International trade shifts part of the health burden of air pollution across countries. This study shows that about 14–18% of global deaths from fine particulate pollution—800,000 annually—are linked ...

Modeling gas-phase atmospheric chemistry is computationally challenging because the underlying dynamics are high-dimensional (requiring many variables) and stiff (occurring across time-scales). Previo...

PNNL is hiring a Masters Intern - Global Urban Modeling in United States. Review all of the job details and apply today!

Using a simple tropospheric ozone chemistry model, we quantify uncertainty caused by simplifying the model with machine learning Compared to the deterministic simplification method, the probabili...

Uncertainty quantification during atmospheric chemistry modeling is computationally expensive as it typically requires a large number of simulations using complex models. As large-scale modeling...

We developed and applied a machine-learned discretization for one-dimensional (1-D) horizontal passive scalar advection, which is an operator component common to all chemical transport models...

In the United States, smoke from wildfires is undoing progress from the Clean Air Act. In poorer countries, the situation is even worse.