Hydrothermal carbonisation for the conversion of food waste to energy products

Food waste is an abundant biomass resource generated continuously all around the world. However, due to numerous technical challenges linked to the heterogeneous nature of food waste, its utilisation is neglected in large parts of the world and underutilised in others. An option for treating food waste is to feed it into synthetic fuel production plants. The core of the synthetic fuel route is a gasification stage to decompose biomass into light-weight gas molecules by partial combustion. However, food waste is not suitable to be treated by this technology due to its heterogenicity and high moisture content. In this regard, there is an emerging technology that locates itself as a potential link between food waste and the synthetic fuel route, hydrothermal carbonisation (HTC). The HTC is a thermochemical technology that consists of treating a solid feedstock submerged in water at sub-critical conditions. This technology can convert food waste into an enhanced solid fuel with coal-like properties, known as hydrochar. However, the HTC treatment of food waste is still significantly unexplored, marked by the lack of insight and studies focused on expanding the feedstock catalogue. Also, most of HTC studies have the one-response-at-a-time approach, which is counterintuitive with a technology known for the trade-off between its responses. Therefore, in this work the HTC of food waste was evaluated with a response surface methodology, using a central composite rotatable design for evaluating the effect of process parameters (temperature, reaction time, and solid load) and ultimately performing optimisation studies involving utilisation-responses and viability-responses. The results include the parametric analysis of the composition and fuel quality of hydrochar, the biomethanation properties of the process water and the validation of empirical models. Also, the HTC process optimisation includes energy efficiency and hydrochar responses with a desirability function.