Earth Scientist
Earth Scientist

Biography

Hamza Ahsan is an Earth Scientist at the Pacific Northwest National Laboratory's Joint Global Change Research Institute (JGCRI) in College Park, MD. His research focuses on anthropogenic emission modeling of the atmosphere and multi-sector dynamics and interactions between human and natural systems. He is a key collaborator to the Community Emissions Data System (CEDS) where he has been developing and implementing new methodologies for quantifying historical air pollutant emissions and generating high resolution emissions data. Hamza obtained his master’s degree and bachelor’s degree in mechanical engineering from the University of Alberta, where he performed research on quantifying emissions from industrial flaring.

Research Interest

  • Anthropogenic emissions modelling
  • Multisector dynamics
  • Bioenergy

Education

  • MS in Mechanical Engineering, University of Alberta
  • BS in Mechanical Engineering, University of Alberta

Publications

2024

  • Lin, M., Horowitz, L. W., Zhao, M., Harris, L., Ginoux, P., Dunne, J., Malyshev, S., Shevliakova, E., Ahsan, H., Garner, S., Paulot, F., Pouyaei, A., Smith, S. J., Xie, Y., Zadeh, N., & Zhou, L. (2024). The GFDL Variable‐Resolution Global Chemistry‐Climate Model for research at the nexus of US climate and air quality extremes. Journal of Advances in Modeling Earth Systems, 16(4). https://doi.org/10.1029/2023ms003984

2023

  • Ahsan, H., Wang, H., Wu, J., Wu, M., Smith, S. J., Bauer, S., Suchyta, H., Olivié, D., Myhre, G., Matsui, H., Bian, H., Lamarque, J.-F., Carslaw, K., Horowitz, L., Regayre, L., Chin, M., Schulz, M., Skeie, R. B., Takemura, T., Naik, V. (2023). The Emissions Model Intercomparison Project (Emissions-MIP): quantifying model sensitivity to emission characteristics. Atmos. Chem. Phys., 23, 14779–14799, https://doi.org/10.5194/acp-23-14779-2023
  • Ahsan, H., Khan, Z., Snyder, A., Kyle, P., Vernon, C.R. (2023). osiris: An R package to process climate impacts on agricultural yields for the Global Change Analysis Model. Journal of Open Source Software, 8(85), 5226. https://doi.org/10.21105/joss.05226