Project-level causal inference of a minimum viable scale threshold and adoption band in CCUS-enabled hydrogen

Counts differ because each database indexes a different set of publications. We treat OpenAlex as the canonical count; Google Scholar is not shown (no API, and crawling it violates its ToS).

In this study, we analyze whether adopting carbon capture, utilization, and storage (CCUS) causally raises the deployable capacity of hydrogen projects, and under what scale and infrastructure conditions any such effect emerges. Analyzing 2,437 announced global hydrogen projects (182 with CCUS, 2,255 without) from the IEA Hydrogen Production Projects Database 2025, we apply a project-level multi-estimator causal-inference stack—augmented inverse probability weighting, propensity-score matching, X-Learner and DR-Learner—with binary-segmentation changepoint detection, Rosenbaum-bound and E -value sensitivity, permutation placebos, region-exclusion tests, and independent exposure validation against the IEA CCUS Projects Database. CCUS behaves as a scale- and context-gated amplifier: capacity uplift concentrates in the 500- 1,000 MWel adoption band with a +1.45× within-stratum effect above the minimum-viable ≥500-MWel scale threshold (Rosenbaum Γ = 3.7; E -value = 12.4) and no detectable effect at smaller scales. The finding reframes CCUS-hydrogen policy design, integrated-assessment modeling, and project finance around scale-conditional CO 2 transport-and-storage and policy prerequisites.