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Phosphorus (P) and nitrogen (N) are essential nutrients for food production but their excess use in agriculture can have major social costs, particularly related to water quality degradation. Nutrient footprint approaches estimate N and P release to the environment through food production and waste management and enable linking these emissions to particular consumption patterns. Following an established method for quantifying a consumer-oriented N footprint for the United States (U.S.), we calculate an analogous P footprint and assess the N:P ratio across different stages of food production and consumption. Circa 2012, the average consumer’s P footprint was 4.4 kg Pmore »capita⁻¹yr⁻¹compared to 22.4 kg N capita⁻¹yr⁻¹for the food portion of the N footprint. Animal products have the largest contribution to both footprints, comprising >70% of the average per capita N and P footprints. The N:P ratio of environmental release based on virtual nutrient factors (kilograms N or P per kilogram of food consumed) varies considerably across food groups and stages. The overall N:P ratio of the footprints was lower (5.2 by mass) than for that of U.S. food consumption (8.6), reinforcing our finding that P is managed less efficiently than N in food production systems but more efficiently removed from wastewater. While strategies like reducing meat consumption will effectively reduce both N and P footprints by decreasing overall synthetic fertilizer nutrient demands, consideration of how food production and waste treatment differentially affect N and P releases to the environment can also inform eutrophication management.

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Abstract The EXO-200 experiment searched for neutrinoless double-beta decay of 136 Xe with a single-phase liquid xenon detector. It used an active mass of 110 kg of 80.6%-enriched liquid xenon in an ultra-low background time projection chamber with ionization and scintillation detection and readout. This paper describes the design and performance of the various support systems necessary for detector operation, including cryogenics, xenon handling, and controls. Novel features of the system were driven by the need to protect the thin-walled detector chamber containing the liquid xenon, to achieve high chemical purity of the Xe, and to maintain thermal uniformity acrossmore »the detector.« less

Abstract The ATLAS experiment at the Large Hadron Collider has a broad physics programme ranging from precision measurements to direct searches for new particles and new interactions, requiring ever larger and ever more accurate datasets of simulated Monte Carlo events. Detector simulation with Geant4 is accurate but requires significant CPU resources. Over the past decade, ATLAS has developed and utilized tools that replace the most CPU-intensive component of the simulation—the calorimeter shower simulation—with faster simulation methods. Here, AtlFast3, the next generation of high-accuracy fast simulation in ATLAS, is introduced. AtlFast3 combines parameterized approaches with machine-learning techniques and is deployed tomore »meet current and future computing challenges, and simulation needs of the ATLAS experiment. With highly accurate performance and significantly improved modelling of substructure within jets, AtlFast3 can simulate large numbers of events for a wide range of physics processes.« less