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Saving energy in greenhouses is an important issue for growers. Here, we present a method to minimize the total energy that is required to heat and cool a greenhouse. Using this method, the grower can define bounds for temperature, humidity, CO2 concentration, and the maximum amount of CO2 available. Given these settings, optimal control techniques can be used to minimize energy input. To do this, an existing greenhouse climate model for temperature and humidity was expanded to include a CO2 balance. Heating, cooling, the amount of natural ventilation, and the injection of industrial CO2 were used as control variables.Standard optimization settings were defined in order to compare the grower's strategy with the optimal solution. This optimization resulted in a theoretical 47% reduction in heating, 15% reduction in cooling, and 10% reduction in CO2 injection for the year 2012. The optimal control does not need to maintain a minimum pipe temperature, in contrast to current practice. When the minimum pipe temperature strategy of the grower was implemented, heating and CO2 were reduced by 28% and 10% respectively.We also analyzed the effect of different bounds on optimal energy input. We found that as more freedom is given to the climate variables, the higher the potential energy savings. However, in practice the grower is in charge of defining the bounds. Thus, the potential energy savings critically depend on the choice of these bounds. This effect was analyzed by varying the bounds. However, because the effect can be demonstrated to the grower, the outcome has value to the grower with respect to decision making, an option that is not currently available in practice today.

AbstractThe surface oxygen exchange on oxides with high oxygen ion mobility is modelled with a two step reaction with adsorbed mono-atomic oxygen species as intermediate. Interpretation of the Po2 dependence of the exchange rates, following from this model, indicates that these adsorbed oxygen atoms are singly charged.For the stabilized δ-Bi2O3 solid electrolyte a good agreement has been found between the isotope exchange model and the electrochemical study of the oxygen exchange using gold electrodes. For the mixed La-Sr cobaltite perovskite a change in the surface exchange reaction is observed going from room temperature to 600°C. Indications are that above 450°C the bulk exchange is rate limiting with a (Po2)−1 dependence while below this temperature it is assumed that the dissociative adsorption is rate limiting with a (Po2)1/2 dependence.

Abstract For the option of “carbon capture and storage”, an integrated assessment in the form of a life cycle analysis and a cost assessment combined with a systematic comparison with renewable energies regarding future conditions in the power plant market for the situation in Germany is done. The calculations along the whole process chain show that CCS technologies emit per kWh more than generally assumed in clean-coal concepts (total CO2 reduction by 72–90% and total greenhouse gas reduction by 65–79%) and considerable more if compared with renewable electricity. Nevertheless, CCS could lead to a significant absolute reduction of GHG-emissions within the electricity supply system. Furthermore, depending on the growth rates and the market development, renewables could develop faster and could be in the long term cheaper than CCS based plants. Especially, in Germany, CCS as a climate protection option is phasing a specific problem as a huge amount of fossil power plant has to be substituted in the next 15 years where CCS technologies might be not yet available. For a considerable contribution of CCS to climate protection, the energy structure in Germany requires the integration of capture ready plants into the current renewal programs. If CCS retrofit technologies could be applied at least from 2020, this would strongly decrease the expected CO2 emissions and would give a chance to reach the climate protection goal of minus 80% including the renewed fossil-fired power plants.

A good process understanding is the foundation for process optimization, process monitoring, end-point detection, and estimation of the end-product quality. Performing good process measurements and the construction of process models will contribute to a better process understanding. To improve the process knowledge it is common to build process models. These models are often based on first principles such as kinetic rates or mass balances. These types of models are also known as hard or white models. White models are characterized by being generally applicable but often having only a reasonable fit to real process data. Other commonly used types of models are empirical or black-box models such as regression and neural nets. Black-box models are characterized by having a good data fit but they lack a chemically meaningful model interpretation. Alternative models are grey models, which are combinations of white models and black models. The aim of a grey model is to combine the advantages of both black-box models and white models. In a qualitative case study of monitoring industrial batches using near-infrared (NIR) spectroscopy, it is shown that grey models are a good tool for detecting batch-to-batch variations and an excellent tool for process diagnosis compared to common spectroscopic monitoring tools.

Plant-soil feedback (PSF) describes the process whereby plant species modify the soil environment, which subsequently impacts the growth of the same or another plant species. Our aim was to explore PSF by two maize varieties (a landrace and a hybrid variety) and three arbuscular mycorrhizal fungi (AMF) species (Funneliformis mosseae, Claroideoglomus etunicatum, Gigaspora margarita, and the mixture). We carried out a pot experiment with a conditioning and a feedback phase to determine PSF with different species of AMF and with a non-mycorrhizal control. Sterilized soil was conditioned separately by each variety, with or without AMF; in the feedback phase, each soil community was used to grow each in its "home" soil and in the "away" soil. Plant performance was assessed as shoot biomass, phosphorus (P) concentration and P content, and fungal performance was assessed as mycorrhizal colonization and hyphal length density. Both maize varieties were differentially influenced by AMF in the conditioning phase. In the feedback phase, PSF was generally negative for non-mycorrhizal plants or when plants were colonized by G. margarita, whereas PSF was positive in the other three AMF treatments. When plants were grown on home soil, hyphal length density was larger than on away soil. We conclude that different maize varieties can strengthen positive plant-soil feedback for themselves through beneficial mutualists for themselves, but not across the maize varieties.