Quantifying uncertainties in greenhouse gas accounting of biomass power generation in China: System boundary and parameters

Systematically quantifying the greenhouse gas (GHG) emissions of biomass power generation is a prerequisite for robust decision-makings associated with the technology's scale deployment. This study compared the planting-to-wire GHG emissions of a typical corn-stover-based power generation system in China, estimated using one process-based and two hybrid life-cycle assessment (LCA) models. Results showed that emissions calculated by process-based LCA were 11% lower than that of hybrid models because of the truncations on services and accessory equipment. The two tiered hybrid approaches yielded total-supply-chain GHG footprints of material and equipment with a negligible difference (0.7%). The parameter settings varied by time and regions/countries resulted in temporal and spatial uncertainties of process-based LCA at 4%-10% and 0.1%-16% respectively. We proposed adopting hybrid LCA models for footprint calculation because of their strength in comprehensive accounting coverage, less dependence on data acquisition, and reduced temporal and spatial uncertainties. As the GHG footprint of biomass energy utilization is region-specific and determined by multiple factors, such as supply-chain configurations and landscape of power generation technology, results of this study help to understand the uncertainties and trade-offs associated with different LCA model deployments in China, and thus, contribute to advancing the country's biomass power sector moving forward.