Energy and Renewable Energies
M. Soleymani; Alireza Keyhani; Mahmood Omid
Abstract
Introduction Replacing fossil fuels with renewable and environmentally friendly fuels is so essential, due to issues such as climate change, increasing fossil fuels prices, energy security and limitations of fossil fuels resources. Alternatives are wind energy, solar energy, geothermal energy, hydropower, ...
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Introduction Replacing fossil fuels with renewable and environmentally friendly fuels is so essential, due to issues such as climate change, increasing fossil fuels prices, energy security and limitations of fossil fuels resources. Alternatives are wind energy, solar energy, geothermal energy, hydropower, biomass and biofuel. Currently, ethanol produced from sugarcane in Brazil or from corn in USA is the most dominant bioufuel in the world. However there is no comprehensive agreement on the environmental benefits of alternative fuels including ethanol. The aim of this study was to conduct a LCA (Life Cycle Assessment) on ethanol produced from sugarcane molasses in Iran and also to compare its environmental impacts with a conventional fossil fuel. Materials and Methods All required data was obtained from Sugarcane Agro-industry and ancillary Industry Development, Karoon Agro-Industry and also from recorded databases. Economic allocation was chosen to allocate emissions between the main product and the byproducts. Also, Simapro software was applied to model and evaluate the life cycle environmental effects in the life cycle of sugarcane molasses based ethanol (from cultivating sugarcane to burn ethanol into the engine). Two different scenarios of ethanol production (existing system and modified system) were considered and the environmental impacts of these two systems were compared with each other. Finally the environmental impacts of whole life cycle of molasses based ethanol were compared to that’s of diesel as a conventional fossil fuel. Results and Discussion Life cycle inventory results showed that electricity, P2O5 and urea respectively had the most negative environmental impacts through the life cycle of molasses based ethanol. Replacing the fossil fuel originated electricity with electricity from renewable resources can have a significant effect on reducing the amount of these negative impacts. Also, producing electricity in the nearest location to the consumption sites will reduce the power transmission losses and consequently reduce these impacts. Since the major share of electricity is used for pumping water to the field, better management of water consumption is so essential. According to the results, in case of emissions, there was significant difference between diesel fuel and sugarcane molasses ethanol in the base scenario. But by modifying the production system and using bagass to produce biogas or electricity (scenario 2), the environmental impacts of life cycle of sugarcane molasses based ethanol would reduce by 10%. Even now, the amount of greenhouse gas (GHG) emission of ethanol is 60% lower than these emissions of diesel fuel. This reduction will reach 70% if wasted bagass in ordinary production system is used to produce biogas and electricity. Comparing with diesel fuel, Molasses based ethanol had less negative impacts on impact categories such as Respiration Inorganics, Climate Change, Acidification/Eutrofication, and fossil fuels and more negative impacts on categories such as Land Use and Carcinogens, only because of using land and also using herbicides and pesticides to cultivate sugarcane. Greenhouse gas emission in the life cycle of one mega joule molasses based ethanol, estimated by Biograce model, is respectively 69, 70 and 60 percent lower than that of gasoline, diesel and natural gas. Due to undeveloped industries to process sugarcane and its byproducts in Iran, studies on the production of ethanol from molasses or electricity from bagass are in the area of waste management. Therefore, in these cases, even if it there was suitable energy or environmental indicato, continuing the production of these products is justified according to other side issues including environmental benefits and employment. Conclusion In terms of environmental aspects, in the current situation there are no significant differences between ethanol and diesel. But if bagass is used to generate electricity, the environmental impact of ethanol production will reach reduced by 10%. Greenhouse gas emissions of ethanol is 60% lower than that of from diesel and this amount will be 70%, if wasted bagass is used to produce biogas or electricity. It is possible to obtain more environmental benefits by applying appropriate management strategies in ethanol production system (such as producing value added products from bagass or other waste materials). Since sugar is the main product in sugarcane industry in Iran and approximately all other byproducts are wasted, to prevent the loss of this valuable byproduct, producing ethanol from molasses, even if in current situation and with current production system is acceptable.
Soil Genesis and Classification
R. Taghizadeh-Mehrjardi; F. Sarmadian; M. Omid; N. Toomanian; M.J. Rousta; M.H. Rahimian
Volume 37, Issue 2 , March 2015, , Pages 101-115
Abstract
In recent years, there has been a great development in the digital soil mapping which has led to production of maps for countries and the continents. Although many studies have been conducted all over the world, few Iranian soil scientists have shown interests in digital mapping. Therefore, in the present ...
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In recent years, there has been a great development in the digital soil mapping which has led to production of maps for countries and the continents. Although many studies have been conducted all over the world, few Iranian soil scientists have shown interests in digital mapping. Therefore, in the present research, different data mining techniques (i.e. regression logistic, artificial neural network, genetic algorithm, decision tree and discriminant analysis) were applied to spatial prediction of great group soils in the area covering of 72000 ha in Ardakan. In this area, by using the conditioned Latin hypercube sampling method, location of 187 soil profiles was selected, which was then described, sampled, analyzed and allocated in taxonomic classes according to soil taxonomy of America. Auxiliary data used in this study to represent predictive soil forming factors were terrain attributes, Landsat 7 ETM+ data and a geomorphologic surfaces map. Results showed that decision tree model had the highest accuracy while it could increase the accuracy of prediction up to 44% in comparison with discriminant analysis technique. Results also indicated using the taxonomic distances led to improving the overall accuracy of decision tree up to 3%. Results confirmed capability of decision tree, artificial neural networks, genetic algorithm, logistic regression, and discriminant analysis with 70%, 65%, 65%, 55%, and 47% accuracy, respectively. Moreover, results showed that decision tree model could predict soil classes in sub-great group with the overall accuracy of 84.2%.
