Satellite Monitoring for Air Quality and Health

Abstract

Data from satellite instruments provide estimates of gas and particle levels relevant to human health, even pollutants invisible to the human eye. However, the successful interpretation of satellite data requires an understanding of how satellites relate to other data sources, as well as factors affecting their application to health challenges. Drawing from the expertise and experience of the 2016–2020 NASA HAQAST (Health and Air Quality Applied Sciences Team), we present a review of satellite data for air quality and health applications. We include a discussion of satellite data for epidemiological studies and health impact assessments, as well as the use of satellite data to evaluate air quality trends, support air quality regulation, characterize smoke from wildfires, and quantify emission sources. The primary advantage of satellite data compared to in situ measurements, e.g., from air quality monitoring stations, is their spatial coverage. Satellite data can reveal where pollution levels are highest around the world, how levels have changed over daily to decadal periods, and where pollutants are transported from urban to global scales. To date, air quality and health applications have primarily utilized satellite observations and satellite-derived products relevant to near-surface particulate matter <2.5 μm in diameter (PM2.5) and nitrogen dioxide (NO2). Health and air quality communities have grown increasingly engaged in the use of satellite data, and this trend is expected to continue. From health researchers to air quality managers, and from global applications to community impacts, satellite data are transforming the way air pollution exposure is evaluated. Expected final online publication date for the Annual Review of Biomedical Data Science, Volume 4 is July 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Systematizing the approach to air quality measurement and analysis in low and middle income countries

“…(c) Satellite, remote sensing, and modeling systems that are rapidly evolving with ongoing improvements in instrumentation, algorithms, and applications with broad air quality and climate change applications 10 . (d) Low-cost sensor networks, which can be valuable in situations of high spatial and temporal variability in pollution concentrations and when absolutely accurate measurements may not be required 11 .…”

“…It is necessary to have active interactions among experts to ensure the analysis system is dynamic and provides the best possible 10 For example, satellite derived estimates of PM2.5 are helping scientists conduct large-scale air quality and health studies. Furthermore, combining satellite data with on-ground measurements (monitoring) and models can be used to fill data gaps (e.g.in locations without ground-level monitors), improve model simulation, and enhance capacity of monitoring and management of air pollution [11]. 11 Such networks are typically deployed in locations where installation of a conventional network can be expensive or where the network can substantively enhance the air quality monitoring capacity in remote and rural areas.…”

“…Furthermore, combining satellite data with on-ground measurements (monitoring) and models can be used to fill data gaps (e.g.in locations without ground-level monitors), improve model simulation, and enhance capacity of monitoring and management of air pollution [11]. 11 Such networks are typically deployed in locations where installation of a conventional network can be expensive or where the network can substantively enhance the air quality monitoring capacity in remote and rural areas. Deployment of such sensor networks can also be valuable for citizen education and citizen engagement.…”

An improved understanding of NOx emissions in South Asian megacities using TROPOMI NO2 retrievals

“…Air pollution is a significant cause of mortality globally [1]. Satellite remote sensing has enabled great progress in mapping air pollution around the globe [2] and is being used to improve exposure estimates for health effect studies [3]. Many health studies rely on numerical models to evaluate the costs of air pollution and the benefits of policies [4].…”

Technical note: Use of PM2.5 to CO ratio as an indicator of wildfire smoke in urban areas

“…Smoke at the surface can originate from nearby or distant fires (e.g., DeBell et al, 2004;Jaffe et al, 2004;Teakles et al, 2017;Rogers et al, 2020). Satellites can provide an exceptional geospatial view of fires and the occurrence and transport of smoke (e.g., Duncan et al, 2014;Kahn, 2020;O'Neill et al, 2021;Holloway et al, 2021). However, with very few exceptions, satellite data provide little to no vertical information directly.…”