Tessum Research Lab

Air pollution kills 3,000,000 people per year. So how can we stop it?

About Us

Ambient air pollution causes ~4% of total deaths in the United States. Our group assesses air pollution levels and the human health impacts caused by them, focusing on air pollution monitoring, environmental exposure modeling, and aerosol measurement and control technology. Most recently, we are developing air quality monitoring strategies to collect high quality air pollution data, and producing accurate air pollution exposure estimates for health studies in both ambient and occupational settings using advanced statistical and machine learning methods.

Approach

How do we science?

Air Sampling

Sampling pollutants in the atmosphere

Exposure Modeling

Modeling the levels of air pollution that people are exposed to over space and time

Machine learning

Leveraging machine learning and artificial intelligence to improve existing models and allow new insights

Projects

Measuring and Predicting Agriculture-related Ambient Air Pollution

Agricultural emissions of air pollutants are of growing concern for air quality, public health, climate change, and environmental justice. However, there are no existing approaches to accurately qualify air pollution exposure in non-urban areas or from agriculture activities.

Traffic Related Air Pollution Prediction Using Video Footage and Deep Learning

Traffic-related air pollution is a major health burden in the United States. “Hyperlocal” pollution quantification is increasingly recognized as important for environmental sustainability and social equity, while traditional direct-measurement techniques do not scale well and are demanding in cost and labor.

Meet the Team

Principal Investigator

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Mei Tessum

Research Assistant Professor of Agricultural & Biological Engineering

Students

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Xiao Ran

Graduate Research Assistant