This project aims to develop a new technology and technique that will aid in the relatively automated detection of respiratory-related changes that are exacerbated by air pollutants (e.g. lung function/respiratory changes due to air-pollution-induced asthma). This work involves understanding air transport in the human respiratory system (including the chemical and physiological impacts of air pollutants), advancing the state of the art in sensing, acoustic signal processing, and machine learning to enhance automation.