Portal de Periódicos da CAPES

Towards a standardization of biomethane potential tests

2016; Pergamon Press; Volume: 74; Issue: 11 Linguagem: Inglês

10.2166/wst.2016.336

1996-9732

Christof Holliger, M. M. Alves, Diana Andrade, İrini Angelidaki, Sergi Astals, Urs Baier, Claire Bougrier, Pierre Buffière, Marta Carballa, Vinnie de Wilde, Florian Ebertseder, Belén Fernández, E. Ficara, Ioannis A. Fotidis, Jean‐Claude Frigon, Hélène Fruteau de Laclos, Dara S.M. Ghasimi, Gabrielle Hack, Mathias Hartel, J. Heerenklage, Ilona Sárvári Horváth, Pavel Jeníček, Konrad Koch, Judith Krautwald, Javier Lizasoain, Jing Liu, Lona Mosberger, Mihaela Nistor, Hans Oechsner, João Vítor Oliveira, M. P. Paterson, André Pauss, Sébastien Pommier, I. Porqueddu, F. Raposo, Thierry Ribeiro, Florian Rüsch Pfund, Sten Strömberg, Michel Torrijos, M.H.A. van Eekert, Jules B. van Lier, Harald Wedwitschka, Isabella Wierinck,

Carbon Dioxide Capture Technologies

Production of biogas from different organic materials is a most interesting source of renewable energy. The biomethane potential (BMP) of these materials has to be determined to get insight in design parameters for anaerobic digesters. Although several norms and guidelines for BMP tests exist, inter-laboratory tests regularly show high variability of BMPs for the same substrate. A workshop was held in June 2015, in Leysin, Switzerland, with over 40 attendees from 30 laboratories around the world, to agree on common solutions to the conundrum of inconsistent BMP test results. This paper presents the consensus of the intense roundtable discussions and cross-comparison of methodologies used in respective laboratories. Compulsory elements for the validation of BMP results were defined. They include the minimal number of replicates, the request to carry out blank and positive control assays, a criterion for the test duration, details on BMP calculation, and last but not least criteria for rejection of the BMP tests. Finally, recommendations on items that strongly influence the outcome of BMP tests such as inoculum characteristics, substrate preparation, test setup, and data analysis are presented to increase the probability of obtaining validated and reproducible results.