The future of direct air capture in Canada: A systematic scenario-based exploration of barriers and possibilities

Integrated assessment models often overlook the interdependencies of socio-political factors shaping the deployment direct air capture (DAC), leading to projections that may be overly optimistic. To address this gap, we systematically explore the conditions under which DAC may (or not) emerge as a competitive carbon dioxide removal (CDR) option in Canada using the system-theoretical scenario method cross-impact balances (CIB), which accommodates both qualitative and quantitative scenario factors. Based on the literature, we identified 10 key factors affecting DAC deployment such as interjurisdictional regulations, public perception, and clean electricity availability. Their interrelationships were assessed by 27 experts to develop an expert-informed CIB model that identified 15 internally consistent scenarios. Results reveal inter-related constraints that DAC must overcome to become competitive with other CDR methods. The cost of DAC remains a significant barrier; unless technological breakthroughs or economies of scale push costs down, DAC is unlikely to play a major future role. Even with cost improvements, public perception remains key—strong societal opposition, particularly around CO₂ transport and storage infrastructure—can delay or block projects. Additionally, interjurisdictional policy coherence matters to advance DAC deployment. From a domestic decision-maker perspective, some of these barriers—such as DAC cost—are influenced largely by global deployment and may be outside their control. However, others—such as policy coherence—can be shaped by domestic policy action. By integrating expert knowledge of qualitative factors using systematic scenario analysis, this study highlights how different institutional and socio-political configurations condition the feasibility of large-scale DAC deployment in Canada. • Uncovers barriers, enablers of a competitive direct-air-capture sector in Canada • Analyzes interconnections among 10 socio-economic and technological factors • Finds cost, public perception, and policy coherence to be key determining factors • Public perception, policy coherence at low levels neutralize favorable conditions • Demonstrates how qualitative system models complement integrated assessment models