Air quality of north Indian cities has worsened over the last few decades which has been posing a great risk to consequential health-related issues. Ground-based monitoring of particulate matter smaller than 10 μ m( PM10 )i n Indian cities has been limited to few selective sites at local hot spots, and thus, related health studies at regional scale were constrained. To overcome this issue, we utilized the aerosol optical depth (AOD) from Moderate Resolution Imaging Spectroradiometer (MODIS) onboard EOS Terra and Aqua satellites to estimate the regional PM10 concentration in Agra City located in the northern part of India. The approach envisaged the developments of linear, log-linear, and multi- linear regression models to estimate PM10 using AODMODIS and in situ measured meteorological parameters by utilizing the data of years 2010 and 2011. The results indicated that both hourly and 24-h average PM10 had a weak correlation withAODMODISwhenchosenas the onlyregressor. However, hourly PM10 showed better correlation with AODMODIS (R ~0.45) than 24-h average PM10 (R ~0.24). The log-linear estimation of PM10 utilizing AODMODIS ,r elative humidity, wind speed, and atmospheric temperature as regressors had the highest correlation coefficient (R=0.81) and a minimum relative standard error as 8.93 %, and thus, it was able to provide the best estimates of PM10 among all the models