Ranking negative emissions technologies under uncertainty

W Y Ng; C X Low; Z A Putra; K B Aviso; M A B Promentilla; R R Tan

doi:10.1016/j.heliyon.2020.e05730

Ranking negative emissions technologies under uncertainty

Heliyon. 2020 Dec 18;6(12):e05730. doi: 10.1016/j.heliyon.2020.e05730. eCollection 2020 Dec.

Authors

W Y Ng¹, C X Low¹, Z A Putra¹, K B Aviso², M A B Promentilla², R R Tan²

Affiliations

¹ Chemical Engineering Department, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, 32610 Perak, Malaysia.
² Chemical Engineering Department, De La Salle University, 0922 Manila, Philippines.

Abstract

Existing mitigation strategies to reduce greenhouse gas (GHG) emissions are inadequate to reach the target emission reductions set in the Paris Agreement. Hence, the deployment of negative emission technologies (NETs) is imperative. Given that there are multiple available NETs that need to be evaluated based on multiple criteria, there is a need for a systematic method for ranking and prioritizing them. Furthermore, the uncertainty in estimating the techno-economic performance levels of NETs is a major challenge. In this work, an integrated model of fuzzy analytical hierarchy process (AHP) and interval-extended Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is proposed to address the multiple criteria, together with data uncertainties. The potential of NETs is assessed through the application of this hybrid decision model. Sensitivity analysis is also conducted to evaluate the robustness of the ranking generated. The result shows Bioenergy with Carbon Capture and Storage (BECCS) as the most optimal alternative for achieving negative emission goals since it performed robustly in the different criteria considered. Meanwhile, energy requirement emerged as the most preferred or critical criterion in the deployment of NETs based on the decision-maker. This paper renders a new research perspective for evaluating the viability of NETs and extends the domains of the fuzzy AHP and interval-extended TOPSIS hybrid model.

Keywords: Chemical engineering; Decision analysis; Environmental science; Fuzzy analytic hierarchy process; Negative emission technologies; Technique for order preference by similarity to ideal solution; Uncertainty.