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Health and Air Quality Data Pathfinder

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.

After getting started here, there are numerous NASA resources that can help develop your skills further. If you are new to remote sensing, check out What is Remote Sensing? or view NASA's Applied Remote Sensing Training on Fundamentals of Remote Sensing.

Air quality is a global issue as seen here in cities around the world . Credit: National Center for Atmospheric Research (NCAR)

Air quality is a global issue as seen here in cities around the world. Credit: National Center for Atmospheric Research (NCAR)

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.

About the Data

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 Satellite Sensor Spatial Resolution Temporal Resolution
Aerosol Index, Aerosol Optical Depth, Nitrogen Dioxide, Ozone, Sulfur Dioxide Aura Ozone Monitoring Instrument (OMI) 13km x 24km daily
Aerosol Index, Carbon Monoxide, Nitrogen Dioxide, Ozone, Sulfur Dioxide ESA Sentinel-5P TROPOspheric Monitoring Instrument (TROPOMI) 7km x 3.5km daily
Aerosol Index, Sulfur Dioxide NASA/NOAA Suomi National Polar-orbiting Parternship (Suomi NPP) Ozone Mapping and Profiler Suite (OMPS) 50km x 50km 101 minutes, daily
Aerosol Optical Depth, Land Surface Reflectance Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) 250m, 500m, 1km 1-2 days
Aerosol Optical Depth, Land Surface Reflectance NASA/NOAA Suomi-NPP Visible Infrared Imaging Radiometer Suite (VIIRS) 375-750m 1-2 days
Carbon Monoxide Terra Measurement of Pollution in the Troposphere (MOPITT) 1° x 1° daily, monthly
Carbon Monoxide, Dust Score, Ozone Aqua Atmospheric Infrared Sounder (AIRS) Level 2 and 3 products 1° x 1° daily, 8-day, monthly

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Use the Data

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.
Particulate pollution can be measured qualitatively through visual imagery as with the Camp Fire smoke plume in the image on the left. Particulate matter and trace gases can be measured quantitatively through atmospheric column products, like the nitrogen dioxide data from the Aura Ozone Monitoring Instrument, in the image on the right.

Particulate pollution can be measured qualitatively through visual imagery as with the Camp Fire smoke plume in the image on the left. Particulate matter and trace gases can be measured quantitatively through atmospheric column products, like the nitrogen dioxide data from the Aura Ozone Monitoring Instrument, in the image on the right.

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.

Use Cases:

Find AOD Data

Find AOD Data

Screenshot showing 2 world maps displaying burning fires and a second map showing average monthly aerosol amounts.

Locations of burning fires (top image) compared to average monthly aerosol optical depth (bottom image).

AOD is a column-integrated value of aerosols in the atmosphere obtained by measuring the scattering and absorption of solar energy from the top of the atmosphere to the surface. The non-aerosol signal of surface reflectance needs to be separated from the aerosol signal to accurately obtain an AOD. This is challenging because the satellite instrument cannot penetrate cloud cover and highly reflective surfaces, such as ice or snow, producing misrepresentations of the data. As such, scientists have developed algorithms for Moderate Resolution Imaging Spectroradiometer (MODIS) data to help with these effects, dark target and deep blue. For more information on these algorithms see: Dark Target Algorithm and Deep Blue Algorithm. In the latest dataset collection, these two have been merged, using the highest quality for each. While it does provide the easiest use of global coverage, there are some risks (see the websites above for more information).

The Visible Infrared Imaging Radiometer Suite (VIIRS), aboard the joint NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) satellite, also collects AOD data at a much finer spatial resolution. VIIRS uses the Deep Blue (DB) algorithm over land and the Satellite Ocean Aerosol Retrieval (SOAR) algorithm over water to determine atmospheric aerosol loading for daytime cloud-free, snow-free scenes. With all of the VIIRS data, downloading a file will provide the data with just the land algorithm, just the ocean algorithm, and the merged algorithm. As with all remote sensing data, make sure you are choosing the best product for your area.

Data Products for Measuring AOD

Research quality data products can be accessed via Earthdata Search. Data are in HDF or NetCDF format, and can be opened using Panoply.

Data products can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, or a time series through an online interactive tool, Giovanni. Follow these steps to plot data in Giovanni: 1) Select a map plot type; for more information on choosing a type of plot, see the Giovanni User Manual. 2) Select a date range. Data are in multiple temporal resolutions, so be sure to note the start and end date to ensure you access the desired dataset. 3) Check the box of the variable in the left column that you'd like to include and then plot the data.

  • OMI AOD in Giovanni
    The Ozone Monitoring Instrument (OMI) on Aura has a coarser spatial resolution than MODIS and VIIRS but provides data at individual wavelengths from the ultraviolet (UV) to the visible. Within Giovanni, you can plot daily data at these individual wavelengths. This is important because pollutants have different spectral signatures; for example, a wavelength range around 400 nm can be used to detect elevated layers of absorbing aerosols such as biomass burning and desert dust plumes. The two AOD products provided through Giovanni use two different algorithms—OMI Multi-wavelength (OMAERO) and OMI UV (OMAERUV). OMI Multi-wavelength (OMAERO) is based on the multi-wavelength algorithm and uses up to 20 wavelength bands between 331 nm and 500 nm. This algorithm uses reflectances for a wide variety of microphysical aerosol models representative of desert dust, biomass burning, volcanic, and weakly absorbing aerosol types. OMI UV (OMAERUV) uses the near-UV algorithm, which is capable of retrieving aerosol properties over a wider variety of land surfaces than is possible using measurements only in the visible or near-IR, because the reflectance of all terrestrial surfaces (not covered with snow) is small in the UV.
  • MODIS AOD in Giovanni
    Provides data products with both algorithms as well as the combined algorithm at daily and monthly intervals.

NRT data can be accessed via Worldview:

  • MODIS Aqua/Terra Combined Algorithm AOD
    The merged Dark Target/Deep Blue AOD layer provides a more global, synoptic view of AOD over land and ocean. It is available from 2000 to the present.
  • VIIRS Level 2 Deep Blue Aerosol Product
    The product uses the Deep Blue algorithm over land and the Satellite Ocean Aerosol Retrieval (SOAR) algorithm over water to determine atmospheric aerosol loading. The product is designed to facilitate continuity in the aerosol record. Deep Blue uses measurements from multiple Earth observing satellites to determine the concentration of atmospheric aerosols along with the properties of these aerosols.
  • OMI AOD Multi-wavelength and UV
    The multi-wavelength layer and the UV absorbing layer displays the degree to which airborne particles (aerosols) prevent the transmission of light through the process of absorption (attenuation), and the UV extinction layer indicates the level at which particles in the air (aerosols) prevent light (extinction of light) from traveling through the atmosphere. Toggling between these three can provide more distinction on the types of aerosols present.

The Applied Remote Sensing Training (ARSET) program has a Jupyter Notebook that accesses VIIRS AOD data and converts AOD to PM2.5, available through the ARSET GitHub site. For more information on using this notebook, view the MODIS to VIIRS Transition for Air Quality Applications and other Health and Air Quality Trainings.

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AOD to PM2.5

AOD to PM2.5

As mentioned above, AOD is the quantity of light removed from a beam by scattering or absorbing during its path through a medium and is a unitless measure. PM2.5, on the other hand, is a measure of the mass of particles in a specific size range within a given volume of air near the surface. So there are a few differences:

  • AOD is an optical measurement, PM2.5 a mass concentration measurement.
  • AOD is an integrated column measurement from the top of the atmosphere to the surface, PM2.5 a ground measurement.
  • AOD is an area-averaged measurement, PM2.5 a point measurement.

Because the two measurements are so different, it may seem that there is no correlation. They do correlate and there are several different techniques to convert from AOD to PM2.5. It is important to note that while there is a relationship between AOD and PM2.5, there are other factors which can affect AOD, like humidity, the vertical distribution of aerosols, and the shape of the particles. For example, an increase in humidity will increase the size of particles and therefore increase the AOD even though the PM2.5 level will be the same.

The different techniques are a two-variable method, a multivariate method using neural networks, and combining satellite data, in-situ data, and models. The latter approach is the most difficult but generally preferred. 

The Applied Remote Sensing Training (ARSET) program has a Jupyter Notebook that accesses VIIRS AOD data and converts AOD to PM2.5, available through the ARSET GitHub site. For more information on using this notebook, view the MODIS to VIIRS Transition for Air Quality Applications and other Health and Air Quality Trainings.

Aerosol optical depth can be used as a source of particulate matter with a diameter of less than 2.5 micrometers through various mathematical methods. Moving from a two-variable method to a multi-variable method increases in complexity, thereby increasing the difficulty level.

Aerosol optical depth can be used as a source of particulate matter with a diameter of less than 2.5 micrometers through various mathematical methods. Moving from a two-variable method to a multi-variable method increases in complexity, thereby increasing the difficulty level. Source: NASA Applied Remote Sensing Training

Ground-based AOD measurements are available online at the Aerosol Robotic Network (AERONET). The Environmental Protection Agency’s ground-based PM and Ozone combined Air Quality Index (AQI) can be accessed at AirNow. AirNow International is an international program for AQI, with information provided from partnering organizations.

For trends in PM2.5, there are several resources that utilize both ground-based and remote sensing data.

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Find Trace Gas Data

Find Trace Gas Data

Nitrogen Dioxide | Sulfur Dioxide | Carbon Monoxide | Ozone

Nitrogen Dioxide, Carbon Monoxide, Sulfur Dioxide, and Ozone are also available through geospatial web map services. For information on accessing the data within a GIS program, view the Atmosphere Geospatial Services within the GIS Data Pathfinder.

Nitrogen Dioxide

Nitrogen Dioxide (NO2) is a pollutant, the primary sources being the burning of fossil fuels, automobiles, and industry. Once in the air, it can aggravate respiratory conditions in humans, especially those with asthma, leading to an increase of symptoms, hospital admissions, and emergency visits. Long-term exposure can lead to the development of asthma and potentially increase susceptibility to respiratory infections. NO2 reacts with other chemicals in the atmosphere, forming particulate matter and ozone, producing haze and even acid rain, and contributing to nitrogen pollution in coastal waters. NASA Goddard’s Air Quality site provides more information on NO2, as well as trend maps and pre-made images of NO2 over cities and power plants.

Research quality data products can be accessed via Earthdata Search:

Data products can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, or a time series through an online interactive tool, Giovanni. Follow these steps to plot data in Giovanni: 1) Select a map plot type; for more information on choosing a type of plot, see the Giovanni User Manual. 2) Select a date range. Data are in multiple temporal resolutions, so be sure to note the start and end date to ensure you access the desired dataset. 3) Check the box of the variable in the left column that you'd like to include and then plot the data.

NRT data can be accessed via Worldview:

NASA also has a global nitrogen dioxide monitoring site that provides imagery of daily NO2 from OMI.

Sulfur Dioxide

Sulfur dioxide measurements from Aura's Ozone Monitoring Instrument (OMI).

Sulfur dioxide measurements from Aura's Ozone Monitoring Instrument (OMI). Source: NASA Aura

Ozone Monitoring Instrument

Sulfur Dioxide (SO2) is a pollutant of great concern; the primary sources are the burning of fossil fuels by power plants and industry. Volcanic emissions also contribute SO2, but in relatively smaller quantities. As with NO2, it can aggravate respiratory conditions in humans, especially those with asthma, leading to an increase of symptoms, hospital admissions, and emergency visits. In areas where there are high levels, sulfur oxides can react with other components creating small particles which contribute to overall particulate matter, which can be ingested by humans, affecting their health, and creates lower visibility in areas where SO2 is high. SO2 can also lead to acid rain.

Research quality data products can be accessed via Earthdata Search:

  • OMI SO2 Data from Earthdata Search
    OMI provides daily total column data at a resolution of 13x24 km; data are in HDF5 format, and can be opened using Panoply.
  • OMPS SO2 Data from Earthdata Search
    SO2 Total and Tropospheric Column data from the Ozone Mapping and Profiling Suite (OMPS) Nadir-Mapper (NM) sensor, aboard the Suomi NPP satellite; data are in HDF5 format, and can be opened using Panoply. Note that the data are at the various atmospheric levels (planetary boundary layer, stratospheric layer, and tropospheric layers).
  • TROPOMI SO2 data from Earthdata Search
    ESA TROPOMI SO2 provides additional information on this level 2 data product. As with the NO2 data above, you will need to adjust the scaling factor. Data are in NetCDF format, and can be opened using Panoply.

Data products can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, or a time series through an online interactive tool, Giovanni. Follow these steps to plot data in Giovanni: 1) Select a map plot type; for more information on choosing a type of plot, see the Giovanni User Manual. 2) Select a date range. Data are in multiple temporal resolutions, so be sure to note the start and end date to ensure you access the desired dataset. 3) Check the box of the variable in the left column that you'd like to include and then plot the data.

NRT data can be accessed via Worldview:

NASA also has a global sulfur dioxide monitoring site that provides imagery of daily SO2 from OMI, OMPS, and TROPOMI. The site also provides information on the source of emissions.

Carbon Monoxide

Carbon Monoxide (CO) is a harmful pollutant that is released when something is burned, such as in the combustion of fossil fuels, the primary source, or biomass burning. Outdoor levels are rarely high enough to cause issues; when they do reach dangerous levels, however, they can be of concern to people with certain types of heart disease.

Research quality data products can be accessed via Earthdata Search:

  • AIRS CO data from Earthdata Search
    Atmospheric Infrared Sounder (AIRS) measures abundances of trace components in the atmosphere including CO. Data are available daily (AIRS3STD), over 8 days (AIRS3ST8), or monthly (AIRS3STM). The instrument measures the amount of CO in the total vertical column profile of the atmosphere (from Earth’s surface to top-of-atmosphere). Data are in HDF format, and can be opened using Panoply.
  • MOPITT CO data from Earthdata Search
    Measurements of Pollution in the Troposphere (MOPITT) measures the amount of CO present in the total vertical column of the lower atmosphere (troposphere) and is measured in mole per square centimeter (mol/cm2). Data are available daily or monthly. Data are acquired using the thermal and near-infrared channels. Data are in HDF5 format, and can be opened using Panoply.
  • TROPOMI CO data from Earthdata Search
    ESA TROPOMI CO provides additional information on this level 2 data product. As with the NO2 data above, you will need to adjust the scaling factor. Data are in NetCDF format, and can be opened using Panoply.

Data products can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, or a time series through an online interactive tool, Giovanni. Follow these steps to plot data in Giovanni: 1) Select a map plot type; for more information on choosing a type of plot, see the Giovanni User Manual. 2) Select a date range. Data are in multiple temporal resolutions, so be sure to note the start and end date to ensure you access the desired dataset. 3) Check the box of the variable in the left column that you'd like to include and then plot the data.

NRT data can be accessed via Worldview:

  • AIRS CO data in Worldview: AIRS Level 2 data are nominally 45 km/pixel at the equator but the data in Worldview has been resampled into a 32 km/pixel visualization. The data are in units of parts per billion by volume at the 500 hPa pressure level, approximately 5500 meters (18,000 feet) above sea level.
  • MOPITT CO data in Worldview

Ozone

Ozone (O3) can be either good or bad, depending on where it is found in the atmosphere. In the stratosphere, O3 protects humans, plants, and animals from harmful UV radiation. In the troposphere or closer to the ground level, however, O3 serves as a potent greenhouse gas and can aggravate existing health problems in humans, especially those with respiratory illnesses. O3 is not emitted directly into the atmosphere but instead forms from the chemical reaction between nitrogen oxides and volatile organic compounds, emitted primarily from cars, power plants, and other industrial facilities; reactions take place in the presence of sunlight. Because of the need for sunlight, unhealthy levels are most often reached on very sunny days and in urban environments.

Ozone can be either good or bad, depending on where it is found in the atmosphere. In the stratosphere, ozone protects humans, plants, and animals from harmful UV radiation. In the troposphere or closer to the ground level, however, ozone serves as a potent greenhouse gas and can aggravate existing health problems in humans.

Ozone can be either good or bad, depending on where it is found in the atmosphere. In the stratosphere, ozone protects humans, plants, and animals from harmful UV radiation. In the troposphere or closer to the ground level, however, ozone serves as a potent greenhouse gas and can aggravate existing health problems in humans. Source: NASA Aura

Research quality data products can be accessed via Earthdata Search. There are several options and determining which to use can be a challenge. The table in About the Data may be of use as it provides information on spatial and temporal resolution.

  • AIRS O3 data from Earthdata Search
    AIRS measures abundances of trace components in the atmosphere including ozone. Data are available daily (AIRS3STD), over 8 days (AIRS3ST8), or monthly (AIRS3STM). The instrument measures the amount of O3 in the total vertical column profile of the atmosphere (from Earth’s surface to top-of-atmosphere). Data are in HDF format, and can be opened using Panoply.
  • TROPOMI O3 data from Earthdata Search
    ESA TROPOMI O3 provides additional information on this level 2 data product. Data are in NetCDF format, and can be opened using Panoply.

Data products can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, or a time series through an online interactive tool, Giovanni. Follow these steps to plot data in Giovanni: 1) Select a map plot type; for more information on choosing a type of plot, see the Giovanni User Manual. 2) Select a date range. Data are in multiple temporal resolutions, so be sure to note the start and end date to ensure you access the desired dataset. 3) Check the box of the variable in the left column that you'd like to include and then plot the data.

NRT data can be accessed via Worldview:

Trends on a national and regional level are available through the Environmental Protection Agency’s Air Quality Trends.

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Find Pollutant Transport Data

Find Pollutant Transport Data

Aerosol Index | Dust Score | Surface Reflectance

Aerosol Index

Aerosol Index (AI) is a measurement related to AOD and indicates the presence of an increased amount of aerosols in the atmosphere. The main aerosol types that cause signals detected in this value are desert dust, significant fire events, biomass burning, and volcanic ash plumes. The lower the AI, the clearer the sky.

During one day in August, tropical cyclones, dust storms, and fires spread tiny particles throughout the atmosphere.

During one day in August, tropical cyclones, dust storms, and fires spread tiny particles throughout the atmosphere. Source: NASA Earth Observatory

Research quality data products can be accessed via Earthdata Search.

  • OMI AI from Earthdata Search
    OMI provides an Ultraviolet Aerosol Index; data are in HDF5 format, and can be opened using Panoply. Note that when opening the data in Panoply, there are a number of different data fields from which to choose. Select UVAerosolIndex.
  • TROPOMI AI data from Earthdata Search
    ESA TROPOMI AI provides additional information on this level 2 data product. Data are NetCDF format, and can be opened using Panoply.

Data products can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, or a time series through an online interactive tool, Giovanni. Follow these steps to plot data in Giovanni: 1) Select a map plot type; for more information on choosing a type of plot, see the Giovanni User Manual. 2) Select a date range. Data are in multiple temporal resolutions, so be sure to note the start and end date to ensure you access the desired dataset. 3) Check the box of the variable in the left column that you'd like to include and then plot the data.

NRT data can be accessed via Worldview:

Dust Score

A Dust Score indicates the level of atmospheric aerosols in the Earth’s atmosphere over the ocean. The numerical scale is a qualitative representation of the presence of dust in the atmosphere, an indication of where large dust storms may form and the areas that may be affected.

NRT data can be accessed via Worldview:

Surface Reflectance

In comparison with the MODIS Corrected Reflectance product, the MODIS Land Atmospherically Corrected Surface Reflectance product (MOD09) is a more complete atmospheric correction algorithm that includes aerosol correction and is designed to derive land surface properties.

Research quality data products can be accessed via Earthdata Search. All of the below data products are in HDF format, and can be opened using Panoply. The data are also customizable to GeoTIFF (see Tools for Data Access and Visualization section).

For higher resolution, the Landsat 7 Enhanced Thematic Mapper (ETM+) sensor and the Landsat 8 Operational Land Imager (OLI) instrument acquire data at 30 m spatial resolution in VNIR every 16 days (or less as you move away from the equator). Landsat 8 was developed as a collaboration between NASA and the USGS. The USGS leads satellite operations and data archiving at the Earth Resources Observation and Science (EROS) center.

Landsat data can be discovered using Earthdata Search, however, you will need a USGS Earth Explorer login to download the data.

Another high resolution option is the new (but currently PROVISIONAL) Harmonized Landsat and Sentinel-2 (HLS) project, which provides consistent surface reflectance and top of atmosphere brightness data from the OLI aboard the joint NASA/USGS Landsat 8 satellite and the Multi-Spectral Instrument (MSI) aboard Europe’s Copernicus Sentinel-2A and Sentinel-2B satellites. The combined measurement enables global observations of the land every 2–3 days at 30 m spatial resolution.

NRT data can be accessed via Worldview:

  • MODIS Land Surface Reflectance Data in Worldview
    These images are called true-color or natural color because this combination of wavelengths is similar to what the human eye would see. The images are natural-looking images of land surface, oceanic, and atmospheric features. Some band combinations “highlight” certain types of features better than others. The information for this dataset provides more details.
  • HLS Surface Reflectance in Worldview

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Find Socioeconomic Data

Find Socioeconomic Data
The Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, 1998–2016 consist of annual concentrations (micrograms per cubic meter) of ground-level fine particulate matter (PM2.5),with dust and sea-salt removed.

The Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD) with GWR, 1998–2016 consist of annual concentrations (micrograms per cubic meter) of ground-level fine particulate matter (PM2.5),with dust and sea-salt removed. Credit: NASA's Socioeconomic Data and Applications Center (SEDAC)

Air quality-related deaths and diseases that are exacerbated by air pollution are preventable, but prevention requires a knowledge of where vulnerable populations exist and what interventions are needed in those communities. Using observations of particulate matter in the air, along with socioeconomic data, can help do just that.

NASA’s Socioeconomic Data and Applications Center (SEDAC) provides a number of datasets on population exposure and vulnerability.

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Public Health

Public Health

Air pollution is a serious health issue all over the world. According to the World Health Organization (WHO), there are millions of deaths every year as a result of exposure to outdoor air pollution. In addition, 91% of the world’s population lives in places where air quality exceeds WHO guideline limits. Breathing air pollution, especially particulate matter, increases the risks of numerous illnesses, specifically respiratory, including pulmonary disease, respiratory infections, and lung cancer. It can also cause heart disease, heart attacks, and strokes. Toxicology, medicine, and epidemiology provide evidence that air pollution is impacting health across the globe. Unfortunately, evaluating toxicology and medicine does not provide a quantifiable measure of how and how much. Epidemiology, however, does, by providing a mechanism to evaluate the statistical relationships between air pollution and health due to variations in space and time

There are numerous health sites that provide information regarding public health as it relates to air pollution:

For an overview of environmental parameters available from NASA Earth science useful for monitoring and predicting health for decision support or for more information on tools available for evaluating the relationship between environmental conditions and health outcomes, view the course materials from the ARSET courses, Fundamentals of Satellite Remote Sensing for Health Monitoring and Methods in Using NASA Remote Sensing for Health Applications.

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Other NASA Assets of Interest

Other NASA Assets of Interest

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.

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External Resources

External Resources

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.

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Tools for Data Access and Visualization

Tools for Data Access and Visualization

Earthdata Search | Panoply | Giovanni | Worldview

Earthdata Search

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.

Screenshot of the Search Earthdata site.

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.

Earthdata Search customization tools diagram.

Panoply

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.

Giovanni

Giovanni is an online environment for the display and analysis of geophysical parameters. There are a few options for analysis.

  1. Time-averaged maps are a simple way to observe the variability of data values over a region of interest.
  2. Map animations are a means to observe spatial patterns and detect unusual events over time.
  3. Area-averaged time series are used to display the value of a data variable that has been averaged from all the data values acquired for a selected region for each time step.
  4. Histogram plots are used to display the distribution of values of a data variable in a selected region and time interval.

For more detailed tutorials:

  • Giovanni How-To’s on NASA's Goddard Earth Sciences Data and Information Services Center (GESDISC) YouTube channel
  • 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.

Worldview

NASA’s EOSDIS Worldview visualization application provides the capability to interactively browse over 900 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.

Worldview's Events tab provides information about events, such as tropical cyclones, wildfires, volcanic eruptions, and even large iceberg movement. Hurricane Barry, as shown in this image, traveled from the Gulf into Louisiana in July 2019.

Worldview's Events tab provides information about events, such as tropical cyclones, wildfires, volcanic eruptions, and even large iceberg movement. Hurricane Barry, as shown in this image, traveled from the Gulf into Louisiana in July 2019.

Animate the imagery over time. Do a screen by screen comparison of data for different time periods or a comparison of different datasets.

Hurricane Maria was a category 5 storm that devastated numerous places, most notably Puerto Rico, in September 2017. In the Woldview comparison, selecting a date pre-storm and then one post-storm shows the nighttime lights over the island, and how the storm affected electricity, even months after.

Hurricane Maria was a category 5 storm that devastated numerous places, most notably Puerto Rico, in September 2017. In the Woldview comparison, selecting a date pre-storm and then one post-storm shows the nighttime lights over the island, and how the storm affected electricity, even months after.

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Benefits and Limitations to Remote Sensing Data

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.

Instrument measuring the vertical column of aerosol optical depth

Aerosol Optical Depth (AOD) represents the amount of aerosols in the entire column of the atmosphere. AOD is the column-integrated value from the top-of-atmosphere to surface. It can be used as a surrogate to represent particulate mass at the surface. Source: NASA Applied Remote Sensing Training

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.

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Please visit the Earthdata Forum, where you can interact with other users and NASA subject matter experts on a variety of Earth science research and applications topics.

Published August 12, 2019

Page Last Updated: Feb 10, 2021 at 12:41 PM EST