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

Changbo Wang, Yuan Chang, Lixiao Zhang, Yongsheng Chen and Mingyue Pang

Energy, 2018, vol. 158, issue C, 121-127

Abstract: 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.

Keywords: Uncertainty; Life cycle assessment (LCA); Biomass power; Greenhouse gas (GHG) emissions; Model selection; System boundary (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544218310612
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:158:y:2018:i:c:p:121-127

DOI: 10.1016/j.energy.2018.06.008

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().