Field evidence of brown carbon absorption enhancement linked to organic nitrogen formation in Indo-Gangetic Plain.

Atmospheric brown carbon (BrC), a short-lived climate forcer, absorbs solar radiation and is a substantial contributor to the warming of the Earth's atmosphere. BrC composition, its absorption properties, and their evolution are poorly represented in climate models, especially during atmospheric aqueous events such as fog and clouds. These aqueous events, especially fog, are quite prevalent during wintertime in Indo-Gangetic Plain (IGP) and involve several stages (e.g., activation, formation, and dissipation, etc.), resulting in a large variation of relative humidity (RH) in the atmosphere. The huge RH variability allowed us to examine the evolution of water-soluble brown carbon (WS-BrC) diurnally and as a function of aerosol liquid water content (ALWC) and RH in this study. We explored links between the evolution of WS-BrC mass absorption efficiency at 365 nm (MAE) and chemical characteristics, viz., low-volatility organics and water-soluble organic nitrogen (WSON) to water-soluble organic carbon (WSOC) ratio (org-N/C), in the field (at Kanpur in central IGP) for the first time worldwide. We observed that WSON formation governed enhancement in MAE diurnally (except during the afternoon) in the IGP. During the afternoon, the WS-BrC photochemical bleaching dwarfed the absorption enhancement caused by WSON formation. Further, both MAE and org-N/C ratio increased with a decrease in ALWC and RH in this study, signifying that evaporation of fog droplets or bulk aerosol particles accelerated the formation of nitrogen-containing organic chromophores, resulting in the enhancement of WS-BrC absorptivity. The direct radiative forcing of WS-BrC relative to that of elemental carbon (EC) was ∼19 % during wintertime in Kanpur, and ∼ 40 % of this contribution was in the UV-region. These findings highlight the importance of further examining the links between the evolution of BrC absorption behavior and chemical composition in the field and incorporating it in the BrC framework of climate models to constrain the predictions.