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The proposed special issue (SI) has invited submissions related to renewable energy, energy storage, power converters and electric drive systems for electrified transportation and smart grid applications [...]

Abstract Given the need to reduce the CO2 emissions coming from the manufacturing sector, it is important, for planning purposes, to know which countries and which manufacturing sub-sectors have the greatest potential for reducing energy use. Using data from the International Atomic Energy Agency and the United Nations Industrial Development Organization, the authors estimate trends in global decoupling of energy use and manufacturing value added, compare energy-use intensity in six country groups and estimate the potential for reducing energy use and CO2 emissions under two scenarios and compare selected sub-sector energy intensity and estimate the potential for reducing energy use CO2 emissions. The comparison of energy intensities across country groups and among countries suggests that there still remains significant potential to reduce energy use and associated CO2 emissions. The analysis of four sub-sectors in developing and transition economies also shows similar but varied potential for reducing energy use and associated CO2 emissions.

A mathematical model has been developed to predict fragmentation of particles under a wide range of pyrolysis and combustion conditions. The model is an upgrade of a previous one that took into account only fragmentation during the heat up and devolatilization stage. The model calculates the temperature and oxygen profiles within the particle, the evolution of internal porosity as a consequence of both devolatilization and carbon combustion, the mechanical stress caused by temperature gradients, and by volatiles-generated overpressure inside the particles. Eventually the model calculates the probability of rupture of the particle based on the Weibull (1939) theory. The model has been used to simulate heating of coal particles under inert conditions at different heating rates and temperatures showing good agreement with previous work. The model has been further used to simulate heating under oxidative conditions in order to highlight the role of combustion on fragmentation phenomena.

Shading the greenhouses is necessary in summer to reduce the solar radiation load. This however generates a considerable amount of thermal radiation heat load that needs to be removed via cooling systems. This study aimed to evaluate the effect of different shading configurations on the solar and thermal radiation in a greenhouse. Nets at four different locations were employed to shade the roof and side-walls of a polycarbonate, mechanically ventilated greenhouse. The spectral radiative properties of all these plastic materials were measured in short and long wave spectrum bands. The net solar and thermal radiations and air temperature were measured outside and inside two identical shaded and unshaded greenhouses. The results showed that external roof-shading is desirable, as it reduced the generated thermal radiation in the greenhouse by 21% and 15% during the day and night time, respectively and reduced the greenhouse air temperature during the day. The internal shading (roof and side walls) is undesirable, since it drastically increased the generated thermal radiation in the greenhouse by 147% and strongly increased the greenhouse air temperature during the day. Shading the side-walls is not recommended because it significantly reduces the transmitted solar radiation in the morning and afternoon (when the outside irradiance is low) and is useless at around noon when the outside irradiance is extremely high.

Abstract Off-grid systems based on PV and batteries are becoming a solution of great interest for rural electrification. Nevertheless, sizing these systems is not straightforward since it means matching unpredictable energy sources with uncertain demands while providing the best reliability and costs. In our opinion, the effect of users’ energy consumptions uncertainty on the sizing of these systems has not been appropriately investigated. This paper addresses this issue and analyzes the effect of load profile uncertainty on the off-grid PV systems optimum design. Specifically a novel sizing methodology has been introduced based on: (i) an effective approach of modelling rural energy needs; (ii) an innovative stochastic method which formulates different possible realistic daily load profiles for un-electrified rural areas; (iii) a PV-battery techno-economic analysis via steady-state simulation; (iv) the evaluation of the optimum system sizing via a numerical method based on net present cost and loss of load probability. Finally, the proposed methodology has been applied to find the optimum size of an off-grid PV system for a peri-urban area of Uganda. The results show that the optimum system configurations are significantly affected by load profiles; consequently an approach to identify the robust solution with regards the assumed uncertainty is proposed.

Abstract The combined production of electricity, heat and cold by a polygeneration system connected to a district heating and cooling network can provide high energy utilization efficiency. The inherent complexity of simultaneous production of different services and the high variability in the energy demand make combined cooling and heating systems performance highly dependent on the operational strategy. In this paper, an operational optimization method based on the moving average of real-time measurements of energy demands and ambient conditions is proposed. Real energy demand data from a district heating and cooling network close to Barcelona, Spain, are used to test the method. A complex polygeneration system is considered, consisting of an internal combustion engine, a double-effect absorption chiller, an electric chiller, a boiler and a cooling tower. A detailed modelling of the system is provided, considering partial load behavior of the components and ambient conditions effects. Results of the real-time optimal management are discussed and compared to traditional operational strategies and to the ideal optimal management achievable with perfectly accurate forecast of energy demands. Moreover, the optimal width of the window adopted for the moving average of real-time data is identified.

With an approach combining crop modelling and biotechnology to assess the performance of three durum wheat cultivars (Creso, Duilio, Simeto) in a climate change context, weather and agronomic datasets over the period 1973–2004 from two sites, Benatzu and Ussana (Southern Sardinia, Itay), were used and the model responses were interpreted considering the role of DREB genes in the genotype performance with a focus on drought conditions. The CERES-Wheat crop model was calibrated and validated for grain yield, earliness and kernel weight. Forty-eight synthetic scenarios were used: 6 scenarios with increasing maximum air temperature; 6 scenarios with decreasing rainfall; 36 scenarios combining increasing temperature and decreasing rainfall. The simulated effects on yields, anthesis and kernel weights resulted in yield reduction, increasing kernel weight, and shortened growth duration in both sites. Creso (late cultivar) was the most sensitive to simulated climate conditions. Simeto and Duilio (early cultivars) showed lower simulated yield reductions and a larger anticipation of anthesis date. Observed data showed the same responses for the three cultivars in both sites. The CERES-Wheat model proved to be effective in representing reality and can be used in crop breeding programs with a molecular approach aiming at developing molecular markers for the resistance to drought stress.

AbstractBACKGROUND: Inappropriate utilisation of biosolids may adversely impact agrosystem productivity. Here, we address the response of wheat (Triticum durum) to different doses (0, 40, 100, 200 and 300 t ha−1) of either municipal solid waste (MSW) compost or sewage sludge in a greenhouse pot experiment. Plant growth, heavy metal uptake, and antioxidant activity were considered.RESULTS: Biomass production of treated plants was significantly enhanced at 40 t ha−1 and 100 t ha−1 of MSW compost (+48% and +78% relative to the control, respectively). At the same doses of sewage sludge, the increase was only 18%. Higher doses of both biosolids restricted significantly the plant growth, in concomitance with the significant accumulation of heavy metals (Ni2+, Pb2+, Cu2+ and Zn2+), especially in leaves. Leaf activities of antioxidant enzymes (ascorbate peroxidase, glutathione reductase, catalase and superoxide dismutase) were unchanged at 40 t ha−1 MSW compost or sewage sludge, but were significantly stimulated at higher doses (200–300 t ha−1), together with higher leaf concentration of reduced glutathione.CONCLUSION: This preliminary study suggests that a MSW supply at moderate doses (100 t ha−1) could be highly beneficial for wheat productivity. Copyright © 2010 Society of Chemical Industry