Techno-Economic and Life Cycle Assessment of Renewable Natural Gas Production from Spent Coffee Grounds Co-Digestion: A European and North American Biorefinery Comparison

High Resolution Image Download MS PowerPoint Slide Spent coffee grounds (SCGs) are a globally abundant organic residue with volatile solids exceeding 90% of total solids and a biomethane potential of 250–350 mL CH 4 /g VS. This study integrates Anaerobic Digestion Model No. 1 (ADM1) kinetics within the BioSTEAM process simulation framework to conduct coupled techno-economic analysis (TEA) and life cycle assessment (LCA) of renewable natural gas (RNG) production from two codigestion scenarios at 5000 kg/h total feed: (i) a Madrid scenario, in which SCGs are codigested with fruit and vegetable waste (FVW) from Mercamadrid, Spain, and (ii) an Iowa scenario, in which SCGs are codigested with mixed prairie biomass in Iowa, USA. Although parameterized for these two locations, the scenarios can also be interpreted more generally as transferable examples of SCG codigestion with food-waste biomass and herbaceous biomass, respectively. Biogas is upgraded to RNG via monoethanolamine scrubbing, and hydrothermal carbonization (HTC) biochar is recovered as a coproduct. The Madrid scenario achieves an RNG rate of 186.3 kg/h, a minimum selling price (MSP) of $41.8/GJ, an internal rate of return of 8.0%, and an NPV of $2.3 M. The Iowa scenario yields 180.6 kg/h RNG at an MSP of $55.9/GJ, an IRR of 3.3%, and an NPV of –$7.6 M; Monte Carlo analysis ( n = 2000) identifies D_VS as the dominant RNG-rate uncertainty driver in both scenarios, while SCG price exerts the strongest influence on MSP. LCA under TRACI 2.1 with system expansion yields global warming potentials of –10.96 and –12.31 kg CO 2 -eq per kg RNG for the Madrid and Iowa scenarios, respectively, with 9 and 8 of 10 impact categories being net negative. Results demonstrate that SCG-based codigestion biorefineries can deliver strong environmental benefits, but economics remain scenario-dependent and do not necessarily align with the most favorable climate outcome.