Differentiating the Contributions of Particle Concentration, Humidity, and Hygroscopicity to Aerosol Light Scattering at Three Sites in China

Abstract

The scattering of light by aerosol particles dictates atmospheric visibility, which is a straightforward indicator of air quality. It is affected by numerous factors, such as particle number size distribution, particle mass concentration (PM2.5), ambient relative humidity (RH), and chemical composition. The latter two factors jointly influence the aerosol liquid water content (ALWC). Here, the particle backscattering coefficient (βp) under ambient RH conditions is investigated to differentiate and quantify the contributions of aerosol properties and meteorology using comprehensive observational datasets acquired at three megacities in China, that is, Beijing (BJ), Nanjing (NJ), and Guangzhou (GZ). Overall, the temporal variations in βp under ambient RH conditions are consistent with those in ALWC at the three sites. The PM2.5 in BJ is systematically higher than in NJ and GZ, while ambient RH and aerosol hygroscopicity in NJ are much higher than in BJ and GZ. Notable differences in the variations of βp with related factors at the three sites are demonstrated. βp is more sensitive to particle hygroscopicity and mass in NJ and ambient RH in BJ. The relative contributions of these factors to βp at the three sites under different pollution conditions are differentiated and quantified. The factor with the largest impact on the variability in βp shifts from particle mass to ambient RH as air quality deteriorated to heavy pollution in BJ. The opposite is true in NJ. In GZ, the contributions of these factors to changes in βp under different pollution conditions are similar, both dominated by PM2.5.

The Spatio-Temporal Variability in the Radiative Forcing of Light-Absorbing Particles in Snow of 2003–2018 over the Northern Hemisphere from MODIS

“…The concentration of LAPs dominates this pattern, resulting in radiative forcing variations of −0.024 W m −2 a −1 in HEUA and −0.068 W m −2 a −1 in NEC, followed by the SI, which accounts for −0.012 W m −2 a −1 (HEUA) and −0.048 W m −2 a −1 (NEC) of interannual variability. These results confirm that levels of airborne pollution decreased during the observation period in both HEUA and NEC, thereby supporting the findings of previous studies [40,[68][69][70][71].…”

“…As previous studies (e.g., Wu et al, 2021 [70]; Cui et al, 2021 [14]; Jin et al, 2022 [71]), RF is dependent primarily on the concentration of LAPs, snow grain size (SGS), snow water equivalent (SWE), solar zenith angle (SZA), cloud fraction (CF), and solar irradiance (SI). An impurity index (I imp ) is utilised to represent the LAP concentration in snow [31,58]:…”