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Plant responses to biotic and abiotic legacies left in soil by preceding plants is known as plant–soil feedback (PSF). PSF is an important mechanism to explain plant community dynamics and plant performance in natural and agricultural systems. However, most PSF studies are short-term and small-scale due to practical constraints for field-scale quantification of PSF effects, yet field experiments are warranted to assess actual PSF effects under less controlled conditions. Here we used unmanned aerial vehicle (UAV)-based optical sensors to test whether PSF effects on plant traits can be quantified remotely. We established a randomized agro-ecological field experiment in which six different cover crop species and species combinations from three different plant families (Poaceae, Fabaceae, Brassicaceae) were grown. The feedback effects on plant traits were tested in oat (Avena sativa) by quantifying the cover crop legacy effects on key plant traits: height, fresh biomass, nitrogen content, and leaf chlorophyll content. Prior to destructive sampling, hyperspectral data were acquired and used for calibration and independent validation of regression models to retrieve plant traits from optical data. Subsequently, for each trait the model with highest precision and accuracy was selected. We used the hyperspectral analyses to predict the directly measured plant height (RMSE = 5.12 cm, R2 = 0.79), chlorophyll content (RMSE = 0.11 g m−2, R2 = 0.80), N-content (RMSE = 1.94 g m−2, R2 = 0.68), and fresh biomass (RMSE = 0.72 kg m−2, R2 = 0.56). Overall the PSF effects of the different cover crop treatments based on the remote sensing data matched the results based on in situ measurements. The average oat canopy was tallest and its leaf chlorophyll content highest in response to legacy of Vicia sativa monocultures (100 cm, 0.95 g m−2, respectively) and in mixture with Raphanus sativus (100 cm, 1.09 g m−2, respectively), while the lowest values (76 cm, 0.41 g m−2, respectively) were found in response to legacy of Lolium perenne monoculture, and intermediate responses to the legacy of the other treatments. We show that PSF effects in the field occur and alter several important plant traits that can be sensed remotely and quantified in a non-destructive way using UAV-based optical sensors; these can be repeated over the growing season to increase temporal resolution. Remote sensing thereby offers great potential for studying PSF effects at field scale and relevant spatial-temporal resolutions which will facilitate the elucidation of the underlying mechanisms. van der Meij et al_Biogeosciences2017_dataThe experimental set-up, treatments, data collection and data analyses are thoroughly described in the Biogeoscience manuscript ‘Remote sensing of plant trait responses to field-based plant-soil feedback using UAV-based optical sensors’ doi:10.5194/bg-2016-452. Therefore we refer to the manuscript for detailed information an here we provide a brief summary to enable readers to follow what the data entail. The data were collected from a 2-year field experiment with plant rotations in a full factorial design. The plant treatments we focused on are legacy effects of the plant treatments (listed below) to the following oat crop. In this oat crop we quantified several plant traits both in situ and via remote sensing by use of UAV and hyperspectral and EGB sensors. The experiment was set-up in five randomized field blocks. We used part of the in situ collected data to parameterize the hyperspectral data based models and we validated these models with the other half of the field plots. Plant treatments Fa= fallow Lp= Lolium perenne Rs= Raphanus sativus Tr= Trifolium repens Vs= Vicia sativa Lp+Tr= 50:50 species mixture (relative to the monoculture seed densities) of the species Lp and Tr Rs+Vs= 50:50 species mixture (relative to the monoculture seed densities) of the species Rs and Vs

The Flameless Combustion (FC) regime has been pointed out as a promising combustion technique to lower the emissions of nitrogen oxides (NOx) while maintaining low CO and soot emissions, as well as high efficiencies. However, its accurate modeling remains a challenge. The prediction of pollutant species, especially NOx, is affected by the usually low total values that require higher precision from computational tools, as well as the incorporation of relevant formation pathways within the overall reaction mechanism that are usually neglected. The present work explores a multiple step modeling approach to tackle these issues. Initially, a CFD solution with simplified chemistry is generated [both the Eddy Dissipation Model (EDM) as well as the Flamelet Generated Manifolds (FGM) approach are employed]. Subsequently, its computational cells are clustered to form ideal reactors by user-defined criteria, and the resulting Chemical Reactor Network (CRN) is subsequently solved with a detailed chemical reaction mechanism. The capabilities of the clustering and CRN solving computational tool (AGNES—Automatic Generation of Networks for Emission Simulation) are explored with a test case related to FC. The test case is non-premixed burner based on jet mixing and fueled with CH4 tested for various equivalence ratios. Results show that the prediction of CO emissions was improved significantly with respect to the CFD solution and are in good agreement with the experimental data. As for the NOx emissions, the CRN results were capable of reproducing the non-monotonic behavior with equivalence ratio, which the CFD simulations could not capture. However, the agreement between experimental values and those predicted by CRN for NOx is not fully satisfactory. The clustering criteria employed to generate the CRNs from the CFD solutions were shown to affect the results to a great extent, pointing to future opportunities in improving the multi-step procedure and its application.

The prevailing need for a more sustainable management of natural resources depends not only on the decisions made by governments and the will of the population, but also on the knowledge of the role of energy in our society and the relevance of preserving natural resources. In this sense, critical work is being done to instill key concepts—such as the circular economy and sustainable energy—in higher education institutions. In this way, it is expected that future professionals and managers will be aware of the importance of energy optimization, and will learn a series of computational methods that can support the decision-making process. In the context of higher education, this paper reviews the main trends and challenges related to the concepts of circular economy and sustainable energy. Besides, we analyze the role of simulation and serious games as a learning tool for the aforementioned concepts. Finally, the paper provides insights and discusses open research opportunities regarding the use of these computational tools to incorporate circular economy concepts in higher education degrees. Our findings show that, while efforts are being made to include these concepts in current programs, there is still much work to be done, especially from the point of view of university management. In addition, the analysis of the teaching methodologies analyzed shows that, although their implementation has been successful in favoring the active learning of students, their use (especially that of serious games) is not yet widespread.

Safety and Security Science

The beginning of the 21st century is defined by geopolitical tensions around resources, an expected shortage of fossil fuel resources and the emerging climate crisis, amplifying the urgency of the transition to renewable energy sources. This energy transition has been at the forefront of public discussion, framed by the 2016 Paris Agreement and the 2019 European Green Deal. In this context, European member states must accelerate the decarbonisation of their industries and the transition to renewable energy sources. As each member state attempts to deal with this challenge, issues associated with social and spatial justice in coal-intensive European regions arise, calling for a coordinated, inclusive and collaborative plan aiming at a just transition. This thesis uses the coal intensive region of Western Macedonia as a case study and proposes the reconfiguration of the energy landscape by formulating a territorial vision, based on an analysis and the evaluation of scenario building. More specifically, it develops a series of spatial and non-spatial strategies aimed at restoring ecological integrity, diversifying the energy production, re-using heritage spaces and promoting governance collaboration and social inclusivity. By examining the vulnerabilities, potential, and opportunities present in the territory of Western Macedonia, this thesis seeks to promote the reconfiguration of Western Macedonia, embracing principles of regenerative development, adaptive re-use, participatory planning and collaborative governance. ; Architecture, Urbanism and Building Sciences | Landscape Architecture

Duurzaamheid is uitgegroeid tot een groot deel van de bouwsector, waar milieu-classificatiesystemen vaker worden gebruikt. Dit onderzoek draait om een case study onderzoek met kwalitatieve interviews uitgevoerd met een groot bouwbedrijf uit Nederland met het oog op de ontwerpfase van een milieu-classificatiesysteem, BREEAM-NL, en hoe het invloed heeft op het gehele bouwproces. Door het verzamelen van verschillende informatie van personen en documenten wordt het proces geanalyseerd. Het rapport biedt een discussie op basis van theorieën binnen duurzaamheid en organisatorische procesveranderingen. De algemene opvatting is dat BREEAM een extra waarde aan het gebouw toevoegt en een meer milieubewuste onderneming genereert. Het BREEAM-proces is niet geïntegreerd in het bouwproces, wat heeft bijgedragen tot een vertraging van het proces. Dit kan veranderd worden door een proces ondersteuning van het bouwteam, evaluatie van het systeem en heldere communicatie tussen de verschillende partijen. ; Design and Construct Management ; Real Estate & Housing ; Architecture

The International Maritime Organization (IMO) issued on the 13th of April 2018 a press release titled: “UN body adopts climate change strategy for shipping”. [1] This document illustrates the commitment of the IMO to significantly reduce the emission of greenhouse gasses (GHG) from international shipping in coming decades. However, the question arises whether the ambitious goals, set out in this press release, are feasible to be met. This aim of this thesis is to investigate the economic and technological feasibility of powering a vessel while emitting minimal greenhouse gasses in 2050. The focus will be on power plant configuration consisting of an energy storage medium and energy converter. A case study, concerning a representative ROPAX ferry built in 2050, is performed to illustrate the feasibility of using such a power plant configuration. Energy storage media considered are hydrogen, ammonia and batteries. The use of internal combustion engines, fuel cells and an ammonia reformer are also investigated. The performance of power plant configurations with respect to their estimated greenhouse gas emission, overall weight, required volume, initial investment cost and cost of the required energy per day of operation is evaluated and based on the results of this study several conclusions are drawn. • First and foremost is the need to reduce the price difference of hydrogen and ammonia compared to LNG. Without this reduction, no single synthetic fuel can be considered economically feasible. Three options to reduce the price difference are identified: - a high LNG price including high emission tax; - a low commercial electric energy price; or - synthetic fuel production using excess renewable energy. Especially the last of these three is considered to be a feasible measure due to the expected presence of excess energy from solar and wind farms. • The second conclusion is that using fuel cells or batteries are the most environmentally friendly option due to the emission of N2O when using internal combustion ...

Abstract Life Cycle Assessment (LCA) is a powerful tool for achieving sustainability. Traditional LCAs analyze well defined and developed industrial systems, but recent developments of LCA focus on analyzing emerging technologies which are not yet optimized with respect to energy and materials. Therefore, LCA results of ex-ante applications can be very different from ex-post applications for the same system. The purpose of this study is to show the different effects of data scales on LCA results regarding global warming, fine particulate matter formation, terrestrial acidification and freshwater eutrophication potentials. For this purpose torrefaction technology was selected as the case study and assessed based on bench scale data, lab scale data, data derived from process simulations, pilot scale data and commercial scale data. Considered environmental impacts were global warming, fine particulate matter formation, terrestrial acidification and freshwater eutrophication. Results showed that process efficiencies improved significantly between the bench scale system and systems with higher technology readiness levels (TRLs), such as pilot, process simulations and commercial scale systems. Furthermore, process simulations result in scores closer to commercial scale regarding all considered environmental impacts. However, if LCA practitioners focus only on global warming impact, then pilot scale is also a good alternative. Finally, due to torrefaction technology being relatively simple in terms of raw materials input, we suggest more complex chemical systems to be assessed with LCA in various TRLs.