Artificial Intelligence Unveils Hidden Risks in Coal Transportation


In the United States, researchers have used AI to create sensors capable of determining pollution caused by coal train traffic. The results are not good.

For some, AIs present an existential threat; for others, their power helps improve the quality of life of humans. But if their consumption in energy remains substantial, they can also make it possible to carry out advanced scientific studies in matter of ecology to reduce pollution.

This is the case in Vallejo, California (United States) where Nicholas Spada , a scientist and engineer in aerosol sat the University of California at Davis, created a strange machine whose data is processed by artificial intelligence. The equipment carried on a tripod includes a camera, a sensor air, a weather station and processor powered by AI. Its objective: to collect long-term information on local air quality.


But not just anywhere, only on the railway lines used to transport coal. For six months, with his team, he used his device to identify the passage of trains carrying coal and record their impact on air quality. It must be said that in the United States, approximately 70% of coal is transported by train from dozens of mines to power plants and maritime terminals. Thus, 513 million tones of coal were transported from one end of the country to the other, not counting exports of 85 million tones. The problem is that this coal travels in open wagons. As soon as there is wind, and with the speed from the train, these wagons release a lot of dust.

An AI to defend populations against pollution

Previously, to measure the impact of this dust released by wagons on air quality, it was necessary for humans to count the coal trains and then compare the data recorded by sensors of ambient air. The use of automatic cameras was not satisfactory. But with the system developed by the team of researchers, artificial intelligence makes it possible to identify the precise moments when these trains pass 24/7 by systematically recognizing them.

The analysis of the pollution data is then coupled with that of the images and that of the local weather. Ultimately , the data analyzed by the team showed that when they cross the city, trains carrying coal considerably increase ambient PM2.5, in other words, the rate of fine particles (2.5micronsdiameters). This type of particle is associated with respiratory and cardiovascular diseases , and increases local mortality. Even short-term exposure to PM2.5 can harm health. Thanks to this AI, and this in-depth study of the real state of ambient pollution generated by coal dust and train diesel, the local populations who collaborated with the researchers could make themselves heard with the authorities so that these the latest legislate against this pollution.