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With the aim to fully exploit the by-products obtained after the industrial extraction of starch from sweet potatoes, a cascading approach was developed to extract high-value molecules, such as proteins and pectins, and to valorize the solid fraction, rich in starch and fibrous components. This fraction was used to prepare new biocomposites designed for food packaging applications. The sweet potato residue was added to poly(3-hydroxybutyrate-co-3-hydroxyvalerate) in various amounts up to 40 wt % by melt mixing, without any previous treatment. The composites are semicrystalline materials, characterized by thermal stability up to 260 °C. For the composites containing up to 10 wt % of residue, the tensile strength remains over 30 MPa and the strain stays over 3.2%. A homogeneous dispersion of the sweet potato waste into the bio-polymeric matrix was achieved but, despite the presence of hydrogen bond interactions between the components, a poor interfacial adhesion was detected. Considering the significant percentage of sweet potato waste used, the biocomposites obtained show a low economic and environmental impact, resulting in an interesting bio-alternative to the materials commonly used in the packaging industry. Thus, according to the principles of a circular economy, the preparation of the biocomposites closes the loop of the complete valorization of sweet potato products and by-products.

Public policy requires public support, which in turn implies a need to enable the public not just to understand policy but also to be engaged in its development. Where complex science and technology issues are involved in policy making, this takes time, so it is important to identify emerging issues of this type and prepare engagement plans. In our horizon scanning exercise, we used a modified Delphi technique. A wide group of people with interests in the science and policy interface (drawn from policy makers, policy adviser, practitioners, the private sector and academics) elicited a long list of emergent policy issues in which science and technology would feature strongly and which would also necessitate public engagement as policies are developed. This was then refined to a short list of top priorities for policy makers. Thirty issues were identified within broad areas of business and technology; energy and environment; government, politics and education; health, healthcare, population and aging; information, communication, infrastructure and transport; and public safety and national security.

The paper presents a preliminary technical-economic comparison between a 3 kV DC railway and the use of trains with on-board storage systems. Numerical simulations have been carried out on a real railway line, which presents an electrified section at 3 kV DC and a non-electrified section, currently covered by diesel-powered trains. Different types of ESS have been analyzed, implementing the models in Matlab/Simulink environment. A preparatory economic investigation has been carried out.

Biomass plays an important role in the world primary energy supplies, currently providing ∼14% of the world's primary energy needs and being the fourth largest contributor following coal, oil and natural gas. Over the past decade, domestic biomass heating has received more governmental and public supports than ever before in many developed countries, such as the UK. Although biomass combustion releases some combustion pollutants, biomass is renewable and produces little net CO 2 emissions to the atmosphere. Owing to the low sulphur and low nitrogen contents of many biomass materials, substituting biomass for fossil fuels, particularly coal, can reduce SO x and NO x emissions. This study investigated flue gas emissions, particularly carbon monoxide and nitrogen oxides, of a domestic biomass boiler under various operating conditions. The biomass boiler used in this study satisfies the current EU regulation (EN 303-05) on emissions of domestic biomass boilers. Emissions of the boiler had been measured not only under normal combustion conditions, but also under 'idle' combustion conditions when the boiler was not in but was ready for full operation. The experimental results are analysed and presented in this paper. Copyright The Author 2010. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org, Oxford University Press.

Abstract In this paper, a general mathematical model for the dynamic simulation of a single-effect LiBr/water absorption chiller is presented. The model is based on mass and energy balances applied to the internal components of the machine, and it accounts for the non-steady behaviour due to thermal and mass storage in the components. The validation of the mathematical model is performed through experimental data collected on a commercial small-capacity water-cooled unit. Due to the peculiar technology adopted in the real chiller, a special effort was made to identify the appropriate values of the main physical parameters. The validation of the model is based on the values of the water temperature at the outlet of the machine, as no measurement inside the machine was possible; anyway, a consistency analysis applied to the internal parameters is also presented. The agreement between experimental and simulated results is very good, both on a daily and on a seasonal basis.

Energy management within microgrids under the presence of large number of renewables such as photovoltaics is complicated due to uncertainties involved. Randomness in energy production and consumption make both the prediction and optimality of exchanges challenging. In this paper, we evaluate the impact of uncertainties on optimality of different robust energy exchange strategies. To address the problem, we present AIROBE, a data-driven system that uses machine-learning-based predictions of energy supply and demand as input to calculate robust energy exchange schedules using a multiband robust optimization approach to protect from deviations. AIROBE allows the decision maker to tradeoff robustness with stability of the system and energy costs. Our evaluation shows, how AIROBE can deal effectively with asymmetric deviations and how better prediction methods can reduce both the operational cost while at the same time may lead to increased operational stability of the system.