Biomass & coal co-milling: Old hat or the route to decarbonization for coal power dependent economies via novel particle size partitioning analysis

Despite the global push towards net zero, coal remains a dominant energy source in many economies. Biomass co-firing offers coal powered dependent economies a transitional decarbonization pathway, yet co-milling remains a critical barrier due to the contrasting fracture mechanics of coal and biomass and lack of understanding in the partitioning of milled blends. This study aims to overcome some of these challenges by investigating the co-milling behaviour of wood pellets and palm kernel shell (PKS), with 7 coals (5 Australian, 1 Indonesian and 1 Colombian) using a ball and race mill with pneumatic classification. These two biomasses were blended with each coal at 10 % and 40 % wt/wt. The milling performance was evaluated using particle size distribution (PSD) statistical analysis, novel application of thermal characterisation on the milled size fractions, and application of Von Rittinger's comminution theory to rank grindability. Results demonstrate that while PKS exhibits mill choking when milled alone, co-milling enables complete milling, indicating a synergistic effect. Thermogravimetric analysis of size fractions enables the first reported estimation of biomass and coal partitioning within co-milled products. The Von Rittinger constant ranking revealed that softer coals require disproportionately higher energy when blended with biomass, particularly at higher blend ratios. Predictive models based on parent material PSD and thermal composition were developed to estimate co-milled particle size and specific energy consumption, showing good agreement at low blend ratios and highlighting synergistic effects at higher biomass contents. This study provides new insights into the physical and thermal partitioning of co-milled biomass and coal blends, demonstrating that co-milling can mitigate biomass milling limitations and improve throughput. The findings support the development of predictive models for PSD and energy consumption based on the parent material properties, offering practical guidance for the transition towards lower-carbon energy systems. • Co-milling biomass with coal avoids mill choking & shows synergistic effects. • Novel thermal analysis reveals biomass-coal partitioning in milled products. • Softer coals need more energy when co-milled with biomass at high ratios. • Predictive models predict size and energy use from parent fuel properties.