A method for semi-automated objective quantification of linear bedforms from multi-scale Digital Elevation Models

The increasing availability of large, detailed digital representations of the Earth’s surface demands the application of objective and quantitative analyses. Given recent advances in the understanding of the mechanisms of formation of linear bedform features from a range of environments, objective measurement of their wavelength, orientation, crest and trough positions, height and asymmetry is highly desirable. These parameters are also of use when determining observation-based parameters for use in many applications such as numerical modelling, surface classification and sediment transport pathway analysis. Here, we (i) adapt and extend extant techniques to provide a suite of semi-automatic tools which calculate crest orientation, wavelength, height, asymmetry direction and asymmetry ratios of bedforms, and then (ii) undertake sensitivity tests on synthetic data, increasingly complex seabeds and a very large-scale (39 000km2) aeolian dune system. The automated results are compared with traditional, manually derived,measurements at each stage. This new approach successfully analyses different types of topographic data (from aeolian and marine environments) from a range of sources, with tens of millions of data points being processed in a semi-automated and objective manner within minutes rather than hours or days. The results from these analyses show there is significant variability in all measurable parameters in what might otherwise be considered uniform bedform fields. For example, the dunes of the Rub’ al Khali on the Arabian peninsula are shown to exhibit deviations in dimensions from global trends. Morphological and dune asymmetry analysis of the Rub’ al Khali suggests parts of the sand sea may be adjusting to a changed wind regime from that during their formation 100 to 10 ka BP.

Colloidal stability of nanoparticles derived from simulated cloud-processed mineral dusts

Laboratory simulation of cloud processing of three model dust types with distinct Fe-content (Moroccan dust, Libyan dust and Etna ash) and reference goethite and ferrihydrite were conducted in order to gain a better understanding of natural nanomaterial inputs and their environmental fate and bioavailability. The resulting nanoparticles (NPs) were characterised for Fe dissolution kinetics, aggregation/size distribution, micromorphology and colloidal stability of particle suspensions using a multi-method approach. We demonstrated that the: (i) acid-leachable Fe concentration was highest in volcanic ash (1 m Mg(-1) dust) and was followed by Libyan and Moroccan dust with an order of magnitude lower levels; (ii) acid leached Fe concentration in the<20 nm fraction was similar in samples processed in the dark with those under artificial sunlight, but average hydrodynamic diameter of NPs after cloud-processing (pH~6) was larger in the former; iii) NPs formed at pH~6 were smaller and less poly-disperse than those at low pH, whilst unaltered zeta potentials indicated colloidal instability; iv) relative Fe percentage in the finer particles derived from cloud processing does not reflect Fe content of unprocessed dusts (e.g. volcanic ash>Libyan dust). The common occurrence of Fe-rich "natural nanoparticles" in atmospheric dust derived materials may indicate their more ubiquitous presence in the marine environment than previously thought.