Improving numerical models of atmospheric pollution to inform multiscale air quality policy and management

Research Opportunity at the United States Environmental Protection Agency

Title:

Improving numerical models of atmospheric pollution to inform multiscale air quality policy and management

Research Area (s):

Air

Lab, Region/Center, Office:

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

Opportunity Location:

Research Triangle Park, NC

Opportunity Funding (Duration):

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

Project Description:

Federal, state, and local environmental agencies rely on large-scale numerical models of the atmosphere to understand the connections among sources of air pollutants like particulate matter, volatile organic compounds, nitrogen and sulfur oxides, and persistent pollutants that resist breakdown in the environment. Research priorities span a multitude of topics, including the chemistry of emissions from human sources of concern (e.g., residential wood burning, mobile sources, industrial facilities, and food cooking), the public health impacts of ultrafine particles, generation of coarse particles, and the fate of novel pollutants of concern like per- and polyfluoroalkyl substances (PFAS).

The research will be conducted at EPA’s state-of-science modeling and atmospheric measurement facilities. The methods and findings developed will support EPA’s roles in pushing forward atmospheric science knowledge and in providing partners with tools to help mitigate human health impacts of air emissions. Examples of these tools include EPA's state-of-the-science Community Multiscale Air Quality (CMAQ; https://www.epa.gov/cmaq) model and the Community Regional Atmospheric Chemistry Multiphase Mechanism (CRACMM; https://www.epa.gov/cmaq/cracmm). The CMAQ model has been used for decades by authorities to demonstrate compliance with air pollution rules and by the National Weather Service to provide the publicly available national ambient air quality forecast predictions.

Fellowship Goal and Learning Objectives:

Goal:  The fellow will learn how numerical models are developed by EPA and combined with measurements to advance scientific understanding of ambient air pollution sources and their impacts on public health.

Learning Objectives:

• Review existing scientific literature to develop a deep understanding of target science questions and formulate hypotheses that can be tested with numerical atmospheric models of appropriate scales.
• Understand the data and configuration requirements needed to execute an atmospheric model simulation so that useful model results can be generated independently.
• Analyze predictive data along with available measurements (e.g., in situ and remote sensing) to gain new insights illustrated with publication-appropriate figures.
• Submit findings to peer-reviewed journals and present to partners within EPA and other agencies, as appropriate.

Preferred Skills and Qualifications:

Preferred Skills:

• Strong verbal and writing skills,
• Ability to work both as a part of a team and independently.
• Familiarity with a programming language (e.g., Fortran, Python, R, MATLAB) is preferred but not required.
• Familiarity with chemical computational models (e.g., CMAQ, F0AM - https://sites.google.com/site/wolfegm/models) or chemical mechanisms (e.g., CRACMM, MCM) is useful but not required.

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

Point of Contact or Research Lead:

Ben Murphy (murphy.benjamin@epa.gov)