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The present study estimates ground-level Respirable Particulate Matter (RSPM) by the combined use of satellite remote sensing Aerosol Optical Depth (AOD) at 550 nm (AOD(MODIS) or MODIS AOD) and ground-based meteorological measurements from April-2010 to March-2014 over Jaipur, semi-arid region in North-western, India.

The satellite MODIS Level 2.0 AOD is used in developing multi-regression statistical models to estimate RSPM values over the study area. The relationship between particulate matter (PM) and AOD depends on size distribution, particle composition and vertical profile of aerosols. Thus, for optimal representation of MODIS AOD, the factors like Height of Planetary Boundary Layer (HPBL) and meteorological parameters has been considered in all regression models in the present study as surrogates. The performance of regression models is analyzed on the basis of descriptive statistical measures i.e. Normalised Mean Square Error (NMSE), Correlation (R), Factor of two observations (FA2), and Fractional Bias (FB). The nonlinear multi-regression model (MODEL V) performed better than other models for our study period and region on the basis of statistical analysis (R = 0.80, NMSE = 0.01, FB = 0.0, FA2 = 100). The coefficients obtained from MODEL V were again used over Jodhpur and found to perform better than other models.

The study is further extended to find out the Air Quality Index (AQI) category over Jaipur. The average RSPM obtained from Rajasthan Pollution Control Board (RPCB) observations and those of model estimated values come under the "Moderately Polluted" category as per Indian air quality standards.