Presenter Name: Lazim Abdullah, Norsyahida Zulkifli and Ahmad Termimi Ab Ghani
Submissionid: 198
Abstract
Climate change, characterized by long-term shifts in temperature and weather
patterns, is predominantly driven by human activities. Although numerous factors,
such as carbon dioxide concentration, changes in the Earth’s orbit, ocean currents,
greenhouse gas emissions, and variations in solar energy reflection or absorption,
are recognized as contributors, the degree of their individual impacts remains
unclear and uncertain. This study aims to prioritize the contributing factors to
climate change by employing the VIKOR method integrated with Q-rung Orthopair
Fuzzy Sets (Q-ROFS), a robust approach to handle vagueness and uncertainty in
expert assessments. Five domain experts provided linguistic evaluations regarding
the importance of each contributing factor. The aggregated linguistic data were
analysed using the Q-ROFS-VIKOR model, revealing that two primary factors,
identified as R1 and R2, are the most significant contributors to climate change.
Interestingly, the factor ‘carbon dioxide concentration’ was ranked lowest,
suggesting a relatively negative impact compared to other factors considered. The
findings provide a clearer perspective on the relative significance of various climate
change factors, offering valuable insights for policymakers and researchers in
designing effective mitigation strategies
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