A modelling approach for the assessment of energy recovery and impact on the water line of sludge pre-treatments. (1st July 2023) - Campo, Giuseppe; Cerutti, Alberto; Zanetti, Mariachiara; De Ceglia, Margherita; Scibilia, Gerardo; Ruffino, Barbara
Abstract: A simple, easy-to-use, first-order model was elaborated to predict the methane production and the release of ammoniacal nitrogen (N–NH3 ) to the digestate in full-scale anaerobic digestion (AD) processes. The study used long-term, semi-continuous AD tests, carried out with samples of primary sludge (PS), raw waste activated sludge (WAS), WAS after a thermo-alkali pre-treatment (90 °C, 90 min, 4 g NaOH/100 g TS) and mixed sludge (PS/treated WAS), to calibrate and validate the model. The results of both the experimental activities and the phase of model tuning demonstrated that the proposed model was capable to provide reliable information to completely characterize the AD process, thus overcoming the limitations due to discontinuity of experimental tests. Furthermore, it was demonstrated that low-temperature thermo-alkali pre-treatments could increase the values of the model parameters, namely methane production after an infinite time (B0, +70%) and hydrolysis constant (k, +450%), and made them comparable to those obtained by the application of commercial, high-energy demanding treatments (e.g. Cambi). Finally, the issue concerning the release of N–NH3 to digestate was deemed to be very worthy to being investigated because, after pre-treatments, the cost for nitrogen removal in the water line, through the traditional processes of nitrification – denitrification, could increase even by 140%. Highlights: Traditional WWTPs must increase their capacity in recovering resources. Hybrid pre-treatments increase both methane production and nitrogen release. Nitrogen release must be controlled in the application of sludge pre-treatments. A simple, first-order model was validated to predict nitrogen release to the digestate. Extra nitrogen in the water line due to pre-treatments raises treatments costs by 140%.