Publications

Chelani, AB (2019). Estimating PM2.5 concentration from satellite derived aerosol optical depth and meteorological variables using a combination model. ATMOSPHERIC POLLUTION RESEARCH, 10(3), 847-857.

Abstract
In India, PM2.5 concentration is monitored at few locations by various agencies. The measurements are sporadic over temporal and spatial scales and include a lot of missing data. Satellite-based observations can complement the existing network of these measurements. In this study, Moderate Resolution Imaging Spectroradiometer (MODIS) derived Aerosol Optical Depth (AOD) at five cities in Maharashtra, India was used in estimating ground PM2.5 concentration during January 2016-May 2017. Meteorological parameters were also included in the model to enhance the accuracy. A combination model that combines multiple linear regression (MLR) and residuals of MLR was developed to obtain the estimates. The applicability of the approach was assessed for the two types of time series; one with less frequency of missing data and the other with a high frequency of missing data. The spatial analysis suggested high AOD at Mumbai. It was observed that the inclusion of meteorology in the regression equation improved the performance of the MLR model. The combination model outperformed MLR due to the consideration of residuals of the MLR model.

DOI:
10.1016/j.apr.2018.12.013

ISSN:
1309-1042