Variability in optical properties of atmospheric aerosols and their frequency distribution over a mega city “New Delhi,” India

The role of atmospheric aerosols in climate and climate change is one of the largest uncertainties in understanding the present climate and in capability to predict future climate change. Due to this, the study of optical properties of atmospheric aerosols over a mega city “New Delhi” which is highly polluted and populated were conducted for two years long to see the aerosol loading and its seasonal variability using sun/sky radiometer data. Relatively higher mean aerosol optical depth (AOD) (0.90 ± 0.38) at 500 nm and associated Angstrom exponent (AE) (0.82 ± 0.35) for a pair of wavelength 400–870 nm is observed during the study period indicating highly turbid atmosphere throughout the year. Maximum AOD value is observed in the months of June and November while minimum is in transition months March and September. Apart from this, highest value of AOD (AE) value is observed in the post-monsoon [1.00 ± 0.42 (1.02 ± 0.16)] season followed by the winter [0.95 ± 0.36 (1.02 ± 0.20)] attributed to significance contribution of urban as well as biomass/crop residue burning aerosol which is further confirmed by aerosol type discrimination based on AOD vs AE. During the pre-monsoon season, mostly dust and mixed types aerosols are dominated. AODs value at shorter wavelength observed maximum in June and November while at longer wavelength maximum AOD is observed in June only. For the better understanding of seasonal aerosol modification process, the aerosol curvature effect is studied which show a strong seasonal dependency under a high turbid atmosphere, which are mainly associated with various emission sources. Five days air mass back trajectories were computed. They suggest different patterns of particle transport during the different seasons. Results suggest that mixtures of aerosols are present in the urban environment, which affect the regional air quality as well as climate. The present study will be very much useful to the modeler for validation of satellite data with observed data during estimation of radiative effect.