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Abstract. Endmember mixing analysis (EMMA) is often used by hydrogeochemiststo interpret the sources of stream solutes, but variations in streamconcentrations and discharges remain difficult to explain. We discoveredthat machine learning can be used to highlight patterns in stream chemistrythat reveal information about sources of solutes and subsurface groundwaterflowpaths. The investigation has implications, in turn, for the balance ofCO2 in the atmosphere. For example, CO2-driven weathering ofsilicate minerals removes carbon from the atmosphere over ∼106-year timescales. Weathering of another common mineral, pyrite, releases sulfuricacid that in turn causes dissolution of carbonates. In that process,however, CO2 is released instead of sequestered from the atmosphere. Thus, understanding long-term global CO2 sequestration by weatheringrequires quantification of CO2- versus H2SO4-drivenreactions. Most researchers estimate such weathering fluxes from streamchemistry, but interpreting the reactant minerals and acids dissolved in streams has been fraught with difficulty. We apply a machine-learningtechnique to EMMA in three watersheds to determine the extent of mineraldissolution by each acid, without pre-defining the endmembers. The resultsshow that the watersheds continuously or intermittently sequester CO2, but the extent of CO2 drawdown is diminished in areas heavily affectedby acid rain. Prior to applying the new algorithm, CO2 drawdown wasoverestimated. The new technique, which elucidates the importance ofdifferent subsurface flowpaths and long-timescale changes in the watersheds,should have utility as a new EMMA for investigating water resourcesworldwide. 

Pyrite is a ubiquitous iron sulfide mineral that is oxidized by trace oxygen. The mineral has been largely absent from global sediments since the rise in oxygen concentration in Earth’s early atmosphere. We analyzed weathering in shale, the most common rock exposed at Earth’s surface, with chemical and microscopic analysis. By looking across scales from 10 −9 to 10 2 meters, we determined the factors that control pyrite oxidation. Under the atmosphere today, pyrite oxidation is rate-limited by diffusion of oxygen to the grain surface and regulated by large-scale erosion and clast-scale fracturing. We determined that neither iron- nor sulfur-oxidizing microorganisms control global pyrite weathering fluxes despite their ability to catalyze the reaction. This multiscale picture emphasizes that fracturing and erosion are as important as atmospheric oxygen in limiting pyrite reactivity over Earth’s history. 

In spite of numerous programs and interventions, homelessness remains a significant societal concern. Long-term homelessness is particularly problematic because it can be increasingly difficult to escape from, and because it represents a continuous drain on societal resources. This paper develops a model for predicting long-term homelessness in response to a simple question: if an individual becomes homeless, what influences the individual's slide to long-term homelessness? The data we analyze to answer the question comes from the City of Boston. The model points to race, veteran status, disability, and age as key factors that predict this slide. The paper describes and illustrates the model along with problems encountered in data preparation and cleansing, prior scholarly work that helped to shape our decisions, and collaboration with participants in the ecosystem for homeless care that complemented the model-building effort. The results are important because they point to possible policy interventions (programs and funding) and process improvements (at homeless shelters) to mitigate this slide.