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Abstract This paper aims to investigate sustainable waste management solutions for the city of Rio de Janeiro in Brazil, based on a life cycle approach. The Life Cycle Assessment (LCA) was performed by using the LCA-IWM methodology. The model was adapted to the Brazilian solid waste context and to the local characteristics, including waste composition, electricity mix and regulations. The annual amount of waste generated was the functional unit adopted. Eight municipal solid waste management strategies were evaluated. Scenarios including mixed waste collection and source separated collection as well as materials recovery and energy from waste were investigated. Scenarios were ranked based on the LCA results. Sensitivity analysis was carried out by varying the electricity mix. The results indicate that the current situation of municipal solid waste (MSW) in Rio de Janeiro presents the worst performance in terms of aggregated environmental burdens, indicating the urgency for implement new strategies toward a more environmentally friendly and sustainable MSW management system. It is noted that the better LCA performances were obtained in scenarios with high separately collection rates. Among them, the scenario based on recyclables recovery and anaerobic digestion shows to be a promising strategy to improve environmental sustainability. Sensitivity analysis demonstrates that the ranking of scenarios was not affected by changes in the electricity mix. From the results, the investment in source separated waste collection and materials recovery is the most environmentally friendly MSW strategy for Rio de Janeiro. In addition, scenarios with an emphasis in materials recovery presented higher environmental benefits than the alternatives focused on energy generation.

Abstract Electricity markets in Europe become increasingly interconnected due to new grid connections and market coupling regulations. This paper examines the interdependencies between the Swiss electricity market and those of neighbouring countries. The Swiss market serves as a good example for a smaller electricity market which is increasingly affected by developments in the large neighbouring countries. To study these cross-border effects, especially those on Swiss electricity prices, we apply two different methodologies, an econometric and a Nash-Cournot equilibrium model. The analyses show that the Swiss electricity price correlates strongly with the German electricity price in the summer, but tends to follow the French electricity price in the winter. Another finding is that gas prices and the electricity load of neighbouring countries have a significant influence on prices. In particular, the load of France and Italy is driving up Swiss prices in the winter, while the German electricity demand and renewable energy generation have a larger influence on Swiss prices in the summer.

Accelerators for heavy-ion inertial fusion energy (HIF) have an economic incentive to fit beam tubes tightly to beams, putting them at risk from electron clouds produced by emission of electrons and gas from walls. Theory and PIC simulations suggest that the electrons will be radially trapped in the /spl ges/1 kV ion-beam potential. We are beginning studies on the High-Current Experiment (HCX) with unique capabilities to characterize electron production and trapping, the effects on ion beams, and mitigation techniques. We are measuring the flux of electrons and gas evolved from a target, whose angle to the beam can be varied between 78/spl deg/ and 88/spl deg/ from normal incidence. Quadrupole magnets are operating with a variety of internal charged particle diagnostics to measure the beam halo loss, net charge, electron ionization rate, and gas density.

We study the role of technology subsidies in climate policies, using a simple dynamic equilibrium model with learning-by-doing. The optimal subsidy rate of a carbon-free technology is high when the technology is first adopted, but falls significantly over the next decades. However, the efficiency costs of uniform instead of optimal subsidies, may be low if there are introduction or expansion constraints for a new technology. Finally, supporting existing energy technologies only, may lead to technology lock-in, and the impacts of lock-in increase with the learning potential of new technologies as well as the possibilities for early entry and thight carbon constraints.

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.

In the past decade, inverter-integrated energy sources have experienced rapid growth, which leads to operating challenges associated with reduced system inertia and intermittent power generation, which can cause instability and performance issues of the power system. Improved control schemes for inverters are necessary to ensure the stability and resilience of the power system. Grid-forming inverters dampen frequency fluctuations in the power system, while grid-following inverters can aggravate frequency problems with increased penetration. This paper aims at reviewing the role of grid-forming inverters in the power system, including their topology, control strategies, challenges, sizing, and location. In order to facilitate continued research in this field, a comprehensive literature review and classification of the studies are conducted, followed by research gaps and suggestions for future studies.

Considerando-se a preocupação crescente com a toxicidade dos efluentes, pela presença de metais e a ocorrência de novos poluentes orgânicos, esse estudo aplicou o Processo Oxidativo Avançado (POA) de fotoeletrooxidação (FEO) como polimento para o efluente após o processo convencional de tratamento de efluentes da indústria metalomecânica, que, muitas vezes, não remove, satisfatoriamente, metais e aditivos orgânicos. A FEO associou, à degradação de aditivos orgânicos, a remoção do níquel. Foram avaliados efluentes sintéticos com composição similar a efluentes do processo de eletrodeposição de níquel contendo aditivos. Empregando o ânodo de Ti revestido com 70%TiO2/30%RuO2 sob incidência de radiação UV de uma lâmpada de vapor de mercúrio de 250 W e um cátodo de aço inox, 2,5 L de efluente foram tratados em um reator de 1,6 L, com vazão de recirculação de 1 L.min-1. Aplicando diferentes densidades de corrente, observou-se redução da DQO de até 83% e remoção de Ni acima de 90%. Os ensaios de citotoxicidade indicaram que a FEO não gerou intermediários mais tóxicos, pois não ocorreu aumento do efeito tóxico na comparação das soluções antes e após a FEO.

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.