Combining information about electric power plant operation with real-time air quality predictions has allowed researchers to create a new capability for minimizing the human health effects of air pollution from power generating facilities.
The Air Pollutant Optimization Model, described in the journal Proceedings of the National Academy of Sciences, provides a new approach for reducing the health effects of ozone and fine particulate pollution. By considering health impacts and generating costs together, the hybrid model may provide a new tool for utility companies seeking to meet air quality standards.
In a test case for the state of Georgia, the model suggested that health impacts could have been reduced by $176 million, while increasing generating costs by $84 million.
“We looked at what would be the least expensive way of running these power plants if you take into account both the generating costs and the health impact costs,” said Valerie Thomas, Anderson Interface Professor of Natural Systems in the H. Milton Stewart School of Industrial and Systems Engineering and School of Public Policy at Georgia Tech. “You would still be operating plants that emit pollutants, of course, but you would reduce operations at the ones having the greatest impact and increase the use of facilities that have less impact or are in other areas.”
The new approach depends on the use of “reduced form” air quality predictions. Comprehensive air quality models typically require days of computer time to calculate concentrations of pollution for one emissions scenario, but the new format uses only the “sensitivities” derived from the full model to accurately produce predictions in less than a second. This capability would allow utility companies, for the first time, to test many possible scenarios in evaluating how air quality would change with different combinations of generating plant operations.
“This is really all about ‘smart generation,’” said Athanasios Nenes, a professor in Georgia Tech’s School of Earth and Atmospheric Sciences and School of Chemical & Biomolecular Engineering. “This shows there’s a way to meet the standards by controlling who emits what and at what time, and that may change the amount of investment you’d need to make in new emission control equipment. Hour-by- hour, we’ll be able to determine what makes the most sense.”
Stewart School of Industrial and Systems Engineering