Page 214 - Materials Chemistry, Second Edition

212 10. Advancing life cycle sustainability assessment using multiple criteria decision making

the most sustainable solution. Similarly, Azapagic et al. (2016) attempted to compare electric-
ity generation scenarios considering the United Kingdom’s (UK) probable future mix by
developing a framework for decision support named “DESIRES.” The study utilized AHP
for weight estimation for social, economic, and environmental indicators, and integrates
the weights for analysis of LCA, LCC, and SLCA for a time horizon of the next 70years
and scope of “cradle to grave.” In another type of application in the energy sector, Gumus
et al. (2016) attempt to select the best wind turbine for wind energy in the United States
(US). TOPSIS is used in combination with environmentally extended input-output based life
cycle assessment (EE-IO-LCA) with multiple socio-economic and environmental indicators.

10.4.5 Consumption and production
The context of production and consumption is important in day to day life and overall op-
eration of society. Therefore, this section attempts to focus on some application of integration
between sustainability assessment with life cycle thinking and MADM. Foolmaun and
Ramjeawon (2013) used AHP for combining LCC, LCA, and SLCA in a study on comparison
of different methods of postconsumer polyethylene terephthalate (PET) bottles consumption
for Mauritius. SLCA was based on UNEP/SETAC guidelines. Similarly, De Luca et al. (2015)
also used AHP to develop a methodology to integrate SLCA with qualitative focus to compare
three different crops of citrus from three different production areas of Calabria in Southern
Italy. Whereas, Angelo et al. (2017) attempted to understand consumption pattern of food and
waste generated from them. The study integrated LCA methodology with a multiattribute
method to develop interactive software, which is used to identify preferred environmental
options for household food waste. Kalbar et al. (2017a) conducted a study on proposing a
method to calculate single scores, which is for environmental decision making and utilized
residential consumption data from Denmark. The study suggests that a liner weighted sum
method is not capable of providing a perspective of stakeholders realistically, and that
TOPSIS, which is a distance-based method was found to be the best MADM method for that
application. In another study, Tziolas et al. (2018) developed a tool that can assess production
from agriculture in multistages involving multiple frameworks of MADM methods (AHP,
VIKOR, ELECTRE, TOPSIS) with life cycle thinking. However, the focus is limited to under-
stand environmental impacts. The above applications of integrated MADM with LCSA
highlight that, although LCC and LCA are widely used, still the majority of studies are
not focusing on SLCA.

10.5 Challenges in the application of MADM for LCSA

As discussed in previous sections, there are many studies applying MADM for LCSA.
However, the detailed analysis of these applications shows that researchers have been facing
numerous challenges while using MADM methods for LCSA application owing to the nature
of LCSA indicators. Hence, below we have discussed in detail major challenges in application
of MADM for LCSA.