Systems Assessment Center, Energy Systems Division, Argonne National Laboratory, 9700 South Cass Avenue, Lemont, Illinois 60439, United States.
Department of Natural Resources and Society, University of Idaho, 875 Perimeter Drive MS 1139, Moscow, Idaho 83844, United States.
Environ Sci Technol. 2021 Nov 2;55(21):14806-14816. doi: 10.1021/acs.est.1c04301. Epub 2021 Oct 15.
This study presents a cradle-to-grave life cycle analysis (LCA) of the greenhouse gas (GHG) emissions of the electricity generated from forest biomass in different regions of the United States (U.S.), taking into consideration regional variations in biomass availabilities and logistics. The regional biomass supply for a 20 MW bioelectricity facility is estimated using the Land Use and Resource Allocation (LURA) model. Results from LURA and data on regional forest management, harvesting, and processing are incorporated into the GHGs, Regulated Emissions, and Energy Use in Technologies (GREET) model for LCA. The results suggest that GHG emissions of mill residues-based pathways can be 15-52% lower than those of pulpwood-based pathways, with logging residues falling in between. Nonetheless, our analysis suggests that screening bioenergy projects on specific feedstock types alone is not sufficient because GHG emissions of a pulpwood-based pathway in one state can be lower than those of a mill residue-based pathway in another state. Furthermore, the available biomass supply often consists of several woody feedstocks, and its composition is region-dependent. Forest biomass-derived electricity is associated with 86-93% lower life-cycle GHG emissions than the emissions of the average grid electricity in the U.S. Key factors driving bioelectricity GHG emissions include electricity generation efficiency, transportation distance, and energy use for biomass harvesting and processing.
本研究对美国不同地区森林生物质发电的温室气体（GHG）排放进行了从摇篮到坟墓的生命周期分析（LCA），考虑了生物质可用性和物流的区域差异。使用土地利用和资源分配（LURA）模型估算了 20 兆瓦生物电能设施的区域生物质供应。LURA 的结果以及关于区域森林管理、采伐和加工的数据被纳入 GHGs、Regulated Emissions 和 Technologies（GREET）模型进行 LCA。结果表明，基于木屑的途径的 GHG 排放量比基于纸浆材的途径低 15-52%，而原木剩余物则介于两者之间。然而，我们的分析表明，仅根据特定的原料类型筛选生物能源项目是不够的，因为一个州的纸浆材途径的 GHG 排放量可能低于另一个州的木屑途径。此外，可用的生物质供应通常由几种木质原料组成，其组成取决于地区。与美国平均电网电力相比，森林生物质衍生的电力的生命周期 GHG 排放量低 86-93%。驱动生物电能 GHG 排放的关键因素包括发电效率、运输距离以及生物质收获和加工的能源使用。
