Introduction to a Special Issue of JA&WMA on Exposure Assessment

摘要

I had the privilege to serve as a member of the National Academy of Sciences Panel on Exposure Science in the 21st Century: "A Vision and a Strategy." One of the key conclusions listed in the panel's report is that "Remote Sensing for Exposure Assessment has emerged as a key innovation in exposure science." Earlier applications of satellite-based remote sensing included characterization of air pollution across space and time, especially in areas with sparse monitoring networks or those not accessible to humans. These applications increased over time due to the increasing number of satellite platforms collecting data with better accuracy, spatiotemporal coverage, and accessibility. The concomitant increase of computing power made it easier to access, manage, and analyze remote-sensing data. However, the different satellite products were qualitative with limited spatial or temporal coverage, which limited their use in the field of human exposure assessment and especially health effects. To overcome this obstacle, recent studies have introduced statistical approaches that aim at calibrating remote-sensing data using ground monitoring data or outputs of chemical transport models. In addition to calibration, new statistical models have made it possible to predict exposures when remote-sensing data are not available. Toward this end, these methods employ land use, meteorological, and air pollution monitoring data, among others. Together, these advancements have created a new dynamic where new applications are continuously emerging.