Evaluating negative emissions technologies using neutrosophic data envelopment analysis

Abstract

Growing energy demand due to population growth and economic progress has led to the need for intensive climate change mitigation. Negative emissions technologies (NETs) will play an important role in limiting global warming by reducing greenhouse gas concentration in the atmosphere. Available options for NETs can be integrated into energy and climate change policies. However, this strategy requires an assessment tool to select a suitable set of NETs to be integrated. A mathematical framework considering multiple environmental and economic factors under uncertainty is needed for the assessment tool. This paper has two main contributions: (1) development of a novel multi-criteria decision analysis tool based on data envelopment analysis method under neutrosophic environment, and (2) application of this tool in the evaluation of NETs considering the risks associated with the uncertainties in these technologies. The model incorporates uncertainties that result in risks when higher performance levels are assumed. A novel neutrosophic data envelopment analysis (NDEA) model is developed for evaluating NETs; this approach uses neutrosophic set theory to account for membership, nonmembership and indeterminacy in uncertain parameter values. A case study is presented to illustrated this technique. Then, a representative case study considering four alternative options for bioenergy with carbon capture and storage (BECCS) is used to demonstrate the tool. The performance assessment of candidate NETs based on literature data is made. Results show different characteristics of NETs in terms of their sensitivity to expert’s risk attitude and perception towards the different dimensions of neutrosophic decision-making environment. For instance, the preference of underground storage over ocean storage for BECCS is evident when improving the technology is assumed to be challenging. Various NETs are evaluated; technologies such as BECCS, and afforestation and reforestation show consistent ranking in different decision environments. The capability of the model to account for uncertainties can allow useful insights to be drawn by policy-makers, and thus, accelerate the deployment of NETs.