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1. Hippocampal and auditory contributions to speech segmentation

Author

Ramos-Escobar, Neus, Mercier, Manuel, Trébuchon-Fonséca, Agnès, Rodriguez-Fornells, Antoni, François, Clément, and Schön, Daniele

Subjects
Quantitative Biology - Neurons and Cognition
Abstract

Statistical learning has been proposed as a mechanism to structure and segment the continuous flow of information in several sensory modalities. Previous studies proposed that the medial temporal lobe, and in particular the hippocampus, may be crucial to parse the stream in the visual modality. However, the involvement of the hippocampus in auditory statistical learning, and specifically in speech segmentation is less clear. To explore the role of the hippocampus in speech segmentation based on statistical learning, we exposed seven pharmaco-resistant temporal lobe epilepsy patients to a continuous stream of trisyllabic pseudowords and recorded intracranial stereotaxic electro-encephalography (sEEG). We used frequency-tagging analysis to quantify neuronal synchronization of the hippocampus and auditory regions to the temporal structure of words and syllables of the stream. Results show that while auditory regions highly respond to syllable frequency, the hippocampus responds mostly to word frequency. These findings provide direct evidence of the involvement of the hippocampus in speech segmentation process and suggest a hierarchical organization of auditory information during speech processing., Comment: Cortex, Elsevier, 2022

Published
2022
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10. Understanding Uncertainty in Market-Mediated Responses to US Oilseed Biodiesel Demand: Sensitivity of ILUC Emission Estimates to GLOBIOM Parametric Uncertainty

Author

Escobar, Neus, Valin, Hugo, Frank, Stefan, Galperin, Diana, Wade, Christopher M., Ringwald, Leopold, Tanner, Daniel, Hinkel, Niklas, Havlík, Petr, Baker, Justin S., Lie, Sharyn, and Ramig, Christopher

Abstract

The life cycle greenhouse gas (GHG) emissions of biofuels depend on uncertain estimates of induced land use change (ILUC) and subsequent emissions from carbon stock changes. Demand for oilseed-based biofuels is associated with particularly complex market and supply chain dynamics, which must be considered. Using the global partial equilibrium model GLOBIOM, this study explores the uncertainty in market-mediated impacts and ILUC-related emissions from increasing demand for soybean biodiesel in the United States in the period 2020–2050. A one-at-a-time (OAT) analysis and a Monte Carlo (MC) analysis are performed to assess the sensitivity of modeled ILUC-GHG emissions intensities (gCO2e/MJ) to varying key economic and biophysical model parameters. Additionally, the influence of the approach on the simulation of future ILUC effects is explored using two alternative ILUC-GHG metrics: a comparative-static approach for 2030 and a recursive-dynamic approach using model outputs through 2050. We find that projected ILUC-GHG values largely vary based on which vegetable oils replace diverted soybean oil, market responses to coproducts, and the carbon content of land converted for agricultural use. These are all, in turn, subject to decision uncertainty through the choice of the modeling approach and the time horizon considered for each ILUC-GHG metric. Given the longer simulation period, ILUC-GHG emission uncertainty ranges increase under the recursive-dynamic approach (42.4 ± 25.9 gCO2e/MJ) compared to the comparative-static approach (40.8 ± 20.5 gCO2e/MJ). The combination of MC analysis with other techniques such as Bayesian Additive Regression Trees (BART) is powerful for understanding model behavior and clarifying the sensitivity of market responses, ILUC, and associated GHG emissions to specific model parameters when simulated with global economic models. The BART reveals that biophysical parameters generate more linear ILUC-GHG responses to changes in assumed parameter values while changes in economic parameters lead to more nonlinear ILUC-GHG results as multiple effects at the interplay of food, feed, and fuel uses overlap. The choice of the recursive-dynamic metric allows capturing the longer-term evolution of ILUC while generating additional uncertainties derived from the baseline definition.

Published
2025
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13. Word Learning in Aphasia: Treatment Implications and Structural Connectivity Analyses

Author

Coran, Monica, Rodriguez-Fornells, Antoni, Ramos-Escobar, Neus, Laine, Matti, and Martin, Nadine

Abstract

Objective: Of current interest in aphasia research is the relevance of what we can learn from studying word learning ability in aphasia. In a preliminary study, we addressed 2 issues related to the novel word learning ability of individuals with aphasia. First, as word learning engages large-scale cognitive-linguistic systems (language skills, verbal short-term memory [STM], other memory and executive functions), we probed whether novel word learning practice in 3 people with aphasia could stimulate these language-related systems. Second, as lesion correlates affecting word learning in aphasia remain unclear, we examined whether the structural integrity of the left arcuate fasciculus (AF) in the same 3 individuals is related to outcomes of novel word learning practice. Method: To stimulate word learning systems, our 3 participants practiced for 4 weeks with an explicit novel word-novel referent word learning task, adopted from the Ancient Farming Equipment learning paradigm (Laine & Salmelin, 2010). The participants' progress on receptive and expressive novel word learning was followed up, and their language and verbal STM abilities as well as single-session novel word learning (Learning to Name Aliens by Gupta, Martin, Abbs, Schwartz, & Lipinski, 2006) were tested before and after the practice period. To address the second question, we analyzed the participants' structural magnetic resonance images with respect to the integrity of the left AF and its overlap with the lesion areas. Results: All participants showed some receptive word learning in the trained task, as well as improvements in verbal STM span at posttesting. Two of the 3 participants also showed improved performance on some of the language outcome measures. One participant with a partially spared left AF, especially temporoparietal connections, exhibited better word learning performance than the other 2 who had larger damage and disconnection of the AF. Conclusions: Although the present results are preliminary, they open the possibility that novel word learning practice in aphasia may stimulate remaining word learning mechanisms in aphasia and thereby influence language and verbal STM abilities. These results also suggest that preservation of novel word learning ability in aphasia in part depends on the integrity of the left arcuate track.

Published
2020
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18. Optimised diets for achieving One Health:A pilot study in the Rhine-Ruhr Metropolis in Germany

Author

Paris, Juliana Minetto Gellert, Escobar, Neus, Falkenberg, Timo, Gupta, Shivam, Heinzel, Christine, Junior, Eliseu Verly, Jolliet, Olivier, Borgemeister, Christian, Nöthlings, Ute, Paris, Juliana Minetto Gellert, Escobar, Neus, Falkenberg, Timo, Gupta, Shivam, Heinzel, Christine, Junior, Eliseu Verly, Jolliet, Olivier, Borgemeister, Christian, and Nöthlings, Ute

Abstract

Dietary changes are needed to align the global food systems with the planetary boundaries and contribute to Sustainable Development Goals. We employed a Life Cycle Assessment (LCA) framework, extended with indicators on human health and animal welfare, to assess 2020 food consumption data of a pilot sample collected through an online survey in the Rhine-Ruhr Metropolis (Germany). Feasible optimisation scenarios representing alternative sustainable choices towards overarching environmental, societal and policy goals were explored. Meat and meat products contributed most to overall environmental impacts (e.g., climate change, terrestrial acidification), and fish and seafood to animal welfare loss (e.g., animal lives lost, animal life years suffered). Sodium intake was the most contributing risk factor for life minutes lost. The combined optimisation scenario reduces 55% of greenhouse gas emissions, improves human health indicators by 25% and reduces animal welfare loss substantially (by 52-97%). This is possible with a shift towards flexitarian and vegetarian dietary scenarios. These optimisations deliver improvements across One Health dimensions with marginal changes in dietary scenarios and align with the sustainability goals of the EU Green Deal. Working with regional data can offer advantages in obtaining more realistic baseline dietary information to promote localised dietary shifts. While this research has limitations regarding sample representativeness, it can serve as a case study to encourage sustainable consumption in the Rhine-Ruhr region.

Published
2024

25. Uncertainty in life cycle greenhouse gas emissions of sustainable aviation fuels from vegetable oils

Author

Seber, Gonca, Escobar, Neus, Valin, Hugo, Malina, Robert, SEBER OLCAY, Gonca, Escobar, Neus, Valin, Hugo, and MALINA, Robert

Subjects
Life cycle assessment, Renewable Energy, Sustainability and the Environment, Biofuels, Sustainable aviation fuel, Vegetable oils, Greenhouse gas emissions reductions, Land use change
Abstract

Sustainable aviation fuel (SAF) is one of the most promising short-to medium-term term options to mitigate greenhouse gas (GHG) emissions from aviation. Life cycle assessment (LCA) is commonly used to estimate GHG emissions from SAF in comparison to fossil kerosene. While there are several studies reporting the GHG emissions from SAF, uncertainty in the results is not always addressed in a comprehensive way.In this work, GHG emissions of hydroprocessed esters and fatty acids (HEFA) fuels derived from jatropha (Jatropha curcas), pennycress (Thlaspi arvense), castor (Ricinus communis), energy tobacco (Nicotiana tabacum, Solaris) and Salicornia (Salicornia bigelovii) oils were estimated. A stochastic methodology was employed where parametric uncertainty was propagated using Monte Carlo simulations. Uncertainty due to methodological choices was incorporated through scenario analyses. Emissions from direct land use change (DLUC) and the associated uncertainty were assessed under the IPCC Tier 1 approach by considering alternative land use tran-sitions per feedstock.Analyzed HEFA pathways provide GHG emissions benefits (34-65%) in comparison to fossil kerosene when DLUC emissions are not considered. Parametric uncertainty yields up to 26% deviation from the median well-to -wake GHG emissions. Changing the allocation choice for the oil extraction step, from the base assumption of energy-based allocation to mass-or market-based, can impact the results by up to 46%. DLUC is a more sig-nificant source of uncertainty than both parametric uncertainty and allocation assumptions in the analysis. DLUC emissions negate any GHG savings from HEFA fuels if forests or natural shrublands are lost. The research efforts from Hasselt University and IIASA were supported by the European Union’s H2020 project ALTERNATE “Assessment on Alternative Aviation Fuels Development” (Grant 875538).

Published
2022

30. Sustainability implications of transformation pathways for the bioeconomy

Author

Federal Ministry of Education and Research (Germany), German Research Foundation, Ministry of Innovation, Science and Research of the State of North Rhine-Westphalia, Stark, Sascha, Biber-Freudenberger, Lisa, Dietz, Thomas, Escobar, Neus, Förster, Jan Janosch, Henderson, James, Laibach, Natalie, Börner, Jan, Federal Ministry of Education and Research (Germany), German Research Foundation, Ministry of Innovation, Science and Research of the State of North Rhine-Westphalia, Stark, Sascha, Biber-Freudenberger, Lisa, Dietz, Thomas, Escobar, Neus, Förster, Jan Janosch, Henderson, James, Laibach, Natalie, and Börner, Jan

Abstract

Countries around the world are devising and implementing bioeconomy strategies to initiate transformation towards sustainable futures. Modern concepts of bioeconomy extend beyond bio-based energy provision and include: (1) the substitution of fossil resource-based inputs to various productive sectors, such as the chemical industry and the construction sector, (2) more efficient, including new and cascading uses of biomass, and (3) a low bulk, but high-value biologisation of processes in agro-food, pharmaceutical, and recycling industries. Outcomes of past attempts at engineering transformation, however, proved to be context-dependent and contingent on appropriate governance measures. In this paper we theoretically motivate and apply a system-level theory of change framework that identifies central mechanisms and four distinct pathways, through which bio-based transformation can generate positive or negative outcomes in multiple domains of the Sustainable Development Goals. Based on emblematic examples from three bio-based sectors, we apply the framework illustrating how case-specific mixes of transformation pathways emerge and translate into outcomes. We find that the observed mixes of transformation pathways evoke distinct mechanisms that link bioeconomic change to sustainability gains and losses. Based on this insight we derive four key lessons that can help to inform the design of strategies to enable and regulate sustainable bioeconomies.

Published
2022

31. Promoting extensive cattle production in the European Union has major implications for global agricultural trade and climate change

Author

Haddad, Salwa, Escobar, Neus, Bruckner, Martin, and Britz, Wolfgang

Subjects
Pastureland, Agricultural and Food Policy, CGE-MRIO approach, Cattle, Environmental Economics and Policy, Land Economics/Use, Land Use Change (LUC) and GHG emissions
Abstract

This paper assesses the potential market-mediated impacts, including global Land Use Change (LUC) and GHG emissions, from increased subsidies to pastureland-based livestock sectors in the EU, through a “tax recycling strategy” simulated against a baseline under SSP2 up to 2030. The budget neutral increase in the level of pastureland subsidy rates in different Member States is achieved by a decrease in land subsidies to other cropping activities. We employ an integrated CGE-MRIO approach, in which we link a recursive dynamic version of the well-known GTAP-CGE model, called GTAP-RDEM to the FABIO MRIO. This approach allows to take advantages from both methods. FABIO offers better resolution with regards to agricultural sectors than in the GTAP database, while the combined use of this MRIO with a CGE model allows to consider price and income dependent feedbacks, required for policy analyses and long run assessments of changes in the global economy. Results show that the redistribution of land-based subsidies provokes significant changes in agricultural markets across the EU. Pastureland areas and cattle production increases in almost all EU Member States, whereas crop land and crop production decreases. The resulting increase in crop prices translates into reduced output of intensive animal production sector, mainly pig and poultry, which rely on concentrate feed to a larger extent compared to cattle. As a result of the decrease in cropland area and overall crop production in the EU, most EU countries increase imports of grain, oilseeds, and cakes from major agricultural producers, essentially soybean cake from Brazil and North America. This generates significant LUC and related GHG emissions that spill outside the EU, mainly in major feed exporters while some emission saving is observed at global level.

Published
2022
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32. Neural signatures of word learning in adults and children: a multi-methodological approach

Author

Ramos Escobar, Neus, Rodríguez Fornells, Antoni, François, Clément, and Universitat de Barcelona. Departament de Cognició, Desenvolupament i Psicologia de l'Educació

Subjects
Sistemes d'imatges, Anàlisi del discurs, Language acquisition, Sistemas de imágenes, Ciències de la Salut, 159.9, Adquisició del llenguatge, Neuropsychology, Análisis del discurso, Imaging systems, Neuropsicologia, Adquisición del lenguaje, Neuropsicología, Discourse analysis
Abstract

[eng] Language is one of the main traits of humans. Language is used to transmit information about thoughts, knowledge, and feelings in a very flexible way. Since childhood, humans show an innate ability to acquire language and to communicate. However, the easiness that children show to acquire language highly contrasts with the difficulty that occurs during adulthood. How both children and adults learn and develop language skills has been a matter of interest in many investigations. One of the milestones of language learning is vocabulary acquisition. This process requires the initial isolation of the novel word from the fluent speech and the subsequent association to a meaningful representation. Research carried out in the last decades to study the mechanisms involved in language learning in adults and children provided wide knowledge of the process. Specifically, the development of neuroimaging techniques such as electroencephalography (EEG), magnetoencephalography (MEG), and magnetic resonance imaging (MRI) has allowed shedding light on the neural mechanisms that subserve word learning. Nonetheless, despite the advances in the field, there are still many unresolved questions about how the different learning steps co-occur on time and which brain regions are involved in each process. The main goal of this Ph.D. thesis is to extend the current knowledge on the neural bases of language learning and vocabulary acquisition in both adults and children by using behavioral and electrophysiological measures. Specifically, we aim to understand better how the initial encoding and the gradual consolidation of novel word forms occur. We also aim to understand how speech segmentation and meaning mapping co-occur and how multimodal information is used in this process to facilitate the learning. Finally, we also want to directly assess the contribution of the hippocampus in the speech segmentation process. Here, we developed three experiments involving both children and adult populations and different experimental tasks to answer these questions and extend the current knowledge on the field. Study I explored how novel word forms are gradually learned and integrated onto the mental lexicon. We developed two event-related potential word learning experiments in which novel word forms are associated with novel objects. In the first experiment, a group of 25 adults was exposed to the novel word-picture pairs over 5-day training sessions, while EEG was recorded during the first and last training session. This experiment allowed us to follow the neural traces of the gradual build-up of mental representation for the novel items, from the initial encoding to the later consolidation of the word forms. This was observable by a decrease of the N400 amplitude within and between sessions and a shift of the topographical distribution from a frontal distribution the first day of training to a parietal distribution the fifth day. In Experiment 2, we aimed to replicate the first experiment and exclude possible confounds of the role of repetition and exposure in the task. With this aim, we randomly assigned 38 new participants to a consistent (Cons) or inconsistent (Incons) learning group. While in the Cons group, word- picture associations were consistent throughout the task; it was not the case for the Incons group. We showed that N400 modulations occurred only in the consistent group evidencing that results of Experiment 1 derived from learning rather than a repetition effect. Overall, we showed that both fast and slow neuroplastic changes over frontal and temporal regions support the gradual build-up of new memory traces during online word learning. In Study II, we explored speech segmentation and meaning mapping, two processes that have been separately studied in the literature. We also aimed to examine the role of multi-sensory cueing in both processes. With these aims, sixty 9-year-old children performed an audio-visual speech segmentation task while EEG was recorded. We showed that children, as adults, can simultaneously segment the words and associate them with meaning. Furthermore, our results showed increased neuronal activity at word and syllable frequency and enhanced fronto- occipital connectivity. The results suggest that multisensory cueing promotes that participants direct the attention to visual cues facilitating the word learning process. In study III, we aimed to directly test whether the hippocampus is involved in speech segmentation based on statistical learning. We observed pharmaco-resistant epileptic patients' oscillatory activity with implanted depth electrodes while they performed a speech segmentation task. We showed that while auditory regions highly responded to syllable frequency, the hippocampus responded only to words. The finding provides direct evidence of the hippocampus's involvement in speech segmentation and advocates for a hierarchical organization of auditory information during speech processing. Altogether, the thesis provides novel insights about how new words are extracted and encoded into the lexico-semantic network. The findings showed here may provide new insights to develop novel lines of investigation that improve our understanding of the neural and cognitive mechanisms involved in language learning and vocabulary acquisition., [spa] El lenguaje es una de las características únicas de la humanidad. Los seres humanos utilizan el lenguaje para transmitir información: pensamientos, conocimiento y emociones de una forma muy flexible e inigualable a ningún otro tipo de lenguaje. Sin embargo, la facilidad con la que los niños aprenden el lenguaje contrasta con la dificultad de esta misma tarea como adultos. Entender cómo los adultos y los niños aprenden nuevas lenguas ha sido tema de interés de muchas investigaciones en el campo tanto de la neurociencia como de la psicología. Uno de los puntos de inflexión en el aprendizaje del lenguaje tanto en adultos como en niños es la adquisición de vocabulario. Este complejo proceso requiere el aislamiento de la nueva palabra de entre el discurso del habla y su consiguiente asociación a un contenido semántico. Investigaciones realizadas durante las últimas décadas han explorado los mecanismos neuropsicológicos implicados en el aprendizaje del lenguaje tanto en adultos como en niños. Específicamente, el desarrollo de técnicas de neuroimagen, como la electroencefalografía (EEG), la magnetoencefalografía (MEG) y la resonancia magnética (MRI), han permitido ampliar el conocimiento de los mecanismos neurales y electrofisiológicos de la adquisición de vocabulario. Sin embargo, a pesar de los grandes avances en el campo, hay todavía un gran número de cuestiones sin resolver. El objetivo principal de esta tesis es ampliar el conocimiento actual sobre las bases neurológicas del aprendizaje del lenguaje y la adquisición de vocabulario tanto en adultos como en niños mediante técnicas de electrofisiología y paradigmas conductuales. Específicamente, el objetivo es entender mejor cómo ocurre la codificación inicial de las palabras y su consiguiente integración en el lexicón. El segundo objetivo de esta tesis es explorar cómo la segmentación del discurso hablado y la asociación de nuevas palabras a un referente semántico ocurre, así como entender cómo la integración de información de forma multimodal influye en estos procesos para facilitar el aprendizaje. Finalmente, también tiene como objetivo explorar el papel del hipocampo en la segmentación del discurso del habla. Para ello, hemos desarrollado tres experimentos con diferentes tareas experimentales que hemos administrado tanto a adultos como a niños. En el Estudio I, mediante un diseño longitudinal, hemos explorado cómo las nuevas palabras se van aprendiendo e integrando gradualmente al lexicón. Para ello, hemos desarrollado dos experimentos en los que nuevas palabras eran presentadas junto con nuevos objetos. En el Experimento 1, se expuso a un grupo de 25 participantes a asociaciones de palabras-objetos a lo largo de 5 sesiones experimentales mientras registramos la actividad eléctrica del cerebro el primer y último día. Este experimento nos permitió explorar los marcadores neurales de la formación de nuevas representaciones léxico-semánticas: desde la codificación inicial hasta la consolidación de las nuevas palabras. Esto fue observable por una disminución de la amplitud de la N400 tanto dentro de una misma sesión como entre sesiones. También observamos un cambio de la distribución topográfica de la N400, inicialmente frontal, pero que pasó a ser parietal el último día de entrenamiento. En el Experimento 2, quisimos replicar el primer experimento y a la vez confirmar que los resultados que habíamos encontrado no eran fruto de la repetición y exposición, sino del aprendizaje. Con este objetivo, asignamos de forma aleatoria 38 nuevos participantes a dos grupos, un grupo de aprendizaje consistente (Cons) y un grupo de aprendizaje no-consistente (Incons). En el grupo Cons las asociaciones palabra-objeto eran consistentes a lo largo de la tarea, mientras que en el grupo Incons las asociaciones iban cambiando en cada exposición de forma que dificultaban/impedían el aprendizaje. Los resultados confirmaron que la modulación de la N400 era debido al aprendizaje y no a la simple exposición, ya que ésta solo se produjo en el grupo Cons, mientras que en el grupo Icons no variaba. En definitiva, el conjunto de experimentos demostró que los cambios plásticos del cerebro, tanto los rápidos como los lentos, son la base de la adquisición de nuevas palabras. En el Estudio II, exploramos la interacción entre la extracción de nuevas palabras dentro del discurso del habla y la asociación de estas nuevas palabras a su significado, dos pasos que típicamente se han considerado de forma independiente en el aprendizaje del lenguaje. También teníamos como objetivo explorar cómo la integración multisensorial influye en este proceso. Para ello expusimos a 60 niños de nueve años de edad a una tarea de segmentación audiovisual mientras registrábamos la actividad eléctrica del cerebro (EEG). Los resultados mostraron que los niños, igual que los adultos, pueden segmentar las palabras y asociarlas a su referente semántico de forma simultánea. Además, los resultados mostraron un incremento de la actividad neuronal a la frecuencia de las palabras y de las sílabas, así como un augmento de la conectividad entre regiones frontooccipitales a esas frecuencias. Estos resultados sugerían que la integración multisensorial facilita que los niños dirijan la atención visual hacia las pistas visuales, facilitando así el aprendizaje de nuevas palabras. El Estudio III tenía como objetivo evaluar el papel del hipocampo en la segmentación del discurso del habla mediante mecanismos de "aprendizaje estadístico". Para ello registramos la actividad eléctrica de pacientes epilépticos que tenían implantados electrodos intracorticales mientras realizaban una tarea de segmentación del habla. Los resultados mostraron que el córtex auditivo respondía claramente a las sílabas, mientras que el hipocampo respondía solo a las palabras. Este resultado demostró la implicación del hipocampo en la segmentación del discurso basada en aprendizaje estadístico. Estos resultados sugieren a su vez una organización jerárquica del procesamiento auditivo durante la segmentación del habla. En conjunto, esta tesis amplía el conocimiento existente sobre cómo las nuevas palabras se extraen y se codifican en el léxico. Los resultados mostrados aquí proporcionan nuevos conocimientos e indicios para desarrollar nuevas líneas de investigación que mejorarán nuestro entendimiento sobre los mecanismos neurales y cognitivos implicados en el aprendizaje del lenguaje y en la adquisición de nuevo vocabulario.

Published
2021

37. Spatially-explicit footprints of agricultural commodities: Mapping carbon emissions embodied in Brazil's soy exports

Author

UCL - SST/ELI/ELIC - Earth & Climate, Escobar, Neus, Tizado, E. Jorge, Zu Ermgassen, Erasmus, Löfgren, Pernilla, Börner, Jan, Godar, Javier, UCL - SST/ELI/ELIC - Earth & Climate, Escobar, Neus, Tizado, E. Jorge, Zu Ermgassen, Erasmus, Löfgren, Pernilla, Börner, Jan, and Godar, Javier

Abstract

Reliable estimates of carbon and other environmental footprints of agricultural commodities require capturing a large diversity of conditions along global supply chains. Life Cycle Assessment (LCA) faces limitations when it comes to addressing spatial and temporal variability in production, transportation and manufacturing systems. We present a bottom-up approach for quantifying the greenhouse gas (GHG) emissions embedded in the production and trade of agricultural products with a high spatial resolution, by means of the integration of LCA principles with enhanced physical trade flow analysis. Our approach estimates the carbon footprint (as tonnes of carbon dioxide equivalents per tonne of product) of Brazilian soy exports over the period 2010–2015 based on ~90,000 individual traded flows of beans, oil and protein cake identified from the municipality of origin through international markets. Soy is the most traded agricultural commodity in the world and the main agricultural export crop in Brazil, where it is associated with significant environmental impacts. We detect an extremely large spatial variability in carbon emissions across sourcing areas, countries of import, and sub-stages throughout the supply chain. The largest carbon footprints are associated with municipalities across the MATOPIBA states and Pará, where soy is directly linked to natural vegetation loss. Importing soy from the aforementioned states entailed up to six times greater emissions per unit of product than the Brazilian average (0.69 t t−1). The European Union (EU) had the largest carbon footprint (0.77 t t−1) due to a larger share of emissions from embodied deforestation than for instance in China (0.67 t t−1), the largest soy importer. Total GHG emissions from Brazilian soy exports in 2010–2015 are estimated at 223.46 Mt, of which more than half were imported by China although the EU imported greater emissions from deforestation in absolute terms. Our approach contributes data for enhanced

Published
2020

39. Music-supported therapy in the rehabilitation of subacute stroke patients: A randomized controlled trial

Author

Grau-Sánchez, Jennifer, 0000-0002-8123-1745, Duarte, Esther, Ramos‐Escobar, Neus, Sierpowska, Joanna, Rueda, Nohora, Redón, Susana, Veciana De Las Heras, Misericordia, Pedro, Jordi, Särkämö, Teppo, Rodríguez‐Fornells, Antoni, Medicum, Cognitive Brain Research Unit, Department of Psychology and Logopedics, Brain, Music and Learning, and Music, Ageing and Rehabilitation Team

Subjects
PHYSICAL REHABILITATION, REWARD, Rehabilitació motora, POSTSTROKE, 515 Psychology, PARTICIPATION, Professors, Music-Supported Therapy, RECOVERY, PERFORMANCE, stroke, Ictus, humanities, 3124 Neurology and psychiatry, rehabilitation, Stroke, Musicoteràpia, music-supported therapy, Qualitat de vida, randomized controlled trial, RELIABILITY, NEUROREHABILITATION, MOTOR, human activities, SCALE
Abstract

The effect of music-supported therapy (MST) as a tool to restore hemiparesis of the upper extremity after a stroke has not been appropriately contrasted with conventional therapy. The aim of this trial was to test the effectiveness of adding MST to a standard rehabilitation program in subacute stroke patients. A randomized controlled trial was conducted in which patients were randomized to MST or conventional therapy in addition to the rehabilitation program. The intensity and duration of the interventions were equated in both groups. Before and after 4 weeks of treatment, motor and cognitive functions, mood, and quality of life (QoL) of participants were evaluated. A follow-up at 3 months was conducted to examine the retention of motor gains. Both groups significantly improved their motor function, and no differences between groups were found. The only difference between groups was observed in the language domain for QoL. Importantly, an association was encountered between the capacity to experience pleasure from music activities and the motor improvement in the MST group. MST as an add-on treatment showed no superiority to conventional therapies for motor recovery. Importantly, patient's intrinsic motivation to engage in musical activities was associated with better motor improvement.

Published
2018

40. Make EU trade with Brazil sustainable

Author

Kehoe, Laura, Reis, Tiago, Virah-Sawmy, Malika, Balmford, Andrew, Kuemmerle, Tobias, Knohl, Alexander, Antonelli, Alexandre, Hochkirch, Axel, Vira, Bhaskar, Massa, Bruno, Peres, Carlos A., Ammer, Christian, Goerg, Christoph, Schneider, Christoph, Curtis, David, de la Pena, Eduardo, Tello, Enric, Sperfeld, Erik, Corbera, Esteve, Morelli, Federico, Valladares, Fernando, Peterson, Garry, Hide, Geoff, Mace, Georgina, Kallis, Giorgos, Olsson, Gunilla Almered, Brumelis, Guntis, Alexanderson, Helena, Haberl, Helmut, Nuissl, Henning, Kreft, Holger, Ghazoul, Jaboury, Piotrowski, Jan A., Macdiarmid, Jennie, Newig, Jens, Fischer, Joern, Altringham, John, Gledhill, John, Nielsen, Jonas O., Mueller, Joerg, Palmeirim, Jorge, Barlow, Jos, Alonso, Juan C., Presa Asencio, Juan Jose, Steinberger, Julia K., Jones, Julia Patricia Gordon, Cabral, Juliano Sarmento, Dengler, Juergen, Stibral, Karel, Erb, Karlheinz, Rothhaupt, Karl-Otto, Wiegand, Kerstin, Cassar, Louis F., Lens, Luc, Rosalino, Luis Miguel, Wassen, M. J., Stenseke, Marie, Fischer-Kowalski, Marina, Diaz, Mario, Rounsevell, Mark, van Kleunen, Mark, Junginger, Martin, Kaltenpoth, Martin, Zobel, Martin, Weigend, Maximilian, Partel, Meelis, Schilthuizen, Menno, Bastos Araujo, Miguel, Haklay, Muki, Eisenhauer, Nico, Selva, Nuria, Mertz, Ole, Meyfroidt, Patrick, Borges, Paulo A. V., Kovar, Pavel, Smith, Pete, Verburg, Peter, Pysek, Petr, Seppelt, Ralf, Valentini, Riccardo, Whittaker, Robert J., Henrique Faria, Sergio, Ulgiati, Sergio, Loetters, Stefan, Bjorck, Svante, Larson, Sven Ake, Tscharntke, Teja, Domingos, Tiago, Krueger, Tobias, Pascual, Unai, Olsson, Urban, Kati, Vassiliki, Winiwarter, Verena, Reyes-Garcia, Victoria, Vajda, Vivi, Sutherland, William J., de Waroux, Yann le Polain, Buckley, Yvonne, Rammig, Anja, Kasimir, Asa, Crona, Beatrice, Sindicic, Magda, Persson, Martin, Lapka, Miloslav, Di Gregorio, Monica, Hahn, Thomas, Boonstra, Wiebren, Lipsky, Zdenek, Zucaro, A., Roeder, Achim, Lopez Baucells, Adria, Danet, Alain, Franco, Aldina, Nieto Roman, Alejandra, Lehikoinen, Aleksi, Collalti, Alessio, Keller, Alexander, Strugariu, Alexandru, Perrigo, Allison, Fernandez-Llamazares, Alvaro, Salaseviciene, Alvija, Hinsley, Amy, Santos, Ana M. C., Novoa, Ana, Rodrigues, Ana, Mascarenhas, Andre, Martins, Andrea Damacena, Holzschuh, Andrea, Meseguer, Andrea S., Hadjichambis, Andreas, Mayer, Andreas, Hacket-Pain, Andrew, Ringsmuth, Andrew, de Frutos, Angel, Stein, Anke, Heikkinen, Anna, Smith, Annabel, Bjoersne, Anna-Karin, Bagneres, Anne-Genevieve, Machordom, Annie, Kristin, Anton, Ghoddousi, Arash, Staal, Arie, Martin, Arnaud, Taylor, Astrid, Borrell, Asuncion, Marescaux, Audrey, Torres, Aurora, Helm, Aveliina, Bauer, Barbara, Smetschka, Barbara, Rodriguez-Labajos, Beatriz, Peco, Begona, Gambin, Belinda, Celine, Bellard, Phalan, Ben, Cotta, Benedetta, Rugani, Benedetto, Jarcuska, Benjamin, Leroy, Boris, Nikolov, Boris Petrov, Milchev, Boyan Petrov, Brown, Calum, Ritter, Camila Duarte, Gomes, Carmen Bessa, Meyer, Carsten, Munteanu, Catalina, Penone, Caterina, Friis, Cecilie, Teplitsky, Celine, Roemer, Charlotte, Orland, Chloe, Voigt, Christian C., Levers, Christian, Zang, Christian, Bacon, Christine D., Meyer, Christoph, Wordley, Claire, Grilo, Clara, Cattaneo, Claudio, Battisti, Corrado, Banks-Leite, Cristina, Zurell, Damaris, Challender, Dan, Mueller, Daniel, Matenaar, Daniela, Silvestro, Daniele, McKay, David Armstrong, Buckley, David, Frantz, David, Gremillet, David, Mateos, David Moreno, Sanchez-Fernandez, David, Vieites, David, Ascoli, Davide, Arlt, Debora, Louis, Deharveng, Zemp, Delphine Clara, Strubbe, Diederik, Gil, Diego, Llusia, Diego, Bennett, Dominic J., Chobanov, Dragan Petrov, Aguilera, Eduardo, Oliveira, Eduardo, Pynegar, Edwin L., Granda, Elena, Grieco, Elisa, Conrad, Elisabeth, Revilla, Eloy, Lindkvist, Emilie, Caprio, Enrico, zu Ermgassen, Erasmus, Berenguer, Erika, Ochu, Erinma, Polaina, Ester, Nuernberger, Fabian, Esculier, Fabien, de Castro, Fabio, Albanito, Fabrizio, Langerwisch, Fanny, Batsleer, Femke, Ascensao, Fernando, Moyano, Fernando Esteban, Sayol, Ferran, Buzzetti, Filippo Maria, Eiro, Flavio, Volaire, Florence, Gollnow, Florian, Menzel, Florian, Pilo, Francesca, Moreira, Francisco, Briens, Francois, Essl, Franz, Vlahos, George, Billen, Gilles, Vacchiano, Giorgio, Wong, Grace, Gruychev, Gradimir Valentinov, Fandos, Guillermo, Petter, Gunnar, Sinare, Hanna, Mumby, Hannah S., Cottyn, Hanne, Seebens, Hanno, Bjorklund, Heidi, Schroeder, Heike, Lopez Hernandez, Heriberto D., Rebelo, Hugo, Chenet, Hugues, De la Riva, Ignacio, Torre, Ignasi, Aalders, Inge, Grass, Ingo, Chuine, Isabelle, Goepel, Jan, Wieringa, Jan J., Engler, Jan O., Pergl, Jan, Schnitzler, Jan, Vavra, Jan, Medvedovic, Jasna, Cabello, Javier, Martin, Jean-Louis, Mutke, Jens, Lewis, Jerome, da Silva, Jessica Fonseca, Marull, Joan, Carvalho, Joana, Carnicer, Jofre, Enqvist, Johan, Simaika, John P., Noguera, Jose C., Blanco Moreno, Jose M., Bruna, Josef, Garnier, Josette, Fargallo, Juan A., Rocha, Juan Carlos, Carrillo, Juan D., Infante-Amate, Juan, Traba Diaz, Juan, Schleicher, Judith, Simon, Judy, Noe, Julia Le, Gerlach, Justin, Eriksson, K. Martin, Prince, Karine, Ostapowicz, Katarzyna, Stajerova, Katerina, Farrell, Katharine N., Snell, Katherine, Yates, Katherine, Fleischer, Katrin, Darras, Kevin, Schumacher, Kim, Orach, Kirill, Thonicke, Kirsten, Riede, Klaus, Heller, Klaus-Gerhard, Wang-Erlandsson, Lan, Pereira, Laura, Riggi, Laura, Florez, Laura V., Emperaire, Laure, Durieux, Laurent, Tatin, Laurent, Rozylowicz, Laurentiu, Latella, Leonardo, Andresen, Louise C., Cahen-Fourot, Louison, de Agua, Luis Borda, Boto, Luis, Lassaletta, Luis, Amo, Luisa, Sekerka, Lukas, Morales, Manuel B., Macia, Manuel J., Suarez, Manuela Gonzalez, Cabeza, Mar, Londo, Marc, Pollet, Marc, Schwieder, Marcel, Peters, Marcell K., D'Amico, Marcello, Casazza, Marco, Florencio, Margarita, Felipe-Lucia, Maria, Gebara, Maria Fernanda, Johansson, Maria, Garcia, Maria Mancilla, Piquer-Rodriguez, Maria, Tengo, Maria, Elias, Marianne, Leve, Marine, Conde, Marta, Winter, Marten, Koster, Martijn, Mayer, Martin, Salek, Martin, Schlerf, Martin, Sullivan, Martin, Baumann, Matthias, Pichler, Melanie, Marselle, Melissa, Oddie, Melissa, Razanajatovo, Mialy, Borregaard, Michael Krabbe, Theurl, Michaela C., Hernandez, Miguel, Krofel, Miha, Kechev, Mihail Ognianov, Clark, Mike, Rands, Mike, Antal, Miklos, Pucetaite, Milda, Islar, Mine, Truong, Minh-Xuan A., Vighi, Morgana, Johanisova, Nadia, Prat, Narcis, Escobar, Neus, Deguines, Nicolas, Rust, Niki, Zafra-Calvo, Noelia, Maurel, Noelie, Wagner, Norman, Fitton, Nuala, Ostermann, Ole, Panferov, Oleg, Ange, Olivia, Canals, Oriol, Englund, Oskar, De Smedt, Pallieter, Petridis, Panos, Heikkurinen, Pasi, Weigelt, Patrick, Henriksson, Patrik J. G., de Castro, Paula Drummond, Matos-Maravi, Pavel, Duran, Paz, Aragon, Pedro, Cardoso, Pedro, Leitao, Pedro J., Hosner, Peter A., Biedermann, Peter, Keil, Petr, Petrik, Petr, Martin, Philip, Bocquillon, Pierre, Renaud, Pierre-Cyril, Addison, Prue, Antwis, Rachael, Carmenta, Rachel, Barrientos, Rafael, Smith, Rebecca, Rocha, Ricardo, Fuchs, Richard, Felix, Rob, Kanka, Robert, Aguilee, Robin, Padro Caminal, Roc, Libbrecht, Romain, Lorrilliere, Romain, van der Ent, Ruud J., Henders, Sabine, Pueyo, Salvador, Roturier, Samuel, Jacobs, Sander, Lavorel, Sandra, Leonhardt, Sara Diana, Fraixedas, Sara, Villen-Perez, Sara, Cornell, Sarah, Redlich, Sarah, De Smedt, Sebastian, van der Linden, Sebastian, Perez-Ortega, Sergio, Petrovan, Silviu, Cesarz, Simone, Sjoberg, Sissel, Caillon, Sophie, Schindler, Stefan, Trogisch, Stefan, Taiti, Stefano, Oppel, Steffen, Lutter, Stephan, Garnett, Tara, Guedes, Thais, Wanger, Thomas Cherico, Kastner, Thomas, Worthington, Thomas, Daw, Tim, Schmoll, Tim, McPhearson, Timon, Engl, Tobias, Rutting, Tobias, Vaclavik, Tomas, Jucker, Tommaso, Robillard, Tony, Krause, Torsten, Ljubomirov, Toshko, Aavik, Tsipe, Richardson, Vanessa A., Masterson, Vanessa Anne, Seufert, Verena, Cathy, Vet Gibault, Colino Rabanal, Victor, Montade, Vincent, Thieu, Vincent, Sober, Virve, Morin, Xavier, Mehrabi, Zia, Gonzalez, Adriana Trompetero, Sanz-Cobena, Alberto, Christie, Alec Philip, Romero-Munoz, Alfredo, Dauriach, Alice, Queiroz, Allan Souza, Golland, Ami, Evans, Amy Louise, Cordero, Ana Maria Araujo, Dara, Andrey, Rilovic, Andro, Pedersen, Anna Frohn, Csergo, Anna Maria, Lewerentz, Anne, Monserand, Antoine, Valdecasas, Antonio G., Doherty, Anya, Semper-Pascual, Asuncion, Bleyhl, Benjamin, Rutschmann, Benjamin, Bongalov, Boris, Hankerson, Brett, Heylen, Brigitte, Alonso-Alvarez, Carlos, Comandulli, Carolina, Frossard, Carolina M., Mckeon, Caroline, Godde, Cecile, Palm, Celinda, Singh, Chandrakant, Sieger, Charlotte Sophie, Ohrling, Christian, Paitan, Claudia Parra, Cooper, Conor, Edler, Daniel, Roessler, Daniela C., Kessner-Beierlein, Daniela, Garcia del Amo, David, Lopez Bosch, David, Gueldner, Dino, Noll, Domink, Motivans, Elena, Canteri, Elisabetta, Garnett, Emma, Malecore, Eva, Brambach, Fabian, Ruedenauer, Fabian, Yin, Fang, Hurtado, Fernando, Mempel, Finn, de Freitas, Flavio Luiz Mazzaro, Pendrill, Florence, Leijten, Floris, Somma, Francesca, Schug, Franz, De Knijf, Geert, Peterson, Gustaf, Pe'er, Guy, Booth, Hollie, Rhee, Howon, Staude, Ingmar, Gherghel, Iulian, Vila Traver, Jaime, Kerner, Janika, Hinton, Jennifer, Hortal, Joaquin, Persson, Joel, Uddling, Johan, Coenen, Johanna, Geldmann, Jonas, Geschke, Jonas, Juergensen, Jonathan, Lobo, Jorge M., Skejo, Josip, Heinen, Julia Helena, Schuenzel, Julia, Daniel-Ferreira, Juliana, Christophe Piquet, Julien, Murtough, Katie L., Prevel, Leonie, Hissa, Leticia B. V., af Segerstad, Louise Hard, Willemse, Luc, Benavides, Lucia, Sovova, Lucie, Figueiredo, Ludmilla, Leidinger, Ludwig, Piemontese, Luigi, da Fonte, Luis Fernando Marin, Moreta, Lys Sanz, Bhan, Manan, Toledo-Hernandez, Manuel, Engert, Manuela, Davoli, Marco, Mas Navarro, Maria, Voigt, Maria, Zirion, Maria, Wandl, Marie-Theres, Kipson, Marina, Johnson, Mark D., Lukic, Marko, Goula, Marta, Jung, Martin, Nunes, Matheus Henrique, Alvarez, Matheus Rodriguez, van den Burg, Matthijs P., Guerrero, Mayra Daniela Pena, Greenfield, Michael, Lobmann, Michael, Nygren, Michelle, Guth, Miriam Karen, Koh, Niak, Stanek, Nicola, Roux, Nicolas, Karagouni, Niki, Tiralla, Nina, Mairota, Paola, Savaget, Paulo, von Doehren, Peer, Benyei, Petra, Lena, Philippe, Rufin, Philippe, Janke, Rebekka, Santagata, Remo, Motta, Renzo, Battiston, Roberto, Oyanedel, Rodrigo, Bernardo-Madrid, Ruben, Vasconcelos, Sasha, Henriques, Sergio, Bager, Simon L., Qin, Siyu, Ivkovic, Slobodan, Cooke, Sophia, Ernst, Stefan, Schmelzer, Stefan, da Silva, Sven, Faberova, Tamara, Enseroth, Tanja, De Marzo, Teresa, Pienkowski, Thomas, Engel, Thore, Boehnert, Tim, Swinfield, Tom, Kurdikova, Vendula, Chvatalova, Veronika, Lopez-Marquez, Violeta, Arlidge, William, Zhang, Zhijie, Kehoe, Laura, Reis, Tiago, Virah-Sawmy, Malika, Balmford, Andrew, Kuemmerle, Tobias, Knohl, Alexander, Antonelli, Alexandre, Hochkirch, Axel, Vira, Bhaskar, Massa, Bruno, Peres, Carlos A., Ammer, Christian, Goerg, Christoph, Schneider, Christoph, Curtis, David, de la Pena, Eduardo, Tello, Enric, Sperfeld, Erik, Corbera, Esteve, Morelli, Federico, Valladares, Fernando, Peterson, Garry, Hide, Geoff, Mace, Georgina, Kallis, Giorgos, Olsson, Gunilla Almered, Brumelis, Guntis, Alexanderson, Helena, Haberl, Helmut, Nuissl, Henning, Kreft, Holger, Ghazoul, Jaboury, Piotrowski, Jan A., Macdiarmid, Jennie, Newig, Jens, Fischer, Joern, Altringham, John, Gledhill, John, Nielsen, Jonas O., Mueller, Joerg, Palmeirim, Jorge, Barlow, Jos, Alonso, Juan C., Presa Asencio, Juan Jose, Steinberger, Julia K., Jones, Julia Patricia Gordon, Cabral, Juliano Sarmento, Dengler, Juergen, Stibral, Karel, Erb, Karlheinz, Rothhaupt, Karl-Otto, Wiegand, Kerstin, Cassar, Louis F., Lens, Luc, Rosalino, Luis Miguel, Wassen, M. J., Stenseke, Marie, Fischer-Kowalski, Marina, Diaz, Mario, Rounsevell, Mark, van Kleunen, Mark, Junginger, Martin, Kaltenpoth, Martin, Zobel, Martin, Weigend, Maximilian, Partel, Meelis, Schilthuizen, Menno, Bastos Araujo, Miguel, Haklay, Muki, Eisenhauer, Nico, Selva, Nuria, Mertz, Ole, Meyfroidt, Patrick, Borges, Paulo A. V., Kovar, Pavel, Smith, Pete, Verburg, Peter, Pysek, Petr, Seppelt, Ralf, Valentini, Riccardo, Whittaker, Robert J., Henrique Faria, Sergio, Ulgiati, Sergio, Loetters, Stefan, Bjorck, Svante, Larson, Sven Ake, Tscharntke, Teja, Domingos, Tiago, Krueger, Tobias, Pascual, Unai, Olsson, Urban, Kati, Vassiliki, Winiwarter, Verena, Reyes-Garcia, Victoria, Vajda, Vivi, Sutherland, William J., de Waroux, Yann le Polain, Buckley, Yvonne, Rammig, Anja, Kasimir, Asa, Crona, Beatrice, Sindicic, Magda, Persson, Martin, Lapka, Miloslav, Di Gregorio, Monica, Hahn, Thomas, Boonstra, Wiebren, Lipsky, Zdenek, Zucaro, A., Roeder, Achim, Lopez Baucells, Adria, Danet, Alain, Franco, Aldina, Nieto Roman, Alejandra, Lehikoinen, Aleksi, Collalti, Alessio, Keller, Alexander, Strugariu, Alexandru, Perrigo, Allison, Fernandez-Llamazares, Alvaro, Salaseviciene, Alvija, Hinsley, Amy, Santos, Ana M. C., Novoa, Ana, Rodrigues, Ana, Mascarenhas, Andre, Martins, Andrea Damacena, Holzschuh, Andrea, Meseguer, Andrea S., Hadjichambis, Andreas, Mayer, Andreas, Hacket-Pain, Andrew, Ringsmuth, Andrew, de Frutos, Angel, Stein, Anke, Heikkinen, Anna, Smith, Annabel, Bjoersne, Anna-Karin, Bagneres, Anne-Genevieve, Machordom, Annie, Kristin, Anton, Ghoddousi, Arash, Staal, Arie, Martin, Arnaud, Taylor, Astrid, Borrell, Asuncion, Marescaux, Audrey, Torres, Aurora, Helm, Aveliina, Bauer, Barbara, Smetschka, Barbara, Rodriguez-Labajos, Beatriz, Peco, Begona, Gambin, Belinda, Celine, Bellard, Phalan, Ben, Cotta, Benedetta, Rugani, Benedetto, Jarcuska, Benjamin, Leroy, Boris, Nikolov, Boris Petrov, Milchev, Boyan Petrov, Brown, Calum, Ritter, Camila Duarte, Gomes, Carmen Bessa, Meyer, Carsten, Munteanu, Catalina, Penone, Caterina, Friis, Cecilie, Teplitsky, Celine, Roemer, Charlotte, Orland, Chloe, Voigt, Christian C., Levers, Christian, Zang, Christian, Bacon, Christine D., Meyer, Christoph, Wordley, Claire, Grilo, Clara, Cattaneo, Claudio, Battisti, Corrado, Banks-Leite, Cristina, Zurell, Damaris, Challender, Dan, Mueller, Daniel, Matenaar, Daniela, Silvestro, Daniele, McKay, David Armstrong, Buckley, David, Frantz, David, Gremillet, David, Mateos, David Moreno, Sanchez-Fernandez, David, Vieites, David, Ascoli, Davide, Arlt, Debora, Louis, Deharveng, Zemp, Delphine Clara, Strubbe, Diederik, Gil, Diego, Llusia, Diego, Bennett, Dominic J., Chobanov, Dragan Petrov, Aguilera, Eduardo, Oliveira, Eduardo, Pynegar, Edwin L., Granda, Elena, Grieco, Elisa, Conrad, Elisabeth, Revilla, Eloy, Lindkvist, Emilie, Caprio, Enrico, zu Ermgassen, Erasmus, Berenguer, Erika, Ochu, Erinma, Polaina, Ester, Nuernberger, Fabian, Esculier, Fabien, de Castro, Fabio, Albanito, Fabrizio, Langerwisch, Fanny, Batsleer, Femke, Ascensao, Fernando, Moyano, Fernando Esteban, Sayol, Ferran, Buzzetti, Filippo Maria, Eiro, Flavio, Volaire, Florence, Gollnow, Florian, Menzel, Florian, Pilo, Francesca, Moreira, Francisco, Briens, Francois, Essl, Franz, Vlahos, George, Billen, Gilles, Vacchiano, Giorgio, Wong, Grace, Gruychev, Gradimir Valentinov, Fandos, Guillermo, Petter, Gunnar, Sinare, Hanna, Mumby, Hannah S., Cottyn, Hanne, Seebens, Hanno, Bjorklund, Heidi, Schroeder, Heike, Lopez Hernandez, Heriberto D., Rebelo, Hugo, Chenet, Hugues, De la Riva, Ignacio, Torre, Ignasi, Aalders, Inge, Grass, Ingo, Chuine, Isabelle, Goepel, Jan, Wieringa, Jan J., Engler, Jan O., Pergl, Jan, Schnitzler, Jan, Vavra, Jan, Medvedovic, Jasna, Cabello, Javier, Martin, Jean-Louis, Mutke, Jens, Lewis, Jerome, da Silva, Jessica Fonseca, Marull, Joan, Carvalho, Joana, Carnicer, Jofre, Enqvist, Johan, Simaika, John P., Noguera, Jose C., Blanco Moreno, Jose M., Bruna, Josef, Garnier, Josette, Fargallo, Juan A., Rocha, Juan Carlos, Carrillo, Juan D., Infante-Amate, Juan, Traba Diaz, Juan, Schleicher, Judith, Simon, Judy, Noe, Julia Le, Gerlach, Justin, Eriksson, K. Martin, Prince, Karine, Ostapowicz, Katarzyna, Stajerova, Katerina, Farrell, Katharine N., Snell, Katherine, Yates, Katherine, Fleischer, Katrin, Darras, Kevin, Schumacher, Kim, Orach, Kirill, Thonicke, Kirsten, Riede, Klaus, Heller, Klaus-Gerhard, Wang-Erlandsson, Lan, Pereira, Laura, Riggi, Laura, Florez, Laura V., Emperaire, Laure, Durieux, Laurent, Tatin, Laurent, Rozylowicz, Laurentiu, Latella, Leonardo, Andresen, Louise C., Cahen-Fourot, Louison, de Agua, Luis Borda, Boto, Luis, Lassaletta, Luis, Amo, Luisa, Sekerka, Lukas, Morales, Manuel B., Macia, Manuel J., Suarez, Manuela Gonzalez, Cabeza, Mar, Londo, Marc, Pollet, Marc, Schwieder, Marcel, Peters, Marcell K., D'Amico, Marcello, Casazza, Marco, Florencio, Margarita, Felipe-Lucia, Maria, Gebara, Maria Fernanda, Johansson, Maria, Garcia, Maria Mancilla, Piquer-Rodriguez, Maria, Tengo, Maria, Elias, Marianne, Leve, Marine, Conde, Marta, Winter, Marten, Koster, Martijn, Mayer, Martin, Salek, Martin, Schlerf, Martin, Sullivan, Martin, Baumann, Matthias, Pichler, Melanie, Marselle, Melissa, Oddie, Melissa, Razanajatovo, Mialy, Borregaard, Michael Krabbe, Theurl, Michaela C., Hernandez, Miguel, Krofel, Miha, Kechev, Mihail Ognianov, Clark, Mike, Rands, Mike, Antal, Miklos, Pucetaite, Milda, Islar, Mine, Truong, Minh-Xuan A., Vighi, Morgana, Johanisova, Nadia, Prat, Narcis, Escobar, Neus, Deguines, Nicolas, Rust, Niki, Zafra-Calvo, Noelia, Maurel, Noelie, Wagner, Norman, Fitton, Nuala, Ostermann, Ole, Panferov, Oleg, Ange, Olivia, Canals, Oriol, Englund, Oskar, De Smedt, Pallieter, Petridis, Panos, Heikkurinen, Pasi, Weigelt, Patrick, Henriksson, Patrik J. G., de Castro, Paula Drummond, Matos-Maravi, Pavel, Duran, Paz, Aragon, Pedro, Cardoso, Pedro, Leitao, Pedro J., Hosner, Peter A., Biedermann, Peter, Keil, Petr, Petrik, Petr, Martin, Philip, Bocquillon, Pierre, Renaud, Pierre-Cyril, Addison, Prue, Antwis, Rachael, Carmenta, Rachel, Barrientos, Rafael, Smith, Rebecca, Rocha, Ricardo, Fuchs, Richard, Felix, Rob, Kanka, Robert, Aguilee, Robin, Padro Caminal, Roc, Libbrecht, Romain, Lorrilliere, Romain, van der Ent, Ruud J., Henders, Sabine, Pueyo, Salvador, Roturier, Samuel, Jacobs, Sander, Lavorel, Sandra, Leonhardt, Sara Diana, Fraixedas, Sara, Villen-Perez, Sara, Cornell, Sarah, Redlich, Sarah, De Smedt, Sebastian, van der Linden, Sebastian, Perez-Ortega, Sergio, Petrovan, Silviu, Cesarz, Simone, Sjoberg, Sissel, Caillon, Sophie, Schindler, Stefan, Trogisch, Stefan, Taiti, Stefano, Oppel, Steffen, Lutter, Stephan, Garnett, Tara, Guedes, Thais, Wanger, Thomas Cherico, Kastner, Thomas, Worthington, Thomas, Daw, Tim, Schmoll, Tim, McPhearson, Timon, Engl, Tobias, Rutting, Tobias, Vaclavik, Tomas, Jucker, Tommaso, Robillard, Tony, Krause, Torsten, Ljubomirov, Toshko, Aavik, Tsipe, Richardson, Vanessa A., Masterson, Vanessa Anne, Seufert, Verena, Cathy, Vet Gibault, Colino Rabanal, Victor, Montade, Vincent, Thieu, Vincent, Sober, Virve, Morin, Xavier, Mehrabi, Zia, Gonzalez, Adriana Trompetero, Sanz-Cobena, Alberto, Christie, Alec Philip, Romero-Munoz, Alfredo, Dauriach, Alice, Queiroz, Allan Souza, Golland, Ami, Evans, Amy Louise, Cordero, Ana Maria Araujo, Dara, Andrey, Rilovic, Andro, Pedersen, Anna Frohn, Csergo, Anna Maria, Lewerentz, Anne, Monserand, Antoine, Valdecasas, Antonio G., Doherty, Anya, Semper-Pascual, Asuncion, Bleyhl, Benjamin, Rutschmann, Benjamin, Bongalov, Boris, Hankerson, Brett, Heylen, Brigitte, Alonso-Alvarez, Carlos, Comandulli, Carolina, Frossard, Carolina M., Mckeon, Caroline, Godde, Cecile, Palm, Celinda, Singh, Chandrakant, Sieger, Charlotte Sophie, Ohrling, Christian, Paitan, Claudia Parra, Cooper, Conor, Edler, Daniel, Roessler, Daniela C., Kessner-Beierlein, Daniela, Garcia del Amo, David, Lopez Bosch, David, Gueldner, Dino, Noll, Domink, Motivans, Elena, Canteri, Elisabetta, Garnett, Emma, Malecore, Eva, Brambach, Fabian, Ruedenauer, Fabian, Yin, Fang, Hurtado, Fernando, Mempel, Finn, de Freitas, Flavio Luiz Mazzaro, Pendrill, Florence, Leijten, Floris, Somma, Francesca, Schug, Franz, De Knijf, Geert, Peterson, Gustaf, Pe'er, Guy, Booth, Hollie, Rhee, Howon, Staude, Ingmar, Gherghel, Iulian, Vila Traver, Jaime, Kerner, Janika, Hinton, Jennifer, Hortal, Joaquin, Persson, Joel, Uddling, Johan, Coenen, Johanna, Geldmann, Jonas, Geschke, Jonas, Juergensen, Jonathan, Lobo, Jorge M., Skejo, Josip, Heinen, Julia Helena, Schuenzel, Julia, Daniel-Ferreira, Juliana, Christophe Piquet, Julien, Murtough, Katie L., Prevel, Leonie, Hissa, Leticia B. V., af Segerstad, Louise Hard, Willemse, Luc, Benavides, Lucia, Sovova, Lucie, Figueiredo, Ludmilla, Leidinger, Ludwig, Piemontese, Luigi, da Fonte, Luis Fernando Marin, Moreta, Lys Sanz, Bhan, Manan, Toledo-Hernandez, Manuel, Engert, Manuela, Davoli, Marco, Mas Navarro, Maria, Voigt, Maria, Zirion, Maria, Wandl, Marie-Theres, Kipson, Marina, Johnson, Mark D., Lukic, Marko, Goula, Marta, Jung, Martin, Nunes, Matheus Henrique, Alvarez, Matheus Rodriguez, van den Burg, Matthijs P., Guerrero, Mayra Daniela Pena, Greenfield, Michael, Lobmann, Michael, Nygren, Michelle, Guth, Miriam Karen, Koh, Niak, Stanek, Nicola, Roux, Nicolas, Karagouni, Niki, Tiralla, Nina, Mairota, Paola, Savaget, Paulo, von Doehren, Peer, Benyei, Petra, Lena, Philippe, Rufin, Philippe, Janke, Rebekka, Santagata, Remo, Motta, Renzo, Battiston, Roberto, Oyanedel, Rodrigo, Bernardo-Madrid, Ruben, Vasconcelos, Sasha, Henriques, Sergio, Bager, Simon L., Qin, Siyu, Ivkovic, Slobodan, Cooke, Sophia, Ernst, Stefan, Schmelzer, Stefan, da Silva, Sven, Faberova, Tamara, Enseroth, Tanja, De Marzo, Teresa, Pienkowski, Thomas, Engel, Thore, Boehnert, Tim, Swinfield, Tom, Kurdikova, Vendula, Chvatalova, Veronika, Lopez-Marquez, Violeta, Arlidge, William, and Zhang, Zhijie

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2019
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47. An agro-industrial model for the optimization of biodiesel production in Spain to meet the European GHG reduction targets

Author

Universitat Politècnica de València. Departamento de Tecnología de Alimentos - Departament de Tecnologia d'Aliments, Generalitat Valenciana, European Regional Development Fund, Ministerio de Ciencia y Tecnología, Escobar, Neus, Manrique-de-Lara-Penate, Casiano, Sanjuán Pellicer, María Nieves, Clemente Polo, Gabriela, Rozakis, Stelios, Universitat Politècnica de València. Departamento de Tecnología de Alimentos - Departament de Tecnologia d'Aliments, Generalitat Valenciana, European Regional Development Fund, Ministerio de Ciencia y Tecnología, Escobar, Neus, Manrique-de-Lara-Penate, Casiano, Sanjuán Pellicer, María Nieves, Clemente Polo, Gabriela, and Rozakis, Stelios

Abstract

[EN] Right after the enforcement of the Directive (EU) 2015/1513, amending the Renewable Energy Directive of the European Union, the situation of the biodiesel sector in Spain is particularly uncertain. Although domestic biodiesel production has significantly increased since 2013, many plants are still idle, leading to an excess of capacity. This paper aims to provide an operational framework that combines Life Cycle Assessment (LCA) with economic optimization to determine the feedstock combination for domestic biodiesel production in Spain in compliance with this Directive, and quantify the associated impacts. A multi-sector, mathematical programming model is proposed in a Partial Equilibrium setting, implementing an LCA module. The optimal oil mix for the sector is highly dependent on assumptions regarding land use change in crude vegetable oil exporting countries. Increasing greenhouse gas savings thresholds enhance the use of waste oils and domestic oilseeds, while preventing deforestation of carbon-rich ecosystems; the only exception is the Brazilian Cerrado savanna. A double-counting scheme for waste oil biodiesel is necessary to make plants with second-generation technology work at full capacity, delivering further environmental benefits. Although there is room for further improvement, the model can provide very good insights for biodiesel policy analysis in the context of Spain.

Published
2017

50. Spatially-explicit footprints of agricultural commodities: Mapping carbon emissions embodied in Brazil's soy exports

Author

Zoologia, Escobar, Neus, Tizado Morales, Emilio Jorge, zu Ermgassen, Erasmus K.H.J., Löfgren, Pernilla, Börner, Jan, Godar, Javier, Zoologia, Escobar, Neus, Tizado Morales, Emilio Jorge, zu Ermgassen, Erasmus K.H.J., Löfgren, Pernilla, Börner, Jan, and Godar, Javier

Abstract

[EN] Reliable estimates of carbon and other environmental footprints of agricultural commodities require capturing a large diversity of conditions along global supply chains. Life Cycle Assessment (LCA) faces limitations when it comes to addressing spatial and temporal variability in production, transportation and manufacturing systems. We present a bottom-up approach for quantifying the greenhouse gas (GHG) emissions embedded in the production and trade of agricultural products with a high spatial resolution, by means of the integration of LCA principles with enhanced physical trade flow analysis. Our approach estimates the carbon footprint (as tonnes of carbon dioxide equivalents per tonne of product) of Brazilian soy exports over the period 2010–2015 based on ~90,000 individual traded flows of beans, oil and protein cake identified from the municipality of origin through international markets. Soy is the most traded agricultural commodity in the world and the main agricultural export crop in Brazil, where it is associated with significant environmental impacts. We detect an extremely large spatial variability in carbon emissions across sourcing areas, countries of import, and sub-stages throughout the supply chain. The largest carbon footprints are associated with municipalities across the MATOPIBA states and Pará, where soy is directly linked to natural vegetation loss. Importing soy from the aforementioned states entailed up to six times greater emissions per unit of product than the Brazilian average (0.69 t t−1). The European Union (EU) had the largest carbon footprint (0.77 t t−1) due to a larger share of emissions from embodied deforestation than for instance in China (0.67 t t−1), the largest soy importer. Total GHG emissions from Brazilian soy exports in 2010–2015 are estimated at 223.46 Mt, of which more than half were imported by China although the EU imported greater emissions from deforestation in absolute terms. Our approach contributes data for enha

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