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Subduction transports volatiles between Earth's mantle, crust, and atmosphere, ultimately creating a habitable Earth. We use isotopes to track carbon from subduction to outgassing along the Aleutian-Alaska Arc. We find substantial along-strike variations in the isotopic composition of volcanic gases, explained by different recycling efficiencies of subducting carbon to the atmosphere via arc volcanism and modulated by subduction character. Fast and cool subduction facilitates recycling of ~43 to 61% sediment-derived organic carbon to the atmosphere through degassing of central Aleutian volcanoes, while slow and warm subduction favors forearc sediment removal, leading to recycling of ~6 to 9% altered oceanic crust carbon to the atmosphere through degassing of western Aleutian volcanoes. These results indicate that less carbon is returned to the deep mantle than previously thought and that subducting organic carbon is not a reliable atmospheric carbon sink over subduction time scales.

Vanguard efforts in forecasting volcanic eruptions are turning to physics-based models, which require quantitative estimates of magma conditions during pre-eruptive storage. Below active arc volcanoes, observed magma storage depths vary widely (~0 to 20 kilometers) and are commonly assumed to represent levels of neutral buoyancy. Here we show that geophysically observed magma depths (6 ± 3 kilometers) are greater than depths of neutral buoyancy, ruling out this commonly assumed control. Observed depths are instead consistent with predicted depths of water degassing. Intrinsically wetter magmas degas water and crystallize deeper than dry magmas, resulting in viscosity increases that lead to deeper stalling of ascending magma. The water-depth relationship provides a critical constraint for forecasting models by connecting depth of eruption initiation to its volatile fuel.

Estimates of climate change damage are central to the design of climate policies. Here, we develop a flexible architecture for computing damages that integrates climate science, econometric analyses, and process models. We use this approach to construct spatially explicit, probabilistic, and empirically derived estimates of economic damage in the United States from climate change. The combined value of market and nonmarket damage across analyzed sectors-agriculture, crime, coastal storms, energy, human mortality, and labor-increases quadratically in global mean temperature, costing roughly 1.2% of gross domestic product per +1°C on average. Importantly, risk is distributed unequally across locations, generating a large transfer of value northward and westward that increases economic inequality. By the late 21st century, the poorest third of counties are projected to experience damages between 2 and 20% of county income (90% chance) under business-as-usual emissions (Representative Concentration Pathway 8.5)., (Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)