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j iiiiiniiiiH'iiii PUBLICATIONS AlllOb MTSQ^l

NIST SPECIAL PUBLICATION 260-149

U. S. DEPARTMENT OF COMMERCE/Technology Administration

National Institute of Standards and Technology

Standard Reference Materials

Value Assignment and Uncertainty Estimation

of Selected Light Stable Isotope Reference Materials:

RMs 8543-8545, RMs 8562-8564, and RM 8566

R. Michael Verkouteren and Donna B. Klinedinst

>nal Institute of Standards and Technology

ology Administration, U.S. Department of Commerce

NIST Special Publication 260-149

Standard Reference Materials®

Value Assignment and Uncertainty Estimation of

Selected Light Stable Isotope Reference Materials:

RMs 8543-8545, RMs 8562-8564, and RM 8566

R. Michael Verkouteren and Donna B. Klinedinst

Surface and Microanalysis Science Division, Chemical Science and Technology Laboratory

National Institute of Standards and Technology

Gaithersburg, MD 20899-8541

U.S. DEPARTMENT OF COMMERCE, Donald L. Evans, Secretary TECHNOLOGY ADMINISTRATION, Phillip J. Bond, Under Secretary of Commerce for Technology NATIONAL INSTITUTE OF STANDARDS AND TECHNOLOGY, Arden L. Bement, Jr., Director

Issued December 2003
Certain commercial equipment, instruments, or materials are identified in this paper in order to specify the experimental procedure adequately. Such identification is not intended

to imply recommendation or endorsement by the National Institute of Standards and

Technology, nor is it intended to imply that the materials or equipment identified are necessarily the best available for the purpose.

National Institute of Standards and Technology Special Publication 260-149

Natl. Inst. Stand. Technol. Spec. Publ. 260-149, 58 pages (December 2003)

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U.S. DEPARTMENT OF COMMERCE

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GAITHERSBURG, MARYLAND 20899

Value Assignment and Uncertainty Estimation of Selected

Light Stable Isotope Reference Materials: RMs 8543-8545,

RMs 8562-8564, and RM 8566

NIST Special Publication 260-149

Overview. We report the technical basis for value assignments of several carbon and oxygen

stable isotope reference materials distributed by NIST and the International Atomic Energy

Agency (IAEA), and make recommendations regarding laboratory practices and future intercomparison exercises. Assignments and estimates of uncertainty are based on measurement

data using one method at NIST and another method at outside collaborating laboratories. All methods are based on isotope ratio mass spectrometry (IRMS) of carbon dioxide: outside

collaborators measured three isobaric forms of CO2, whereas NIST measured four forms. This

additional capability allowed NIST to assess measurement accuracy, and design an IRMS

method that minimized bias from cross-contamination. The international comparison exercise was designed, involving standard chemical preparation and isotopic measurement — under strict requirements designed by the IAEA-Working Group for Reference Materials — of CO: derived from carbonates, waters, and pure CO: reference

materials. Our goal was to determine precise <5 13C and c) 18 0 value assignments that were

consistent across the materials and corrected for cross-contamination, and to relate variations in results with specific laboratory practices to guide future intercomparisons. Measurement data from all participants were compiled in a spreadsheet and inspected for consistency. Those data meeting the performance requirements were corrected for cross-contamination through direct measurement of this effect, then processed using internationally accepted procedures to determine standardized <5 13 C and c) 18 0 values. For the carbonate and CO2 materials, the results of

this intercomparison provide value assignments shifted slighted towards more depleted

compositions with uncertainties improved by factors up to two over the previous assignments. For the water materials, results were more variable yet suggested that the ^' l8 0 value of SLAP on

the VSMOW isotope ratio scale is between -55.7 %0 and -56.2 %o. Statistical approaches were

used to discern relationships between results and discretionary factors; these relationships are described. To investigate the effects of oxygen isotope compositional assumptions used in data processing,

several sets of assumptions were applied. Results are compared and recommendations made

regarding the use of these assumptions and the effect on intercomparability of data.

1
Acknowledgments

The NIST-IAEA Measurement Intercomparison of Carbon and Oxygen Stable Isotope Reference

Materials was made possible by the support and exeeptional work of many people. We

acknowledge especially the Isotope Hydrology Section of the IAEA and the Standard Reference

Materials Program at NIST for their active interest and support for the project. We especially wish to thank Manfred Groening (IAEA), Nancy Trahey (formerly at SRMP-NIST), and Harro

A.J. Meijer (CIO) for their leadership in enabling this exercise. The participants of this intercomparison exercise (Table 1) are most gratefully recognized for

their substantial and pro bono efforts, as well as discussions, comments, and post-exercise feedback that have led to this report. Their involvement has been crucial to the advancement of

the stable isotope metrology activities of the IAEA and NIST, which in turn support and benefit isotope measurement communities worldwide. The IAEA Working Group at the 1998 and 2000 meetings did a commendable job in conceiving and designing this exercise, which included identifying and balancing the control of important

variables against the technical practicalities of the measurements. This group included Colin

Allison, S. K. Bhatacharya, Tyler Coplen, Paul DeBievre, Tiping Ding, Matthias Gehre, Roberto

Gonfiantini, Manfred Groening, Stanislaw Halas, Donna Klinedinst, Harro Meijer, Willem

Mook, Rolf Neubert, Gerhard Strauch, Philip Taylor, and Mike Verkouteren.

Finally, we wish to thank Stefan Leigh and James Yen of the NIST Statistical Engineering

Division for their diligent efforts in the statistical evaluation of the data, especially regarding the significance of the discretionary factors.

R. Michael Verkouteren Donna B. Klinedinst Surface and Microanalysis Science Division

National Institutes of Standards and Technology

Gaithersburg, Maryland USA

2
Table of Contents

Acronyms, Terms, and Symbols 4

Introduction 7 Laboratory Performance Metrics 8 Calculations 9 Cross-Contamination Correction 9

Standardization 10 Conversion 10 Gas Dilution Correction 1

Unrestricted Variables 11 Results and Discussion 1

Outliers 11 Cross-Contamination Coefficient 11 Results 12 Other Comparisons 12 Effects from Unrestricted Variables 13 Water Samples 13 Carbonate Samples 14 CO2 Samples 15 NIST Measurements 16 Algorithm Considerations 17 Conclusions 18 Recommendations 19 References 21 Tables 22

Figures 31 Appendix 1 : Mandatory procedures 40 Appendix 2: Summary measurement reporting form 44 Appendix 3: Questionnaire regarding unrestricted variables 47 Appendix 4: Individual laboratory results calculated through four sets of assumptions 51 Appendix 5: Links to Current NIST Reports of Investigation for RMs 56

3
Acronyms, Terms, and Symbols

CCM. Cross-contamination Model. See explanation under the symbol //. CIO. The Center for Isotope Research (Centrum voor IsotopenOnderzoek) is an

interdisciplinary research institute within the University of Groningen. The center has a long and distinguished history in measurements and standards activities regarding the natural abundances and variations in rare isotopes. GS-40. Groningen Standard 40, an isotopically-enhanced pure CO: with nominal composition

of c^Cvpdb ~ +1000 %o (2 %

l3 C) and ^

8 0Vpdb.co2 ~ +2000 %o (0.8 %

l8 0). Prepared by

H.A.J. Meijer and R. Neubert of CIO, Groningen. GS-40 was used to determine the level of

cross-contamination in each participating instrument through Eq. 5 (see text). IAEA. International Atomic Energy Agency. The IAEA serves as the world's foremost

intergovernmental forum for scientific and technical co-operation in the peaceful use of

nuclear technology. The IAEA Isotope Hydrology Section serves the needs of 130 Member

States through the Light Stable Isotope Programme, which includes standards activities as well as measurement and training services.

I RMS. Isotope Ratio Mass Spectrometry, which for gases may be differentiated into three modes: absolute IRMS, dual-inlet IRMS, and continuous-flow IRMS (or isotope ratio monitoring IRMS). Absolute IRMS, with the aid of small correction factors, measures

absolute abundance ratios, albeit with limited precision. Dual-inlet IRMS measures the

isotopic difference between two gases with high precision. In this work, we used this mode

exclusively, where all isotopic compositions were effectively referenced against the gas NBS19-CO:. The third mode, continuous-flow IRMS, requires much less sample (and time)

than dual-inlet IRMS, but is less precise. Continuous-flow IRMS involves on-line chemical

separation techniques, such as Gas Chromatography-Combustion (GCC-IRMS) or Elemental Analysis (EA-IRMS).

Isotopomers. Molecules distinguished by having a particular isotopic mass.

16012 C17 0 and

16 013 C16 0 are both mass 45 isotopomers of C02 . LSVEC. Li2CC>3 isotope reference material (NIST RM 8545) originally prepared by H. Svec, Iowa State University.

LSG. Laboratory Standard Gas. Each laboratory had discretion to use a LSG of any

composition, although we suggested a pure CO2 similar to their working reference gas (WRG). Samples of LSG were part of the sample analysis sequence.

m/z. Mass-to-Charge ratio. NBS19. RM 8544 limestone. This primary reference material is used to realize the VPDB

isotope ratio scale, where 5

i3 Cnbsi9/vpdb = +1.95 %o and ^8 0nbsi9/vpdb = -2.20 %o NBSI9-CO2 or NBS19.C02. The C02 derived from NBS19 through digestion in 100% H3PO4

at 25 °C, where the isotopic fractionation factor criimestone-to-co2 = 1.01025 for

18 0/160, and

unity for

,3 C/ 12 C. NIST. National Institute of Standards and Technology, formerly known as the National Bureau

of Standards (NBS). NIST is a non-regulatory federal agency in the U.S. Department of

4
Commerce, with responsibility for developing, maintaining and disseminating fundamental metrology to benefit industry and improve the quality of life. NIST programs include

international standards activities that impact this mission. PCA. Principal Components Analysis, which is a technique for reducing complex multivariate

data to fewer, more easily interpretable dimensions. In this work, we used PCA to determine

the significance of unrestricted variables on the results of the intercomparison exercise. RM. Reference Material, often numbered to identify a particular material. Value assignments

(and associated uncertainties) of RMs are not certified, but are the best values based on

current knowledge. SLAP. Standard Light Antarctic Precipitation (NIST RM 8537 water) obtained from a South

Pole firn sample collected by E. Picciotto, Universite Libre de Bruxelles, at Plateau Station, Antarctica in 1967. SRM. K Standard Reference Material, designating a material having stated properties as certified by NIST. VPDB. Vienna-PeeDee Belemnite. The internationally-accepted isotope ratio scale, primarily

realized through RM 8544 (NBS 19), for reporting relative

l3 C and l8 0 measurements

through the delta {S) notation. Also, the name given to the conceptual (but non-existent) reference artefact that defines the VPDB carbon and oxygen isotope ratio scales. VPDB-CO2 or VPDB.C02. The isotope ratio scale based on CO2 derived from the conceptual

artefact VPDB, where the internationally-accepted isotopic fractionation factor (Xco2-caicitc =

1.01025 for equilibration of

l8 0 abundance at 25 °C, and unity forl3 C abundance. VSMOW. Vienna Standard Mean Ocean Water. The internationally-accepted isotope ratio scale for reporting relative

l8 0 and deuterium measurements through the delta {§) notation. Also,

the name given to the reference water (NIST RM 8535) that defines the VSMOW hydrogen

and oxygen isotope ratio scales. VSMOW-CO2 or VSMOW.C02. The isotope ratio scale based on C02 derived from VSMOW, where the internationally-accepted isotopic fractionation factor a C02-H20 =

1 .0412 for equilibration of ls O abundance at 25 °C. WRG. Working Reference Gas, also known as the Working Machine Gas (WMG), which is used on the "Standard" or Reference side (and introduced via Inlet 2) of a dual inlet IRMS

system to provide a common measurement reference for samples (introduced via Inlet 1 ) in the sequence of analyses. The composition of the WRG was an unrestricted variable in each

laboratory. WMG. See WRG

Z and AZ. Voltage ratio, and difference between two voltage ratios. Here, used to measure the degree of stability of ion source conditions (Eq. 4), and to determine the cross-contamination

effect through Eq. 5 (see text).

5
The symbol delta. A dimensionless quantity used to express the value of an isotope ratio (R)

in a sample relative to a stated reference (Equation 1 ), where the m term designates the minor isotope or isotopomers in the ratio considered (e.g., m = 13 for

13 C/ i2 C, m= 18 for

l8 0/ ,6 0, or m = 45 for

45 C02/44C02 ). Here, the stated reference may be VPDB, VPDB-CCX

NBS19-C02 , VSMOW-CO2, or the WRG. Since a delta value is normally a highly precise value between -0.1 and +0.1, it is commonly multiplied by 1000 and denoted by %o (per

mill).

'"R. Eq. 1

The symbol alpha. A dimensionless quantity, known as the fractionation factor, is used to express the fractionation expected from isotopic exchange between two substances under

standard conditions. For example, the fractionation in

18 0/l6 0 expected when CO2 is equilibrated with H2 0 is expressed in Eq. 2, where ]H R values are

l8 0/ 160 ratios in C02 and H2 0. For further details, see O'Neil (1986).

Eq. 2

X. The symbol lambda. A dimensionless quantity used to express the relationship between the

stable isotope ratios of oxygen in a sample with that in a reference material (Eq. 3). The

letter a has also been used for this purpose but we wish to avoid confusion with the symbol

alpha. A value for X is needed to convert J

45 C02 and c) 46C02 measurements to <5 13 C and 5 nO

r R

n

R.

18 R.

Eq. 3

values, and before precise measurements of this quantity were available, 0.5 was set as the accepted value. The historical constancy of this accepted value is important for maintaining

the intercomparability of past and future measurement results. However, precise measurements of the true value and natural variation in lamba, and the resultant influences on the accuracy and uncertainty of 3nC and c) l8 0 values, have been recent concerns of the IAEA Consultants

1 Working Group on Light Stable Isotope Reference Materials.

77. The symbol eta. Here, a dimensionless quantity used to express cross-contamination

coefficients 7745 and 7745. Values of 77 indicate the fraction of reference gas that contaminates

the sample, and vice versa, during dual-inlet measurements. Cross-contamination is considered a property of a particular IRMS dual-inlet system during a particular time, and is dependent upon the instrumental settings under which measurements are performed.

a). The symbol omega. Here, a quantity used to express the average relative change between

sample-to-sample measures of the WRG voltage ratio, which is a metric of instability in ion source conditions. Values of co are considered related to the level of uncertainty in applied values of 7.

6
Introduction

Isotope reference materials are used to relate field measurements to stated references in many

applications of economic, industrial, and global relevance. The total combined uncertainties of

these field measurements are, in large part, due to uncertainties in the realization of the

internationally accepted isotope ratio scales. This situation arises from the uncertainties in value assignments of Reference Materials (RMs) and, more fundamentally, lack of control of subtle physicochemical and instrumental factors that limit the accuracy and reproducibility of isotopic measurements. Because these factors can be complex combinations of many variables, intercomparison exercises across independent laboratories have been considered the best method

to represent and explore the broad range of variables and to establish consensus values for RMs.

In the past, participants had been asked to perform measurements of RMs, self-evaluate the data, and report "best" results (Hut 1987, Stichler 1995, Verkouteren 1999). The resulting reproducibility among laboratories was two-to-ten times poorer than the sample repeatability within the average laboratory, with variability increasing as the compositional difference increased between the RM and the realization point of the isotope ratio scale. Because total uncertainties of RM value assignments reflect the variation in intercomparison results, this problem has hindered consensus in value assignments, the intercomparability of standardized

results across measurement networks, and the development of new and improved isotope measurement methods due to difficulty in benchmarking and validating performance. For

example, a 0.1 %o variation in the determination of 5

I3 C can translate to a variation (or misallocation) of 0.2 % in the apportionment of distinct carbon sources. In terms of the atmospheric carbon inventory, this variation could translate up to one PgC (10

15 g C), which would be the size of a regionally significant carbon source or sink. This report summarizes the results of a special intercomparison exercise which has also produced new NIST RMs. The goal of this exercise was to improve, by at least a factor of two, the uncertainties of value assignments for a suite of light stable carbon and oxygen isotope RMs

distributed by the IAEA and the NIST. This required designing a special intercomparison

exercise, which was initialized by the IAEA Light Stable Isotope Advisory Working Group in 1998. Incorporated into the design were mandatory procedures (Appendix 1) involving:

1 . standard conditions for the chemical derivation of CO2 from the RMs;

2. the use of a broad array of dual-inlet IRMS systems with triple collectors;

3. a specified sequence of replicated analyses to be performed within 24 hours (if possible)

against a single Working Reference Gas (WRG). The sequence was selected to minimize

the compositional differences between samples, thereby minimizing sample-to-sample

memory effects;

4. the fixed setting of instrumental parameters and CO2 inlet pressures during the analysis sequence;

5. the reporting of raw voltage ratios as well as c^CO^ and (546C02 measurements;

6. the direct measurement of the "cross-contamination" effect (Meijer et al., 2000) within each IRMS instrument during the analysis sequence, and;

7. the return of a questionnaire detailing laboratory discretionary procedures and the values of unrestricted variables.

7
Nine laboratories with internationally recognized expertise were invited to participate. The

Standard Reference Materials Program (SRMP) of NIST provided the participants with units of

the Reference Materials, while the Centrum voor IsotopenOnderzoek (CIO) Rijksuniversiteit Groningen provided isotopically enhanced samples of pure CO2 (GS-40). Additionally,

intercalibrated hydrometers were included for specific gravity measurement of the phosphoric

acid used for the carbonate digestions. The eight laboratories that reported data are listed in Table 1, while the suite of analyzed materials is listed in Table 2. Laboratory Performance Metrics The requirement for reporting raw d

A5C02 and <S46C02 data (against the working machine gas)

instead of reporting <5 13 C and e)

llS 0 values served to avoid biases from prior knowledge of value

assignments.

1 This precaution, combined with centralized data processing (Verkouteren and Lee, 2001) circumvented potential inconsistencies among data reduction algorithms and outlier rejection procedures.

NIST received measurement data from each laboratory in electronic form (Appendix 2). Data were merged into a spreadsheet and quality control checks were performed to identify and, with

the help of the participants, correct data inconsistencies. The basic 8-laboratory dataset (as an Excel file) is available at http://ww.cstlnist.gov/div837/837.01/outputs//NIMJCONI.xIs. Lab#8

had severe instrumental difficulties and was unable to run the specified analytical sequence of 49

samples. We have included their incomplete data here for comparison purposes, but have not used the data in the statistical evaluations beyond Figure 1 . The remaining dataset consisted of 343 sample runs of which 16 were missing due to lost samples.

After the data were validated, we compared ^COt and <546C02 measurement repeatability within

the laboratories for each RM (Figure 1). The medians of the average repeatability (standard

deviation) of tJ^CG^ and <546C02 measurements for each sample type were: 0.022 %o and 0.068 %o (waters); 0.033 %o and 0.049 %o (carbonates); 0.015 %o and 0.012 %> (carbon dioxides). We plotted measured voltage ratios for the WRG across the entire analytical sequence (Figures 2 and 3). These ratios are very sensitive indicators of the stability of conditions in each ion source. While gradual drift in these ratios is normal, abrupt shifts suggest that inlet pressures or ion source settings may have changed, or that the measurements were taken over extended periods. Under these circumstances, the degree of cross-contamination across the measurement sequence would also change, compromising our ability to correct for this effect. The average relative change between successive measures of a voltage ratio represents the degree of inconsistency in ion source conditions, represented by co (Eq. 4), where Z is the voltage ratio of m/z 45 to m/z 44

(n = 45) or m/z 46 to m/z 44 {n = 46), x is the total number of sample runs in the measurement

sequence (here, x = 43 for the full pre-GS-40 sequence), and /' is the run number. The co values

„ jo" y

[z, ~Z/-J Eq 4

Long-recognized is the "SRM Syndrome" (Byrne 1974), where analysts can succeed in repeating reported results, but fail when such samples are presented as blind unknowns.

8
for each laboratory are listed on the plots in Figures 2 and 3, as well as in Table 3. Values for Lab#7 were significantly higher than the other laboratories, and Lab#8 reported no voltage ratio

data. It is reasonable to assume that the values of co are proportional to the uncertainty of the cross-contamination coefficient, although the explicit relationship has not been determined. For now, we report the calculated values of co to indicate relative instability in the voltage ratios and

increased uncertainty in the cross-contamination correction, but do not use co to exclude data. In Tables 4A and 4B, we list raw J

45 C02 and (S46CC>2 measurements of the RMs versus WRG,

along with standard uncertainties (;/,) based upon measurement repeatabilities. These data were

then corrected for cross-contamination and standardized against the NBS19-C02 measurements

as described in the following section. Values of standardized <545C02 and <546C02 with uc greater than 0.2 %o were deemed too uncertain to include in subsequent calculations. These included all the measurements from Lab#8, all <T CO2 measurements from Lab#7, all LSVEC measurements

from Lab#l, and ^

6COi SLAP measurements from Lab#2 and Lab#4. These excluded data, however, were included in the subsequent statistical evaluation of the discretionary procedures.

Remaining data, consisting of 1 00 averaged results from 7 laboratories, were corrected for cross- contamination and processed into <5 I3 Cvpdb and<5

180VPDB.C02 results as described below. Calculations

Cross-Contamination Correction For e^CCh and eT^CO^ measurements in each instrument, cross-contamination correction factors

(745 and 746) were determined by using the isotopically-enhanced GS-40 gas between repetitions of the laboratory standard gas (LSG) near the end of the analysis sequence (Figure 4, plots A and

B). Mandatory procedures required that all samples be analyzed at a fixed inlet pressure and rri/z = 44 voltage, even though the m/z = 45 and m/z = 46 pre-amplifiers might saturate when

analyzing the GS-40 sample. Unfortunately, in three of the six laboratories, the inlet pressure was decreased (either manually or by automated control) to unsaturate these pre-amplifiers. This

action altered gas conditions in the ion source and prevented an accurate measure of the cross- contamination effect during the analysis sequence. Later, two of these laboratories were able to rerun a shortened sequence of the gases to allow reasonable estimates of the effect, although we

note that the level of cross-contamination may have shifted considerably during the delay. The

values of 745 and 746 were calculated through Equation 5:

nm = AZlRC /(AZlRG + AZ:s ) E^- 5

where: m is 45 or 46, signifying the minor m/z isotopomers of the ratio considered (against the m/z 44 isotopomer); AZwrg is the absolute difference in voltage ratio measurements of the working reference gas (introduced through inlet 2) before and during the GS-40 analysis; and AZes is the absolute difference in voltage ratio measurements between GS-40 and the laboratory standard gas (introduced through inlet 1). The calculated rj values were applied to correct the raw

^

45C02 and J

46C02 values (as measured against the working reference gas) as follows (Meijer et al.,2000): SL = (SD/V - 2rj

m - rjJU Eq-6

9
N18 !' Spc

One laboratory (Lab#l ) had no appropriate measurements of the GS-40 material. The 7745 and 7746 values were therefore determined through that laboratory's measurements of RM 8562

referenced to RM 8563 (Eq. 7). This required knowledge of the true differentials in the RM

values, which are consistent with this exercise and verified by subsequent measurements at NIST.

nm = —-n— Eq- 7 s M+s1)

Standardization

Tables 5A and 5B list the cross-contamination corrected J^CGb and (T CO2 measurements

versus WRG. These corrected measurements were standardized against the corrected NBS19-

CO2 measurements through Eq. 8, the results of which are listed in Table 6A and 6B.

(S'" IIWRC +0 C o X" =

v ""'/l/r " /< '' _ 1 Eq. 8

Usample/NBS 19.C02 , r.m . NBS\9.C02/WRG ' The standardized values in Tables 6A and 6B are the primary measurement-based results of this exercise. While corrected for cross-contamination, they are entirely independent of assumptions

regarding oxygen isotope relationships, fractionation constants, and the definition of the VPDB

scale. After this point, assumptions were applied to relate these measurements to the VPDB-CO2

scale, to convert the measurements to S UC and <5 18 0 values, and to correct the VSMOW and SLAP results for gas dilution effects.

Conversion

The standardized measurements were related to the VPDB scale through Eq. 9, where

^nbsiq.cto/vpdb.coz and ^

46nbsi9.co2/vpdb.co2 are defined as +1.75637 %o and -2.19377 %o, respectively (Allison, Francey and Meijer 1995). Values of <5 13 Cvpdb and <S i8 Ovpdb.co2 were then

dsample/VPDB.COl ~ ^SXllmplc/NBS\9.C02 + ^ NBS19.C02/VPDB.C02 + ^ ^ Eq. 9

calculated through the internationally accepted algorithm, which was facilitated through a Webbased data processing tool (Verkouteren and Lee, 2001). Implicit in the definitions of

<5m

NBSi9.co2/vPDB.co2 and the IAEA algorithm were several assumptions that were applied

consistently. These included the following:

• S nC (NBS19 vs VPDB) = 1.95 %o exactly

• t$ 18 0 (NBS19 vs VPDB) = -2.20 %o exactly

• «

1S co2-nbsi9 = «' 8 co2-vpdb = 1.01025 (see Eq. 2)

• tf

18 co2-vsMow = <2I8 co2-slap = 1.0412 (see Eq. 2)

• A =0.5 (see Eq. 3)

•

]7Rrct= 0.000378866601, 187?rcf = 0.002067160680 (ref = VPDB-calcite, Allison et al., 1995)

10
Gas Dilution Correction

Finally, to compensate for the gas dilution effect in the water samples, the VSMOW and SLAP

delta values were corrected through Eq. 10 (Craig 1957), where /?is the mole fraction of water to CO? used in the isotope exchange, a is the isotope fractionation factor for oxygen- 18 between CO2 and H2O at the temperature utilized (Brenninkmeijer et al., 1983), and e) ls O(gas) is the

original delta value of the CO2 gas used in the exchange. For VSMOW, this correction ranged from 0.01 %o to 0.06 %o (p values from 920 to 185). For SLAP, the correction amounted to -0.03 %o to -0.25 %o.

S^O(corr) = \ +

«

d nO -

a

S

l *0(gas) Eq. 10 P _ _P_

Unrestricted Variables.

In addition to the measurement data, each laboratory completed a questionnaire regarding

discretionary chemical and instrumental procedures (Appendix 3). This information was used to evaluate over 30 unrestricted variables (Table 7) that may have influenced the reproducibility of

the measurements. There were three important types of unrestricted variables: reported numerical measurements and settings (CODE = R); values calculated from reported measurements (CODE

= C); and interpreted procedural differences (CODE = I). For this last type, integer values were

assigned based upon the differences among procedures used in each laboratory. Correlation

analysis and Principal Components Analysis (PCA) were then used to explore the relationships among the unrestricted variables and the measurement results. To simplify and improve the

interpretation of PCA, matrices were selected to explore cohesive subsets of the variables and

results. Results and Discussion

Outliers Among the 100 standardized RM results, there was a single 2-sigma outlier (<5 18 0 of VSMOW,

Lab#4); this outlier had a procedural explanation (see discussion of Effects from Unrestricted Variables - Water Samples, p. 13- 14). The scarcity of outliers can be attributed, in part, to the

expertise of our selected participants, and to the pre-exclusion of data based on instrument performance standards. By comparison, the Stichler (1995) exercise, an intercomparison that included many of these materials, reported 139 results (plus 15 missing values). In this earlier exercise, eleven of the reported results were identified as 2-sigma outliers, with another six flagged in sequential 2-sigma determinations. That study was designed partially as a learning

exercise, where participation was open and a greater range of expertise was represented. However, the resulting dispersion of the results created difficulties in data evaluation. Without

performance standards it is difficult to justify the exclusion of outliers, yet, the consequence of

including them are uncertainty bounds that prevent precise value assignments. The scarcity of

outliers was therefore an important benefit of our exercise. Cross-Contamination Coefficient

In this exercise, the determinations of the r/45 and 7745 values were not completely

straightforward. Inspection of plots in Figures 2 and 3 show that the perturbations to the WRG

voltage ratios from the repeated GS-40 analyses (Run Sequence 44-46) frequently exhibited an

1 1
approach to a new equilibrium. This suggests that source gas loading and outgassing behavior

(hence the cross-contamination effect) had a time component much greater than the dual inlet switchover idletime (Verkouteren et al, 2003a). This complicated the cross-memory

determination, so we used those replicated measurements that were closest to the new

equilibrium and which maximized the AZwrg and fj values; relative uncertainty of the r/ values is estimated at 30%. Comparison of /74s and i]m, values, calculated for all laboratories using the GS40 and RM methods, also shows some discrepancies. Some rj values determined by the RM

method are negative, which may arise as artifacts from measurement uncertainty, but also may

suggest that the cross-contamination model only partially explains the dispersion in the data. This deserves further investigation. For now, we consider the GS-40 results as the best estimation of the cross-contamination effect. The cross-contamination coefficients determined

for each instrument are listed in Table 3. Generally 2-7745 « 7745, although there are exceptions: in Lab#4 the values are comparable, while in Lab#5 the 7746 value exceeded 7745 by about a factor of

nine. This could reflect high water levels in the leaks or ion source, which could increase the cross-memory of m/z 46 preferentially. Lab#5 reported that their source had not been cleaned for two years, which may have contributed to the observed behavior. Results Cross-contamination corrections ranged from -0.01 %o to -0.33 %o among results from individual

laboratories. Corrections to the averaged results were very consistent, amounting to 0.0018/A 13 J

and 0.0035/A 18 £ where AS was the difference between the delta values of the sample and NBS19-C02. These averaged corrections ranged from -0.00 %o to -0.20 %o. In every case, the corrected <5 13 C and e>' 8 0 values were more negative than the previously accepted reference values

(included in Table 8 for comparison purposes). While a negative shift was expected from the correction for cross-contamination, this factor was only partially responsible for the total corrections. We cannot attribute the remainder of the shifts to any specific factor, but are confident that some combination of the specific chemical and instrumental protocols and

centralized data processing was responsible.

Average corrected <5 I3 C and e) 18 0 values and standard uncertainties are given in Table 8. The mean d

l3C and (5 I8 0 values from this exercise are well within the 2-sigma band of the previous

reference values. Generally, the uncertainties of the new values are much improved (in some

cases reduced by over a factor of two) over the previous uncertainties. The uncertainties for the CO2 RMs remain essentially unchanged since the prior determination (Verkouteren, 1999) had

already minimized the cross-contamination effect. Other Comparisons

Comparison of the CO2 RM value assignments with those proposed through Meijer et al. (2000)

deserves comment. Those proposed values, based on the measurement data from the 1997

intercomparison (Verkouteren, 1999), were generated under the assumption that the observed

dispersion in the data was due entirely to the varying contributions of cross-contamination in each analyzing instrument. This cross-contamination model (CCM) predicted values, especially

for the materials isotopically depleted against NBS19-C02, which were beyond the most

negative values collected in the 1997 exercise. While we had recognized that a consensus mean

would not be an accurate assignment for any of these materials, our measurements of the difference in compositions among the CO2 RMs using self-consistent <545 C02, ^COj, and

(547C02 measurements supported only modest corrections in the consensus means. In part, this current exercise was designed to resolve the discrepancy.

12
Here, we have found that the prior assignments for c> 13 C in the CO2 RMs have been justified, with minor adjustments within the original uncertainty bounds. All values for d

l *0 have been

shifted by about -0.1 %o, due mainly to an improved realization of the VPDB oxygen- 18 scale. The new value assignments are now based upon consensus means that consider the contributions from cross-contamination. We believe that the CCM, which was a reasonable attempt at improving value assignments, was limited by its application to our data from the 1997

intercomparison. These data were "best results" of measurements made at each participating

laboratory, where no information was collected regarding the variation in ion source conditions

or time needed to complete the measurements. As such, it is extremely unlikely that fixed cross- contamination coefficients could be applied accurately to all data reported from any laboratory. Secondly, there were unverifiable factors other than cross-contamination, such as the balance and

control of fractionation between the leaks, preparation of NBS19-C02, and data reduction, which

could lead to scale shifts or expansion rather than the simple scale contraction assumed in the CCM. The uncertainties expressed from the application of this model were based on the fit of the

data, but were not comprehensive in the evaluation of other potential contributions. Effects from Unrestricted Variables

Visual inspection, correlation analysis, and multivariate evaluation of relationships between the discretionary variables and the standardized results - both corrected and uncorrected for cross- contamination - were performed to identify and explore possible factors of significance. While

these evaluations were severely limited by the large number (N > 30) of unrestricted variables and the small number (N = 7) of reporting laboratories, some patterns were evident. Effects on

water samples (VSMOW, SLAP), carbonate samples (NBS-18, LSVEC, IAEA-CO-9), and C02 samples (RM 8562, RM 8563, RM 8564) will be discussed in turn. Water Samples. Results for VSMOW and SLAP exhibited the largest and most interpretable dispersions. The amounts of CO2 and water used in the isotope exchange process, as well as the amount of time allowed for isotope exchange, were determining variables. We have plotted all water data in the two plots of Figure 5, including those data earlier excluded on the basis of

performance standards. Dashed lines denote accepted values. Error bars indicate standard

uncertainties of the <5 18 0 results, but do not include influences from unrestricted variables.

Plot A of Figure 5 shows VSMOW-C02 results referenced to VPDB-C02 , along with water-C02 exchange time (abscissa) and amount of C02 used (proportional to shaded bubble size). Data in

this plot indicate the degree of closure attained between the VPDB and VSMOW oxygen- 18

scales. The one outlier in the exercise (result of Lab#4) had the shortest exchange time (5 hours). This exchange time is 1 1 hours shorter than the next smallest time. The results from Lab#2 and Lab#7 were characterized at the lower extreme of C02 amount, and both values were biased from the accepted value by 0.3 %o to 0.4 %0 . The remaining results (Lab#l, Lab#3, Lab#5,

Lab#6) precisely clustered on the accepted value, and were similar in the amounts of C02 and

times used in the isotopic exchange.

Plot B of Figure 5 shows SLAP-C02 results referenced to VSMOW-C02 (these are the only

results reported in this report that are independent of the NBS19-C02 measurements). Data in

this plot test consistency with the IUPAC-accepted value of e) I8 0 SLAP = -55.5 %o used to define the VSMOW/SLAP normalized scale. Water-CO? exchange time is plotted along the

abscissa, with unshaded bubble size proportional to the reported H2 0/C02 molar ratio. Results of

three labs (Lab#2, Lab#4, Lab#7) had been excluded by the performance standard of

repeatability (uc > 0.2 %o) but are included here. No results were statistically equivalent with the

13
[UPAC value. In contrast, the precise cluster of results from Lab#l, Lab#3, and Lab#5 give a

6> ls 0 SLAP value of-56.18 %o (u\ = 0.01 %o), which is also supported by the (excluded) result of

Lab#2. The relatively short times (5 h) used for H2O-CO2 isotopic exchange in Lab#4 may have

influenced r)' l8 0 values and repeatability. After 16 h at 25 °C with agitation, equilibration is indicated by the consistency of the Lab#l -Lab#3-Lab#5 cluster. We note that while Lab#6 used

a 25 h exchange time at 25 °C, they did not agitate the H2O-CO2 mix. This lack of agitation may

be significant: Lab#2, which used amounts of water similar to Lab#6 and no agitation, achieved

a <S 18 0 value consistent with the Lab#l-Lab#3-Lab#5 cluster after 48 hours. The difference between the accepted value of <5 I8 0 SLAP and that determined by the Lab#lLab#3-Lab#5 cluster is -0.68 %o, and cannot be explained simply by the correction from cross- contamination, the average of which was -0.20 %o. With the precise result of Lab#6 averaged

into the cluster, the mean becomes -56.07 %o (u\ = 0.22 %o), which still is significantly different

(at the 95% level of confidence) from the accepted value of -55.5 %o. Results suggest that the

true value for (5 lx O SLAP vs VSMOW lies between -55.7 %o and -56.2 %o. The averaged water

results in Table 8 include Lab#6, but we recommend that future intercomparison exercises

specify that exchange times be greater than 16 hours and that agitation be utilized. Carbonate Samples. The repeatability of carbonate <545 C02 measurements was strongly

correlated with sample size, although the correlation disappeared for ^COi measurements. This

is illustrated in Figure 6 for NBS19-C02 measurements against WRG. Since the VPDB scale is directly realized through measurements of NBS19-C02, this link in the traceability chain affects the combined uncertainty of all e) 13 C and <5 18 0 results. Our results suggest that using carbonate sample sizes of at least 20 mg would minimize uncertainty in <5 13 C. A specific question for the exercise was to determine whether the range in specific gravity of the various phosphoric acids would affect the <S 18 0 results. Through reported measurements in the

distributed hydrometers, specific gravity of the phosphoric acids ranged from 1.90 to 1.95, corresponding to 102.3 to 106.5 "%H3 P04" (Wachter and Hayes, 1985). In Figure 7, we plot the ^

8 0 values of RM 8562 and NBS-I8-CO2 against the specific gravity of the acid. We include

the non-carbonate RM 8562 since all results are standardized against CO2 generated from NBS19 carbonate digestion. A specific gravity effect may therefore not appear in carbonates but may manifest itself in non-carbonates. However, no significant correlations were apparent for any of the samples and we conclude that the range of phosphoric acid compositions did not

influence the results. Results of NBS-I8-CO2, IAEA-C09-C02, and LSVEC-CO2 exhibited moderate interlaboratory

variation (combined standard uncertainties of 0.03 %o to 0.19 %o and 0.07 %o to 0.21 %o for <5 I3 C

and <5 18 0, respectively). We wished to identify factors most responsible for this variation. For

this purpose, we performed PCA on a data matrix consisting of the unrestricted variables under

the categories of "Phosphoric Acid" and "Acid/Carbonate Reaction" (Table 7), and against each

of the dependent variables (<5 13 C and <5 180 results for NBS-I8-CO2, IAEA-C09-C02 , and LSVEC-CO2). Our strategy was to look for consistently high correlations between the principal components (eigenvectors) and each candidate response variable, then identify the variables of

highest loading (or weights) in these eigenvectors that had the largest explanatory power for response.

14
While the PCA results for each material indicated a particular pattern of influencing variables, these patterns were only moderately consistent across the carbonate materials and did not point

to any one factor as being of major significance. For example, variations in LSVEC and IAEACO-9 results, which are similar in <5 I3C value, were nearly equally influenced by sample size, amount of acid used, the volume of the reaction vessel, and the duration of the reaction, contrasted with the specific density of the acid. On the other hand, the <5 I3 C results of NBS-18

were influenced more heavily by the amount of acid, and contrasted with the sample size and volume of reaction vessel. Of possible interest was the observation that the specific density of the acid had a marginally stronger influence on (5 I3 C results uncorrected for cross-contamination. PCA on the S

l O results for the carbonates exhibited a large level of randomness. We draw the conclusion that no particular unrestricted variable was important to the e) 13 C and S

ls O results of

the carbonates in this study. This is quite plausible given that all carbonate results were

standardized to the NBS 19-CO: results, so carbonate-specific factors could have been

diminished. C02 Samples. RM 8562, RM 8563, RM 8564, and LSG were generally the most repeatable and most reproducible samples, an observation anticipated from the absence of chemical processing.

Results of these materials were useful for exploring the variables of the measurement process.

First, we investigated suspected bivariate relationships by plotting the most variable S nC and

d

ls O results (RM 8563) against the composition of the WRG (Figure 8) and against instrument

sample-reference switchover time (Figure 9). Also in Figure 9, we plotted results corrected and

uncorrected for cross-contamination. No obvious dependencies were evident. The corrected

results were marginally less variable than the uncorrected results, and the cross-contamination

effect and variability seemed to be a minor component of the total variability. We had anticipated otherwise. Another factor seemed to be responsible for the observed variability. We investigated all "Inlet" and "Measurement

1

' variables in Table 7 using PCA as detailed in the section on Carbonate Samples. We compared the corrected and uncorrected results for RM 8563, which exhibited the greatest variation. This PCA analysis indicated that uncorrected <5 I3 C and

<S I8 0 results exhibited strong negative correlations with eigenvectors heavily weighted by

combinations of "time" variables (evacuation time, idle time, and integration time) and exhibited

positive correlations with acceleration voltage. These correlations essentially disappeared in the corrected dataset. These observations are explained below.

In some instruments, higher accelerating voltages are used to increase m/z resolution and

sensitivity. However, accelerating voltage is also known to influence the amount of ion-induced

sputtering in an ion source, which augments cross-contamination and sample-to-sample memory.

In this exercise, we corrected for the cross-contamination that acted across the sample-reference

gas switchover times (idle time plus integration time). Indeed, the dependencies noted in the variation of RM 8563 results with accelerating voltage and measurement times disappeared when

cross-contamination was taken into account. There remains our attempt to explain the observed variation in the corrected RM results. PCA

suggests that single eigenvectors (i.e., factors) explained more than 80% of the variation. For

<S I3 C, the instrument model appeared to be the most important factor; for e) 18 0, the three "time"

variables mentioned above were most important, followed closely by the specific gravity of the phosphoric acid used to prepare the NBS19-C02 used for standardization. While these results are suggestive, they are not compelling since variables of measurement would be expected to act

15
fairly consistently across all materials and delta values. This consistency was not observed so we

judged that the PCA was inherently limited by the small variation in results, the small number of

laboratories, and the large number of variables. We also consider that the major source of the variation was either not considered in our set of unrestricted variables, or that the metrics used were inadequate to accurately characterize the influential factor. IR.MS instruments are dynamic systems where the levels and compositions of background are constantly changing. The specific method each laboratory used to measure and compensate for the changing background was discretionary, but we did not collect detailed information on this factor. Future exercises should consider this potentially significant factor more carefully. Memory and conditioning effects in IRMS systems can have half-lives of a few minutes

(Verkouteren et al., 2003a), which are not fully compensated by corrections for short-term cross- contamination or long-term background. We attempted to control these mid-term effects through

the experimental design, which included a specified analysis sequence with replication (n = 2 to 5) and short total duration (24 hours if possible). We were only partially successful in compensating for mid-term effects, which cause delta measurements to be influenced by the composition of the prior sample; this was noted frequently in the exercise. We also noted that the observed voltage ratios of the WRG tended to drift in one direction during the analysis sequence, and to shift during breaks in that sequence. These breaks could be short, such as extended

evacuations between certain samples, or longer due to practical considerations by the analyst. In any case, there were inherent limitations in our attempt to control ion source conditions during

the entire analytical sequence, which was needed to optimize the standardization procedure and

to enable a representative measurement of cross-contamination. This limitation may have played

a role in the observed variation of sample results. The performance metric co was formulated to measure this limitation across the analysis sequence. NIST Measurements

By measuring 5

47CC>2 along with S

45 C02 and 846C02, measurement accuracy may be tested. The

measured 8

47 C02 value will be identical statistically to the expected S47CC>2 value (as calculated from 8

45 C02 and 846C02) when all three measurements are accurate, a condition difficult to

satisfy in the presence of cross-contamination. Accurate measurements, as verified by this technique, became possible only after improvements were made to the ion source of the NIST

instrument (Verkouteren et al., 2003b). Additionally, an idletime of at least 60 seconds and a

fully opened Variable Ion Source Conductance (VISC) window were necessary to eliminate

significant sample-reference cross-contamination. The detector array was configured for measurement of the m/z 44, 45, 46, and 47 ion beams, using resistors of 30 Mf2, 3 GQ, 10 Gf2, and 1 TQ, respectively. About 28 kPa of inlet pressure was needed to generate a 4 volt (or greater) signal across each resistor. Operating pressure in the ion source was about 50 uPa and

instrument response was linear up to this level. The precision limit (standard uncertainty) due to shot noise (Merritt and Hayes, 1994) was 0.004 %o, 0.006 %o, and 0.056 %„, for 8

45 C02 , 546C02 , and 8

47 C02 respectively, which was closely approached in measurement repeatability. Since the

16
ThermoFinnigan2 MAT 252 signal acquisition system (ISODAT version 6.1) was configurable to measure only three beams (two ratios) simultaneously, methods were used that alternated repeatedly between two detector configurations: [8

45 C02 + 8

46C02 ] and [845 C02 + 547 C02 ]. Replicated measurements of 8

45 C02 , 546C02 , and 547 C02 among three laboratory standard gases (LSG) and the three RMs are listed in Table 9. The 5

47C02 value expected from accurate measurement of 8

45 C02 and 8

46C02 was calculated by numerical methods and compared to the observed value. In all cases, the calculated 8

47C02 values were statistically equal to the measured

values, verifying the accuracy of the measurements. The 8

45 C02 and 846C02 values (and

uncertainties) between the RMs were calculated through Eq. 1 1, where m = 45 or 46, x = 3 or 4, and y = 2.

RMS56x vs. RM$56 v

( SRMS56xvs.LSGx + ]

>

' (S

LSGx vs. LSGv

1) - 1 ^RM%56v vs. LSGv + ^ ^LSGv vs. LSGv + ^

Eq. 11

With the compositional differences (A8) among the three RMs accurately characterized,

realization of the VPDB scale was made through the intercomparison results using RM 8562 (for S

I3 CVPdb) and RM 8564 (for 8

,8 0vpdb.co2)- These RMs exhibit the best interlaboratory

reproducibility, and are closest in composition to NBS 19 C02 , the primary reference material. For 8

13 Cvpdb in RM 8562, the value of -3.76 %o was assigned. This value was considered the best estimate of the true value because: 1) it represents the consensus mean of S

13 Cvpdb values

corrected for cross-contamination, and 2) this value was identical to the value determined

through another intercomparison exercise (Verkouteren 1999). For 8

18 Ovpdb.co2 in RM 8564, the value of -10.06 %o was assigned because: 1) this represents the consensus mean of S

18 Cvpdb co2 values corrected for cross-contamination, and 2) this value is consistent within the uncertainty of

the value previously assigned through the original intercomparison exercise (Verkouteren 1999). Through these assignments and the NIST AS measurements, the values of the remaining delta values were thereby determined and assigned; these are listed in Table 8. The combined standard

uncertainty (uc) of each assignment includes the uncertainty (standard deviation) in the defining

RM, the standard deviation of the A845 C02 and A846C02 measurements, and the known sampleto-sample isotopic variation combined in quadrature. In all cases, the value assignments of the CO: RMs are within the uncertainty of results reported in the prior and current

intercomparisons. As a result, all assigned values may be considered consensus values, with

uncertainties improved by the NIST measurements. Algorithm Considerations

Appendix 4 contains individual laboratory results calculated from measurement data in Table 6

using four different sets of fundamental assumptions regarding oxygen isotopes. Besides measurement data, an algorithm must fix two independent variables, X and 17 Rref (see Eq. 3).

" Certain commercial equipment, instruments, and materials are identified in this paper to specify adequately the experimental procedure. Such identification does not imply recommendation or endorsement by the National

Institute of Standards and Technology, nor does it imply that the materials or equipment identified are necessarily the best available for the purpose.

17
These may be recast into two interdependent variables X and K, where K =

17Rref/( 18 Rref)A

' and

l8Rref is usually taken from Baertschi (1976) for VSMOW or Allison et al. (1995) for VPDB.

Table 10-A (in Appendix 4) contains results using the IAEA-recommended values of A,=0.5 and

K=0. 0083330 (Assumption Set A). As results of this intercomparison are the most precise to date, they directly expose the well-known problem of interdependence of 5

I3 C and 5

lx O values

calculated using these assumptions, and exhibited in the S

13 C values of VSMOW-CO2, SLAPCO2, and LSG. These values should be identical within any laboratory, but differences of 0.1 %o

to 0.3 %o are the result in this exercise. This long-standing issue has been tolerated to preserve long-term historical intercomparability of 5

I3 C values in the literature, and this is a valid reason

to continue the practice. However, we also note that use of this set of assumptions compromises

the ability to use

13 G as a conservative tracer in high-precision applications, such as in atmospheric chemistry and forensic studies, since 5

I3 C values calculated through Assumption Set A are influenced by the oxygen composition of the CO?. This is also an intercomparability issue, and a concern with CO2 samples collected across latitudes and altitudes where oxygen isotopic compositions are highly variable, and in laboratory settings where carbonaceous materials are combusted with oxidants having different oxygen compositions.

We recalculated 5

I3 C and 8I8 0 values using other assumption sets. In Appendix 4, Table 10-B

uses ^ = 0.516 (Matsuhisa et al., 1978) and I7 RV sm<>w = 0.0003799 (Li et al., 1988). Table 10-C

uses X = 0.516 and I7 RVS mow = 0.000402326 (Santrock et al., 1985), and Table 11-D uses

A,=0.528 (Meijer and Li, 1998) and 17 RVS mow = 0.000386913 (Assonov and Brenninkmiejer,

2002). In each table, the degree of similarity of the 8

I3 C values for VSMOW-C02 , SLAP-CO2,

and LSG in each laboratory is determined by two simple methods: 1) The difference between

o

I3 CVpdb(VSMOW-C02 ) and 5I3 CVpdb(SLAP-C02 ) (= Fit Coeff.l), and 2) standard deviation of

the mean of 5

I3 CVpdb(VSMOW-C02 ), 5I3 Cvpdb(SLAP-C02 ), and oI3 CVpdb(LSG) (= Fit Coeff.2). We then pooled results that passed the measurement performance criteria for these data (from Lab#l, Lab#3, Lab#5, and Lab#6). We added the Fit Coeff.l values, and averaged the Fit Coeff.2 values. Pooled Fit Coefficients approaching zero indicated the set of assumptions that minimized the co-variance of 8

13 C and 818 0 values across the laboratories. From inspection of the fit coefficients, one fact is clear: the assumption set that is currently recommended by the IAEA leads to significant and systematic co-variance of 5

I3 C and 518 0

values. This co-variance can be reduced by applying other assumption sets. Assumption Set D is marginally better than the other sets, and while inconsistencies exist in individual laboratories, these tend to average out across the participants. Conclusions

Through this exercise, we have made tangible progress in understanding and controlling the fundamental factors that influence the accuracy and reproducibility of high-precision isotope

ratio measurements, and have improved the value assignments of Reference Materials used to standardize isotope measurements for many applications. This accomplishment was made

possible through the commitment of many individuals and organizations in a designed exercise having strict sample preparation and measurement protocols, and where IRMS performance

criteria were used to filter data. This was the first exercise to take raw measurement data from

the participants and centrally process this data into standardized results. This was also the first exercise to correct for cross-contamination. For most of the materials, value assignments were

18
shifted in part due to the cross-contamination correction, with uncertainties improved by factors up to two over the previous assignments.

In order to explain the observed variation among standardized delta values, statistical approaches were used to discern relationships between these results and the reported values of unrestricted

variables. For VSMOW and SLAP, the relative amounts of CO2 and FLO, exchange time, and

presence of agitation during the isotope exchange process were found to relate with the variation

in the S

l80 values. For the carbonate and CO2 RMs, however, we show that no monitored

variables were responsible for the variation observed across the RMs. While this is most likely a

result of the small number of laboratories, the small variation in results, and the large number of

unrestricted variables, we also consider that latent factors may be responsible. One possibility is mid-term memory that is difficult to model and correct. Subtle effects from differences in background corrections could also be present.

Lastly, we showed that the oxygen isotope assumptions in the algorithm used to convert 8

45 C02

and 5

46C02 measurements to 5

I3 C and 5I8 0 values influenced the level of undesired covariation

in the 8

I3 C and 5

I8 0 values. Four assumption sets of K and X values were tested on the data. The

currently-accepted set led to the largest covariation, whereas other sets generally minimized the covariation across the data. Recommendations

1. To minimize uncertainty in the realization of the VPDB scale, samples of NBS19 carbonate should be greater than 20 mg and the amount of phosphoric acid should be at least 2 mL. The

specific gravity of the phosphoric acid should be equal or greater than 1.90 and the digestions

last 6 h to 24 h at temperatures between 20 °C and 25 °C.

2. For water-RMs, we recommend that at least 1 mL FLO be equilibrated with an amount of CO2 where the H2 0/C02 molar ratio is greater than 200. Agitation for at least 16 hours at 25 °C should be allowed for each equilibration. Under these conditions, we recommend that future exercises revisit the composition of SLAP vs VSMOW, and include other relevant samples such as RM 8536 (GISP: Greenland Ice Sheet Precipitation).

3. The value assignments reported here are based upon R13vpdb = 0.0112372000, R18vpdb.co2 = 0.0020883491, and X = 0.5. Should other values become internationally accepted, then the value assignments of the RMs must be recalculated (from data in Tables 6A and 6B; see Appendix 4) to remain consistent with these definitions. Debate of issues relevant to this change is recommended. Towards making informed decisions, efforts should be made to enable and preserve intercomparability of literature values with isotope ratio scales (e.g., through conversion expressions, co-reporting results, explicit traceability, etc). 4. The design of future intercomparison exercises of light stable isotope RMs should consider:

• reporting raw measurements as well as best results through data evaluation at each

laboratory.

• reporting the method for background measurement and subtraction.

• centralized data processing for consistent standardization, conversion, and data filtration based on accepted standards and performance criteria.

19
correction for cross-contamination using isotopically enhanced or depleted materials. The

composition should be set so that the signals from the Faraday cups do not become

saturated under th gas inlet conditions.

collection of information on chemical and instrumental variables and the use of

multivariate methods to link variation of results with specific factors. analyzing a sequence of materials by dual-inlet IRMS that would include RMs designed

for GC-IRMS and EA-IRMS, such as RM 8567 (caffeine), RM 8568 (KN03 - low l8 0), RM 8569 (NaN03 - high

17 0 and l8 0), RM 8573 (L-glutamic acid - normal l3 C and l5 N), and RM 8574 (L-glutamic acid - high l3 C and l5 N).

20
References

Allison, C. E.; Francey, R. J.; Meijer, H. A. J. (1995) Recommendations for the reporting of stable isotope measurements of carbon and oxygen in C02 gas. In: Reference and Intercomparison Materials for Stable Isotopes ofLight Elements; IAEA-TECDOC-825; IAEA: Vienna, pp. 155-162. Assonov, S.S. and Brenninkmeijer, C.A.M. (2003) A redetermination of absolute values for R-17(VPDBC02)and R-17(VSMOW). Rapid Commun. Mass Specfrom. 17, 1017-1029.

Baertschi, P. (1976) Absolute

lsO content of standard mean ocean water. Earth Planet. Sci. Lett. 31, 341-344.

Brenninkmeijer, C.A.M., Kraft, P. and Mook W.G. (1983) Oxygen isotope fractionation between C02 and H2 0. Isotope Geoscience 1, 181-190. Byrne, F.P. (1974) Introductory Statement. Some Fundamentals of Analytical Chemistry, ASTM STP 564, American Society for Testing and Materials, pp. 1-5. Craig, H. (1957) Isotopic standards for carbon and oxygen and correction factors for mass-spectrometric

analysis of carbon dioxide. Geochim. Cosmochim. Acta 12, 133-149.

Hut, G. (1987) Consultants' Group Meeting on Stable Isotope Reference Samples for Gcochemical and

Hydrological Investigations. IAEA Report, 16-18 September 1985, Vienna: Austria. ISO (1993) Guide to the Expression of Uncertainty in Measurement, First edition, ISBN 92-67-10188-9,

International Organization for Standardization: Switzerland.

Li, W.J., Ni, B.L., Jin, D.Q. and Chang, T.L. (1988) Measurement of the absolute abundance of oxygen- 17 in VSMOW. Kexue Tongbao (Chinese Science Bulletin) 33, 1610-1613.

Matsuhisa, Y., Goldsmith, J.R. and Clayton, R.N. (1978) Mechanisms of hydrothermal crystallization of

quartz at 250 °C and 15 kbar. Geochim. Cosmochim. Acta 42, 173-182.

Meijer, H.A.J, and Li, W.J. (1998) The use of electrolysis for accurate 5

i7 0 and 5I80 isotope measurements in water. Isotopes Environ. Health Stud. 34, 349-369.

Meijer, H.A.J., Neubert, R.E.M., Visser,G.H. (2000) Cross-contamination in dual inlet isotope ratio mass

spectrometers. Int. J. Mass. Spec. 198, 45-61.

Merritt, D.A. and Hayes, J.M. (1994) Factors controlling precision and accuracy in isotope ratio monitoring mass spectrometry. Anal. Chem. 66, 2336-2347.

O'Neil, J.R. (1986) Appendix: Terminology and Standards. In: Stable Isotopes in High Temperature

Geological Processes, Reviews in Mineralogy 16, 561-570.

Stichler W. (1995) Interlaboratory comparison of new materials for carbon and oxygen isotope ratio measurements. In: Reference and Intercomparison Materials for Stable Isotopes ofLight Elements; IAEA- TECDOC-825; IAEA: Vienna, pp. 67-74. Verkoutcrcn, R.M. (1999) Preparation, characterization, and value assignment of carbon dioxide isotopic reference materials: RMs 8562, 8563, and 8564. Anal. Chem. 71, 4740-4746.

Verkouteren, R.M. and Lee, J.N. (2001 ) Web-based interactive data processing: application to stable isotope metrology. Fresenius J. Anal. Chem. 370, 803-810.

Verkouteren, R.M., Allison, C.E., Studlcy S.A. and Leckrone K.J. (2003a) Isotopic metrology of carbon

dioxide. I. Interlaboratory comparison and empirical modeling of inlet equilibration time, inlet pressure, and

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Verkouteren, R.M., Assonov, S., Klinedinst, D.B. and Brand, W.A. (2003b) Isotopic metrology of carbon

dioxide. II. Effects of ion source materials and conductance on dual-inlet cross-contamination. Rapid Commun. Mass Spectrom. 17, 777-782. Wachter, E.A. and Hayes, J.M. (1985) Exchange of oxygen isotopes in carbon dioxide-phosphoric acid systems. Chem. Geol. (Isotope Geoscience Section) 52, 365-374. Werner, R.A. and Brand, W.A. (2001) Referencing strategies and techniques in stable isotope ratio analysis. Rapid Commun. Mass Spectrom. 15, 501-519. 21
Table 1. Participants of the NIST-IAEA Measurement Intercomparison

for Stable Carbon/Oxygen Isotope Ratio Measurements

Laboratory Personnel

National Hydrology Research Institute Len Wassenaar and Geoff Koehler Environment Canada

Saskatoon, Saskatchewan, CANADA

Isotope Hydrology Laboratory Manfred Groening, Ahmad Tanweer,

International Atomic Energy Agency Liliana Andreescu, Michael Van Duren

Vienna, AUSTRIA

Ldooraiory oi isotope oeoiogy 1 lpillg LMIlg, rvUl-lllCl Dal, .1 111-LIlCIlg 1^1 Chinese Academy of Geological Sciences

Beijing, CHINA

Maria Curie - Sklodowska University Stanislaw Halas

Lublin, POLAND

Centrum voor IsotopenOnderzoek (CIO) Harro A.J. Meijer, H.G. Jansen, J.J. Rijksuniversiteit Groningen Spriensma, R.E.M. Neubert

Groningen, THE NETHERLANDS

Laboratory of Stable Isotopes Matthias Gehre, Petra Bluemel,

UFZ-Umweltforschungszentum Leipzig-Halle Martina Neuber

Halle, GERMANY

Biogeochemical Laboratories Arndt Schimmelmann, German Mora,

lllUluIld vJlllVCIaliy jicvc oiuuicy

Bloomington, Indiana, USA

United States Geological Survey Sample preparation (USGS): Tyler

Reston, Virginia, USA Coplen, Jessica Hopple

National Institute of Standards and Technology IRMS measurements (NIST): Mike

Gaithersburg, Maryland, USA Verkouteren, Donna Klinedinst Order of laboratories has been randomized and does not reflect laboratory numbers identified

in this document.

22
Table 2. Materials Used in the Intercomparison Exercise

Carbonates

RM 8544 (NBS 19) Limestone RM 8543 (NBS 18) Carbonatite RM 8545 (LSVEC) Lithium carbonate RM 8566* (IAEA CO-9) Barium carbonate Waters

RM 8535 (VSMOW) Vienna Standard Mean Ocean Water RM 8537 (SLAP) Standard Light Antarctic Precipitation Carbon Dioxides

RM 8562 (Heavy, Paleomarine Origin)

RM 8563 (Light, Petrochemical Origin)

RM 8564 (Biogenic, Modem Biomass Origin)

GS-40 (Isotopically-Enhanced Material) LSG (Individual Laboratory Standard Gas)

* RM 8566 is not yet distributed by the NIST

23
Table 3. Selected Performance Metrics

Lost or WRC Signal Cross- Cross- Missing

Samples'

Instability Contamination: Contamination:

GS-40 Method RM 8562/RM 8563

6)45 (t>4(, 7745 (10

3

) /74 6 (10

3

) TJ45 (10

3

) 7746 (to

3

) Lab#l 3 49 89 0.53 1.72 Lab#2 0 26 69 1.30 2.24 2.55 3.49 Lab#3 1 127 265 0.48* 0.89* -1.08

1 5.26 Lab#4 1 135 68 0.25* 0.18* 1.45 2.24 Lab#5 2 111 111 0.25 2.37 0.10 -0.691 Lab#6 0 126 171 1.17 2.33 1.67 -0.671 Lab#7 9 580 678 1.48 4.53 3.85 5.16

+ The full analysis sequence called for 49 sample runs (see Appendix 2). Because of measurement replication, these missing samples did not prevent us from obtaining complete

sets of averaged results.

^ See text for a discussion of negative values and the comparability between the methods for determining // values.

* These values of 7 were determined through a follow-up exercise occurring many months after completion of the original measurements, therefore they may be less applicable to the correction for cross contamination.

24
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Tabic 7. Reported Values of Unrestricted Variables

CODE Lab//

Lab//2 Lab//3 Lab//4 Lab//5 Lab//

Lab//7

phoric Acid

Prep Method 3 2 3 3 3 I 3

1 1 5 2 7 4 Obs.Sp. Gravity R 1.93 1.918 1.955 1 .91 1 .91 1.93 1 .92 Hydrometer (ID//) N 732101 732092 732073 732099 29481 732067 NR

Temp. (deg. C) R 20 23.8 24.2 22 24.5 20.5 23

Rcl.Sp. Gravity c 1.91 1.90 1.94 1.89 1.90 1.91 1.90 Carb Reaction Amt.Carbonate (nig) R 8 5 20.5 200 20 20 6 Amount Acid (mL) R 0.5 3 5 2 4 5 Volume (mL) R 8.5 20 40 57 70 70 50 Time (hr) R 6 24 17 24 18 18.5 24 Temp. (deg. C) R 25 25 25 30 25 25 25

Water-CO, Eq

Inlet

Pre-Eq Treatment I 3 2 3 1 1 Amt. Water (mL) R 4 0.96 3 3 1 4 Amt. CO: (pmol) R 332 58 350 440 200 450 30

Identity CO: N LGS LGS LGS LGS other LGS other Volume (mL) R 22.7 5.7 27 25 48 16.5 25 Temp. (deg. C) R 25 25 25 18 25 25 25

Agitation B 1 1 1 1 2 1 Time (hr) R 17 48 16 5 18 25 24

Posl-Eq Treatment B 1 2 1 1 1 1

Storage Vessel 1 0 2 3 4 2 1 2 Storage Time R 1 4 2 6 5 3 7 urement

Instrument Manufacturer B 1 1 1 1 2 2

Instrument Model I 6 1 4 5 2 8 7 History I 3 1 0 0 4 0

Refill 1 4 1 2 1 3 EvacTime (s) R 80 60 30 60 120 40 120

InlctPressure (mbar) R 30 33 NR 47 42 25 NR

IdleTime (s) R 14 16 8 10 30 15 IntegrationTime (s) R 8 8 8 8 16 10 20

Elcct.Energy (eV) R 90 80 72 10 60 58 60.9

Accel. Voltage (keV) R 3 9.88 8 3 6.6 2.77 3.5 WRG (S

45 v.NBS19)°/oo C 0.03 -11.90 -21.24 -5.04 -14.44 -11.63 -37.67 WRG (8

46v.NBS19)%o C -0.62 -6.69 -6.85 -13.02 -10.48 -6.12 -22.90

Further explanation in text and on website version at http://www.cstl.nist.gOv/div837/837.0 1/outputs/ISiIMiCONLxls. Codes: I - integer variable based on interpretation of textual information provided by participants R - reported continuous variable N - informational variable C - calculated continuous variable B - binary variable NR - not recorded

28
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Figure 2. Plots of reported voltage ratio* (V45 V44) for the laboratory reference gases (data not reported from

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conditions during the analysis sequence. > he performance metric <M> is listed for each laboratory in the upper left corner of each plot - low values signify low inconsistency and better applicability of the measured cross contamination coefficient to the measurement data. Measurements of GS-40 replicates during run sequence 44-46 are indicated by the oval markitms.
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laboratory in the upper left comer of each plot - lower

values signify lower inconsistencies and better applicability of the measured cross contamination coefficient to the measurement data. Measurements ofGS-40 replicates during run sequence 44-46 are indicated by the oval markings.
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Figure 4. The determination of the cross contamination coefficient (Eq. 5) requires the measurement of the voltage ratio difference between the WRG baseline and the isotopically enhanced sample (plot A), and the voltage ratio difference between the WRG baseline and

the "perturbed" WRG during, the measurement ofthe isotopically enhanced sample (plot B). Measurements of WRG are indicated by the triangles; the diamonds indicate measurements of samples.
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Figure 6. The effects of NBS- 1 9 carbonate sample size (plotted as reciprocal) on the

repeatability of o^CCh arid t) u,COz measurements against a WRG. Data in plot A

indicate thai uncertainly in the realization ofdie VPDB carbon isotope ratio scale may

be minimized by using at least 20 mg of carbonate per NBS- 1 9 sample replicate. In

contrast, the amount of MBS- 19 carbonate was irocoiisejauenLial in the realization of the VPDB oxygen isotope ratio scale (plot B) where other factors play a more significant

role in inducing variation.
ORM8562

NBS-18-C023

1.91 1.92 1.93 1.94 Specific Qravity of Phosphoric Acid

Figure 7. Scatter plots of <5 l8 0 results for RM 8562 and NBS-I8-CO2 vs. the specific gravity of the. phosphoric acid used for the carbonate digestions- Data identified with lab numbers.

Since results are normalized to the measurements of NBS-19-C02 we compare a carbonate sample and non-carhonate sample to investigate whether specific gravity (hence the water

content of the acid) has an effect on the S

] *0 results. Neither type of sample shows a HepenHpnre nn the specific gravity within the range of this study.
-41.1

Plot A

10

32.4 t

2

m 3

10 20

8

45 C02 WRG vs NBS-19-CQ2

10 15

30 40

20 25

8

46 C02 WRG vs. NBS-19-CQ2

Figure 8. Plots of Working Reference Gas (WRG) compositions against the results of RM

8563. Error bars are standard uncertainties of the measurements, but do not include effects of

unrestricted variables. Neither plot suggests an obvious bivariate relationship, a conclusion

substantiated by multivariate Principal Components Analysis on the CO2 samples.
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APPENDIX 1: Mandatory Procedures

40
Sample Preparation

- General

It is mandatory that all samples be measured as soon as possible after being prepared. While

less than 24 hours is preferable, the 1AEA-TWG realizes that this may be impractical. The

selection of appropriate interim C02 storage vessels is discretionary. When ready for measurement, each sample of C02 must be introduced into the sample inlet consistently, minimizing potential differences in isotopic fractionation among and across samples from the

three different source types: carbonates, waters, and breakseals. The procedures addressing

this concern are discretionary. - Carbonates

Bottles of NBS-19 limestone (RM8544), NBS-1 8 carbonatite (RM8543), LSVEC lithium carbonate (RM8545), and IAEA-CO-9 barium carbonate (RM8566) are provided, each

containing 0.5 grams of material. For each replicate, aliquants of carbonate standard must be

reacted with 100% phosphoric acid at 25.0 °C to generate the C02 samples. Acid preparation,

the amounts of acid and carbonate, reaction volume and time must be identical across the samples in your laboratory. The particular values selected for these factors are discretionary. - Breakseals Each tubular breakseal contains pure C02 at a pressure near 0.9 bar (NIST RM8562-8564) or

0. 35 bar (CIO GS-40). Lightly score the tube and break in a clean, dry and evacuated tube

cracker. Immediately, the gas should be cryogenically transferred into another port or interim

storage vessel. Note the pressure of non-condensable gas. - Water Equilibrations Vials of VSMOW (RM8535) and SLAP (RM8537) standard waters arc provided, each

containing 20 mL. This should be sufficient for four replications each. Select a single Laboratory Standard Gas (LSG) for all equilibrations; the relative amounts of LSG and water used are discretionary. The system used for the equilibrations must allow complete isotopic exchange between the LSG and water at 25.0 °C, and deliver dry C02 to the sample inlet without further isotopic fractionation. The procedures for introduction of the C02 gas into the water vessel and the prior evacuation of this vessel are discretionary. The IAEA-TWG

recommends a manual system, without capillaries, where the C02 may be extracted quasi- instantaneously, with experimental procedures similar to those reported in Epstein and Maycda (1953) Geochim. Cosmochim. Acta 4, 213 (but using a smaller volume system). • Measurements - Acid Density

A hydrometer and ungraduated cylinder are provided for measuring the density of the phosphoric acid. The hydrometers used in this exercise are uniquely numbered, closely matched, and calibrated relative to each other. The acid must be thermally equilibrated with

the hydrometer and cylinder (i.e., kept together in the same room overnight) before taking the measurement and the temperature recorded to the nearest degree Celsius. Measurement Procedure:

1 . Rinse the hydrometer and cylinder with methanol three times and dry with a lint-free cloth.

2. Allow the hydrometer, ungraduated cylinder, and the phosphoric acid to equilibrate thermally overnight to a stable temperature between 20 °C to 25 °C.

3. Place approximately 50 ml of the equilibrated phosphoric acid into the cylinder, without

introducing bubbles.

41
4. Carefully place the hydrometer into the liquid. The position of the hydrometer should be

adjusted to avoid contact with the side or bottom of the cylinder. If the hydrometer is resting on the bottom of the cylinder, more phosphoric acid must be added. Take the density reading after the hydrometer level has reached a steady state (about 3 minutes) by

reading at the bottom of the meniscus. - Carbon Dioxide

Isotope measurements must be performed by the classical dual inlet technique, and all must

be performed in a single day (sec general note on Sample Preparation above)

.

A single working reference gas (WRG) must be used on the "standard/reference" side of the

inlet for all measurements; refill procedures used for the WRG during the exercise are discretionary. A single laboratory standard gas (LSG) must be identified, for measurements on the "sample"

side of the inlet, and as the C02 used for the water equilibrations. If possible, the LSG should be similar in isotopic composition to the WRG - preferably from the same source.

All measurements must utilize a single, matched inlet pressure for the sample and WRG.

All measurements must be replicated (reproduced) using independent aliquots of the samples;

if time permits, measurement replication on any sample is allowed.

All measurements must ulnlcttilize identical instrument settings; in particular, the major ion currents for sample and WRG, the idle time after sample-WRG changeover, the integration time, and the pumping time between the different samples. The particular instrument settings selected arc discretionary, as is the inlet refill procedure for the WRG.

- Order of measurements (see Summary Measurement Reporting Form)

1. LSG (5 independent replications)

2. NBS-19 C02 (5 independent replications)

3. VSMOW-C02 (4 independent replications)

4. RM 8562 (2 independent replications)

5. NBS-1 8 C02 (5 independent replications)

6. RM 8564 (2 independent replications)

7. IAEA-CO-9 C02 (5 independent replications)

8. LSVEC C02 (5 independent replications)

9. RM 8563 (2 independent replications)

10. SLAP C02 (4 independent replications)

1 1 . LSG (4 independent replications)

12. GS-40 (3 independent replications)

13. LSG (3 independent replications) - Note: GS-40

This gas is isotopically enhanced (2% 13 C and 0.8% 18 0), therefore the signals from the faraday cups for the minor ion beams (m/z = 45 and 46) might be saturated. It is important

that any automated procedures that access the sample inlet for pressure balancing or beam

centering be performed using the m/z = 44 beam. Additionally, the automated routines of some instruments may attempt to "correct" saturated signals by decreasing the pressure in the

inlet at the beginning of a run. Therefore, manual control over the GS-40 measurements may

be necessary to prevent this problem.

42
• Data - Mean data must be reported as 5

45 and 546 (±s) with respect to the WRG for each independent

analysis; values must be reported to the nearest 0.001 %o (on Summary Measurement Reporting Form) - Background-corrected mean voltage ratios ( 45 V/44V and 46V/44V) measured for the WRG, LSG,

and GS-40 must be reported; values must be reported with eight significant digits and standard

deviations must be reported to the same level of number precision (e.g.: 1.2345678 ± 0.0000057

or 0.43210567 ±0.00000169) - Except for background subtraction and (possibly) peak overlap compensation, no other

corrections to the measurements should be applied Outlier rejection is permitted, but only with discretionary caution

43
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Assumption Set A

(IAEA recommendation - historical) 1=0.5 K=0.0083330

Assumption Set B

X=0.516 K=0.0093703

Assumption Set C

(Santrock recommendation)

1=0.516 K=0.0099235

Assumption Set D

(Assonov recommendation)

},=0.528 K=0.0102819

51
TABLE 10-A. Laboratory Results

Assumption Set A

lambda=0.5 S17=0.000378866601 S18=0.002067160680

K=0.0083329582

Lab#1 Lab#2 Lab#3 Lab#4 Lab#5 Lab#6 Lab#7 Average (std de

0 U(KMOODZ) -3.77 -3.78 -3.78 -3.79 -3.76 -3.69 -3.65 o 7C /n C\A \ 0 L(KMoobo) -41 .59 -41.51 -41 .59 -41 .3C -4 i .of (u.uy) 0 U(KIVIO0D4J -10.45 -10.41 1045 1045 -10.48 1043 -10.3c - 1 n AA IC\ C\1\ 1 U.44 (U.Uo ) s'^P/MDC -1 Q \ O L/(Nbo 1 o) -5.04 -O.UD (U.Uz ) -47.38 -47.20 -47.32 c -4/ .6 I (U. 14) 0 U(LbVbU) -46.21 -46.46 -46.69 -46.36 -46.59 -46.55 -46. 8C AG. C*3 /r\ 17\ U

s:13p/\V/QMn\AA OIVIVjvV ) -2 81 -10 48 -20 44 -2 78 -45 08 -3 18 -12 5^ 5

13 C(SLAP) -2.88 -10.81 -20.61 -3.16 -45.22 -3.40 -13.15 n/a 5

13 C(LSG) -2.74 -10.51 -20.49 -2.91 -13.13 -3.25 -37.31 n/a

6

1s O(RM8562) -18.65 -18.52 -18.59 -18.63 -18.54 -18.42 -17.85 -18.56(0.09) 5

18 0(RM8563) -33.86 -33.70 -33.67 -33.78 -33.85 -33.72 -33.06 -33.76(0.08) 5

18 0(RM8564) -10.07 -10.13 -10.02 -10.05 -10.10 -10.00 -9.49 -10.06(0.05) 5

1s O(NBS18) -23.21 -23.17 -23.32 -23.31 -23.25 -23.17 -22.34 -23.24(0.07) 5

18 0(IAEA-C09) -15.56 -15.42 -15.43 -15.86 -15.47 -15.56 -14.96 -15.55(0.16) 5

1s O(LSVEC) -26.54 -26.81 -26.44 -26.60 -26.98 -26.73 -26.12 -26.71(0.20) 6

18 0(VSMOW) -0.24 0.15 -0.27 0.84 -0.29 -0.20 0.35 -0.17(0.18) 5

1s O(SLAP) -56.42 -55.59 -56.42 -52.39 -56.45 -55.92 -54.79 -56.30(0.26) 6

18 0(LSG) -14.06 -8.83 -8.99 -15.22 -12.63 -11.20 -25.10 n/a

Delta values are expressed as per mill relative differences of C02 derived from sample (listed) against VPDB.C02

Values in shaded cells are calculated from measurements outside range of performance requirements and excluded from average

Values of d13VSMOW, d13SLAP, and d13LSG are expected to be different across the laboratories, but identical within any laboratory, since these samples are derived from the same laboratory C02 (for Lab#5 and Lab#7, where different gases were used for LSG and water

equilibration, only d13VSMOW and d13SLAP are expected to be equal). FitCoefM 0.07 0.34 0.17 0.38 0.14 0.22 0.61 0.60 FitCoeff2 0.07 0.18 0.09 0.19 0.10 0.11 0.43 0.09

Fit Coeff 1 is the difference between d13(VSMOW) and d13(SLAP). The sum of these for the four laboratories meeting performance criteria for these data is listed at right.

Fit Coeff 2 is the standard deviation between d13(VSMOW), d13(SLAP), and d13(LSG), except for Lab#5 and Lab#7, where d13(LSG)

is excluded. The average standard deviation across the four laboratories meeting performance criteria for these data is listed at right.

52
TABLE 10-B. Laboratory Results

Assumption Set B

lambda=0.516

S17=0. 0003799

S18=0. 0020052 K= 0.0093703524

Lab#1 Lab#2 Lab#3 Lab#4 Lab#5 Lab#6 Lab#7 Average (std dev)

5

,3 C(RM8562) -3.75 -3 76 -3 76 -3 76 -3 74 -3 67 -3 63 -3.74(0 04) 5

13 C(RM8563) -41.59 -41 51 -41 72 -41 52 -41 59 -41 47 -41 30 -41 .57(0 09) 5

13 C(RM8564) -10.45 -10 41 -10 46 -10 45 -10 48 -10 43 -10 34 -10.45(0 03) 5

13 C(NBS18) -5.02 -5 01 -5 05 -5 04 -5 06 -5 02 -4 96 -5.03(0 02) 6

3 C(IAEA-C09) -47.41 -47 23 -47 58 -47 20 -47 35 -47 28 -47 23 -47.34(0 14) 6

13 C(LSVEC) -46.22 -46 48 -46 71 -46 38 -46 60 -46 57 -46 82 -46.55(0 17) 6

13 C(VSMOW) -2.82 -10 50 -20 47 -2 80 -45 14 -3 19 -12 56 n/a 5

13 C(SLAP) -2.79 -10 74 -20 54 -3 08 -45 19 -3 31 -13 08 n/a 5

13 C(LSG) -2.73 -10 52 -20 51 -2 90 -13 13 -3 24 -37 32 n/a

5

1s O(RM8562) -18.65 -18 52 -18 59 -18 63 -18 54 -18 41 -17 85 -18.56(0 09) 5

1s O(RM8563) -33.86 -33 69 -33 67 -33 78 -33 85 -33 72 -33 05 -33.76(0 08) 5

18 0(RM8564) -10.07 -10 13 -10 02 -10 05 -10 10 -9 99 -9 49 -10.06(0 05) 5

18 0(NBS18) -23.21 -23 17 -23 32 -23 31 -23 25 -23 17 -22 34 -23.24(0 07) 6

18 0(IAEA-C09) -15.56 -15 41 -15 43 -15 86 -15 47 -15 56 -14 96 -15.55(0 16) 6

,8 0(LSVEC) -26.54 -26 80 -26 44 -26 60 -26 98 -26 73 -26 11 -26.71(0 20) 6

,8 0(VSMOW) -0.24 0 15 -0 27 0 84 -0 29 -0 20 0 35 -0.17(0 18) 5

18 0(SLAP) -56.42 -55 59 -56 42 -52 39 -56 45 -55 92 -54 79 -56.30(0 25)

6

18 0(LSG) -14.06 -8 83 -8 99 -15 22 -12 63 -11 20 -25 10 n/a

Delta values are expressed as per mill relative differences of C02 derived from sample (listed) against VPDB.C02

Values in shaded cells are calculated from measurements outside range of performance requirements and excluded from average

Values of d13VSMOW, d13SLAP, and d13LSG are expected to be different across the laboratories, but identical within any laboratory, since these samples are derived from the same laboratory C02 (for Lab#5 and Lab#7, where different gases were used for LSG and water

equilibration, only d13VSMOW and d13SLAP are expected to be equal). FitCoeffl -0.03 0.24 0.07 0.29 0.05 0.12 0.52 0.22 FitCoeff2 0.05 0.13 0.04 0.15 0.03 0.06 0.37 0.04

Fit Coeff 1 is the difference between d13(VSMOW) and d13(SLAP). The sum of these for the four laboratories meeting performance criteria for these data is listed at right.

Fit Coeff 2 is the standard deviation between d13(VSMOW), d13(SLAP), and d13(LSG), except for Lab#5 and Lab#7, where d13(LSG)

is excluded. The average standard deviation across the four laboratories meeting performance criteria for these data is listed at right.

53
TABLE 10-iA

lambda=0.516

S1 7= 0.000402326 S18=0.0020052 K= 0.0099234991

Lab#1 Lab#2

5

1J C(RM8562) -3.74 -3.75 5

13 C(RM8563) -41.69 -41.61 5

13 C(RM8564) -10.48 -10.44 5

13 C(NBS18) -5.00 -5.00 5

13 C(IAEA-C09) -47.57 -47.39

5

13 C(LSVEC) -46.36 -46.61 5

13 C(VSMOW) -2.84 -10.55 5

13 C(SLAP) -2.70 -10.68 6

13 C(LSG) -2.72 -10.55

. Laboratory Results

sumption Set C

Lab#3 Lab#4 Lab#5 Lab#6 Lab#7 Average (std dev)

-3.75 -3.75 -3.73 -3.66 -3.62 -3.73(0.04) -41.83 -41.62 -41.69 -41.58 -41.40 -41.67(0.09)

-10.49 -10.48 -10.52 -10.46 -10.37 -10.48(0.03)

-5.03 -5.03 -5.05 -5.00 -4.95 -5.02(0.02) -47.74 -47.36 -47.51 -47.44 -47.39 -47.50(0.14)

-46.85 -46.52 -46.74 -46.70 -46.95 -46.68(0.17)

-20.56 -2.82 -45.32 -3.21 -12.62 n/a -20.52 -3.00 -45.26 -3.23 -13.03 n/a -20.58 -2.89 -13.17 -3.24 -37.42 n/a

5

18 0(RM8562) -18.65 -18.52 -18.59 -18.63 -18.54 -18.42 -17.85 -18.56(0.09) 5

,s O(RM8563) -33.86 -33.69 -33.67 -33.78 -33.84 -33.71 -33.05 -33.76(0.08) 5

18 0(RM8564) -10.07 -10.13 -10.02 -10.05 -10.10 -9.99 -9.49 -10.06(0.05) 6

18 0(NBS18) -23.21 -23.17 -23.32 -23.31 -23.25 -23.17 -22.34 -23.24(0.07) 5

18 0(IAEA-C09) -15.55 -15.41 -15.42 -15.85 -15.46 -15.55 -14.96 -15.54(0.16) 5

18 0(LSVEC) -26.54 -26.80 -26.44 -26.60 -26.98 -26.72 -26.11 -26.71(0.20) 5

18 0(VSMOW) -0.24 0.15 -0.26 0.84 -0.28 -0.20 0.35 -0.17(0.18) 6

1s O(SLAP) -56.43 -55.59 -56.42 -52.39 -56.44 -55.92 -54.79 -56.30(0.25) 6

18 0(LSG) -14.06 -8.83 -8.98 -15.22 -12.63 -11.20 -25.09 n/a

Delta values are expressed as per mill relative differences of C02 derived from sample (listed) against VPDB.C02

Values in shaded cells are calculated from measurements outside range of performance requirements and excluded from average

Values of d13VSMOW, d13SLAP, and d13LSG are expected to be different across the laboratories, but identical within any laboratory, since these samples are derived from the same laboratory C02 (for Lab#5 and Lab#7, where different gases were used for LSG and water

equilibration, only d13VSMOW and d13SLAP are expected to be equal). FitCoeffl -0.14 0.13 -0.04 0.18 -0.07 0.01 0.41 -0.23 FitCoeff2 0.07 0.07 0.03 0.09 0.05 0.01 0.29 0.04

Fit Coeff 1 is the difference between d13(VSMOW) and d13(SLAP). The sum of these for the four lat iratories meeting performance criteria for these data is listed at right.

Fit Coeff 2 is the standard deviation between d13(VSMOW), d13(SLAP), and d13(LSG), except for Lab#5 and Lab#7, where d13(LSG)

is excluded. The average standard deviation across the four laboratories meeting performance criteria for these data is listed at right.

54
TABLE 10-D. Laboratory Results

Assumption Set D

lambda= 0.528

S1 7= 0.00038691

3

S18=0. 0020052 K=0.0102819162

Lab#1 Lab#2 Lab#3 Lab#4 Lab#5 Lab#6 Lab#7 Average (std de

5

I3 C(RM8562) -3.73 -3.75 -3.74 -3.75 -3.73 -3.65 -3.61 -3.72(0.04) 5

13 C(RM8563) -41 .60 -41.52 -41.73 -41.52 -41.60 -41.48 -41.31 -41.57(0.09) 5

,3 C(RM8564) -10.45 -10.41 -10.46 -10.45 -10.49 -10.43 -10.34 -10.45(0.03) 5

13 C(NBS18) -4.99 -4.99 -5.03 -5.02 -5.04 -4.99 -4.94 -5.01 (0.02) 5

13 C(IAEA-C09) -47.45 -47.27 -47.62 -47.24 -47.39 -47.32 -47.27 -47.38(0.14) 5

13 C(LSVEC) -46.25 -46.50 -46.73 -46.40 -46.63 -46.59 -46.84 -46.57(0.17) 5

13 C(VSMOW) -2.82 -10.51 -20.50 -2.81 -45.20 -3.20 -12.58 n/a 5

13 C(SLAP) -2 71 -10.67 -20.49 -3.02 -45.16 -3.24 -13.02 n/a 5

13 C(LSG) -2.72 -10.52 -20.52 -2.88 -13.13 -3.23 -37.33 n/a

5

1s O(RM8562) -18.65 -18.52 -18.59 -18.63 -18.54 -18.41 -17.85 -18.56(0.09) 6

18 0(RM8563) -33.86 -33.69 -33.67 -33.78 -33.85 -33.72 -33.05 -33.76(0.08) 6

18 0(RM8564) -10.07 -10.13 -10.02 -10.05 -10.10 -9.99 -9.49 -10.06(0.05) 5

18 0(NBS18) -23.21 -23.17 -23.32 -23.31 -23.25 -23.17 -22.34 -23.24(0.07) 6

18 0(IAEA-C09) -15.56 -15.41 -15.43 -15.85 -15.46 -15.56 -14.96 -15.54(0.16) 6

18 0(LSVEC) -26.54 -26.80 -26.44 -26.60 -26.98 -26.72 -26.11 -26.71(0.20) 6

18 0(VSMOW) -0.24 0.15 -0.27 0.84 -0.28 -0.20 0.35 -0.17(0.18) 5

1s O(SLAP) -56.42 -55.59 -56.42 -52.39 -56.44 -55.92 -54.79 -56.30(0.25)

5' 8 0(LSG) -14.06 -8.83 -8.99 -15.22 -12.63 -11.20 -25.10 n/a

Delta values are expressed as per mill relative differences of C02 derived from sample (listed) against VPDB.C02

Values in shaded cells are calculated from measurements outside range of performance requirements and excluded from average

Values of d13VSMOW, d13SLAP, and d13LSG are expected to be different across the laboratories, but identical within any laboratory, since these samples are derived from the same laboratory C02 (for Lab#5 and Lab#7, where different gases were used for LSG and water

equilibration, only d13VSMOW and d13SLAP are expected to be equal). FitCoefM -0.11 0.16 -0.01 0.21 -0.04 0.04 0.44 -0.11 FitCoeff2 0.06 0.09 0.02 0.11 0.03 0.02 0.31 0.03

Fit Coeff 1 is the difference between d13(VSMOW) and d13(SLAP). The sum of these for the four laboratories meeting performance criteria for these data is listed at right.

Fit Coeff 2 is the standard deviation between d13(VSMOW), d13(SLAP), and d13(LSG), except for Lab#5 and Lab#7, where d13(LSG)

is excluded. The average standard deviation across the four laboratories meeting performance criteria for these data is listed at right.

55
APPENDIX 5: Links to Current NIST Reports of Investigation for Reference Materials Included in this Exercise

Waters

Report of Investigation for R M 8535

Report of Investigation for RM 8537

Carbonates

Report of Investigation for RM 8543

Report of Investigation for RM 8544

Report of Investigation for RM 8545

Report of Investigation for RM (8566)*

Carbon Dioxides

Report of Investigation for RM 8562

Report of Investigation for RM 8563

Report of Investigation for RM 8564

*Pending.

56