Seasonal Variability of Atmospheric Aerosol Parameters over Greater Noida Using Ground Sunphotometer Observations

Abstract

Atmospheric aerosols over northern India are subject of significant temporal and spatial variability and many studies have been carried out to investigate their physico-chemical and optical properties. The present work emphasizes on examining the aerosol optical properties and types over Greater Noida, Delhi region, using ground-based sun photometer data during the period 2010-2012. The analysis reveals a relatively high mean aerosol optical depth at 500 nm (AOD 500 = 0.82 ± 0.39), associated with a moderate Angstrom exponent α 440-870 of 0.95 ± 0.37. Both parameters, exhibit significant daily, monthly and seasonal variability with higher values of AOD 500 during post-monsoon (0.98 ± 0.50) and winter (0.87 ± 0.35) seasons associated with high α values (> 1.1) suggesting significant urban and biomass-burning contribution. On monthly basis, the highest AOD is found during July and November and the lowest one in the transition months of March and September. The aerosol-type discrimination via the relationship AOD vs. α shows a clear dominance of urban/industrial and biomass-burning aerosols during post-monsoon and winter in fractions of 74.5% and 72%, respectively, while aerosols of desert-dust characteristics were most frequent in pre-monsoon (41.7%) and monsoon (21%) seasons. In general, the analysis shows a rather well-mixed aerosol type under very turbid atmosphere, which is associated with the long range transport of pollutants through the westerly winds from the Thar desert and biomass burning in the western parts of India.

Ground-Based Remote Sensing of Aerosol Properties over a Coastal Megacity of Pakistan

“…A number of methodologies have been used for the classification of aerosols. Kaskaoutis et al [24], Sharma et al [25], and Tariq et al [13] used correlation of AOD and AE, while Russell et al [26] and Giles et al [27] used correlation between absorption and extinction AE to discriminate aerosol types. Russell et al [26] used absorptionÅngström exponent (440-870) (AAE) and extinctionÅngström exponent (440-870) (EAE) from AERONET to classify dominant aerosol types.…”

Analysis of size-segregated winter season aerosol data from New Delhi, India

“…It is also important to consider that in Indian cities, land-use is mixed, and as a result, different emission sources are often found in close vicinity of each other, and this can often generate complex size distribution patterns associated with small changes in wind direction. Further, longrange transport of agricultural burning aerosols (Bisht et al, 2015;Sharma et al, 2014), as well as sources such as brick kilns which do not operate within the city limits can lead to higher PM concentrations (Guttikunda and Goel, 2013).…”

Vertical Distribution and Columnar Optical Properties of Springtime Biomass-Burning Aerosols over Northern Indochina during 2014 7-SEAS Campaign

“…Dubovik et al (2002) compared different fire regions and suggested that Boreal and Amazonian forest fire smoke are less absorbing than grassland-dominated smoke from the African savanna and South American cerrado. Furthermore, recent studies have investigated aerosol mixtures (Eck et al, 2010), types (Giles et al, 2012;Kumar et al, 2014;Sharma et al, 2014), and hygroscopicity (Zhang et al, 2015) associated with haze particles by using AERONET data sets. For determining the vertical profile of smoke aerosols, lidar has proven to be a highly effective tool in aerosol characterization experiments.…”