This K4DD Rapid Evidence Review collates available evidence on early warning systems and air quality forecasting.
It identifies a diverse and expanding evidence base including academic articles and grey literature (particularly produced by the World Meteorological Organisation (WMO) and UN bodies). The evidence base clearly highlights that predictive capabilities have improved over the last two decades, driven by improved data and new techniques for analysing sources of information i.e., artificial intelligence and machine learning. Despite these advances, the ability to forecast air quality levels remains challenging, particularly beyond two days. There is also a distinct variance in capabilities between data rich and data poor regions.
Explore all K4DD outputs here.