The contribution of non-CO2 greenhouse gas mitigation to achieving long-term temperature goals

In the latest (fifth) assessment from the Intergovernmental Panel on Climate Change (IPCC) non-CO2 emssions accounted for 28% of total GHG emissions in 2010, when measured on the basis of their global warming potential (relative to CO2) over a 100-year and nitrous oxide (N2O) accounting for about half of all non-CO2 GHGs. With population and incomes increasing, especially in emerging economies, these emissions could grow significantly in the future. Other major sources of non-CO2 GHGs are fugitive CH4 from the extraction and distribution of fossil fuels, N2O from industrial production of nitric and adipic acid, as well as fluorinated gases (F-gases) from a range of industrial manufacturing and product uses. This paper analyses the emissions and cost impacts of mitigation of non-CO2 greenhouse gases (GHGs) at a global level, in scenarios which are focused on meeting a range of long-term temperature goals (LTTGs). The paper demonstrates how an integrated assessment model (TIAM-Grantham) representing CO2 emissions (and their mitigation) from the fossil fuel combustion and industrial sectors is coupled with a model covering non-CO2 emissions (GAINS) in order to provide a complete picture of GHG emissions in a reference scenario in which there is no mitigation of either CO2 or non-CO2 gases, as well as in scenarios in which both CO2 and non-CO2 gases are mitigated in order to achieve different LTTGs

On the criticality of inferred models

Advanced inference techniques allow one to reconstruct the pattern of interaction from high dimensional data sets. We focus here on the statistical properties of inferred models and argue that inference procedures are likely to yield models which are close to a phase transition. On one side, we show that the reparameterization invariant metrics in the space of probability distributions of these models (the Fisher Information) is directly related to the model's susceptibility. As a result, distinguishable models tend to accumulate close to critical points, where the susceptibility diverges in infinite systems. On the other, this region is the one where the estimate of inferred parameters is most stable. In order to illustrate these points, we discuss inference of interacting point processes with application to financial data and show that sensible choices of observation time-scales naturally yield models which are close to criticality.Comment: 6 pages, 2 figures, version to appear in JSTA

Motif Statistics and Spike Correlations in Neuronal Networks

Motifs are patterns of subgraphs of complex networks. We studied the impact of such patterns of connectivity on the level of correlated, or synchronized, spiking activity among pairs of cells in a recurrent network model of integrate and fire neurons. For a range of network architectures, we find that the pairwise correlation coefficients, averaged across the network, can be closely approximated using only three statistics of network connectivity. These are the overall network connection probability and the frequencies of two second-order motifs: diverging motifs, in which one cell provides input to two others, and chain motifs, in which two cells are connected via a third intermediary cell. Specifically, the prevalence of diverging and chain motifs tends to increase correlation. Our method is based on linear response theory, which enables us to express spiking statistics using linear algebra, and a resumming technique, which extrapolates from second order motifs to predict the overall effect of coupling on network correlation. Our motif-based results seek to isolate the effect of network architecture perturbatively from a known network state

Monitoring the impacts of trade agreements on food environments

The liberalization of international trade and foreign direct investment through multilateral, regional and bilateral agreements has had profound implications for the structure and nature of food systems, and therefore, for the availability, nutritional quality, accessibility, price and promotion of foods in different locations. Public health attention has only relatively recently turned to the links between trade and investment agreements, diets and health, and there is currently no systematic monitoring of this area. This paper reviews the available evidence on the links between trade agreements, food environments and diets from an obesity and non-communicable disease (NCD) perspective. Based on the key issues identified through the review, the paper outlines an approach for monitoring the potential impact of trade agreements on food environments and obesity/NCD risks. The proposed monitoring approach encompasses a set of guiding principles, recommended procedures for data collection and analysis, and quantifiable ‘minimal’, ‘expanded’ and ‘optimal’ measurement indicators to be tailored to national priorities, capacity and resources. Formal risk assessment processes of existing and evolving trade and investment agreements, which focus on their impacts on food environments will help inform the development of healthy trade policy, strengthen domestic nutrition and health policy space and ultimately protect population nutrition.The following organizations provided funding support for the travel of participants to Italy for this meeting and the preparation of background research papers: The Rockefeller Foundation, International Obesity Taskforce (IOTF), University of Auckland, Deakin University, The George Institute, University of Sydney, Queensland University of Technology, University of Oxford, University of Pennsylvania Perelman School of Medicine, World Cancer Research Fund International, University of Toronto, and The Australian National University. The Faculty of Health at Deakin University kindly supported the costs for open access availability of this paper, and the Australian National Health and Medical Research Council Centre for Research Excellence in Obesity Policy and Food Systems (APP1041020) supported the coordination and finalizing of INFORMAS manuscripts

Academic self-concept, gender and single-sex schooling

This paper assesses gender differences in academic self-concept for a cohort of children born in 1958 (the National Child Development Study). We address the question of whether attending single-sex or co-educational schools affected students’ perceptions of their own academic abilities (academic self-concept). Academic selfconcept was found to be highly gendered, even controlling for prior test scores. Boys had higher self-concepts in maths and science, and girls in English. Single-sex schooling reduced the gender gap in self-concept, while selective schooling was linked to lower academic self-concept overall

Comments on the continuing widespread and unnecessary use of a defective emission equation in field emission related literature

Field electron emission (FE) has relevance in many different technological contexts. However, many related technological papers use a physically defective elementary FE equation for local emission current density (LECD). This equation takes the tunneling barrier as exactly triangular, as in the original FE theory of 90 years ago. More than 60 years ago, it was shown that the so-called Schottky-Nordheim (SN) barrier, which includes an image-potential-energy term (that models exchange-and-correlation effects) is better physics. For a metal-like emitter with work-function 4.5 eV, the SN-barrier-related Murphy-Good FE equation predicts LECD values that are higher than the elementary equation values by a large factor, often between around 250 and around 500. By failing to mention/apply this 60-year-old established science, or to inform readers of the large errors associated with the elementary equation, many papers (aided by defective reviewing) spread a new kind of "pathological science", and create a modern research-integrity problem. The present paper aims to enhance author and reviewer awareness by summarizing relevant aspects of FE theory, by explicitly identifying the misjudgment in the original 1928 Fowler-Nordheim paper, by explicitly calculating the size of the resulting error, and by showing in detail why most FE theoreticians regard the 1950s modifications as better physics. Suggestions are made, about nomenclature and about citation practice, that may help to diminish misunderstandings.Comment: Submitted for publication; in v2 a correction to historical information (with no numerical consequences) has been made in Appendix

Host Biomarkers Are Associated With Response to Therapy and Long-Term Mortality in Pediatric Severe Malaria.

Background. Host responses to infection are critical determinants of disease severity and clinical outcome. The development of tools to risk stratify children with malaria is needed to identify children most likely to benefit from targeted interventions.Methods. This study investigated the kinetics of candidate biomarkers of mortality associated with endothelial activation and dysfunction (angiopoietin-2 [Ang-2], soluble FMS-like tyrosine kinase-1 [sFlt-1], and soluble intercellular adhesion molecule-1 [sICAM-1]) and inflammation (10 kDa interferon γ-induced protein [CXCL10/IP-10] and soluble triggering receptor expressed on myeloid cells-1 [sTREM-1]) in the context of a randomized, double-blind, placebo-controlled, parallel-arm trial evaluating inhaled nitric oxide versus placebo as adjunctive therapy to parenteral artesunate for severe malaria. One hundred eighty children aged 1–10 years were enrolled at Jinja Regional Referral Hospital in Uganda and followed for up to 6 months.Results. There were no differences between the 2 study arms in the rate of biomarker recovery. Median levels of Ang-2, CXCL10, and sFlt-1 were higher at admission in children who died in-hospital (n = 15 of 180; P < .001, P = .027, and P = .004, respectively). Elevated levels of Ang-2, sTREM-1, CXCL10, and sICAM-1 were associated with prolonged clinical recovery times in survivors. The Ang-2 levels were also associated with postdischarge mortality (P < .0001). No biomarkers were associated with neurodisability.Conclusions. Persistent endothelial activation and dysfunction predict survival in children admitted with severe malaria

CFD Model of a Planar Solid Oxide Electrolysis Cell: Base Case and Variations

A three-dimensional computational fluid dynamics (CFD) model has been created to model high-temperature steam electrolysis in a planar solid oxide electrolysis cell (SOEC). The model represents a single cell, as it would exist in an electrolysis stack. Details of the model geometry are specific to a stack that was fabricated by Ceramatec, Inc. and tested at the Idaho National Laboratory. Mass, momentum, energy, and species conservation and transport are provided via the core features of the commercial CFD code FLUENT. A solid-oxide fuel cell (SOFC) model adds the electrochemical reactions and loss mechanisms and computation of the electric field throughout the cell. The FLUENT SOFC user-defined subroutine was modified for this work to allow for operation in the SOEC mode. Model results provide detailed profiles of temperature, Nernst potential, operating potential, activation over-potential, anode-side gas composition, cathode-side gas composition, current density and hydrogen production over a range of stack operating conditions. Mean model results are shown to compare favorably with experimental results obtained from an actual ten-cell stack tested at INL. Mean per-cell area-specific-resistance (ASR) values decrease with increasing current density, consistent with experimental data. Predicted mean outlet hydrogen and steam concentrations vary linearly with current density, as expected. Effects of variations in operating temperature, gas flow rate, cathode and anode exchange current density, and contact resistance from the base case are presented. Contour plots of local electrolyte temperature, current density, and Nernst potential indicated the effects of heat transfer, reaction cooling/heating, and change in local gas composition. Discussion of thermal neutral voltage, enthalpy of reaction, hydrogen production, cell thermal efficiency, cell electrical efficiency, and Gibbs free energy are discussed and reported herein

Character and environmental lability of cyanobacteria-derived dissolved organic matter

Autotrophic dissolved organic matter (DOM) is central to the carbon biogeochemistry of aquatic systems, and the full complexity of autotrophic DOM has not been extensively studied, particularly by high-resolution mass spectrometry (HRMS). Terrestrial DOM tends to dominate HRMS studies in freshwaters due to the propensity of such compounds to ionize by negative mode electrospray, and possibly also because ionizable DOM produced by autotrophy is decreased to low steady-state concentrations by heterotrophic bacteria. In this study, we investigated the character of DOM produced by the widespread cyanobacteriaMicrocystis aeruginosausing high-pressure liquid chromatography-electrospray ionization-high-resolution mass spectrometry.M. aeruginosaproduced thousands of detectable compounds in axenic culture. These compounds were chromatographically resolved and the majority were assigned to aliphatic formulas with a broad polarity range. We found that the DOM produced byM. aeruginosawas highly susceptible to removal by heterotrophic freshwater bacteria, supporting the hypothesis that this autotroph-derived organic material is highly labile and accordingly only seen at low concentrations in natural settings