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The average depth in the ocean at which the majority of sinking organic matter particles remineralise is a fundamental parameter in the ocean's role in regulating atmospheric CO. Observed spatial patterns in sinking fluxes and relationships between the fluxes of different particles in the modern ocean have widely been used to invoke controlling mechanisms with important implications for CO regulation. However, such analyses are limited by the sparse spatial sampling of the available sediment trap data. Here we explore whether model ocean circulation rates, in the form of a transport matrix, can be used to derive remineralisation rates and infer sinking particle flux curves from the much more highly resolved observations of dissolved nutrient concentrations. Initially we show an example of the method using a transport matrix from the MITgcm model and demonstrate that there are a number of potential uncertainties associated with the method. We then use the Earth system model GENIE to generate a synthetic tracer data set to explore the method and its sensitivity to key sources of uncertainty arising from errors in the tracer observations and in the model circulation. We use a 54-member ensemble of different, but plausible, estimates of the modern circulation to explore errors associated with model transport rates. We find that reconstructed remineralisation rates are very sensitive to both errors in observations and model circulation rates, such that a simple inversion cannot provide a robust estimate of particulate flux profiles. Estimated remineralisation rates are particularly sensitive to differences between the “observed” and modelled circulation …