Hydrothermal carbonisation is a promising technology for greenhouse gas (GHG) mitigation through landfill avoidance and power generation, as it can convert high-moisture wastes into bio-coal which can be used for coal substitution. The GHG mitigation potential associated with landfill avoidance of high-moisture food waste (FW) generated in India, China and the EU was calculated and the potential for coal substitution to replace either grid energy, hard coal, or lignite consumption were determined. Different HTC processing conditions were evaluated including temperature and residence times and their effect on energy consumption and energy recovery. The greatest mitigation potential was observed at lower HTC temperatures and shorter residence times with the bio-coal replacing lignite. China had the greatest total mitigation potential (194 MT CO2 eq), whereas India had the greatest mitigation per kg of FW (1.2 kgCO2/kg FW). Significant proportions of overall lignite consumption could be substituted in India (12.4%) and China (7.1%), while sizable levels of methane could be mitigated in India (12.5%), China (19.3%), and the EU (7.2%). GHG savings from conversion of high-moisture FW into bio-coal and subsequent coal replacement has significant potential for reducing total GHG emissions and represents in India (3%), China (2.4%), and the EU (1%).

To maximize food waste utilization, it is necessary to understand the effect of process variables on product distribution. To this day, there is a lack of studies evaluating the effects of the multiple variables of HTC on food waste. A Design of Experiment (DoE) approach has been used to investigate the influence of three process variables on the product distribution and composition of process streams from the HTC of food waste. This work evaluates the effect of hydrothermal carbonization process conditions on the composition and utilization capabilities of hydrochar from food waste. Parametric analysis was carried out with a design of experiments of central composite rotatable design (CCRD) and response surface methodology (RSM). Derringer’s desirability function was employed to perform a multi-response evaluation. The optimized process conditions were 260.4 °C, 29.5 min reaction time, and 19.6% solid load. The predicted optimized responses were EMC = 2.7%, SY = 57.1%, EY = 84.7%, ED = 1.5, and HHV of 31.8 MJ/Kg, with a composite desirability of 0.68. Temperature and solid load had a significant effect on all evaluated responses, while reaction time was non-significant.