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The gasification of biomass and waste is a potentially high efficiency process for energy generation. However, the appropriate cleaning of the produced fuel gas is a major issue, in particular for tar removal. This study investigates the performance of three new-generation activated carbons, which are able to adsorb a wide spectrum of tars at high temperature, from 750 °C up to 900 °C. For this purpose, a laboratory-scale hot gas filtration apparatus was designed and set-up. Experimental tests were carried out with naphthalene as the reference tar compound. The selected activated carbons were tested under different conditions of temperature, test duration and naphthalene concentration. The procedure allows evaluating the contributions of adsorption and cracking phenomena on the overall tar removal efficiency. Complete naphthalene removal was obtained with two of the selected activated carbons, at 850 °C and 900 °C respectively. Simultaneously, a partial reforming of adsorbed naphthalene was observed, and molecular hydrogen was detected in the gas phase. Results were correlated to the differences in porosimetry and chemical surface of the selected activated carbons, as well as to those highlighted by Scanning Electronic Microscopy and X-ray analyses. Finally, a procedure for activated carbon regeneration by carbon dioxide is reported, together with results from preliminary tests. [ABSTRACT FROM AUTHOR]

Activated carbons are efficient catalysts for tar cracking, suitable for hot cleaning of the syngas produced during biomass- and waste-to-energy gasification processes. This study investigates the conversion of naphthalene, utilised as reference for tar compounds, when catalysed by a coal-derived activated carbon. The attention focuses on the influence of the operating temperature, in the range 750–900 °C, and the size of selected activated carbon, which has been used under form of pellets, granules and powders. The conversion efficiency improves when the temperature raised from 750 °C to 900 °C (from 79% to 99%, for the pellets), and when the catalyst size reduced from pellets to powders (from 79% to 97%, at 750 °C). The diffusional resistance in the catalyst particles has been then quantified in terms of Thiele modulus and internal effectiveness factor. A gradual reduction of catalyst surface area has been also observed for longer tests, due to the progressive deposition of soot from naphthalene decomposition over and inside the porous structure of the activated carbon. The carbon content of these deposits has been quantified, showing larger percentages on the surface of granules and powders. • Naphthalene is used as reference compound for tars in the syngas from gasification. • Operating temperature and catalyst size have been investigated. • Results indicate a pore diffusion resistance in coarser particles. • Catalyst powders have limited pore diffusion resistance and do not lead to high pressure drops. • Progressive reduction of the catalytic surface area is related to soot deposition. [ABSTRACT FROM AUTHOR]

The study reviews and compares the most utilised techniques to obtain high quality biomethane by upgrading biogas from anaerobic digestion of the organic fraction of municipal solid waste. Environmental and economic aspects of membrane separation, water scrubbing, chemical absorption with amine solvent, and pressure swing adsorption have been quantified in a life cycle perspective. An attributional environmental Life Cycle Assessment has been implemented with the support of a Material Flow Analysis and in combination with a complementary environmental Life Cycle Costing. The analyses are based on data largely obtained from Italian existing plants but they can be generalised to the whole European Union, as demonstrated by a companion sensitivity analysis. The comparative assessment of the results indicates all the examined options as fully sustainable, also identifying the "win-win" situations. In particular, the membrane separation technique appears to have the best performances, even though in some cases with limited differences. With reference to base case scenarios, this technique shows better results for the respiratory inorganics potential (up to 34%, i.e. up to 328 kg PM2.5eq /y), global warming potential (up to 7%, i.e. up to 344 t CO2eq /y), and non-renewable energy potential (up to 12%, i.e. up to 6400 GJ primary /y) as well as for life cycle costs (up to 3.4%, i.e. about 60 k€/y). The performances of the examined techniques appear anyway dependent on site-specific conditions (such as the injection pressure in the gas grid or the existence/amount of local economic incentives) and commercial strategies for the market of interest. • Environmental and economic impacts of biogas upgrading units have been assessed. • Life Cycle Assessment and Life Cycle Costing have been used as analytical tools. • All examined techniques imply a reduction of environmental and economic impacts. • Win-win situations indicate some advantages for membrane separation technique. • Site-specific conditions and market strategies affect upgrading technique selection. [ABSTRACT FROM AUTHOR]

Abstract: The aim of our search is the analysis of aftershock temporal series following a mainshock with magnitude M ≥7.0. Investigating aftershock behavior may find the key to explain better the mechanism of seismicity as a whole. In particular, the purpose of this work is to highlight some methodological aspects related to the observation of possible anomalies in the temporal decay. The data concerning the temporal series, checked according to completeness criteria, come from the NEIC-USGS data bank. Here we carefully analyze the New Guinea 29 April 1996 seismic sequence. The observed temporal series of the shocks per day can be considered as a sum of a deterministic contribution (the aftershock decay power law, n(t)= K·(t + c)−p + K 1) and of a stochastic contribution (the random fluctuations around a mean value represented by the above mentioned power law). If the decay can be modeled as a non-stationary Poissonian process where the intensity function is equal to n(t)= K·(t + c)−p + K 1, the number of aftershocks in a small time interval Δt is the mean value n(t)·Δt, with a standard deviation . [Copyright &y& Elsevier]