In this paper we explore the development of two specific carbon capture technologies, namely Carbon Capture, Transport, and Storage (CCTS) and Direct Air Capture (DAC) with respect to the role attributed to them by long-term climate scenarios. We ask whether the critical assessment in earlier literature of the gap between ambitious targets in top-down energy and climate models and the modest level of real-world implementation still persists. We provide a survey of the full set of projects on CCTS in the energy and industry sectors, as well as of all DAC projects world-wide. For CCTS, we find that although several demonstration projects have been implemented over the past 15 years, the scale of deployment remains low. In the power sector, only a few large-scale projects remain operational as of 2025; others have been delayed or cancelled. Industrial CCTS shows broader engagement, yet most projects remain below the 1 MtCO2 /year threshold. The deployment of DAC, too, has remained at very low levels: While integrated assessment models (e.g., EMF-38 and AR6 scenarios) project deployment of several gigatons per year by 2050, the actual installed DAC capacity in June 2025 remains below 0.05 MtCO2 /year. The paper concludes that while carbon capture remains a compelling field for innovation, the gap between scenario optimism and real-world progress has not closed. This is not the “fault” of the models, but these findings suggest that optimal technology deployment strategies might be more complex to implement than these models suggest.
Month: July 2026
Demand-Side Flexibility under Alternative Electricity Market Designs: Insights from a Multi-Level Modelling Framework
The transformation of the European electricity system from centralized fossil-based generation to a decentralized renewable-based system poses challenges for the current market design with uniform national price zones. This design lacks spatially differentiated investment signals and market incentives for grid-supportive flexibility behavior. This study examines various market design options—such as bidding zone reconfigurations, capacity payments, and dynamic tariffs—and analyzes their combined effects on investment decisions, dispatch and ex-post congestion management. A multi-level electricity market model is applied to the German power system for the year 2030, incorporating market-driven investments and system operation. Results indicate that a uniform price zone leads to suboptimal investment signals and inefficient deployment of flexibility options. Capacity payments can ensure overall installed capacity levels but fail to provide regional incentives. In contrast, zonal pricing reflects structural congestion and aligns investment incentives with grid information, substantially improving flexibility deployment and reducing congestion. Overall, regional price differentiation emerges as the key driver of efficient investment and system operation, while capacity payments and dynamic tariffs only unfold additional value when combined with such locational signals.