing S, Sr, Na and nssS ∕ Na records from a nearby core (see Sect. 3.6) assupport for the first 6.5 m. Dashed lines indicate the estimated New Year,and the red dotted line indicates uncertainty in dating, explained in the text.(b) Dating for the full core (y axis is logarithmic). The red dotted line indicatesuncertainty in dating, as explained in the text.
4.2 Core density and annual snow accumulation
The core density (measured in the field) ranged from 0.38 to 0.60 g cm−3. Using the corrected density curve obtained from our fieldmeasurements and from Schwanck et al. (2016b),we calculated that the 20.16 m length core represents 10.37 w.e. m (Fig. 3).
Average annual snow accumulation is0.21±0.04 w.e. m per year andvaries little throughout the record, with an exception of a peak inaccumulation of 0.31 w.e. m in 1971. The average accumulation is similar towhat Banta et al. (2008)found for the WAIS Divide ice core for the last centuries (0.20±0.03 w.e. m yr−1, elevation 1759 m a.s.l.) and to the higher altitude cores(>1700 m a.s.l.) from Kaspariet al. (2004) (0.18 to 0.23 w.e. m yr−1); although the latter workalso presents lower altitude cores (1200 to 1600 m a.s.l.) closer to thedrilling site with accumulation rates between 0.32 and 0.42 w.e. m yr−1.
Figure 3TT07 density profile (blue). Depth is presented in meters andwater equivalent (w.e.) meters. The quadratic fit was calculated from theaverage density profile (black) from this work and fromSchwanck et al. (2016b).
4.3 rBC concentrations and fluxes
In agreement with other studies(Bisiauxet al., 2012a; Pasteris et al., 2014; Sand et al., 2017; Winstrup et al.,2019), we found a well-marked seasonal rBC cycle along the core, with thesame pattern of low summer–fall and high winter–spring concentrations (Fig. 4). As we collected our samples in January and the drilling was carried outfrom the snow surface, our core starts at approximately the 2015 New Year.The core's annual rBC geometric mean concentration was 0.030 µg L−1 with a minimum of 0.001 µg L−1 and a maximum of 0.080 µg L−1. Winter–spring (dry season) concentration geometric meanwas 0.057 µg L−1, while summer–fall (wet season) concentrationgeometric mean was 0.001 µg L−1. Wet season averageconcentrations remained constant over time, while dry season averageconcentrations showed more variation with peak values in 1999 but noapparent trend. The main results from TT07 rBC analysis are summarized inTable 3.
Table 3Main results from the core rBC analysis. All values in micrograms per liter, except fluxes, which are in micrograms per square meter per year. Geomean is the geometric mean and1σ* is the multiplicative standard deviation,representing 68.3 % of the variability(Bisiauxet al., 2012b; Limpert et al., 2001).
Figure 4(a) rBC concentrations for the entire core. The thick black linerepresents annual averages, while the gray line represents monthly values.Note they-axis scale is logarithmic.(b) Dry season and wet seasonaverage concentrations per year.
We calculated annual rBC fluxes to account for potential biases in annualrBC concentrations due to changes in snow accumulation rates. Concentrationsand fluxes follow a similar pattern along the core, as can be observed inFig. 5. This means that rBC concentration variability likely reflectsvariations in BC emissions, transport and deposition at the site instead ofreflecting changes in snow accumulation.
4.4 Comparison with other rBC records in Antarctica
BC has been studied in Antarctic snow since the late 1980s and early 1990s(Chýlek et al., 1987, 1992;Warren and Clarke, 1990). These initial studies used filter-based methods,which could under- or overestimate BC concentrations due to some analyticalartifacts(Soto-Garcíaet al., 2011; Torres et al., 2014; Wang et al., 2012). Studies using the SP2started appearing more than 2 decades later, aiming at recent snow rBCconcentrations(Caseyet al., 2017; Khan et al., 2019), near-surface air(Khan et al., 2018),recent-past ice cores (couple centuries –Bisiauxet al., 2012a, b; Pasteris et al., 2014) and the past millennia(Arienzo et al., 2017).From these, a few rBC records overlap temporally with the TT07 corepresented in this work (Table 4). rBC concentrations are low at all sites(<0.5 µg L−1); thus small differences in concentrationfrom one core to another could result in a 2–3-fold difference in rBCconcentrations.
Table 4Coordinates, elevation, period covered and rBC information for thisstudy and previous studies in Antarctica with time overlap with this study.We show only studies that used the SP2 in snow and ice to have a directcomparison between them.
a Multiplicative standard deviation representing 95.5 % of the interval of confidence.b From Criscitiello et al. (2014).c Core goes back to∼1800, and we present only from 1963 on to have time overlap between these and this study.d Not annual.e From Mosley-Thompson et al. (1999).f From Witherow and Lyons (2008).
Pasteris et al. (2014) present rBC records from three high-accumulation West Antarctic ice cores: Pine Island Glacier, ThwaitesGlacier and the divide between the two sites (220, 750 and 370 kmapart from TT07 core, respectively). The cores presented annual rBCconcentrations of 0.22 (Pine Island), 0.21 (Thwaites) and 0.20 µg L−1 (Divide). The lower-altitude cores (DIV2010 – 1329 m a.s.l. and PIG2010 – 1593 m a.s.l.)presented almost 1.5 times more snow accumulation than the higher-altitudecore (THW2010 – 2020 m a.s.l.) and almost 2 times more than TT07. The meanannual rBC concentrations from Pasteris et al. (2014) arealmost 6 times higher than the rBC annual values observed in TT07. HigherrBC concentrations in Pasteris et al. (2014) could be aresult of higher accumulation rates, considering that BC is primarilydeposited through wet deposition(Flanner etal., 2007). This is discussed later on in this section.
The WAIS Divide rBC record fromBisiaux et al. (2012a)is located 350 km away from TT07, has similar accumulation rates to TT07and rBC annual concentration 2.7 times higher than annual values from TT07(0.08 µg L−1 at WAIS and 0.03 µg L−1 at TT07). Theauthors observed a steep increase in rBC concentrations in the WAIS corefrom 1970 to 2001 (∼0.06 to∼0.11 µg L−1) and related this to an increase infossil fuel consumption and deforestation in the SH. This increasing trendwas not observed in the TT07 core, which showed fairly stable annualconcentrations and fluxes through time. Although the WAIS Divide core islocated almost at the same distance from TT07 as DIV2010, and farther thanPIG2010, its snow accumulation rates and rBC annual concentrations are moresimilar to TT07 than the cores from Pasteris et al. (2014).
The South Pole samples (1120 km from TT07) fromCasey et al. (2017) were collected in early austral summer, possibly still reflecting theSH dry season. They present even higher rBC concentrations thanPasteris et al. (2014), although the samples werecollected close to the Amundsen–Scott scientific station, and even the“clean air sector” can present local influence, particularly in comparisonto the TT07 remote site.
Khan et al. (2018)found rBC concentrations on the same order of magnitude asCasey et al. (2017), although the Dry Valleys collection site fromKhan et al. (2018)was far from local interference of scientific station activities. The coresfrom Bisiauxet al. (2012b) (East Antarctica) present the highest elevations from thecited bibliography and show similar rBC fluxes compared to TT07, althoughthese fluxes are a result of high rBC concentrations with low accumulationrates in East Antarctica, while the TT07 fluxes are the opposite – highaccumulation rates (similar to the WAIS Divide core) with low rBCconcentrations.
Figure 6rBC records from Antarctica. rBC concentrations plottedagainst snow accumulation, elevation and distance from the sea. Solid linesindicate statistically significant correlations (p<0.05), whiledashed lines indicate not significant correlations (p>0.05).
Figure 6 shows a comparison of the abovementioned rBC records with snowaccumulation, elevation and distance from the open sea. Distance from the seainfluences rBC fluxes in West Antarctica(Arienzo et al., 2017) andwas calculated considering the median sea ice extent from 1981 to 2010 forSeptember (Matsuoka et al., 2018), when rBC emissions startto rise in South America–Australia–New Zealand and rBC concentrations beginto rise in West Antarctica(Arienzoet al., 2017; Bisiaux et al., 2012b; Pasteris et al., 2014). We measured thedistance from the rBC records to the closest open sea source (Amundsen Seafor West Antarctic records, Lazarev to Cosmonauts seas for NUS0X-X, and MawsonSea for Law Dome). We acknowledge this is a simplistic approximation andthat the preferred air mass pathways from the sea to the points are not asstraightforward, but for the scope of this work we consider thisapproximation sufficient.
No patterns are clear for both East and West Antarctica, whereas whenconsidering the data from East and West Antarctica separately, oppositetrends are observed. In East Antarctica, rBC concentrations have a negativecorrelation with snow accumulation and positive correlation with elevationand distance to the sea, whereas in West Antarctica rBC concentrationspresent a positive correlation with snow accumulation and a negativecorrelation with elevation and distance to the sea. We observed that forEast Antarctica, rBC vs. snow accumulation and rBC vs. elevation presentedstatistically significant correlations (r2=0.78,p<0.01 for the former andr2=0.79,p<0.01 for the latter). On the other hand, distance from the sea is notsignificantly correlated with rBC (r2=0.52,p=0.06).
For West Antarctica, relationships are the opposite: positive correlationbetween rBC concentrations and snow accumulation (r2=0.69,p=0.08) and negative correlations between rBC concentrations andelevation and distance from the sea (r2=0.30,p=0.33 forthe former andr2=0.79,p<0.05 for the latter).Only the correlation between rBC vs. distance from the sea, though, isstatistically significant. McMurdo and South Pole points are not consideredin this calculation as they likely reflect local contamination instead oflong-range transport(Caseyet al., 2017; Khan et al., 2018).Bisiaux etal. (2012b) have also observed negative (positive) relationships between rBCconcentrations and snow accumulation (elevation) for East Antarctica,although their comparison also included the WAIS Divide point in thedataset.
These opposite trends may indicate differences in rBC transport to East andWest Antarctica. While for East Antarctica upper-tropospheric transport anddry deposition may be the main controllers of rBC concentrations(Bisiaux et al.,2012b), for West Antarctica rBC concentrations may be modulated by intrusionof air masses from the marine boundary layer. Low elevations in WestAntarctica facilitates the intrusion of moisture-rich cyclones and thetransport of aerosols inland (Neff andBertler, 2015; Nicolas and Bromwich, 2011), while the positive relationshipbetween West Antarctica rBC concentrations and snow accumulation mayindicate rBC to be primarily deposited through wet deposition, beingscavenged along the coastal regions where snow accumulation is higher.
4.5 BC impact on snow albedo
To investigate BC impact on snow albedo we used SNICAR online to simulatethree scenarios with the same parameters but varying rBC concentrations. Weran the model using the wet and dry season geomeans and the highest seasonalgeomean (0.015, 0.057 and 0.105 µg L−1, respectively). Resultsshow that snow albedo reduction at the TT07 site due to BC is very low tononexistent (Table 5). This was already expected considering (observed)albedo reported byCasey et al. (2017). Although significant albedo reductions have been reported in morecontaminated zones near the South Pole Station, the authors found a minor tonegligible reduction in albedo for the “clean sector” snow.
Table 5Albedo changes due to rBC concentrations at the TT07 site (fromSNICAR online).
We note that this albedo reduction occurs only in the austral summer, as thesite is located almost at 80∘ S.
4.6 Emission sources and influence of transport on the record
Variability in ice core records reflects variability in BC emissions,atmospheric transport and deposition(Bisiaux et al., 2012a). AsBC stays in the atmosphere for a short period of time (7 to 10 d;IPCC et al., 2013), increases in BCemissions would rapidly reflect increases in BC concentrations in snow, andthus comparing the seasonality of the two records may help to elucidatesource regions. To this end, we compared BC monthly emissions in the SH(from the GFED4s model) with monthly rBC values from the TT07 record (Fig. 7a). The BC seasonality at TT07, with increasing concentrations in July, apeak in October and minimum values in April–May, is the same as reported forthe nearby Pine Island Glacier (Pasteris et al., 2014;Fig. 1), indicating that comparing the TT07 seasonality to regionalemissions is valid.
Figure 7(a) TT07 rBC (monthly averages, 1968–2014) and BC emissionsestimated from GFED4s for the four SH regions (normalized, 1997–2014). Theshaded area represents 1 geometric standard deviation of monthly rBC values.(b) Absolute BC emissions estimated from GFED4s for the SH.
Some models indicate that the carbonaceous load in the Antarctic tropospheremainly originates from South American emissions(Koch et al., 2007); othersrecognize both South America and Australia as the main sources(Stohl and Sodemann, 2010). Althoughsouthern Africa has the largest BC emissions in the SH, it is not consideredto be a significant contributor to the aerosol load in Antarctica(Liet al., 2008; Neff and Bertler, 2015; Stohl and Sodemann, 2010). BothAustralia (Bisiaux et al.,2012a) and South America(Arienzo et al., 2017) havebeen suggested as sources of BC to West Antarctica.
Figure 7a shows the rBC monthly-average values for TT07 (1968–2014) andmonthly-averaged BC emissions from GFED4s (1997–2015) for the four SHemission regions (regions defined in GFED4s; see website). rBC in the TT07starts increasing considerably in July, peaks in October and shows high butdecreasing concentrations until December.
African emissions increase and decrease earlier in the year compared withother SH emission sources and with the TT07 BC record (Kendall's tau = 0.30,p=0.17,n=12). Equatorial Asia BC emissions increase inAugust and peak in September, not reflecting the initial rBC increase inTT07 record (Kendall's tau = 0.33,p=0.13,n=12). The increasingtrend matches South American emissions, as they start rising in the sameperiod, although peaking in September and dropping significantly after(Kendall's tau = 0.66,p<0.01,n=12). At last, Australia andNew Zealand emit much less BC than the other three regions (Fig. 7b) butatmospheric circulation favors aerosol transport from there to WestAntarctica (Li et al., 2008;Neff and Bertler, 2015). Australian and New Zealand emissions startincreasing in August and peak in October, falling later than the otherregions (December) (Kendall's tau = 0.85,p<0.01,n=12). Thecorrelation coefficients then indicate Australia–New Zealand as the mostprobable source region for BC at the site for the period studied, followedby SH South America. SH Africa and Equatorial Asia present much weakercorrelations, which likely indicates these two regions do not contributesubstantially to the rBC flux to the TT07 site. This is consistent withprevious research(Arienzoet al., 2017; Bisiaux et al., 2012a).
There is a small increase in Australian emissions earlier in the year (May)that is not observed in the TT07 rBC monthly averages. This difference couldbe associated with the seasonal difference in particulate transport toAntarctica in winter–summer(Haraet al., 2008; Schwanck et al., 2017; Stohl and Sodemann, 2010).
4.7 Spectral analysis
We further investigated the possible emission sources and transportinfluences to the site using the REDFIT spectral analysis. We compared therBC record with ENSO, AAO and ASL indexes (Fig. 8). This investigation wouldgive information about the effect of local to regional changes inatmospheric circulation on the BC records(Bisiaux et al., 2012a).
Figure 8Spectral analysis of the rBC concentrations and comparison withexisting datasets (Sentinel Hotspots Australia, ASL, AAO and ENSO indexes).Numbers in bold indicate cycle frequency, in years. Red lines are confidenceintervals 99 %(a, b), 95 %(c, d) and 90 % (e). The green lineindicates the AR1 red-noise background. The question mark in the Australian firespot spectrum indicates a longer unidentified cycle.
The TT07 rBC spectrum showed significant cycles in the 6-year band (AR1confidence interval, CI>90 %) and in the 2-year band (AR1 CI∼90 %). Intra-annual cycles in the 0.6 and 0.5 frequencieswere also observed at a 95 % confidence interval. Comparing the TT07 rBCrecord spectrum with the GFED4s and fire spot spectra, we identifiedsimilar periodicities only in the Sentinel Hotspots (Australia) record (Fig. 8), more specifically in the 2-year band (AR1 CI∼90 %)and in the 0.6-year band (AR1 CI >90 %). All other spectra(including Programa Queimadas satellite data) showed only well-marked annualperiodicities and intra-annual periodicities of two and three cycles per year (0.5-and 0.3-year bands, not shown). We consider some of these intra-annualcycles questionable, as the high-frequency end of the spectrum is oftenoverestimated and can present aliases, “folded signals”, of another frequencyprocess (Mudelsee, 2010; Schulz and Mudelsee,2002), in this case aliases of the annual cycle at the 0.5- and 0.3-yearbands. Due to this, we do not consider 0.5- and 0.3-year cycles to berepresentative.
rBC and AAO present similar cycles (2.1- and 0.6-year bands), as well as rBCand ENSO (2-year band).
Using the multitaper method,Bisiaux et al. (2012a)observed the rBC periodicities for the WAIS Divide ice core and Law Dome(both dated to 1850–2001). Although WAIS is closer to the TT07 drilling site(∼350 km), the TT07 core presented similarities with the LawDome spectrum (in the 6- and 2-year bands, not shown). It is not clear to uswhat the relation between the two sites could be, as the TT07 site location,annual accumulation and site elevation are more related to the WAIS ice corethan to Law Dome (Table 4).Arienzo et al. (2017)used the multitaper method to analyze the WAIS Divide rBC flux for theperiod spanning 14–6 kyr BP and found a 6.6-year cycle (AR1 CI = 95 %) and a 2.3-year cycle (AR1 CI >95 %), similar to therBC cycles found in this work; although timescales and methodology usedwere different. BothArienzoet al. (2017) and Bisiaux et al. (2012a) attribute the 2.3-year cycle to anindirect effect of the Quasi-Biennial Oscillation (QBO). Although the QBOcirculation spans the Equator to∼30∘,QBO-generated variability can affect Antarctica(Strahan et al., 2015), in which case an upper-troposphere–stratospheric component may be important for BC transport to thecontinent.
In summary, the spectral analysis suggests Australia and New Zealand as themost probable sources of rBC to the drilling site. Also, rBC seems to berelated to the AAO (0.6- and 2-year cycle) and to ENSO (2-year cycle) but not toASL, and similarities between rBC cycles at the TT07 site and the WAISDivide site have been observed.
4.8 Particle trajectory simulations using HYSPLIT
We simulated particle transport during the austral wet and dry seasons asanother mean of addressing rBC source areas. We ran the HYSPLITback-trajectory model every 5 d from 1968 to 2015, for 10 d each(estimated maximum BC lifetime in the troposphere) and clustered the resultsin five groups for the wet and dry seasons (Fig. 9).
Figure 9HYSPLIT clusters of 10 d back trajectories run every 5 d from 1968 to 2015 arriving at the TT07 drilling site. Results areseparated by wet and dry seasons and grouped in five clusters (percentage oftrajectories for each cluster is shown in parentheses). Number oftrajectories (n) used for the cluster algorithm is shown at the top, on theleft side.
Figure 10Individual trajectories used for the cluster analysis inFig. 8. Number of trajectories (n) used for each cluster is shown at thetop, on the left side. Clusters 1, 2 and 4 show air masses arriving fromAustralia and New Zealand to the TT07 drilling site, while clusters 2, 3 and4 show the (limited) contribution of South American air parcels to the site.Similar clusters from the wet and dry seasons are side by side for comparison.The wet season presented 76 ungrouped trajectories, while the dry season presentednone.
A significant part of the simulated air parcels arriving at the drillingsite (50 % in the wet season and 57 % in the dry season) presented aslow-moving trajectory (speed is proportional to trajectory length),reflecting a local and/or regional influence more than long-range transport fromother continents (clusters 3 and 4 in Fig. 9). This local and/or regionalinfluence is observed in both the wet and dry seasons, although during theformer the contribution of air masses from the Antarctic Peninsula andacross the Weddell Sea is higher than during the latter. A fast-moving,year-round continental group is also present (cluster 5) and may partlyrepresent katabatic winds flowing from the continent's higher altitudes(East Antarctica) towards lower-altitude West Antarctica. The strongestcontribution of long-range air parcels is from the South Pacific (clusters 1and 2). These air masses are also fast-moving and present slight seasonalvariations, shifting poleward during the wet season, when they represent34 % of all air parcels, and away from Antarctica during the dry season,when they respond for 22 % of all air parcels modeled.
Results from clusters 1 and 2, along with individual trajectories of eachcluster (Fig. 10) support our conclusion that Australia and New Zealand arethe most probable sources of rBC to the drilling site, consideringtropospheric transport. The most visible influence of air parcels from thesetwo countries to the drilling site can be seen in the individualtrajectories of cluster 1 (Fig. 10) for both dry and wet seasons, while forclusters 2 and 4 there are trajectory variations from one season to another.The poleward shift of cluster 1 trajectories in the wet season (Fig. 9) maybe a reason why the Australian emissions earlier in the year (May) are notvisible in the TT07 rBC record. South American influence on the TT07drilling site, on the other hand, is restricted to the higher-latitudecountries (Chile, Argentina), as shown in the individual trajectories ofclusters 2, 3 and 5 (Fig. 10). This suggests that South American fires arenot significant contributors to the rBC concentrations observed at the TT07site when considering only tropospheric transport.
BC in Antarctica has been studied only in the recent decades, but long-rangeanthropogenic influences have already been observed(Bisiauxet al., 2012a; Stohl and Sodemann, 2010). Models predict a continuedincrease in BC emissions from source areas(Bondet al., 2013) and a continued increase in BC flux to the Antarctic region,mostly to the Antarctic Peninsula and West Antarctica(Arienzo et al., 2017).Understanding the spatial variability of BC is then essential to predictBC's future impact on the continent.
We analyzed a 20 m long snow–firn core from West Antarctica spanning1968–2015 for rBC. Results show a well-defined seasonal variability in therecord, with low (high) concentrations during the Southern Hemisphere wet(dry) season but no long-term trend along the 47 years of the core. Snowaccumulation remained stable during this period. rBC annual concentrationswere found to be the lowest in samples from recent decades compared toother studies, while rBC annual fluxes compare with the low values found byBisiaux etal. (2012b) for high-elevation East Antarctica ice cores. Correlationsbetween rBC and snow accumulation, elevation and distance to the sea forEast and West Antarctica records indicate rBC transport and deposition mightbe different for each. SNICAR modeling indicated BC does not affect snowalbedo significantly at the site, with a reduction of 0.48 % and 0.41 %for the highest rBC concentrations found in the core and for dry seasongeomean concentrations relative to clean snow, respectively. Negligibleimpact on albedo was observed for wet season geomean concentrations. BCemission estimates, satellite data of fire spots and HYSPLIT particletransport simulations suggest Australia and New Zealand as the maincontributors to the rBC present in the TT07. Based on GFED4s emissionestimates, SH South America may be a secondary contributor, although this isnot supported by spectral analysis results or air mass trajectories.Spectral analysis of the rBC shows influence of AAO and ENSO periodicities;ASL influences were not detected. This core is the highest-elevation rBCcore collected in West Antarctica and its low BC concentrations compared toprevious studies indicate spatial variability in the transport anddeposition of BC in West Antarctica.
TT07 data are available upon request;auxiliary data can be downloaded from respective sources cited along with thiswork.
This work was conceptualized by all authors. Funding was acquired by JCS, who also administered the project. JCS and LM participated on the fieldwork, while laboratory work was done by LM supervised by SK. LM wrote the original draft with contributions from SK and JCS. All authors contributed to the interpretation of study results.
The authors declare that they have no conflict of interest.
We thank the Centro Polar eClimático (CPC/UFRGS) and the Department of Geological Sciences (CWU)faculty and staff for the support of this work. We also thank the authorsBisiauxet al. (2012a, b),Casey et al. (2017), Khan et al. (2018) and Pasteris et al. (2014) for rBC dataavailability.
This research is part of the Brazilian AntarcticProgram (PROANTAR) and was financed with funds from the Brazilian NationalCouncil for Scientific and Technological Development (CNPq) Split FellowshipProgram (no. 200386/2018-2), from the CNPq projects 465680/2014-3 and442761/2018-0, CAPES project “INCT da Criosfera” 88887.136384/2017-00 andPROANTAR project 88887.314450/2019-00.
This paper was edited by Mark Flanner and reviewed by two anonymous referees.
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