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Chris Russo

Publications and source records attributed to Chris Russo.

2 recordsLinked to original sources

Magmatic source of the opening phase of Kīlauea’s 2018 Lower East Rift Zone eruption

The 2018 eruption of Kīlauea volcano in its Lower East Rift Zone began with the discharge of evolved high-Ti basalt as weak lava fountains and short, slow-moving lava flows. The lavas were quickly geochemically recognized as being derived from magmas stored within the rift zone and remobilized by a new intrusion, a sequence that is common at Kīlauea. This initial phase of the 2018 eruption, referred to as phase 1a, lasted for 6 days and was followed by extrusion of mixed magma after a 3-day pause. Even though remobilization of older rift zone magmas is common within Kīlauea’s rift zones, it is difficult to determine which past intrusion(s) may have initially emplaced those stored magmas. This difficulty stems from the tendency for Kīlauea magmas to follow very similar differentiation paths without significant variations in major, minor, or even trace element chemistry. We investigate possible magma sources for the lavas erupted during phase 1a of the 2018 eruption using whole-rock, mineral, and glass major and trace element compositions from historical East Rift Zone eruptions with adjacent fissures. We consider two primary hypotheses for the phase 1a source: magmas associated with the 1955 Lower East Rift Zone eruption or the nine eruptions in the Middle and Upper East Rift Zone during the 1960s. Our results suggest that magma associated with the earliest phases of Kīlauea’s 1955 eruption was the most likely source of the 2018 phase 1a remobilized magma. We determine volatile saturation pressures from melt inclusion chemistry and find similar storage depths for the 2018 phase 1a and early 1955 magmas. The phase 1a and early 1955 lavas are nearly indistinguishable in all of the compositional criteria considered, implying that the leftover 1955 magma body barely cooled and differentiated in the 63 years between eruptions (cooling rates of ~0.1 °C/year). This study sheds light on the potential for protracted storage of eruptible magmas in rift zones at Kīlauea, and highlights some of the challenges and solutions to identifying genetic relationships between magmas at Kīlauea.

Hawaii↗

lasertram: A Python library for time resolved analysis of laser ablation inductively coupled plasma mass spectrometry data

Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) data has a wide variety of uses in the geosciences for in-situ chemical analysis of complex natural materials. Improvements to instrument capabilities and operating software have drastically reduced the time required to generate large volumes of data relative to previous methodologies. Raw data from LA-ICP-MS, however, is in counts per unit time (typically counts per second), not elemental concentrations and converting these count ratesto concentrations requires additional processing. For complex materials where the ablated volume may contain a range of material compositions, a moderate amount of user input is also required if appropriate concentrations are to be accurately calculated. In geologic materials such as glasses and minerals that potentially have numerous heterogeneities (e.g., microlites or other inclusions) within them, this is typically determiningwhether the total ablation signal should be filtered to remove these heterogeneities. This necessitates that the LA-ICP-MS data processing pipeline is one that is not automated, but is also designed to enable rapid and efficient processing of large volumes of data. Here we introduce , a Python library for the time resolved analysis of LA-ICP-MS data. We outline its mathematical theory, code structure, and provide an example of how it can be used to provide the time resolved analysis necessitated by LA-ICP-MS data of complex geologic materials. Throughout the pipeline we show how metadata and data are incrementally added to the objects created such that virtually any aspect of an experiment may be interrogated and its quality assessed. We also show, that when combined with other Python libraries for building graphical user interfaces, it can be utilized outside of a pure scripting environment. can be found at https://doi.org/10.5066/P1DZUR3Z

Applied Computing and Geosciences↗