Research

Dust morphology and its impact on the aerosol optics, reactive uptake of trace gases and UV-Vis trace gas retrievals

Mineral dust is often treated as spherical in chemical transport and trace gas retrieval models. We investigate how dust shape affects gas-particle and radiation-particle interactions. We examine the impact of dust shape on optical properties and trace gas retrievals at ultraviolet and visible wavelengths. We find that treating dust as nonspherical in trace gas retrievals of nitrogen dioxide decreases the retrieval sensitivity to dust. We also examine the impact of dust shape on heterogeneous chemistry by developing and applying a theoretical model. We find that dust pores change particle surface area significantly and subsequently, reaction and diffusion parameters. Overall, this study signifies the importance of accounting for nonsphericity in chemical transport and trace gas retrieval models.

Fire plume height and it’s impact on the surface PM2.5 inferred from satellite AOD

Wildfires can inject smoke at high altitudes in the atmosphere. The resulting free tropospheric aerosols may affect inference of ground-level fine particulate matter (PM2.5) from satellite retrievals of columnar aerosol optical depth (AOD), yet the effects of accounting for plume height in this inference are poorly understood. In this study, we include in the GEOS-Chem chemical transport model a plume height parameterization (GFAS, Global Fire Assimilation System) that represents the vertical distribution of wildfire smoke to examine its effect on PM2.5 inferred from satellite AOD during wildfires over the United States and Canada. We examine the GFAS plume height against satellite observations from EPIC (Earth Polychromatic Imaging Camera) and find a low bias of a factor 1.7 in the GFAS plume height over evergreen needleleaf forests of North America during the six years examined (2016-2018, 2020-2022). We scale the GFAS plume height over evergreen needleleaf forests in GEOS-Chem to better represent the EPIC observations. We focus on the years 2018 and 2020 when large wildfires yield prominent signals. We find that replacing the default ground-level wildfire emissions in GEOS-Chem with the scaled GFAS vertically distributed emissions reduces the bias between measured PM2.5 and PM2.5 inferred from MAIAC satellite AOD for 2018 (slope decreases from 2.6 to 1.4) and for 2020 (slope decreases from 2.7 to 0.98). Vertically distributing the wildfire emissions using GFAS plume height also improves the simulated AOD versus sun photometer observations in 2018 (slope increases from 0.35 to 0.86, r^2 increases from 0.41 to 0.46) and 2020 (slope increases from 0.20 to 0.79, and r^2 increases from 0.32 to 0.88). Overall, this study signifies the importance of vertically distributing wildfire emissions for inference of PM2.5 from satellite AOD during wildfires.