
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.



del Rio, A. V., Campos, J. L., Da Silva, C., Pedrouso, A., & MosqueraCorral, A. (2019). Determination of the intrinsic kinetic parameters of ammoniaoxidizing and nitriteoxidizing bacteria in granular and flocculent sludge. Sep. Purif. Technol., 213, 571–577.
Abstract: The different oxygen affinities of ammoniaoxidizing (AOB) and nitriteoxidizing bacteria (NOB) are often used to define the operational strategy to achieve partial nitritation (PN) required before the anammox (AMX) process. For this purpose, apparent kinetic parameters are mainly used in the case of granular sludge, which can lead to errors when defining the operational conditions to obtain only nitritation (avoiding nitratation). In the present study, a mathematical methodology is proposed to determine the intrinsic kinetic parameters of AOB and NOB in granular sludge based on data obtained by respirometric assays. Additionally, the oxygen affinity constant (KO2) and maximum specific rate (r(max)) of flocculent and granular sludge sample, produced under mainstream and sidestream conditions were determined at various temperatures (15, 20 and 30 degrees C). The results show that for granules, the intrinsic KO2 and r(max) values were lower and higher, respectively, than the apparent values. Furthermore, the KO2 values for flocs and granules at all of the tested temperatures were lower for NOB than for AOB. The values obtained for the kinetic parameters indicated that it is impossible to maintain partial nitritation by only controlling the dissolved oxygen concentration.



ReadDaily, B. L., Sabba, F., Pavissich, J. P., & Nerenberg, R. (2016). Kinetics of nitrous oxide (N2O) formation and reduction by Paracoccus pantotrophus. AMB Express, 6, 7 pp.
Abstract: Nitrous oxide (N2O) is a powerful greenhouse gas emitted from wastewater treatment, as well as natural systems, as a result of biological nitrification and denitrification. While denitrifying bacteria can be a significant source of N2O, they can also reduce N2O to N2. More information on the kinetics of N2O formation and reduction by denitrifying bacteria is needed to predict and quantify their impact on N2O emissions. In this study, kinetic parameters were determined for Paracoccus pantotrophus, a common denitrifying bacterium. Parameters included the maximum specific reduction rates, (q) over cap, growth rates, (mu) over cap, and yields, Y, for reduction of NO3 (nitrate) to nitrite (N2O), N2O to N2O, and N2O to N2, with acetate as the electron donor. The (q) over cap values were 2.9 gN gCOD(1) d(1) for NNO3 to NO2, 1.4 gN gCOD(1) d(1) for N2Oto N2O, and 5.3 gN gCOD(1) d(1) for N2O to N2. The (mu) over cap values were 2.7, 0.93, and 1.5 d(1), respectively. When N2O and NO3 were added concurrently, the apparent (extant) kinetics, (q) over cap (app), assuming reduction to N2, were 6.3 gCOD gCOD(1) d(1), compared to 5.4 gCOD gCOD(1) d(1) for NO3 as the sole added acceptor. The (mu) over cap (app) was 1.6 d(1), compared to 2.5 d(1) for NO3 alone. These results suggest that NO3 and N2O were reduced concurrently. Based on this research, denitrifying bacteria like P. pantotrophus may serve as a significant sink for N2O. With careful design and operation, treatment plants can use denitrifying bacteria to minimize N2O emissions.

