Environmental Health Insights

With the increasing awareness of health impacts of particulate matter, there is a growing need to comprehend the spatial and temporal variations of the global abundance of ground-level airborne particulate matter (PM₂.₅). Here we use a suite of remote sensing and meteorological data products together with ground based observations of PM₂.₅ from 8,329 measurement sites in 55 countries taken between 1997 and 2014 to train a machine learning algorithm to estimate the daily distributions of PM₂.₅ from 1997 to the present. We demonstrate that the new PM₂.₅ data product can reliably represent global observations of PM₂.₅ for epidemiological studies. An analysis of Baltimore schizophrenia emergency room admissions is presented in terms of the levels of ambient pollution. PM₂.₅ appears to have an impact on some aspects of mental health.