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The global importance of gas-phase peroxy radical accretion reactions for secondary organic aerosol loading

This work outlines an investigation into an understudied atmospheric chemical reaction pathway with the potential to form particulate pollution that has important impacts on air quality and climate. It suggests that this chemical pathway is responsible for a large fraction of the atmospheric particulate matter observed in tropical forested regions, but also highlights the need for further ambient and lab investigations to inform an accurate representation of this process in atmospheric models.

Clear-air turbulence derived from in situ aircraft observation – a weather feature-based typology using ERA5 reanalysis

Turbulence can occur in clear-air conditions at cruising altitude. From around 5000 clear-air turbulence events identified using aircraft measurements, nonlinear breaking of large-scale waves and rapidly ascending airstreams associated with cyclones are found concurrent with 40 % and 30 % of them respectively. The results further show that these weather systems may trigger turbulence by generating highly deformed flow or flow instability, improving our understanding of clear-air turbulence.

Conditions for instability in the climate–carbon cycle system

An increase in CO₂ in the atmosphere warms the climate through the greenhouse effect, but also leads to uptake of CO₂ by the land and ocean. However, the warming is also expected to suppress carbon uptake. If this suppression were strong enough, it could overwhelm the uptake of carbon, leading to a runaway feedback loop causing severe global warming. We find it is possible that this runaway could be relevant in complex climate models and even at the end of the last ice age.

Applications of Machine Learning and Artificial Intelligence in Tropospheric Ozone Research

Machine learning is being more widely used across environmental and climate science. This work reviews the use of machine learning in tropospheric ozone research, focusing on three main application areas in which significant progress has been made. Common challenges in using machine learning across the three areas are highlighted, and future directions for the field are indicated.

Including different mesozooplankton feeding strategies in a biogeochemical ocean model impacts global ocean biomass and carbon cycle

Mesozooplankton gather small current-drifting animals. They are very diverse and play key roles in the functioning of marine ecosystem and carbon cycle, especially through the production of rapidly sinking particles. Usually represented as one compartment, here we add three feeding strategies in an ocean biogeochemical model and investigate their impact on carbon cycle at global scale. We find distinct distributions between mesozooplankton types and diverse contributions to carbon export.

Uncovering the deep structure of the Koillismaa Layered Intrusion Complex, Finland using a novel 3D seismic survey

Solid Earth
DOI 10.5194/se-16-1437-2025
24 November 2025

We acquired and processed novel 3D seismic data to reveal the hidden structure of a deep rock formation in northeastern Finland. This study uncovered a complex, layered system rather than a simple magma channel, and identified a major fault that may influence mineral deposits. Our findings offer new tools and insights for exploring valuable underground resources in hard rock environments.

Conflict-induced ship traffic disruptions constrain cloud sensitivity to stricter marine pollution regulations

Militia attacks on ships in the Red Sea disrupted container ship traffic in 2024. We use these traffic changes to quantify how the cloud-altering properties of ship pollution decreased following sulfur regulations in 2020 with measurements of two types of ship pollution, one of which is sensitive to fuel composition and another which is not. Near Africa, cloud changes in 2024 were nearly as large as before the regulations, but only one-third as strong after accounting for increased traffic.

Novel oxalate-carbonate pathways identified in the tropical dry evergreen forest of Tamil Nadu, India

The oxalate-carbonate pathway, where trees and microbes store inorganic carbon as minerals, was studied on four tree species of the threatened tropical dry evergreen forest Indian forest. We used high-throughput sequencing of a gene to detect oxalate-degrading microbes. For all tree species, produced oxalate led to carbonate formation in soils and on wood. This carbon may be leached into water, suggesting a hidden source of inorganic carbon with implications for climate and conservation.

The frosty frontier: redefining the mid-latitude tropopause using the relative humidity over ice

We present a new technique to determine the tropopause based on the gradient of relative humidity over ice. This approach captures the character of the tropopause remarkably well, both in individual vertical profiles and in long-term averages, providing a consistent and physically meaningful representation of the transition between the troposphere and the stratosphere.

Recent history and future demise of Jostedalsbreen, the largest ice cap in mainland Europe

We model the historical and future evolution of the Jostedalsbreen ice cap in Norway, projecting substantial and largely irreversible mass loss for the 21st century, and that the ice cap will split into three parts. Further mass loss is in the pipeline, with a disappearance during the 22nd century under high emissions. Our study demonstrates an approach to model complex ice masses, highlights uncertainties due to precipitation, and calls for further research on long-term future glacier change.

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