This week’s publication highlights cover a wide range of issues related to the use of low-carbon technologies in the Yangtze River Delta region, forestation in CMIP6 and direct air capture.
Optimal Pathways toward a Carbon-Neutral Power System Considering Low-Carbon Technologies in the Yangtze River Delta Region
Abstract
Because of its important role in China, many scholars have addressed the decarbonization of the Yangtze River Delta Region (YRDR). However, little work has been conducted on appropriate ways to transform the YRDR power system into a carbon-neutral system. This study develops an optimization model to explore the optimal pathways toward a carbon-neutral power system in the YRDR by 2060. In addition to traditional power generation technologies, the model includes carbon tax (or carbon emission cost), carbon capture and storage (CCS), forest carbon sink (FCS), renewable energy, and energy imports from outside the YRDR. The main findings are as follows: (1) in the business-as-usual (BAU) scenario, the YRDR’s power system could reach its carbon peak by 2030, but it would not achieve carbon neutrality by 2060; (2) in the carbon neutrality scenario, FCS could mitigate 88% of the carbon emissions of the YRDR power system; and (3) a high proportion of renewable energy could help transform the YRDR’s power system to a carbon-neutral one, but would increase the cost by 44.8%. The main policy implication is that implementing a carbon tax and promoting renewable energy, FCS, CCS, and other carbon dioxide removal (CDR) technologies should be considered together to transform the YRDR power system.
Zhang, Y. et al. (2025) Optimal Pathways toward a Carbon-Neutral Power System Considering Low-Carbon Technologies in the Yangtze River Delta Region. Journal of Management Science and Engineering.
Read the full paper here: Optimal Pathways toward a Carbon-Neutral Power System Considering Low-Carbon Technologies in the Yangtze River Delta Region. Journal of Management Science and Engineering.
Forestation in CMIP6: Wide Model Spread in Tree Cover and Land Carbon Uptake
Abstract
Forestation is expected to play a significant role as a terrestrial carbon dioxide removal (tCDR) technology in low-emission scenarios by storing carbon in the biosphere, thereby changing the physical properties of the land surface. To represent land use change, including afforestation and reforestation (AR), Earth system models (ESMs) that contribute to the Coupled Model Intercomparison Project Phase 6 (CMIP6) draw on common projected land use data from Integrated Assessment Models (IAMs). The extent and spatial distribution of AR differ substantially between the CMIP6 models ranging from -197 to 363~Mha of tree cover change by 2100 in the low-emission scenario SSP1-2.6 that has the highest AR among all future scenarios. The variability in simulated tree cover distributions, in combination with different representations of the carbon cycle, causes a high uncertainty in future land carbon uptake. Here, we disentangle the input information used to represent AR by CMIP6 models and differences in the carbon uptake process to explain the variable simulated potential of carbon sequestration due to AR. We provide recommendations on how AR might be implemented more consistently in future model intercomparison studies, especially regarding more consistent tree cover input (e.g. aligning present-day tree cover, consistent transition between land use and land cover types), and carbon-cycle-related processes (e.g. nitrogen cycle and disturbances). Adoption of these recommendations would increase the relevance of ESMs in terms of providing more accurate estimates of future land carbon uptake through AR.
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Egerer, S. et al. (2025) Forestation in CMIP6: Wide Model Spread in Tree Cover and Land Carbon Uptake. Environmental Research Letters
Read the full paper here: Forestation in CMIP6: Wide Model Spread in Tree Cover and Land Carbon Uptake I Environmental Research Letters
Direct Air Capture of CO2 for Solar Fuel Production in Flow
Abstract
Direct air capture is an emerging technology to decrease atmospheric CO2 levels, but it is currently costly and the long-term consequences of CO2 storage are uncertain. An alternative approach is to utilize atmospheric CO2 on-site to produce value-added renewable fuels, but current CO2 utilization technologies predominantly require a concentrated CO2 feed or high temperature. Here we report a gas-phase dual-bed direct air carbon capture and utilization flow reactor that produces syngas (CO + H2) through on-site utilization of air-captured CO2 using light without requiring high temperature or pressure. The reactor consists of a bed of solid silica-amine adsorbent to capture aerobic CO2 and produce CO2-free air; concentrated light is used to release the captured CO2 and convert it to syngas over a bed of a silica/alumina-titania-cobalt bis(terpyridine) molecular–semiconductor photocatalyst. We use the oxidation of depolymerized poly(ethylene terephthalate) plastics as the counter-reaction. We envision this technology to operate in a diurnal fashion where CO2 is captured during night-time and converted to syngas under concentrated sunlight during the day.
Kar, S. et al. (2025) Direct Air Capture of CO2 for Solar Fuel Production in Flow. Nature Energy.
Read the full paper here: Direct Air Capture of CO2 for Solar Fuel Production in Flow. Nature Energy.
Large Eddy Simulation of CO2 Direct Air Capture Units in Different Atmospheric Boundary Layer Wind Profiles
Abstract
Direct air capture of CO2 (DAC) is one of the promising technologies for removing CO2 from the atmosphere and combating global warming. This study explores the effect of wind velocity on the atmospheric dispersion of CO2-depleted air released from the outlet of DAC units. This is an important consideration in determining the optimum design and location of DAC units in a large-scale CO2 capture plant and ultimately the overall land footprint requirement. We considered a crosswind cooling tower as a single DAC absorption unit. Following its validation with field-scale and lab-scale experimental data as well as direct numerical simulation (DNS) data, the large eddy simulation (LES) technique was used to simulate the interaction between the longitudinal atmospheric boundary layer wind and the vertical plume of CO2-depleted air exiting the DAC unit. The behaviour of the DAC-wind flow regime depends on the velocity ratio of the DAC vertical flow and the longitudinal wind velocity (RU) which can be divided into three DAC-wind flow regimes: 𝑅𝑈≫1, 𝑅𝑈≈1, and 𝑅𝑈≪1. As the wind velocity increases, the CO2-depleted air is mixed faster with the free-stream atmospheric flow. Some CO2-depleted air re-enters the unit through the leeward inlet at moderate and high wind velocities. Using the LES results, practical statistical relationships were developed for CO2-depleted plume concentration as a function of distance downwind of a DAC unit for different DAC-wind flow regimes. The findings of this study provide insights into the impact of wind on DAC unit performance and the optimal distance required between the units in a large-scale DAC plant.
Eftekharian, E. et al. (2025) Large Eddy Simulation of CO2 Direct Air Capture Units in Different Atmospheric Boundary Layer Wind Profiles. 114 (109824) International Journal of Heat and Fluid Flow.
Read the full paper here: Large Eddy Simulation of CO2 Direct Air Capture Units in Different Atmospheric Boundary Layer Wind Profiles I International Journal of Heat and Fluid Flow.
Planning Negative Emissions Technologies Portfolios under Neutrosophic Environment
Abstract
The deployment of large-scale Negative Emission Technologies (NETs) is now considered a key strategy in climate change mitigation due to their capability to counteract emissions biophysically and economically. However, large-scale NETs will require resources such as land, water, and energy that are limited and uncertainties are present in such technologies. Managing such uncertainties is critical in NET portfolio modeling because they significantly impact the resulting optimized solutions. Existing studies often fail to adequately address these uncertainties, particularly in portfolio optimization, as traditional models often rely on post-optimization sensitivity analysis that does not fully capture the inherent uncertainties in NET performance. This work addresses the research gaps by developing a neutrosophic linear programming (NeLP) model that incorporates membership, non-membership, and indeterminacy components to represent the uncertainties in resource availability, CDR capacities, and synergistic interactions. Unlike previous models, the current novel NeLP model applies different models of uncertainty as neutrosophic sets and adjust expert’s risk tolerance levels providing a more flexible and realistic approach to NET portfolio optimization . The model is demonstrated in two case studies. The results suggest that the carbon dioxide removal (CDR) levels of various options have different behaviors across different risk settings, as illustrated by the two case studies. The changing optimal solutions in response to shifts in risk appetite provide decision-makers with valuable insight into selecting NETs with significant CDR potential for reducing large-scale greenhouse gas emissions
Tapia, J. and Sumagang, M. (2025) Planning Negative Emissions Technologies Portfolios under Neutrosophic Environment. 83 Neutrosophic Sets and Systems.
Read the full paper here: Planning Negative Emissions Technologies Portfolios under Neutrosophic Environment I Neutrosophic Sets and Systems.