Characterizing Sources of Persistent and Emerging Air Pollution in North America

Characterizing Sources of Persistent and Emerging Air Pollution in North America

Air

Center for Environmental Measurement and Modeling (CEMM), Office of Research and Development

Research Triangle Park, NC

• National Science Foundation Non-Academic Research Internships for Graduate Students (INTERN) Supplemental Funding Opportunity (6 months maximum)
• Other Programs (contact research lead)

The project focuses on research in atmospheric science to address persistent and emerging issues in air pollution and human exposure. One or more of the following research topics could be included: (1) atmospheric modeling of ozone, particulate matter, and climate-influencing pollutants, (2) development of key model inputs (e.g., emissions), (3) meteorological modeling, (4) statistical-based modeling and machine learning approaches, and (5) analysis of measurement data collected in the field. All of these research areas are applied to understanding the sources and processes (chemical and physical) contributing to air pollution and human exposure at hemispheric to local scales. The research will be conducted at EPA’s state-of-science modeling and atmospheric measurement facilities.

Goal:  The fellow will learn and apply modeling techniques, data analysis, or a combination of these to advance the understanding the sources of poor air quality and exposure to air pollutants. 

Learning Objectives:

• Modeling of air pollutants to understand their origin (emissions), transport, transformation, and fate to characterize adverse effects on environmental and human health.
• Conduct experiments, analyze data, and write peer-reviewed journal articles.
• Learn the use and operation of different modeling techniques and data analysis methodologies.

Preferred Skills:

• Strong verbal and writing skills,
• Ability to work both as a part of a team and independently.
• Basic knowledge of atmospheric science, air quality modeling, meteorological modeling, statistical/machine learning modeling, ambient measurements, or analytical instrumentation.

Qualifications:  Graduate student or Ph.D. in one of the relevant fields (e.g., Chemistry, Chemical Engineering, Environmental Engineering, Environmental Chemistry, Environmental Science, Statistics, Public Health, Atmospheric Science)

Kirk Baker (baker.kirk@epa.gov)