The feasibility of climate action: Bridging the inside and the outside view through feasibility spaces

Abstract

The feasibility of different options to reduce the risks of climate change has engaged scholars for decades. Yet there is no agreement on how to define and assess feasibility. We define feasible as “do‐able under realistic assumptions.” A sound feasibility assessment is based on causal reasoning; enables comparison of feasibility across climate options, contexts, and implementation levels; and reflexively considers the agency of its audience. Global climate scenarios are a good starting point for assessing the feasibility of climate options since they represent causal pathways, quantify implementation levels, and consider policy choices. Yet, scenario developers face difficulties to represent all relevant causalities, assess the realism of assumptions, assign likelihood to potential outcomes, and evaluate the agency of their users, which calls for external feasibility assessments. Existing approaches to feasibility assessment mirror the “inside” and the “outside” view coined by Kahneman and co‐authors. The inside view considers climate change as a unique challenge and seeks to identify barriers that should be overcome by political choice, commitment, and skill. The outside view assesses feasibility through examining historical analogies (reference cases) to the given climate option. Recent studies seek to bridge the inside and the outside views through “feasibility spaces,” by identifying reference cases for a climate option, measuring their outcomes and relevant characteristics, and mapping them together with the expected outcomes and characteristics of the climate option. Feasibility spaces are a promising method to prioritize climate options, realistically assess the achievability of climate goals, and construct scenarios with empirically‐grounded assumptions.This article is categorized under: Climate, History, Society, Culture > Disciplinary Perspectives Assessing Impacts of Climate Change > Representing Uncertainty The Carbon Economy and Climate Mitigation > Decarbonizing Energy and/or Reducing Demand

Simulating institutional heterogeneity in sustainability science

“…For instance, when only qualitative evidence is available or competing theories still exist, quantitative representation of these factors is unlikely to yield solid quantitative conclusions. These factors are thus better treated outside of the numerical models; they can be represented as scenario narratives as a way to generate qualitative insights into their importance, or be used to create relevant indicators for feasibility assessment ( 27 , 61 , 62 ). When quantitative evidence is available, it can be used to constrain model assumptions and parameter values to align better with socio-political realities ( 63 , 64 ).…”

Feasible deployment trajectories of carbon capture and storage compared to the requirements of climate targets

“…1). We use the feasibility space approach [28,41] which compares a target case -in this case future CCS growth -with different reference cases [42,43] for each growth phase (Table 1).…”

“…We address these challenges by building on the tradition of using empirical evidence [15,16,[21][22][23][24][25][26][27] through a set of reference cases or historical technology analogies [28,29], where we contribute with three innovations. First, we analyse historical failure rates (i.e.…”

Probabilities of reaching required diffusion of granular energy technologies in European countries

“…[12][13][14] Hence, recent research increasingly explores ways to conceptualize and quantify real-world feasibility of future energy projections. [15][16][17] One way to model feasible projections is to adopt probabilistic methods by empirically learning from historical data. 6,18,19 Such probabilistic projections do not describe discrete future scenarios anymore, but rather a range of possible future outcomes and thereby combine predictive thinking (forecasting) with indepth uncertainty quantification.…”