Towards metric-like higher-spin gauge theories in three dimensions

We consider the coupling of a symmetric spin-3 gauge field to three-dimensional gravity in a second order metric-like formulation. The action that corresponds to an SL(3,R) x SL(3,R) Chern-Simons theory in the frame-like formulation is identified to quadratic order in the spin-3 field. We apply our result to compute corrections to the area law for higher-spin black holes using Wald's entropy formula.Comment: 29 pages; v2: typos correcte

governance problems and decision-making needs

Researchers and policy makers agreed that we need to take measures now to respond to climate change impacts in the future. As the EU, its Member States and regions start to organise their adaptation efforts, it is important to understand the institutional contexts and potential challenges that might arise in the course of developing and implementing adaptation policies. This paper gives an overview of governance problems and decision-making needs that policy makers currently face. Based on empirical research in eight European countries, we mapped out the institutional context in which adaptation decisions are made and identified ten categories of needs as perceived by core policy-makers. We found no significant patterns as to why certain countries have specific needs, but there are indications that the needs change during the adaptation planning process and that Central and Eastern European countries might benefit from EU coordination efforts

What is redundant and what is not? Computational trade-offs in modelling to generate alternatives for energy infrastructure deployment

Given the urgent need to devise credible, deep strategies for carbon neutrality, approaches for `modelling to generate alternatives' (MGA) are gaining popularity in the energy sector. Yet, MGA faces limitations when applied to state-of-the-art energy system models: the number of alternatives that can be generated is virtually infinite; no realistic computational effort can discover the complete technology and spatial diversity. Here, based on our own SPORES method, a highly customisable and spatially-explicit advancement of MGA, we empirically test different search strategies - including some adapted from other MGA approaches - with the aim of identifying how to minimise redundant computation. With application to a model of the European power system, we show that, for a fixed number of generated alternatives, there is a clear trade-off in making use of the available computational power to unveil technology versus spatial diversity of system configurations. Moreover, we show that focussing on technology diversity may fail to identify system configurations that appeal to real-world stakeholders, such as those in which capacity is more spread out at the local scale. Based on this evidence that no feasible alternative can be deemed redundant a priori, we propose to initially search for options in a way that balances spatial and technology diversity; this can be achieved by combining the strengths of two different strategies. The resulting solution space can then be refined based on the feedback of stakeholders. More generally, we propose the adoption of ad-hoc MGA sensitivity analyses, targeted at testing a study's central claims, as a computationally inexpensive standard to improve the quality of energy modelling analyses

Active machine learning for spatio-temporal predictions using feature embedding

Active learning (AL) could contribute to solving critical environmental problems through improved spatio-temporal predictions. Yet such predictions involve high-dimensional feature spaces with mixed data types and missing data, which existing methods have difficulties dealing with. Here, we propose a novel batch AL method that fills this gap. We encode and cluster features of candidate data points, and query the best data based on the distance of embedded features to their cluster centers. We introduce a new metric of informativeness that we call embedding entropy and a general class of neural networks that we call embedding networks for using it. Empirical tests on forecasting electricity demand show a simultaneous reduction in prediction error by up to 63-88% and data usage by up to 50-69% compared to passive learning (PL) benchmarks

Sub-national variability of wind power generation in complex terrain and its correlation with large-scale meteorology

The future European electricity system will depend heavily on variable renewable generation, including wind power. To plan and operate reliable electricity supply systems, an understanding of wind power variability over a range of spatio-temporal scales is critical. In complex terrain, such as that found in mountainous Switzerland, wind speeds are influenced by a multitude of meteorological phenomena, many of which occur on scales too fine to capture with commonly used meteorological reanalysis datasets. Past work has shown that anticorrelation at a continental scale is an important way to help balance variable generation. Here, we investigate systematically for the first time the possibility of balancing wind variability by exploiting anticorrelation between weather patterns in complex terrain. We assess the capability for the Consortium for Small-scale Modeling (COSMO)-REA2 and COSMO-REA6 reanalyses (with a 2 and 6 km horizontal resolution, respectively) to reproduce historical measured data from weather stations, hub height anemometers, and wind turbine electricity generation across Switzerland. Both reanalyses are insufficient to reproduce site-specific wind speeds in Switzerland's complex terrain. We find however that mountain-valley breezes, orographic channelling, and variability imposed by European-scale weather regimes are represented by COSMO-REA2. We discover multi-day periods of wind electricity generation in regions of Switzerland which are anticorrelated with neighbouring European countries. Our results suggest that significantly more work is needed to understand the impact of fine scale wind power variability on national and continental electricity systems, and that higher-resolution reanalyses are necessary to accurately understand the local variability of renewable generation in complex terrain.ISSN:1748-9326ISSN:1748-931

Harder, better, faster, stronger: understanding and improving the tractability of large energy system models

Energy system models based on linear programming have been growing in size with the increasing need to model renewables with high spatial and temporal detail. Larger models lead to high computational requirements. Furthermore, seemingly small changes in a model can lead to drastic differences in runtime. Here, we investigate measures to address this issue. We review the mathematical structure of a typical energy system model, and discuss issues of sparsity, degeneracy and large numerical range. We introduce and test a method to automatically scale models to improve numerical range. We test this method as well as tweaks to model formulation and solver preferences, finding that adjustments can have a substantial impact on runtime. In particular, the barrier method without crossover can be very fast, but affects the structure of the resulting optimal solution. We conclude with a range of recommendations for energy system modellers

Comparing concentrating solar and nuclear power as baseload providers using the example of South Africa

b Grantham Institute -Climate Change and the Environment, Imperial College London Despite the increasing importance of variable renewable power generation, baseload, that is stable and predictable power generators, remain the backbone of many countries' power systems. We here compare CSP (concentrating solar power) and nuclear power as baseload electricity providers for the case of South Africa, which is adding significant new generation capacity, has an abundant solar resource, but also one existing and additional planned nuclear power plants. Both of these technologies are considered baseload-capable with sufficient available fuel (sunlight or fissible material) to provide large amounts of nearly emissionsfree electricity. We find that under a range of technological learning assumptions, CSP compares favorably against nuclear on costs in the period to 2030, and has lower investment and environmental risks. The results suggest that while nuclear power may be an important low-emissions power technology in regions with little sun, in the case of South Africa, CSP could be capable of providing a stable baseload supply at lower cost than nuclear power, and may have other non-cost benefits

Vulnerability of solar energy infrastructure and output to climate change

This paper reviews the potential vulnerability of solar energy systems to future extreme event risks as a consequence of climate change. We describe the three main technologies likely to be used to harness sunlight—thermal heating, photovoltaic (PV), and concentrating solar power (CSP)—and identify critical climate vulnerabilities for each one. We then compare these vulnerabilities with assessments of future changes in mean conditions and extreme event risk levels. We do not identify any vulnerabilities severe enough to halt development of any of the technologies mentioned, although we do find a potential value in exploring options for making PV cells more heat-resilient and for improving the design of cooling systems for CS

Thallium adsorption onto phyllosilicate minerals

The adsorption of thallium (Tl) onto phyllosilicate minerals plays a critical role in the retention of Tl in soils and sediments and the potential transfer of Tl into plants and groundwater. Especially micaceous minerals are thought to strongly bind monovalent Tl(i), in analogy to their strong binding of Cs. To advance the understanding of Tl(i) adsorption onto phyllosilicate minerals, we studied the adsorption of Tl(i) onto Na- and K-saturated illite and Na-saturated smectite, two muscovites, two vermiculites and a naturally Tl-enriched soil clay mineral fraction. Macroscopic adsorption isotherms were combined with the characterization of the adsorbed Tl by X-ray absorption spectroscopy (XAS). In combination, the results suggest that the adsorption of Tl(i) onto phyllosilicate minerals can be interpreted in terms of three major uptake paths: (i) highest-affinity inner-sphere adsorption of dehydrated Tl(+) on a very low number of adsorption sites at the wedge of frayed particle edges of illite and around collapsed zones in vermiculite interlayers through complexation between two siloxane cavities, (ii) intermediate-affinity inner-sphere adsorption of partially dehydrated Tl(+) on the planar surfaces of illite and muscovite through complexation onto siloxane cavities, (iii) low-affinity adsorption of hydrated Tl(+), especially in the hydrated interlayers of smectite and expanded vermiculite. At the frayed edges of illite particles and in the vermiculite interlayer, Tl uptake can lead to the formation of new wedge sites that enable further adsorption of dehydrated Tl(+). On the soil clay fraction, a shift in Tl(i) uptake from frayed edge sites (on illite) to planar sites (on illite and muscovite) was observed with increasing Tl(i) loading. The results from this study show that the adsorption of Tl(i) onto phyllosilicate minerals follows the same trends as reported for Cs and Rb and thus suggests that concepts to describe the retention of (radio)cesium by different types of phyllosilicate minerals in soils, sediments and rocks are also applicable to Tl(i)

Mice lacking neutral amino acid transporter B⁰AT1 (Slc6a19) have elevated levels of FGF21 and GLP-1 and improved glycaemic control

OBJECTIVE: Type 2 diabetes arises from insulin resistance of peripheral tissues followed by dysfunction of β-cells in the pancreas due to metabolic stress. Both depletion and supplementation of neutral amino acids have been discussed as strategies to improve insulin sensitivity. Here we characterise mice lacking the intestinal and renal neutral amino acid transporter B⁰AT1 (Slc6a19) as a model to study the consequences of selective depletion of neutral amino acids. METHODS: Metabolic tests, analysis of metabolite levels and signalling pathways were used to characterise mice lacking the intestinal and renal neutral amino acid transporter B⁰AT1 (Slc6a19). RESULTS: Reduced uptake of neutral amino acids in the intestine and loss of neutral amino acids in the urine causes an overload of amino acids in the lumen of the intestine and reduced systemic amino acid availability. As a result, higher levels of glucagon-like peptide 1 (GLP-1) are produced by the intestine after a meal, while the liver releases the starvation hormone fibroblast growth factor 21 (FGF21). The combination of these hormones generates a metabolic phenotype that is characterised by efficient removal of glucose, particularly by the heart, reduced adipose tissue mass, browning of subcutaneous white adipose tissue, enhanced production of ketone bodies and reduced hepatic glucose output. CONCLUSIONS: Reduced neutral amino acid availability improves glycaemic control. The epithelial neutral amino acid transporter B⁰AT1 could be a suitable target to treat type 2 diabetes.This work was supported by a sponsored research agreement with Sanofi-Aventis, Germany