{"id":2987,"date":"2022-06-13T15:59:45","date_gmt":"2022-06-13T15:59:45","guid":{"rendered":"https:\/\/blogs.edf.org\/global-clean-air\/?p=2987"},"modified":"2022-06-13T15:59:45","modified_gmt":"2022-06-13T15:59:45","slug":"introducing-air-tracker-a-backward-take-on-air-quality-to-pinpoint-sources","status":"publish","type":"post","link":"https:\/\/blogs.edf.org\/global-clean-air\/2022\/06\/13\/introducing-air-tracker-a-backward-take-on-air-quality-to-pinpoint-sources\/","title":{"rendered":"Introducing Air Tracker: A backward take on air quality to pinpoint sources"},"content":{"rendered":"

EDF\u2019s new <\/span><\/i>Air Tracker<\/span><\/i><\/a> tool allows us to better understand how local air pollution behaves, illuminating the path it takes from a likely source area. Because this tool allows us to look backwards at where pollution likely originated, it shifts the focus, putting communities and people first. Developing it required a shift in thinking.\u00a0<\/span><\/i><\/p>\n

Most atmospheric scientists focus on particle and air movement to help us predict what\u2019s going to happen in the future. As a scientist working in air pollution, I wanted to use those same principles to look backwards so I could better understand how the emissions upwind of us mix and travel through the air, providing a better picture of what we\u2019re breathing at any given time. This way, we don\u2019t have to model every single source to know what\u2019s important to who and when.<\/span><\/p>\n

When I joined EDF in 2019, our scientists had already successfully shown how mobile air monitoring programs could highlight dramatic differences in pollution levels within individual city blocks. We wanted to go beyond showing the presence of pollution\u2013and illustrate how it traveled to get there.\u00a0<\/span><\/p>\n

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EDF and academia joined forces to leverage cutting edge insights.<\/b><\/p>\n

To do this, we enlisted the help of <\/span>John C. Lin<\/span><\/a>, an atmospheric scientist from the University of Utah who developed the STILT model (which has since been incorporated into NOAA\u2019s <\/span>HYSPLIT<\/span><\/a> model). He and his team were already working with our partners at Google Earth Outreach on a source apportionment project. We also tapped <\/span>Paul Dille<\/span><\/a> (who pulled in Randy Sargent and Amy Gottsegen) from CREATE Lab at Carnegie Mellon University, whose <\/span>Smell PGH<\/span><\/a> application allows users to better understand the pollution landscape in Allegheny County, PA. EDF colleagues Alex Franco, Mindi DePaola and Grace Tee Lewis provided invaluable insight and help as well.<\/span><\/p>\n

Air Tracker <\/span><\/a>runs on\u00a0 real-time, trusted, scientific models coupled with air pollution and weather data to help residents, scientists and cities learn more about the air they\u2019re breathing. While Air Tracker is currently mapping fine particle pollution trajectories in Houston, Salt Lake City and Pittsburgh, we designed it to work with other primary pollutants anywhere in the world.\u00a0<\/span><\/p>\n

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Air Tracker allows users to trace the path of likely sources of air pollution in Houston, Pittsburgh and Salt Lake City.<\/figcaption><\/figure>\n

Filling current air monitoring gaps<\/b><\/p>\n

Despite advances in low-cost mobile and stationary monitoring networks, existing air pollution tracking is still lacking. Currently designed to provide us with a solid understanding of background air pollution, the federal and state government\u00a0 system of monitors essentially smudges out the rough edges to create averages, which underemphasizes the very real, very harmful pollution burden many urban\u2013often historically vulnerable\u2013communities face.\u00a0<\/span><\/p>\n

Air Tracker can help counter that averaging effect. It allows users to click anywhere within their city map to see the most likely source area of the air they\u2019re breathing at any given time.\u00a0<\/span><\/p>\n

Beyond the mapping application, it can improve air quality efforts in the following ways:<\/span><\/p>\n

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