Health and Air Quality Data Pathfinder

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, check out NASA's Health and Air Quality Applied Sciences Team (HAQAST).

1. For qualitative understanding, satellite images allow air quality managers to see and communicate spatial patterns, atmospheric transport, and trends in air pollution.
2. Satellite data can also be used to quantify change and relative abundance.
3. 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 PM_2.5 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 PM_2.5, using specific conversion techniques. 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. When available, NASA’s Land, Atmosphere Near real-time Capability for EOS (LANCE) provides data to the public within 3 hours of satellite overpass, which allows for near real-time (NRT) monitoring and decision making, specifically regarding aerosol and dust indices and pollutant transport. When coupled with public health information, the air quality data can provide a valuable resource to forecasting and monitoring exposure and risk.

Datasets referenced in this pathfinder include:

Satellite	Sensor	Spatial Resolution	Temporal Resolution
Aqua	Atmospheric Infrared Sounder (AIRS) Level 2 and 3 products	1° x 1°	daily, 8-day, monthly
Terra and Aqua	Moderate Resolution Imaging Spectroradiometer (MODIS)	250m, 500m, 1km	1-2 days
Terra	Measurement of Pollution in the Troposphere (MOPITT)	1° x 1°	daily, monthly
Aura	Ozone Monitoring Instrument (OMI)	13km x 24km	daily
Suomi-NPP	Ozone Mapping and Profiler Suite (OMPS)	50km x 50km	101 minutes, daily
Sentinel-5P	TROPOspheric Monitoring Instrument (TROPOMI)	7km x 3.5km	daily
Suomi-NPP	Visible Infrared Imaging Radiometer Suite (VIIRS)	375-750m	1-2 days

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Earthdata Search | Panoply | Giovanni | Worldview

Earthdata Search

Earthdata Search is a tool for data discovery of Earth Observation data collections from NASA’s Earth Observing System Data and Information System (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.

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.

• Panoply Orientation on NASA's Earthdata YouTube channel.
• A Tutorial on Creating Plots in Panoply

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.

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

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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.

• MODIS/Aqua AOD from Earthdata Search (3km resolution, merged algorithm)
• MODIS/Terra AOD from Earthdata Search (3km resolution, merged algorithm)
• MODIS Terra/Aqua-MAIAC Retrieval AOD from Earthdata Search
  Multi-angle Implementation of Atmospheric Correction (MAIAC) Land AOD utilizes a new advanced algorithm which uses time series (TMS) analysis and a combination of pixel- and image-based processing to improve the accuracy of cloud detection, aerosol retrievals and atmospheric correction.

• VIIRS AOD at 1 degree x 1 degree from Earthdata Search (daily global data coverage)
• VIIRS AOD at 6km from Earthdata Search (daily)
• Monthly VIIRS AOD at 1 degree x 1 degree from 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.

• 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.

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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. PM_2.5, 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, PM_2.5 a mass concentration measurement.
• AOD is an integrated column measurement from the top of the atmosphere to the surface, PM_2.5 a ground measurement.
• AOD is an area-averaged measurement, PM_2.5 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 PM_2.5. It is important to note that while there is a relationship between AOD and PM_2.5, 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 PM_2.5 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. For more information about the different techniques and an exercise in doing this conversion, view the course materials from NASA's Applied Remote Sensing Training (ARSET) course, NASA Earth Observations, Data and Tools for Air Quality Applications.

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 PM_2.5, there are several resources that utilize both ground-based and remote sensing data.

• PM<2.5 micrometers in Worldview
  Data are available from 2001-2012.
• Worldbank mean exposure to PM_2.5 across the globe

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Nitrogen Dioxide | Sulfur Dioxide | Carbon Monoxide | Ozone

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:

• OMI NO₂ data from Earthdata Search
  The OMI, aboard the Aura spacecraft, provides daily gridded and non-gridded products at 13x24 km resolution; data are in HDF5 format (Hierarchical Data Format Release 5) and can be opened using Panoply. A tutorial on using OMI NO₂ data is available as a PDF and a webinar on Analyzing NO₂ data within Java and Excel is available from NASA's Earthdata YouTube website.
• TROPOMI NO₂ data from Earthdata Search

  

  
  The TROPOspheric Monitoring Instrument (TROPOMI) aboard Sentinel 5, is a European Space Agency (ESA) Mission. ESA's TROPOMI NO₂ provides additional information on this level 2 data product. It is important to note that, because of the very small numbers in tropospheric vertical column of NO₂, you will need to change the scaling factor in Panoply (see image from June 2018 to right). 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.

• OMI NO₂ data in Giovanni

NRT data can be accessed via Worldview:

• OMI NO₂ data in Worldview
• Trends over time: Ground level NO₂ in Worldview (data are from 1996-1998 and 2010-2012)

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

Sulfur Dioxide

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.

• OMI SO₂ data in Giovanni

NRT data can be accessed via Worldview:

• OMI SO₂ data in Worldview: The imagery created from the data is at 2km spatial resolution.
• OMPS SO₂ data in 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.

• AIRS CO data in Giovanni (daily and monthly data)
• MOPITT CO data in Giovanni (monthly 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.

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.

• OMI O₃ data from Earthdata Search
  OMI provides daily total column data; data are in HDF5 format, and can be opened using Panoply.

• 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.

• AIRS O₃ data in Giovanni (data are daily and monthly)
• OMI O₃ data in Giovanni (data are daily)

NRT data can be accessed via Worldview:

• OMI O₃ data in Worldview
  Visualization of the amount of ozone in the total column measured in Dobson Units (DU).

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

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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.

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.

• OMI AI data in Giovanni

NRT data can be accessed via Worldview:

• OMI AI data in Worldview
• OMPS AI data in Worldview
  OMPS Aerosol Index layer indicates the presence of ultraviolet (UV)-absorbing particles in the air.

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:

• AIRS Dust Score in Worldview
  Measurement from the AIRS Infrared quality assurance subset; the imagery resolution is 2 km.

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).

• MODIS/Aqua Land Surface Reflectance Data from Earthdata Search
  Data are available daily and 8-day at various spatial resolutions.
• MODIS/Terra Land Surface Reflectance Data from Earthdata Search
  Data are available daily and 8-day at various spatial resolutions.
• VIIRS/NPP Land Surface Reflectance Data from Earthdata Search
  Data are available daily and 8-day at various spatial resolutions.

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.

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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:

• Air Quality Observations from Space explains how NASA is monitoring air quality and the associated health impacts from space.
• WHO Ambient Air Pollution Health Impacts describes the pollutants and the health risks associated with them as well as statistical information and interventions.
• EPA BenMAP-CE is a open-source computer program that calculates the number and economic value of air pollution-related deaths and illnesses.

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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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

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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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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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 PM_2.5, 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.

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