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Los lípidos constituyen una parte importante de la dieta y participan en numerosas funciones biológicas vitales. Particularmente, el aceite de pescado es un valioso producto rico en ácidos grasos poliinsaturados Omega-3, que en la actualidad se considera atractivo por sus efectos benéficos a la salud humana. Los aceites marinos a menudo se descartan como desecho en muchas industrias pesqueras, principalmente debido a la falta de implementación de procesos innovadores de recuperación y refinado de estos recursos de forma lucrativa y sustentable. En este trabajo se aborda dicha problemática al proponer una metodología sistemática con el objetivo de integrar los aspectos económicos, ambientales y sociales en las decisiones de diseño de procesos de una refinería de aceite de pescado crudo, enfocado en la producción de concentrados de Omega-3 a partir del aceite residual de una planta procesadora de harina de atún en México. Esto puede realizarse mediante la formulación y solución de un problema de optimización multi-objetivo que incluye opciones de procesamiento convencionales, así como intensificadas dentro una superestructura. El problema MINLP (Mixed Integer Non-Linear Programing) resultante es solucionado con una combinación de métodos lexicográfico y de restricción épsilon (ε-constraint), para luego someter a una evaluación comparativa las soluciones obtenidas en forma de frente de Pareto utilizando Análisis de Ciclo de Vida y Análisis de Riesgos con la asistencia de un software de simulación de procesos (SuperPro Designer®). La metodología de búsqueda del diseño de proceso óptimo sustentable arrojó tres configuraciones factibles, destacando la selección de procesos intensificados como nano-neutralización, destilación molecular, transesterificación con ultrasonido y cromatografías argentométrica y con CO2. De los cuales, el proceso utilizando cromatografía con CO2 supercrítico resultó tener mejor desempeño en términos de indicadores de Análisis de Ciclo de Vida y seguridad industrial. A su vez, este trabajo proporciona una base de datos de propiedades de los compuestos lipídicos y técnicas de procesamiento que puede ser implementada en futuros proyectos. Además, ayuda a demostrar que la revalorización de los aceites marinos, así como de los desechos de la industria alimentaria en general, es importante para lograr un modelo de economía circular dentro del desarrollo productivo sustentable. Lipids constitute an important part of the diet and participate in numerous vital biological functions. Fish oil, in particular, is a valuable nutritious product, mainly due to its Omega-3 polyunsaturated fatty acids content that is currently attractive for its beneficial health effects. Marine oils are often discarded as waste in many seafood industries, primarily due to the lack of implementation of innovative resource recovery and oil refining processes in a lucrative and sustainable way. This work tackles this issue by proposing a systematic framework with the objective to integrate the economic, environmental and social aspects together in the process design decisions of a crude fish oil refinery focused on the production of Omega-3 concentrates from waste oil of a tuna processing plant in Mexico. This is addressed by the formulation and solution of a multi-objective optimization design problem that includes conventional and intensified processing options in a superstructure. The resulting MINLP (Mixed Integer Non-Linear Programing) problem is solved with a combination of lexicographic and ε-constraint methods. Then, the solutions provided in the form of a Pareto front are subject to benchmarking with a Life Cycle Assessment and risk analysis methodology with the assistance of a process simulation software (SuperPro Designer®). The search methodology of the sustainable optimal process design resulted in three feasible configurations, highlighting the selection of intensified processes such as nano-neutralization, molecular distillation, ultrasound assisted transesterification, and argentometric and CO2 chromatography. Among these, the process using supercritical CO2 chromatography has the best performance in terms of Life Cycle Assessment and industrial safety indicators. At the same time, this work provides a database of lipid compound properties and processing techniques that can be implemented in future projects. In addition, it helps to demonstrate that the revalorization of marine oils, as well as other waste from the food industry in general, is relevant to achieve a circular economy model within sustainable productive development. Administradores Investigadores Estudiantes

Machine learning's application in solar-thermal desalination is limited by data shortage and inconsistent analysis. This study develops an optimized dataset collection and analysis process for the representative solar still. By ultra-hydrophilic treatment on the condensation cover, the dataset collection process reduces the collection time by 83.3%. Over 1,000 datasets are collected, which is nearly one order of magnitude larger than up-to-date works. Then, a new interdisciplinary process flow is proposed. Some meaningful results are obtained that were not addressed by previous studies. It is found that Radom Forest might be a better choice for datasets larger than 1,000 due to both high accuracy and fast speed. Besides, the dataset range affects the quantified importance (weighted value) of factors significantly, with up to a 115% increment. Moreover, the results show that machine learning has a high accuracy on the extrapolation prediction of productivity, where the minimum mean relative prediction error is just around 4%. The results of this work not only show the necessity of the dataset characteristics' effect but also provide a standard process for studying solar-thermal desalination by machine learning, which would pave the way for interdisciplinary study.

While the operating cost of electricity grids based on thermal generation was largely driven by the cost of fuel, as renewable penetration increases, ancillary services represent an increasingly large proportion of the running costs. Electric frequency is an important magnitude in highly renewable grids, as it becomes more volatile and therefore the cost related to maintaining it within safe bounds has significantly increased. So far, costs for frequency-containment ancillary services have been socialised in most countries, but it has become relevant to rethink this regulatory arrangement. In this paper, we discuss the issue of cost allocation for these services, highlighting the need to evolve towards a causation-based regulatory framework. We argue that parties responsible for creating the need for ancillary services should bear these costs. However, this would imply an important change in electricity market policy, therefore it is necessary to understand the impact on current and future investments on generation, as well as on electricity tariffs. Here we provide a mostly qualitative analysis of this issue, defining guidelines for practical implementation and further study. Published in journal Energy Policy

In the last decade, the manufacturing capacity of silicon, the dominant PV technology, has increasingly been concentrated in China. This has led to PV cost reduction of approximately 80%, while, at the same time, posing risks to PV supply chain security. Recent advancements of novel perovskite tandem PV technologies as an alternative to traditional silicon-based PV provide opportunities for diversification of the PV manufacturing capacity and for increasing the GHG emission benefit of solar PV. Against this background, we estimate the current and future cost-competitiveness and GHG emissions of a set of already commercialized as well as emerging PV technologies for different production locations (China, USA, EU), both at residential and utility-scale. We find EU and USA-manufactured thin-film tandems to have 2 to 4% and 0.5 to 2% higher costs per kWh and 37 to 40%and 32 to 35% less GHG emissions per kWh at residential and utility-scale, respectively. Our projections indicate that they will also retain competitive costs (up to 2% higher)and a 20% GHG emissions advantage per kWh in 2050.