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Title: Relationship Between Satellite-derived Aerosol Optical Depth and Ground Level Pm10 Concentrations at Shimla
Authors: Sharma, Guru Sharan Dass
Ganguly, Rajiv [Guided by]
Keywords: Particulate matter
Moderate resolution imaging spectroradiometer
Aerosol optical depth
Issue Date: 2016
Publisher: Jaypee University of Information Technology, Solan, H.P.
Abstract: Aerosols are a fundamental component of Earth’s atmospheric chemistry and radiative balance. Atmospheric aerosols can affect climate through the Earth’s radiation balance by scattering and absorbing incoming solar radiation and by acting cloud condensation nuclei. Atmospheric aerosols play a important role in the understanding of global and regional climate effects. Knowledge of aerosol properties is essential for correcting the atmospheric effect in satellite remote sensing of Earth’s surface. Therefore, the understanding of aerosol and their radiative effects are important in climate forcing studies. To assess the relationship of ground-level fine particulate matter (PM) the concentrations measured as part of the National Ambient air quality monitoring (NAAQM) network at two monitoring stations in Shimla city, versus remote-sensed PM10 determined from aerosol optical depth (AOD) calculated by the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite instruments. The Shimla city in Himachal Pradesh has air quality trouble directly attributed to particulate matter in India primarily due to vehicular emissions. State and Central regulatory agencies monitor particulate matter with a network of ground sensors throughout the Shimla. Satellite technology provides aerosol optical depth data for the entire world every two days. Varying degrees of correlation have been found worldwide in the research of comparing satellite aerosol optical depth to ground sensor particulate matter. The satellite and ground data were compared on the basis of the linear correlation(R), standard deviation(SD), index of agreement (IA), normalized mean square error (NMSE), Pearson’s correlation coefficient (R), the fractional bias (FB) and the factor of two (F2). In Shimla comparing PM10 data to satellite aerosol optical depth data demonstrates a varying correlation seasonly.
Appears in Collections:Dissertations (M.Tech.)

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