Optical characterisation of mineral dust in polar ice: towards an improved understanding of climate-regulating processes

Le résumé fourni par la source

Polar ice cores represent a unique and invaluable archive, offering an exceptional resource for enhancing our understanding of the atmospheric composition over time and its aerosol content. These cores preserve, over millennia, crucial information such as air bubbles, solid particles trapped in ice, as well as isotopes, heavy metals, and radioactive elements. Among the various paleoclimatic proxies, mineral dust is widely recognized as a key component of the climate system, strongly linked to the glacial-interglacial climate oscillations of the Quaternary period. Nevertheless, its impact on the radiative balance of the planet system remains to be fully quantified, primarily due to the considerable variations in its optical properties that occur over both space and time. In this context, laser-sensing instruments emerge as a versatile and non-destructive tool suitable for in-line characterisation of particle radiative properties. In this work, we present an optical technique which provides two optical parameters, namely the extinction cross-section and the polarizability, of each particle passing through a focused laser beam under continuous forced flow, called Single Particle Extinction and Scattering (SPES). This method, developed by the Instrumental Optics of the Physics Department of the University of Milan, is based on the far-field, self-reference interference between the zero-angle field scattered by each nano- or microparticle and the more intense field transmitted through the sample. This analysis has been applied to the EPICA ice core drilled at Dome C, East Antarctica, with depth range from about 200 to 2900 m. In deeper sections, where growth and recrystallisation of ice grains might cause relocation of impurities, particular attention has been directed towards the identification of dust aggregates, which have the potential to alter the original paleoclimate signal. Preliminary results and insight on the SPES method will be presented.

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