Biogenic Carbon and Temporary Storage Addressed with Dynamic Life Cycle Assessment. (27th July 2012)

• Record Type: Journal Article
• Authors: Levasseur, Annie; Lesage, Pascal; Margni, Manuele; Samson, Réjean
• Is Part Of: Journal of industrial ecology. Volume 17:Number 1(2013:Feb.)
• Page Start: 117
• Page End: 128
• Publication Date: 2012-07-27
• Subjects: Industrial ecology -- Periodicals; Product life cycle -- Environmental aspects -- Periodicals; Industrial management -- Environmental aspects -- Periodicals; Écologie industrielle -- Périodiques; 658.56
• DOI: 10.1111/j.1530-9290.2012.00503.x
• Languages: English
• ISSNs: 1088-1980

Abstract

<abstract abstract-type="main"> <title>Summary</title> <p>A growing tendency in policy making and carbon footprint estimation gives value to temporary carbon storage in biomass products or to delayed greenhouse gas (GHG) emissions. Some life cycle‐based methods, such as the British publicly available specification (PAS) 2050 or the recently published European Commission's <italic>International Reference Life Cycle Data System (ILCD) Handbook</italic>, address this issue. This article shows the importance of consistent consideration of biogenic carbon and timing of GHG emissions in life cycle assessment (LCA) and carbon footprint analysis. We use a fictitious case study assessing the life cycle of a wooden chair for four end‐of‐life scenarios to compare different approaches: traditional LCA with and without consideration of biogenic carbon, the PAS 2050 and <italic>ILCD Handbook</italic> methods, and a dynamic LCA approach. Reliable results require accounting for the timing of every GHG emission, including biogenic carbon flows, as soon as a benefit is given for temporarily storing carbon or delaying GHG emissions. The conclusions of a comparative LCA can change depending on the time horizon chosen for the analysis. The dynamic LCA approach allows for a consistent assessment of the impact, through time, of all GHG emissions (positive) and sequestration (negative). The dynamic LCA is also a valuable approach for decision makers who have to understand the sensitivity of the conclusions to the chosen time horizon.</p> </abstract>