Colins Johnny Jesudhas

The upper Kodaganar basin, located in Dindigul district of Tamil Nadu, India, is composed of hard rock terrain. Groundwater is the major source of domestic and irrigation needs and it is being contaminated by tannery wastewater that is discharged into the nearby Sengulam Lake. The main aim of this work was to develop a contaminant transport model using the total dissolved solids (TDS) concentration of groundwater measured in the basin. The model was developed to predict the fate of contaminant in the aquifer. The TDS concentrations in the wells ranged from 249 to 20,120 mg/L, wherein extremely high values were observed in some of the severely contaminated wells. Three scenarios were proposed to predict the fate of the contaminant and to mitigate the effect of contaminant on groundwater receptors for the year 2020: scenario I: developed with the existing discharge conditions; scenario II: developed with discharge as per the standards; scenario III: developed with zero discharge. The results of this study showed that scenario III reduced the contaminated area from 12 km² to 6 km². The reduction in area for different concentration contours, namely 2000 mg/L, 5000 mg/L, 10,000 mg/L, and 15,000 mg/L, was 2 km², 0.5 km², 0.2 km², and 0.1 km², respectively, and the groundwater remediation was expected to take 2050 years. Hence, there is an urgent need for the application of clean and resource efficient technologies in process industries, and the implementation of suitable wastewater treatment technologies to prevent ground water pollution in the region.

Sponsored by the Environmental & Water Resources Institute (EWRI)

COVID-19 pandemic situation has highly restricted the human movements including public transport, commercial and industrial activities in India since the end of March 2020. With the necessity to demonstrate the effectiveness of local emissions, the study aims in analysing the relative variation of ambient air quality before and during COVID-19 with the aid of in situ measurement and Sentinel 5P space technologies. ESA Sentinel 5P Level 2 data \sets including Carbon monoxide (CO), nitrogen dioxide (NO₂), Sulphur dioxide (SO₂), and Ozone (O₃)were pre-processed in SNAP and QGIS platform for the extraction of air quality parameters. Results concluded that the concentration of air quality parameters CO, NO₂, SO₂, and O₃reduced 50.52%, 85.81%, 71.61% and 313.4%, respectively, between March and June 2020. Accuracy of air quality parameters CO, NO₂, SO₂, and O₃obtained from Sentinel 5P datasets are found to be 89.5%, 83.54%, 86% and 94%, respectively, when compared with the in situ measurements. As a favourable outcome of the COVID 19 lockdown, better air quality is recorded over the vulnerable locations due to the absence of significant activities and with the improvement in the air quality the study illustrates the importance of temporary pollution source control measures in a suitable time interval. Integration of in situ measurements and satellite datasets will remove the conventional barriers and provide spatially distributed observations that can assist the decision-makers in formulating the best air pollution control strategy.