It’s a first for South Dakota State University and for graduate student Najam Khan.
Khan, who completed his master’s degree in operations management in May 2018, received the 2019 Midwestern Association of Graduate Schools Distinguished Master’s Thesis Award in the mathematics, physical sciences and engineering category. He is the first SDSU graduate student to win the regional award.
“This is an exciting moment for our university, our graduate school and this outstanding student,” said Nicole Lounsbery, assistant dean of the SDSU Graduate School. Since 2015, the graduate school has been recognizing outstanding research and scholarship through the university’s Master’s Thesis Award. Each year, the SDSU thesis award winner is then nominated for the regional award.
The Midwestern Association thesis committee reviewed submissions in the mathematics, physical sciences and engineering category from 27 universities, including Washington University in St. Louis, University of Michigan-Ann Arbor, University of Illinois at Urbana-Champaign and University of Wisconsin-Madison.
“The university recognition was quite a surprise but receiving the regional award was definitely unexpected. This is indeed an honor that will provide much needed motivation for my Ph.D. studies,” said Khan, who is working on his doctorate in agricultural, biosystems and mechanical engineering at SDSU. Through the regional award, Khan will receive a $750 honorarium and $500 toward travel expenses to attend the Midwestern Association annual meeting March 20-22 in St. Louis.
For his master’s research, Khan combined emissions modeling with operational cost analyses to help companies select locations for coal-powered electricity plants. The goal is to minimize the public’s exposure to airborne pollutants while providing customers with the electricity they need.
“My research provides a decision analysis tool that allows a strategic compromise between profitability and environmental care,” Najam said. An article describing his model appears in the January issue of the American Journal of Operations Research.
“Najam is a very motivated, hard-working student. He is an independent learner who wants to figure things out for himself. He definitely deserves this award,” said Assistant Professor Ekaterina Koromyslova, Khan’s thesis adviser.
While completing his bachelor’s degree at State, Khan took graduate courses that applied to the master’s degree requirements. “Because of this, he was one-third of the way through the graduate program when he started in fall 2016,” Koromyslova pointed out.
Khan began working full time as an operations research analyst at CSW in Olympia, Washington, while finishing his thesis. “Working made me have a practical approach to the thesis,” he said. Khan continues his work at CSW while pursuing his doctorate.
Despite the increased usage of renewable energy technologies, many countries, including China and India, still rely heavily on coal for electricity generation, Khan explained. In addition, an increasing number of African countries are turning to coal to supply electricity for industrial development, but most do not have emissions regulations.
“Typically, locations for coal-powered electrical plants were determined by where the coal was or who the largest electricity consumer was,” Khan said. As a result, coal power plants were often built near manufacturing/commercials hubs, thereby exposing large populations to airborne pollutants.
“This research provides a tool for industrial zone planners, environmental engineers and stakeholders that can help to minimize the public’s exposure to harmful emissions while maintaining minimal operational costs,” he explained. “We want the plant to be far enough away from the population, but not too far. It is a balancing act.”
To develop the model, Khan used Environmental Protection Agency pollutant dispersion models to estimate pollutant dispersion from the coal power plant. He then combined that with an algorithm to calculate transmission line losses and coal transportation costs.
“Transportation costs always come into play when deciding on a location,” Khan said. Using a grid search, the program reduces the number of possible locations until it identifies the optimum location.
During his doctoral work, Khan hopes to expand the model to consider emissions from multiple industries and thereby help community planners strategically select sites for industrial parks.