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Municipal solid waste (MSW) management in Spain, particularly in the Valencian Community, heavily relies on mechanical–biological treatment (MBT) plants followed by landfill disposal. These MBT facilities utilize mechanical processes like shredding, screening, and sorting to segregate recyclables (metals, plastics, paper) from organic material and other nonrecyclables. While public funding supports these plants, private entities manage them through complex, long-term concession contracts. This structure restricts access to crucial data on the sale prices of the byproducts generated during MBT. Publicly available information on relevant company and administration websites is typically absent, hindering transparency surrounding byproduct revenue. This study addresses this gap by analyzing 2012’s available data on revenues obtained from byproduct sales following mechanical treatment at MBT plants within the Valencian Community and comparing them with Spanish national data. This research revealed a significant finding—the statistical distribution of average prices obtained from Ecoembes auctions in the Valencian Community mirrored the corresponding distribution for prices calculated from auctions conducted in other Spanish regions. This suggests a potential uniformity in byproduct pricing across the country. It has also been found that none of the analyzed price distributions exhibited a normal (Gaussian) distribution. The findings also highlight the need for alternative pricing models that move beyond simple averages and account for regional variations and outliers. As actual prices are not available after 2012, this lack of transparency poses a challenge in comprehensively evaluating the economic viability of MBT plants. Furthermore, it raises concerns regarding whether the revenue generated from byproduct sales reflects fair market value. Limited public access to this information can potentially indicate conflicts of interest or inefficiencies within the waste management system.

Abstract Conventional spouted beds have been extensively used in many real-life applications but are not suited for all types of materials, especially fine particles, which require internal devices to improve their motion in the spouted bed. However, unlike conventional spouted beds, there are almost no mechanistic or empirical models available for the design of spouted beds with internals. Given the availability of an extensive but not experimentally designed database, the main purpose of this study is to present an analysis of neural networks and empirical models in terms of their suitability to fit and predict average cycle times in conical spouted beds with and without draft tubes. The parameters investigated are particle size, density, contactor angle, gas inlet diameter, static bed height, and draft tube features. Although the amount of information is always a key factor when fitting models, the size of the database used in this study strongly affects the fitting performance of empirical models, whereas artificial neural networks are more influenced by how the data are scaled. Results of model verification show that both techniques are suitable for predicting average cycle times for data outside the range covered by the database.

Five years after the efficiency tests of the European COST ES0601 project (known as “HOME”) new tests are planned with the use of a new benchmark dataset. New tests are needed for three reasons: i) Several homogenization methods have newer versions since HOME, while some other methods were not tested by HOME; ii) The HOME benchmark represented only one climatic region (i.e. the central-western European climate) and a not very large selection of inhomogeneity problems; and iii) The number of networks in the HOME benchmark was small, and thus certain kinds of results with them have large statistical uncertainty. For all these reasons the representativeness of HOME results is limited. The new tests will be performed by researchers of the Centre for Climate Change of the University Rovira i Virgili and those of the Spanish Meteorological Agency (AEMET) with the support of a Spanish national project. We will develop and use a much larger benchmark dataset than the HOME benchmark, but we will test automatic methods only, thus the amount of the required work remains feasible. Primarily, the openly accessible automatic methods will be tested, which do not need the direct collaboration of the method developers. However, we intend to keep contact with the developers in order to test the best versions of the methods with the best possible parameterizations . Until the autumn of 2016 we will be accepting newly developed methods and versions for testing. In the development of the new benchmark, we will build on the knowledge gathered before the creation of HOME benchmark, but we aim to create an even more realistic benchmark including various segments representing particular climatic regions and inhomogeneity problems. For instance, the new benchmark will consider that a) The frequency of breaks of detectable size is generally much higher for temperature series than for precipitation series; b) The annual cycle of biases depends both on the examined variable and the geographical region; c) The frequent presence of short-term, platform-shaped inhomogeneities in observed temperature series. The efficiencies will be evaluated with the residual root mean square error of monthly and annual values in homogenized series, as well as with the residual trend bias errors for individual time series and network mean trends. Presentación realizada en: 10th EUMETNET Data Management Workshop celebrado en St. Gallen, Suiza, del 28 al 30 de octubre de 2015.

The utilisation of thermoelectric technology as a heat pump in heating applications necessitates comprehensive investigation. The scalable nature of thermoelectric technology enables its operation at elevated temperatures without the requirement of refrigerants. In this work, an accurate computational model that can simulate one- and two-stage thermoelectric heat pumps is developed. This model uses the electric-thermal analogy and the finite difference method, including the thermoelectric effects, temperature dependent properties, thermal contact resistances and all heat exchangers, even the intermediate heat exchanger in the case of a two-stage configuration. Moreover, the model has been experimentally validated by built and tested prototypes, being the first time that a two-stage thermoelectric heat pump model is experimentally validated. The discrepancy between the simulated and experimental results is below the ± 10 % for , ± 8 % for generated heat and temperature lift in the airflow, and less than the ± 6 % for consumed power. Additonally, the model simulates real tendencies under different operating conditions, proving the reliability of the developed thermoelectric heat pump model. Finally, the model is used to optimise a thermoelectric system combining one- and two-stage thermoelectric heat pumps, and hybridising them with electric resistances. An airflow of 16.5 m3/h is heated from 25 °C to 160 °C, achieving a maximum of 1.21. Lastly, the importance of considering the thermal resistances of the heat exchangers is computationally modelled and demonstrated. Not taking them into account would overestimate the performance of the TEHP system by more than the 7 %. The authors would like to acknowledge the support of the grant TED2021-130071A-I00 funded by MCIN/AEI/10.13039/501100011033 and, as appropriate, by 'European Union Next Generation EU/PRTR', as well as the Government of Navarre, as part of the 'Grants to SINAI agents for the realization of collaborative R&D projects' under the PC066-067-068 FlexORCStorage. Open access funding provided by Universidad Pública de Navarra.

Исследование ландшафтов всегда было традиционным научным направлением географии. В России подобная направленность исследований остаётся актуальной, несмотря на то, что термины «геоэкология» и «ландшафтная экология» сегодня более распространены в англоязычном научном сообществе. Наш краткий обзор показывает значительное ускорение антропогенных ландшафтных изменений в Европе, Центральной Азии и азиатской части России за последние пять десятилетий. Ландшафтные исследования в антропоцене должны быть направлены на достижение и сохранение устойчивости ландшафта при его высокой производительности, что включает в себя прекращение деградации ландшафтов, развитие культурных и сохранение природных ландшафтов. Чистая вода и чистый воздух, плодородные и здоровые почвы для производства продуктов питания и других экосистемных услуг, а также биологически разнообразная зеленая среда являются атрибутами ландшафтов, обеспечивающих выживание и благополучие населения. Дисциплинарные и междисциплинарные исследования должны генерировать знания, инновации и правила принятия действенных решений. Генерация знаний в глобализованном мире основана на сборе больших массивов данных и моделировании сценариев. Международные длительные полевые опыты и системы агроэкологического мониторинга будут предоставлять данные для экосистемных моделей и систем поддержки принимаемых решений. Landscape research has been a traditional scientific discipline of geography. This is still the case in Russia, whilst the terms geo-ecology and landscape ecology have become established in the English speaking scientific community. Our short review reveals huge and accelerating anthropogenic landscape transformations in Europe, Central Asia and Asian Russia since the end the 1960s. Landscape research in the Anthropocene has to focus on achieving landscape sustainability at high productivity. This includes halting landscape degradation, developing cultural landscapes, and maintaining semi-natural landscapes. Clean water and air, fertile and healthy soils for food and other ecosystem services and a green and bio-diverse environment are attributes of landscapes for the survival and well-being of humans. Research has to generate knowledge, innovations and decision rules by disciplinary, interdisciplinary and trans-disciplinary work. Knowledge generation in a globalized world is based on big data gathering and scenario modelling. International long-term experiments and agri-environmental monitoring systems will deliver data for ecosystem models and decision support systems.

Abstract New techniques for emissions reduction and energy efficiency are important challenges of the steel industry. Although great advantages have been reached in these fields, there are still new opportunities. One of them is the possible development of systems to recover energy from slags. The recent policies that encourage the use of renewable and alternative energies determine a favorable scenario for the development of new techniques of heat recovering. In this context, this article presents a new heat recuperation system for the slags produced in the factories of Arcelor–Mittal in Asturias (Spain) and study in detail the design of an innovative slags heat exchanger. To adjust its performance and to determine the influence of the geometric and flow design parameters, the heat exchanger has been simulated using numerical analysis software (CFD).

[ES]Se ha elaborado una nueva base de datos de precipitaciones medias mensuales y temperaturas máximas y mínimas medias mensuales, con la que se han analizado los datos de 142 estaciones meteorológicas obtenidos de la Agencia Estatal de Meteorología (AEMET) para el periodo (1989-2018). En este estudio se presentan los resultados de diferentes pruebas de homogeneización y relleno de 134, 172 y 176 series de temperaturas y precipitaciones provenientes de las estaciones ubicadas en la región de Extremadura. Para ello, se realizó un primer control de calidad de los datos cumpliendo con los requisitos de la Organización Meteorológica Mundial (OMM) y las recomendaciones indicadas por el Real Instituto Meteorológico de los Países Bajos (KNMI). Posteriormente se llevó a cabo la homogeneización de las series utilizando el software Climatol, en el que se han implementado diferentes funciones que permiten depurar los datos a través de un análisis de los valores atípicos y de la homogeneidad, así como la completación de las lagunas de las series. Los análisis confirman la obtención de unos niveles de depuración de los datos muy altos, confiables y de buena calidad; obteniendo así una nueva base de datos para posteriores estudios climáticos. [EN]A new database of monthly average rainfall and monthly average maximum and minimum temperatures has been developed, with which data from 142 weather stations obtained from the Agencia Estatal de Meteorología (AEMET) for the period (1989-2018) have been analysed. This study presents the results of different homogenisation and backfilling tests of 134, 172 and 176 temperature and precipitation series from stations located in the region of Extremadura. For this purpose, a first quality control of the data was carried out in compliance with the requirements of the World Meteorological Organisation (WMO) and the recommendations indicated by the Royal Netherlands Meteorological Institute (KNMI). Subsequently, the series were homogenised using Climatol software, in which different functions have been implemented to clean the data through an analysis of outliers and homogeneity, as well as filling in the gaps in the series. The analyses confirm the achievement of very high, reliable and good quality data cleaning levels, thus obtaining a new database for further climate studies. Esta investigación fue financiada por la Junta de Extremadura y el Fondo Europeo de Desarrollo Regional (FEDER) a través de la ayuda al grupo de investigación Alcántara (TIC008), GR21006, y el Proyecto IB18001 “Análisis y modelización del impacto del cambio climático sobre la distribución de zonas vitícolas en Extremadura”. Ponencia presentada en: XII Congreso de la Asociación Española de Climatología celebrado en Santiago de Compostela entre el 19 y el 21 de octubre de 2022.