Dr. Jordan Schnell

Postdoctoral Scholar, Dept. of Earth & Planetary Science

Jordan uses mathematical programming to simulate the chemistry of the real-world atmosphere. Specifically, he works on problems related to air quality (e.g., haze pollution in California and China), which is controlled by a combination of emissions (e.g., cars, power plants, and even vegetation) and weather (e.g., hotter weather with more sunshine equals enhanced chemical reaction rates). He writes code for the giant (10s of thousands of lines of code) mathematical global chemistry-climate models that try to replicate how the chemistry of the atmosphere has evolved over the recent past (1850s – present) so that those models can make predictions of how future atmospheric chemistry will evolve. One project he is working on asks: How would air quality be impacted if the U.S. switched to electric vehicles. This project involves developing hypothetical emission data sets (using mathematical programming) that are then used as input to the global climate models he works on and with. Learn more about his research here:

http://sites.northwestern.edu/danethan/jordan-schnell-bio/

Daniel Garcia

PhD Student, Department of Chemical and Biological Engineering

Daniel uses mathematical programming to design sustainable production and manufacturing systems. He defines some problem and then write a system of equations and constraints that, when solved, results in the best production method. For example, one goal could be to design a biofuel plant that has the lowest cost and/or lowest environmental impact. Constraints could be that the plant must produce enough ethanol to meet demand, the venture should be profitable, etc. We could change which feedstock to use (corn, switchgrass, wood, etc.), which set of technologies to choose, where to site the plant, etc. Mathematical programming turns these options into variables and the constraints into equations or inequalities. Then, an algorithm is applied to identify the values of the variables that minimize cost and/or environmental impact.