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Increasing lignocellulosic feedstock for advanced biofuels can tackle the decarbonization of the transport sector. Dedicated biomass produced alongside food systems with low indirect land use change (iLUC) impact can broaden the feedstock availability, thus streamlining the supply chains. The objective of this study was the design and evaluation of advanced ethanol value chains for the Emilia‐Romagna region based on low iLUC feedstock. Two dedicated lignocellulosic crops (biomass sorghum and sunn hemp) were evaluated in double cropping systems alongside food crop residues (corn stover and wheat straw) as sources to simulate the value chains. A parcel‐level regional analysis was carried out, then the LocaGIStics2.0 model was used for the spatial design and review of the biomass delivery chain options regarding cost and greenhouse gas (GHG) emissions of the different feedstock mixes. Literature data on bioethanol production from similar feedstocks were used to estimate yields, process costs, and GHG emissions of a biorefinery process based on these biomasses. Within the chain options, GHG emissions were overly sensitive to cultivation input, mostly N‐fertilization. This considered, GHG emissions resulted similar across different feedstock with straw/stover (averaging 13 g CO2eq MJ−1 fuel), sunn hemp (14 g CO2eq MJ−1 fuel), and biomass sorghum (16 g CO2eq MJ−1 fuel). On the other hand, the bioethanol produced from biomass sorghum (608 € Mg−1 of bioethanol) was cheaper compared with straw (632 € Mg−1), sunn hemp (672 € Mg−1), and stover (710 € Mg−1). The bioethanol cost ranged from 0.0017 to 0.020 € MJ−1 fuel depending on the feedstock, with operations and maintenance impacting up to 90% of the final cost. In summary, a single bioethanol plant with an annual capacity of 250,000 Mg of biomass could replace from 5% to 7% of the Emilia‐Romagna's ethanol fuel consumption, depending on the applied sourcing scenario. Increasing lignocellulosic feedstock for advanced biofuels can help decarbonize the transport sector. The study evaluated two dedicated crops (biomass sorghum and sunn hemp) alongside food crop residues (corn stover and wheat straw) to simulate value chains. Greenhouse gas (GHG) emissions were similar across feedstocks (13–16 g CO2eq MJ−1 fuel). Biomass sorghum produced cheaper bioethanol (608 € Mg−1) compared to straw, sunn hemp, and stover. A single bioethanol plant could replace 5%–7% of Emilia‐Romagna's ethanol fuel consumption. Operations and maintenance significantly impacted costs.

The feeding pattern and control of energy intake in mice housed in groups are poorly understood. Here, we determined and quantified the normal feeding microstructure of social male and female mice of the C57BL/6J genetic background fed a chow diet. Mice at 10w, 20w and 30w of age showed the expected increase in lean and fat mass, being the latter more pronounced and variable in males than in females. Under ad libitum conditions, 20w and 30w old females housed in groups showed significantly increased daily energy intake when adjusted to body weight relative to age-matched males. This was the combined result of small increases in energy intake during the nocturnal and diurnal photoperiods of the day without major changes in the circadian pattern of energy intake or spontaneous ambulatory activity. The analysis of the feeding microstructure suggests sex- and age-related contributions of meal size, meal frequency and intermeal interval to the control of energy intake under stable energy balance, but not under negative energy balance imposed by prolonged fasting. During the night, 10-20w old females ate less frequently bigger meals and spent more time eating them resulting in reduced net energy intake relative to age-matched males. In addition, male and female mice at all ages tested significantly shortened the intermeal interval during the first hours of re-feeding in response to fasting without affecting meal size. Further, 20-30w old males lengthened their intermeal interval as re-feeding time increased to reach fed-levels faster than age-matched females. Collectively, our results suggest that the physiological mechanisms controlling meal size (satiation) and the non-eating time spent between meals (satiety) during stable or negative energy balance are regulated in a sex- and age-dependent manner in social mice.

To support the assessments of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), the IPBES Expert Group on Scenarios and Models is carrying out an intercomparison of biodiversity and ecosystem services models using harmonized scenarios (BES-SIM). The goals of BES-SIM are (1) to project the global impacts of land-use and climate change on biodiversity and ecosystem services (i.e., nature's contributions to people) over the coming decades, compared to the 20th century, using a set of common metrics at multiple scales, and (2) to identify model uncertainties and research gaps through the comparisons of projected biodiversity and ecosystem services across models. BES-SIM uses three scenarios combining specific Shared Socio-economic Pathways (SSPs) and Representative Concentration Pathways (RCPs) – SSP1xRCP2.6, SSP3xRCP6.0, SSP5xRCP8.6 – to explore a wide range of land-use change and climate change futures. This paper describes the rationale for scenario selection, the process of harmonizing input data for land use, based on the second phase of the Land Use Harmonization Project (LUH2), and climate, the biodiversity and ecosystem services models used, the core simulations carried out, the harmonization of the model output metrics, and the treatment of uncertainty. The results of this collaborative modeling project will support the ongoing global assessment of IPBES, strengthen ties between IPBES and the Intergovernmental Panel on Climate Change (IPCC) scenarios and modeling processes, advise the Convention on Biological Diversity (CBD) on its development of a post-2020 strategic plans and conservation goals, and inform the development of a new generation of nature-centred scenarios.

The climate effectiveness of forestation in Europe is debated, as it may provide more warming via solar energy absorption than evaporative cooling. Since forests play an important role in European climate policy, it is necessary to explore potential solutions to this issue in a warmer world. Here, based on experiments conducted with a regional climate model under several forest change scenarios, we find that conversion from coniferous to broadleaved trees in currently forested areas can provide cooling for summer hot extremes (e.g., reducing the monthly mean daily maximum temperature in July over Continental Europe by 0.6 °C). The conversion can also mitigate the undesired warming impacts of forestation with present-day forest composition in most of Europe, e.g., reversing effects on the monthly mean daily maximum temperature in July over Continental Europe from +0.3 °C to −0.7 °C. This study highlights the importance of considering tree species in European forest policy development and suggests that the Northern and Central regions should be prioritised for forestation over the Western and Southern parts. This study investigates the effects of forestation on temperature in Europe using climate model experiments. The findings indicate that conversion from coniferous to broadleaved trees in currently forested areas can provide cooling for summer hot extremes.

The European Union (EU) set clear climate change mitigation targets to reach climate neutrality, accounting for forests and their woody biomass resources. We investigated the consequences of increased harvest demands resulting from EU climate targets. We analysed the impacts on national policy objectives for forest ecosystem services and biodiversity through empirical forest simulation and multi-objective optimization methods. We show that key European timber-producing countries – Finland, Sweden, Germany (Bavaria) – cannot fulfil the increased harvest demands linked to the ambitious 1.5°C target. Potentials for harvest increase only exists in the studied region Norway. However, focusing on EU climate targets conflicts with several national policies and causes adverse effects on multiple ecosystem services and biodiversity. We argue that the role of forests and their timber resources in achieving climate targets and societal decarbonization should not be overstated. Our study provides insight for other European countries challenged by conflicting policies and supports policymakers.

Most scenarios from integrated assessment models (IAMs) that project greenhouse gas emissions include the use of bioenergy as a means to reduce CO2 emissions or even to achieve negative emissions (together with CCS – carbon capture and storage). The potential amount of CO2 that can be removed from the atmosphere depends, among others, on the yields of bioenergy crops, the land available to grow these crops and the efficiency with which CO2 produced by combustion is captured. While bioenergy crop yields can be simulated by models, estimates of the spatial distribution of bioenergy yields under current technology based on a large number of observations are currently lacking. In this study, a random-forest (RF) algorithm is used to upscale a bioenergy yield dataset of 3963 observations covering Miscanthus, switchgrass, eucalypt, poplar and willow using climatic and soil conditions as explanatory variables. The results are global yield maps of five important lignocellulosic bioenergy crops under current technology, climate and atmospheric CO2 conditions at a 0.5∘×0.5∘ spatial resolution. We also provide a combined “best bioenergy crop” yield map by selecting one of the five crop types with the highest yield in each of the grid cells, eucalypt and Miscanthus in most cases. The global median yield of the best crop is 16.3 t DM ha−1 yr−1 (DM – dry matter). High yields mainly occur in the Amazon region and southeastern Asia. We further compare our empirically derived maps with yield maps used in three IAMs and find that the median yields in our maps are > 50 % higher than those in the IAM maps. Our estimates of gridded bioenergy crop yields can be used to provide bioenergy yields for IAMs, to evaluate land surface models or to identify the most suitable lands for future bioenergy crop plantations. The 0.5∘×0.5∘ global maps for yields of different bioenergy crops and the best crop and for the best crop composition generated from this study can be download from https://doi.org/10.5281/zenodo.3274254 (Li, 2019).

While the gnotobiotic zebrafish have been a powerful model for interrogation of host-microbiota interactions, their use has been limited to early life stages due to complications of long-term husbandry. To address this limitation, we developed a simple protocol that enables rearing germ-free zebrafish well beyond larval stages. Germ-free fish exhibit physiological and developmental defects that mirror those described in mammalian counterparts supporting a conserved role for microbiota in vertebrate development and physiology. Our protocol provides a method to investigate microbial influences on adaptive immunity, metabolism, and chronic disease processes in zebrafish not possible with current methodologies. Given the rapid and simple methods for gnotobiotic derivation and the large number of transgenic animal lines available for zebrafish, we anticipate this model will accelerate mechanistic discovery of microbial impacts on host health.

A compact radiation imaging system capable of detecting, localizing, and characterizing special nuclear material (e.g. highly-enriched uranium, plutonium…) would be useful for national security missions involving inspection, emergency response, or war-fighters. Previously-designed radiation imaging systems have been large and bulky with significant portions of volume occupied by photomultiplier tubes (PMTs). The prototype imaging system presented here uses silicon photomultipliers (SiPMs) in place of PMTs because SiPMs are much more compact and operate at low power and voltage. The SiPMs are coupled to the ends of eight stilbene organic scintillators, which have an overall volume of 5.74 × 5.74 × 7.11 cm 3 . The prototype dual-particle imager’s capabilities were evaluated by performing measurements with a 252 Cf source, a sphere of 4.5 kg of alpha-phase weapons-grade plutonium known as the BeRP ball, a 6 kg sphere of neptunium, and a canister of 3.4 kg of plutonium oxide (7% 240 Pu and 93% 239 Pu ). These measurements demonstrate neutron spectroscopic capabilities, a neutron image resolution for a Watt spectrum of 9.65 ± 0.94° in the azimuthal direction and 22.59 ± 5.81° in the altitude direction, imaging of gamma rays using organic scintillators, and imaging of multiple sources in the same field of view.

Background and Objectives: Under the Paris Agreement, the European Union (EU) sets rules for accounting the greenhouse gas emissions and removals from forest land (FL). According to these rules, the average FL emissions of each member state in 2021–2025 (compliance period 1, CP1) and in 2026–2030 (compliance period 2, CP2) will be compared to a projected forest reference level (FRL). The FRL is estimated by modelling forest development under fixed forest management practices, based on those observed in 2000–2009. In this context, the objective of this study was to estimate the effects of large-scale uptake of alternative forest management models (aFMMs), developed in the ALTERFOR project (Alternative models and robust decision-making for future forest management), on forest harvest and forest carbon sink, considering that the proposed aFMMs are expanded to most of the suitable areas in EU27+UK and Turkey. Methods: We applied the Global Forest Model (G4M) for projecting the harvest and sink with the aFMMs and compared our results to previous FRL projections. The simulations were performed under the condition that the countries should match the harvest levels estimated for their FRLs as closely as possible. A representation of such aFMMs as clearcut, selective logging, shelterwood logging and tree species change was included in G4M. The aFMMs were modeled under four scenarios of spatial allocation and two scenarios of uptake rate. Finally, we compared our results to the business as usual. Results: The introduction of the aFMMs enhanced the forest sink in CP1 and CP2 in all studied regions when compared to the business as usual. Conclusions: Our results suggest that if a balanced mixture of aFMMs is chosen, a similar level of wood harvest can be maintained as in the FRL projection, while at the same time enhancing the forest sink. In particular, a mixture of multifunctional aFMMs, like selective logging and shelterwood, could enhance the carbon sink by up to 21% over the ALTERFOR region while limiting harvest leakages.

Compliance of member States to the Treaty on the Non-Proliferation of Nuclear Weapons is monitored through nuclear safeguards. The Passive Gamma Emission Tomography (PGET) system is a novel instrument developed within the framework of the International Atomic Energy Agency (IAEA) project JNT 1510, which included the European Commission, Finland, Hungary and Sweden. The PGET is used for the verification of spent nuclear fuel stored in water pools. Advanced image reconstruction techniques are crucial for obtaining high-quality cross-sectional images of the spent-fuel bundle to allow inspectors of the IAEA to monitor nuclear material and promptly identify its diversion. In this work, we have developed a software suite to accurately reconstruct the spent-fuel cross sectional image, automatically identify present fuel rods, and estimate their activity. Unique image reconstruction challenges are posed by the measurement of spent fuel, due to its high activity and the self-attenuation. While the former is mitigated by detector physical collimation, we implemented a linear forward model to model the detector responses to the fuel rods inside the PGET, to account for the latter. The image reconstruction is performed by solving a regularized linear inverse problem using the fast-iterative shrinkage-thresholding algorithm. We have also implemented the traditional filtered back projection (FBP) method based on the inverse Radon transform for comparison and applied both methods to reconstruct images of simulated mockup fuel assemblies. Higher image resolution and fewer reconstruction artifacts were obtained with the inverse-problem approach, with the mean-square-error reduced by 50%, and the structural-similarity improved by 200%. We then used a convolutional neural network (CNN) to automatically identify the bundle type and extract the pin locations from the images; the estimated activity levels finally being compared with the ground truth. The proposed computational methods accurately estimated the activity levels of the present pins, with an associated uncertainty of approximately 5%.