CORRESPONDENCE/REBUTTAL pubs.acs.org/est
Reply to Comment on “Parameter Identification and Modeling of the Biochemical Methane Potential of Waste Activated Sludge” n their correspondence, Batstone et al.1 expressed some concerns on the results of the paper of Appels et al.,2 mainly regarding three issues, that is, (i) the correctness of the experimental procedure, (ii) the suitability of stochastical modeling, and (iii) the interpretation and overgeneralization of the results. In the present comments, we formulate our reply to these concerns.
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’ INOCULUM/SLUDGE RATIO In their correspondence, Batstone et al.1 noticed the low inoculum/sludge ratio that was applied in the experiments, possibly leading to excessive acidification and low methane yield. While this ratio is indeed low on a volume basis, we would like to point out that the dry matter (DM) content of the inoculum (being approximately 89 g DM/kg inoculum) was in most cases significantly higher than the DM of the sludge. When assessing the inoculum/sludge ratio, obviously this ratio should be expressed in terms of dry solids, resulting in an inoculum/sludge ratio between 0.70 and 4.54. In only one sample, a DM content of 87.6 g DM/kg sludge was measured, leading to an inoculum/ sludge ratio of 0.70. For all other sludge samples, this ratio was at least 0.96. The confusion was possible because we did not report the DM content of the inoculum. Moreover, the biochemical methane potential (BMP) of the sludge sample with the highest DM concentration of the data set was 356 mL CH4/g ODM (organic dry matter), a figure that lies within the values to be expected for waste activated sludge and not suggesting an overload. Only a few samples resulted in a rather low BMP, but we choose not to remove these results since there was not a significant difference between the three replicas of these samples. Having a look at both external validation samples (one with a low BMP) included in Appels et al.,2 the model developed was able to make a very good prediction of the actual BMP of the samples and so it seems that the inclusion of all data-points did not affect the accuracy of the model. To further address the comments of Batstone et al.,1 Figure 1 illustrates the methane production as function of time for some selected samples. As can be seen from the Figure, the obtained profiles do not suggest an overload and strongly resemble typical profiles as reported by various other authors, including Wang et al.,3 Onyeche et al.,4 Lopez Torres and Llorens,5 Tang et al.,6 and Ge et al.7 In 2009, Angelidaki et al.8 published for the first time a standardized test to determine the BMP of biomass and sludge. Unfortunately, this standardized test was not available at the time of performing the experiments reported in Appels et al.2 At that time, several teams developed their own (and thus not standardized) tests (e.g., Ferrer et al.,9 Isci and Demirer 10). ’ STOCHASTIC MODELING We agree with Batstone et al. 1 that the stochastic modeling of BMP does not include biochemical and microbial aspects of anaerobic digestion and, therefore, does not replace mechanistic r 2011 American Chemical Society
Figure 1. Cumulative methane production of four selected WWTPs.
models such as ADM1, published by Batstone et al.11 However, stochastic models have their relevance and, because of their low complexity, offer the possibility of making a first estimation of the suitability of a certain substrate for anaerobic digestion. Other authors, including Mottet et al.12 and Schievano et al,13 have also used partial least-squares (PLS) and other regression models for this purpose. The main goal of the PLS regression we described in ref 2 is to identify the main components that are influencing the final BMP. By no means, a mechanistic relation between the PLS modeling input and the final BMP (i.e., PLS model output) is claimed. The developed model is a logical consequence from this approach and is included in the paper to illustrate the potential of the PLS approach.
’ INTERPRETATION RESULTS Finally, Batstone et al.1 pointed out that the work did not include pretreated sludges and, therefore, should not generalize that soluble COD is not a reliable indicator of sludge anaerobic degradability. We obviously agree with this comment, since we mentioned explicitly in ref 2 that “Extended research (including a wider measurement interval) is, however, needed to confirm this hypothesis”. We consider sCOD as a reliable indicator for the improvement of the BMP within a specific experimental setup. When comparing various studies with each other, the sCOD, however, does not seem to provide a univocal relationship with BMP. This observation led to the hypothesis formulated in Appels et al.,2 but certainly needs to be confirmed in further research. ve, Lise Appels,* Joost Lauwers, Geert Gins, Jan Degre Jan Van Impe, and Raf Dewil Chemical and Biochemical Process Technology and Control Section, Department of Chemical Engineering, Katholieke Universiteit Leuven, Willem De Croylaan 46, B-3001 Heverlee, Belgium
Published: August 02, 2011 7598
dx.doi.org/10.1021/es202267w | Environ. Sci. Technol. 2011, 45, 7598–7599
Environmental Science & Technology
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’ AUTHOR INFORMATION Corresponding Author
*Phone: +3215316944; fax: +3215317453; e-mail: lise.appels@ cit.kuleuven.be.
’ REFERENCES (1) Batstone, D. J.; Pavlostathis, S.; Jensen, P.; Angelidaki, I. Comment on “Parameter identification and modeling of the biochemical methane potential of waste activated sludge. Environ. Sci. Technol. 2011, DOI: 10.1021/es201803j. (2) Appels, L.; Lauwers, J.; Gins, G.; Degreve, J.; Van Impe, J.; Dewil, R. Parameter identification and modeling of the biochemical methane potential of waste activated sludge. Environ. Sci. Technol. 2011, 45, 4173–4178. (3) Wang, Q.; Kuninobu, M.; Kakimoto, K.; I.-Ogawa, H.; Kato, Y. Upgrading of anaerobic digestion of waste activated ultrasonic pretreatment. Bioresour. Technol. 1999, 68, 309–313. (4) Onyeche, T. I.; Schl€afer, O.; Bormann, H.; Schr€oder, C.; Sievers, M. Ultrasonic cell disruption of stabilised sludge with subsequent anaerobic digestion. Ultrasonics 2002, 40, 31–35. (5) Lopez Torres, M.; Espinosa Llorens, M. d. C. Effect of alkaline pretreatment on anaerobic digestion of solid wastes. Waste Manage. 2008, 28, 2229–2234. (6) Tang, B.; Yu, L.; Huang, S.; Luo, J.; Zhuo, Y. Energy efficiency of pre-treating excess sewage sludge with microwave irradiation. Bioresour. Technol. 2010, 101, 5092–5097. (7) Ge, H.; Jensen, P. D.; Batstone, D. J. Increased temperature in the thermophilic stage in temperature phased anaerobic digestion (TPAD) improves degradability of waste activated sludge. J. Hazard. Mater. 2011, 187, 355–361. (8) Angelidaki, I.; Alves, M.; Bolzonella, D.; Borzacconi, L.; Campos, J. L.; Guwy, A. J.; Kalyuzhnyi, S.; Jenicek, P.; van Lier, J.B. Defining the biomethane potential (BMP) of solid organic wastes and energy crops: a proposed protocol for batch assays. Water Sci. Technol. 2009, 59, 927–934. (9) Ferrer, I.; Ponsa, S.; Vazquez, F.; Font, X. Increasing biogas production by thermal (70 °C) sludge pre-treatment prior to thermophilic anaerobic digestion. Biochem. Eng. J. 2008, 42, 186–192. (10) Isci, A.; Demirer, G. N. Biogas production potential from cotton wastes. Renewable Energy 2007, 32, 750–757. (11) Batstone, D. J.; Keller, J.; Angelidaki, I.; Kalyuzhnyi, S. V.; Pavlostathis, S. G.; Rozzi, A.; Sanders, W. T. M.; Siegrist, H.; Vavilin, V. A. Water Sci. Technol. 2002, 45, 65–73. (12) Mottet, A.; Francois, E.; Latrille, E.; Steyer, J. P.; Deleris, S.; Vedrenne, F.; Carrere, H. Estimating anaerobic biodegradability indicators for waste activated sludge. Chem. Eng. J. 2010, 160, 488–496. (13) Schievao, A.; D’Imporzano, B. S. G.; Malagutti, L.; Gozzi, A.; Adani, F. Prediction of biogas potentials using quick laboratory analyses: Upgrading previous models for application to heterogeneous organic matrices. Bioresour. Technol. 2009, 100, 5777–5782.
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