Remote Sensing of Particulate Pollution from Space: Have We Reached the Promised Land?

TLDR

Satellite remote sensing of air quality has progressed over 50 years, with 42 relevant instruments launched since 1995, and recent studies show that aerosol optical depth can estimate ground‑level PM₂.₅ with ±20 % measurement precision and ±30 % prediction accuracy, underscoring the need to integrate satellite, ground, and model data. The study examines which air‑quality applications can benefit from satellite‑derived PM₂.₅ estimates. The review surveys satellite instruments that measure trace gases and aerosol optical depth in columnar form across the stratosphere and troposphere. Satellite data enable event detection, transport modeling, and emission estimation, with AOD measurements achieving ±20 % precision and PM₂.₅ predictions within ±30 % accuracy.

Abstract

Abstract The recent literature on satellite remote sensing of air quality is reviewed. 2009 is the 50th anniversary of the first satellite atmospheric observations. For the first 40 of those years, atmospheric composition measurements, meteorology, and atmospheric structure and dynamics dominated the missions launched. Since 1995, 42 instruments relevant to air quality measurements have been put into orbit. Trace gases such as ozone, nitric oxide, nitrogen dioxide, water, oxygen/tetraoxygen, bromine oxide, sulfur dioxide, formaldehyde, glyoxal, chlorine dioxide, chlorine monoxide, and nitrate radical have been measured in the stratosphere and troposphere in column measurements. Aerosol optical depth (AOD) is a focus of this review and a significant body of literature exists that shows that ground-level fine particulate matter (PM2.5) can be estimated from columnar AOD. Precision of the measurement of AOD is ±20% and the prediction of PM2.5 from AOD is order ±30% in the most careful studies. The air quality needs that can use such predictions are examined. Satellite measurements are important to event detection, transport and model prediction, and emission estimation. It is suggested that ground-based measurements, models, and satellite measurements should be viewed as a system, each component of which is necessary to better understand air quality.