From our study we are able to infer that COVID19 has influenced the progress in SDG indicators in the manners listed below. In carrying out this study, we have used open-source data, primarily obtained from NASA Satellites and a few other organizations as cited accordingly.

1. In addressing global warming, one leading pollutant besides the GHG is NO2. We compare the NO2 emissions in the Indian Sub-continent over Jan-May 2019 and 2020. Particularly we plot the data for densely populated cities with high traffic congestion (over 75% on any regular day)- namely, Delhi and Bengaluru. NO2 data is obtained from Sentinel-5P. We know, the major source of NO2 emissions is the burning of fossil fuels and petroleum-derived products, especially used in cars or the burning of firewood in rural areas. Being urban areas with the widespread use of LPG/CNG for culinary requirements, the amount of NO2 emitted due to the burning of firewood is almost negligible in these cities. Hence, the major source of NO2 emissions in these two cities is the burning of fuels used in vehicles. Due to the lockdown imposed, human mobility was restricted and there were very few vehicles moving on the road, only in an emergency, with transport being minimum in the month of April. In Bengaluru, it reflects a 39% drop in NO2 emissions when compared to April 2019 and the NO2 emissions in during Jan-May 2020 are 23.9% lower than in 2019. Similarly, in Delhi, the NO2 emissions dropped by almost 59% in the month of April 2020 when compared to April 2019 and by around 40% compared to March 2020. This sudden drop can be attributed to reduced mobility. As a validation, we compared the NO2 emissions in Bhuj, a deserted region,  where the nominal NO2 concentration is already extremely low due to very little emission activities taking place here. We were able to notice a dip of almost 22 % in Apr 2020 when compared to Apr 2019. This speaks volumes of how reducing the NO2 emissions at hotspots also affects the overall air standards across the country and even farther.  Therefore, we may conclude that the lockdown helped in significantly lowering the NO2 content in the atmosphere. Additionally, if the NO2 emissions continue to be reduced, either by adopting public transport, or electric vehicles (with electricity obtained from renewable sources) over a long time, we can hope for less harmful effects of global warming.
2. Another important pollutant in the atmosphere is SO2. The major hotspots of SO2 emissions are power plants burning coal and oil, and other industries releasing sulphur compounds into the atmosphere. In recent years, India has been a leading contributor of SO2 emissions. However, the lockdown imposed in India due to COVID19 has reduced SO2 emissions. India obtains a huge fraction of electricity requirements from thermal power plants (almost 56%). We studied the power consumption data released by the Power System Operation Corporation Limited National Load Despatch Centre for the months of Jan- Apr in 2019 and 2020. We observed that in 2019, the power consumed increases from Feb-Apr, as expected due to the weather getting hotter and more humid during summer months. However, the power consumption dropped significantly in 2020 after Feb 2020 due to the concept of work from home. The fact that most offices and industries were shut down since mid-Mar testifies that workplaces account for almost 45% of the total energy consumed under normal conditions. We further obtained SO2 data from Sentinel-5P and compared the SO2 emissions during Jan-May 2019 and 2020. We observe over 50% drop in the SO2 emissions in the Eastern India region, which could mainly be due to the significantly reduced load on the thermal power plants. A maximum drop in SO2 emissions was recorded in early May 2020 compared to May 2019. This helps us to conclude that if we resort to renewable power generation techniques, we can cut down SO2 emissions by a huge fraction, and consequently help reduce global warming.
3. An unexplored impact of COVID19 is the variation in Sea and Land Surface Temperatures due to change in air quality. We obtained precipitation data from ECMWF ERA5 atmospheric data, while Carbon Monoxide and Water Vapour concentration data were obtained from Copernicus Sentinel 5P. We obtained LST and SST data from the MODIS satellite from Jan 2019 to May 2020. We also obtained the AOD data from AQUA AIRS. An interesting feature we noted was the variation in AOD that implicitly influenced precipitation in the Bay of Bengal region during the months of Mar-Apr 2020. The improvement in air quality observed in the form of a reduced number of aerosols helps cool the land partially. This is explained by the subtle drops in the LST during Mar-Apr 2020. We also obtained maps for relative humidity in the Kolkata region based on data from AQUA AIRS. As explained by Ng et. Al in [Ng, D.H.L., Li, R., Raghavan, S.V. et al. Investigating the relationship between Aerosol Optical Depth and Precipitation over Southeast Asia with Relative Humidity as an influencing factor. Sci Rep 7, 13395 (2017). https://doi.org/10.1038/s41598-017-10858-1], aerosols affect the precipitation by varying the cloud properties and earth’s energy budget, with relative humidity as an influencing factor. Accordingly, we obtain a positive correlation between AOD and precipitation during the stated period. The SST plots further showed a slight increase due to reduced heat-trapping aerosols in the atmosphere. In fact, this feature could have amplified the effect of Cyclone Amphan in the Bay of Bengal and this remains to be explored. The biggest takeaway from this study is an approach to explain how reducing GHG emissions eventually improves precipitation and reduces LST, which would help in achieving better agricultural produce and help combat the SDG of hunger.
4. In the wake of rising cases of COVID19 and a belief that animals carry the novel coronavirus, there was a sudden drop in an ever-increasing amount of meat production and consumption. The plot below shows quarter-yearly data obtained from the United States Department of Agriculture from 2016 to the present. The data includes the total amount of red meat and poultry produced including beef, pork, mutton, broilers, and turkeys. It is evident from the plot that the meat production varies each quarter, perhaps depending on the season and consequent food demand. Accordingly, when compared to the first quarter in the previous years, meat consumption was at a record high during the first quarter of 2020. Soon after, there is a sudden drop in total meat consumption, the lowest in at least four years, dropping by over 8% when compared to the second quarter of 2019. Particularly, beef consumption went down by over 17.3 %, pork consumption dropped by around 8.8 %, broilers by 3.6 % while the consumption of turkeys and mutton almost remained the same. Reports based on previous research suggest that a cow on an average release between 70 to 120 kg methane per year. A release of 100 kg of Methane is equivalent to the release of almost 2300 kg of Carbon Dioxide per year. We notice that despite the consumption of broilers and turkeys, remain the same, there is a significant drop in CO2 equivalent emissions. We can thus conclude that avoiding beef and pork is a major step towards reducing carbon foot-print. It is important to observe that from the time-series plots of Methane obtained from AQUA AIRS, methane emission increased when the cattle consumption went down. This is because the dependence of cattle on agricultural produce increased when consumption went down. We can extrapolate this correlation to identify how much of CH4 is released in order to raise every cow and pig until it is slaughtered. If the demand for meat decreases over time and the number of cattle raised reduces, we can significantly reduce the carbon footprint due to meat and livestock. Indirectly, this helps improve the air quality by leaps and bounds and achieve SDG3 i.e., health and wellbeing.