Aerosol climatology characterization over Bangladesh using ground-based and remotely sensed satellite measurements

Abstract

Atmospheric aerosols affect human health, alter cloud optical properties, influence the climate and radiative balance, and contribute to the cooling of the atmosphere. Aerosol climatology based on aerosol robotic network (AERONET) and ozone monitoring instrument (OMI) data from two locations (Urban Dhaka and coastal Bhola Island) over Bangladesh was conducted for 8 years (2012–2019), focusing on two characterization schemes. Four aerosol parameters, such as extinction angstrom exponent (EAE), absorption AE (AAE), single scattering albedo (SSA), and real refractive index (RRI), were exclusively discussed to determine the types of aerosol. In addition, the light absorption properties of aerosol were inspected tagging the association between size parameters similar to fine mode fraction (FMF), AE, and absorption parameters (SSA and AAE). Results of aerosol absorption optical depth (AAOD) were validated with the satellite-borne cloud–aerosol lidar and infrared pathfinder satellite observation (CALIPSO) aerosol subtype profiles. The overall average values of AAOD for Dhaka and Bhola were (0.110 ± 0.002) [0.106, 0.114] and (0.075 ± 0.001) [0.073, 0.078], respectively. The values derived by OMI were the similar (0.024 ± 0.001 [0.023, 0.025] for Dhaka, and 0.023 ± 0.001 [0.023, 0.024] for Bhola). Two types of aerosols were potentially identified, for example, biomass burning and urban/industrial types over Bangladesh with insignificant contribution from the dust aerosol. Black carbon (BC) was the prominent absorbing aerosol (45.9%–89.1%) in all seasons with negligible contributions from mixed BC and/or dust and dust alone. Correlations between FMF and SSA confirmed that BC was the dominant aerosol type over Dhaka and Bhola. CALIPSO’s vertical information was consistent with the AERONET column information. The results of aerosol parameters will have a substantial impact on the aerosol radiative forcing, and climate modeling as well as air quality management in Southeast Asia’s heavily polluted territories.