The U.S. Environmental Protection Agency has awarded almost $6 million in research grants to nine universities to improve air-quality models.
Colorado State University in Fort Collins and the University of Colorado Boulder were among the grant recipients announced Thursday.
The air-quality models are designed to simulate ozone, particulate matter, regional haze, air toxics and emerging pollutants, and will focus on how chemicals react in the atmosphere.
Projects funded through the EPA’s Science to Achieve Results (STAR) program include:
- Colorado State University, $400,000, to gain insights on how emissions from wildfires and volatile chemical products contribute to formation of fine particles in the atmosphere.
- University of Colorado Boulder, $396,135, to incorporate volatile chemical products compounds to current chemical mechanisms to improve air-quality model predictions of ozone in U.S. urban areas.
- Columbia University, New York, $799,699, to develop tools that will improve the computational efficiency of chemical mechanisms for use in air-quality models.
- Harvard University, Cambridge, Massachusetts, $785,010, to improve modeling of isoprene, halogen, and mercury chemistry; and increase the computational efficiency of chemical mechanisms in a widely used model to support air-quality management.
- Massachusetts Institute of Technology, Cambridge, $799,667, to develop a systematic approach towards developing chemical mechanisms for formation of particulate matter from complex organic compounds by using state-of-the science laboratory data.
- University of California, Riverside, $784,743, to develop chemical mechanisms for emerging sources of pollutants, such as wildland fires and volatile chemical products, and approaches for increasing the computational efficiency of chemical mechanisms for use in air-quality models.
- University of Illinois, Urbana, $399,469, to improve the computational efficiency of chemical mechanisms using machine-learning algorithms.
- University of Maryland, College Park, $796,885, to develop software packages using machine learning methods to gain insights on atmospheric chemical processes and increase computational efficiency of chemical mechanisms for use in air quality models.
- University of Wisconsin, Madison, $798,234, to develop and validate a new way of simulating heterogeneous chemistry of dinitrogen pentoxide to improve modeling of ozone and particulate matter.