Da Silva, C., Astals, S., Peces, M., Campos, J. L., & Guerrero, L. (2018). Biochemical methane potential (BMP) tests: Reducing test time by early parameter estimation. Waste Manage., 71, 19–24.
Abstract: Biochemical methane potential (BMP) test is a key analytical technique to assess the implementation and optimisation of anaerobic biotechnologies. However, this technique is characterised by long testing times (from 20 to > 100 days), which is not suitable for waste utilities, consulting companies or plants operators whose decisionmaking processes cannot be held for such a long time. This study develops a statistically robust mathematical strategy using sensitivity functions for early prediction of BMP firstorder model parameters, i.e. methane yield (B0) and kinetic constant rate (k). The minimum testing time for early parameter estimation showed a potential correlation with the k value, where (i) slowly biodegradable substrates (k <= 0.1 d(1)) have a minimum testing times of >= 15 days, (ii) moderately biodegradable substrates (0.1 < k < 0.2 d(1)) have a minimum testing times between 8 and 15 days, and (iii) rapidly biodegradable substrates (k > 0.2 d(1)) have testing times lower than 7 days. (C) 2017 Elsevier Ltd. All rights reserved.

Da Silva, C., Peces, M., Faundez, M., Hansen, H., Campos, J. L., Dosta, J., et al. (2022). Gamma distribution function to understand anaerobic digestion kinetics: Kinetic constants are not constant. Chemosphere, 306, 135579.
Abstract: The Gamma model is a novel approach to characterise the complex degradation dynamics taking place during anaerobic digestion. This three parameters model results from combining the firstorder kinetic model and the Gamma distribution function. In contrast to conventional models, where the kinetic constant is considered invariant, the Gamma model allows analysing the variability of the kinetic constant using a probability density function. The kinetic constant of monodigestion and codigestion batch tests of different wastes were modelled using the Gamma model and two common firstorder models: onestep onefraction model and onestep twofraction model. The Gamma distribution function approximates three distinct probability density functions, i.e. exponential, lognormal, and delta Dirac. Specifically, (i) cattle paunch and pig manure approximated a lognormal distribution; (ii) cattle manure and microalgae approximated an exponential distribution, and (iii) primary sludge and cellulose approximated a delta Dirac distribution. The Gamma model was able to characterise two distinct waste activated sludge, one approximated to a lognormal distribution and the other to an exponential distribution. The same cellulose was tested with two different inocula; in both tests, the Gamma distribution function approximated a delta Dirac function but with a different kinetic value. The potential and consistency of Gamma model were also evident when analysing pig manure and microalgae codigestion batch tests since (i) the mean k of the codigestion tests were within the values of the monodigestion tests, and (ii) the profile of the density function transitioned from lognormal to exponential distribution as the percentage of microalgae in the mixture increased.
