AI helps Texas A&M researchers understand weather-induced pollution
Texas A&M University last Thursday announced that some of its researchers are using artificial intelligence to track pollution caused by accidental chemical emissions following natural events, like severe weather.
A recent paper shows that better understanding the interplay between such natural hazards and chemical emissions could help to mitigate pollution in the environment. Researchers used AI to analyze reports about chemical emissions and weather data collected from the Houston region over the past 20 years.
“In this study, we pursued a data-driven understanding of how climate extremes elevate the likelihood of excessive industrial emissions,” Qingsheng Wang, a professor of chemical engineering at Texas A&M, said in the announcement. “This understanding is laying the groundwork for predictive tools allowing regulators and operators to anticipate natural hazard-triggered technological accidents.”
According to researchers, severe weather events often lead to chemical emissions, such as in 2017 when Hurricane Harvey’s floodwaters disabled refrigeration trailers at a processing facility, leading to more than 350,000 pounds of chemicals burning.
