: Secondary sedimentation tank sludge (SSTS) is a severe type of waste that needs to be treated to prevent human health risks. Anaerobic digestion (AD) alone can be ineffective for treating SSTS due to low substrate biodegradability. This study proposes the use of ultrasonic pretreatment (UP) on SSTS for 0 - 60 min. UP effect on SSTS was analyzed through the actual specific energy input, nominal energy input, and soluble chemical oxygen demand. The highest cumulative methane yield (CMY) of 241.56 mL/g VS obtained during the AD of the pretreated substrate (i.e., 30 min) was 58.4% higher than that of untreated SSTS. The resulting CMY curves were subsequently simulated via the modified Logistic and Gompertz, Artificial Neural Network, Auto-Regressive Integrated Moving-Average (ARIMA) models. As a novel proposal for predicting CMYs, the ARIMA model is recommended due to its simplicity and better performance than sigmoidal models (R2 = 0.9975 - 0.9988).

Improved methane production from ultrasonically-pretreated secondary sedimentation tank sludge and new model proposal: Time series (ARIMA)

Bianco, Francesco
;
2023-01-01

Abstract

: Secondary sedimentation tank sludge (SSTS) is a severe type of waste that needs to be treated to prevent human health risks. Anaerobic digestion (AD) alone can be ineffective for treating SSTS due to low substrate biodegradability. This study proposes the use of ultrasonic pretreatment (UP) on SSTS for 0 - 60 min. UP effect on SSTS was analyzed through the actual specific energy input, nominal energy input, and soluble chemical oxygen demand. The highest cumulative methane yield (CMY) of 241.56 mL/g VS obtained during the AD of the pretreated substrate (i.e., 30 min) was 58.4% higher than that of untreated SSTS. The resulting CMY curves were subsequently simulated via the modified Logistic and Gompertz, Artificial Neural Network, Auto-Regressive Integrated Moving-Average (ARIMA) models. As a novel proposal for predicting CMYs, the ARIMA model is recommended due to its simplicity and better performance than sigmoidal models (R2 = 0.9975 - 0.9988).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11580/103147
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