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1. Metrics for quantifying the efficiency of atmospheric CO ₂ reduction by marine carbon dioxide removal (mCDR)

   https://doi.org/10.1088/1748-9326/ad7477  

   Yamamoto, Kana; DeVries, Tim; Siegel, David_A (September 2024, Environmental Research Letters)

   Abstract Marine carbon dioxide removal (mCDR) is gaining interest as a tool to meet global climate goals. Because the response of the ocean–atmosphere system to mCDR takes years to centuries, modeling is required to assess the impact of mCDR on atmospheric CO₂reduction. Here, we use a coupled ocean–atmosphere model to quantify the atmospheric CO₂reduction in response to a CDR perturbation. We define two metrics to characterize the atmospheric CO₂response to both instantaneous ocean alkalinity enhancement (OAE) and direct air capture (DAC): the cumulative additionality (α) measures the reduction in atmospheric CO₂relative to the magnitude of the CDR perturbation, while the relative efficiency (ϵ) quantifies the cumulative additionality of mCDR relative to that of DAC. For DAC,αis 100% immediately following CDR deployment, but declines to roughly 50% by 100 years post-deployment as the ocean degasses CO₂in response to the removal of carbon from the atmosphere. For instantaneous OAE,αis zero initially and reaches a maximum of 40%–90% several years to decades later, depending on regional CO₂equilibration rates and ocean circulation processes. The global meanϵapproaches 100% after 40 years, showing that instantaneous OAE is nearly as effective as DAC after several decades. However, there are significant geographic variations, withϵapproaching 100% most rapidly in the low latitudes whileϵstays well under 100% for decades to centuries near deep and intermediate water formation sites. These metrics provide a quantitative framework for evaluating sequestration timescales and carbon market valuation that can be applied to any mCDR strategy. 

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2. Carbon Dioxide Capture at Nucleophilic Hydroxide Sites in Oxidation‐Resistant Cyclodextrin‐Based Metal–Organic Frameworks**

   https://doi.org/10.1002/anie.202206718  

   Zick, Mary E.; Pugh, Suzi M.; Lee, Jung‐Hoon; Forse, Alexander C.; Milner, Phillip J. (June 2022, Angewandte Chemie International Edition)

   Abstract Carbon capture and sequestration (CCS) from industrial point sources and direct air capture are necessary to combat global climate change. A particular challenge faced by amine‐based sorbents—the current leading technology—is poor stability towards O₂. Here, we demonstrate that CO₂chemisorption in γ‐cylodextrin‐based metal–organic frameworks (CD‐MOFs) occurs via HCO₃⁻formation at nucleophilic OH⁻sites within the framework pores, rather than via previously proposed pathways. The new framework KHCO₃CD‐MOF possesses rapid and high‐capacity CO₂uptake, good thermal, oxidative, and cycling stabilities, and selective CO₂capture under mixed gas conditions. Because of its low cost and performance under realistic conditions, KHCO₃CD‐MOF is a promising new platform for CCS. More broadly, our work demonstrates that the encapsulation of reactive OH⁻sites within a porous framework represents a potentially general strategy for the design of oxidation‐resistant adsorbents for CO₂capture. 

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3. Characterizing the Effects of Policy Instruments on Cost and Deployment Trajectories of Direct Air Capture in the U.S. Energy System

   https://doi.org/10.1029/2025EF005924  

   Kanyako, Franklyn; Craig, Michael (June 2025, Earth's Future)

   Abstract Capturing and sequestering carbon dioxide (CO₂) from the atmosphere via large‐scale direct air capture (DAC) deployment is critical for achieving net‐zero emissions. Large‐scale DAC deployment, though, will require significant cost reductions in part through policy and investment support. This study evaluates the impact of policy interventions on DAC cost reduction by integrating energy system optimization and learning curve models. We examine how three policy instruments—incremental deployment, accelerated deployment, and R&D‐driven innovation—impact DAC learning investment, which is the total investment required until the technology achieves cost parity with conventional alternatives or target cost. Our findings show that while incremental deployment demands significant learning investment, R&D‐driven innovation is considerably cheaper at cost reduction. Under a baseline 8% learning rate, incremental deployment may require up to $998 billion to reduce costs from $1,154 to $400/tCO₂, while accelerated deployment support could save approximately $7 billion on that investment. In contrast, R&D support achieves equivalent cost reductions at less than half the investment of incremental deployment. However, the effectiveness of R&D intervention varies with learning rates and R&D breakthroughs. R&D yields net benefits in all cases except at extremely low breakthroughs (5%) and very high learning rates (20%), where they are slightly more expensive. For learning rates below 20%, R&D provides net benefits even at minimal breakthroughs. These findings underscore the need for comprehensive public policy strategies that balance near‐term deployment incentives with long‐term innovation investments if we are to ensure DACS becomes a viable technology for mitigating climate change. 

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4. Land-use emissions play a critical role in land-based mitigation for Paris climate targets

   https://doi.org/10.1038/s41467-018-05340-z  

   Harper, Anna B.; Powell, Tom; Cox, Peter M.; House, Joanna; Huntingford, Chris; Lenton, Timothy M.; Sitch, Stephen; Burke, Eleanor; Chadburn, Sarah E.; Collins, William J.; et al (August 2018, Nature Communications)

   Abstract Scenarios that limit global warming to below 2 °C by 2100 assume significant land-use change to support large-scale carbon dioxide (CO₂) removal from the atmosphere by afforestation/reforestation, avoided deforestation, and Biomass Energy with Carbon Capture and Storage (BECCS). The more ambitious mitigation scenarios require even greater land area for mitigation and/or earlier adoption of CO₂removal strategies. Here we show that additional land-use change to meet a 1.5 °C climate change target could result in net losses of carbon from the land. The effectiveness of BECCS strongly depends on several assumptions related to the choice of biomass, the fate of initial above ground biomass, and the fossil-fuel emissions offset in the energy system. Depending on these factors, carbon removed from the atmosphere through BECCS could easily be offset by losses due to land-use change. If BECCS involves replacing high-carbon content ecosystems with crops, then forest-based mitigation could be more efficient for atmospheric CO₂removal than BECCS. 

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5. Rapid design of top-performing metal-organic frameworks with qualitative representations of building blocks

   https://doi.org/10.1038/s41524-023-01125-1  

   Comlek, Yigitcan; Pham, Thang Duc; Snurr, Randall Q.; Chen, Wei (September 2023, npj Computational Materials)

   Abstract Data-driven materials design often encounters challenges where systems possess qualitative (categorical) information. Specifically, representing Metal-organic frameworks (MOFs) through different building blocks poses a challenge for designers to incorporate qualitative information into design optimization, and leads to a combinatorial challenge, with large number of MOFs that could be explored. In this work, we integrated Latent Variable Gaussian Process (LVGP) and Multi-Objective Batch-Bayesian Optimization (MOBBO) to identify top-performing MOFs adaptively, autonomously, and efficiently. We showcased that our method (i) requires no specific physical descriptors and only uses building blocks that construct the MOFs for global optimization through qualitative representations, (ii) is application and property independent, and (iii) provides an interpretable model of building blocks with physical justification. By searching only ~1% of the design space, LVGP-MOBBO identified all MOFs on the Pareto front and 97% of the 50 top-performing designs for the CO₂working capacity and CO₂/N₂selectivity properties. 

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