By Ryleigh Czajkowski

I have always been curious about the weather and climate, as my dad was a pilot and used to teach me little things about the atmosphere. When I entered college, I decided to follow that curiosity by majoring in atmospheric sciences and developed a new interest in air quality along the way. Air quality is an issue that has global effects with potential detrimental impacts, and I would like to find a job that uses scientific understanding of air pollution to make impactful actions and policies. Specifically, I would like to go into pollution modeling and management to help mitigate the effects of pollution on communities and ecosystems.

This interest was sparked during an internship I had last summer as part of NASA’s Student Airborne Research Program (SARP). This experience allowed me to use airborne data to validate the Environmental Protection Agency’s (EPA) Community Multiscale Air Quality Model (CMAQ), to see how accurately the model predicts the concentrations of different pollutants. The CMAQ model works by incorporating meteorological (wind, temperature, etc.), emission, and chemical models to simulate the concentrations of trace gases, particulate matter, and atmospheric pollutants both spatially and temporally (EPA, 2022). 

For my senior capstone project, I will be expanding on my previous research to build a better understanding of the capabilities of the model, as it recently underwent an update in 2022 to improve the meteorological processes and emissions. I will focus on the South Coast Air Basin in California, an area with known, notable air quality issues (Chen, et al., 2020) and the levels of formaldehyde and methane there. Both methane and formaldehyde act as active gases in the atmosphere. With methane concentrations on the rise (Feng, et al., 2023) and formaldehyde as a health and environmental irritant (Lucken, et al., 2018), they are important gases to study and understand. I will be assessing how well the CMAQ model can simulate the concentrations of formaldehyde and methane in the atmosphere, as well as the accuracy of  the meteorological inputs (i.e., wind) as they greatly affect the behavior and amounts of those gasses. (Barsanti, et al., 2019). 

CMAQ is a beneficial tool that is utilized by agencies such as the National Weather Service to put out public health warnings and the EPA to monitor pollution levels nationally (EPA, 2022). By gaining an understanding of how accurately the model simulates gas concentrations and meteorological parameters, it will help these regulatory agencies put out better warnings and policies to help safeguard the health and safety of the public and the environment. Additionally, studying the capabilities will allow for insight into how to make the model more accurate and provide scientists with an understanding into what/how pollution processes are changing and developing. In studying this model, it will not only help with scientific development but allow for the progress towards a safer and healthier environment in the future.

Citations

• Barsanti, K. C., Pickering, K. E., Pour-Biazar, A., Saylor, R. D., & Stroud, C. A. (2019). The Sixth External Peer Review of the Community Multiscale Air Quality (CMAQ) Modeling System. Environmental Protection Agency (EPA). https://www.epa.gov/sites/default/files/2019-08/documents/sixth_cmaq_peer_review_comment_report_6.19.19.pdf
• Chen, J., Yin, D., Zhao, Z., Kaduwela, A. P., Avise, J. C., DaMassa, J. A., Beyersdorf, A., Burton, S., Ferrare, R., Herman, J. R., Kim, H., Neuman, A., Nowak, J. B., Parworth, C., Scarino, A. J., Wisthaler, A., Young, D. E., & Zhang, Q. (2020). Modeling air quality in the San Joaquin Valley of California during the 2013 Discover-Aq Field campaign. Atmospheric Environment: X, 5, 100067. https://doi.org/10.1016/j.aeaoa.2020.100067
• Environmental Protection Agency (EPA). (2022). Community Multiscale Air Quality (CMAQ) Modeling System. EPA. https://www.epa.gov/system/files/documents/2022-10/CMAQ_Factsheet_2022.pdf
• Feng, L., Tavakkoli, S., Jordaan, S. M., Andrews, A. E., Benmergui, J. S., Waugh, D. W., Zhang, M., Gaeta, D. C., & Miller, S. M. (2023). Inter‐annual variability in atmospheric transport complicates estimation of US methane emissions trends. Geophysical Research Letters, 50(14). https://doi.org/10.1029/2022gl100366
• Luecken, D. J., Napelenok, S. L., Strum, M., Scheffe, R., & Phillips, S. (2018). Sensitivity of ambient atmospheric formaldehyde and ozone to precursor species and source types across the United States. Environmental Science & Technology, 52(8), 4668–4675. https://doi.org/10.1021/acs.est.7b05509