These images capture the recent evolution of the air pollution event in China where the Air Quality Index (AQI) reached a peak value of 775. According to the EPA, when the index values are between 301 and 500, a health warning is triggered and anyone in the affected area is at risk of experiencing health effects, usually respiratory; the table below breaks down the AQI classifications.
So how can space technology be used to potentially warn citizens of a pending air quality episode similar to the recent event in China? Several important atmospheric variables which contributed to this event can be monitored from space via satellite, but the MODIS platform seems to be a good place to start. Data retrieved from NASA's MODIS (MODerate resolution Imaging Spectroradiometer) platform are useful in reconstructing a slowly evolving time series towards the examination such an event. MODIS data is actually collected from the AQUA and TERRA satellites; combined, they capture images from the entire surface of the Earth every 1-2 days. It follows that this platform is of great use when scientists want to monitor slow changes in the biosphere that evolve over time. While MODIS retrieves information in 36 spectral bands, Aerosol Optical Thickness (AOT) or Depth is retrieved in the 545-565 nm wavelength range. AOT is a good measure of the concentration of aerosol particles at various levels in the atmosphere and it has been demonstrated to show a strong correlation with air quality. AOT can then be used as a useful proxy in estimating the concentration of PM-10 in the atmosphere. PM-10 are defined as particulates with a diameter that is less than 10 micrometers; they are a key criteria related to respiratory illness, so this is an important variable to monitor when it reaches the levels recently seen around Beijing.
A useful early warning system can be easily implemented by developing site-specific time series of AOT in vulnerable regions. This could be done by first constructing weekly and monthly AOT climatologies indicative of typical seasonal profiles, and then monitoring regions to identify prolonged periods of elevated exposure.
I access the majority of the MODIS data that I use from NASA's Giovanni portal. Once I download and organize the data, I can perform more detailed modeling and analysis. The Giovanni portal provides a wealth of data that can be easily extracted. Future posts will continue to highlight the many uses of this data for both science and application purposes.