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Alejo, L., Atkinson, J., Guzman-Fierro, V., & Roeckel, M. (2018). Effluent composition prediction of a two-stage anaerobic digestion process: machine learning and stoichiometry techniques. Environ. Sci. Pollut. Res., 25(21), 21149–21163.
Abstract: Computational self-adapting methods (Support Vector Machines, SVM) are compared with an analytical method in effluent composition prediction of a two-stage anaerobic digestion (AD) process. Experimental data for the AD of poultry manure were used. The analytical method considers the protein as the only source of ammonia production in AD after degradation. Total ammonia nitrogen (TAN), total solids (TS), chemical oxygen demand (COD), and total volatile solids (TVS) were measured in the influent and effluent of the process. The TAN concentration in the effluent was predicted, this being the most inhibiting and polluting compound in AD. Despite the limited data available, the SVM-based model outperformed the analytical method for the TAN prediction, achieving a relative average error of 15.2% against 43% for the analytical method. Moreover, SVM showed higher prediction accuracy in comparison with Artificial Neural Networks. This result reveals the future promise of SVM for prediction in non-linear and dynamic AD processes.
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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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Crutchik, D., Barboza, J., Vazquez-Padin, J. R., Pedrouso, A., del Rio, A. V., Mosquera-Corral, A., et al. (2023). Integrating food waste management into urban wastewater treatment: Economic and environmental impacts. J. Environ. Manage., 345, 118517.
Abstract: Food waste is the main component of municipal solid waste (MSW) and its sustainable management is a global challenge. Co-treatment of food waste and urban wastewater in wastewater treatment plants (WWTPs) could be a plausible management strategy to reduce the MSW amount that is disposed in landfills, while converting its organic fraction into biogas in the WWTP. However, the increased organic load in the wastewater influent would impact the capital and operating costs of the WWTP, mainly due to the increase in sludge production. In this work, different scenarios for co-treatment of food waste and wastewater were studied from both economic and environmental perspectives. These scenarios were designed based on different sludge disposal and management options. The results showed that the co-treatment of food waste and wastewater would be more environmentally friendly than their separate treatment, but its economic feasibility strongly depends on the ratio between the management costs of MSW and sewage sludge.
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Crutchik, D., Franchi, O., Caminos, L., Jeison, D., Belmonte, M., Pedrouso, A., et al. (2020). Polyhydroxyalkanoates (PHAs) Production: A Feasible Economic Option for the Treatment of Sewage Sludge in Municipal Wastewater Treatment Plants? Water, 12(4), 12 pp.
Abstract: Sludge is a by-product of municipal wastewater treatment plants (WWTPs) and its management contributes significantly to the operating costs. Large WWTPs usually have anaerobic sludge digesters to valorize sludge as methane and to reduce its mass. However, the low methane market price opens the possibility for generating other high value-added products from the organic matter in sludge, such as polyhydroxyalkanoates (PHAs). In this work, the economic feasibility of retrofitting two types of WWTPs to convert them into biofactories of crude PHAs was studied. Two cases were analyzed: (a) a large WWTP with anaerobic sludge digestion; and (b) a small WWTP where sludge is only dewatered. In a two-stage PHA-production system (biomass enrichment plus PHAs accumulation), the minimum PHAs cost would be 1.26 and 2.26 US$/kg PHA-crude for the large and small WWTPs, respectively. In a single-stage process, where a fraction of the secondary sludge (25%) is directly used to accumulate PHAs, the production costs would decrease by around 15.9% (small WWTPs) and 19.0% (large WWTPs), since capital costs associated with bioreactors decrease. Sensitivity analysis showed that the PHA/COD (Chemical Oxygen Demand) yield is the most crucial parameter affecting the production costs. The energy, methane, and sludge management prices also have an essential effect on the production costs, and their effect depends on the WWTP's size.
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Crutchik, D., Rodriguez-Valdecantos, G., Bustos, G., Bravo, J., Gonzalez, B., & Pabon-Pereira, C. (2020). Vermiproductivity, maturation and microbiological changes derived from the use of liquid anaerobic digestate during the vermicomposting of market waste. Water Sci. Technol., 82(9), 1781–1794.
Abstract: Recently, it has been suggested that the liquid fraction of anaerobic digestate, derived from the treatment of wastewater and solid wastes, could be used in vermicomposting as a solution to its disposal, and even for its valorization. Nevertheless, the literature does not provide enough information about its impact on the process of vermicomposting itself and on the final quality of the end-product. In this study, the effect of different doses of digestate in the vermicomposting process treating market waste is assessed measuring earthworm population dynamics, the bacterial community succession present in the vermibeds, as well as maturation and the end-quality of the vermicompost. Our results show that the addition of liquid digestate to the vermibeds increased the earthworms biomass, i.e. 71%, 94% and 168% in control, and vermibeds with 30% and 60% digestate, respectively. Further, the increase in the amount of N in the vermicompost decreased as the digestate addition increased, i.e. 75%, 8%, 3%. The maturity achieved was high in all treatments as shown by the C/N ratio, 7.98, 7.40 and 10.20, and the high seed germination rate, above 90%. Finally, the succession of the microbial community was not disturbed and compositional stabilization was reached after 92 days.
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Crutchik, D., Rodriguez-Valdecantos, G., Bustos, G., Bravo, J., Gonzalez, B., & Pabon-Pereira, C. (2020). WATER SCIENCE AND TECHNOLOGY. Water Sci. Technol., 82(9), 1781–1794.
Abstract: Recently, it has been suggested that the liquid fraction of anaerobic digestate, derived from the treatment of wastewater and solid wastes, could be used in vermicomposting as a solution to its disposal, and even for its valorization. Nevertheless, the literature does not provide enough information about its impact on the process of vermicomposting itself and on the final quality of the end-product. In this study, the effect of different doses of digestate in the vermicomposting process treating market waste is assessed measuring earthworm population dynamics, the bacterial community succession present in the vermibeds, as well as maturation and the end-quality of the vermicompost. Our results show that the addition of liquid digestate to the vermibeds increased the earthworms biomass, i.e. 71%, 94% and 168% in control, and vermibeds with 30% and 60% digestate, respectively. Further, the increase in the amount of N in the vermicompost decreased as the digestate addition increased, i.e. 75%, 8%, 3%. The maturity achieved was high in all treatments as shown by the C/N ratio, 7.98, 7.40 and 10.20, and the high seed germination rate, above 90%. Finally, the succession of the microbial community was not disturbed and compositional stabilization was reached after 92 days.
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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 decision-making 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 first-order model parameters, i.e. methane yield (B-0) 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.
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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 first-order 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 mono-digestion and co-digestion batch tests of different wastes were modelled using the Gamma model and two common first-order models: one-step one-fraction model and one-step twofraction model. The Gamma distribution function approximates three distinct probability density functions, i.e. exponential, log-normal, 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 log-normal 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 co-digestion batch tests since (i) the mean k of the co-digestion tests were within the values of the mono-digestion tests, and (ii) the profile of the density function transitioned from log-normal to exponential distribution as the percentage of microalgae in the mixture increased.
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Pabon-Pereira, C. P., de Vries, J. W., Slingerland, M. A., Zeeman, G., & van Lier, J. B. (2014). Impact of crop-manure ratios on energy production and fertilizing characteristics of liquid and solid digestate during codigestion. Environ. Technol., 35(19), 2427–2434.
Abstract: The influence of maize silage-manure ratios on energy output and digestate characteristics was studied using batch experiments. The methane production, nutrients availability (N and P) and heavy metals' content were followed in multiflask experiments at digestion times 7, 14, 20, 30 and 60 days. In addition, the available nutrient content in the liquid and solid parts of the digestate was evaluated. Aanaerobic digestion favoured the availability of nutrients to plants, after 61 days 20-26% increase in NH4+ and 0-36% increase in PO43- were found in relation to initial concentrations. Digestion time and maize addition increased the availability of PO43-. Inorganic nutrients were found to be mainly available in the liquid part of the digestate, i.e. 80-92% NH4+ and 65-74% PO43-. Manure had a positive effect on the methane production rate, whereas maize silage increased the total methane production per unit volatile solids in all treatments.
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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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Puig-Castellvi, F., Midoux, C., Guenne, A., Conteau, D., Franchi, O., Bureau, C., et al. (2022). A longitudinal study of the effect of temperature modification in full-scale anaerobic digesters – dataset combining 16S rDNA gene sequencing, metagenomics, and metabolomics data. Data Br., 41, 107960.
Abstract: Data in this article provides detailed information on the microbial dynamics and degradation performances in two fullscale anaerobic digesters operated in parallel for 476 days. One of them was kept at 35 degrees C for the whole experiment, while the other was submitted to sub-mesophilic (25 degrees C) conditions between days 123 and 373. Sludge samples were collected from both digesters at days 0, 80, 177, 218, 281, 353, and 462. The provided data include the operational conditions of the digesters and the characterization of the sludge samples at the physicochemical level, indicative of the digesters' degradation performance. It also includes the characterization of the sludge samples at the multiomics level (16S rRNA gene sequencing, metagenomics, and metabolomics profiling), to decipher the changes in the microbial structure and molecular activity. The 16S rDNA gene sequencing, metagenomics, and metabolomics data were generated using an IonTorrent PGM sequencer, an Illumina NextSeq 500 sequencer, and LTQ-Orbitrap XL mass spectrometer respectively. The 16S rDNA gene raw data and the metagenomics data have been deposited in the BioProject PRJEB49115, in the ENA database (https://www.ebi.ac.uk/ena/browser/view/PRJEB49115). The metabolomics data has been deposited at the Metabolomics Workbench, with study id ST002004 (DOI: 10.21228/M8JM6B). The data can be used as a source for comparisons with other studies working with data from full-scale anaerobic digesters, especially for those investigating the effect of the temperature modification. The data is associated with the research article “Metataxonomics, metagenomics, and metabolomics analysis of the influence of temperature modification in full-scale anaerobic digesters” (Puig-Castellvi et al [1]). (c) 2022 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
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