J. Michael Rhodes

UThRa systematics in Kilauea and Mauna Loa basalts, Hawaii

We describe 226Ra230Th238U (dis)equilibria and RbBaThULa concentration relationships in historical and prehistoric lavas from Kilauea and Mauna Loa. (226Ra230Th), (230Th232Th), Th/U, Ba/Rb and Ba/La ratios [but not (Rb,Ba,La)/(Th,U) ratios] are essentially identical in both volcanoes, whereas the absolute concentrations (after correction for olivine crystallization) differ by up to a factor of 2, in response to varying melt fractions. This shows that bulk partition coefficients of these elements are significantly smaller than melt fractions. Very small or absent 230Th238U disequilibrium implies very small or negligible magmatic fractionation between Th and U. 226Ra230Th disequilibria are significantly larger (∼ 20% excess 226Ra on average) but are also independent of melt fraction. The combination of significant RaTh fractionation together with small or absent ThU fractionation provides constraints on recently proposed models to explain U-series disequilibria during partial melting and melt extraction. Instantaneous melt extraction models are rejected: (a) because they are inconsistent with experimentally determined partition coefficients; and (b) more generally because they would require significant covariation of (226Ra230Th) with melt fraction. On the other hand, dynamic melting models involving slow fractional melting or melt infiltration within the garnet stability region, followed by rapid movement through the lithosphere, are consistent with the results and yield melt porosities between 10−3 and 10−2 for plume upwelling velocities of 1 m yr−1. In addition, we tentatively proposed alternative models for creating the Ra excesses in the magma. One such process involves the mobilization of Ra within the volcanic edifice, subsequent advection toward and redeposition within the roof region of the magma chamber, and finally incorporation into the magma itself. Another mechanism for incorporating excess Ra in the magma might be transport of very small amounts of carbonate fluids or carbonatite melts (containing very large excesses of 226Ra) into partially molten regions in the mantle. Given the currently available data and state of knowledge about magma extraction processes, there is no obvious preference for either the purely magmatic models or those involving “extraneous” fluids in the mantle or within the volcanic edifice.

Matrix Effects in Quantitative Analysis of Laser-Induced Breakdown Spectroscopy (LIBS) of Rock Powders Doped with Cr, Mn, Ni, Zn, and Co:

Obtaining quantitative chemical information using laser-induced breakdown spectroscopy is challenging due to the variability in the bulk composition of geological materials. Chemical matrix effects caused by this variability produce changes in the peak area that are not proportional to the changes in minor element concentration. Therefore the use of univariate calibrations to predict trace element concentrations in geological samples is plagued by a high degree of uncertainty. This work evaluated the accuracy of univariate minor element predictions as a function of the composition of the major element matrices of the samples and examined the factors that limit the prediction accuracy of univariate calibrations. Five different sample matrices were doped with 10–85 000 ppm Cr, Mn, Ni, Zn, and Co and then independently measured in 175 mixtures by X-ray fluorescence, inductively coupled plasma atomic emission spectrometry, and laser-induced breakdown spectroscopy, the latter at three different laser energies (1.9, 2.8, and 3.7 mJ). Univariate prediction models for minor element concentrations were created using varying combinations of dopants, matrices, normalization/no normalization, and energy density; the model accuracies were evaluated using root mean square prediction errors and leave-one-out cross-validation. The results showed the superiority of using normalization for predictions of minor elements when the predicted sample and those in the training set had matrices with similar SiO2 contents. Normalization also mitigates differences in spectra arising from laser/sample coupling effects and the use of different energy densities. Prediction of minor elements in matrices that are dissimilar to those in the training set can increase the uncertainty of prediction by an order of magnitude. Overall, the quality of a univariate calibration is primarily determined by the availability of a persistent, measurable peak with a favorable transition probability that has little to no interference from neighboring peaks in the spectra of both the unknown and those used to train it.