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Seismic interrogation of the upper mantle from the base of the crust to the top of the mantle transition zone has revealed discontinuities that are variable in space, depth, lateral extent, amplitude and lack a unified explanation for their origin. Improved constraints on the detectability and properties of mantle discontinuities can be obtained with P-to-S receiver function (Ps-RF) where energy scatters from P to S as seismic waves propagate across discontinuities of interest. However, due to the interference of crustal multiples, uppermost mantle discontinuities are more commonly imaged with lower resolution S-to-P receiver function (Sp-RF). In this study, a new method called CRISP-RF (Clean Receiver-function Imaging using SParse Radon Filters) is proposed, which incorporates ideas from compressive sensing and model-based image reconstruction. The central idea involves applying a sparse Radon transform to effectively decompose the Ps-RF into its underlying wavefield contributions, that is direct conversions, multiples, and noise, based on the phase moveout and coherence. A masking filter is then designed and applied to create a multiple-free and denoised Ps-RF. We demonstrate, using synthetic experiment, that our implementation of the Radon transform using a sparsity-promoting regularization outperforms the conventional least-squares methods and can effectively isolate direct Ps conversions. We further apply the CRISP-RF workflow on real data, including single station data on cratons, common-conversion-point stack at continental margins and seismic data from ocean islands. The application of CRISP-RF to global data sets will advance our understanding of the enigmatic origins of the upper mantle discontinuities like the ubiquitous mid-lithospheric discontinuity and the elusive X-discontinuity.

 

Plastic pollution is a defining environmental contaminant and is considered to be one of the greatest environmental threats of the Anthropocene, with its presence documented across aquatic and terrestrial ecosystems. The majority of this plastic debris falls into the micro (1 lm–5 mm) or nano (1–1000 nm) size range and comes from primary and secondary sources. Its small size makes it cumbersome to isolate and analyze reproducibly, and its ubiquitous distribution creates numerous challenges when controlling for background contamination across matrices (e.g., sediment, tissue, water, air). Although research on microplastics represents a relatively nascent subfield, burgeoning interest in questions surrounding the fate and effects of these debris items creates a pressing need for harmonized sampling protocols and quality control approaches. For results across laboratories to be reproducible and omparable, it is imperative that guidelines based on vetted protocols be readily available to research groups, many of which are either new to plastics research or, as with any new subfield, have arrived at current approaches through a process of trial-and-error rather than in consultation with the greater scientific community. The goals of this manuscript are to (i) outline the steps necessary to conduct general as well as matrix-specific quality assurance and quality control based on sample type and associated constraints, (ii) briefly review current findings across matrices, and (iii) provide guidance for the design of sampling regimes. Specific attention is paid to the source of microplastic pollution as well as the pathway by which contamination occurs, with details provided regarding each step in the process from generating appropriate questions to sampling design and collection.