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This master thesis explores the integration of Artificial Intelligence (AI) in Environmental, Social, and Governance (ESG) reporting, focusing on its potential to enhance the accuracy, transparency, and efficiency of ESG disclosures. It investigates how AI can transform ESG reporting from a reactive to a proactive tool, enabling companies to better assess and mitigate ESG-related risks. The study examines the perceptions of industry professionals regarding AI's role in ESG, considering factors such as age, education, and professional background. It highlights the significant impact AI can have on sectors like finance, energy, and healthcare, while addressing challenges and ethical concerns. The findings suggest that AI can be a powerful enabler of ESG transparency, but its adoption requires sector-specific adaptations and careful ethical considerations. Future research is recommended to explore long-term effects and deeper ethical issues in AI-driven ESG reporting. Objectius de Desenvolupament Sostenible::9 - Indústria, Innovació i Infraestructura Objectius de Desenvolupament Sostenible::16 - Pau, Justícia i Institucions Sòlides

With the increasing demand for clean and renewable energy sources, the need for reliable offshore wind technologies is undeniable. Given the elevated costs of maintenance at sea, it is crucial to ensure the proper functioning of each of the components of the machine, therefore, proper validation is essential. This thesis presents a methodological approach on the validation of one of the actuators from the yaw system, responsible of keeping the turbine facing the wind at all times. Each actuator is comprised of an electric motor and a variable frequency drive (VFD), which have been tested in a back-to-back test bench, property of GE VERNOVA. First, two small motors have been evaluated to obtain their internal parameters and familiarise with the tools and procedures. Then, two 7.5 kW motors have been studied to ensure that they are capable for implementation in the wind turbine, and they have been compared to find the better candidate. The results have shown that the Bonfiglioli BE160M seems to present better features that the Nord 160M/6CUS in terms of torque capabilities, efficiency, and size. Nevertheless, more testing is desired to corroborate the results. In conclusion, opting for the Bonfiglioli motor could potentially improve the performance of the GE VERNOVA offshore turbines. As future work, it would be interesting to support the findings by simulating real wind loads on the back-to-back test bench and analysing thermal properties of each motor.

[eng] Developing advanced and efficient electrocatalytic energy conversion systems is of great and practical significance for propelling the efficient development of clean energy for the construction of new low-carbon power systems. Among them, electrocatalytic reduction reactions driven by renewable electricity to transform biomass-derived chemicals into biofuels and high value-added chemicals provide an effective way to improve the H/C ratio of biomass-derived chemicals and the stabilizations of bio-oil systems. However, the electrocatalytic reduction of organic compounds is more intricate compared to the electrocatalytic reduction of water molecules. It involves the adsorption of various organic functional groups, multi-step electron transfer, and the generation of organic intermediates. Meanwhile, organic electrocatalytic reduction calls for designing efficient, highly selective, and cost- effective electrocatalysts. During a series conversion process of raw biomass, aldehydes are believed to be particularly troublesome for the aldol condensation and polymerization reactions. To avoid them, hydrogenation processes are necessary. As an alternative to traditional high-pressure and -temperature processing, we choose electrochemistry that can operate in ambient conditions for the conversion of benzaldehyde (BZH), which was chosen as a typical biomass-derived chemical. Another reason for choosing BZH is that the hydrogenation products benzyl alcohol (BA) and hydrobenzoin (HDB) are important industrial chemicals. Based on the mentioned above, this work seeks to design highly efficient and high selective catalysts for the electrocatalytic conversion of the carbonyl group of BZH into BA, HDB or benzoic acid (BZA) in aqueous solution at pH＞5 (avoiding the deoxygenation product toluene). Additionally, this work screens the optimal reaction conditions for various products and speculates their most probable reaction pathways. Chapter 4 focused on the electrocatalytic reduction of BZH into BA. Pd nanoparticles supported on a nickel metal-organic framework (MOF), Ni-MOF-74, are prepared and their activity towards the ECH of BZH in a 3M sodium acetate-acetic acid (pH 5.2) aqueous electrolyte is explored. An outstanding ECH rate up to 283 µmol cm-2 h-1 with a Faradic efficiency (FE) of 76% is reached. Besides, higher FEs of up to 96% are achieved using a step-function voltage. Materials studio and density functional theory calculations show these outstanding performances to be associated with the Ni- MOF support that promotes H-bond formation, facilitates water desorption, and induces a favorable tilted BZH adsorption on the surface of the Pd nanoparticles. In this configuration, BZH is bonded to the Pd surface by the carbonyl group rather than through the aromatic ring, thus reducing the energy barriers of the elemental reaction steps and increasing the overall reaction efficiency. Chapter 5 focused on the electrochemical reduction of self-coupling of BZH to HDB using semiconductor electrocatalysts with nanosheet morphologies. The effects of electrode potential and electrolyte pH on BZH self-coupling reaction were comprehensively studied on several semiconductor electrocatalysts. A correlation is observed between their band gap and the electrochemical potential necessary to maximize selectivity towards HDB in alkaline medium, which we associate with the charge accumulation at the semiconductor surface. N-type CuInS2 provides the highest conversion rate at 0.3 mmol cm−2 h−1 with a selectivity of 98.5% at -1.3 V vs. Hg/HgO in aqueous alkaline solution pH=14. Additional density functional theory calculations demonstrate a lower kinetic energy barrier at the CuInS2 surface compared with graphitic carbon, proving its catalytic role in the self-coupling reaction of BZH. Based on the previous two works, we realize that even when selecting materials with poor HER performance, different voltages and pH values have a significant impact on the selectivity of HDB. This drives us towards the rational design of electrocatalysts for these two different reaction pathways. Chapter 6 employed material with exposed active sites Cu2S and the material Cu2S-OAm with ligands capped to catalyze the electrocatalytic reduction reaction of the biomass platform molecule BZH convert into BA and HDB. Cu2S particles are used as electrocatalysts for the BZH electrochemical conversion. We particularly analyze the effect of surface ligands, oleylamine (OAm), on the selective conversion of BZH to BA or HDB. The effect of the electrode potential, electrolyte pH, and temperature are studied. Results indicate that bare Cu2S exhibits higher selectivity towards BA, while OAm-capped Cu2S promotes HDB formation. This difference is explained by the competing adsorption of protons and BZH. During the BZH electrochemical conversion, electrons first transfer to the C in the C=O group to form a ketyl radical. Then the radical either couples with surrounding H+ to form BA or self-couple to produce HDB, depending on the available H+ that is in turn affected by the electrocatalyst surface properties. The presence of OAm inhibits the H adsorption on the electrode surface therefore reducing the formation of high-energy state Had and its combination with ketyl radicals to form BA instead promotes the outer sphere reaction for obtaining HDB. Finally, we turn our attention to the anodic reaction in chapter 7. The electrooxidation of organic compounds offers a promising strategy for producing value-added chemicals through environmentally sustainable processes. A key challenge in this field is the development of electrocatalysts that are both effective and durable. In this study, we grow gold nanoparticles (Au NPs) on the surface of various phases of titanium dioxide (TiO2) as highly effective electrooxidation catalysts. Subsequently, the samples are tested for the oxidation of BZH to BZA coupled with a hydrogen evolution reaction (HER). We observe the support containing a combination of rutile and anatase phases to provide the highest activity. The excellent electrooxidation performance of this Au-TiO2 sample is correlated with its mixed-phase composition, large surface area, high oxygen vacancy content, and the presence of Lewis acid active sites on its surface. This catalyst demonstrates an overpotential of 0.467 V at 10 mA cm-2 in a 1 M KOH solution containing 20 mM BZH, and 0.387 V in 100 mM BZH, well below the oxygen evolution reaction (OER) overpotential. The electrooxidation of BZH not only serves as OER alternative in applications such as electrochemical hydrogen evolution, enhancing energy efficiency, but simultaneously allows the generation of high-value byproducts such as BZA [spa] El desarrollo de sistemas de conversión de energía electrocatalítica avanzados es crucial para la energía limpia y un sistema energético de bajo carbono. La reducción electrocatalítica de productos químicos de biomasa mejora la relación H/C y estabiliza los aceites biológicos, aunque es compleja debido a la transferencia de electrones y generación de intermediarios. Es esencial diseñar electrocatalizadores eficientes y selectivos. La hidrogenación de aldehídos en la biomasa cruda es necesaria para evitar reacciones no deseadas. Se utilizó la electroquímica para convertir benzaldehído (BZH) en productos industriales valiosos como alcohol bencílico (BA) e hidrobencoína (HDB). Este trabajo diseñó catalizadores eficientes para convertir BZH en BA, HDB o ácido benzoico (BZA) en solución acuosa con pH ＞ 5, optimizando las condiciones de reacción. En el Capítulo 4, se usaron nanopartículas de Pd en un marco metal-orgánico de níquel (Ni-MOF-74) logrando una alta eficiencia faradaica (FE) y mejor adsorción de BZH. El Capítulo 5 estudió el acoplamiento de BZH a HDB con electrocatalizadores semiconductores, destacando el CuInS₂ de tipo N por su alta selectividad y eficiencia. En el Capítulo 6, se usaron partículas de Cu₂S con y sin oleylamine (OAm), mostrando que OAm promueve la formación de HDB al inhibir la adsorción de protones. El Capítulo 7 se enfocó en la electrooxidación de BZH a BZA usando nanopartículas de oro (Au NPs) en dióxido de titanio (TiO₂), logrando alta actividad y eficiencia energética, generando además subproductos valiosos. Programa de Doctorat en Electroquímica. Ciència i Tecnologia

El cambio climático es un desafío polifacético que impacta profundamente en los entornos agrícolas, forestales y urbanos de todo el mundo. Esta tesis aborda la necesidad urgente de comprender y mitigar los efectos causados por el cambio climático, integrando la perspectiva ecológica y social. Así, analiza como la modelización socio-ecológica integrada puede mejorar la resiliencia y la capacidad de adaptación para hacer frente a los retos del cambio climático. Hasta ahora, las investigaciones han analizado los impactos del cambio climático dentro de marcos aislados, ya sea centrados en los impactos ecológicos o sociales. En esta conceptualización se ignora la interrelación de estos sistemas y no se consigue integrar el riesgo en su conjunto, adaptado al contexto ni identificar las oportunidades específicas. La tesis identifica este vacío en la evaluación socio-ecológica integrada bajo los riesgos climáticos, en diferentes contextos, poniéndolo al alcance tanto de científicos como de gestores del territorio. Esta investigación busca abordar este vacío generando estrategias resilientes y efectivas que mejoren la sostenibilidad a largo plazo. Impulsada por técnicas de razonamiento automático e inteligencia artificial, y alineada con los principios de la ciencia abierta y colaborativa, la metodología de esta tesis es innovadora e interdisciplinaria. Abarca el uso de modelos espacialmente explícitos adaptados al contexto, mediante datos de sensores remotos, el uso de sistemas de información geográfica y algoritmos avanzados de aprendizaje automático. Este marco metodológico permite un análisis detallado de interacciones complejas entre variables climáticas y ambientales de los sistemas socio-ecológicos. Los resultados de esta investigación destacan la eficiencia de la modelización integrada para comprender, pronosticar y mitigar los impactos potenciales del cambio climáticos. En los sistemas agrícolas, los modelos proyectan cambios en la dinámica ganadera, la lixiviación de nitrógeno y la salud de los pastos, lo cual lleva a prácticas de gestión integrales más sostenibles. En el sector forestal, los modelos de riesgo de incendios muestran una mayor precisión en la predicción de la probabilidad de incendios forestales y fundamentan las prácticas de gestión y prevención. El análisis urbano dentro de la tesis revela las claves de los efectos de enfriamiento de las zonas verdes, impulsando iniciativas de planificación urbana para ciudades más resilientes contra el aumento de las temperaturas. Los hallazgos de esta tesis identifican el papel crucial que ejerce la modelización estratégica en la comprensión y acción sobre los complejos desafíos que ejerce el cambio climático sobre los sistemas socio-ecológicos. Las implicaciones de esta investigación alcanzan ámbitos diversos y requieren apoyo de los agentes sociales para que se puedan desarrollar e implementar políticas de acción. Tales políticas podrán garantizar que los sistemas socio-ecológicos sean resilientes no solo ante los riesgos climáticos actuales, sino que también sean capaces de adaptarse a las condiciones climáticas futuras. Además, se pide un esfuerzo en promover la ciencia abierta, así como una colaboración transversal continúa para poder garantizar el desarrollo sostenible y la resiliencia de los sistemas socio-ecológicos a múltiples escalas. El canvi climàtic és un desafiament polifacètic que impacta profundament en els entorns agrícoles, forestals i urbans de tot el món. Aquesta tesi aborda la necessitat urgent de comprendre i mitigar els efectes causats pel canvi climàtic, integrant la perspectiva ecològica i social. Així, analitza com la modelització socioecològica integrada pot millorar la resiliència i la capacitat d'adaptació per fer front als reptes del canvi climàtic. Fins ara, les investigacions han analitzat els impactes del canvi climàtic dins de marcs aïllats, ja sigui centrats en els impactes ecològics o socials. En aquesta conceptualització s'ignora la interrelació d'aquests sistemes i no s'aconsegueix integrar el risc en el seu conjunt, adaptat al context ni identificar les oportunitats específiques. La tesi identifica aquest buit en l'avaluació socioecològica integrada sota els riscos climàtics, en diferents contextos, posant-lo a l’abast tant de científics com de gestors del territori. Aquesta investigació busca abordar aquest buit generant estratègies resilients i efectives que millorin la sostenibilitat a llarg termini. Impulsada per tècniques de raonament automàtic i intel·ligència artificial, alineada amb els principis de la ciència oberta i col·laborativa, la metodologia d'aquesta tesi és innovadora i interdisciplinària. Abasta l'ús de models espacialment explícits adaptats al context, mitjançant dades de sensors remots, l’ús de sistemes d'informació geogràfica i algorismes avançats d'aprenentatge automàtic. Aquest marc metodològic permet una anàlisi detallada d'interaccions complexes entre variables climàtiques i ambientals dels sistemes socioecològics. Els resultats d'aquesta recerca destaquen l'eficiència de la modelització integrada per a comprendre, pronosticar i mitigar els impactes potencials del canvi climàtics. En els sistemes agrícoles, els models projecten canvis en la dinàmica ramadera, la lixiviació de nitrogen i la salut de les pastures, la qual cosa porta a pràctiques de gestió integrals més sostenibles. En el sector forestal, els models de risc d'incendis mostren una major precisió en la predicció de la probabilitat d'incendis forestals i fonamenten les pràctiques de gestió i prevenció. L’anàlisi urbà dins de la tesi revela les claus dels efectes de refredament de les zones verdes, impulsant iniciatives de planificació urbana per a ciutats més resilients contra l'augment de les temperatures. Les troballes d’aquesta tesis identifiquen el paper crucial que exerceix la modelització integrada i estratègica en la comprensió i acció sobre els complexos desafiaments del canvi climàtic sobre els sistemes socioecològics. Les implicacions d'aquesta recerca abasten molts àmbits i requereixen suport dels agents socials perquè es puguin desenvolupar i implementar. Tals polítiques podran garantir que els sistemes socioecològics siguin resilients no sols davant dels riscos climàtics actuals sinó també capaços d'adaptar-se a les condicions climàtiques futures. A més, es demana un esforç en ciència oberta així com una col·laboració transversal continua per tal de poder garantir el desenvolupament sostenible i la resiliència dels sistemes socioecològics a múltiples escales. Climate change is a multifaceted challenge that impacts agricultural, forestry, and urban settings in deep ways throughout the world. This thesis addresses the pressing need to understand and mitigate risks caused by climate change from an overall perspective of integrating the ecological and social dimensions of the impacts. The central thesis question investigates the role that integrated socio-ecological modeling can play in enhancing resilience and adaptive capacity within these systems against climate change challenges. Current research typically analyses the impacts of climate change within isolated frameworks, focusing on either ecological or social impacts. The interrelationship between these systems is ignored in this conceptualization and fails to capture the overall risk and opportunities for adaptation. This thesis identifies a critical gap in the integrated assessment of climate risks and responses across different socio-ecological contexts by sharing solutions with scientists and land managers. This research seeks to address this gap by generating resilient and effective strategies that enhance the long-term sustainability of these systems. Empowered by AI-driven and machine reasoning techniques and in line with open and collaborative science, the methodology of this thesis is both innovative and interdisciplinary. It encompasses the use of spatially explicit models adapted to the context, by remotely sensed data, use of geographic information systems, and advanced machine learning algorithms. This methodological framework allows for a detailed analysis of the complex interactions between climate and environmental variables of socio-ecological systems. The results from this research highlight the efficiency of integrated modeling in understanding, forecasting, and mitigating potential impacts of climate change. In agricultural systems, the models project changes in livestock dynamics, nitrogen leaching, and pasture health, leading to integral sustainable management practices. In forestry, fire risk models show an increase in accuracy in predicting the probability of wildfires and better inform effective management and prevention practices. Urban analysis reveals clues to the cooling effects of green spaces, informing urban planning initiatives toward boosting city resilience to rising temperatures. The findings of this work identify the crucial role that strategic integrated modeling plays in understanding and acting upon the complex climate change challenges of socio-ecological systems. The implications of this research are significant, and call for policy support in terms of innovative technologies that can be developed and implemented collaboratively. Such policies will ensure that socio-ecological systems are fit not just for current climate risks but are also able to adapt to changing climatic conditions. Moreover, it calls for an effort to promote open science, as well as continued cross-cutting collaboration, to guarantee the sustainable development and resilience of social-ecological systems at multiple scales.

In this paper, a land-use modelling framework is presented combining empirical and theory-based modelling approaches to determine economic potential of biofuel production avoiding indirect land-use changes (iLUC) resulting from land competition with other functions. The empirical approach explores future developments in food and feed production to determine land availability and technical potential of biofuel production. The theory-based approach assesses the economic performance of biofuel crops on the surplus land in comparison with other production systems and determines the economic potential of biofuel production. The framework is demonstrated for a case study in Argentina to determine the development of biofuel potential from soy and switchgrass up to 2030. Two scenarios were considered regarding future developments of productivity in agriculture and livestock production. It was found that under a scenario reflecting a continuation of current trends, no surplus land is expected to become available. Nevertheless, the potential for soybean biodiesel is expected to keep increasing up to 103 PJ in 2030, due to the existence of a developed agro-industrial sector jointly producing feed and biodiesel. In case large technological developments occur, 32 Mha could become available in 2030, which would allow for a technical potential of 472 PJ soybean biodiesel and 1445 PJ switchgrass bioethanol. According to the economic assessment, an economic potential of 368 PJ of soy biodiesel and 1.1 EJ switchgrass bioethanol could be attained, at a feedstock production cost of 100–155 US$/ton and 20–45 US$/ton, respectively. The region of southwest Buenos Aires and La Pampa provinces appeared to be particularly promising for switchgrass. The ability of jointly assessing future developments in land availability, technical and economic potential of biofuel production avoiding iLUC and spatial distribution of viable locations for growing biofuel crops means that the proposed framework is a step forward in assessing the potential for biofuel production that is both economically viable and sustainably produced.

El propòsit de la tesi va ser explorar mitjançant estudis empírics l'evolució de l'ús de les eines Lean a les empreses manufactureres europees i el seu vincle amb les tecnologies de la Indústria 4.0 i les pràctiques green. En primer lloc, es va investigar l'adopció i la internalització de les eines Lean i el seu impacte en el rendiment productiu a les empreses manufactureres espanyoles. Tot seguit, es va analitzar la influència de la internalització de les eines Lean en l'adopció de tecnologies de la Indústria 4.0 a les empreses manufactureres europees. I, finalment, es va examinar la relació entre l'ús conjunt d'eines Lean i les pràctiques green associat a l'exercici mediambiental a les empreses manufactureres espanyoles. La metodologia emprada al llarg dels estudis presentats es va basar en l'anàlisi de dades extretes de la European Manufacturing Survey The purpose of the thesis was to explore through empirical studies the evolution of the use of lean tools in European manufacturing firms and their link with Industry 4.0 technologies and green practices and Circular Economy. First, the adoption and internalisation of lean tools and their impact on production performance in Spanish manufacturing firms were investigated. Next, the influence of the internalisation of Lean tools on the adoption of Industry 4.0 technologies in European manufacturing firms was analysed. Finally, the relationship between the joint use of Lean tools and green practices associated with environmental performance in Spanish manufacturing firms was examined. The methodology employed throughout the studies presented was based on the analysis of data extracted from the European Manufacturing Survey Programa de Doctorat Interuniversitari en Dret, Economia i Empresa

El món s'enfronta actualment a un dels majors desafiaments en la història de la humanitat: l'escalfament global. La transició cap a les energies renovables és crucial per al desenvolupament sostenible. Al mateix temps, al voltant de 750 milions de persones no tenen accés a l'electricitat. Així, la humanitat s'enfronta a un doble problema: proporcionar un accés més fàcil a l'electricitat i assegurar-se que aquesta energia prové de fonts netes per evitar un desastre climàtic. Aquesta tesi explora el potencial de les microrredes d'energia renovable per millorar l'accés a l'electricitat en els països en desenvolupament. La primera part és una introducció general i una revisió de l'estat de l'art de les tecnologies actuals de microrredes, incloent-hi sistemes fotovoltaics, eòlics i petites hidroelèctriques, il·lustrats amb exemples de projectes reeixits a tot el món. La segona part se centra en el potencial de les microrredes d'energia renovable a Jacmel, Haití. L'estudi inclou una anàlisi detallada del panorama energètic existent, els patrons de demanda, l'anàlisi de costos i la viabilitat d'integrar tecnologies renovables. Utilitzant el programari HOMER, es comparen diferents escenaris mitjançant simulacions per optimitzar l'eficiència, el cost i l'impacte ambiental. Els resultats demostren que la incorporació de microrredes d'energia renovable pot millorar significativament la fiabilitat energètica i reduir les emissions de carboni. Aquest estudi integral proporciona valuosos coneixements sobre els aspectes tècnics i econòmics de la implementació de sistemes d'energia renovable en regions en desenvolupament, contribuint als objectius més amplis de transició energètica d'Haití. Destaca els beneficis de les microrredes renovables en la millora de l'accés i la sostenibilitat energètica, servint com a model per a regions similars a tot el món.