Abstract
PurposeA circular (bio)economy is sustained through use of secondary raw material and biomass feedstock. In life cycle assessment (LCA), the approach applied to address the impact of these feedstocks is often unclear, in respect to both handling of the recycled content and End-of-Life recyclability and disposal. Further, the modelling approach adopted to account for land use change (LUC) and biogenic C effects is crucial to defining the impact of biobased commodities on global warming.MethodWe depart from state-of-the-art approaches proposed in literature and apply them to the case of non-biodegradable plastic products manufactured from alternative feedstock, focusing on selected polymers that can be made entirely from secondary raw material or biomass. We focus on global warming and the differences incurred by recycled content, recyclability, LUC, and carbon dynamics (effects of delayed emission of fossil C and temporary storage of biogenic C). To address the recycled content and recyclability, three formulas recently proposed are compared and discussed. Temporary storage of biogenic C is handled applying methods for dynamic accounting. LUC impacts are addressed by applying and comparing a biophysical, global equilibrium and a normative-based approach. These methods are applied to two case studies (rigid plastic for packaging and automotive applications) involving eight polymers.Results and discussionDrawing upon the results, secondary raw material is the feedstock with the lowest global warming impact overall. The results for biobased polymers, while promising in some cases (polybutylene succinate), are significantly affected by the formulas proposed to handle the recycled content and recyclability. We observe that some of the proposed formulas in their current form do not fully capture the effects associated with the biogenic nature of the material when this undergoes recycling and substitutes fossil materials. Furthermore, the way in which the recycled content is modelled is important for wastes already in-use. LUC factors derived with models providing a combined direct and indirect impact contribute with 15–30% of the overall life cycle impact, which in magnitude is comparable to the savings from temporary storage of biogenic C, when included.ConclusionEnd-of-Life formulas can be improved by addition of corrective terms accounting for the relative difference in disposal impacts between the recycled and market-substituted product. This affects the assessment of biobased materials. Inclusion of LUCs effects using economic/biophysical models in addition to (direct) LUC already embedded in commercial datasets may result in double-counting and should be done carefully. Dynamic assessment allows for detailed modelling of the carbon cycle, providing useful insights into the impact associated with biogenic C storage.
Highlights
More than 90% of plastic today is produced from fossil feedstock generating approximately 400 million tonnes of greenhouse gas (GHG) emissions per year globally (World Economic Forum and Foundation, 2016); estimates for 2012)
We present the results in a sequential fashion: (i) we focus on recycled content and recyclability
A = 0 and A = 1; LUC and biogenic C dynamics are not included assuming neutrality as the default); (ii) we add dynamic carbon accounting and characterisation (Fig. 4); and (iii) we add the effects of land use change
Summary
More than 90% of plastic today is produced from fossil feedstock generating approximately 400 million tonnes of greenhouse gas (GHG) emissions per year globally (World Economic Forum and Foundation, 2016); estimates for 2012). When assessing the climate change impact of biobased products, the biogenic C cycle has a strong timedependent nature: the biomass is harvested and transformed into a product, and while the biogenic C is stored in the technosphere during the use phase of the bio-product, the biomass re-grows sequestering atmospheric C O2 through specific dynamic trajectories (i.e. annual crops will re-sequester harvested C O2 every year, while a forest stand will take decades to regrow) The way these phenomena are characterized differs across various studies, based on the choice of climate metrics (instantaneous vs cumulative; Giuntoli et al 2015), the choice of absolute or normalised metrics (Cherubini et al 2013), the choice of reference system (Koponen et al 2018), and the choice of temporal boundaries of the analysis (Brandao et al 2013; Levasseur, 2016; Breton et al 2018). According to this and assuming no consumer’s behavioural changes (e.g. diet), the supply of goods and services should be assumed to be fully elastic, i.e. an increase in demand is to be met by a corresponding (1:1) increase in supply
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
