Page 85 - AJWEP-v22i3

Eco versus traditional denim: LCA analysis

example, we assumed ±10% variation in energy and 3. Results and discussion
water consumption values to reflect measurement
uncertainty and operational variability, and a wider 3.1. Life cycle impact comparison between
uncertainty (±20% or more) for processes such as traditional and eco-friendly denim manufacturing
cotton agriculture yields and emissions, which can approaches
vary significantly year-to-year. During the Monte The life-cycle impact results for the two scenarios (per
Carlo analysis, input values were randomly sampled 1,000 pairs of jeans) are summarized in Table 2 and
from assumed distributions (using default log-normal illustrated in Figure 3. Overall, the S2 scenario achieved
uncertainty factors from Ecoinvent where available, notably lower impacts than the S1 scenario across
and expert judgment for others), and the impact results nearly all categories. S2 outperformed S1 in six of the
for S1 and S2 were recalculated for each iteration. seven impact categories, with approximately 30% lower
This produced a distribution of possible outcomes for GHG emissions, 64% lower blue water consumption,
each impact category under both scenarios. We then 50% lower terrestrial acidification potential, 40% lower
examined the extent of overlap between the S1 and S2 eutrophication potential, 41% lower fossil resource
result distributions for each impact category. depletion, and 50% lower HTP. The only category
The Monte Carlo results confirmed that the S2 where S2 did not improve upon S1 was land use, which
scenario’s advantages are statistically robust. In all showed S2 showed a slight increase (~10%) in required
evaluated categories except land use, the impacts of S2 land area. These differences reflect the influence of the
were lower than S1 in over 95% of the simulations. In other sustainable practices implemented in S2’s life cycle.
words, even when accounting for uncertainties in the data, For the climate change (GHG emissions) category,
it is highly unlikely that S2 would perform worse than S1 generates an estimated 20,000 kg of CO -equivalent
2
S1 in those categories. For land use, the results exhibited emissions per 1,000 pairs of jeans, whereas S2 produces
greater overlap between scenarios: in approximately half approximately 14,000 kg of CO -equivalent for the same
2
of the simulations, S2 showed slightly higher land use functional unit, achieving a 30% reduction in carbon
than S1, primarily due to variability in organic cotton footprint. This significant drop is largely explained by
yields. In simulations where more favorable assumptions S2’s cleaner energy mix and higher energy efficiency. S1
were made – such as higher organic yields or the adoption relies on thermal energy from gas/diesel and electricity
of improved farming practices – S2’s land use was from a national grid dominated by natural gas, powering
comparable to, or even marginally lower than, that of S1. the energy-intensive production phases and contributing
Nonetheless, the difference in land use remained relatively heavily to GHG emissions. In contrast, S2 utilizes more
minor in magnitude and did not outweigh the substantial efficient machinery and renewable energy (e.g., solar
environmental benefits demonstrated by S2 across the power), directly reducing CO emissions. Replacing a
2
other impact categories. Overall, the uncertainty analysis portion of fossil fuels with low-carbon alternatives in
indicates that our findings are reliable. The probability S2 further supports this reduction. On a per-unit basis,
that the S1 scenario might outperform the S2 scenario in S2 emits around 14 kg CO versus 20 kg CO per pair of
2
2
any impact category is very low. jeans in S1 – a 6 kg CO saving per denim item. From
2
Table 2. Summary of life cycle environmental impact results for 1,000 pairs of denim trousers under
traditional (S1) versus eco-friendly (S2) scenarios, across key impact categories

Impact category Unit (per 1,000 pairs) S1 S2 Changes in S2 realtive
to S1 (%)
Climate change kg CO -eq 20,000 14,000 −30
2
Water consumption m freshwater 5,500 2,000 −64
3
Terrestrial acidification kg SO -eq 100 50 −50
2
Eutrophication kg PO -eq 7.5 4.5 −40
3
4
Land use m 2 2,500 2,750 +10
FRS kg oil-eq 5,600 3,300 −41
HTP kg 1,4-DCB-eq 1,200 600 −50
Abbreviations: DCB: Dichlorobenzene; Eq: Equivalents; FRS: Fossil resource scarcity; HTP: Human toxicity potential.

Volume 22 Issue 3 (2025) 79 doi: 10.36922/ajwep.6241