2024 journal article
Evaluating Cotton Apparel with Dynamic Life Cycle Assessment: The Climate Benefits of Temporary Biogenic Carbon Storage
BIORESOURCES, 19(3), 5074–5095.
author keywords: Biogenic carbon; Dynamic life cycle assessment; Climate change; Cotton sustainability; Circular economy; Regenerative agriculture; Textile sustainability
bioresources.cnr.ncsu.edu (publisher PDF)
Source: Web Of Science
Added: July 17, 2024
Static life cycle assessment (LCA) methodologies fail to consider the temporal profiles of system inputs and outputs (including emission timing), such that they underestimate the benefits of temporarily stored biogenic carbon in bioproducts, such as cotton. This research focuses on greenhouse gas emission timing and applies dynamic emission accounting to the life cycle of cotton woven pants. The significance of temporary biogenic carbon storage and emission timing is illustrated by converting the 2017 Cotton Incorporated static LCA to a dynamic model using the Dynamic Carbon Footprinter (baseline scenario). A reduction in cumulative radiative forcing for dynamic relative to static modeling of 22%, 5%, and 2% are observed at 10-years, 30-years, and 100-years, respectively. Alternative scenarios analyzed include converting cotton woven pants at end of life to bioenergy, to compost, or to building insulation, an alternative cotton production scenario using regenerative agricultural practices, and two pants extended lifetime scenarios. The regenerative agricultural practice scenario provides reductions in cumulative impacts compared to the baseline scenario of 96%, 69%, and 105% after 10, 30, and 100-years, respectively. A 3x extension in the lifetime of pants provides a benefit in reduced cumulative impacts of 31%, 40%, and 41%, after 10, 30, and 100-years, respectively. This case study with cotton demonstrates that dynamic LCA is a useful tool for assessing the benefits of biobased products, and it allows for more nuanced analysis of reductions in climate impacts in both the short- and long-term time horizons.