Florida’s Lake Okeechobee is essential for water management but faces harmful algal blooms, which thrive in warm, nutrient-rich waters.  Daily vertical migration enables them to survive in turbid conditions. A new study using a physical-biogeochemical model reveals that cyanobacteria move toward the surface for sunlight in the morning, boosting growth, and are redistributed by wind and mixing at night. This daily migration, combined with temperature and wind patterns, influences bloom development, offering insights to better monitor and manage harmful algal blooms.

A new FAU survey reveals that more than two-thirds of Floridians are moderately or extremely concerned about hurricanes increasing in strength and frequency, and more than half are worried about the ability to afford and maintain homeowners insurance due to climate change. Nearly two-thirds of Floridians believe that state and federal governments should be doing more to address the impacts of climate change. Most also support expanding the use of renewable energy. About 88% of all Floridians believe climate change is happening.

Biomass is currently the EU’s largest renewable energy source, but climate strategies often focus on other energy sources. A comprehensive analysis, led by Chalmers University of Technology in Sweden, now shows that biomass is crucial for Europe's ability to reach its climate targets, as it can be used to produce fossil-free fuels and chemicals and also enables carbon dioxide removal from the atmosphere. If biomass were excluded from the European energy system, it would cost an extra 169 billion Euros per year – about the same as the cost of excluding wind power.

Dust-on-snow is a major threat to water in the Colorado River, yet no snowmelt forecasts integrate dust-accelerated melt. Using pioneering remote sensing techniques, new research is the first to capture how dust impacts the headwaters of the Colorado River system. The new method could help predict the timing and magnitude of snow darkening and impacts on melt rates on snowpacks, in real time.

A NIMS research team has developed an approach capable of accurately and  short-timeframe predicting the degradation behavior of electrocatalysts used in water electrolyzers by employing data assimilation—a method commonly employed in weather forecasting. After analyzing only 300 hours of experimental data, this approach accurately predicted the degradation of an electrocatalytic material occurring after approximately 900 hours of water electrolysis. This approach is able to accelerate and simplify the comparison of degradation properties among various electrocatalytic materials, potentially facilitating investigations into their degradation mechanisms and expediting the development of more efficient, economical and durable electrocatalytic materials.