Description:

Abstract: Climate change and air pollution are urgent, intertwined global challenges with profound implications for public health and the environment. Air pollution can be exacerbated by extreme events linked to climate change and cause health crises, while also serving as short-lived climate forcers (SLCFs) with much shorter lifetimes than carbon dioxide (CO2), making them critical for immediate climate change mitigation. I will present how we apply satellite observations, physics-based simulations, and data-driven methods to develop science-based strategies to mitigate and adapt to these challenges. I will start with climate change mitigation through atmospheric methane regulation. Methane is the second most important greenhouse gas and has been identified as the best lever to control near-term climate change due to its potent warming effect and much shorter atmospheric lifetime than CO2. We integrate satellite data and Bayesian inversion to explain the recent surge of atmospheric methane, assess progress in national emission regulations, and explore the implications of increased wetland emissions for achieving climate goals. In the second part, I will introduce our data-driven frameworks for monitoring greenhouse gases and air pollutants. These frameworks integrate state-of-the-art remote sensing observations with physics-based atmospheric simulations to provide near-real-time emission estimates ranging from urban to global scales for major source sectors such as transportation, residential, and power plants. Lastly, I will demonstrate how these data and simulations can assist with actionable predictions, inform urban planning, reduce health risks, and support adaptations to severe pollution events in a changing climate.

Bio: Dr. Zhen Qu is a tenure-track assistant professor in the Department of Marine, Earth and Atmospheric Sciences at North Carolina State University. She received her Ph.D. in Mechanical Engineering (Air Quality Track) from the University of Colorado Boulder in 2019 and her B.S. in Physics from Peking University in 2014. She had postdoctoral training in the Environmental Engineering program at Harvard University from 2020 to 2022 before joining NC State University in 2023. Dr. Qu’s research leverages data-driven methods to mitigate and adapt to environmental and public health challenges associated with climate change and air pollution. Her interdisciplinary approach combines remote sensing and multiscale observations, physics-based atmospheric simulations, Bayesian inference, machine learning, and sensitivity analysis. Her work pushes the boundary of using observation-based emission estimates to inform public policy and has led to a number of interactions with environmental agencies. In 2024, she received the NASA Early Career Investigator Award to investigate the global methane surge using data-driven methods and satellite observations.