Air pollution modelling and control represent critical intersections between environmental science, engineering and public policy. Modelling techniques—ranging from deterministic dispersion models and ...

AI is helping scientists detect pollution earlier by combining data from water, air, and soil to spot environmental damage ...

A major review is underway to modernise the methods for modelling air pollutants in NSW, with consultation now open on ...

A new ADB report highlights that accurate pollution measurement at the source, not just modeling its spread, is critical for ...

The Kolmogorov-Arnold Network (abbr. KAN) is a novel neural network architecture inspired by the Kolmogorov-Arnold ...

The lack of air-quality monitoring capabilities across the U.S. affects the health of millions of people and disproportionately impacts minority and low socioeconomic-status communities, say ...

Wildfire fire-induced air pollution is an urgent public health and environmental issue. The frequency, intensity, and duration of wildfires are rising ...