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the ADRF over the IGB using ground-based and satellite observations, and
through a regional aerosol optical model.
2. Methodology
The radiometers deployed at various locations around the world in a network,
e.g. Aerosol Robotic Network, AERONET, 18 MWR network by Indian Space
Research organization, 19 and the satellites measure the composite aerosol
optical properties. To infer the anthropogenic contribution to the ADRF,
one needs to delineate the anthropogenic components from the natural
ones in the composite aerosol properties. An optically equivalent aerosol
model constrained by ground-based direct and retrieved measurements of
various aerosol parameters has been developed to achieve this. In this
section, first the model features are described, followed by the method of
estimating anthropogenic fraction and the uncertainties involved in these
estimations.
2.1 . Model features
The model considers three major individual components, water-soluble
(gas-to-particle conversion and organics), black carbon (BC), and mineral
dust, based on the chemical composition analyzed in Kanpur during
the winter (December-February) season. 13 Themainideaistohavea
unique combination of these components for any particular time, which
can reproduce the composite optical properties similar to those retrieved
by AERONET. In this way, information on the individual components
can be obtained. To achieve this, first we calculated the BC number
concentrations from the measured BC mass concentration during December
2004 onwards. 9 For the earlier period (January 2001-November 2004),
we have considered the BC concentration inferred from the AERONET-
retrieved refractive index (for the algorithm, see Ref. 20). Once the BC
number concentration is fixed, the number concentrations of the other
components are varied iteratively until the model-derived composite aerosol
optical properties match with the AERONET-retrieved optical properties.
During the simulations, the aerosol vertical profiles are taken from the
aircraft measurements by Tripathi
et al. 10 , 21 over Kanpur during the winter,
pre-monsoon, and post-monsoon (October-November) seasons. Another
factor considered here is the relative humidity (RH). The model simulates
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