Based on the results from the LCA model, a key contributor to the overall environmental impact is the manufacturing phase, particularly during the production of the eyeglasses. Within this phase, electricity consumption emerges as the dominant factor across all impact categories, highlighting the energy-intensive nature of the production process. This suggests that efforts to reduce environmental burden should prioritize improvements in energy efficiency or the use of renewable energy sources during manufacturing.
In terms of specific materials, the boxboard carton used in packaging stands out as having a significantly higher environmental impact compared to many other materials analyzed. This indicates that while packaging might seem secondary to the product itself, it can contribute disproportionately to the overall footprint, and should therefore be considered a priority area for sustainable design and material substitution.
To further reduce the environmental footprint of reading glasses, two interventions—one involving material redesign and one targeting user behavior—are proposed:
Material Substitution: Titanium to Recycled Aluminum
Titanium, though durable and lightweight, is energy-intensive to produce and results in a high carbon dioxide emissions. Replacing it with recycled aluminum would offer substantial environmental savings. Titanium on average emits 10 tons of CO2 (Springer Nature, 2021), compared to recycled aluminum which on average emits 0.52 tons of CO2 (“As Well As”, 2024). Based on this data, it is evident that recycled aluminum would emit significantly less carbon dioxide. Additionally, although the density of aluminum is 2.7g/cm³ is less than titanium's 4.5 g/cm³ and therefore more material would be necessary to achieve the equivalent strength, there would still be a reduction in emissions with the use of recycled aluminum (Jon, 2025). Switching to recycled aluminum, while ensuring the design is structurally reinforced to maintain strength, could be an intervention that proves to reduce frame production emissions.
Consumer Behavior: Return and Redistribution Program
Another impactful behavioral intervention involves implementing a take-back and redistribution system. Earth 911, an advocacy organization, estimates that around 4 million pairs of eyeglasses are disposed of every year in North America (“How to Recycle, 2024). Thus, intervening in this end of life stage by encouraging consumers to return their used reading glasses after their useful life could significantly reduce the overall environmental footprint. After the consumer “recycles” their eyeglasses, they would be inspected, refurbished if necessary, and redistributed to individuals in need, such as those in underserved communities or low-income countries.
This system diverts used pairs from landfills, further minimizing lifecycle emissions. Awareness campaigns, free return shipping labels, and partnerships with non-profit distribution channels can boost participation and impact.
Some limitations of the study include the fact that the transport in the use and landfill stages were not included because there was no data to reasonably pull to get these numbers. Rather than assuming the transportation in these stages, the transportation was not included due to the absence of reliable data. If included, there would have been significant speculation, which would potentially undermine the validity of the results. By not including these phases, the results display incorrect life cycle categories in terms of carbon footprint and resource depletion.
Additionally, the product is typically made with cellulose acetate, however, the OpenLCA did not have cellulose acetate as an input. Therefore, vinyl acetate was used as an alternative material in the LCA model. Furthermore, typically the cardboard is made from 100% recycled wood pulp, however, this was not an input available. Therefore, folding boxboard carton was used with the packaging being from a supplier in Tennessee. The alternative material choice may present results that differ in energy intensity, production emissions, and end-of-life characteristics. Global warming potential and water consumption results may also not be an accurate depiction of the glasses life cycle.
Another limitation was the lack of data available. There was uncertainty pertaining to where most of the materials used in the production process were sourced from, therefore, there were major assumptions about where most materials came from. In turn, these assumptions affect the analysis of transportation as well. For example, titanium production was assumed to take place in China. There was location uncertainty, and does not account for the fact that the factory used in the LCA model just produced raw titanium and not the frames and screws for the glasses. In turn, these assumptions affect electricity since most of the production process is automated and reliant on electricity. There was no data available on how much electricity the manufacturing process would take to produce the eyeglasses, which skewed the results. Therefore, the limitations highlight how data gaps and modeling assumptions can affect the results and conclusions of the LCA.