Andrew S. Brown

Gravimetric methods for the preparation of standard gas mixtures

The most widely used method for the preparation of primary standard gas mixtures involves weighing the individual components into a cylinder. We present a new mathematical description of the method and its uncertainties. We use this to demonstrate how strategies for serial dilution can be identified that minimize the uncertainty in the final mixture and show how they can be implemented practically. We review published reports of high accuracy gravimetry and give examples of relative uncertainties in the composition of standards approaching 1 part-per-million in the best cases and in the range of 100 to 1000 parts-per-million more typically.

Implementation of a generalized least-squares method for determining calibration curves from data with general uncertainty structures

The determination of a best-fit calibration curve that describes the response of a measuring system to the value of a standard is one of the most widely used procedures in metrology. The mathematical basis for a generalized least-squares solution to this problem is reviewed. Examples of the application of a software implementation of the method are presented to illustrate the treatment of calibration problems with different uncertainty structures for the calibration data, including correlated data. The examples concern the calibration of analysers to measure the composition of natural gas and the calibration of a gas flow dilutor.

Sample matrix and critical interference effects on the recovery and accuracy of concentration measurements of arsenic in ambient particulate samples using ICP-MS{

An investigation of isobaric and molecular interferences in the measurement of arsenic in complex environmental matrices is presented. Practical solutions to ensure the validity and accuracy of such routine analytical measurements are proposed. It is shown that the positive bias on arsenic recovery data may be due to persistent interferences that may not be completely eliminated by the use of arithmetic corrections or reaction cell strategies but can be removed by careful optimisation of the nebuliser gas flow.

Assessment of the effect of degradation by atmospheric gaseous oxidants on measured annual average benzo[a]pyrene mass concentrations.

A novel method for assessing the effect of degradation by atmospheric species on measured annual average benzo[a]pyrene (BaP) concentrations is presented. The method is based on assessing the difference in measured BaP mass concentrations using different sampling periods and extrapolation using assumed pseudo-first order reaction rate kinetics to produce the expected BaP mass concentration when theoretical sampling periods of zero duration are used - during which no degradation would be observed. The results suggest that the use of a one day sampling period as specified by the required reference method for BaP assessment in the UK may result in an underestimation of the annual average BaP mass concentration by approximately 6%. This is relatively small compared to the overall uncertainty of the measurement.

Memory Effects on Adsorption Tubes for Mercury Vapor Measurement in Ambient Air: Elucidation, Quantification, and Strategies for Mitigation of Analytical Bias

The short- and long-term memory effects associated with measurements of mercury vapor in air using gold-coated silica adsorption tubes have been described. Data are presented to quantify these effects and to determine their dependence on certain relevant measurement parameters, such as number of heating cycles used for each analysis, age of adsorption tube, mass of mercury on adsorption tube, and the length of time between analyses. The results suggest that the long-term memory effect is due to absorption of mercury within the bulk gold in the adsorption tube, which may only be fully liberated by allowing enough time for this mercury to diffuse to the gold surface. The implications of these effects for air quality networks making these measurements routinely has been discussed, and recommendations have been made to ensure any measurement bias is minimized.

Spatial inhomogeneity of metals in particulate matter on ambient air filters determined by LA-ICP-MS and comparison with acid digestion ICP-MS

Laser ablation inductively coupled plasma-mass spectrometry (LA-ICP-MS) has been used to examine the spatial distribution of metals in particulate matter on ambient air filters. The implications of the inhomogeneous distribution observed for the sub-sampling of such filters for multiple analyses have been discussed. It has been shown that large biases in measured values may occur unless the position and size of the sub-sample are chosen judiciously. Additionally, LA-ICP-MS has been compared against acid digestion ICP-MS as an alternative method for the determination of metals in particulate matter. It has been shown that the majority of variation in the LA-ICP-MS sensitivity accrues from small differences in the positioning of samples.

Validation of the gravimetric values and uncertainties of independently prepared primary standard gas mixtures

The uncertainty of primary standard gas mixtures is limited by the uncertainty of their gravimetric preparation. Although this fact is widely accepted, it has never been demonstrated directly because the uncertainty involved in the analysis of gas mixtures is much larger than that from the gravimetric preparation alone. We report the first-ever analysis by a single comparison process of a set of independently prepared gravimetric gas mixtures. The analysis of the data has used a method that calculates the parameters of a regression relationship that minimizes the random contributions from both the model and the gravimetric component. The standards studied here are comparable with a standard deviation of the residuals of seven measurements (after the exclusion of two outliers) of 0.002% (relative to value), or an expanded uncertainty of 0.004% relative. This is a factor of between 2 and 30 less than the estimated uncertainties for the gravimetric preparation of each individual standard and serves to confirm the state of the art in this field.

Principal Component Analysis as an Outlier Detection Tool for Polycyclic Aromatic Hydrocarbon Concentrations in Ambient Air

Principal component analysis has been used as a tool for the detection of potentially outlying observations in multivariate data sets of polycyclic aromatic hydrocarbon concentrations (PAHs) in ambient air. The outlier statistic developed is the vector distance of each observation at a given site from the origin of principal component space. It is shown that the success of this technique relies on the usually very strong correlation of concentrations of different PAHs in ambient air, such that any deviation from this correlation is noteworthy. Indeed, it is so strong that the first principal component has been omitted from the technique since it is related mostly to absolute concentration. The method has been successful in detecting observations with unusually high concentrations of one or more PAHs. Moreover, it has been possible to identify periods where the UK pollution climate was abnormal during periods of extreme weather. Advice and guidance for the practical use of the technique is also given.

Analytical methodologies with very low blank levels : Implications for practical and empirical evaluations of the limit of detection

Abstract Limit of detection criteria in analytical chemistry are regularly specified in terms of the distribution of the measured blank response. The consequences of an analytical blank response with a negligible distribution of measured values on the calculation and significance of limit of detection criteria receive scarce attention. A consideration of a hypothetical analytical methodology where the blank response is zero and the distribution of blank values is negligible is described. The impact of this situation on the traditional limit of detection criteria and on calibration relationships is discussed in detail. A simple, empirical method of estimating indicative method detection limits based on whole‐method repeatability is proffered. This model has been validated with experimental data.

Optimised determinations of water in ethanol by encoded photometric near-infrared spectroscopy: A special case of sequential standard addition calibration

A special limiting case of sequential standard addition calibration (S-SAC) has been applied to measurement of the water content of ethanol using encoded photometric near infrared spectroscopy. The method has shown good comparability with certified reference materials and to measurements made by Karl Fischer titration. The technique is quick and easy to use and should have application in high throughput and process measurement, for instance in biofuels analysis at port-of-entry or in bio-refineries. The characteristics of this limiting case of S-SAC have been fully described, and the corrections required to the value obtained by extrapolation to avoid bias have been calculated. The precision of the S-SAC procedure has been studied, and proposals have been made to optimise this with respect to the analytical precision. The technique should be applicable for the measurement of water in ethanol mass fractions of up to 0.1g g(-1) with an expanded uncertainty of less than 2% (relative).