As we count down to the 4th International Conference on Carbon Dioxide Removal in Milano, we are hosting a series of discussions on the research that will be shaping our sessions this June! 
This research introduces a novel “time-explicit” LCA framework 
to better account for how a rapidly decarbonizing economy affects the actual efficiency of technologies like Direct Air Capture. 
By moving beyond static models, the authors reveal that the timing of emissions and removals is critical 
for accurately measuring long-term climate benefits and policy relevance! 
Read the full paper here: Link 
Full Abstract: Temporal dynamics strongly influence the climate benefits of carbon dioxide removal technologies
Authors: Tom Terlouw, Arthur Jakobs, Romain Sacchi, Christian Bauer
Environmental Life Cycle Assessment (LCA) is a common method for evaluating the net carbon removal efficiency (i.e., the fraction of initially captured CO2​ that is permanently removed from the atmosphere) and the environmental burdens of CDR technologies. However, conventional LCA approaches the global economy as static, overlooking how decarbonization in electricity, steel, and other sectors unfolds over time. Prospective LCA shifts the analysis to future snapshots by incorporating external energy system model scenarios (those from integrated assessment models); however, it does not account for the timing of emissions and removals. Consequently, both approaches miss temporal dynamics that may significantly affect how environmental impacts distribute over time.
Time-explicit LCA aims to capture such temporal aspects by evaluating the timing of emissions and removals during the lifetime of a product system and translating those into time-dependent environmental burdens. The analysis of such time-explicit aspects is particularly relevant for CDR technologies. For example, CDR technologies based on temporary CO2​storage (such as biomass-based CDR) and long-term geological storage (such as direct air capture with storage) can yield different cumulative radiative forcing outcomes, as differences in the timing of CO2​ emissions and removals translate into distinct time-integrated climate forcing profiles. Time-explicit LCA can better assess such differences by: (i) coupling the product life cycle to energy-system transition pathways to better reflect changing LCA background over time, (ii) propagating dynamic retention and decay functions for sequestered CO2​, and (iii) evaluating outcomes using time-sensitive metrics, such as (cumulative) radiative forcing.
In this work, we present novel results from a time-explicit LCA of a solid-sorbent direct air capture with CO2​ storage (DACS) system coupled to the European power grid (with a high-temperature heat pump). The main novelty is the application of two newly developed time-explicit LCA frameworks to assess CDR technologies – using DACS as an example – and systematically compare conventional, prospective, and time-explicit LCA outcomes. We show that climate impacts and benefits are significantly influenced by the LCA approach used. The time-explicit LCA approach applied to DACS results in substantially higher CDR efficiencies (89.0%) than conventional LCA (66.8%), but lower than for prospective LCA (92.3%), primarily due to the explicit representation of declining background power grid mix GHG intensities (using a business-as-usual scenario from REMIND) and the timing of CDR. Overall, we argue that applying time-explicit LCA to CDR will improve the accuracy of sustainability analyses and, in turn, further increase policy relevance. Future work will (i) explore additional time-explicit results for DACS, and (ii) apply the two novel time-explicit LCA frameworks to other CDR technologies.
If time-explicit LCA reveals significantly higher efficiency for technologies like DACS compared to conventional static models, should this approach become the mandatory standard for carbon removal certification and policy-making? 
