Wildfires are becoming more frequent and are ravaging new parts of the world due to global warming. A study led by researchers from the University of Gothenburg shows that this change is increasing the vulnerability of thousands of plants, animals and fungi.

Scientists have found a new way to detect subtle chemical signatures in seawater—revealing previously invisible details about the ocean’s chemistry from data continuously collected by thousands of autonomous robotic floats drifting across the seas.

Tungsten (W), a metal widely used in industries from electronics to ammunition, is increasingly recognized as an environmental contaminant. Once it leaches into water systems, it can become highly mobile, potentially contaminating drinking water sources and posing health risks. In some areas, high levels of tungsten in aquifers have been linked to clusters of childhood leukemia. Despite these concerns, the environmental behavior of tungsten, particularly how it interacts with its surroundings, has remained poorly understood.

Dissolved organic matter (DOM) represents one of the largest and most dynamic pools of organic carbon on Earth. Found in soil, glaciers, rivers, oceans, and the atmosphere, this complex mixture of molecules is fundamental to the global carbon cycle, ecosystem health, and climate regulation. Understanding the source, transformation, and ultimate fate of DOM is critical for predicting environmental changes, yet its immense complexity has long posed a significant challenge to scientists.

A new investigation into air quality in northern China has determined a strong connection between winter domestic heating and elevated levels of carbonaceous aerosol pollution. The study, led by researchers Yuewei Sun and Jing Chen at the State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Beijing Normal University, focused on Yuncheng, a city in the heavily polluted Fenwei Plain. The findings show that during the winter heating period, concentrations of organic and elemental carbon in fine particulate matter PM2.5 increased by over 58 percent.

A new study published in Big Earth Data introduces the Cloud-Aware Mixture-of-Experts Linear Transformer U-Net (CA-MTransU-Net) for precise forest burned area (FBA) detection. By integrating Sentinel-1 SAR and Sentinel-2 optical data, the model overcomes traditional challenges such as cloud contamination and the high computational complexity of standard segmentation models. Achieving the highest mean Intersection-over-Union (mIoU) of 87.00% and an inference speed of 6.26 ms, this architecture significantly outperforms conventional benchmark models, offering a robust and efficient solution for post-fire environmental monitoring.