Predicting the biochemical methane potential of organic waste by near infrared spectroscopy

The biochemical methane potential (BMP) evaluates the ultimate amount of methane produced by any given waste orbiomass under anaerobic conditions. This value is currently one of the most important parameter for the design andcontrol of anaerobic digestion plants and more specifically in co-digestion plants where a broad rang of substrates canbe treated.

Further Authors:
J. Doublet, C. Laroche, A. Ponthieux, J. Cacho-Rivero - Veolia Environnement Research and Innovation

However, BMP test is time consuming (30-50 days) and expensive, making the current protocol non-adaptedfor industrial plants management and optimisation. New technologies providing fast determination of BMP become thusnecessary. It has been demonstrated that Near Infrared Spectroscopy (NIRS) is a suitable method for fast prediction of awide range of organic parameters for plant biomass, waste, or soil. It is a spectroscopic method using the infrared regionof the electromagnetic spectrum (800-2500 nm). The prediction of the reference value is only based on spectral data andthus do not need any chemical analysis. Its suitability has been demonstrated for the monitoring of anaerobic digestionprocess, the control of the incoming feedstock and finally for the prediction of BMP in case of municipal solid waste(MSW) and meadow grasses.The anaerobic co-digestion of organic solid waste is increasingly popular. It indeed offers several advantages in termsof biogas yield as well of as diversity of waste treated. Therefore, fast waste characterisation and more specificallyBMP determination becomes crucial for industrial plant management and process monitoring. In that context the use ofNIRS to predict BMP potential is a promising alternative. For most of the NIR models used in anaerobic digestion,calibrations were performed for one type of waste or substrate. These models would not therefore be able to take intoaccount the variability of a wide range of waste.The aim of our study was therefore to develop a NIRS calibration model for the prediction of the BMP value in a codigestioncontext, that is, for a broad range of organic waste such as MSW, agro-industrial waste, meat waste,vegetables, fruits, crops…A total of 296 samples including most of the substrates treated by anaerobic co-digestion were used for NIRScalibration and validation. Spectra collection and BMP tests were conducted in duplicates and for both, on dried and 1mm grinded samples. The NIRS calibrations were performed by partial least square (PLS) regression between spectraand BMP values, and for different spectra transformations (multiple scatter correction, standard normal variate, de-trendand derivatives).The NIRS predictions of the BMP values were satisfactory (Root Mean Square error = 40 ml CH4.kg-1 VSfed; RelativeStandard Error = 12.7%). The integration of the entire substrate diversity in the model remained nevertheless difficultdue to specific organic matter properties and the high level of uncertainty of the BMP values. The addition of moresamples in the dataset in order to perform local calibrations would probably improve this point. Calibrated with 224 samples, the determined model allows the prediction of the BMP for a large range of organic substrates.



Copyright: © European Compost Network ECN e.V.
Quelle: Orbit 2012 (Juni 2012)
Seiten: 9
Preis inkl. MwSt.: € 9,00
Autor: M. Poitrenaud

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