Integration of anaerobic digestion with heat Pump: Machine learning-based technical and environmental assessment

Abstract

Anaerobic digestion (AD)-based biogas production mitigates the environmental footprint of organic wastes (e.g., food waste and sewage sludge) and facilitates a circular economy. The work proposed an integrated system where the thermal energy demand of an AD is supplied using an air source heat pump (ASHP). The proposed system is compared to a baseline system, where the thermal energy is supplied by a natural gas-based heating system. Several machine learning models are developed for predicting biogas production, among which the Gaussian Process Regression (GPR) showed a superior performance (R2 = 0.84 and RMSE = 0.0755 L gVS−1 day−1). The GPR model further informed a thermodynamic model of the ASHP, which revealed the maximum biogas yield to be approximately 0.585 L.gVS−1.day−1 at an optimal temperature of 55 °C (thermophilic). Subsequently, life cycle assessment showed that ASHP-based AD heating systems achieved 28.1 % (thermophilic) and 36.8 % (mesophilic) carbon abatement than the baseline system.