Anaerobic digestion of waste activated sludge (WAS) is currently enjoying renewed interest due to the potential for methane production. However, methane production is often limited by the slow hydrolysis rate and/or poor methane potential of WAS. This study presents a novel pretreatment strategy based on free nitrous acid (FNA or HNO2) to enhance methane production from WAS. Pretreatment of WAS for 24 h at FNA concentrations up to 2.13 mg N/L substantially enhanced WAS solubilization, with the highest solubilization (0.16 mg chemical oxygen demand (COD)/mg volatile solids (VS), at 2.13 mg HNO2-N/L) being six times that without FNA pretreatment (0.025 mg COD/mg VS, at 0 mg HNO2-N/L). Biochemical methane potential tests demonstrated methane production increased with increased FNA concentration used in the pretreatment step. Model-based analysis indicated FNA pretreatment improved both hydrolysis rate and methane potential, with the highest improvement being approximately 50% (from 0.16 to 0.25 d(-1)) and 27% (from 201 to 255 L CH4/kg VS added), respectively, achieved at 1.78-2.13 mg HNO2-N/L. Further analysis indicated that increased hydrolysis rate and methane potential were related to an increase in rapidly biodegradable substrates, which increased with increased FNA dose, while the slowly biodegradable substrates remained relatively static.

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The model structure in anaerobic digestion has been clarified following publication of the IWA Anaerobic Digestion Model No. 1 (ADM1). However, parameter values are not well known, and uncertainty and variability in the parameter values given is almost unknown. Additionally, platforms for identification of parameters, namely continuous-flow laboratory digesters, and batch tests suffer from disadvantages such as long run times, and difficulty in defining initial conditions, respectively. Anaerobic sequencing batch reactors (ASBRs) are sequenced into fill-react-settle-decant phases, and offer promising possibilities for estimation of parameters, as they are by nature, dynamic in behaviour, and allow repeatable behaviour to establish initial conditions, and evaluate parameters. In this study, we estimated parameters describing winery wastewater (most COD as ethanol) degradation using data from sequencing operation, and validated these parameters using unsequenced pulses of ethanol and acetate. The model used was the ADM1, with an extension for ethanol degradation. Parameter confidence spaces were found by non-linear, correlated analysis of the two main Monod parameters; maximum uptake rate (k(m)), and half saturation concentration (K(S)). These parameters could be estimated together using only the measured acetate concentration (20 points per cycle). From interpolating the single cycle acetate data to multiple cycles, we estimate that a practical "optimal" identifiability could be achieved after two cycles for the acetate parameters, and three cycles for the ethanol parameters. The parameters found performed well in the short term, and represented the pulses of acetate and ethanol (within 4 days of the winery-fed cycles) very well. The main discrepancy was poor prediction of pH dynamics, which could be due to an unidentified buffer with an overall influence the same as a weak base (possibly CaCO3). Based on this work, ASBR systems are effective for parameter estimation, especially for comparative wastewater characterisation. The main disadvantages are heavy computational requirements for multiple cycles, and difficulty in establishing the correct biomass concentration in the reactor, though the last is also a disadvantage for continuous fixed film reactors, and especially, batch tests.

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