No abstract

Currently, there is a growing worldwide interest for the treatment of wastes, and especially farm wastes, by anaerobic digestion. Biochemical methane potential is a key parameter for the design, optimisation and monitoring of the anaerobic digestion process, but it is also time consuming (4-7 weeks). Near infrared reflectance spectroscopy seems a promising method to predict the biochemical methane potential of a wide range of organic substrates. This study compares a 'global' predictive model mainly built with biogas plant feedstocks, and a more 'agricultural' specific one built with farm wastes only (e.g. manures and crop residues). The global model was calibrated with 245 samples and the specific one with 171 samples. In parallel, validation sets composed of 36 farm wastes and eight other wastes (sludge, fruit residues and vegetables) were used to evaluate and compare both models. Satisfying results were obtained on the validation sets considering, respectively for the global and the specific models, a root mean square error of prediction of 44 and 34 NL CH kg volatile solid, a coefficient of determination of 0.76 and 0.83, and a ratio of performance to deviation of 2.0 and 2.4. In general rules, the specific model was better than the global one in the prediction of farm wastes methane potential. However, thanks to its larger sample variability, the global one was more robust, especially towards the 'other' wastes, which can be introduced punctually in agricultural biogas plant.

During the last decade, the application of pretreatment has been investigated to enhance methane production from lignocellulosic biomass such as wheat straw (WS). Nonetheless, most of these studies were conducted in laboratory batch tests, potentially hiding instability problems or inhibition, which may fail in truly predicting full-scale reactor performance. For this purpose, the effect of an alkaline pretreatment on process performance and methane yields from WS (0.10 g NaOH g−1 WS at 90 °C for 1 h) co-digested with fresh wastewater sludge was evaluated in a pilot-scale reactor (20 L). Results showed that alkaline pretreatment resulted in better delignification (44%) and hemicellulose solubilization (62%) compared to untreated WS. Pilot-scale study showed that the alkaline pretreatment improved the methane production (261 ± 3 Nm3 CH4 t−1VS) compared to untreated WS (201 ± 6 Nm3 CH4 t−1VS). Stable process without any inhibition was observed and a high alkalinity was maintained in the reactor due to the NaOH used for pretreatment. The study thus confirms that alkaline pretreatment is a promising technology for full-scale application and could improve the overall economic benefits for biogas plant at 24 EUR t−1 VS treated, improve the energy recovery per unit organic matter, reduce the digestate volume and its disposal costs.

Agricultural biogas plants are increasingly being used in Europe as an alternative source of energy. To optimize the sizing and operation of existing or future biogas plants, a better knowledge of different feedstocks is needed. Our aim is to characterize 132 common agricultural feedstocks in terms of their chemical composition (proteins, fibers, elemental analysis, etc.) and biochemical methane potential shared in five families: agro-industrial products, silage and energy crops, lignocellulosic biomass, manure, and slurries. Among the families investigated, manures and slurries exhibited the highest ash and protein contents (10.3–13.7% DM). High variabilities in C/N were observed among the various families (19.5% DM for slurries and 131.7% DM for lignocellulosic biomass). Methane potentials have been reported to range from 63 Nm3 CH4/t VS (green waste) to 551 Nm3 CH4/t VS (duck slurry), with a mean value of 284 Nm3 CH4/t VS. In terms of biodegradability, lower values of 52% and 57% were reported for lignocelluloses biomasses and manures, respectively, due to their high fiber content, especially lignin. By contrast, animal slurries, silage, and energy crops exhibited a higher biodegradability of 70%. This database will be useful for project owners during the pre-study phases and during the operation of future agricultural biogas plants.