Counterrotating Stars in Simulated Galaxy Disks

Counterrotating stars in disk galaxies are a puzzling dynamical feature whose origin has been ascribed to either satellite accretion events or to disk instabilities triggered by deviations from axisymmetry. We use a cosmological simulation of the formation of a disk galaxy to show that counterrotating stellar disk components may arise naturally in hierarchically-clustering scenarios even in the absence of merging. The simulated disk galaxy consists of two coplanar, overlapping stellar components with opposite spins: an inner counterrotating bar-like structure made up mostly of old stars surrounded by an extended, rotationally-supported disk of younger stars. The opposite-spin components originate from material accreted from two distinct filamentary structures which at turn around, when their net spin is acquired, intersect delineating a "V"-like structure. Each filament torques the other in opposite directions; the filament that first drains into the galaxy forms the inner counterrotating bar, while material accreted from the other filament forms the outer disk. Mergers do not play a substantial role and most stars in the galaxy are formed in situ; only 9% of all stars are contributed by accretion events. The formation scenario we describe here implies a significant age difference between the co- and counterrotating components, which may be used to discriminate between competing scenarios for the origin of counterrotating stars in disk galaxies.Comment: 7 pages, 7 figures. Accepted for publication in MNRA

The missing risks of climate change

The risks of climate change are enormous, threatening the lives and livelihoods of millions to billions. The economic consequences of many of the complex risks associated with climate change cannot, however, currently be quantified. We argue that these unquantified, poorly understood, and often deeply uncertain risks can and should be included in economic evaluations and decision making processes. We present an overview of these unquantified risks and an ontology of them founded on the reasons behind their lack of robust evaluation. These consist of risks missing due to (a) delays in sharing knowledge and expertise across disciplines, (b) spatial and temporal variations of climate impacts, (c) feedbacks and interactions between risks, (d) deep uncertainty in our knowledge, and (e) currently unidentified risks. We highlight collaboration needs within and between the natural and social science communities to address these gaps. We also provide an qpproach for integrating assessments or speculations of these risks in a way which accounts for interdependencies, avoids double counting and makes assumptions clear. Multiple paths exist for engaging with these missing risks, with both model-based quantification and non-model-based qualitative assessments playing crucial roles

Exposure to waste sites and their impact on health: a panel and geospatial analysis of nationally representative data from South Africa, 2008–2015

Background Rapid population growth, urbanisation, and economic development have led to an unprecedented number of waste sites in developing countries. This challenge has become a contentious international relations issue, with an unsustainable amount of waste and its health consequences often being borne by developing countries. However, little national-level evidence is available in sub-Saharan Africa to quantify the association between exposure to waste sites and health. Methods We used panel data from the South African National Income Dynamics Study (SA-NIDS) to investigate the association between exposure to waste sites and asthma, tuberculosis, diabetes, and depression. The SA-NIDS is a panel survey of a nationally representative sample in South Africa, which includes data reporting the health status of 32 255 individuals between 2008 and 2015. The study exposure was distance of households, in km, to the nearest waste site, derived from waste site geospatial locations from the South Africa Waste Information System. Findings We observed a substantial increase in exposure of households to waste sites between 2008 and 2015. The median distance between study households and waste sites decreased from 68·3 km (IQR 31·1–111·7) to 8·5 km (3·0–23·7). Residing within 5 km of a waste site was significantly associated with asthma (adjusted relative risk 1·41; 95% CI 1·20–1·64), tuberculosis (1·18; 1·02–1·36), diabetes (1·25; 1·05–1·49), and depression (1·08; 1·03–1·14). The association persisted even after controlling for multiple socioeconomic factors. Interpretation We identified multiple adverse health outcomes in individuals living close to waste sites at a national level in South Africa, suggesting the need to reduce the number and size of waste sites to diminish harmful effects on health and wellbeing for communities living in close proximity to such sites. Funding South African Medical Research Council, South African National Treasury, and Wellcome Trust

Effects of climate change on combined labour productivity and supply: an empirical, multi-model study

Although effects on labour is one of the most tangible and attributable climate impact, our quantification of these effects is insufficient and based on weak methodologies. Partly, this gap is due to the inability to resolve different impact channels, such as changes in time allocation (labour supply) and slowdown of work (labour productivity). Explicitly resolving those in a multi-model inter-comparison framework can help to improve estimates of the effects of climate change on labour effectiveness. In this empirical, multi-model study, we used a large collection of micro-survey data aggregated to subnational regions across the world to estimate new, robust global and regional temperature and wet-bulb globe temperature exposure-response functions (ERFs) for labour supply. We then assessed the uncertainty in existing labour productivity response functions and derived an augmented mean function. Finally, we combined these two dimensions of labour into a single compound metric (effective labour effects). This combined measure allowed us to estimate the effect of future climate change on both the number of hours worked and on the productivity of workers during their working hours under 1·5°C, 2·0°C, and 3·0°C of global warming. We separately analysed low-exposure (indoors or outdoors in the shade) and high-exposure (outdoor in the sun) sectors. We found differentiated empirical regional and sectoral ERF's for labour supply. Current climate conditions already negatively affect labour effectiveness, particularly in tropical countries. Future climate change will reduce global total labour in the low-exposure sectors by 18 percentage points (range −48·8 to 5·3) under a scenario of 3·0°C warming (24·8 percentage points in the high-exposure sectors). The reductions will be 25·9 percentage points (–48·8 to 2·7) in Africa, 18·6 percentage points (–33·6 to 5·3) in Asia, and 10·4 percentage points (–35·0 to 2·6) in the Americas in the low-exposure sectors. These regional effects are projected to be substantially higher for labour outdoors in full sunlight compared with indoors (or outdoors in the shade) with the average reductions in total labour projected to be 32·8 percentage points (–66·3 to 1·6) in Africa, 25·0 percentage points (–66·3 to 7·0) in Asia, and 16·7 percentage points (–45·5 to 4·4) in the Americas. Both labour supply and productivity are projected to decrease under future climate change in most parts of the world, and particularly in tropical regions. Parts of sub-Saharan Africa, south Asia, and southeast Asia are at highest risk under future warming scenarios. The heterogeneous regional response functions suggest that it is necessary to move away from one-size-fits-all response functions to investigate the climate effect on labour. Our findings imply income and distributional consequences in terms of increased inequality and poverty, especially in low-income countries, where the labour effects are projected to be high

Integrated perspective on translating biophysical to economic impacts of climate change

Estimates of climate change’s economic impacts vary widely, depending on the applied methodology. This uncertainty is a barrier for policymakers seeking to quantify the benefits of mitigation. In this Perspective, we provide a comprehensive overview and categorization of the pathways and methods translating biophysical impacts into economic damages. We highlight the open question of the persistence of impacts as well as key methodological gaps, in particular the effect of including inequality and adaptation in the assessments. We discuss the need for intensifying interdisciplinary research, focusing on the uncertainty of econometric estimates of damages as well as identification of the most socioeconomically relevant types of impact. A structured model intercomparison related to economic impacts is noted as a crucial next step

The Angular Momentum Problem in Cosmological Simulations of Disk Galaxy Formation

We conduct a systematic study of the angular momentum problem in numerical simulations of disk galaxy formation. We investigate the role of numerical resolution using a semi-cosmological setup which combines an efficient use of the number of particles in an isolated halo while preserving the hierarchical build-up of the disk through the merging of clumps. We perform the same simulation varying the resolution over 4 orders of magnitude. Independent on the level of resolution, the loss of angular momentum stays the same and can be tied to dynamical friction during the build-up phase. This is confirmed in a cosmological simulation. We also perform simulations including star formation and star formation and supernova feedback. While the former has no influence on the angular momentum problem, the latter reduces the loss to a level potentially in agreement with observations. This is achieved through a suppression of early star formation and therefore the formation of a large, slowly rotating bulge. We conclude that feedback is a critical component to achieve realistic disk galaxies in cosmological simulations. Numerical resolution is important, but by itself not capable of solving the angular momentum problem.Comment: 13 pages, 13 figures, submitted to MNRA

Adrenal tropism of SARS-CoV-2 and adrenal findings in a post-mortem case series of patients with severe fatal COVID-19

Progressive respiratory failure and hyperinflammatory response is the primary cause of death in the coronavirus disease 2019 (COVID-19) pandemic. Despite mounting evidence of disruption of the hypothalamus-pituitary-adrenal axis in COVID-19, relatively little is known about the tropism of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to adrenal glands and associated changes. Here we demonstrate adrenal viral tropism and replication in COVID-19 patients. Adrenal glands showed inflammation accompanied by inflammatory cell death. Histopathologic analysis revealed widespread microthrombosis and severe adrenal injury. In addition, activation of the glycerophospholipid metabolism and reduction of cortisone intensities were characteristic for COVID-19 specimens. In conclusion, our autopsy series suggests that SARS-CoV-2 facilitates the induction of adrenalitis. Given the central role of adrenal glands in immunoregulation and taking into account the significant adrenal injury observed, monitoring of developing adrenal insufficiency might be essential in acute SARS-CoV-2 infection and during recovery.</p

Multisectoral Climate Impact Hotspots in a Warming World

The impacts of global climate change on different aspects of humanity's diverse life-support systems are complex and often difficult to predict. To facilitate policy decisions on mitigation and adaptation strategies, it is necessary to understand, quantify, and synthesize these climate-change impacts, taking into account their uncertainties. Crucial to these decisions is an understanding of how impacts in different sectors overlap, as overlapping impacts increase exposure, lead to interactions of impacts, and are likely to raise adaptation pressure. As a first step we develop herein a framework to study coinciding impacts and identify regional exposure hotspots. This framework can then be used as a starting point for regional case studies on vulnerability and multifaceted adaptation strategies. We consider impacts related to water, agriculture, ecosystems, and malaria at different levels of global warming. Multisectoral overlap starts to be seen robustly at a mean global warming of 3 degC above the 1980-2010 mean, with 11% of the world population subject to severe impacts in at least two of the four impact sectors at 4 degC. Despite these general conclusions, we find that uncertainty arising from the impact models is considerable, and larger than that from the climate models. In a low probability-high impact worst-case assessment, almost the whole inhabited world is at risk for multisectoral pressures. Hence, there is a pressing need for an increased research effort to develop a more comprehensive understanding of impacts, as well as for the development of policy measures under existing uncertainty

REMIND2.1: transformation and innovation dynamics of the energy-economic system within climate and sustainability limits

This paper presents the new and now open-source version 2.1 of the REgional Model of INvestments and Development (REMIND). REMIND, as an integrated assessment model (IAM), provides an integrated view of the global energy–economy–emissions system and explores self-consistent transformation pathways. It describes a broad range of possible futures and their relation to technical and socio-economic developments as well as policy choices. REMIND is a multiregional model incorporating the economy and a detailed representation of the energy sector implemented in the General Algebraic Modeling System (GAMS). It uses non-linear optimization to derive welfare-optimal regional transformation pathways of the energy-economic system subject to climate and sustainability constraints for the time horizon from 2005 to 2100. The resulting solution corresponds to the decentralized market outcome under the assumptions of perfect foresight of agents and internalization of external effects. REMIND enables the analyses of technology options and policy approaches for climate change mitigation with particular strength in representing the scale-up of new technologies, including renewables and their integration in power markets. The REMIND code is organized into modules that gather code relevant for specific topics. Interaction between different modules is made explicit via clearly defined sets of input and output variables. Each module can be represented by different realizations, enabling flexible configuration and extension. The spatial resolution of REMIND is flexible and depends on the resolution of the input data. Thus, the framework can be used for a variety of applications in a customized form, balancing requirements for detail and overall runtime and complexity