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AbstractExtreme weather events can have strong negative impacts on species survival and community structure when surpassing lethal thresholds. Extreme, short‐lived, winter warming events in the Arctic rapidly melt snow and expose ecosystems to unseasonably warm air (for instance, 2–10 °C for 2–14 days) but upon return to normal winter climate exposes the ecosystem to much colder temperatures due to the loss of insulating snow. Single events have been shown to reduce plant reproduction and increase shoot mortality, but impacts of multiple events are little understood as are the broader impacts on community structure, growth, carbon balance, and nutrient cycling. To address these issues, we simulated week‐long extreme winter warming events – using infrared heating lamps and soil warming cables – for 3 consecutive years in a sub‐Arctic heathland dominated by the dwarf shrubsEmpetrum hermaphroditum, Vaccinium vitis‐idaea(both evergreen) andVaccinium myrtillus(deciduous). During the growing seasons after the second and third winter event, spring bud burst was delayed by up to a week forE. hermaphroditumandV. myrtillus, and berry production reduced by 11–75% and 52–95% forE. hermaphroditumandV. myrtillus, respectively. Greater shoot mortality occurred inE. hermaphroditum(up to 52%),V. vitis‐idaea(51%), andV. myrtillus(80%). Root growth was reduced by more than 25% but soil nutrient availability remained unaffected. Gross primary productivity was reduced by more than 50% in the summer following the third simulation. Overall, the extent of damage was considerable, and critically plant responses were opposite in direction to the increased growth seen in long‐term summer warming simulations and the ‘greening’ seen for some arctic regions. Given the Arctic is warming more in winter than summer, and extreme events are predicted to become more frequent, this generates large uncertainty in our current understanding of arctic ecosystem responses to climate change.

Abstract Wood pellets were pyrolyzed using a microwave oven and different microwave power, apparatus set-up and microwave absorbers (none, Fe, and carbon). Pyrolysis was realized in a short time in the presence of Fe or carbon while it was incomplete if the absorber was not present. Furthermore when the absorber was present the shape of the pellets remained unaltered while if the absorber was not employed pellets were disaggregated. Three fractions were collected from each pyrolysis: a gas, a liquid also called bio-oil and a solid called bio-char. The bio-oil contained two phases and they were quantitatively characterized through a GC/MS-FID procedure using an internal standard according to a previously reported method. HPLC/MS, FTIR and 1 H NMR spectroscopy were also employed for characterization of these liquids. Cellulose pyrolysis products were present in the upper phase such as water, acetic acid, furans (such as furfural), carbohydrates and their derivatives. Compounds from pyrolysis of lignin such as phenols and veratric acid were present in the bottom phase. The microwave assisted pyrolysis showed the possibility to efficiently convert wood pellets in different products. The main economical important components may be separated and used as chemicals, natural drugs or pesticides, while the remaining components, the solid and the gas may be used for energy production (solid and bio-oil). Solid may be also used for carbon sequestration.

Background: The present paper describes the results of a rating study performed by a group of European Union (EU) drug experts using the multi-criteria decision analysis model for evaluating drug harms. Methods: Forty drug experts from throughout the EU scored 20 drugs on 16 harm criteria. The expert group also assessed criteria weights that would apply, on average, across the EU. Weighted averages of the scores provided a single, overall weighted harm score (range: 0–100) for each drug. Results: Alcohol, heroin and crack emerged as the most harmful drugs (overall weighted harm score 72, 55 and 50, respectively). The remaining drugs had an overall weighted harm score of 38 or less, making them much less harmful than alcohol. The overall weighted harm scores of the EU experts correlated well with those previously given by the UK panel. Conclusion: The outcome of this study shows that the previous national rankings based on the relative harms of different drugs are endorsed throughout the EU. The results indicates that EU and national drug policy measures should focus on drugs with the highest overall harm, including alcohol and tobacco, whereas drugs such as cannabis and ecstasy should be given lower priority including a lower legal classification.

We have observed and reported previously that very small precipitates with sizes of the order of 2–10nm can form in silicon from slow diffusing transition metals. These nano-precipitates can act as exceptionally powerful recombination centers. In this paper we present experimental results on the recombination dynamics and show that the behavior is not well described by previous work on larger precipitates or by the conventional Shockley-Read-Hall model widely used for recombination associated with point defects. The basic reason for this is that the Fermi sea of the metal particle system allows a huge degree of freedom for charge exchange and many size dependent effects on the capture rates. These defects, which are Coulomb attractive for the minority carrier can stably capture and bind several minority carriers with large cross section. However majority carrier capture is into a repulsive centre, but the potentials associated with sub 10 nm particles are sufficiently sharp that the strength of tunneling process hugely enhances the majority carrier capture rate. In the limit of ultra-small (but still metallic) systems Coulomb blockade effects will further modify majority carrier capture. All cross sections are net charge state dependent but self-consistent three dimensional solutions to the Poisson and Schrodinger equations can successfully model capture and recombination physics. The measured and calculated trends clearly show that such precipitates may be lifetime controlling in multi-crystalline Si.

Dual active bridge converters enable bidirectional power flow in buck and boost operating modes. This paper presents an advanced switching sequence and burst-mode strategy to balance conduction, switching, and magnetic losses under light, medium, and heavy loading conditions, leading to improved operating efficiency. The implementation of the switching sequence employs the natural state-plane trajectories of the converter and contributes to higher efficiency and the ability to perform burst mode. The proposed switching sequences improve the overall efficiency of the converter by enabling soft switching and adjusting the frequency to match the minimum RMS transformer current in the full operating range. Furthermore, it incorporates a fully controlled burst-mode switching sequence for light loading conditions to further extend the efficiency gains. As a result, maximum efficiency is obtained by taking advantage of all the possible switching structures of the converter. The analysis provides insight into the natural trajectories of the converter, which produce soft-switching transitions and enable the converter structures to achieve the target operating point directly. Simulation and experimental results are presented to validate the benefits of the switching sequence and illustrate the burst-mode operation.

In this study we evaluate the skill of a new, merged soil moisture product (ECV_SM) that has been developed in the framework of the European Space Agency's Water Cycle Multi-mission Observation Strategy and Climate Change Initiative projects. The product combines in a synergistic way the soil moisture retrievals from four passive (SMMR, SSM/I, TMI, and AMSR-E) and two active (ERS AMI and ASCAT) coarse resolution microwave sensors into a global data set spanning the period 1979-2010. The evaluation uses ground-based soil moisture observations of 596 sites from 28 historical and active monitoring networks worldwide. Besides providing conventional measures of agreement, we use the triple collocation technique to assess random errors in the data set. The average Spearman correlation coefficient between ECV_SM and all in-situ observations is 0.46 for the absolute values and 0.36 for the soil moisture anomalies, but differences between networks and time periods are very large. Unbiased root-mean-square differences and triple collocation errors show less variation between networks, with average values around 0.05 and 0.04m3m-3, respectively. The ECV_SM quality shows an upward trend over time, but a consistent decrease of all performance metrics is observed for the period 2007-2010. Comparing the skill of the merged product with the skill of the individual input products shows that the merged product has a similar or better performance than the individual input products, except with regard to the ASCAT product, compared to which the performance of ECV_SM is inferior. The cause of the latter is most likely a combination of the mismatch in sampling time between the satellite observations and in-situ measurements, and the resampling and scaling strategy used to integrate the ASCAT product into ECV_SM on the other. The results of this study will be used to further improve the scaling and merging algorithms for future product updates.

Plant communities, through species richness and composition, strongly influence soil microorganisms and the ecosystem processes they drive. To test the effects of other plant community attributes, such as the identity of dominant plant species, evenness, and spatial arrangement, we set up a model mesocosm experiment that manipulated these three attributes in a full factorial design, using three grassland plant species (Anthoxanthum odoratum, Plantago lanceolata, and Lotus corniculatus). The impact of the three community attributes on the soil microbial community structure and functioning was evaluated after two growing seasons by ester-linked phospholipid fatty-acids analysis, substrate-induced respiration, basal respiration, and nitrogen mineralization and nitrification rates. Our results suggested that the dominant species identity had the most prevalent influence of the three community attributes, with significant effects on most of the measured aspects of microbial biomass, composition and functioning. Evenness had no effects on microbial community structure, but independently influenced basal respiration. Its effects on nitrogen cycling depended on the identity of the dominant plant species, indicating that interactions among species and their effects on functioning can vary with their relative abundance. Systems with an aggregated spatial arrangement had a different microbial community composition and a higher microbial biomass compared to those with a random spatial arrangement, but rarely differed in their functioning. Overall, it appears that dominant species identity was the main driver of soil microorganisms and functioning in these model grassland communities, but that other plant community attributes such as evenness and spatial arrangement can also be important.

Abstract The sustainability of the built environment largely depends on its energy and environmental performances. The overall objective, across the different phases of the building life cycle, is to improve building and system performances in terms of economics, comfort, environmental impact and durability. Several modelling methodologies have been developed in order to evaluate the energy performance of buildings. Generally, every modelling methodology responds effectively to some specific tasks, but there exists a lack of integration in particular with respect to the cross-disciplinary role of data. Given the multi-scale and multi-objective nature of the problem of optimization of the energy and environmental performances of the built environment, an appropriate synthesis and integration process in modelling methodologies has to be identified, addressing realistically the uncertainties inherently present in modelling strategies. Visualization and data analysis techniques are successfully used in a wide variety of applications, both in theoretical and applied domains, but questions remains about their robustness, efficiency and applicability to the problems introduced before. The paper aims to analyze critically these topics by means of case studies, showing a possible path to create a multi-scale methodology able to synthesize all the relevant aspects.