Determination of δ11B by HR-ICP-MS from mass limited samples: Application to natural carbonates and...

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Geochimica et Cosmochimica Acta 140 (2014) 531–552

Determination of d11B by HR-ICP-MS from mass limitedsamples: Application to natural carbonates and water samples

Sambuddha Misra a,⇑, Robert Owen a,b, Joanna Kerr a, Mervyn Greaves a,Henry Elderfield a

a University of Cambridge, Department of Earth Sciences, Godwin Laboratory for Paleoclimate Research, Downing Street, Cambridge CB2

3EQ, United Kingdomb University of Oxford, Department of Earth Sciences, Oxford OX1 3PR, United Kingdom

Received 17 September 2013; accepted in revised form 24 May 2014; Available online 16 June 2014

Abstract

We present an improved method for accurate and precise determination of the boron isotopic composition (11B/10B) ofcarbonate and water samples using a mineral acid matrix and HR-ICP-MS. Our method for d11B determination utilizes amicro-distillation based boron purification technique for both carbonate and seawater matrices. The micro-distillation meth-od is characterized by low blank (60.01 ng-B) and 99.8 ± 5.7% boron recovery. We also report a new ICP-MS method, per-formed in a hydrofluoric acid matrix, using a jet interface fitted Thermo� Element XR that consumes <3.0 ng-B perquintuplicate analyses (±0.5&, 2r, n = 5). A comparatively high matrix tolerance limit of 650 ppb Na/K/Mg/Ca character-izes our ICP-MS method. With an extremely low procedural blank (60.05 ± 0.01 ng-B) the present isotope method isoptimized for rapid (�25 samples per session) analysis of small masses of carbonates (foraminifera, corals) with low boronabundance and small volume water samples (seawater, porewater, river water). Our d11B estimates of seawater(39.8 ± 0.5&, 2r, n = 30); SRM AE-120 (�20.2 ± 0.5&, 2s, n = 33); SRM AE-121 (19.8 ± 0.4&, 2s, n = 16); SRMAE-122 (39.6 ± 0.5&, 2s, n = 16) are within analytical uncertainty of published values. We apply this new method to assessthe impacts of laboratory handling induced sample contamination and seawater physio-chemical parameters (temperature,pH, and salinity) on marine carbonate bound d11B by analyzing core-top planktonic foraminifera samples.� 2014 Elsevier Ltd. All rights reserved.

1. INTRODUCTION

The isotopes of boron (10B and 11B) fractionate stronglyduring low-temperature geochemical processes, renderingboron isotopes a powerful tracer of earth surface processes(e.g., Spivack and Edmond, 1987; James and Pamer 2000;Lemarchand et al., 2002; Raitzsch and Hoenisch, 2013).Dissolved B in seawater is a conservative element, homoge-neous in both concentration and isotopic composition(d11BSW 39.61 ± 0.2&) with a long residence time

http://dx.doi.org/10.1016/j.gca.2014.05.047

0016-7037/� 2014 Elsevier Ltd. All rights reserved.

⇑ Corresponding author. Tel.: +44 1223333440.E-mail address: [email protected] (S. Misra).

(sB � 10 Myr) (Lemarchand et al., 2000; Foster, 2008;Foster et al., 2010; Louvat et al., 2010). In aqueous solutionB undergoes pH dependent speciation between trigonalboric acid (H3BO3) and tetrahedral borate ion (H4BO4

�)(Fig. 1). The H3BO3 form is isotopically heavier thanH4BO4

�, because of the lower vibrational energy of thetrigonal form (Kakihana et al., 1977; Vengosh et al.,1991; Klochko et al., 2006).

B OHð Þ3 þH2O ¼ B OHð Þ�4 þHþ ð1Þ

where pK�B is the dissociation constant of boric acid in sea-water (Dickson, 1990).


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Fig. 1. pH dependent speciation and isotopic composition of Boron in seawater. pH dependent boron speciation between trigonal boric acidand tetrahedral borate ion in seawater (A), and isotopic composition of the two boron species (B). The calculations were done following Eqs.(1) and (3), after Dickson (1990) and Klochko et al. (2006). T = 25 �C and S = 35 psu.

532 S. Misra et al. / Geochimica et Cosmochimica Acta 140 (2014) 531–552

The isotopic equilibrium between trigonal boric acid andtetrahedral borate ion can be expressed as:

10BðOHÞ3 þ 11BðOHÞ�4 ¼ 11BðOHÞ3 þ 10BðOHÞ�4 ð2Þ

The equilibrium constant aB of Eq. (2) is defined as:

aB ¼ð11B=10BÞH3BO3

ð11B=10BÞH4BO�4

ð3Þ

where aB = f (T, P, Salinity)Hence, the isotopic composition of the two dissolved

species of boron in seawater is strongly pH dependent(Vengosh et al., 1991; Hemming and Hanson, 1992;Sanyal et al., 1996; Pearson and Palmer, 2000; Honischand Hemming, 2004; Pagani et al., 2005; Zeebe, 2005;Honisch and Hemming, 2007; Hemming and Honisch,2007; Zeebe, 2012).

Marine carbonates are thought to preferentially uptakeborate ions from seawater, and therefore the boron isotoperatio preserved in marine carbonates (d11BCaCO3

) has thepotential to elucidate past changes in seawater pH(Hemming and Hanson, 1992). The numerical relationshipbetween seawater pH and d11BCaCO3

can be expressed as:

pH¼ pK�B� log � d11BSW�d11BCaCO3

d11BSW�aB �d11BCaCO3�1000ðaB�1Þ

!

ð4Þ

Glacial–interglacial pH changes, reconstructed fromd11BCaCO3

, are in accordance with the seawater pH changesexpected from ice-core records of atmospheric pCO2 fluctu-ations (Sanyal et al., 1995; Petit et al., 1999; Honisch andHemming, 2005; Foster, 2008; Honisch et al., 2009; Raeet al., 2011; Henehan et al., 2013). Seawater pH is closelyrelated to atmospheric pCO2 and is a key parameter inmodels of the marine dissolved inorganic carbon system

(Zeebe, 2012). Understanding natural variations in seawa-ter pH is therefore central to our efforts to understand bothpast and future climate change.

Importantly, the boron isotopic compositions of marinecarbonates are influenced by factors other than seawaterpH including, but not limited to, the temperature of calcifi-cation, salinity of ambient seawater, and presence of symbi-otic photosynthetic organisms (Pagani et al., 2005; Klochkoet al., 2006). Among these factors, temperature of calcifica-tion is an important consideration for d11BCaCO3

basedreconstruction of glacial–interglacial seawater pH(Kakihana et al., 1977; Honisch et al., 2008). Foraminiferaspecies depending on their depth habitat in the water col-umn and whether they migrate across the thermocline, aresubject to a range of calcification temperatures. Similarly,variation in surface water pH, on a diurnal to seasonaltimescale, can have a strong impact on the d11BCaCO3

. A crit-ical assessment of the influence of the physio-chemicalparameters of the foraminiferal habitat on d11BCaCO3

is nec-essary to utilize the of boron isotopes as a seawater paleo-pH proxy.

Boron isotope ratios have traditionally been measuredby P-TIMS or N-TIMS techniques and more recently byMC-ICP-MS (Table 1) (Spivack and Edmond, 1987;Lemarchand et al., 2002; Aggarwal et al., 2003; Fosteret al., 2006; Louvat et al., 2010; Rae et al., 2011; Gangjianet al., 2013). Continental and basaltic rocks, seawater andporewaters with their relatively high boron content arerarely mass limited for mass spectrometric analysis (Li andSchoonmaker, 2003; Rudnick and Gao, 2003). However,natural carbonates with relatively low boron concentration([B]Carbonate � 2–20 ppm) and smaller sample availability(65 mg CaCO3 per sample) are mass limited for boron.Accurate and precise analysis of boron isotope ratios in suchmass limited samples is analytically challenging. As a light

Table 1Summary of d11B methods.

Author Sample Separation method Recovery Instrument Mass foram Mass B Blank Precision(2r)

Shima (1963) Rock, meteorite, seawater

Distillation with methylalcohol

>90% Solid source massspectrometer

– �10 lg – –

Spivack andEdmond (1986)

Silicates rocks andseawater

Mixed bedresin + pyrohydrolysis

>98% P-TIMS – – <7.5 � 10�10

mol0.36&

Kiss (1988) Silicates rocks andnatural waters

Amberlite XE 243 94–99% Spectrophotometer – – – 2.74%

Xiao et al. (1988) Borax Cation exchange resin – P-TMIS – 3–0.05 lg 40–180 pg 0.01%Vengosh et al.(1989)

Natural waters andcarbonates

Amberlite XE 743 – N-TIMS – 50–200 ng – 1.7&

Vengosh et al.(1991)

Modern biogeniccalcarous skeletons

Amberlite IRA-743 – Solid source massspectrometer

– – 0.003 ppm 1.5&

Hemming andHanson (1992)

Modern marinecarbonates

Amberlite IRA-743 – NTIMS – – 30 pg 0.05–0.3&

Nakamura et al.,1992

Silicate rocks andnatural waters

Bio-Rad AG50WX12 99 ± 1% PTIMS – <1 lg 3–4 ng 0.1–0.2&

Hemming andHanson (1994)

Seawater, carbonate Amberlite IRA-743 100 ± 1% N-TIMS – 0.5–100 ng 160 pg 0.7&

Sanyal et al. (1995) Planktonic and benthicForaminifera

– – N-TIMS – – – 0.7&

Palmer et al., 1998 Carbonate – – VG 446 – – – 0.3&

Gaillardet et al.(2001)

B Standards Micro-sublimation 100% P-TIMS – 250 ng – <0.12&

Lemarchand et al.(2002)

River water Amberlite IRA-743 98–100% P-TIMS 250 ng 3 ng 0.35&

Foster et al., 2006 Seawater andforaminifera

Amberlite 743 – NTIMS 0.1 mg 300 pg <5 pg 0.7&

Foster (2008) Foraminifera Amberlite IRA-743 – MC-ICP-MS (Neptune) 1–3 mg 15–30 ng – 0.25&

Louvat et al. (2010) Seawater andCarbonates

AG 50 W X12 andAmberlite IRA-743

– MC-ICP-MS (Neptune) – <100 ng – 0.25&

Ishikawa andNagaishi (2011)

Coral standard andseawater standard

AG 50 W X12 >97% P-TIMS (Triton) – 50–100 ng – 0.1&

Wang et al. (2010) Natural waters andmarine carbonates

Micro-sublimation >97% MC-ICP–MS (Neptune) – – <8 pg 0.33&

Chao et al. (2011) Fluids from mudvolcanoes

Micro-sublimation – MC-ICP-MS (Neptune) – 50 ng – 0.3&

Rae et al. (2011) Benthic foraminifera Amberlite IRA 743 >95% MC-ICP-MS (Neptune) 0.35–3 mg �2–20 ng – 0.25&

S.

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mass element with a large fractionation factor, boron isreadily fractionated within the instrument during mass spec-trometric measurements and during sample preparation.Mass spectrometric boron isotope determination methods,both thermal and ICP mass spectrometry, are susceptibleto large matrix dependent instrumental mass bias effectsdue to low tolerance for matrix impurities. To minimizematrix-dependent fractionation within the instrument, theanalyte boron must be isolated from other matrix elements.This boron separation technique must be quantitative (i.e.100% boron recovery) to eliminate the possibility of han-dling induced isotope fractionation at this stage. However,the types of applicable boron separation techniques are lim-ited by the high volatility of boron in an acidic matrix: vol-atilization of boron leads to strong Rayleigh fractionation.This triggers fractionation of the analyte and contaminationduring sample preparation. In addition, this volatilitycontributes to a strong memory effect, complicating boronisotope measurements by traditional ICP-MS methods(Al-Ammar et al., 1999, 2000b).

Traditionally the separation of boron from its matrixhas been done either by ion exchange chromatography inanionic form or by sequestering boron with D-Mannitol(Spivack and Edmond, 1987; Kiss, 1988; Foster, 2008;Rae et al., 2011). The application of a micro-column tech-nique with boron specific resin Amberlite IRA 743 andsodium acetate–acetic acid buffer suffers from blank relatedcontamination, boron mass loss due to volatility, and mostimportantly this method limits the choice of matrix forICP-MS analysis. An alternative method for boron separa-tion is the micro-distillation technique (Gaillardet et al.,2001; Wang et al., 2010), which utilizes the volatile natureof boron in an acid matrix. The micro-distillation methodis less susceptible to contamination issues; however, incom-plete boron recovery and loss of boron during high temper-ature separation can lead to Rayleigh fractionation andintroduce artificial bias in the measured isotopic composi-tion of the analyte. We have developed an improved sin-gle-step micro-distillation method characterized by lowblanks (60.01 ng-B), quantitative boron recovery, andabsence of processing induced isotopic fractionation ofthe analyte.

The major analytical challenges associated with boronisotope measurements by ICP-MS are: (i) a strong memoryeffect requiring long washout time; (ii) large instrument andlaboratory blanks due to the volatile nature of boron; (iii)low matrix tolerance; (iv) large instrument induced massbias; (v) strong 20Ne2+ and 40Ar4+ interferences on 10B atlow resolution (Dm/m = 300); and (vi) low sensitivity/poorionization efficiency due to high first ionization potential(B-IP1 = 8.3 eV). Additionally, the low abundance ofboron in calcites coupled with its high IP1 makes instru-mental sensitivity a limiting factor for boron isotope ratiodetermination.

Methods for precise isotope ratio determination by ICP-MS rely either on rapid Standard–Sample Bracketing (SSB)or internal standard addition techniques to account forinstrumental drift and mass bias. Addition of a lithiuminternal standard during boron analysis is a possible stan-dard addition method. However, due to the large relative

mass difference between lithium and boron (�40%), lithiuminternal standard addition fails to improve the internal pre-cision of boron isotope ratio measurements (Al-Ammaret al., 2000a). To maximize the potential of the SSB tech-nique, a quick washout of the analyte between samples isnecessary. Volatility and strong surface adsorption proper-ties of boron in nitric acid matrix render rapid SSB analyt-ically challenging. The use of ammonia gas in the sampleintroduction system has been successfully employed toovercome this problem (Al-Ammar et al., 1999, 2000b;Foster, 2008). The application of direct injection nebuliza-tion allows for precise 10B/11B measurements by MC-ICP-MS with low boron mass consumption and fast washout(Louvat et al., 2010). We propose an alternative solutionto the washout problem by using reducing mineral acid(HF) with a strong affinity for boron as the sample matrixto improve the wash out time (Makishima et al., 1997). Inan HF matrix boron will undergo a series of reactions tofrom fluoroboric acid (HBF4�H2O). Fluoroboric acid is astrong acid, as a result its conjugate base BF4

– (the borontetrafluoride anion) will be the dominant boron species inthe HF matrix. The following reactions will determine thespeciation of B in an HF matrix:

BðOH3 þ 3HF ¼ BF3 þ 3H2O

BF3 þHFþH2O ¼ HBF4 �H2O

HBF4 �H2O! BF�4 þH3Oþ

BðOHÞ3 þ 4HF! BF�4 þH3Oþ þ 2H2O

Both BF3 and HBF4�H2O are highly soluble in water(solubility at 20 �C of BF3 = 1060 gL�1 and HBF4�H2-

O = infinite), the dominant solvent in the matrix. Addition-ally, the boiling point of HBF4�H2O is �129 �C, implyingthat the dominant boron species in the HF matrix will havevery low volatility under laboratory conditions.

In this article we show that our HR-ICP-MS method canachieve accurate, high precision d11B measurements(60.5&, 2r) with low boron mass consumption (<3.0 ng-B/quintuplicate analysis) and with high tolerance for matrixcontaminants. We have applied this new method for boronisotope ratio determination in mass limited carbonate sam-ples to investigate the influence of calcification temperatureon d11BCaCO3

in foraminifera. We analyzed core-top samplesof Orbulina universa, a planktonic foraminifera species thatmigrates across the thermocline, to assess the impact of tem-perature of calcification and seawater salinity on d11BCaCO3

.

2. MATERIALS AND METHOD

2.1. Acids and labware

All acids and standards were prepared under Class 100clean lab conditions to minimize the boron, sodium,potassium, magnesium, and calcium blanks. Pre-cleanedNalgene� Teflon� bottles (boiled in �7 M HNO3) wereused for solution storage. Savillex� Teflon� beakers andICP-MS vials (boiled in �7 M HNO3) were used for samplepreparation and analysis. All acids, ICP-MS standards andsample dilutions were prepared using 18.3 Mega-Ohm MQwater and Seastar�Optima�(Fisher�) grade HF and HNO3.

S. Misra et al. / Geochimica et Cosmochimica Acta 140 (2014) 531–552 535

Eppendorf� snap cap vials (0.5 ml) were used for foraminif-era cleaning and analysis. The Eppendorf� vials were boiledin 10% v/v HCl, rigorously rinsed and then boiled in MQwater to rinse off any residual acid. Our reagent blanks(ammonia, NaOH, and H2O2) were identical to our acidmatrix blank of �1 pg-B/ml.

2.2. Boron isotope standard preparation

Boron isotopic composition is reported as per mil (&)deviation from NIST SRM 951a (11B/10B = 4.04362 ±0.00137) (Catanzaro et al., 1970). Where

d11BSample ¼

11B10B

� �Sample

11B10B

� �NIST�951a

264

375� 1

8><>:

9>=>;� 1000 ð5Þ

Approximately 57.2 mg of NIST SRM 951a (boric acid)was gravimetrically dissolved in 100 ml of MQ water to pre-pare a 100 ppm (100 mg/l) boron stock solution. Subse-quently, an intermediate boron isotope standard of100 ppb (100 lg/l) was prepared by gravimetric dilutionof the stock solution. Working standards for isotope ratiomeasurements were prepared from the stock solution byvolumetric dilution on the day of analysis using the sameacid as used for sample preparation.

2.3. Mass spectrometry

Boron isotopes were analyzed by a Thermo� ElementXR, a single collector, sector field, high-resolution induc-tively coupled plasma mass spectrometer, fitted with a highsensitivity interface pump (Jet pump). Instrumental settingsfor isotope analyses are listed in Table 2. In order to ana-lyze boron isotopes in an HF matrix (0.3 M HF) a Teflon�

Scott type (single pass) spray chamber was constructed.Additionally, we used a platinum injector (1.8 mm I.D) to

Table 2ICP-MS settings for boron isotopes and X/Ca determinations.

Parameter Isotope mode

Plasma RF Power 1250 WNebulizer SavillexTM – 50 ll (C-flow)Sray Chamber Teflon Scott type (single pass)a

Injector ESITM Platinum (1.8 mm I.D)Sample Cone Ni – JETSkimmer Cone Ni – XExtraction Voltage �2000 VSample Matrix 0.3 M HFUptake time 60 sAnalysis time 210 sWashout time 150 sMass Resolution LowMagnet Mass 10.012 (fixed)10B Mass Range 10.012–10.01311B Mass Range 11.008–11.009Samples per peak 200 (10B and 11B)Runs 225Passes 10Detection mode Analog

a Assembled from Savillex� PFA parts for column components.

significantly reduce the instrumental boron blanks (Table 3).Time resolved analyses of boron uptake and washout in dif-ferent acid matrices (Supplement 1), along with evaluationof boron blanks, were done to determine the best matrix forisotope analysis.

Boron isotope analyses were made following a Sample–Standard Bracketing (SSB) technique. NIST 951a was usedas the standard and samples were concentration matched(typically ±5%) with the standard and were analyzed inquintuplicate (Supplement 2). The instrument was opti-mized for maximum boron sensitivity (1 M-cps/ppb on11B) and samples were usually analyzed at 5.0 ± 1.0 ppbboron concentration (>1 M-cps 10B signal) with a signalto blank intensity ratio of >500. To compensate for poorionization of boron in the plasma, high performance extrac-tion cones (Jet sampler and ‘X’ skimmer) were used toboost boron sensitivity. However, this increase in sensitivityis accompanied by a proportional increase in 20Ne2+ and40Ar4+ ion beams, resulting in an isobaric interference peakon 10B. The instrument plasma conditions and mass cali-bration were appropriately adjusted to eliminate any artifi-cial mass bias caused by 20Ne2+ and 40Ar4+ peak tailinginto the 10B+ peak.

A key aspect of the present method is the use of Pt injec-tor and the HF matrix to achieve very high signal to blankratio for boron (Table 3). Additionally, the use of a highsensitivity Jet interface (Jet Sampler and ‘X’ Skimmercones) to improve instrumental boron sensitivity by �5-foldwas one of the major factors in reducing the boron massrequirement per analysis. The 11B sensitivity (in a 0.3 MHF matrix) increased from 0.2 M-cps/ppb, with normalion extraction cones, to 1.0 M-cps/ppb using Jet extractioncones. Typical boron blanks for a 0.3 M HF matrix were1200 ± 100 cps on 11B and for a 5 ppb boron analyte thesensitivity was �5.0 � 106 cps on 11B. A 180s washout inan HF matrix after each analysis was sufficient to reducethe boron blank down to background levels. For isotoperatio analysis pre-analysis boron blanks were subtractedfrom each standard and sample measurement. Duringboron analysis at low mass resolution (Dm/m = 300) theuse of high performance extraction cones led to a propor-tional increase in the 20Ne2+ (m/z = 9.99622) and 40Ar4+

(m/z = 9.99095) ion beam intensities, the two plasma basedisobaric interferences on the light mass end of 10B (m/z = 10.01294). In order to eliminate the tailing effects of20Ne2+ and 40Ar4+ beams onto the 10B peak the mass cali-bration for 10B was fractionally biased towards the heavymass end without compromising the peak shape of 10B inthe analysis window (Supplement 4). We avoided using ahigh RF power (>1400 W) to improve ionization efficiencyof boron in the plasma as this led to a proportionateincrease in multiply charged plasma based interferences.Instrument sensitivity optimization was carried out at anRF power of 1250 W to reduce the contribution from the20Ne2+ and 40Ar4+ beam intensities. Moreover, by adjustingthe flows of sample gas, additional gas, and the samplingdepth we achieved an 40Ar4+ interference to 10B+ analytesignal ratio of 1:2 with a 5 ppb-B solution. During analysesthe magnet mass was fixed on 10B at m/z = 10.012 to allowrapid quasi-simultaneous scanning of the two isotopes.

Table 3Boron blanks and sensitivity in different acid matrices.a

Spray Chamber Injector [HNO3] [HF] 11B Blank 1 ppb 11B 11B-S/N 115In Blank 1 ppb 115In 115In-S/N

Material Type Material (M) (M) (cps) (cps) (cps) (cps)

Quartz Cyclonic Quartz 0.1 – 16,953 193,140 11 4611 2,028,881 440Quartz Cyclonic Platinum 0.1 – 11,623 214,302 18 2102 2,497,732 1188Quartz Cyclonic Platinum 0.4 – 5422 118,875 22 5851 1,557,314 266Teflon Scott Platinum 0.1 – 7708 302,183 39 19,105 4,357,595 228Teflon Scott Platinum 0.2 – 19,663 299,794 15 14,594 4,176,358 286Teflon Scott Platinum 0.4 – 19,750 286,104 14 11,152 3,904,246 350Teflon Scott Platinum 0.1 0.15 4970 288,935 58Teflon Scott Platinum 0.2 0.15 6456 265,298 41Teflon Scott Platinum 0.4 0.15 3587 250,590 70Teflon Scott Platinum 0.1 0.3 2011 315,428 157Teflon Scott Platinum 0.2 0.3 2286 285,282 125Teflon Scott Platinum 0.4 0.3 3312 264,047 80

S/N is defined as Signal to Noise (Blank) ratio where the ‘Signal’ is the sensitivity in counts per second (cps) of the isotope of an analyte for a1 ppb solution and the ‘Noise’ is defined as the matrix blank in cps.

a All measurements were performed with normal sample and skimmer cones.


Both isotopes of boron were measured in analog detectionmode to avoid detector dead-time induced instrumentalmass bias. Each sample was analyzed in quintuplicate,requiring �1 h of instrument time per sample.

Plasma source mass spectrometric methods for isotoperatio determination suffer from instrumental mass biascaused by preferential extraction and transmission of hea-vier ions over lighter ions. The two isotopes of boron expe-rience differential space-charge effect, the mutual repulsionof positively charged ions within the ion beam by plasmabased ions such as 40Ar+, 16O+. The 10% mass differencebetween 10B and 11B leads to significantly reduced spacecharge effects on 11B compared to 10B. This differentialspace charge effect on the lighter isotope results in largeinstrumental mass bias in boron isotope ratios (�50&).Using an internal standard such as lithium to correct forthis instrumental mass bias is not a judicious optionbecause of the large relative mass difference between lithiumand boron (�40%), and due to the considerable differencein the first ionization potential (IP-1) of the two elements(LiIP-1 5.4 eV; BIP-1 8.3 eV). In the present study, to correctfor instrumental mass bias, we applied the external normal-ization technique of SSB. To account for instrument driftand a large but fixed mass bias, multiple short analyticalruns bracketed by NIST 951a boron standards were per-formed. An additional key improvement of the presentmethod is the rapid boron washout time, which allows forfast switching between sample and standard and henceallows for closely bracketed analyses (Table 3; Supplement1). The precision of existing ICP-MS boron isotope ratiodetermination methods suffers from long boron washouttimes, which prolongs the interval between sample andstandard analyses (Makishima et al., 1997; Al-Ammaret al., 1999). Introduction of alkaline ammonia gas to thesample spray chamber to facilitate boron washout has beensuccessfully utilized to improve the internal precision ofMC-ICP-MS methods (Foster, 2008; Louvat et al., 2010;Rae et al., 2011) and analyze small samples at high preci-sion. The present scheme of efficient boron washout using

dilute HF is similar to the NH3 method in its boron wash-out efficiency and results in no build up of boron in thesample introduction system (Supplement 1). However,stronger affinity of halogens for boron leads to a �10%drop in boron ionization efficiency in the plasma, comparedwith a nitric acid matrix (Table 3). Despite the small drop insensitivity the large reduction of boron instrumental blanksleads to a significant net gain in signal to blank ratio, allow-ing for analysis of <3.0 ng-B without requiring an extensiveblank correction. Additionally, the use of a simple, lowflow, large volume sample introduction system producesvery stable plasma conditions over long periods.

Similar to plasma based mass biases, all ICP-MS isotoperatio determination methods for low mass elements (Li, B,Mg) suffer from an artificial mass bias effect caused by thepresence of other matrix elements (Gregoire et al., 1997;Galy et al., 2001; Foster, 2008; Misra and Froelich, 2009).We tested the potential influence of matrix-based contami-nation from Na, Mg, K, and Ca on the measured d11Baccuracy and precision by doping a standard of knownisotopic composition (AE-120) with variable amounts(5–200 ppb) of the contaminant elements. The influence ofthese four elements as matrix contaminants wasinvestigated because of (a) the ease with which laboratoryhandling can introduce Na, Mg, and K blanks, and (b)the high abundance of these elements in carbonate and sea-water samples.

2.4. Boron purification by micro-distillation

Boron was separated from the sample matrix by a sin-gle-step micro-distillation method, modified afterGaillardet et al., 2001. Savillex� Teflon� fin legged 5 mlbeakers with conical interior were used as the distillationreservoir. Samples, in <50 ll volume, were loaded on tothe cap of a pre-cleaned beaker – the beaker was tightlyclosed to avoid boron loss and set on a hotplate at95 �C with the conical end pointing up. We used Analabe

Teflon� coated graphite hotplates and digestion blocks with

Table 4External precision on SRM NIST 951a, AE-120, AE-121, AE-122, and Seawater d11B determinations.

Standard d11BAccepted Direct ICP analyses Micro-distilled W/O matrix Micro-distilled with matrix

d11B ± 2r& n d11B ±2r& n d11B ±2r& n

NIST 951a 0.0& 0.03 ± 0.27 23 �0.07 ± 0.24 6 0.28 ± 0.35 3AE 120 �20.2 ± 0.6& �20.21 ± 0.45 33 �19.97 ± 0.14 3AE 121 19.9 ± 0.6& 19.75 ± 0.35 16 19.74 ± 0.63 3 19.74 ± 0.51 35AE 122 39.6 ± 0.6& 39.58 ± 0.47 16 39.42 ± 0.46 4 39.74 ± 0.44 3Seawater 39.6 ± 0.4& 39.77 ± 0.38 30


precise (±0.5 �C) and uniform temperature control. The pHof the load solution was always kept below 2 by adding anappropriate volume of Optima� grade concentrated HCl.This was done to improve the volatility of boron in thesample load, as at low pH the dominant boron species insolution is the volatile boric acid (Chetelat et al., 2005).The distillation process was carried out for 15–18 h toachieve a quantitative yield of boron from the load intothe distillate. Sample load volume was kept below 50 ll pri-marily to avoid the accumulated droplet at the conical endfrom dropping back onto the cap; with appropriate setuplarger volume samples can be micro-distilled. Post distilla-tion, beakers were taken off the hotplate, allowed to coolfor �15 min, then 0.5 ml of 0.3 M HF was added and the

Fig. 2. Matrix effect on d11B. Boron standard, SRM AE-120 (d11B:�20.2 ± 0.6&), doped with 5, 10, 25, and 50 ppb of Na, K, Mg,and Ca was analyzed against NIST 951a SRM. The AE-120 SRMwas doped both individually (open symbols) and collectively (solidsymbols) with the four elements. AE-120 SRMs doped with Na arerepresented by open circles, K by open squares, Mg by opendiamonds, Ca by open up-triangles, and all four elements(Na + K + Mg + Ca) together by solid down-triangles. The NIST951a standards and AE-120 samples were concentration matchedat 5.0 ppb B. The analytical uncertainties represent 2r standarderror on quintuplicate measurements (2r=

ffiffiffinp

). A control sample,AE-120 without any matrix contaminant, was analyzed with thedoped samples. The grey area represents the accepted range ofvalues for AE-120.

beakers were capped with a fresh acid clean cap. The sam-ple residue left on the cap was taken up in 0.1 M HNO3 fortrace element (X/Ca) analysis and determination of the dis-tillation yield.

We investigated the effects of temperature and of thecomposition of the sample matrix (in terms of quantityand type of dissolved cations and matrix acid strength) todetermine the optimal conditions to achieve quantitativeseparation of boron from seawater and foraminiferalmatrix matched loads. We also performed a time resolvedanalysis of the isotopic composition of boron micro-dis-tilled from seawater and foraminiferal matrix matched solu-tion to determine the minimum distillation durationrequired to achieve complete (boron) recovery and isotopic

Fig. 3. Analyte concentration effect on d11B. Boron SRM AE-122(d11B: 39.6 ± 0.6&) was analyzed at variable concentrationsagainst a fixed concentration NIST 951a SRM. AE-122 SRMswere analyzed at a concentration difference of ±10%, ±30%, and±50% from NIST 951a at 5.0 ppb. Triplicate measurements of AE-122 were done at exact concentration matching with the standardto serve as control. Control samples are represented by openaddition symbols and the samples at variable concentrations bysolid diamonds. The analytical uncertainties represent 2r standarderror on quintuplicate measurements (2r=

ffiffiffinp

). The grey arearepresents the accepted range of values for AE-122. The right handY-axis shows the 11B counts in million-cps at different boronconcentrations of the analyte and is non-linear.


homogeneity. Different volumes of seawater samples weredistilled to assess the effect of sample size and laboratorycontamination on the composition of the distilled boronfraction. Additionally, NIST SRM 951a and three ERMSRMs of known boron isotopic composition: AE 120(�20.2& ± 0.6&); AE 121 (19.9& ± 0.6&); AE 122(39.7& ± 0.6&) were micro-distilled from pure elementalsolutions and from solutions with high calcium concentra-tion (10,000–40,000 ppm Ca) to evaluate boron recoveryand possible fractionation during the distillation process.We gravimetrically dissolved calcium carbonate solids (AlfaAesar� 99.997% purity) in Optima� grade concentratedHCl to prepare a 10,000 ppm calcium solution. Equal vol-ume Optima� grade concentrated HCl was added to thecalcium solution and it was dried down to a gelatinous blobat 98 �C to drive off the boron. This step was repeated twiceto create a boron free solution. The final gelatinous blobwas taken up in a known volume of 1.0 N HCl to preparea 80,000 ppm calcium solution. The boron blank of the cal-cium solution was determined by our B/Ca determinationmethod by diluting the concentrate to 10 ppm Ca (Misraet al., 2014) and was identical (1.2 lmol/mol) to the detec-tion limit, �1 lmol/mol. We also micro-distilled 50 ll ali-quots of the 80,000 ppm calcium solution. The boronblank of the distillates was identical to our matrix boronblank of <1 pg-B/ml. Estimates of boron recovery weredone by measuring the B/Ca of the residue on the cap ofthe beaker (Supplement 6). The foraminiferal matrixmatched solution used in the experiment reported inFig. 4 was prepared by adding minor (Na, Mg, K, andSr) and trace (Li, Al, Mn, Fe, Zn, Ba, Cd, and U) elements,

Fig. 4. (A) and (B). Time resolved analysis of [B] and d11B of micro-distillA time resolved analysis of boron recovery and d11B of the distilled fracsolution doped with ROMILe boron (B). The load volume and micro-diSimilarly, boron concentrations in both loads were closely matched. The bhand Y-axis and the d11B values are plotted on the right hand Y-axis asrepresents 2r standard error on quintuplicate measurements (2r=

ffiffiffinp

). Indistillates form the 9th hour onwards, excluding the outlier, with 2r unc

using ROMILe high purity single element standard, ataverage planktonic foraminiferal proportion to this80,000 ppm Ca solution. This solution was then doped withknown amount of ROMILe high purity boron solution.

2.5. Foraminifera sample preparation

Foraminifera shells were handpicked under an opticalmicroscope to separate by species and size fractions. Shellswith visible signs of diagenetic alteration or significantauthigenic mineral deposits were discarded. Species-specificsamples of O. universa, Globoratalia inflata, Globigerinoides

bulloides, and Globigerinoides sacculifer (0.5–4 mg byweight) of size fraction 300–355 lm were picked. Addition-ally, three sets of species-specific (2� O. universa and 1� G.

inflata) samples of large mass (>5 mg) consisting of mixedsize-fractions were processed to assess the external precisionof the micro-distillation method with respect to naturalsamples. Core-top foraminifera samples from the WesternIndian Ocean and North Eastern Atlantic Ocean wereselected for this study (Supplement 3). All foraminifera testswere gently crushed between two glass plates to crack openthe chambers. Samples were cleaned in batches of 1 mg orless; this required that the larger samples were split intoequal weight fractions during cleaning and recombinedbefore dissolution. Fragmented foraminifera were first ultr-asonicated in MQ water (3 times), methanol (2 times), andagain in MQ water (2 times) to remove clay materials.Following clay removal they were either reductively(Ammonia–Ammonium Acetate buffer and Hydrazine) and/oroxidatively (Sodium Hydroxide and Hydrogen Peroxide)

ed boron from Seawater and foraminifera matrix matched solution.tion from seawater samples (A) and foraminifera matrix matched

stillation temperature (75 �C) were kept fixed for both experiments.oron mass recovery on both plots are plotted as solid circles on leftsolid diamonds. The analytical uncertainty of d11B measurementsfigure B the open square represents the average d11B value of all

ertainty.


cleaned (Boyle and Keigwin, 1985; Rosenthal et al., 1997;Barker et al., 2003). To evaluate the effect of the samplecleaning method on calcite bound d11B, species-specificcore-top foraminifera samples were split into three fractionsand cleaned following either the Red-Ox-Red, the Red-Ox,or just Ox cleaning steps. Post chemical cleaning the sam-ples were leached with very dilute ultra clean HCl(0.001 M) to release any chemisorbed elements from thesurface of the calcite. Leached samples were dissolved inminimum volume of 1 M HCl (40–60 ll), centrifuged for2 min at 10,000 rpm and the supernatant was used for anal-ysis. The bulk of the dissolved sample �50 ll (P95%) wassubjected to the micro-distillation technique and theremainder of the concentrated sample solution was dilutedwith 200 ll of 0.1 M HNO3 for X/Ca analysis.

Fig. 5. d11B of Seawater. Boron isotopic composition of seawater(d11BSW) micro-distilled from different load volumes. The opensymbols represent individual micro-distillation experiment and thesolid symbols represent the average for each load volume with 2runcertainty. Seawater samples of 20 ll load are represented bydiamonds (n = 6), 25 ll by up-triangles (n = 5), 30 ll by squares(n = 4), 35 ll by down-triangles (n = 4), 40 ll by left-hand-triangles(n = 7), and 50 ll by right-hand-triangles (n = 4). The average all30 measurements, with 2r uncertainty, is represented by the solidcircle at the bottom of plot. The dashed line represents thepublished/accepted d11BSW of 39.61 ± 0.2& (2r) (Foster et al.,2010).

3. RESULTS AND DISCUSSION

3.1. d11B determination by ICP-MS

Previous methods for boron isotope ratio determinationby MC-ICP-MS and TIMS have a large B mass require-ment (Table 1). For example, high precision TIMS meth-ods, except for total evaporation N-TIMS methods havea minimum boron mass requirement of >50 ng-B to achievea d11B precision of <0.5& (Spivack and Edmond, 1987;Vengosh et al., 1991; Hemming and Hanson, 1994; Fosteret al., 2006). On the other hand, MC-ICP-MS methodshave a boron mass requirement of 15 ± 5 ng-B to obtaina d11B precision of �0.2&. Here we achieve d11B precisionbetter than that of established single collector-ICP-MSmethods (60.5&) while consuming <3.0 ng-B per quintu-plicate analysis. The present method reduces the analytemass requirement by �50% compared to established meth-ods to achieve an intermediate d11B precision of �0.5&

(Foster, 2008; Louvat et al., 2010; Rae et al., 2011)(Table 4). During the method development stage we useda suite of secondary boron isotope standards with distinctisotopic compositions, AE 120 (�20.2 ± 0.6&), AE 121(19.9 ± 0.6&), AE 122 (39.6 ± 0.6&), to establish theinstrumental precision, the efficiency of boron washout,influence of matrix effects and concentration effects (Vogland Rosner, 2011).

A series of back-to-back analyses of NIST 951a boronstandards were done to quantify instrumental drift(<0.5&/h). High instrument sensitivity, stability and theability to do rapid SSB helped us achieve d11B precisionbetter than existing single collector ICP-MS methods witha much lower sample mass requirement (Table 1). Theexternal precision of the instrument, calculated on repeatmeasurement of NIST SRM 951a and seawater, rangesfrom ±0.27& on NIST 951a, to ±0.38& for processed sea-water samples (Table 4).

The present mass spectrometric method has a compara-tively high tolerance for matrix contamination from Na,Mg, K, and Ca, up to 200 ppb total per 5 ppb B, whetherpresent as a single element or a combination of all four(Fig. 2). ICP-MS analyses also suffer from analyte concen-tration dependent mass bias, which requires concentrationmatching between samples and standard. The present

method, with a fixed ion detection mode and a linear sensi-tivity-concentration response, has a large concentrationmatching tolerance of ±50% at 5.0 ppb B (Fig. 3).

3.2. d11B of seawater, SRMs, and foraminifera

Quantitative recovery of boron from calcite matrix isanalytically challenging (Table 1). Additionally, laboratoryprocessing of a volatile element with large relative mass dif-ference between its two isotopes can easily lead to handlinginduced artificial fractionation and/or contamination. Thepresence of boron in normal boro-silicate HEPA filters(>8% by wt) leads to sublimation of boron vapors to labair, especially when exposed to acid vapors. This airborneboron contamination can cause a significant offset in themeasured ratio from the true value (Supplement 5). Thehandling induced boron contamination sets limits on theminimum mass of boron required to make an accurate mea-surement. Additionally, sample processing, micro-distilla-tion or column elution, can introduce an artificial offsetbetween true and measured values. We estimated a boronblank of 1 ng/h out of non PTFE HEPA filters. Whenworking in a non-HEPA environment or PTFE HEPA fit-ted environment no measurable (�1 pg/h) boron blankswere observed. We exposed blank acids to lab air for 1 h– a representative sample exposure time.

Fig. 6. (A)–(D). Micro-distillation of boron from Calcite matrix: Boron mass yield and d11B. The efficiency of boron recovery and its d11Bduring micro-distillation from foraminifera matrix was evaluated by distilling 4–25 ng of SRM AE-121 (d11B: 19.9 ± 0.6&) from high puritycalcium solutions with 1 � 104, 2 � 104, 3 � 104, and 4 � 104 ppm [Ca]Matrix. The boron doping of the calcium solutions was donevolumetrically. Boron yield during micro-distillation plotted with respect to calcium concentration of the load matrix and B/Ca ratios of theload are shown in figures (A) and (B) respectively. Similarly, figures (C) and (D) show d11B plotted with respect to calcium concentration ofthe load matrix and B/Ca ratios of the load respectively. The grey area in the figures (A) and (B) represents the average boron yield of100.0 ± 5.0% and in figures (C) and (D) represents the accepted range of values for d11BAE-121. All distillations were performed at 95 �C for18 h and the sample load volume ranged from 10 ll to 50 ll (Table 5; Supplement 6). The average boron yield and d11B of SRM AE-121 loadof 4 ng are represented by solid up-triangles, 8 ng by open down-triangles, 10 ng by open squares, 12 ng by solid right-triangles, 16 ng by solidleft-triangles, 20 ng by open circles, and 25 ng by solid diamonds. Average recovery and d11B of samples distilled without matrix (n = 3) isrepresented by solid square at the bottom of the plots. Long-term average of d11BAE-121 analyzed without distillation (n = 16) is represented bythe open addition symbol in plots (C) and (D). All ICP-MS analyses were performed at 5 ppb B concentrations of standards and samples.Boron recoveries were calculated by analyzing B/Ca in the distillation residue. The error bars represent 2s uncertainty.



3.2.1. Micro-distillation of boron from seawater and calcite

matrices

Purification of boron from sample matrix was carriedout by the micro-distillation method, which utilizes the vol-atile nature of boron at high temperatures in acidic medium(pH < 2) (Gaillardet et al., 2001; Chetelat et al., 2005). Atime resolved analysis of boron recovery and d11B of thedistillate using samples of known isotopic composition (sea-water and foraminifera matrix matched solution) was car-ried out to determine an optimal micro-distillation time(Fig. 4(A) and (B)). For seawater isotopic equilibriumand a recovery >95% were observed after 9 h of distillation.Within the 12th hour complete recovery of boron wasachieved. However, micro-distillation of boron from a solu-tion containing elements in the proportions expected fromdissolved foraminifera required longer than 10 h for the dis-tilled fraction to attain isotopic equilibrium and 14 h forcomplete mass recovery (Fig. 4(A) and (B)). The distilledboron fraction from both matrices was initially isotopicallyheavier (�2&) than the load. This initial enrichment of thedistilled fraction can be explained by the preferential con-densation of the heavier isotope from the vapor phase oralternatively by the distillation of the heavier isotope outof the load (Chetelat et al., 2005). Based on these findingsand other experiments we adopted a minimum distillationtime of 18 h at a temperature P95 �C to achieve completeboron recovery from (foraminifera) sample loads.

Accurate isotope ratio determination by ICP-MSrequires that the analyte be in a pure matrix with lowamounts of total dissolved solids (TDS). Unfortunately,low mass elements like lithium, boron and magnesium,due to the large relative mass difference between their iso-topes, are susceptible to laboratory handling induced frac-tionation during their matrix purification. This ubiquitousartificial fractionation of low mass elements requires100% mass recovery of these elements during their chemicalseparation from the matrix. Separation of boron from itssample matrix, especially from high concentration CaCO3,using the micro-distillation method is susceptible to<100% boron recovery and small but significant mass bias

Table 5Boron mass recovery and d11B of micro-distilled SRM AE-121.

[Ca] (ppm) BLoad (ng) VolumeLoad (ll) B/CaLoad (lmol/mol) Yi

0 25 50 � 1010,000 610 620 185.6 910,000 20 40 185.6 910,000 25 50 185.6 920,000 610 620 92.8 920,000 20 40 92.8 920,000 25 50 92.8 930,000 610 620 61.9 930,000 20 40 61.9 930,000 25 50 61.9 940,000 4 40 9.3 1040,000 8 40 18.6 1040,000 12 40 27.8 1040,000 16 40 37.1 940,000 610 620 46.4 1040,000 20 40 46.4 940,000 25 50 46.4 10

(Gaillardet et al., 2001; Chetelat et al., 2005; Wang et al.,2010). The boron concentration of benthic and planktonicforaminifera varies from 610 lmol/mol B/Ca in Trifarina

Spp. to P200 lmol/mol in Cibicidoides wuellerstorfi. As aresult, to target �4 ng-B per sample a variable amount ofcalcite needs to be processed. Assuming 50% sample lossduring foraminifera chemical cleaning, P9 mg of Trifarina

Spp. and P0.5 mg of C. wuellerstorfii sample mass arerequired to yield 4 ng-B. The limitation on the load volume(650 ll) means that low B/Ca samples produce very highconcentrations of calcium (P1000 ppm) in the load. To testthe effect of calcium concentration of the load matrix onboron recovery and the boron isotopic composition of thedistillate, NIST 951a and the three secondary SRMs weredistilled from acid matrix with variable and high calciumconcentrations P10,000 ppm (Supplement 6).

To assess the accuracy and precision of our boron sepa-ration and ICP-MS methods we first compared our seawa-ter d11B (d11BSW) measurements with published results. Wealso processed a range of seawater (20, 25, 30, 35, 40 and50 ll) samples to assess the effects of sample size on d11Band boron recovery during the micro-distillation. Our esti-mate of d11BSW of 39.8 ± 0.4& (2r, n = 30) is independentof sample size and is in agreement with published values of39.61 ± 0.20& (Foster et al., 2010) and 39.7 ± 0.6&

(Spivack and Edmond, 1987) (Fig. 5). These results suggestthat boron separation by the micro-distillation methodadopted in this study has a negligible (<0.01 ng-B) blankand is quantitative for seawater samples.

To establish the boron recovery yield of calcite-basedsolutions we micro-distilled 4–25 ng samples of SRM AE121 (d11B = 19.9&) from calcite-based solutions with Caconcentrations ranging from 10,000 ppm to 40,000 ppm,corresponding to a B/Ca range of 7.5–185 lmol/mol. Theseresults are compared with SRM AE 121 samples analyzednon-distilled, and those micro-distilled without a calcite-based matrix (Fig. 6; Table 5; Supplement 6). The averaged11B of SRM AE 121 non-distilled (19.75 ± 0.35&,n = 16), distilled without matrix (19.74 ± 0.63&, n = 3),and distilled with matrix (19.74 ± 0.51&, n = 35) are

eldAVERAGE (%) 2r (%) n d11BAVERAGE (&) 2r (&) n

0.0 0.03 3 19.74 0.63 28.9 1.2 68.5 1.0 3 19.53 0.44 29.5 0.8 3 19.73 0.34 39.2 2.3 6 19.78 0.70 67.3 1.9 3 19.67 0.23 39.3 0.7 3 19.70 0.30 29.6 2.2 56.9 1.2 3 19.91 0.24 38.9 2.1 3 19.69 0.50 37.0 12.3 34.9 2.7 31.2 2.3 3 19.78 0.71 39.2 3.1 3 19.74 1.06 20.6 0.8 54.8 4.7 3 19.61 0.45 20.2 3.9 15 19.79 0.61 6

Fig. 7. (A)–(D). Long-term d11B precision on NIST 951a, SRM AE-120, AE-121, and AE-122. Compilation of all d11B measurements ofSRMs NIST 951a (d11B: 0.0&), AE-120 (d11B: �20.2 ± 0.6&), AE-121 (19.9 ± 0.6&), and AE-122 (39.6 ± 0.6&) in figures (A), (B), (C) and(D) respectively. SRMs analyzed directly by the ICP-MS are represented by open diamonds, micro-distilled without matrix by open squares,and micro-distilled with matrix by open circles. The corresponding solid symbols represent the average of each type of measurement. For opensymbols the analytical uncertainties represent 2r standard error on quintuplicate measurements (2r=

ffiffiffinp

) and for solid symbols the error barsrepresent 2r uncertainty on all individual measurements. In each figure samples are sorted according to their date of analysis. All sampleswere analyzed at 5 ppb B concentrations following SSB technique with SRM NIST 951a. The grey area in each figure represents the acceptedrange of values for each SRM.


indistinguishable from one another. The different AE 121SRM fractions that were distilled from a varying amountof total dissolved calcium in the load matrix and variableamount of starting boron mass are also within analyticaluncertainty of d11B estimates of the non-distilled standard.The present micro-distillation method has a boron recoveryof 99.8 ± 5.7% (2r, n = 70). The average boron recoveriesfrom 10,000, 20,000, 30,000, and 40,000 ppm calcitematrices are 99.0 ± 1.2% (n = 12), 98.8 ± 2.5% (n = 12),98.7 ± 3.0% (n = 11), and 100.7 ± 7.3% (n = 35)respectively. The average recoveries from samples with B/

Ca < 20 lmol/mol and >150 lmol/mol are 104.4 ± 8.1%(n = 9) and 99.0 ± 1.2% (n = 12) respectively (Table. 5;Supplement 6). Similarly, the d11B values of non-distilled,distilled without matrix, and distilled with matrix SRMsNIST 951a, AE 120 (d11B = �20.2&), and AE 122(d11B = 39.6&) are identical to their accepted value(Fig. 7(A)–(D)) (Vogl and Rosner, 2011). Unfortunately,prolonged instrumental downtime compromised the d11Bdetermination on <10 ng boron micro-distillationexperiment samples. However, the uniform boron yield fromdistillation loads of different matrix strength and total boron

Fig. 8. (A)–(D). Impact of Boron Contamination on Foraminiferal d11B. Results from contaminated d11B analyses of core-top and down-coreOrbulina universa, Globigerinoides bulloides, and Globigerinoides sacculifer samples from Western Indian Ocean (WIND 5 K, 10 K, and 28 K)and North Eastern Atlantic Ocean (NEAP 8 K) (Supplements 3 and 7). d11B values are plotted against net mass of boron present in thesample after chemical cleaning of the carbonates. Data for all foraminifera specimens, Globigerinoides sacculifer (open triangles),Globigerinoides bulloides (open diamonds), and Orbulina universa (open circles) are represented in figures (A), (B), (C) and (D) respectively.Oxidatively cleaned specimens are represented by blue symbols and reductive–oxidatively cleaned ones by red symbols. The grey arearepresents the published range of foraminiferal d11B values. In figures (B)–(D) the grey contour lines represents calculated d11B values fordifferent fixed initial sample boron mass between 0.5 and 20 ng-B (given by the number in parenthesis) and increasing amount of boroncontamination. The d11B of the foraminiferal end members for Globigerinoides sacculifer, Globigerinoides bulloides, and Orbulina universa areassumed to be 20.5&, 19.5&, and 19.5&, respectively and are represented by the horizontal black line. The d11B of the contaminant, boronsublimed off HEPA filters, is considered to be �5.0&. The error bars represent 2r standard error on quintuplicate measurements. (Forinterpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)


content validates the low blank and quantitative recovery ofthe present micro-distillation method as suggested by thed11BSW analyses. The consistency of boron mass recoveryand d11B of the SRMs modified to match foraminiferamatrix solutions establishes the method of boron purifica-tion by micro-distillation as a robust analytical techniquecapable of performing low blank boron separation from a

variety of high TDS matrices without net fractionation ofthe analyte.

3.2.2. The relative effects of sample size and contamination of

foraminiferal d11B

The use of foraminifera carbonate tests to reconstructpast seawater chemical compositions is complicated by


post-depositional diagenesis of the carbonate tests, second-ary calcite deposition from porewaters, and preferential dis-solution of the heterogeneous primary calcite (highmagnesium calcite) (Boyle, 1983; Brown and Elderfield,1996; Barker et al., 2003). Diagenetic alteration of tests (dis-solution and recrystallization to high Mg-containingCaCO3) and the presence of authigenic mineral phases(iron–manganese oxides, marine clays) can offset the truecalcite bound trace element signature in unprocessed/uncleaned foraminifera samples. A variety of chemicalcleaning techniques have been used to remove post deposi-tional materials from calcite in order to minimize the effectof these secondary phases on the analyte of interest (Boyle,1983; Boyle and Keigwin, 1985; Rosenthal et al., 1997).However, chemical-cleaning methods can lead to preferen-tial leaching of the foraminiferal calcite and the subse-quently analyzed composition can be biased towardsmore dissolution resistant phases (Barker et al., 2003).

Our initial attempts to determine d11B of core-top anddown-core foraminifera samples from Western IndianOcean (WIND 5 K, 10 K, and 28 K) and North EasternAtlantic Ocean (NEAP 8 K) were compromised by boroncontamination (Fig. 8(A) and Supplement 7). Anomalouslylight d11B (<4&) were observed from chemically cleaned(Ox and Red-Ox) O. universa, G. bulloides, and G. sacculifer

samples. Samples with low carbonate mass, hence low totalboron, were observed to be isotopically lighter than theirheavier counterparts (Fig. 8(B)–(D)). However, sampleswith an initial carbonate weight of >4 mg resulted ind11BForaminifera values comparable to publishedmeasurements (Fig. 8(B)). Foraminifera samples can be

Fig. 9. (A) and (B). Foraminifera d11B: External reproducibility. The d11

foraminifera samples are plotted as deviation from their respective speciessamples cleaned by oxidative method are represented by blue symboloxidative–reductive method by red symbols. In both figures Orbulina u

diamonds, Globigerinoides bulloides by squares, and Globigerinoides saccul

in figure (A) are from size fractions >355 lm and G. sacculifer samples arare from >212 lm size fraction, where >5 mg samples were cleaned oxidatdistillation. Core-top samples from Sites WIND 10 K and NEAP 8 K weDd11B. (For interpretation of the references to colour in this figure legen

contaminated by isotopically light boron through threepossible modes: presence of authigenic clay minerals;incomplete removal of Fe/Mn oxides from the calcite sur-face; and by laboratory contamination (James and Pamer,2000; Foster et al., 2006; Lemarchand et al., 2007). Thechemically cleaned O. universa, G. bulloides, and G. sacculifer

samples showed no signs of boron contamination fromauthigenic clay or Fe/Mn oxide as evident from the lowTi/Ca, Fe/Ca, and Mn/Ca values of the samples (Supple-ment 7). Reagent blanks for all solutions used in foraminiferacleaning and ICP-MS sample preparation were measuredand found to be nominal, <1.0 pg-B/ml (identical to thedetection limit of the present method). Isotopically lightboron subliming off standard HEPA filters was traced tobe the source of contamination (Rosner et al., 2005). Weestimated a boron contamination rate >1 ng/h by exposingboron free MQ water and dilute acids in 15 ml Savillex�

PTFE beakers to HEPA filter airflow. The average isotopiccomposition of the boron sublimed from the HEPA filterswas �5& (d11BContaminant). As the major steps of foraminif-era sample preparation (chemical cleaning, leaching, dissolu-tion, and post micro-distillation processing) were performedunder over pressured Class 100 clean lab conditions, thesamples were exposed to laboratory air for variableamounts of time and contaminated by different amounts ofisotopically light boron subliming off the HEPA filters.Boron contamination during chemical cleaning offoraminifera through chemisorption of negatively chargedborate ions onto carbonate shells from high pH cleaningsolutions is one possible way to explain the observed trendin d11BForaminifera. At high pH, typical of foraminifera

B values of chemically cleaned, core-top, single species, planktonicaverage (Dd11BSample = d11BSpecies Average - d11BSample). Foraminiferas, reductive–oxidative method by black symbols, and reductive–niversa samples are represented by circles, Globorotalia inflata byifer by triangles. The O. universa, G. inflata, and G. bulloides samplese from >425 lm size fraction. The three sets of samples in figure (B)ively and post dissolution were split up in equal fractions for micro-re used (Supplement 3). The grey area represents ±0.5& spread ind, the reader is referred to the web version of this article.)

Fig. 10. d11B of Core-top Orbulina universa Samples from SiteCD159-05. d11B values of core-top Orbulina universa specimensfrom the top 1 cm of sediments from North Eastern Atlantic OceanSite CD159–05 (solid symbols) are plotted against 1/BTotal of thesamples (Table 6). The top X-axis (non linear scaling) representsthe total boron content of the samples. d11B values of contaminatedOrbulina universa specimens from Site NEAP 8 K (Fig. 8(D)) areplotted as open symbols within grey shaded area. Foraminiferasamples cleaned by oxidative method, reductive–oxidative method,and reductive–oxidative–reductive method are represented by blue,red, and black symbols. The error bars represent 2r standard erroron quintuplicate measurements. (For interpretation of the refer-ences to colour in this figure legend, the reader is referred to theweb version of this article.)


cleaning solutions, borate ion is the dominant dissolvedspecies (Fig. 1). As a result, samples with lower total boroncontent are more sensitive to contamination and showgreater deviation from accepted foraminiferal d11B values.Similarly, foraminifera species with lower B/Ca ratio showsgreater deviation from acceptable d11B values (Fig. 8(C)and (D)). This contamination problem was avoided initiallyby working in a laboratory with no HEPA filtered airflowand subsequently overcome by installing PTFE HEPAfilters.

The impact of foraminfera chemical cleaning on calcitebound boron isotopic composition was evaluated by pro-cessing core-top samples by different cleaning techniques.Species-specific samples of O. universa and G. inflata (sizefraction 300–355 lm) were cleaned following Red-Ox-Red, Red-Ox or just Ox methods. The cleaning procedurestarted with approximately 10 mg of foraminifera samples,and after each of the cleaning steps an aliquot of the car-bonate was dissolved for d11B analysis. Similarly, samplesof G. bulloides (Red-Ox-Red and Red-Ox) and G. sacculifer

(Ox) were cleaned for d11B analyses (Fig. 9(A) and (B)).Species-specific foraminifera samples chemically cleanedusing different methods are identical (Dd11B �0.5&) totheir respective group averages. The absence of cleaningmethod dependent systematic d11B offsets demonstratesthat the calcite bound boron isotopic composition offoraminifera tests is unaffected by the choice of chemicalcleaning method for the samples used in this study. Theaverage d11B values of O. universa (>300 lm, n = 20, 2r)and G. sacculifer (>425 lm, n = 4, 2r) of 17.25 ± 1.52&

and 20.20 ± 1.0& respectively are within the range of pub-lished values (Honisch et al., 2009; Foster et al., 2010).

The external precision of the micro-distillation methodon natural samples was evaluated by analyzing three setsof species-specific (2� O. universa and 1� G. inflata) sam-ples of large mass (>5 mg) consisting of variable size-frac-tions. These consistency samples were Ox-cleaned and ondissolution split into 4–6 separate fractions for micro-distil-lation (Fig. 9(B)). The individual micro-distillates of thethree different consistency samples are identical (Dd11B�0.5&) to their respective group averages. The reproduc-ibility (0.5&) of the micro-distillation method with naturalsamples establishes the robustness of the analytical tech-nique and its potential application to natural carbonates.

3.2.3. The influence of seawater pH and calcification

temperature on foraminiferal d11B

We analyzed core-top (top 1 cm) O. universa samplesfrom North Eastern Atlantic (Site CD159-05) to evaluatethe effects of seawater pH, salinity and calcification temper-ature on foraminiferal calcite bound d11B (Fig. 10)(McCave, 2005). O. universa is a planktonic foraminiferawith symbiotic dinoflagellates known to migrate betweensurface and �100 m depth on diurnal timescales. As aresult, at locations with shallow thermoclines (<100 m,e.g. Site CD159-05) individual O. universa specimens willhave calcified at different water temperatures. To minimizebias in the d11B data due to variability in foraminiferasample mass (weight of CaCO3) and size fraction of thespecimens, we analyzed samples comprising of 25 or 50

O. universa (0.7–2.2 mg CaCO3) tests from size fraction300–355 lm (Table 6).

The core-top O. universa samples record a range ofd11BO. universa values (17.2 ± 1.77&, n = 20, 2r) with nomeasurable difference between cleaning methods. Thed11BO. universa values of samples cleaned by the Ox method(17.13 ± 1.7&, n = 15, 2r), Red-Ox method(17.75 ± 2.5&, n = 3, 2r) and, Red-Ox-Red method(17.37 ± 2.0&, n = 2, 2r) are identical within the rangeof core-top values. While it is possible that the variabilityin the amount of sample (CaCO3) loss during the chemicalcleaning process introduces a minor sample size dependentbias, the measured d11BO. universa values show no sample size(analyte boron mass) dependency and are within the rangeof published values (Sanyal et al., 1995; Honisch et al.,2003; Foster et al., 2010) (Fig. 10).

The d11BO. universa variability of core-top samples fromSite CD159-05 could be explained by one or a combinationof the following factors: (i) variability in seawater pHacross the dwelling depth of O. universa at the samplingsite, (ii) absence of accurate age control of the samples,(iii) laboratory contamination, (iv) size dependent d11B var-iation in O. universa, (v) analytical uncertainty in d11Bdetermination, (vi) difference in foraminifera calcificationtemperature, and (vii) changes in seawater salinity. If the

Table 6d11B data and pH reconstruction of O. universa samples from Site CD159-05.

# Core Species Depth(cm)

No. ofspecimens

Sizefraction(lm)

InitialCaCO3

(lg)

Cleaningprotocol

B-Total(ng)

d11B(&)

2r(&)

S.E(&)

pHT = 9 �CS = 35

pHT = �CS =

pHT = 15 �CS = 35

pHT = 12 �CS = 32.5

pHT = 12 �CS = 37.5

1 CD159-05-23

O.

Universa

1 25 >300 0.749 Ox 2.06 17.21 0.19 0.10 8.27 8.21 8.16 8.22 8.20

2 CD159-05-23

O.

Universa

1 25 >300 1.082 Ox 2.98 17.57 0.79 0.40 8.30 8.24 8.19 8.26 8.23

3 CD159-05-23

O.

Universa

1 25 >300 1.193 Ox 3.28 16.98 0.83 0.41 8.25 8.19 8.13 8.20 8.18

4 CD159-05-23

O.

Universa

1 25 >300 0.860 Ox 2.37 16.46 0.63 0.31 8.20 8.14 8.08 8.15 8.13

5 CD159-05-23

O.

Universa

1 25 >300 0.868 Ox 2.39 17.66 0.31 0.16 8.30 8.25 8.20 8.26 8.24

6 CD159-05-23

O.

Universa

1 25 >300 0.667 Ox 1.83 16.70 0.67 0.39 8.22 8.16 8.11 8.18 8.15

7 CD159-05-23

O.

Universa

1 25 >300 0.815 Ox 2.24 15.43 0.60 0.27 8.09 8.03 7.97 8.05 8.02

8 CD159-05-23

O.

Universa

1 25 >300 0.809 Ox 2.22 17.54 0.47 0.21 8.29 8.24 8.19 8.25 8.23

9 CD159-05-23

O.

Universa

1 25 >300 1.25 Ox 3.44 17.56 0.87 0.44 8.30 8.24 8.19 8.26 8.23

10 CD159-05-23

O.

Universa

1 25 >300 1.209 Ox 3.32 16.30 0.33 0.15 8.18 8.12 8.07 8.14 8.11

11 CD159-05-23

O.

Universa

1 25 >300 1.207 Ox 3.32 17.31 1.11 0.56 8.27 8.22 8.17 8.23 8.21

12 CD159-05-23

O.

Universa

1 25 >300 0.944 Ox 2.60 16.40 0.55 0.25 8.19 8.13 8.08 8.15 8.12

13 CD159-05-23

O.

Universa

1 50 >300 1.680 Ox 4.62 17.12 0.60 0.30 8.26 8.20 8.15 8.22 8.19

14 CD159-05-23

O.

Universa

1 50 >300 1.900 Ox 5.23 19.09 0.60 0.30 8.41 8.36 8.31 8.38 8.35

15 CD159-05-23

O.

Universa

1 49 >300 2.330 Ox 6.41 17.65 0.60 0.30 8.30 8.25 8.20 8.26 8.24

16 CD159-05-23

O.

Universa

1 50 >300 2.189 Red-Ox 4.82 16.35 0.60 0.30 8.19 8.13 8.07 8.14 8.12

17 CD159-05-23

O.

Universa

1 50 >300 2.067 Red-Ox 4.55 18.76 0.60 0.30 8.39 8.34 8.29 8.35 8.33

18 CD159-05-23

O.

Universa

1 50 >300 1.744 Red-Ox 3.84 18.14 0.60 0.30 8.34 8.29 8.24 8.30 8.28

19 CD159-05-23

O.

Universa

1 50 >300 2.201 Red-Ox-Red

3.63 16.66 0.60 0.30 8.22 8.16 8.10 8.17 8.15

20 CD159-05-23

O.

Universa

1 50 >300 1.983 Red-Ox-Red

3.27 18.08 0.60 0.30 8.34 8.28 8.23 8.30 8.27

546S

.M

israet

al./G

eoch

imica

etC

osm

och

imica

Acta

140(2014)

531–552

1235


d11B spread of 3.4& in the core-top O. univera sampleswere solely due to ambient seawater pH variations wewould calculate a pH range of 0.3 units (8.03–8.36). Thisis similar to glacial-interglacial pH change and is largerthan the range of in situ estimates (Foster, 2008; Keyet al., 2004; Honisch et al., 2009). Therefore it is unlikelythat the in situ pH variation is the sole driver of the 3.4&

range in d11BO. universa. The eastern part of the North Atlan-tic Ocean is a major sink of atmospheric CO2, accountingfor �40% of global oceanic CO2 drawdown, and the watercolumn is known to show large seasonal variations in CO2

concentrations (Peng et al., 1987; Key et al., 2004). There isno published record of the water column pH profile for SiteCD159-05, however, GLODAP data from neighboringNorth Atlantic sites records >0.1 unit pH variation(7.95 ± 0.1) in the top 100 m of the surface ocean on sea-sonal to diurnal timescales (Key et al., 2004). Assumingfor a more conservative pH range of ±0.05 unit(8.0 ± 0.05) at Site CD159–05 in the preferred depth habitatof O. universa, we calculate seawater d11B–Borate wouldrange from 16.67& at pH = 7.95 to 17.70& at pH 8.05(Fig. 11). This conservative estimate of �1.0& Dd11B–Borate ion in the O. universa habitat can therefore onlypartly explain the low d11B values. Importantly, somed11B values <16.5& lie well outside the range of the calibra-tion data and likely record contamination by isotopicallylight boron. As discussed before, we estimate airborneboron contamination at �1 ng-B/h with a d11B of �5.0&.For low mass samples this posses a serious challenge to gen-erating high fidelity d11B data under normal laboratoryconditions. However, the absence of a strong correlationbetween analyte boron mass and d11BO. universa suggests thatthe observed variability of 3.4& in d11B has, for the mostpart, little to do with laboratory contamination.

These two factors – variation in surface water pH andlaboratory contamination – cannot account for the entire

Fig. 11. Impact of pH of calcification seawater on d11BBðOHÞ4 –d11BCaCO3. d

expanded borate ion d11B over possible calcification pH range (B). The caand Klochko et al. (2006). T = 25 �C and S = 35 psu.

3.4& range in d11B values. The absence of robust age con-trol for the core-top samples implies that glacial samples,calcified at high pH/d11B values, might be present in thecore-top assemblages. However, based on the sedimenta-tion rate estimates of Site CD159-05, it is highly unlikelythat the core-top sediments contain glacial material(McCave, 2005). Minor variability in d11B is to be expectedin core-top samples due to the lack of uniformity in samplesize fraction for symbiont hosting planktonic foraminiferasuch as O. universa (Honisch et al., 2003). However, sucheffects are minor and cannot explain the 3.4& range ind11BO. universa. The analytical uncertainty of present method(±0.5&, 2r, external) explains only ±0.05 spread in pHestimates, again insufficient to explain the recorded values.We therefore conclude that a significant component of core-top d11BO. universa variation is likely due to due to changes inseawater in salinity or the calcification temperature. SiteCD159-05 has a steep thermocline with a typical early sum-mer surface water temperature of 12 �C and decreasing to<9 �C at water depths of �100 m (Supplement 8).

The dissociation coefficient of boric acid (pK�B) in seawateris a function of temperature, salinity, and pressure (Dickson,1990). The experimental relationship between pK�B and sea-water temperature and salinity can be expressed as:

lnK�

K0

� �¼ð�8966:90�2890:51�S

12�77:942�S�0:0993�S2Þ

�ðT�1Þþð148:0248þ137:1942�S12þ1:62142�SÞ

þð�24:4344�25:085�S12�0:2474�SÞ� lnðT�1Þ

þð0:053105�S12Þ�ðT�1Þ

where K� = 1 mol (kg-soln�1)

K� ¼ ½Hþ� � ½BðOHÞ�4 �½BðOHÞ3�

11B of boric acid and borate ion over pH range of 7.6–8.4 (A), andlculations were done following Eqs. (1) and (3), after Dickson (1990)

Fig. 12. (A)–(F): Seawater pH Reconstruction. Seawater pH reconstruction of Site CD159-05, represented as histograms, from d11B values ofcore-top Orbulina universa samples. Foraminiferal d11B values are binned in 0.25& interval and calculated pH values in 0.05 pH units. Thedashed line in each figure represents the average value. d11B based seawater pH reconstructions done at T = 12 �C and S = 35, T = 12 �C andS = 32.5, T = 12 �C and S = 37.5, T = 9 �C and S = 35, and T = 15 �C and S = 35 are represented in by figures (B–F), respectively.Calculations were done following equations in the text after Kakihana et al. (1977), Dickson (1990), Hemming and Hanson (1992), Klochkoet al. (2006); and Honisch et al. (2008).



S = Salinity and T = Temperature in degree KelvinThe sensitivity of pK�B to changes in temperature is more

pronounced than either salinity or pressure for the range ofvalues observed in the surface ocean. Additionally, the iso-topic fractionation factor (a) of boron between trigonalboric acid and tetrahedral borate ion, although uncertain,is thought to be temperature-dependent (a = 1.0293 �0.000082 * T�C) (Kakihana et al., 1977; Honisch et al.,2008). As a result, accurate reconstruction of paleo-seawa-ter pH using foraminiferal d11B requires knowledge of theambient seawater salinity and temperature at the time ofcalcification. At Site CD159-05 the variability in salinityat water depths <100 m is extremely small (�0.01 unit)and cannot explain the observed variation in d11BO. universa

(Supplement 8). Seawater pH reconstruction followingHemming and Hanson (1992) across a five unit change insalinity (35.0 ± 2.5) results in 0.04 unit change in calculatedpH, an order of magnitude smaller than the observed range(Fig. 12(C) and (D)). In contrast, seawater pH reconstruc-tion for three calcification temperatures 12 �C ± 3 �C, atfixed salinity of 35, results in >0.1 unit difference in calcu-lated pH values (Fig. 12(E) and (F)). This implies that thetemperatures of calcification may affect the boron isotopiccomposition of O. universa and of other planktonic foram-inifera that migrate across the thermocline. Additionally,depending on the season of calcification, an even largerrange of calcification temperatures may be expectedbetween specimens of the same species. This seasonalityeffect will magnify the temperature sensitivity of foraminif-eral d11B based pH reconstruction.

The spread in core-top O. universa d11B data from SiteCD159-05 represents a combination of pH variation of

Fig. 13. d11B analysis by MC-ICP-MS. Compilation of d11B measuremenMC-ICP-MS (Thermo� Neptune Plus) are presented figures (A) and (B) rethe MC-ICP-MS following SSB protocol. 10B and 11B beams were meas2008; Louvat et al., 2010; Rae et al., 2011). Each sample was measured innumbers in the parenthesis represents the number of measurements duriindividual analytical session and the analytical uncertainties represent 2r100 ppb. The grey area in the figures represents the 2r uncertainty of th

the surface ocean, a potential size fraction effect, theinfluence of foraminiferal calcification temperature, labora-tory contamination and some contribution from analyticaluncertainty. These results highlight the importance ofselecting sample sites with suitable hydrography and phy-sio-chemical conditions when interpreting d11B data fromthermocline dwelling foraminifera. The choice of plank-tonic foraminifera species used in paleo-seawater pH recon-struction should take into account the lifecycle and depthhabitat of the selected species. The ideal approach is to ana-lyze foraminifera species that dwell outside of the thermo-cline region and not in surface waters with large pHfluctuations, preferably at depths with uniform seasonaltemperature. The choice of sampling with favorablehydrography is also critical for reconstruction of seawaterpH by foraminiferal d11B analyses. Importantly, glacial–interglacial seawater pH reconstruction from d11BCaCO3

must be done by using multi-collector mass spectrometryto minimize the instrumental uncertainty (Fig. 13).

3.3. Boron isotope ratio by MC-ICP-MS (Thermo-NeptunePlus)

The present sample introduction technique when coupledwith a MC-ICP-MS (Thermo-Neptune Plus) instrument canbe utilized to generate accurate and precise (<0.2&, 2r)d11B measurements on small samples (<3.0 ng-B) (Fig. 13).The precision and mass requirement of the present methodadapted to MC-ICP-MS are comparable to those of estab-lished MC-ICP-MS methods (Foster, 2008; Louvat et al.,2010; Rae et al., 2011; Foster et al., 2013; Henehan et al.,2013). In an HF sample matrix and using a setup identical

ts of SRMs NIST 951a (d11B: 0.0&) and AE-121 (19.9 ± 0.6&) byspectively (Vogl and Rosner, 2011). SRMs were analyzed directly byured on L3 and H3 Faraday cups with 1011-ohm resistors (Foster,blocks of 5 with 10 cycles per block and 4.2 s integration time. The

ng a single analytical session. The open symbols are the average ofstandard deviation. Samples were analyzed at [B] of 15, 25, 50, ande present ICP-MS method based on all measurements.


to that described in Table 2 our 11B blanks were <1.2 mVand boron sensitivity was �15 V/ppm. This allowed for asignal to blank ratio of �900 for a 100 ppb B solution.Our estimates of NIST 951a and ERM AE-121 boronSRMs, analyzed over a concentration range of 15–100 ppbB, are 0.00 ± 0.09& (2s, n = 95) and 19.57 ± 0.14& (2s,n = 45) respectively (Fig.13). The d11B values of SRM AE-121 determined on the MC-ICP-MS at a mass consumptionof 2.8 ng-B per analysis are identical, within analyticaluncertainty, to published values of Foster et al. (2013) andVogl and Rosner (2011).

4. CONCLUSIONS

An improved method for boron micro-distillation fromcalcite and seawater matrix, and rapid determination of11B/10B by single collector ICP-MS is outlined. The keyimprovement of the present method is the reduction inboron blanks and mass requirement, permitting the analysisof smaller samples. The use of an HF matrix and inert (Tef-lon/Pt) sample introduction system for ICP-MS analysesallow for rapid Standard–Sample Bracketing. We reportan external precision of ±0.5&, 2r at low boron mass con-sumption (<3.0 ng-B per quintuplicate analyses). Thismethod can readily be integrated with existing MC-ICP-MS methods for 11B/10B determinations to achieve highprecision (<0.2&, 2r) at low mass requirement (2.8 ng Bper sample). The improved micro-distillation method forboron purification yields a quantitative recovery of boronfrom both seawater and calcite matrix. Our estimates ofd11B of seawater and secondary SRMs are identical to pub-lished values. This new d11B determination method can beapplied to mass limited samples requiring low blank highprecision measurements and is ideally suited for naturalsamples with P1& variation in d11B, viz. pore-waters, sam-ples of fluid-rock interaction, ancient carbonates. Labora-tory contamination of samples remains the greatestchallenge for high fidelity d11B determination methods,especially for low mass samples. d11B values of core-topforaminifera samples, species that migrate across thermo-clines on diurnal timescales, from North Atlantic Oceanshow a considerable range in d11BCaCO3

due to variationsin the pH of ambient seawater, calcification temperature,and possible boron contamination. Paleo-seawater pHreconstruction from foraminiferal d11B analyses warrantsboth careful handling of samples and judicious selectionof sample species with robust knowledge of their diurnallifecycle and favorable hydrography at the sampling site.

ACKNOWLEDGEMENT

This work was funded by The European Research Council(ERC Grant 2010-NEWLOG ADG-267931 HE) to Prof. HenryElderfield. The contributions of Dr. Munir Humayun for the spraychamber design and construction and of Dr. Karen Van Hoeckewith the micro-distillation method are greatly appreciated. Discus-sions with Dr. Adina Paytan greatly helped with improving themanuscript. Help from Dr. Jason Day, Dr. Salima Souanef-Ureta,Linda Booth, Caroline Daunt and especially from Dr. MarylineVautravers are sincerely acknowledged. The thoughtful commentsof Claudine Stirling, Jerome Gaillardet, Gavin Foster, and an

anonymous reviewer greatly helped in improving the quality andpresentation of this work.

APPENDIX A. SUPPLEMENTARY DATA

Supplementary data associated with this article can befound, in the online version, at http://dx.doi.org/10.1016/j.gca.2014.05.047.

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Determination of δ11B by HR-ICP-MS from mass limited samples: Application to natural carbonates and...

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