4.8 Article

A Life Cycle Analysis on a Bio-DME production system considering the species of biomass feedstock in Japan and Papua New Guinea

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APPLIED ENERGY
卷 87, 期 1, 页码 58-67

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ELSEVIER SCI LTD
DOI: 10.1016/j.apenergy.2009.08.030

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Bio-DME (Biomass Di-methyl Ether); LCA methodology; Monte Carlo simulation; The regression analysis

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This paper describes the performance and/or CO2 intensities of a Bio-DME (Biomass Di-methyl Ether) production system, considering the differences of biomass feedstock. In the past LCA studies on an energy chain model, there is little knowledge on the differences of biomass feedstock and/or available condition. Thus, in this paper, we selected Papua New Guinea (PNG) which has good potential for supply of an energy crop (a short rotation forestry), and Japan where wood remnants are available, as model areas. Also, we referred to 9 species of biomass feedstock of PNG, and to 8 species in Japan. The system boundary on our LCA consists of (1) the pre-treatment process, (2) the energy conversion process, and (3) the fuel transportation process. Especially, since the pre-treatment process has uncertainties related to the moisture content of biomass feedstock, as well as the distance from the cultivation site to the energy plant, we considered them by the Monte Carlo simulation. Next, we executed the process design of the Bio-DME production system based on the basic experimental results of pyrolysis and char gasification reactions. Due to these experiments, the gas components of pyrolysis and the gasification rate under H2O (Steam) and CO2 were obtained. Also, we designed the pressurized fluid-bed gasification process. In a liquefaction process, that is, a synthesis process of DME, the result based on an equilibrium constant was used. In the proposed system, a steam turbine for an auxiliary power was assumed to be equipped, too. The energy efficiencies are 39.0-56.8 LHV-%, depending upon the biomass species. Consequently, CO2 intensities in the whole system were 16.3-47.2 g-CO2/MJ-DME in the Japan case, and 12.2-36.7 g-CO2/MJ-DME in the PNG one, respectively. Finally, using the results Of CO2 intensities and energy efficiencies, we obtained the regression equations as parameters of hydrogen content and heating value of a feedstock. These equations will be extremely significant when we install the BTL (biomass-to-liquid, ex. Bio-DME) energy system in the near future, in order to mitigate CO2 emissions effectively, and to estimate the energy's efficiency. (C) 2009 Elsevier Ltd. All rights reserved.

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