The global production of textiles carries a significant share in global greenhouse gas emissions, with a demand projected to grow. Especially for scope 3 emissions, materials play a significant role, with polyethylene terephthalate (PET) as a dominating fibre material with unique properties. Virgin PET based on fossil oil as the conventional option is non-renewable, not aligning with a sustainable future supply route. Alternative drop-in feedstock options for PET are biobased or recycled. Biobased PET has the potential for an emission reduction, but that is not automatically the case. Also there is a trade-off with a worse performance in other impact categories because of the agricultural production. With recycled PET, there are mechanical and chemical recycling options. Mechanical recycling for fibres is feasible and established as open-loop recycling from bottles. For mechanical recycling from textiles, a blend with virgin PET becomes necessary to maintain the required quality. Chemical recycling is more promising for closed-loop recycling from textile waste, but infrastructure and design barriers are current limitations for its expansion. Because these PET sourcing routes come with different trade-offs and barriers, it is reasonable to explore other routes as well, such as basic oxygen furnace (BOF) gas fermentation and compare them with the alternatives.
In this study, Life Cycle Assessment (LCA) was conducted to determine the climate change impact of BOF gas fermentation-based PET compared to mechanically recycled and fossil-based PET. Then, the results were also compared to literature values for biobased and chemically recycled PET, embedding the results in the context of alternative sourcing routes for PET in the textile industry. In the focus technology of this study, feedstock gases rich in carbon are fermented into ethanol by microorganisms. Through several intermediates, monoethylene glycol (MEG) is made as one of the two main components of PET. Together with pure terephthalic acid (PTA), it is polymerised into PET. Several carbon-rich feedstock gases such as syngas from biomass or wastes, but also reformed natural gas have been explored in previous research and development. However, the commercially available option is to use off-gas from the steel industry from the BOF. Therefore, the examined feedstock in this LCA is BOF gas with a composition of 85% CO and 15% CO2.
With a climate change impact of 4.95 CO2eq / kg PET, fermentation-based PET had the highest impact within the LCA model results of this study, followed by virgin PET (2.93 kg CO2 eq per kg PET) and then mechanically recycled PET (1.05 kg CO2 eq per kg PET). Biobased PET literature values ranged between comparable impacts to mechanically recycled PET up to values higher than all other investigated sourcing alternatives. Chemically recycled PET had an impact between mechanically recycled PET and virgin PET. In terms of environmental contributions, for all alternatives the major share of greenhouse gas emissions was from fossil CO2 (around 80%). Technosphere contribution hotspots were the carbon dioxide released during the fermentation and high voltage electricity production, mainly for the conditioning of the feedstock gas (compression and cooling). Also the provision of the virgin PTA component had a considerable contribution (1.11 CO2eq / kg PET).
Under the current global electricity mix, the gas fermentation technology was concluded to not be an advisable alternative to reduce greenhouse gas emissions. A combination of a best-case renewable electricity scenario, a substitution of the missing energy from the BOF gas in the steel process with wind energy instead of natural gas and an orange-peel based PTA sourcing route could reduce the climate change impact down to be comparable to mechanically recycled PET. However, that result is only valid if the emission credit assumption for the avoided emissions in the steel process holds. Otherwise, the gas fermentation technology emits more greenhouse gas emissions than both conventional alternatives, even under the best-case scenario.