Why energy models should integrate social and environmental factors : Assessing user needs, omission impacts, and real-word accuracy in the European Union

Unidad de excelencia María de Maeztu CEX2019-000940-MEnergy models are used to inform and support decisions within the transition to climate neutrality. In recent years, such models have been criticised for being overly techno-centred and ignoring environmental and social factors of the energy transition. Here, we explore and illustrate the impact of ignoring such factors by comparing model results to model user needs and real-world observations. We firstly identify concrete user needs for better representation of environmental and social factors in energy modelling via interviews, a survey and a workshop. Secondly, we explore and illustrate the effects of omitting non-techno-economic factors in modelling by contrasting policy-targeted scenarios with reality in four EU case study examples. We show that by neglecting environmental and social factors, models risk generating overly optimistic and potentially misleading results, for example by suggesting transition speeds far exceeding any speeds observed, or pathways facing hard-to-overcome resource constraints. As such, modelled energy transition pathways that ignore such factors may be neither desirable nor feasible from an environmental and social perspective, and scenarios may be irrelevant in practice. Finally, we discuss a sample of recent energy modelling innovations and call for continued and increased efforts for improved approaches that better represent environmental and social factors in energy modelling and increase the relevance of energy models for informing policymaking

Discrimination of astringent and deastringed hard "Rojo Brillante" persimmon fruit using a sensory threshold by means of hyperspectral imaging

[EN] Persimmon fruit cv. 'Rojo Brillante' is an astringent cultivar due to its content of soluble tannins, which are insolubilised during the ripening of the fruit. Traditionally, the consumption of this cultivar has only been possible when the fruit is overripe and the texture is soft. Postharvest treatments based on exposing fruits to high CO2 concentrations allow astringency removal while preserving high flesh firmness. However, the effectiveness of this treatment is controlled by means of slow destructive methods. The aim of this work is to study the application of hyperspectral imaging in the spectral range 450-1040 nm to discriminate astringent (A) and deastringed (DA) fruits non-destructively. To separate both type of fruit, it was used a threshold of soluble tannins based on sensorial perception (0.04% of fresh weight). The spectral information from three different areas of each fruit (calyx, middle and apex) was used to build models to predict the soluble tannins (ST) content using partial least squares regression (PLS-R). The results using this method indicated that it was not possible to accurately discriminate fruit with levels of ST below 0.04%, especially in the case of DA fruits (42.2%). Thus, another classification models were performed using partial least squares discriminant analysis (PLS-DA) that included other properties in order to discriminate between A and DA using the ST threshold. The most accurate models using all and optimal wavelengths selected were those which focused on the middle and apex areas of the fruit, a correct classification rate of 87.0% being achieved for A fruits and above 84.4% for DA fruits. To date, there are only subjective and destructive analytical methods to monitor the effectiveness of the astringency removal treatments in persimmon. The results obtained in this study indicate that hyperspectral images can therefore be considered as an objective and non-destructive alternative in the control of this process.This work was partially funded by INIA and FEDER funds through project RTA2015-00078-00-00. Sandra Munera thanks INIA for the FPI-INIA grant num. 43 (CPR2014-0082), partially supported by European Union FSE funds.Munera, S.; Aleixos Borrás, MN.; Besada, C.; Gómez-Sanchis, J.; Salvador, A.; Cubero, S.; Talens Oliag, P.... (2019). Discrimination of astringent and deastringed hard "Rojo Brillante" persimmon fruit using a sensory threshold by means of hyperspectral imaging. Journal of Food Engineering. 263:173-180. https://doi.org/10.1016/j.jfoodeng.2019.06.008S17318026

Astringency assessment of persimmon by hyperspectral imaging

[EN] One of the current challenges of persimmon postharvest research is the development of non-destructive methods that allow determination of the internal properties of the fruit, such as maturity, flesh firmness and astringency. This study evaluates the usefulness of hyperspectral imaging in the 460 1020 nm range as a non-destructive tool to achieve these aims in Persimmon cv. Rojo Brillante which is an astringent cultivar. Fruit were harvested at three different stages of commercial maturity and exposed to different treatments of CO2 (95% CO2 20 ºC from 0 to 24 h) in order to obtain fruit with different levels of astringency. Partial Least Square (PLS) based methods were used to classify persimmon fruits by maturity and to predict flesh firmness from the average spectrum of each fruit. The results showed a 97.9% rate of correct maturity classification and an R2P of 0.80 for firmness prediction with only five selected wavelengths. For astringency assessment, as our results showed that the soluble tannins that remain after CO2 treatments are distributed irregularly inside the flesh, a model based on PLS was built using the spectrum of every pixel in the fruit. The model obtained an R2P of 0.91 which allowed the creation of the predicted distribution maps of the tannins in the flesh of the fruit, thereby pointing to hyperspectral systems as a promising technology to assess the effectiveness of the deastringency treatments that are usually applied before commercialising persimmons from astringent cultivars.This work has been partially funded by the Instituto Nacional de Investigacion y Tecnologia Agraria y Alimentaria de Espana (INIA) through projects RTA2012-00062-C04-01, RTA2012-00062-C04-03 and RTA2013-00043-C02 with the support of FEDER funds and by the Conselleria d' Educacio, Investigacio, Cultura i Esport, Generalitat Valenciana, through the project AICO/2015/122. Sandra Munera thanks INIA for the grant FPI-INIA #43 (CPR2014-0082) partially supported by FSE funds.S354112

Maturity assessment of ‘Rojo Brillante’ persimmon by Hyperspectral Imaging

Persimmon cv. ‘Rojo Brillante’ is an astringent cultivar highly appreciated by consumers due to its good aspect, high size, sweetness and absence of seeds. However, this cultivar is very astringent and the fruit cannot be consumed until a high degree of overripeness with takes long time and makes the fruit difficult to handle. A method based on exposing fruit to high CO2 concentrations was recently developed to eliminate quickly the astringency preserving the firmness; however, the adequate duration of this treatment depends mostly on the maturity at harvest. Therefore the aim of this work was to investigate a non-destructive and reliable method based on hyperspectral imaging to assess the maturity of persimmon cv ‘Rojo Brillante’ before deastringency treatments. For this purpose, 150 persimmon fruits were harvested at three different stages of commercial maturity and flesh firmness was determined after the image acquisition. Hyperspectral images of each fruit were taken using a hyperspectral system based on two liquid crystal tuneable filters, sensitive in the spectral range 420-1080 nm. Partial Least Square-Discriminant Analysis (PLS-DA) was used on the hyperspectral images to select optimal wavelengths and classify persimmon fruits by maturity. The results achieved 90.1% of correct classification using six selected wavelengths. Additionally, flesh firmness was predicted by using partial least square regression (PLS-R) and the selected wavelengths. A R2 of 0.80 and a square error of prediction (SEP) of 4.34 N were obtained. All of these results were considered as good for a non-invasive maturity assessment technique of ‘Rojo Brillante’ persimmon

Non-destructive assessment of the internal quality of intact persimmon using colour and VIS/NIR hyperspectral imaging

The internal quality of intact persimmon cv. Rojo Brillante was assessed trough visible and near infrared hyperspectral imaging. Fruits at three stages of commercial maturity were exposed to different treatments with CO2 to obtain fruit with different ripeness and level of astringency (soluble tannin content). Spectral and spatial information were used for building classification models to predict ripeness and astringency trough multivariate analysis techniques like linear and quadratic discriminant analysis (LDA and QDA) and support vector machine (SVM). Additionally, flesh firmness was predicted by partial least square regression (PLSR). The full spectrum was used to determine the internal properties and later principal component analysis (PCA) was used to select optimal wavelengths (580, 680 and 1050 nm). The correct classification was above 92% for the three classifiers in the case of ripeness and 95% for QDA in the case of astringency. A value of R2 = 0.80 and a ratio of prediction deviation (RPD) of 1.86 were obtained with the selected wavelengths for the prediction of firmness which demonstrated the potential of hyperspectral imaging as a non-destructive tool in the assessment of the firmness, ripeness state and astringency level of Rojo Brillante persimmon.This work has been partially funded by the INIA and FEDER through projects RTA2012-00062-C04-01, RTA2012-00062-C04-03 and RTA2013-00043-C02, GVA through the project AICO/2015/122, the International S&T Cooperation Programs of China (2015DFA71150), and the International S&T Cooperation Program of Guangdong Province, China (2013B051000010). Sandra Munera thanks INIA for the grant FPI-INIA #43 (CPR2014-0082) partially supported by FSE funds.Munera-Picazo, S.; Besada Ferreiro, CM.; Aleixos Borrás, MN.; Talens Oliag, P.; Salvador, A.; Sun, D.; Cubero-García, S.... (2017). Non-destructive assessment of the internal quality of intact persimmon using colour and VIS/NIR hyperspectral imaging. Food Science and Technology. 77:241-248. https://doi.org/10.1016/j.lwt.2016.11.063S2412487

Prediction of the level of astringency in persimmon using visible and near-infrared spectroscopy

[EN] Early control of fruit quality requires reliable and rapid determination techniques. Therefore, the food industry has a growing interest in non-destructive methods such as spectroscopy. The aim of this study was to evaluate the feasibility of visible and near-infrared (NIR) spectroscopy, in combination with multivariate analysis techniques, to predict the level and changes of astringency in intact and in the flesh of half cut persimmon fruits. The fruits were harvested and exposed to different treatments with 95 % CO2 at 20 ºC for 0, 6, 12, 18 and 24 h to obtain samples with different levels of astringency. A set of 98 fruits was used to develop the predictive models based on their spectral data and another external set of 42 fruit samples was used to validate the models. The models were created using the partial least squares regression (PLSR), support vector machine (SVM) and least squares support vector machine (LS-SVM). In general, the models with the best performance were those which included standard normal variate (SNV) in the pre-processing. The best model was the PLSR developed with SNV along with the first derivative (1-Der) pre-processing, created using the data obtained at six measurement points of the intact fruits and all wavelengths (R2=0.904 and RPD=3.26). Later, a successive projection algorithm (SPA) was applied to select the most effective wavelengths (EWs). Using the six points of measurement of the intact fruit and SNV together with the direct orthogonal signal correction (DOSC) pre-processing in the NIR spectra, 41 EWs were selected, achieving an R2 of 0.915 and an RPD of 3.46 for the PLSR model. These results suggest that this technology has potential for use as a feasible and cost-effective method for the non-destructive determination of astringency in persimmon fruits.This work has been partially funded by the Institute Nacional de Investigacion y Tecnologia Agraria y Alimentaria de Espana (INIA) through research projects RTA2012-00062-004-01/03, RTA2013-00043-C02, and RTA2015-00078-00-00 with the support of European FEDER funds, and by the Conselleria d' Educacio, Investigacio, Cultura i Esport, Generalitat Valenciana, through the project AICO/2015/122. V. Cortes thanks the Spanish MEC for the FPU grant (FPU13/04202).Cortés López, V.; Rodríguez Ortega, A.; Blasco Ivars, J.; Rey Solaz, B.; Besada, C.; Cubero García, S.; Salvador, A.... (2017). Prediction of the level of astringency in persimmon using visible and near-infrared spectroscopy. JOURNAL OF FOOD ENGINEERING. 204:27-37. doi:10.1016/j.jfoodeng.2017.02.017S273720

Detection of Astringent and Deastringent Persimmon Fruits using Hyperspectral Imaging Technology

Persimmon fruit cv. ‘Rojo Brillante’ is an astringent cultivar due to its content of soluble tannins. Traditionally, the consumption of this cultivar has been only possible when the astringency has been naturally removed before harvest, when fruit is overripe and the manipulation is very delicate. In recent years, new postharvest treatments, which allow astringency removal while preserving high flesh firmness, have been developed. Among them, the most widely used in commercial settings is based on exposing fruits to high CO2 concentrations for 24 h–36 h. This method promotes anaerobic respiration in the fruit, giving rise to an accumulation of acetaldehyde and insolubilizing tannins at the end of the treatment. The effectiveness of this treatment is controlled by means of methods that are destructive, time-consuming and only a few samples per batch can be analysed. For this reason, the objective of this work is to study the application of the hyperspectral imaging technology in the detection of astringent and deastringent fruits non-destructively. A total of 300 fruits were used and exposed to CO2 during different times in order to obtain fruit with different content of soluble tannins. The hyperspectral images of the fruits were acquired using a VIS-NIR hyperspectral system, which covers the spectral range 450-1040 nm. A reference analysis of soluble tannins was performed in order to find out if the fruits were astringent or deastringent. The spectral information of the two thirds of the fruits was used to build the classification models by means of partial least squares (PLS) and support vector machine (SVM) discriminant analysis methods. The remaining third was used to validate the models as test set. As result, 92.6 % astringent and 84.4 % deastringent fruits were classified correctly using the SVM method. This shows the great potential of hyperspectral imaging technology to detect astringent and deastringent fruits in industrial setups

La agresividad en la conducción: Una investigación a partir de la visión de la población española

¿Qué entendemos por conducción agresiva? La agresividad en la conducción ha sido poco estudiada en nuestro país, hay una falta de conciencia pública y social. La investigación es el único modo de obtener herramientas eficaces para alcanzar objetivos con garantías de éxito. La difusión de los datos obtenidos puede servir para concienciar al público sobre esta problemática por lo que necesitamos conocer el grado de aceptación social de los distintos tipos de intervenciones. Las encuestas han sido el método más utilizado y además permiten la comparación de los datos obtenidos entre diferentes estudios. Permiten identificar grupos de riesgo y por tanto llevar a cabo estrategias de intervención específicas dirigidas a poblaciones concretas. Existe una clara preocupación social en torno a la agresividad en la conducción pero posiblemente no interpretamos del mismo modo la misma acción cuando la realizamos nosotros que cuando la llevan a cabo otros conductores. ¿Qué circunstancias hacen que se produzca agresividad en la conducción? ¿Cómo perciben los españoles la agresividad en la conducción? Este estudio pretende ofrecer un panorama descriptivo de la agresividad en la conducción en nuestro país. La óptica que se ha adoptado se centra en la percepción de la agresividad que manifiestan los conductores en España a través de la expresión de una serie de opiniones sobre cómo observan el fenómeno, cómo lo valoran o cómo lo relacionan con una serie de factores en el entorno del tráfico. En las conclusiones tratamos de sistematizar las distintas opiniones en torno a las temáticas desde la óptica de la población en general. De este modo obtenemos una imagen de lo que la población española opina de la agresividad en la conducción. Y por otro lado, también tratamos de sistematizar las opiniones en función de las características diferenciales de esta población (edad, sexo, nivel de estudios, etc.) en el intento de generar un retrato robot de las opiniones de cada uno de dichos segmentos tiene

Possible futures for groundwater in Burkina Faso under a changing climate

This narrative describes three possible future scenarios for water resources in Burkina Faso and the human and socio-economic impacts that might be experienced by people living in rural areas. The narratives aim to stimulate discussion towards realistic policy responses and the decision support tools needed to assist future planning needs. It is important to recognise that the scenarios do not represent every possible outcome projected by hydroclimate models, and resulting impacts will be contextualised by local circumstances. See here for information about BRAVE (www.walker.ac.uk) and the UPGro programme: upgro.org/consortium/brave2/

Assessment of the Methodology for Establishing the EU List of Critical Raw Materials - Annexes

This report presents the results of work carried out by the Directorate General (DG) Joint Research Centre (JRC) of the European Commission (EC), in close cooperation with Directorate-General for Internal Market, Industry, Entrepreneurship and SMEs (GROW), in the context of the revision of the EC methodology that was used to identify the list of critical raw materials (CRMs) for the EU in 2011 and 2014 (EC 2011, 2014). As a background report, it complements the corresponding Guidelines Document, which contains the “ready-to-apply” methodology for updating the list of CRMs in 2017. This background report highlights the needs for updating the EC criticality methodology, the analysis and the proposals for improvement with related examples, discussion and justifications. However, a few initial remarks are necessary to clarify the context, the objectives of the revision and the approach. As the in-house scientific service of the EC, DG JRC was asked to provide scientific advice to DG GROW in order to assess the current methodology, identify aspects that have to be adapted to better address the needs and expectations of the list of CRMs and ultimately propose an improved and integrated methodology. This work was conducted closely in consultation with the adhoc working group on CRMs, who participated in regular discussions and provided informed expert feedback. The analysis and subsequent revision started from the assumption that the methodology used for the 2011 and 2014 CRMs lists proved to be reliable and robust and, therefore, the JRC mandate was focused on fine-tuning and/or targeted incremental methodological improvements. An in depth re-discussion of fundamentals of criticality assessment and/or major changes to the EC methodology were not within the scope of this work. High priority was given to ensure good comparability with the criticality exercises of 2011 and 2014. The existing methodology was therefore retained, except for specific aspects for which there were policy and/or stakeholder needs on the one hand, or strong scientific reasons for refinement of the methodology on the other. This was partially facilitated through intensive dialogue with DG GROW, the CRM adhoc working group, other key EU and extra-EU stakeholders.JRC.D.3-Land Resource