# Bio-Based Polyester Fiber Substitutes: From GWP to a More Comprehensive Environmental Analysis
## 4 Results and Discussion
### Single Score Results  
The aggregate environmental impacts of the fiber were examined through single scores. The results that bring all 16 impact categories together were produced with _Default EF_ and are presented in Figure 5. When all the impacts are addressed jointly, it is shown that only partially bio-based polyesters derived from sugarcane (Scenarios 2A/2B) and PLA fiber (Scenario 7) have comparable performance to conventional polyester. Their  
Figure 4: Contribution of feedstock (agriculture and transport) to the resulting impacts of fibers. Note that 100% of each impact stands for the resulting impact of the fiber in question. Feedstock contributions were calculated for each scenario as (impact of the crop as per _Default EF_ method x feedstock requirement per kg of fiber)/impact of the fiber as per _Default EF_ method. single score results are in the \(\pm 10\%\) range from the said baseline. Conversely, conventional polyester outperforms all other bio-based alternatives, notably all fully bio-based ones just like elaborated midpoint scores had shown. Fully bio-based polyester made from corn (Scenario 3) is characterized by the most substantial increase in environmental impact relative to polyester. The choice of the crop has a decisive impact on the aggregate performance of the fiber, owing to their different environmental intensities. Corn-derived fibers have a higher overall environmental impact relative to the corresponding sugar-derived ones as Scenarios 1 and 2A/2B show. Here, only MEG is substituted with a bio-based form, making sugarcane a better alternative than corn for MEG sourcing. Bio-based PTA is found to have a poorer performance relative to the fossil-based version of the monomer. Due to its relevance for the bio-based C content of the polyester and PTT fibers (80% and 73% C content), the environmental performance of these bio-based fibers hinges on the development of the environmentally sound bio-PTA. On the side of LCA, it should be noted that the modeling of PTA is subject to many approximations, and to increase the accuracy, bio-PTA assessment necessitates either on-site process data or modeling in chemical engineering software. As it stands at present, an increase in the bio-based content is shown to have an adverse effect on the aggregate environmental performance of the bio-based fibers in question. Furthermore, the lighter colored bars in Figure 6 represent the results obtained with the _Modified EF_ method. Three substitute scenarios (2A, 2B, 7) are again shown to have comparable performance to conventional polyester. The remaining bio-based scenarios again show a poorer overall environmental performance, with an increase in the bio-based content resulting in a bigger gap between the two methods. For each scenario, the entire score gap between modified and default EF results stems from the difference in the climate impacts due to carbon crediting. Figure 5: The aggregate environmental impact of polyester and its bio-based substitutes. The results refer to single scores obtained with _Default EF_ method. As a final step, in order to corroborate that non-climate impacts of fibers are highly relevant to the overall environmental performance, we performed a sensitivity analysis of single scores. We applied European distance-to-policy-target weighting factors for the _Default Castellani_ and the _Modified Castellani_ methods (see Materials and Methods). Notably, we find that trends stay largely the same--bio-content in linked to poorer performance of the bio-based fibers, while the gravity of the performance gap increases. Distance-to-target weights show that when climate change is given less priority, the aggregate impacts of the bio-based fibers in fact increase, which demonstrates that the substitution of polyester by bio-based alternatives goes against achieving environmental targets of the EU.