FEEM Research Seminar on "Evaluating Solar Radiation Management (SRM) Using Cost-Risk Analysis"
12:30 - 14:00
Fondazione Eni Enrico Mattei
Corso Magenta 63
video-conference (at FEEM Venice) and GoToMeeting broadcast available
h. 12.30 Seminar
In Milan a light lunch will follow the seminar for registered participants.
Mohammad Mohammadi Khabbazan, Hamburg University
Following the Paris Agreement highlighting the pursuit of efforts to limit the atmospheric temperature rise to 1.5° C above its pre-industrial level, the research question has been raised that what the role of climate engineering in compliance with 1.5° C-temperature target would be. While SRM offers an option to ameliorate anthropogenic temperature rise, it is not simultaneously expected to entirely compensate for anthropogenic changes in further climate variables.
Here, considering global and regional temperature and precipitation disparities, we ask to what extent a proponent of the temperature targets would apply SRM in conjunction with mitigation. Employing the integrated assessment model MIND, we firstly conduct a deterministic cost-effectiveness analysis (CEA) when both temperature and precipitation targets are activated. Then, we apply cost-risk analysis (CRA), which is a decision analytic framework that makes a trade-off between the expected welfare-loss from climate policy costs and the climate risks from transgressing a climate target, with probabilistic information on CS. We adopt three different scenarios: temperature-risk-only, precipitation-risk-only, and both-risks scenarios. Using CEA, our simulations find no feasible solution to comply with 1.5° C-temperature target by only mitigation in both global and regional settings, which emphasizes the significant role of SRM in reaching this target. Our simulations highlight that by altering the temperature target from 2° C to 1.5° C under CEA, SRM usage either does not change in the regional analysis or decreases in the global analysis, that is, the need for more mitigation. Applying CRA, our findings show infeasibility when the conventional calibration process is used.
As a solution, we circumvent the calibration process by distinguishing between the concept of risk in calibration phase and decision making phase. Our results indicate that in the temperature-risk-only scenario, SRM can reduce all regional temperature risks to zero with negligible cost. However, it matters how regions are weighted in the regional precipitation-risk-only and both-risks scenarios. To sum, in our study, we show the complexities of decision making on the optimal climate policies when regions have different weights and the target changes. This has been mostly ignored in the welfare-based economic studies so far.