A research assistant, Meng Zhou, at the University of Iowa Technology Institute earned the 1st place Outstanding Oral Presentation award at the 25th Conference on Satellite Meteorology, Oceanography, and Climatology in August.

Leaders of the U.S. Department of Homeland Security (DHS) HQ Office of Academic Engagement (OAE) visited the University of Iowa campus to gain an Iowa perspective on national security-related topics, a post on the college’s website states.

University of Iowa researchers conducted a novel investigation into whether community scientists could map air quality and improve urban health at a time when extreme heat and air pollution threaten large cities.  

Leaders of the U.S. Department of Homeland Security (DHS) HQ Office of Academic Engagement (OAE) visited the University of Iowa campus to gain an Iowa perspective on national security-related topics.  

Jun Wang, assistant director of the Iowa Technology Institute, was named the principal investigator for two NASA grants worth $1.56 million. NASA’s TEMPO mission, set to launch this year, is intended to revolutionize air quality forecasting. TEMPO, which stands for Tropospheric Emissions: Monitoring Pollution, is a space-based ultraviolet and visible spectrometer scheduled to be launched into space aboard a commercial satellite — after nearly ten years of planning — before the year is over.

University of Iowa researchers specializing in atmospheric sciences were selected to aid NASA’s TEMPO mission that’s set to launch this year. TEMPO (Tropospheric Emissions: Monitoring Pollution) is intended to revolutionize air quality forecasting. 

Jun Wang, professor of chemical and biochemical engineering and James E. Ashton Professor in Engineering, has been awarded $1.55 million to improve regional air quality monitoring from space.

Zeyuan Ru, a University of Iowa Technology Institute graduate research assistant, has been recognized by the AGU Atmospheric Sciences Section. Ru works with Prof. Jun Wang and is a graduate student at the College of Engineering.

Dr. Xi Chen, working with Prof. Joe Gomes and Prof. Jun Wang, published their collaborative work presenting a new, machine-learning based, approach to predict light scattering properties of non-spherical dust particles. The approach will have wide applications in satellite remote sensing and climate model predictions. Chen, Gomes, and Wang are affiliated with the University of Iowa Technology Institute.

University of Iowa Technology Institute faculty, staff, and student researchers are developing a low-cost canopy sensor system to help farmers set more efficient irrigation schedules and plan their day-to-day operations for the crop fields.