Chengzhe Li is a University of Iowa PhD candidate in chemical and biochemical engineering and the lead author of a paper outlining the research.
Wednesday, April 10, 2024
Chengzhe Li

A new predictive atmospheric model developed at the University of Iowa will allow scientists to forecast and issue warnings for air pollution events in developing countries. 

The model simulates particulates in the atmosphere to pinpoint both the timing and location of occurrences of air pollution, said Chengzhe Li, a member of the research team. 

The PhD candidate in chemical and biochemical engineering is the lead author of a paper outlining the research. The paper – “Improvement of Surface PM2.5 Diurnal Variation Simulations in East Africa for the MAIA Satellite Mission” – has been published online and was selected for the cover of the American Chemical Society journal, ACS ES&T Air

The paper presents a seminal method of improving air quality prediction that is feasible in developing countries where a limited surface air monitoring network is available. The method was tested in Ethiopia and combines surface air pollution data collected from instruments at two U.S. State Department facilities in Addis Ababa and data collected by citizens using a network of low-cost air pollution sensors.

The Iowa team’s work is part of the investigation for Multi-Angle Imager for Aerosols (MAIA), which seeks to measure airborne fine particulate matter (PM2.5) concentrations and better understand their impacts on human health. The satellite instrument that is part of the MAIA investigation is planned for launch into space in 2025.

In 2016, NASA selected the MAIA investigation as part of the Earth Venture Instrument program to investigate the health impacts of exposure to ambient particulate matter. 

NASA’s MAIA investigation is led by David J. Diner at NASA’s Jet Propulsion Laboratory (JPL). MAIA co-investigator Jun Wang, Li’s advisor and the James E. Ashton Professor of Engineering at Iowa, leads the team providing chemistry transport modeling support to the project.  

Authors of the paper include Li, Wang, Huanxin Zhang, and Nathan Janechek, all from Wang’s Atmospheric and Environmental Research Group. Other contributors include Diner and Sina Hasheminassab, MAIA’s science system engineer at JPL.