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The rapidly changing climate presents unprecedented challenges, especially in permafrost regions, where its thawing directly affects houses, mines, roads, pipelines, airport runways, and rail tracks. Monitoring the dynamics of ground ice in permafrost landscapes is essential for assessing geohazards and adapting infrastructure to changing conditions. This abstract presents a new initiative utilizing cosmic neutrons metrology for permafrost studies, specifically focusing on ground-ice content monitoring. Traditional methods for assessing ground-ice content in permafrost regions involve labor-intensive surveys and analysis of geomorphological features. However, these approaches are often limited in spatial coverage and may not capture the full extent of ground-ice distribution. In response to these challenges, we propose leveraging cosmic neutrons as a non-invasive and scalable method for assessing ground-ice content. Cosmic neutrons naturally penetrate the Earth's surface and interact with hydrogen atoms in the soil, including those bound in water molecules. By measuring the cosmic neutron albedo, which is the flux of epithermal neutrons that are partially thermalized in the ground, we can infer the presence and distribution of ground ice. This approach builds upon established techniques used for soil moisture monitoring, adapting them for permafrost studies. In that regard, we conducted Monte Carlo simulations of cosmic neutron transport and interaction with modeled ground to investigate the feasibility of using cosmic neutrons for ground-ice content monitoring. Our simulations considered various ground compositions and ice concentrations to assess the sensitivity of cosmic neutron measurements to ground-ice content. The results of our simulations provide promising proof-of-concept for the proposed method, demonstrating its potential for accurately estimating ground-ice content in permafrost landscapes. Additionally, we are developing at DOSEO (CEA – Saclay, France) thermal over fast neutron reference fields that could be used to test, characterize, and calibrate detectors specifically for the presented application. The proposed method offers several advantages. Firstly, it provides measurements on a metric scale (~10m wide on ~1m depth), effectively balancing local detail with regional coverage, thus making it well-suited for mapping geohazards on a kilometric scale. Additionally, cosmic neutrons albedo measurements is non-destructive and non-invasive and can be applied across diverse permafrost landscapes, offering valuable insights into ground-ice dynamics. Moreover, mapping ground-ice content is feasible through the flexible deployment of neutron detectors. These detectors can either be moved around the study area to gather spatially distributed measurements or installed as fixed monitoring stations, enabling continuous observation of ground-ice dynamics across different seasons and over time. Integration of data from cosmic neutrons albedo measurements into Geographic Information System (GIS) applications enhances the ability to map geohazards and predict future changes in permafrost landscape stability. By combining information on ground-ice content with elevation, drainage patterns, periglacial features, and infrastructure, a better understanding of the interactions between climate change and geohazards in permafrost regions is achievable.In conclusion, cosmic neutrons metrology offers a promising approach for monitoring ground-ice content in permafrost landscapes. By advancing our understanding of permafrost dynamics, this initiative contributes to the broader goals of cryosphere monitoring and sustainable development.

Abstract In this paper, a general mathematical model for the dynamic simulation of a single-effect LiBr/water absorption chiller is presented. The model is based on mass and energy balances applied to the internal components of the machine, and it accounts for the non-steady behaviour due to thermal and mass storage in the components. The validation of the mathematical model is performed through experimental data collected on a commercial small-capacity water-cooled unit. Due to the peculiar technology adopted in the real chiller, a special effort was made to identify the appropriate values of the main physical parameters. The validation of the model is based on the values of the water temperature at the outlet of the machine, as no measurement inside the machine was possible; anyway, a consistency analysis applied to the internal parameters is also presented. The agreement between experimental and simulated results is very good, both on a daily and on a seasonal basis.

A worldwide increase in tree decline and mortality has been linked to climate change and, where these represent foundation species, this can have important implications for ecosystem functions. This study tests a combined approach of phylogeographic analysis and species distribution modelling to provide a climate change context for an observed decline in crown health and an increase in mortality in Eucalyptus wandoo, an endemic tree of south-western Australia.Phylogeographic analyses were undertaken using restriction fragment length polymorphism analysis of chloroplast DNA in 26 populations across the species distribution. Parsimony analysis of haplotype relationships was conducted, a haplotype network was prepared, and haplotype and nucleotide diversity were calculated. Species distribution modelling was undertaken using Maxent models based on extant species occurrences and projected to climate models of the last glacial maximum (LGM).A structured pattern of diversity was identified, with the presence of two groups that followed a climatic gradient from mesic to semi-arid regions. Most populations were represented by a single haplotype, but many haplotypes were shared among populations, with some having widespread distributions. A putative refugial area with high haplotype diversity was identified at the centre of the species distribution. Species distribution modelling showed high climatic suitability at the LGM and high climatic stability in the central region where higher genetic diversity was found, and low suitability elsewhere, consistent with a pattern of range contraction.Combination of phylogeography and paleo-distribution modelling can provide an evolutionary context for climate-driven tree decline, as both can be used to cross-validate evidence for refugia and contraction under harsh climatic conditions. This approach identified a central refugial area in the test species E. wandoo, with more recent expansion into peripheral areas from where it had contracted at the LGM. This signature of contraction from lower rainfall areas is consistent with current observations of decline on the semi-arid margin of the range, and indicates low capacity to tolerate forecast climatic change. Identification of a paleo-historical context for current tree decline enables conservation interventions to focus on maintaining genetic diversity, which provides the evolutionary potential for adaptation to climate change.

Les conséquences du changement climatique sont particulièrement aiguës au Kenya, où 80 % des terres sont arides ou semi-arides. Quelle perspective critique et constructive le concept d’habitabilité peut-il offrir dans ce contexte ? Fondé sur un travail de terrain réalisé au Kenya en 2022 et 2023, cet article entend affiner une définition in situ de l’habitabilité, en utilisant exclusivement des données qualitatives issues de deux phases de recherche, complétées par des exercices de vidéo-cartographie. Loin de proposer une lecture positiviste de l’habitabilité, portée par une conception exclusivement mécanique et linéaire des dynamiques de mobilité, cette étude propose de mieux relier l’habitabilité aux pratiques quotidiennes, aux habitudes, aux solidarités, voire aux résistances qui constituent la vie ordinaire des habitants des communautés et des personnes déplacées. L’habitabilité se situerait alors au cœur de l’intrication entre socialité et spatialité, entre social et biologique, qui définit – selon Stanley Cavell – la forme de vie humaine. The consequences of climate change are particularly acute in Kenya, where 80% of the land is arid or semi-arid. What critical and constructive perspective can the concept of habitability offer in this context? Based on fieldwork carried out in Kenya in 2022 and 2023, this article aims to refine an in-situ definition of habitability, using exclusively qualitative data from two research phases, supplemented by video-mapping exercises. Far from proposing a positivist reading of habitability, driven by an exclusively mechanical and linear conception of mobility dynamics, this study proposes to better link habitability to the daily practices, habits, solidarities and even resistances that make up the ordinary lives of community dwellers and displaced persons. Habitability would then lie at the heart of the intricacy between sociality and spatiality, between the social and the biological, which defines – according to Stanley Cavell – “the human form of life.”

Points out that sustainability as such does not provide a clearcut guide to policy. First one has to decide what is to be sustained. If this is agreed, it must be in an operational from. However, difficulties may still emerge since opinions may differ about how to achieve. This is illustrated by differences in the views of economists about how sustainable development is to be achieved. Orthodox economists stress the importance of the accumulation of man-made capital to achieve this end whereas neo-Malthusians stress the importance of conserving natural resource and environmental capital. Both take an anthropocentric point of view. For political reasons the neo-Malthusian has had little support but it may eventually turn out to be correct. Economics is concerned with reducing economic scarcity and economists have traditionally suggested four main ways of doing this of which economic growth is one. However, neo-Malthusian economists believe that this may not be a sustainable strategy – it may result in future poverty. It should be noted that economic systems are embedded in social and natural systems and depend on these. Economic sustainability depends on the sustainability of these other systems. So from this point of view, it is just one of several bottom lines. Values must be considered in relation to sustainability. Economics is completely anthropocentric in its approach. Therefore, economic approaches to conservation and sustainability can be at odds with the values of deep ecologists or those willing to accord rights to other sentient beings or ecosystems independent of human wishes, or those who want to make use of value judgments other than those based on the measuring rod of money. Consequently economics evaluation is sometimes ineffective in resolving social conflict, including conflict about what should be sustained. As a rule economics alone should not be the final arbiter of social decisions. It is a part (often an important part) of the social evaluation process but not the bottom line, or just one of many lines.

This paper examines the hypothesis that there is a single economic market for the international steam coal industry and investigates the degree of steam coal market integration over time. A regression test of convergence is employed to test for group convergence within a panel of steam coal exporting countries. The long-run relations between international steam coal prices are tested through cointegration analysis and the Kalman Filter analysis is employed to examine the convergence path of the price series. Monthly Free on Board (F.O.B.) prices for Australia, China, Colombia, Indonesia, Poland and South Africa between January 1995 and July 2007 are used. Considering the outcomes of the three econometric techniques as a whole, we conclude that the international steam coal market is generally integrated.

Porous materials especially nanoporous carbon, appear especially attractive due to their high specific surface area, well-defined pore structure, high thermal and chemical stability, intrinsic high electrical conductivity, low density and wide availability. In the search for renewable, environmental friendly, cheap, abundant precursors for nanoporous carbon, biomass has been the most promising material, and the nanoporous carbon derived from it has been implemented in energy storage devices and environmental applications, as well as in biomedical sites. Among the various types of biomass, jute fiber, being the world’s second most produced natural fiber, with a 2.8 million metric tons produced each year, had witnessed a great decline in use over the past decade, impacting the livelihoods of over 12 million farmers. Transforming this cheap precursor into high-value -added material with a range of applications has been the main goal. This thesis firstly highlights the various synthesis route available for transforming cheap biomass into high value added nanoporous carbon, focusing on the merits and demerits of each process. Later, it encompasses the various applications using biomass-derived nanoporous carbon and a detailed comparison of the types of biomass utilized and their relative performance in each category. From this understanding, it was possible to devise a synthesis process, which involved an economically viable and simple physical activation procedure for jute fiber at different temperatures. The optimum temperature of 800◦C yielded a moderately high surface area of 981 m2/g with retention of the original fibrous morphology. This jute-derived nanoporous carbon prepared at 800°C displayed an impressive Methylene blue adsorption capacity of 146 mg/g, comparable to expensive activated carbon yielding 176 mg/g. This thesis next explores a novel synthetic process which involves pre-carbonization at 300°C, followed by impregnation with KOH and subsequent high temperature chemical activation of three ...

It is now recognized that analytical chemistry must also be a target for green principles, in particular chromatographic methods which typically use relatively large volumes of hazardous organic solvents. More generally, high performance liquid chromatography (HPLC) is employed routinely for quality control of complex mixtures in various industries. Acetonitrile and methanol are the most commonly used organic solvents in HPLC, but they generate an impact on the environment and can have a negative effect on the health of analysts. Ethanol offers an exciting alternative as a less toxic, biodegradable solvent for HPLC. In this work we demonstrate that replacement of acetonitrile with ethanol as the organic modifier for HPLC can be achieved without significantly compromising analytical performance. This general approach is demonstrated through the specific example analysis of a complex plant extract. A benchmark method employing acetonitrile for the analysis of Bidens pilosa extract was statistically optimized using the Green Chromatographic Fingerprinting Response (GCFR) which includes factors relating to separation performance and environmental parameters. Methods employing ethanol at 30 and 80°C were developed and compared with the reference method regarding their performance of separation (GCFR) as well as by a new metric, Comprehensive Metric to Compare Liquid Chromatography Methods (CM). The fingerprint with ethanol at 80°C was similar to or better than that with MeCN according to GCFR and CM. This demonstrates that temperature may be used to replace harmful solvents with greener ones in HPLC, including for solvents with significantly different physiochemical properties and without loss in separation performance. This work offers a general approach for the chromatographic analysis of complex samples without compromising green analytical chemistry principles.

Energy management within microgrids under the presence of large number of renewables such as photovoltaics is complicated due to uncertainties involved. Randomness in energy production and consumption make both the prediction and optimality of exchanges challenging. In this paper, we evaluate the impact of uncertainties on optimality of different robust energy exchange strategies. To address the problem, we present AIROBE, a data-driven system that uses machine-learning-based predictions of energy supply and demand as input to calculate robust energy exchange schedules using a multiband robust optimization approach to protect from deviations. AIROBE allows the decision maker to tradeoff robustness with stability of the system and energy costs. Our evaluation shows, how AIROBE can deal effectively with asymmetric deviations and how better prediction methods can reduce both the operational cost while at the same time may lead to increased operational stability of the system.