According to the United Nations, air pollution kills an estimated seven million people every year, making it one of the biggest environmental health risks of our time. The condition is exacerbated in low to middle income countries, where 98% of urban centers with a population of more than 100,000 people do not meet the World Health Organization’s guidelines.
Air pollution is caused by both anthropogenic and natural events, including cookstoves, coal-fired power plants, vehicle emissions, as well as wildfires and dust storms. It’s critical for air quality managers and public health researchers to monitor air pollutants locally, regionally, and globally to further determine the risk for health conditions or diseases that are exacerbated by poor air quality. This is critical as countries strive to meet the United Nations Sustainable Development Goals (SDGs), specifically Goal 3: Good Health and Well Being for all citizens.
Air pollution is transboundary, often crossing regional to international boundaries. A combination of ground- and satellite-based tools provides a unique view of the globe to better understand the movement and impacts of air pollution events. These measurements help scientists, researchers, and decision makers in forecasting events and assessing conditions in near real-time to make timely decisions.
New to using NASA Earth science data? This pathfinder is designed to help guide you through the process of selecting and using applicable datasets, with guidance on resolutions and direct links to the data sources.
Satellite measurements of aerosols, called aerosol optical thickness, are based on the fact that the particles change the way the atmosphere reflects and absorbs visible and infrared light. AOD data can be integrated with ground-based data to estimate PM2.5.
Trace gases, like nitrogen dioxide, carbon monoxide, etc., are released to the atmosphere through human actions, such as the burning of fossil fuels. Upon inhalation, these gases can cause respiratory issues, making breathing more difficult, as well as exacerbate other conditions, such as asthma and diabetes.
Socioeconomic data on population density, poverty, mortality, etc. coupled with NASA pollutant data provides insight into vulnerable communities with the goal of developing strategies to mitigate risk and exposure to these communities.
Exposure to air pollution (indoor and outdoor) is responsible for about 1 in 9 deaths worldwide. Researchers are using NASA data in combination with public health data to mitigate risks to vulnerable communities.
About the Data
NASA collaborates with other federal entities and international space organizations, including NOAA, USGS, and the European Space Agency (ESA), to collect and distribute air quality data. Many NASA data products provide information on primary (directly emitted) and secondary pollutants (formed by chemical reactions), some of which can serve as precursors to other types of air pollution.
Datasets referenced in this pathfinder are from satellite and airborne sensors shown in the table below, including their spatial and temporal resolutions. Note that many satellites/platforms carry multiple sensors; the table below only lists the primary sensor used in collecting the specified measurement. When available, NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE) provides data to the public within three hours of satellite overpass, which allows for near real-time (NRT) monitoring and decision making (sensors from which select datasets are available in LANCE are marked with *).
Note: This is not an exhaustive list of datasets but rather only includes datasets from NASA's Earth Observing System Data and Information System (EOSDIS).
Measurement of Pollution in the Troposphere (MOPITT)
1° x 1°
Carbon Monoxide, Dust Score, Ozone
Atmospheric Infrared Sounder (AIRS) Level 2 and 3 products
1° x 1°
daily, 8-day, monthly
Use the Data
There are three main ways to use satellite data for policy applications: for qualitative applications, for quantitative applications, and for more advanced analysis. To review these three applications in more detail, view NASA's Health and Air Quality Applied Sciences Team (HAQAST) Getting Started Resource.
For qualitative understanding, satellite images allow air quality managers to see and communicate spatial patterns, atmospheric transport, and trends in air pollution.
Satellite data can also be used to quantify change and relative abundance.
Beyond qualitative and simple quantitative calculations, satellite data support a wide range of advanced analysis, especially when combined with complementary data sources.
Monitoring air quality provides a means to visualize trends, forecast events or movement of pollutants, and respond to events. Aerosol Optical Depth/Thickness (AOD/AOT) provides a measurement of the quantity of light that small particles remove by absorption and scattering within a column. Absorption and scattering is caused by the composition (each element has a unique spectral fingerprint) and color of the particles (light reflects, dark absorbs). For more information on this process, check out the NASA Earth Observatory article, Aerosols and Incoming Sunlight. AOD is not the equivalent of PM2.5, which is the measure of the mass of particles in a specific size range near surface, but with additional processing AOD provides a means of estimating PM2.5, using specific conversion techniques.
NASA's ARSET Program offers satellite remote sensing training that builds the skills to integrate NASA Earth Science data into an agency’s decision-making activities. ARSET has numerous air quality webinars. For example, there are webinars that include R and Python code for accessing and extracting data, deriving annual PM2.5, and applications for health monitoring.
NASA's Multi-Angle Imager for Aerosols (MAIA) investigation will seek to understand how different types of air pollution affect human health. MAIA is set to launch in 2022. Different epidemiological studies are planned for the primary target areas; studies in each area will focus on the health impacts associated with exposure to PM over following timescales - acute, subchronic, and chronic.
NASA's Tropospheric Emissions: Monitoring of Pollution (TEMPO) mission will be a geostationary mission to measure lower tropospheric ozone, formaldehyde and nitrogen dioxide as the primary pollutant gases. TEMPO additionally will measure sulfur dioxide, glyoxal, water vapor, halogen oxides, aerosols, clouds, ultraviolet-B radiation, and foliage properties. The goal is to launch in 2019
ASDC’s Science Outreach Team has made a new interactive ArcGIS StoryMap entitled Introduction to MAIA & TEMPO that gives users a glimpse into two new exciting satellites that will monitor air quality, both of which are scheduled to launch in 2022.
NASA's Air Quality Citizen Science is a citizen science program funded by the Earth Science Data Systems (ESDS) Program to add value to AOD measurements obtained by the Aqua and Terra satellites. Citizen scientists are helping create a network of high quality, "low-cost" sensors in Los Angeles, California; Raleigh, North Carolina; and Delhi, India.
Citizen-Enabled Aerosol Measurements for Satellites (CEAMS) is another citizen science program funded by ESDS to improve our understanding of how aerosols affect local air quality. Citizen scientists take backyard air quality measurements using sun photometers.
NASA's Short-term Prediction Research and Transition Center (SPoRT) is a project to transition unique observations and research capabilities to the operational weather community to improve short-term forecasts on a regional scale. SPoRT provides access to numerous near real-time datasets that provide information on dust transport. Specifically, the GOES-16 satellite’s Advanced Baseline Imager has a dust RGB product. The SPoRT dust guide provides information on dust imagery and the interpretation.
My NASA Data is an effort to develop microsets of Earth science data that are accessible, interesting and useful to the K-12 and citizen scientist communities. My NASA Data's Earth System Data Explorer is a data visualization tool the data has already been cataloged and formatted, so that maps of the data can be easily plotted.
Explore 19 Years of Global Air Quality in Living Atlas showcases how global air quality patterns have changed over time and how poor air quality impacts the human population. The feature layer contains aggregated PM2.5 concentrations offered by SEDAC at multiple geography levels. At each geography level you can learn more about the trends, statistical patterns, and population impact of air quality throughout the world.
Global Air Quality is an Esri story map that shows 19 years of particulate matter in the air.
State of the Global Air, developed as part of the Institute for Health Metrics and Evaluation’s (IHME) annual Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), provides an interactive tool to view and compare the latest air pollution and health data, create custom maps and graphs, and download the images and data.
Global Burden of Diseases, Injuries, and Risk Factors Study, out of the Institute for Health Metrics and Evaluation (IHME) is an independent population health research center at the University of Washington that provides rigorous and comparable measurement of the world's most important health problems and evaluates the strategies used to address them.
Earthdata Search is a tool for data discovery of Earth Observation data collections from EOSDIS, as well as U.S and international agencies across the Earth science disciplines. Users (including those without specific knowledge of the data) can search for and read about data collections, search for data files by date and spatial area, preview browse images, and download or submit requests for data files, with customization for select data collections.
In the project area, you can select to customize your granule. You can reformat the data and output as HDF, NetCDF, ASCII, KML or a GeoTIFF. You can also choose from a variety of projection options. Lastly you can subset the data, obtaining only the bands that are needed.
HDF and NetCDF files can be viewed in Panoply, a cross-platform application that plots geo-referenced and other arrays. Panoply offers additional functionality, such as slicing and plotting arrays, combining arrays, and exporting plots and animations.
Data recipe for downloading a Giovanni map, as NetCDF, and converting to quantified map data in the form of lat-lon-data value ASCII text.
NASA’s EOSDIS Worldview visualization application provides the capability to interactively browse over 1,000 global, full-resolution satellite imagery layers and then download the underlying data. Many of the available imagery layers are updated within three hours of observation, essentially showing the entire Earth as it looks “right now.” This supports time-critical application areas such as wildfire management, air quality measurements, and flood monitoring. Imagery in Worldview is provided by NASA’s Global Imagery Browse Services (GIBS). Worldview now includes nine geostationary imagery layers from the Geostationary Operational Environmental Satellite (GOES) -East, GOES-West and Himawari-8 available at ten minute increments for the last 30 days. These layers include Red Visible, which can be used for analyzing daytime clouds, fog, insolation, and winds; Clean Infrared, which provides cloud top temperature and information about precipitation; and Air Mass RGB, which enables the visualization of the differentiation between air mass types (e.g., dry air, moist air, etc.). These full disk hemispheric views allow for almost real-time viewing of changes occurring around most of the world.
View current natural hazards and events using the Events tab which reveals a list of natural events, including wildfires, tropical storms, and volcanic eruptions.
Animate the imagery over time. Do a screen by screen comparison of data for different time periods or a comparison of different datasets.
Benefits and Limitations to Remote Sensing Data
The United States is fortunate to have numerous ground-based measurements for assessing atmospheric particulate matter and other types of pollution, like ozone or NO2. However, this is not the case in other countries and in more rural areas of the United States. Satellite data provide a more regional to global spatial coverage; some of the information is available in near real-time, allowing for more efficient response. With satellite data, assessments can be made regarding the AOD, which can then be correlated to PM2.5, aerosol types and aerosol transport. Incorporating satellite and in-situ data into modeling programs makes for a more robust and integrated forecasting system. Satellite data also provide enough information to determine exposure and risk categories.
While the data provides a more global view, it’s important to note that the satellites are measuring the vertical column of air above the surface and not at ground level (where the ground-based sensors are measuring). As such, there may be some discrepancies between the two. In addition, many of the polar-orbiting satellites only pass over the same spot every 1-2 days or sometimes every 16+ days, as they are providing near-global coverage. Geostationary satellites, however, which rotate with the Earth, can monitor the fixed location as they rotate every 15-30 minutes. Finding the right instrument or understanding the modeling processes for your area of interest is key.