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Using AI to track coal train dust

1 min read

Undark reporter Emma Foehringer Merchant writes about scientists in California who are working with local communities — and a suite of AI tools — to understand air pollution from coal transport.

In a nutshell:

The study found that trains carrying coal significantly increased ambient PM2.5, a type of particulate matter that has been linked to respiratory and cardiovascular diseases. The research could help answer questions about the impact of coal facilities and trains on air quality in urban areas. Artificial intelligence technology could also be used to monitor other sources of pollution that have been historically difficult to track.

Key quote:

“I’m not an AI fan,” said Bart Ostro, an environmental epidemiologist at UC Davis and the lead author of the paper. “But this thing worked amazingly well, and we couldn’t have done it without it.”

The big picture:

These findings could help communities that are concerned about the impact of coal pollution on their health. The main pollutants emitted from coal combustion are particulate matter, sulfur dioxide, nitrogen oxides and mercury. Particulate matter is a mixture of solid particles and liquid droplets that can be inhaled into the lungs. It can cause respiratory problems such as asthma, bronchitis and lung cancer.

Read the article at Undark.

Want to know more about how artificial intelligence can help reduce exposure to pollution? Krystal Vasquez reported recently for EHN that AI give more advance warning of bad air days and reduce hospital visits.

About the author(s):

EHN Staff

Articles written and posted by staff at Environmental Health News

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