Xu: Simulate Wildfire Chemistry in Lab

Research Focus

Wildfires pose severe threats to urban air quality. As a result of ongoing climate change and historical fire suppression practices, wildfires in North America became more intense, frequent, and widespread in the 2000s. These trends have significantly impacted urban air quality in the last two decades, offsetting some of the improvements from anthropogenic emission reduction. The wildfire impacts are spatially widespread in the U.S. The cities in the western U.S. are situated in a wildfire-active region. The cities in the eastern U.S. are not spared, as the western and Canadian wildfires can transport across the continent. In future scenarios with warmer temperatures, longer dry seasons, and reduced anthropogenic emissions, wildfire emissions will play a more significant role in modulating urban air quality. The student will conduct laboratory experiments to simulate wildfire chemistry. A suite of analytical instruments will be deployed. 

Skills, Techniques, Methods

• Analysis of complex dataset
• Matlab programming
• Air quality and atmospheric chemistry
• Hands-on ability of plumbing and soldering.
  

Research Conditions

The research will be conducted in person. It will involve both data analysis with a computer and experimental work in the laboratory. 

Team Structure and Opportunities

The CFD lab. research team includes postdoctoral researchers, doctoral students, MS and undergraduate students. Undergraduate students work closely with one of the doctoral or MS students as their daily point-of-contact. Undergraduate students meet at least once a week with the CFD lab. Director Prof. Ramesh Agarwal. The CFD lab. has a weekly research group meeting, and the participating undergraduate/graduate students discuss their research and occasionally are asked to give a presentation in this meeting describing the progress and difficulties encountered during research. All undergraduate students have independent projects and conduct independent research under the mentorship of a doctoral student and PI. 

Requirements

It is desirable that the student has taken the undergraduate level courses in Fluid Dynamics and MATLAB and possesses some familiarity in running a computer code in C++. Some experience with computer programming in C++ is a big plus, but not necessary.