After more than a decade of steady decreases, surface ozone (O₃) trends in North America reversed in 2015 despite policy mitigation efforts, report Weizhi Deng and colleagues. Their research links this reversal to O₃ emissions from wildfires and additionally documents a related rise in premature mortality. “Despite regulated reductions in anthropogenic emissions of O₃ precursors, observation stations indicate that policy-relevant surface O₃ levels have plateaued,” the authors write, tying this phenomenon to an increase in wildfire emissions. They describe the relationship between wildfires and surface O₃ trends more closely by using deep learning models to evaluate existing yet sparse EPA, satellite, and meteorological measurements, generating a dataset of daily surface O₃ measurements at a 1-kilometer resolution in North America from 2003 to 2024. Doing so revealed that O₃ trends flipped from a decrease of 0.65 parts per billion (ppb) per year before 2015 to an increase of 0.13 ppb per year after 2015. Further analyses determined this post-2015 rate would have stayed in decline (−0.25 ppb per year) if not for wildfire emissions. The authors then examined correlations between O₃ trends and premature deaths, attributing emissions to an additional 318 deaths per year since 2013. Essentially, after 2013, the mortality rate attributable to wildfire-sourced O₃ rose by 46%. Finally, Deng et al. examined O₃ emissions from 2022 to 2024, a period marked by extreme fires and smoke in Canada. Results showed wildfire emissions alone exposed 43 million people to unhealthy levels of air pollution, in excess of the United States’ O₃ air quality standard of 70 ppb. The authors suggest that these emissions prevented the United States from tightening its O₃ air quality standard by 4 ppb. They elaborate: “If the O₃ standard were lowered to 65 ppb, 60% of the population (202 million people) would fall into nonattainment, and under a 60-ppb standard, the fraction would increase to 87% (294 million people). These findings demonstrate the challenge in adopting a more stringent O₃ standard as growing wildfires contribute to high O₃ episodes.”

Concordia University researchers have developed an AI-powered operating room scheduling tool that plans surgeries, manages last-minute emergencies, and minimizes patient disruptions within a single framework. Tested on real hospital data, the model reduces variables compared to existing approaches, cutting wait times and day-of-surgery cancellations. The study appears in the International Journal of Production Research.