https://uvadoc.uva.es/handle/10324/1166 42 2026-05-05T20:17:35Z https://uvadoc.uva.es/handle/10324/84208 Green roofs and walls can mitigate the environmental and climate change of a city. They can decrease the urban heat island (UHI), reduce greenhouse gas emissions, fix environmental pollutants, manage urban stormwater runoff, attenuate noise, and enhance biodiversity. This paper aims to analyse green roofs and walls in the possible mitigation of urban climate change and compare it by continent. Green roofs and walls might decrease the air temperature in a city up to 11.3 degrees C and lower the thermal transmittance into buildings up to 0.27 W/m(2) K. Urban greening might sequester up to 375 g C center dot m(-2) per two growing seasons and increase stormwater retention up to 100%. Urban greening might attenuate city noise up to 9.5 dB. The results found green roofs and walls of varied effectiveness in ameliorating climate extremes present in host continents. Results show urban planners might focus on green roofs and walls exposure to attenuate temperatures in hotter Asian cities and advise greening in cities in Africa and Asia. European and American designers might optimise runoff water capacity of green roofs and walls systems and use greening in old buildings to improve insulation. Recommendations are made based on the study to concentrate certain designs to have greater impact on priority climate challenges, whether UHI or stormwater related. This study provides information for decision and policymakers regarding design and exposure of green roofs and walls to mitigate urban environmental and climate change. 2021-01-01T00:00:00Z https://uvadoc.uva.es/handle/10324/84207 Uno de los actuales retos para mejorar la competitividad y productividad del sector agrario es atraer y retener personal cualificado. El objetivo del presente trabajo es analizar las diferencias en las preferencias ante el empleo en el sector agrario, con el objeto de mejorar la atracción y retención del talento. Se analizó una muestra probabilística de 522 trabajadores y universitarios. Se realizaron entrevistas personales y grupos focales. Las pruebas de contraste no paramétrico de U de Mann‑Whitney y Kruskal Wallis sirvieron para obtener las diferencias significativas entre las preferencias ante el empleo según puesto, género, generación y trabajadores actuales y futuros. Los resultados muestran un cambio en las preferencias ante el empleo en las nuevas generaciones; los trabajadores hasta los 40 años se diferencian en preferir empleos en que puedan realizarse profesionalmente y los universitarios, el salario y las retribuciones flexibles y para los menores de 20 años que el trabajo esté en consonancia con sus ideas. Las mujeres universitarias se diferencian en preferir un trabajo en consonancia con sus ideas y los hombres, las retribuciones por rendimiento. Los directivos y gerentes se diferencian en preferir retribuciones por rendimiento y flexibles, el desarrollo personal, la conciliación, el ambiente laboral, la estabilidad y la consonancia de ideas. Además, los trabajadores futuros difieren significativamente en preferir un trabajo que les permita desarrollarse profesionalmente y que la empresa ofrezca formación, reconocimientos u otras formas de motivación. Se concluye la necesidad de llevar a cabo una gestión diferenciada de personal, así como mejorar la alineación universidad-empresa para atraer y retener el talento en el sector agrario mejorando la competitividad y productividad. 2021-01-01T00:00:00Z https://uvadoc.uva.es/handle/10324/84206 This research aims to analyse the potential of Urban Agriculture (UA) in the city of Palencia (Castilla y Leon) to address the problems and challenges facing the city and analyse what factors can favour its development. In doing so, the challenges established in the Strategy for Sustainable and Integral Urban Development (EDUSI) of Palencia and the possible contribution of the AU were analysed. The data of the geographic information system of agrarian data along with semi-structured surveys and visits to managers of UA initiatives in the city, the city's participatory processes and other factors that can contribute to its promotion were analysed. The results show a drastic decrease in the horticultural function in Palencia. The contribution of the UA to face the challenges of the city of Palencia can be based on: the AU is an innovative solution with the capacity to contribute to mitigating the effects of climate change; allows a healthy leisure offer to an aging population; it can contribute to creating a culture favourable to organic, local and local food; allows innovative forms of social action, favouring the integration of different groups (retired, disabled, young people, people at risk of social exclusion...) and contributes to promoting the low-carbon city model, helping to create more resilient cities in adapting to climate change. The UA currently has, therefore, multiple functions. Participatory processes around the challenges of the city and the food system can be a good starting point for its development. Also, managers in charge are needed, a detailed analysis of the possible reusable land, transfer of agricultural land and greater support and regulation of the activity that allows the development of urban models of agriculture with a multitude of functions: social, occupational, leisure, participatory, productive (favouring close access to healthy food), providing safe outdoor spaces and fulfilling a function of natural self-regulation of ecosystems. 2022-01-01T00:00:00Z https://uvadoc.uva.es/handle/10324/84203 Urban agriculture is a nature-based solution recommended for regeneration and adaptation of urban areas to climate change, in line with the European Green Deal. However, for the development of urban agriculture, the availability, access and usability of arable land in urban areas are of particular concern. This study aimed to use the AGRO-GIS digital agricultural geographic information system to calculate and predict the potential of urban agriculture from abandoned horticultural land and greenhouses in urban areas. In this way, the variation of agricultural land in urban areas was calculated. A binary logistic regression modeled abandoned horticultural land and greenhouses in urban areas to derive determinants of urban agricultural potential. An analysis of variance (ANOVA) was then used to obtain significant differences in the variation of agricultural land between urban areas. The results show that an average of 97.85 ha of abandoned horticultural land and greenhouses can provide potential urban arable land in cities. A variation in non-irrigated land and grassland-woodland are determinants of urban agricultural potential. A one-hectare decrease in non-irrigated land is associated with an 87.98% increase in the chance of potential urban agriculture. A one-hectare increase in grassland/grassland area increases the probability of potential urban agriculture by 67.59%. In addition, it concludes that differentiated planning and management of urban agriculture according to urban areas is needed. This study can help urban planners to manage, plan and forecast arable land for urban agriculture. 2022-01-01T00:00:00Z https://uvadoc.uva.es/handle/10324/84201 This study aimed to get insight into the acceptance of insects as food using neophobia descriptors. Data were collected through questionnaires applied to a Spanish-Dominican sample. Models were created using binary logistic regression, and determinants of acceptance of insects as food were obtained. The results reveal that Dominicans presented the highest food neophobia and the lowest acceptance of insects as food. The openness to eat almost anything is the positive determinant in Spain for accepting insects as food, while in the Dominican Republic to overstate the benefits of the new food technologies. Principal component analysis was used to calculate the optimal number of descriptors in the neophobia scales; 3–5 descriptors could be removed. Marketers can use these results to better understand how to market insect-based products considering different contexts. 2021-01-01T00:00:00Z https://uvadoc.uva.es/handle/10324/84191 Eight scenarios of fresh tomato supply to urban citizens were analysed using a Life Cycle Analysis (LCA) approach. Two of the scenarios corresponded to unheated greenhouses and a long distance transportation to the final consumer; four scenarios corresponded to zero-miles agriculture in a rural environment, including heated greenhouses, unheated greenhouses and open-field production; another two scenarios corresponded to Urban Agriculture (UA). The objective was to compare the environmental impacts of the production and transportation of tomatoes to the final consumer. Zero-miles production in heated greenhouses had the highest environmental impact (e.g. the Global Warming Potential GWP was 0.33 kg CO2 eq per kg of tomato), to such an extent that production in unheated greenhouses far away was comparatively better (GWP was 0.21 kg CO2 eq). Conversely, zero-miles production in the open-field was, environmentally, the best option with a GWP of 0.12 kg CO2 eq. Interestingly, the distance travelled by the product was less important than the efficiency of the transport. Other important environmental burdens were inefficient irrigation, chemical disinfection of the soil and the technological appliances used for micro-agriculture. As a consequence, the best zero-miles agriculture scenario was not the one where tomatoes were grown closest to the consumer's table, but the one that used the most efficient and less contaminating agronomic management and transport strategy. Thus, UA was not environmentally superior to zero-miles agriculture carried out in rural areas; conversely, rural horticulture helps to stabilize the population in regions suffering from depopulation. 2022-01-01T00:00:00Z https://uvadoc.uva.es/handle/10324/84188 Cultured meat is a relatively new product, enjoying consumer appreciation as a more sustainable meat option. The present study builds on a sample from a diverse set of countries and continents, including China, the US, the UK, France, Spain, Netherlands, New Zealand, Brazil, and the Dominican Republic and uses partial least square structural equation modelling. The proposed conceptual model identified key factors driving and inhibiting consumer willingness to try, buy, and pay a price premium for cultured meat. Results relate to the overall sample of 3091 respondents and two sub-sample comparisons based on gender and meat consumption behaviour. Food neophobia, having food allergies, being a locavore, and having concerns about food technology were found to be inhibiting factors towards willingness to try, buy, and pay a price premium for cultured meat. Food curiosity, meat importance, and a consumer's perception of cultured meat as a realistic alternative to regular meat were found to be important drivers that positively impacted consumers' willingness to try, buy and pay more. Best practice recommendations address issues facing marketing managers in food retail and gastronomy. 2022-01-01T00:00:00Z https://uvadoc.uva.es/handle/10324/84151 The aim of this research is to explore content, traffic and visibility on four social platforms to boost social visibility.Design/methodology/approachThe study explores content, traffic and visibility in the context of Spanish beer brands. A sample of 3,332 beer brands' social media (SM) sites, specifically the four most commonly used platforms amongst Spaniards, was analysed. An inductive content analysis by a panel of experts identified the main contents. A cluster analysis then divided the significantly different beer brand SM sites, and a Kruskal-Wallis test confirmed the significant differences by content and traffic. To determine and predict SM visibility, a binary logistic regression was conducted.FindingsThe findings reveal that traffic is not significantly correlated with social visibility. Moreover, the SM sites with the highest traffic show significant leisure content. Twitter is significantly different network in traffic and content, whilst YouTube is the best for boosting social visibility.Practical implicationsThe study's findings constitute valuable information in understanding how content, traffic and visibility are correlated and help in managing brands' public presence and exposure on SM.Originality/valueThis study contributes to the existing literature by exploring four SM platforms (Twitter, Instagram, YouTube and Facebook), two dimensions of SM interactions (traffic and social visibility) and three main focal points of contents (leisure, product and promotion). This research bridges the gap amongst content, traffic and social visibility and ascertains how to gain traffic and boost social visibility. 2023-01-01T00:00:00Z https://uvadoc.uva.es/handle/10324/84150 This study aims to analyse how regions benefit from developing urban agriculture into the research and innovation smart specialisation strategy (RIS3). To this end, the socio-economic structural variables employed by the EU to design regional RIS3s were analysed from a sample of 100 European regions. A binary logistic regression revealed that a population over the age of 65 is a key factor in developing urban agriculture, and an increase of 1% in this age group could lead to a 72.75% increase in urban agriculture. Then, an ANOVA showed that regions benefit from developing urban agriculture as part of the RIS3 in the promotion of active ageing and diversification, in alleviating the pressure of urbanisation on city resources, and in the development of technology, patents in mechanical engineering, creativity and new ideas, improving governance and increasing their social capital. Methodologically, socio-economic structural variables were reduced from 42 to 24 with shortest and simple instruments capturing the most important information, easier to manage and work with. It is concluded that lagging and leading regions benefit from the development of UA into RIS3. 2025-01-01T00:00:00Z https://uvadoc.uva.es/handle/10324/84145 The growing integration of variable renewable energy (VRE) challenges traditional capacity valuation methods in electricity markets, which mainly rely on probabilistic models and technical adequacy metrics and are not linked to market design and economic incentives. This study introduces a new approach to assessing the Economic Capacity Value (ECV) of VRE resources, which measures their contribution to system reliability, considering resource availability and market conditions. The methodology is applied using a co-optimization model of the energy market and the capacity remuneration mechanism that minimizes total system costs and capacity payments. The framework is applied to the Dominican Republic's electricity market, using 2023 demand and generation data. Results show that VRE resources provide a significant contribution to system reliability under existing market conditions. Solar photovoltaic ECVs range from 21.8 MW (17.2%) in the north region to 107.2 MW (33.6%) in the southwest, while wind power exhibits higher values, reaching 87.6 MW (43.9%) in the north and 74.7 MW (34.4%) in the southwest. In all cases, ECV surpasses the capacity factor, indicating that VRE contributes more to reliability than its average production suggests. Sensitivity analysis shows that ECV is highly sensitive to market design parameters, with ±25% variations in capacity payments or scarcity prices resulting in ECV changes of up to 34%. These findings show that capacity value can be influenced by both resource availability during high demand periods and market design, supporting the inclusion of VRE in capacity remuneration mechanisms based on ECV. 2026-01-01T00:00:00Z https://uvadoc.uva.es/handle/10324/83993 Photovoltaic power plants require module inspections to detect failures, thereby avoiding safety issues and optimizing overall operation. Luminescence imaging acquisition offers a viable solution for photovoltaic inspections, providing valuable information about module performance. This article presents a novel technique termed passive electroluminescence and photoluminescence, capable of producing luminescence images under daylight conditions by using sunlight or string current as excitation sources for photoluminescence and electroluminescence modulation, respectively. To achieve this modulation, an electronic board has been developed, which connects within a photovoltaic string and allows for measurements during the normal operation of the plant. The study focuses on analysing two strategies: synchronous and asynchronous lock-in approaches. While the synchronous method requires coordination between the camera and the electronic board, the asynchronous method operates independently of such synchronization. Although both strategies have been successfully validated, results indicate that the asynchronous strategy is faster and simpler to implement, whereas the synchronous approach may yield slightly higher quality results. 2026-01-01T00:00:00Z https://uvadoc.uva.es/handle/10324/83917 The estimation of series resistance in photovoltaic (PV) cells is a crucial parameter that significantly influences their efficiency and overall performance. This study proposes a novel methodology to predict the slope of the current–voltage (Ⅰ–Ⅴ) curve of a PV cell in the first quadrant, where this slope (the electrical conductance) is directly associated with the series resistance of the cell. By leveraging artificial intelligence techniques, a convolutional neural network model has been developed to estimate this slope from electroluminescence (EL) images of the cells. The model was trained on a dataset consisting of EL images of PV cells with artificially induced defects, together with the corresponding slope values derived from the cells' Ⅰ–Ⅴ curves. Furthermore, this work presents a second model that combines the slope information and EL images to improve the prediction of the maximum power point (MPP) of a PV cell, surpassing previous approaches that rely solely on EL imagery. Both models demonstrated low error rates across multiple evaluation metrics, evidencing their accuracy and robustness. Additionally, comparative analysis with other machine learning methods highlights the competitive performance of the proposed approaches. These contributions provide promising tools for enhancing the assessment and diagnosis of PV cell efficiency and reliability, potentially leading to improved performance and increased longevity of photovoltaic systems. 2026-01-01T00:00:00Z https://uvadoc.uva.es/handle/10324/83754 This manuscript introduces two Adaptive Neuro-Fuzzy Inference Systems developed to predict the energy output of Photovoltaic cells. These models are trained using Electroluminescence imagery of the cells for input data along their Current–Voltage curves, which offer insights output power of cells. The input characteristics of the cells are quantified based on pixel distribution and classified into three distinct categories: Black, White, and Gray values. The second model enhances this representation by incorporating an additional fuzzy categorization input, derived from a Mamdani Classifier Fuzzy Logic Model. By combining the rule-based interpretability of Fuzzy Logic with the adaptive learning capabilities of Artificial Neural Networks, the Adaptive Neuro-Fuzzy Inference System (ANFIS) emerges as an alternative to Convolutional Neural Networks (CNNs). This approach contributes to Explainable Artificial Intelligence by addressing one of the major limitations of CNNs—the lack of symbolic knowledge representation, while maintaining robust learning performance. Comparative analysis with other Machine Learning techniques demonstrates the enhanced performance provided by ANFIS models, achieving a Mean Absolute Error (MAE) of 0.053 and a Mean Squared Error (MSE) of 0.007. 2026-01-01T00:00:00Z https://uvadoc.uva.es/handle/10324/83311 Overripening of grapes, due to global warming, can result in unbalanced wines with higher alcohol content, lower acidity and an altered sensory profile. Pre-fermentative treatment of the must with a glucose oxidase- catalase enzyme system immobilized in silica‑calcium-alginate hydrogel capsules degraded up to 17.3% of the glucose in the must in 48 h to obtain wines with 1.0–1.3% vol (v/v) lower alcoholic strength. Most of the gluconic acid produced by glucose oxidation was retained in the capsules, resulting in a mild reduction in the pH, thereby avoiding a strong acidification of the must. The remainder of the gluconic acid present in the must was largely degraded during the fermentation process using a selected strain of the yeast Schizosaccharomyces pombe (S. pombe). Both the enzymatic treatment of the must with the capsules and the use of S. pombe, either in unique inoculation or in sequential inoculation with a Saccharomyces cerevisiae (S. cerevisiae), led to balanced wines with a unique chemical profile. The combination of these two strategies, pre-fermentative and fermentative, presents an innovative and promising approach, not investigated so far, to counteracting the adverse effects of rising temperatures due to global warming. 2026-01-01T00:00:00Z https://uvadoc.uva.es/handle/10324/83091 This paper presents the design, construction, and calibration of a modular low-cost 3D printer based on open-source technologies, developed as part of an academic research project. The printer utilises fused filament fabrication (FFF) and is built using locally available materials and components, including a T-slot aluminium frame, NEMA 23 stepper motors, and an Arduino Mega 2560 with RAMPS 1.4 control board. The system integrates Marlin firmware and CURA slicing software, enabling autonomous operation via an LCD panel and encoder interface. A detailed methodology is provided for mechanical assembly, electronic integration, firmware configuration, and calibration procedures. Special attention is given to the challenges encountered during the initial testing phase, including filament feeding issues, thermal inconsistencies, and mechanical misalignments. Solutions such as replacing inadequate components (e.g., fibreglass bushings with PTFE), adjusting spring tension, and refining firmware parameters are discussed. The results demonstrate successful printing of complex geometries after iterative calibration, validating the printer’s performance and replicability. This work contributes to the democratisation of additive manufacturing by offering a replicable, open-source solution for educational and prototyping purposes. The findings are relevant to machine design, automation, and robotics communities seeking practical insights into low-cost fabrication systems. 2026-01-01T00:00:00Z https://uvadoc.uva.es/handle/10324/82998 Intensive farming causes an important amount of greenhouse gas emissions. This scenario can be significantly reduced by the implementation of renewable technologies and transforming farms from energy consumers to energy providers. In the particular case of livestock production, biogas and solar energy reduce greenhouse gas emissions and the energy demand of the installations. However, the implementation of these technologies requires solutions adapted to local scenarios, such as connectivity to the energy grids. In this work, a biogas/biomethane production system, energetically covered with hybrid solar panels is proposed as a solution for isolated areas where biodegradable substrates (manure) are abundant. Thus, the electrical and thermal requirements of the digester are supplied by solar panels, reducing the biogas self-consumption and the energy inputs from the electrical grid. Hybrid solar panels also provide sufficient energy for operation of an upgrading system to obtain biomethane of fuel vehicle quality, increasing the energy self-sufficiency of the agricultural activities. This solution has been simulated in five different climatic regions corresponding to areas of intense pig farming activity. The results demonstrate the sustainable bioenergy production in isolated farms with limited connection to the energy grid and organic matter availability. Furthermore, the economic study showed that the proposed technology is competitive compared to other technologies in the energy sector. 2023-01-01T00:00:00Z