Evaluating the Ability of the Thorium-232 and Thorium-230 Isotopic Couple to Quantify Lithogenic Fluxes to the Ocean

The transfer of lithogenic material from the land to the ocean plays a key role in the global cycles of many elements. In spite of their importance, these fluxes are still poorly known. Here, we present lithogenic fluxes estimated using a thorium-isotope technique. Thorium-232 (²³²Th) is supplied to the ocean uniquely by dust and rivers. On the other hand, the dominant source of ²³⁰Th is the in situ decay of dissolved ²³⁴U at a uniform and well-known rate. Assuming that both isotopes have similar chemistries, the scavenging-induced mixed-layer deficit of dissolved ²³⁰Th can in principle be used to infer the removal flux of ²³²Th if the mixed layer residence times of both isotopes are similar. Assuming a steady-state one-dimensional balance, the vertical lithogenic ²³²Th flux necessary to support observed ²³²Th profiles can be calculated and the corresponding lithogenic mass flux inferred if the lithogenic abundance and solubility of ²³²Th are known.

We first present fluxes calculated from a global dataset of ²³²Th and ²³⁰Th measurements and contrast these results with values from other available model-based dust-deposition estimates. We then test the limitations of the thorium-based estimates using 3-d ocean model simulations of ²³²Th and ²³⁰Th. Since the “true” lithogenic fluxes are perfectly known in the simulations, they can be used to quantify the absolute and relative errors associated with the observational estimates and evaluate how the error changes under various scenarios. By modulating the strength of the various sources and the scavenging intensity of each isotope in the model, the regional contribution of river and dust fluxes can also be constrained. Overall, we find that thorium-based fluxes represent dust-fluxes relatively well away from the coasts, that the precision depends strongly on ²³²Th solubility and that while the accuracy of the fluxes varies spatially, the relative error is often better than a factor of 2.