Bridging Surface and Column Perspectives: Insights into Aerosol Chemical Composition and Optical Properties from SPARTAN and AERONET Data

This study integrates long-term data from the Surface Particulate Matter Network (SPARTAN) and the Aerosol Robotic Network (AERONET) to analyze the relationship between aerosol chemical composition and optical properties across 14 globally distributed sites. SPARTAN provides filter-based measurements of PM_2.5 chemical species, including ammoniated sulfate (AS), ammonium nitrate (AN), fine soil (FS), and black carbon (BC). In contrast, AERONET offers column-based remote sensing optical data, such as aerosol optical depth (AOD), fine mode fraction (FMF), and single scattering albedo (SSA). By applying a collocation methodology to harmonize the SPARTAN and AERONET datasets, we conducted a detailed investigation of aerosol behavior using data collected from 2016 to 2023. Notable differences in aerosol optical properties were observed according to the mass differences and mass ratios of these chemical components. For FS, an increase in its mass led to decreases in dSSA and FMF, with changes of 0.0045 and 0.033 per 1 µg/m³, respectively. For non-absorbing components like AS and AN, an increase in their mass ratio consistently increased SSA across all wavelengths. This relationship was further supported by grouping data by PM_2.5/AOD categories, revealing a correlation coefficient as high as 0.69. This integrated approach bridges the gap between column-based optical properties and surface-level chemical measurements, providing novel insights into aerosol classification and behavior. The findings underscore the importance of combining SPARTAN and AERONET datasets to enhance the understanding of aerosol dynamics and atmospheric impacts.

 

This work was supported by a grant from the National Institute of Environment Research (NIER), funded by the Ministry of Environment (MOE) of the Republic of Korea (Grant Number NIER-2021-03-03-007) and the Korea Meteorological Administration Research and Development Program under Grant RS-2024-00404042.