Risk-based Decision Support Tool for Selection and Evaluation of Negative Emissions Technologies

Download or read book Risk-based Decision Support Tool for Selection and Evaluation of Negative Emissions Technologies written by John Frederick D. Tapia and published by Infinite Study. This book was released on with total page 6 pages. Available in PDF, EPUB and Kindle. Book excerpt: As the rate at which climate change is increasing in making an impact to the planet, the need to develop and deploy technologies to reduce greenhouse gas (GHG) emissions becomes increasingly necessary. The United Nations' Sustainable Development Goal 13 (SDG 13) of reducing the effects of climate change would require ambitious actions and implementation towards achieving it. Negative emissions technologies (NETs) will contribute to this goal by reducing GHG concentrations in the atmosphere. Options for NETs are available for integration into energy and climate change policies. Barriers for large-scale implementation are present in each of these technologies; risks are present when it comes to integrating them into climate change mitigation strategies. In this paper, a novel multi-criteria decision analysis (MCDA) tool is developed for ranking and evaluating NETs under different risk levels. The tool is based on integrating the concept of neutrosophic sets into data envelopment analysis, or neutrosophic data envelopment analysis (NDEA) to examine the consequential effect of inefficiencies and uncertainties in the characteristics of different NETs. This considers a decoupled approach to the inherent efficiency, inefficiency, and uncertainty of each technology. A case study is presented to illustrate this tool. Results show the advantages of different NETs under different levels of expert's risk attitude and perception, i.e. tolerance factors. Soil carbon sequestration technology is efficient at tolerance levels from 60 % to 100 % as presented in the results. This can be an effective tool to select which technologies is appropriate in different scenarios.