# The Effect of Isotopic Composition on the Uncertainty  of Routine Metal Mass Concentration Measurements in  Ambient Air

Authors: Richard J. C. Brown; Sharon L. Goddard; Andrew S. Brown; Rachel E. Yardley
Journal: Journal of Automated Methods and Management in Chemistry
 (2008)

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## Abstract

The main sources of uncertainty encountered during the analysis of the mass concentration of metals in ambient air as part of the operation of the UK Heavy Metals Monitoring Network are presented.  It is observed that the uncertainty contribution from possible variation in the isotopic composition of the sample depends on the element in question, but can be significant (e.g., for Pb, Cd, and Hg). The working curve method for the ICP-MS analysis of metals in solution, with a low resolution, high throughput instrument measuring at onem/z ratio per element, relies on the relative abundance of the isotopes under consideration being the same in both the sample and the calibration solution.  Calculation of the uncertainty in this analysis assumes that the isotopic composition variation within the sample and calibration solution is limited to a defined range. Therefore, in order to confirm the validity of this quantification methodology and its uncertainty budget, the isotopic composition of the calibration standards used for quantification has been determined. The results of this analysis are presented here.


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## Body

## 1. Introduction

The general public
and the environment can be exposed to several classes of hazardous compounds
containing metallic elements which occur naturally or are released by domestic
or industrial processes [1].
The total concentration levels of Pb, Ni, As, and Cd allowable in the PM10 fraction of ambient air (particles with an aerodynamic diameter of 10 μm or
less) are now limited by European legislation [2–4].
In order to enforce this legislation, to measure human and environmental
exposure, and to show compliance with limit and target values, the total
concentration levels of ambient metals, at multiple sites on nationwide air
quality monitoring networks, need to be measured. To this end, nationwide
networks for the measurement of a wide range of particulate-borne and gaseous
pollutants are now well established in many developed countries around the
world.  NPL currently manages and
operates the UK Heavy Metals Monitoring Network (the “network”) on behalf of
the UK Department for Environment, Food and Rural Affairs (Defra).  The “network” consists of 24 monitoring sites
around the UK collecting PM10 particulate matter which is then sent
back to NPL for the analysis of the mass concentration of Ni, As, Cd, Pb, (as
required by European legislation) and also Hg, Cr, Cu, Fe, Mn, V, Zn, and Pt to
contribute to long-term UK data sets [5].  Whilst the data quality objectives laid down
by the air quality legislation are not especially exacting—the maximum
allowable expanded uncertainty for Pb determination is 25%, and for Ni, As, and
Cd is 40%—it is still necessary
to ensure that these objectives are routinely and consistently met.
Additionally NPL also sets a self-imposed maximum measurement uncertainty of
40% on the nonmandated metals.To determine the mass concentration of particulate-phase metals in ambient
air, particles are collected onto air filters which are then digested in acid
before being analysed by inductively coupled plasma-mass spectrometry (ICP-MS).
The ICP-MS is calibrated by a working curve method using matrix matched
solutions prepared from commercially available elemental solutions certified
for metal mass fraction, and compared with NIST standard reference material
(SRMs) by NPL to ensure consistency and accuracy. Whilst NPL includes a
component of uncertainty to take account of the possibility of the isotopic
composition of metals in ambient air varying within natural limits, for a
working curve method this assumes that the isotopic composition of the
calibration standards being used also falls within this assumed range. If it
does not, then an additional uncertainty contribution, or a correction factor,
may need to be applied. In order to validate this hypothesis, the isotopic
composition of the standards used for these routine analyses requires measurement. This work
presents the results of this analysis and the effect of these findings on the
uncertainty budget of the measurement. We also present the contributions to
overall uncertainty budget from the possible variations in the isotopic
compositions of the ambient air samples.


## 2. Experimental

Particulate
samples were taken at all sites in the “network” using Partisol 2000
instruments (fitted withPM10 heads) operating at a calibrated flow
rate, nominally of 1m3⋅h−1, in accordance with European
standard method EN 12341 [6].  Samples were taken for a period of one week [7]
onto 47 mm diameter GN Metricel membrane filters. The analysis for
particulate-phase metals took place using a PerkinElmer Elan DRC II ICP-MS,
following NPL's UKAS accredited procedure, which is fully compliant with the
requirements of European standard method EN 14902 [8]
(the EU “reference method” for the analysis of metals in ambient air).  Upon arrival at NPL, the filters sampled with
particulate matter were cut accurately in half, and each portion digested at
temperatures up to 220°C using a CEM Mars X microwave. The digestion mixtures
used were as follows.(i)
Hg and Pt: 5 ml
of nitric acid and 5 ml hydrochloric acid.(ii)
All other metals:
8 ml of nitric acid and 2 ml hydrogen peroxide.These digested solutions were then diluted with deionised water (Millipore, Milli Q, Mass, USA) prior to analysis. ICP-MS
analysis took place as previously described [9] using at least four-matrix-matched gravimetrically
prepared calibration solutions [10]
prepared from monoelemental standard solutions (VWR, checked for total
elemental composition against the NIST SRM 3100 series). A detector dead time
correction was applied [11]
and a full span dual detector linearity check was performed in order to
minimise any detector nonlinearity [9] since the concentration of different isotopes within
the samples may span several orders of magnitude. A quality control standard
was repeatedly analysed (after every two solutions), and the change in response
of the quality control standard was mathematically modelled to correct for the
long-term drift of the instrument. The short-term drift of the ICP-MS was corrected by the use of an internal
standards mixture (containing Y, In, Bi, Sc, Ga, and Rh) continuously added to
the all samples via a mixing block. Each sample was analysed in triplicate,
each analysis consisting of five replicates.
For each element, one isotope at one m/z value was chosen and
monitored. The mass of each metal in solution (and its uncertainty) was then
determined by a method of generalised least squares using XLGENLINE (an
NPL-developed programme [12])
to construct a calibration curve. The analysis of the isotopic ratios of the
calibration standards was performed by determining the blank-corrected
intensity at each appropriate m/z ratio.
The isotopic composition of the calibration standards was measured by
analysing the separate monoelemental standard solutions used to make up the
calibration solutions. All the usual corrections for isobaric and polyatomic
corrections were applied. The mass fraction of the sum of all isotopes of metal
analyte in each standard solution was approximately 1 μg/g. All isotopes of
the elements of interest were measured, not simply the ones used for
quantification. Whilst no additional effort was made to determine additional
corrections for isotopes not usually used for quantification by the NPL
procedure, additional type-B uncertainty components were included in the
uncertainty budget to account for unresolved inaccuracies owing to mass bias
and mass discrimination effects, based on conservative estimates from existing
literature data [13].
Given the low precision of the measurements, these factors are expected to have
a minimal contribution to the overall uncertainty [14]. Uncertainty contributions were
also added to account for residual dead time effects and detector nonlinearity.
Matrix effects were minimised by the matrix matching of all solutions prior to
analysis.  Total expanded measurement uncertainties for each analysis are
calculated using a full GUM [15]
approach and are expressed with a coverage factor of k=2 representing
the 95% confidence interval.


## 3. Results and Discussion

The working curve
method for the ICP-MS analysis of metals in solution, with a low resolution,
high throughput instrument measuring at onem/z ratio per element relies
on the relative abundance of the isotopes under consideration being the same in
both the sample and the calibration solution. If this is not the case, a
multiplicative bias in the observed results for element X, δX,
will be observed, and is given by
(1)δX=na,cal⋅∑ini,samna,sam⋅∑ini,cal,
where na,cal is the amount of isotope a of element X
in the calibration standard, ∑ini,cal is the amount of all isotopes of element X in
the calibration standard, na,sam is the amount of isotope a of element X
in the sample, and ∑ini,sam is the amount of all isotopes of element X in
the sample [16].
When the relative abundance of the isotope used for quantification in both the
sample and the calibration solution is the same, then δX=1 and no bias is observed. It is interesting to
note that the isotopic composition with respect to the other isotopes not used
for quantification has no effect on the measurement. (As and Mn are also
measured by the “network,” but are monoisotopic
and therefore not considered as part of this treatment).Rather than assess the
isotopic composition of each individual sample, the uncertainty budget
developed for this measurement includes a component of uncertainty to recognise
that the isotopic composition of the sample may fall anywhere within the range
of natural variations, or the representative isotopic composition, whichever is
the larger range [17]. (The actual range of isotopic
composition in environmental samples may be considerably narrower [18].)
In practice, this assumption assigns δX=1 but imposes a relative uncertainty on this
value equal to the possible range of isotope abundances expected for the
isotopes used for quantification. Relatively little detail exists in the
literature on the isotopic composition of metals in ambient air particulates.
The vast majority of the work that has been published has been on Pb isotopic
composition, where the greatest variation is expected. Determination of isotope
ratios has been mostly used as a route to determining the origin of the Pb
sampled, particularly with regard to specific industrial processes or
long-range pollutant transport [14].  One study [19]
has examined the Pb isotopic composition in deposition in order to compare how
this changed before and after the closure of a local Pb mine. Others studies [20, 21]
have used the changing Pb isotope ratios in ambient particulate matter to
demonstrate the seasonal variation long-range transport of pollutants across
the Asian continent. Measured Pb isotope ratios have also been used as a route
to determine the changing origins of Pb emissions in an urban environment
during and after the phasing out of leaded petrol [22].
Cu and Zn isotopes ratios have been analysed near a large Zn refinery [23]
as a means of determining the origin of metallic ores, and Sr and Nd isotope
ratios have been used in the discrimination of emissions from various
industrial sources and traffic emissions, respectively [24].
In all cases, the observed ranges of the isotopic compositions fell well within
the natural ranges predicted [17] and these natural ranges have been used to construct
the uncertainty budget presented in this paper. Moreover, when the isotopic
composition of samples under consideration in this study has been measured
periodically, the abundance of the isotope used for quantitation has always
been well within these ranges as well [25].
The major contributions to the overall measurement uncertainty for the
determination of the mass concentration of metal in ambient air are shown in
Figure 1.Figure 1
Relative contributions to the
standard uncertainty of the determination of metal mass concentration in
ambient air, as part of the UK Heavy Metals Monitoring Network. This example
shows a measurement with an overall expanded uncertainty at the 95% confidence
interval of approximately 20%. The changing uncertainty contribution from the
variation in the sample isotopic composition for the different metals measured
by the “network” is indicated by the additional lines and labelling on the
bottom bar.As can be seen, the
contribution from the possible variation in the isotopic composition of the
sample is strongly dependent on the element being determined. This contribution
is very significant for Pb, significant for Hg, and Cd, less significant for
Cu, Zn and Pt, and negligible for Cr, Ni, Fe, and V.  This is highlighted in Figure2 which shows
the fraction of the overall measurement uncertainty contributed by uncertainty
in the isotopic composition of the sample being measured [25]. As expected from the data in Figure 1, this
contribution is very significant for Pb, notable for Hg, Cd and possibly Cu,
and insignificant for all other elements.Figure 2
The fraction of the overall
measurement uncertainty for each metal contributed by the uncertainty inδX.The summary uncertainty budget
presented in Figures1 and 2 (and the measurement equation from which this has
been developed) is only valid if the abundance of the isotope used for
quantification in the calibration standards also falls within this range
allowed for the samples.  If it does not,
then an additional uncertainty contribution, or a correction factor, may need
to be applied. This is not something that may be taken for granted since the
calibration standards may often have been prepared from isotopically enriched
pure materials, and must be measured in order to determine whether an increase
in the uncertainty estimate for the overall determination was required. The
results of the determination of the isotopic composition of the calibration
standards used are shown in Figures 3(a) and 3(b) which show that the majority
of isotopes demonstrated good agreement between the measured value and the
expected range of isotopic abundances. Table 1 highlights the level of this
agreement for the isotopes used for quantification.Table 1
Agreement between the measured abundances for the isotopes used for quantifications and the expected abundance ranges.
Isotope used for quantificationAgreement with predicted rangeV50No +0.01%Cr52No, −0.1%Fe56No, +0.4%Ni60No, +0.3%Cu63YesZn66YesCd111YesPt194YesHg200YesPb208Yes(a) V, Cr, Fe, Ni, Cu, and Zn: comparison of
the measured relative isotopic abundance of the calibration standards (black
circles, with the grey bars representing the standard error of the mean)
against the expected range in natural, or representative, isotopic compositions
(whichever is the larger range) (black bars). The relative atomic mass number is
displayed for each isotope, with the boxed number being the isotope used for
the quantification of the samples. Values are normalised to the centre of the
natural (or representative) composition range for each isotope. The relative
abundance is displayed for each element in the separate plot beneath the main
chart. (b) Cd, Pt, Hg, and Pb: comparison
of the measured relative isotopic abundance of the calibration standards (black
circles, with the grey bars representing the standard error of the mean)
against the expected range in natural, or representative, isotopic compositions
(whichever is the larger range) (black bars). The relative atomic mass number
is displayed for each isotope, with the boxed number being the isotope used for
the quantification of the samples. Values are normalised to the centre of the
natural (or representative) composition range for each isotope. The relative
abundance is displayed for each element in the separate plot beneath the main
chart.
(a)(b)Where there is agreement with
the predicted range, we may assume that the uncertainty budget for the
measurement already covers the expected range of isotopic compositions for both
sample and calibration standard. Where Table1 shows a lack of agreement, an
additional component of uncertainty equal to the discrepancy in agreement needs
to be added to justify the uncertainty statement. Given the large overall
measurement uncertainties reported for the measurement of metal mass
concentration in ambient air, these small additional uncertainty components are
unlikely to increase the overall uncertainty of the measurement significantly.
(An additional component of uncertainty has been added, rather than adding a
term into the uncertainty budget to correct for bias, since in all cases the
standard error of the mean of the isotopic composition measurements is greater
than the observed disagreement in all cases, and thus a bias correction term is
not justified.) Perhaps not surprisingly, Table 1 highlights that a disagreement
was found for the elements with the smallest predicted range of isotopic
compositions, where the accuracy of the isotopic measurement is more
critical.A brief inspection of Figures3(a) and 3(b) suggests that the bias between the measured isotopic abundance
and the centre of the expected range of isotopic abundances shows some tendency
to increase as the isotopic abundance decreases. This relationship is plotted
in Figure 4. Since the isotopes used for quantification are generally ones with
high abundances, little attention is usually paid to the less abundant
isotopes, and therefore, there may well be more bias in these measurements
owing to unresolved interferences, unresolved detector nonlinearity, and
instrument instabilities which have a larger proportional effect on the
measurement results than for high abundance species.Figure 4
The relationship between the relative isotopic abundance of all the
isotopes considered and the relative difference between the measured isotopic
abundance and the centre of the expected range of isotopic abundance.


## 4. Conclusions

A summary of the main sources of
uncertainty encountered during the analysis of the mass concentration of metals
in ambient air as part of the operation of the UK Heavy Metals Monitoring
Network has been presented. It has been observed that the uncertainty
contribution from possible variations in the isotopic composition of the sample
depends on the element in question, but can be significant (as in the cases of
Pb, Cd, and Hg). The working curve method for the ICP-MS analysis of metals in
solution, with a low resolution, high throughput instrument measuring at onem/z ratio per element relies on the relative abundance of the isotopes under
consideration being the same in both the sample and the calibration solution.
Calculation of the uncertainty in this analysis assumes that the isotopic
composition variation within the sample and calibration solution is limited to
a defined range.The results of the isotopic
analysis of these calibration standards have shown that the isotopic
composition of the calibration standards agrees with the expected range of
isotopic comparisons in the samples for all but four elements. In these cases,
additional uncertainty components were required to be added to the uncertainty
budget to account for this bias, although the increase in the overall uncertainty
of the measurement was not significant. It is interesting to note that the
isotopic composition with respect to the other isotopes not under consideration
not used for quantification has no effect, in theory, on the measurement.The bias between the measured
isotopic abundance and the centre of the expected range of isotopic abundances
shows some tendency to increase as the isotopic abundance decreases. It has
been suggested that since the isotopes used for quantification are generally
ones with high abundance and little attention is paid to the lower abundance
isotopes, the bias in these measurements may well be due to unresolved
interferences, unresolved detector nonlinearity, and instrument instability
which have a larger proportional effect on the measurement results than for
high abundance species.In future, it may be
expeditious to determine more rigorously the isotopic composition of samples
collected across the “network” so that the uncertainty contribution fromδX for the elements where this is most
significant (in particular Pb) may be reduced, thereby reducing the overall
measurement uncertainty.



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