Atmospheric Chemistry Modeling Group – Harvard University
ACMG Mickley Subgroup
Group Leaders Daniel J. Jacob and Loretta J. Mickley
Loretta J. Mickley
Senior Research Fellow
John A. Paulson School of Engineering and Applied Sciences
Harvard University
Loretta Mickley co-leads the Atmospheric Chemistry Modeling Group at Harvard. Her research focuses on chemistry-climate interactions in the troposphere. She seeks to understand how short-lived gases and particles affect climate and how climate, in turn, influences atmospheric composition. Key topics:
- Effects of climate change on smog episodes and wildfires.
- Impacts of aerosol trends on regional climate.
- Oxidation capacity and fire activity in preindustrial and paleo atmospheres.
- Effects of air pollution on human health.
Pierce Hall 109A, 29 Oxford Street, Cambridge, MA 02138
mickley@fas.harvard.edu, mickley@seas.harvard.edu
Xu Feng
Postdoctoral Fellow
John A. Paulson School of Engineering and Applied Sciences
Harvard University
Makoto Kelp
PhD 2023
Department of Earth and Planetary Sciences
Harvard University
Makoto’s research focuses on using machine learning to expand the capabilities of atmospheric chemistry models, developing dimensionality reduction algorithms that can determine the optimal placement of air quality sensors, and quantifying impacts of chemical data assimilation on air pollution forecasts for NASA’s GEOS Composition Forecasting model (GEOS-CF).
Tianjia (Tina) Liu
PhD 2022
Department of Earth and Planetary Sciences
Harvard University
The main goals of Tina’s research all evolve around fire: 1) investigation of trends in the timing and magnitude of crop residue burning in northwestern India (Punjab and Haryana), as well as the drivers and air quality consequences of these shifts; 2) quantification of smoke exposure and public health impacts associated with fire emissions in Indonesia; and 3) assessment of wildfires and fire-related smoke in North America. She uses a combination of remote sensing, GIS, statistics, and atmospheric modeling with both ground-based and satellite-derived datasets.
