Measurement uncertainty of fluoride determination in vegetation: contributions from sampling and analysis

Abstract

Accumulation of fluoride in vegetation can have ecological and toxicological implications not only for the plants themselves, but for other organisms higher up the food chain. Assessment of fluoride concentration in vegetation requires reliable estimates of the associated measurement uncertainty. We investigate the fluoride concentration in three types of vegetation in Iceland (grass, downy birch, and rowan) and evaluate the contributions of both sampling and chemical analysis to the measurement uncertainty. Sampling of vegetation is performed following a standardized protocol at predetermined locations in the vicinity of aluminum smelters in Iceland, with subsequent determination of fluoride using ion selective electrodes. Measurement uncertainty arising from sampling and analysis was evaluated using an approach that couples duplicate sampling with duplicate analysis. The results of this analysis indicate that sampling contributes substantially to the measurement uncertainty, dominating the uncertainty budget for grass and downy birch, while analytical and sampling uncertainty was found to be of comparable magnitude for rowan. These findings demonstrate that estimates of measurement uncertainty that are based solely on data from the chemical analysis part severely underestimate the total measurement uncertainty. When expressed as relative expanded measurement uncertainty, the measurement uncertainty of fluoride content in vegetation is found to be 43%, 45%, and 13% for grass, downy birch, and rowan, respectively. The approach applied here and the obtained results provides a reliable way to incorporate contributions from sampling into assessment of measurement uncertainty in environmental monitoring using vegetation. The results are expected to allow for meaningful interpretation of fluoride data in vegetation when comparing them to limit values in permits or to species-specific damage thresholds of vegetation.