Browse Articles

The authors investigated the impact of light pollution on astrophotography.

This manuscript investigates the urban heat island (UHI) effect by utilizing two satellite datasets: Landsat (high spatial resolution, lower temporal resolution) and MODIS (lower spatial resolution, high temporal resolution). The authors hypothesized that Landsat would provide better spatial detail, while MODIS would better capture temporal variations. Their analysis in the Washington D.C.–Baltimore region supports these hypotheses, demonstrating that Landsat offers finer spatial details, whereas MODIS provides more consistent seasonal patterns and better detects heatwave frequencies.

This study investigates PFAS contamination in Santa Clarita groundwater, focusing on potential sources. The study employs statistical analysis to assess data quality and trends which allowed them to identified domestic waste, fire extinguisher materials, and food packaging as the most likely sources of contamination.

The authors looked at how nanosilver particles may negatively impact the pond water environment. They used D. magna as an indicator species to look at the impact of different concentrations of nanosilver particles.

The authors studied the ability of deep learning models to predict droughts in the midwestern United States.

The authors looked at how soil temperature changes with fire to develop a sensor system that could aid in earlier detection of fires.

Here the authors present an autonomous drone air filtration system that uses a novel algorithm, the gradient ascent ML particle filter (GA/MLPF), to efficiently locate and mitigate outdoor air pollution. They demonstrate that their GA/MLPF algorithm is significantly more efficient than the conventional gradient ascent algorithm, reducing both the time and number of waypoints needed to find the source of pollution.

The authors looked at the impact of different harvest and feeding treatments on Heterandria formosa over three generations as a model for changes in marine ecosystems.

The authors looked at beach nourishment (a way to combat erosion on coasts) and resulting grain size distribution. Their work is important to understand the dynamics of erosion and it's relation to wave action and the implications this has for efforts to mitigate coastal erosion.

Using machine learning to predict the risk of algae bloom