Global climate and weather forecasting use predictive models which divide the Earth’s atmosphere into a grid, with each section typically covering tens to hundreds of kilometers. Now a new model, run by a team at the University of Tokyo, has narrowed this grid spacing down to just 220 meters. This higher resolution removed instances of “popcornlike” rain, bursts of heavy rain which appear on simulations but not in real life, providing more accurate predictions of extreme local weather from a global model.

Researchers tracked air pollution at 15 monitoring sites across New York City during the first year of the country’s first congestion pricing program.

Fine particulate pollution inside the congestion zone fell about 13 percent beyond what regional trends, weather and year-to-year variability would predict.

The decline closely matched the roughly 11 percent drop in vehicles entering the zone, though pollution had already been falling citywide for other reasons.

Nitrogen dioxide dropped more than 20 percent across the metro area, but the study could not attribute that regional decline to congestion pricing.