Estimation of atmospheric aerosol composition from ground‐based remote sensing measurements of Sun‐sky radiometer

Abstract

Remote sensing provides aerosol loading information, but to address climate and air quality model validation, there are additional needs to acquire aerosol composition information. In this study, a comprehensive aerosol composition model is established to quantify black carbon (BC), brown carbon (BrC), mineral dust (DU), particulate organic matters, ammonium sulfate like (AS), sea salt, and aerosol water uptake. We develop forward modeling of aerosol components, including microphysical parameters (real and imaginary refractive indices, volume fraction ratio of fine to coarse mode, and sphericity) and hygroscopic growth models, and propose an optimization scheme to estimate the components. The uncertainties caused by input parameters are also assessed. Sun‐sky radiometer measurements and meteorological data obtained during a campaign in Huairou, Beijing, are processed to estimate aerosol components, which are further compared with synchronous in situ chemical measurements. The results show generally good consistencies between remotely estimated and measured components (e.g., correlation coefficients for BC, BrC, AS, and PM2.5 lie in about 0.8–0.9). The comparisons between modeled and observed microphysical parameters also show good agreements, with the exception of sphericity, which is likely caused by high uncertainties of this parameter. Sensitivity studies show that BC and BrC are highly sensitive to imaginary refractive index, while DU is strongly correlated to both volume size and sphericity. The performance of composition retrieval is expected to be improved when the sphericity uncertainty is significantly reduced.

Aerosol optical, microphysical, chemical and radiative properties of high aerosol load cases over the Arctic based on AERONET measurements

“…Moreover, the inferred component volume fractions can be transformed into columnar mass concentrations using component densities. More details of the algorithm can be found in our previous study 12 .…”

“…The Aerosol Robotic Network 11 (AERONET) includes several long-term observation sites in the Arctic region and provides an online archive of the many derived aerosol parameters. Such ground-based remote sensing observations like satellite observations derive column average aerosol properties in ambient conditions 12 . Previous studies analysed the optical properties of Arctic aerosol using AERONET products 13 – 15 , and some used AERONET data to validate models and satellite retrievals 10 , 16 , 17 .…”

“…The columnar mass concentrations of the main aerosol components can be quantitatively estimated by ground-based remote sensing measurements. With the development of composition estimation algorithms 21 – 25 , a modified aerosol composition model covering major tropospheric aerosol species and a method for inferring these components with optical and microphysical parameters 12 have been proposed. In this study, we employ this method to obtain the columnar aerosol composition over the Arctic region under high aerosol load conditions.…”

A Closure Study of Total Scattering Using Airborne In Situ Measurements from the Winter Phase of TCAP

“…Values are taken from [39][40][41]. Also, this table includes values of these parameters for sea salt (or sodium chloride; NaCl) from Xie et al [42]. It should be emphasized that the measured mass fractions correspond to sub-µm particles.…”

Laboratory measurements of light scattering properties of kaolinite dust at 532 nm

“…As a result, their optical behavior does not follow the well-established Lorenz-Mie theory (Bohren and Huffman 1983). Satellite (Tanr e et al 2011;Winker et al 2007), airborne (Burton et al 2012), and ground-based (Chazette et al 2010) remote sensing techniques are powerful tools to retrieve aerosol shapes and sizes from local to global scales, though uncertainties are still significant due to variable compositions and nonsphericity effects (Xie et al 2017).…”