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Argiz, L., Reyes, C., Belmonte, M., Franchi, O., Campo, R., Fra-Vazquez, A., et al. (2020). Assessment of a fast method to predict the biochemical methane potential based on biodegradable COD obtained by fractionation respirometric tests. J. Environ. Manage., 269, 9 pp.
Abstract: The biochemical methane potential test (BMP) is the most common analytical technique to predict the performance of anaerobic digesters. However, this assay is time-consuming (from 20 to over than 100 days) and consequently impractical when it is necessary to obtain a quick result. Several methods are available for faster BMP prediction but, unfortunately, there is still a lack of a clear alternative. Current aerobic tests underestimate the BMP of substrates since they only detect the easily biodegradable COD. In this context, the potential of COD fractionation respirometric assays, which allow the determination of the particulate slowly biodegradable fraction, was evaluated here as an alternative to early predict the BMP of substrates. Seven different origin waste streams were tested and the anaerobically biodegraded organic matter (CODmet) was compared with the different COD fractions. When considering adapted microorganisms, the appropriate operational conditions and the required biodegradation time, the differences between the CODmet, determined through BMP tests, and the biodegradable COD (CODb) obtained by respirometry, were not significant (CODmet (57.8026 +/- 21.2875) and CODb (55.6491 +/- 21.3417), t (5) = 0.189, p = 0.853). Therefore, results suggest that the BMP of a substrate might be early predicted from its CODb in only few hours. This methodology was validated by the performance of an inter-laboratory studyconsidering four additional substrates.
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Pabon-Pereira, C. P., Castanares, G., & van Lier, J. B. (2012). An OxiTop (R) protocol for screening plant material for its biochemical methane potential (BMP). Water Sci. Technol., 66(7), 1416–1423.
Abstract: A protocol was developed for determining the biochemical methane potential (BMP) of plant material using the OxiTop (R) system. NaOH pellets for CO2 absorption and different pretreatment methods were tested for their influence in the BMP test. The use of NaOH pellets in the headspace of the bottle negatively affected the stability of the test increasing the pH and inhibiting methanization. Sample comminution increased the biodegradability of plant samples. Our results clearly indicate the importance of test conditions during the assessment of anaerobic biodegradability of plant material, considering BMP differences as high as 44% were found. Guidelines and recommendations are given for screening plant material suitable for anaerobic digestion using the OxiTop (R) system.
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Pabon-Pereira, C. P., Hamelers, H. V. M., Matilla, I., & van Lier, J. B. (2020). New Insights on the Estimation of the Anaerobic Biodegradability of Plant Material: Identifying Valuable Plants for Sustainable Energy Production. Processes, 8(7), 23 pp.
Abstract: Based on fifteen European plant species, a statistical model for the estimation of the anaerobic biodegradability of plant material was developed. We show that this new approach represents an accurate and cost-effective method to identify valuable energy plants for sustainable energy production. In particular, anaerobic biodegradability (B-o) of lignocellulosic material was empirically found to be related to the amount of cellulose plus lignin, as analytically assessed by the van Soest method, i.e., the acid detergent fiber (ADF) value. Apart from being theoretically meaningful, the ADF-based empirical model requires the least effort compared to the other four proposed conceptual models proposed, as individual fractions of cellulose, hemicellulose, and lignin do not need to be assessed, which also enhances the predictive accuracy of the model's estimation. The model's results showed great predictability power, allowing us to identify interesting crops for sustainable crop rotations. Finally, the model was used to predictB(o)of 114 European plant samples that had been previously characterized by means of the van Soest method.
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