This is an exciting topic which studied at the air quality in Mumbai city, India. My peer gave a detailed presentation on the background of Mumbai, which is the most populated city in India and the fifth most populated in the world. The air quality in the city deteriorated from 2004 to 2012, and the potential influenced factors included polluting factories, better cars, and better fuel options. The objectives and method are also clearly demonstrated in the presentation. The first objective is to interpolate the air quality in regions where does not have data from the monitoring station, and the second objective is to determine the economic costs of. Morbidities caused by air pollution. Then, I really admire that the research conducted three types of GIS interpolation to predict air quality. However, it is a pity that the study did not give a clear visualization to present the air quality results. The table and graphs cannot represent the complete results and audience may understand the effect better by showing the interpolating raster maps. On the other hand, my peer indicated the research could be flawed because of limited station collecting data and incomplete influential variables.