Fate of mercury in tree litter during decomposition

We performed a controlled laboratory litter incubation study to assess changes in dry mass, carbon (C) mass and concentration, mercury (Hg) mass and concentration, and stoichiometric relations between elements during decomposition. Twenty-five surface litter samples each, collected from four forest stands, were placed in incubation jars open to the atmosphere, and were harvested sequentially at 0, 3, 6, 12, and 18 months. Using a mass balance approach, we observed significant mass losses of Hg during decomposition (5 to 23 % of initial mass after 18 months), which we attribute to gaseous losses of Hg to the atmosphere through a gas-permeable filter covering incubation jars. Percentage mass losses of Hg generally were less than observed dry mass and C mass losses (48 to 63 % Hg loss per unit dry mass loss), although one litter type showed similar losses. A field control study using the same litter types exposed at the original collection locations for one year showed that field litter samples were enriched in Hg concentrations by 8 to 64 % compared to samples incubated for the same time period in the laboratory, indicating strong additional sorption of Hg in the field likely from atmospheric deposition. Solubility of Hg, assessed by exposure of litter to water upon harvest, was very low (<0.22 ng Hg g<sup>−1</sup> dry mass) and decreased with increasing stage of decomposition for all litter types. Our results indicate potentially large gaseous emissions, or re-emissions, of Hg originally associated with plant litter upon decomposition. Results also suggest that Hg accumulation in litter and surface layers in the field is driven mainly by additional sorption of Hg, with minor contributions from "internal" accumulation due to preferential loss of C over Hg. Litter types showed highly species-specific differences in Hg levels during decomposition suggesting that emissions, retention, and sorption of Hg are dependent on litter type

Demonstration of algorithmic quantum speedup

Quantum algorithms theoretically outperform classical algorithms in solving problems of increasing size, but computational errors must be kept to a minimum to realize this potential. Despite the development of increasingly capable quantum computers (QCs), an experimental demonstration of a provable algorithmic quantum speedup employing today's non-fault-tolerant, noisy intermediate-scale quantum (NISQ) devices has remained elusive. Here, we unequivocally demonstrate such a speedup, quantified in terms of the scaling with the problem size of the time-to-solution metric. We implement the single-shot Bernstein-Vazirani algorithm, which solves the problem of identifying a hidden bitstring that changes after every oracle query, utilizing two different 27-qubit IBM Quantum (IBMQ) superconducting processors. The speedup is observed on only one of the two QCs (ibmq_montreal) when the quantum computation is protected by dynamical decoupling (DD) -- a carefully designed sequence of pulses applied to the QC that suppresses its interaction with the environment, but not without DD. In contrast to recent quantum supremacy demonstrations, the quantum speedup reported here does not rely on any additional assumptions or complexity-theoretic conjectures and solves a bona fide computational problem, in the setting of a game with an oracle and a verifier.Comment: 12 pages, 6 main figures + 5 supplementary figures, 1 tabl

Subtropical dust storms and downslope wind events

We performed detailed mesoscale observational analyses and Weather Research and Forecasting (WRF) model simulations to study the terrain-induced downslope winds that generated dust-emitting winds at the beginning of three strong subtropical dust storms in three distinctly different regions of North Africa and the Arabian Peninsula. We revisit the Harmattan dust storm of 2 March 2004, the Saudi dust storm of 9 March 2009, and the Bodélé Depression dust storm of 8 December 2011 and use high-resolution WRF modeling to assess the dynamical processes during the onset of the storms in more depth. Our results highlight the generation of terrain-induced downslope winds in response to the transition of the atmospheric flow from a subcritical to supercritical state in all three cases. These events precede the unbalanced adjustment processes in the lee of the mountain ranges that produced larger-scale dust aerosol mobilization and transport. We see that only the higher-resolution data sets can resolve the mesoscale processes, which are mainly responsible for creating strong low-level terrain-induced downslope winds leading to the initial dust storms. ©2017. The Authors

Modeling a Nb\u3csub\u3e3\u3c/sub\u3eSn Cryounit in GPT at UITF

Nb3Sn is a prospective material for future superconducting radio frequency (SRF) accelerator cavities. Compared to conventional niobium, the material can achieve higher quality factors, higher temperature operation, and potentially higher accelerating gradients (Eacc ≈ 96 MV/m). In this work, we performed modeling of the Upgraded Injector Test Facility (UITF) at Jefferson Lab utilizing newly constructed Nb3Sn cavities. We studied the effects of the buncher cavity and varied the gun voltage from 200-500 keV. We have calibrated and optimized the SRF cavity gradients and phases for the Nb3Sn five-cell cavities\u27 energy gains with the framework of the General Particle Tracer (GPT). Our calculations show the beam goes cleanly through the unit. There is full energy gain out of the second SRF cavity but not from the first SRF cavity due to non-relativistic phase shifts

The design of green supply chains under carbon policies: A literature review of quantitative models

Carbon footprinting of products and services is getting increasing attention due to the growing emphasis on carbon related policies in many countries. As a result, many enterprises are focusing on the design of green supply chains (GSCs) with research on supply chains (SCs) focused not only on cost efficiency, but also on its environmental consequences. The review presented in this paper focuses on the implications of carbon policies on SCs. The concept of content analysis is used to retrieve and analyze the information regarding drivers (carbon policies), actors (for example, manufacturers and retailers), methodologies (mathematical modeling techniques), decision-making contexts (such as, facility location and order quantity), and emission reduction opportunities. The review shows a lack of emissions analysis of SCs that face carbon policies in different countries. The research also focuses on the design of carbon policies for emissions reduction in different operating situations. Some possible research directions are also discussed at the end of this review.A NPRP award NPRP No.5-1284-5-198 from the Qatar National Research Fund (a member of The Qatar Foundation).Scopu