Sustainable development aspects of biodiesel production and application in Brazil

Concerns about climate change effects have prompted many countries to search for solutions to reduce fossil fuel consumption. In the last few years biodiesel production has gained world attention, as it is seen as a sustainable and renewable energy source. Biodiesel is a natural substitute for diesel oil, and can be obtained from different oleaginous plants. However, there are worries about devastation of forests and biodiversity-rich areas to produce biodiesel. Even considering biodiesel as a promising solution, the impacts of its production must be carefully evaluated. This work examines the Brazilian scenario for biodiesel production and use as an automotive fuel. Native and adapted oleaginous in many Brazilian regions and their potentiality for biodiesel production are presented. Experimental results of hydrocarbons (HC), carbon monoxide (CO), and carbon dioxide (CO2) emissions from a diesel power generator fuelled by blends of diesel oil and castor oil or soybean biodiesel are also presented

Further developments on biodiesel production and applications in brazil

Environmental concerns have motivated many countries to search for solutions to reduce fossil fuel consumption. In the last few years, biodiesel has attracted attention as a possible sustainable and renewable energy source to substitute diesel oil. Biodiesel can be produced from different oleaginous plants, but there are worries about food competition and forests and biodiversity-rich areas devastation to produce biodiesel. Even considering biodiesel as a promising solution, its production impacts must be carefully evaluated. This work examines the Brazilian prospects for biodiesel production and use as an engine fuel for automotive propulsion and power generation. The potential for biodiesel production of many native and adapted oleaginous plants in Brazilian territory is discussed. Experimental results of hydrocarbons, carbon monoxide, and carbon dioxide emis-sions from a diesel power generator fuelled by blends of diesel oil and castor oil or soybean biodiesel are also presented

Efeito de silagens de milho, de sorgo e de capim elefante no desempenho de novilhos confinados.

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ALDEHYDE EMISSIONS FROM A STATIONARY DIESEL ENGINE OPERATING WITH CASTOR OIL BIODIESEL – DIESEL OIL BLENDS

The presence of aldehyde in the exhaust gas of a stationary, direct injection, compression ignition engine operating with castor oil biodiesel/diesel oil blends (B5, B10, B20 and B35) is analyzed. The diesel engine was operated with constant speed of 1800 rev/min and load of 37.5 kW. The gas sample was collected directly from the exhaust. Aldehydes were identified and quantified using gas chromatography (GC) with flame ionization detector analyzer (FID). Acetaldehyde presented higher exhaust concentration than formaldehyde for all fuel blends tested. In general, the exhaust aldehyde levels were very low and did not present significant differences between the fuel blends tested

A Dynamic Model of Cascades on Random Networks with a Threshold Rule

Cascades on random networks are typically analyzed by assuming they map onto percolation processes and then are solved using generating function formulations. This approach assumes that the network is infinite and weakly connected, yet furthermore approximates a dynamic cascading process as a static percolation event. In this paper we propose a dynamic Markov model formulation that assumes a finite network with arbitrary average nodal degree. We apply it to the case where cascades follow a threshold rule, that is, that a node will change state ("flip") only if a fraction, exceeding a given threshold, of its neighbors has changed state previously. The corresponding state transition matrix, recalculated after each step, records the probability that a node of degree k has i flipped neighbors after j steps in the cascade's evolution. This theoretical model reproduces a number of behaviors observed in simulations but not yet reported in the literature. These include the ability to predict cascades in a domain previously predicted to forbid cascades without assuming that the network is locally tree-like, and, due to the dynamic nature of the model, a "near death" behavior in which cascades initially appear about to die but later explode. Cascades in the "no cascades" region require a sufficiently large seed of initially flipped nodes whose size scales with the size of the network or else the cascade will die out. Our theory also predicts the well known properties of cascades, for instance that a single node seed can start a global cascade in the appropriate regime regardless of the (finite) size of the network. The theory and simulations developed here are compared with a foundational paper by Watts which used generating function theory.Comment: Rev 1: Added citation to prior work by Gleeson and Cahalane. Revised abstract to sui