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The focus of this study is to assess spatiotemporal variability of tropospheric NO2over South Asia using data from spaceborne OMI during the past decade (2004–2015). We find an average value of NO21.0 ± 0.05 × 1015 molec/cm2and a significant decadal increase of 14%. The elevating NO2pollution over the region is linked to rise in motor vehicles and industrial and agricultural activities and increase in biomass fuel usage. The observed seasonality of NO2is associated with change in meteorological conditions and seasonal cycles of anthropogenic emissions. OMI data reveal a seasonal peak in spring followed by winter largely linked to metrological conditions and anthropogenic emissions from crop residue and biomass burning for heating purpose, and low concentration in summer is mostly attributed to meteorological conditions. Significant increase, up to 42%, in NO2concentrations over northwestern IGB, is observed connected to large scale postmonsoon crop residue events of 2010 and 2012. It is seen that NO2is mounting over all the hotspot locations and most of the cities. Dhaka shows the highest increase of 77% followed by Islamabad (69%), Kabul (68%), Korba (64%), Bardhaman (47%), and Lahore (40%). On the contrary, DG Khan has shown negative trend of −11%.

This study compares the suitability of different satellite-based vegetation indices (VIs) for environmental hazard assessment of municipal solid waste (MSW) open dumps. The compared VIs, as bio-indicators of vegetation health, are normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), and modified soil adjusted vegetation index (MSAVI) that have been subject to spatiotemporal analysis. The comparison has been made based on three criteria: one is the exponential moving average (EMA) bias, second is the ease in visually finding the distance of VI curve flattening, and third is the radius of biohazardous zone in relation to the waste heap dumped at them. NDVI has been found to work well when MSW dumps are surrounded by continuous and dense vegetation, otherwise, MSAVI is a better option due to its ability for adjusting soil signals. The hierarchy of the goodness for least EMA bias is MSAVI> SAVI> NDVI with average bias values of 101 m, 203 m, and 270 m, respectively. Estimations using NDVI have been found unable to satisfy the direct relationship between waste heap and hazardous zone size and have given a false exaggeration of 374 m for relatively smaller dump as compared to the bigger one. The same false exaggeration for SAVI and MSAVI is measured to be 86 m and-14 m, respectively. So MSAVI is the only VI that has shown the true relation of waste heap and hazardous zone size. The best visualization of distance-dependent vegetation health away from the dumps is also provided by MSAVI.