The Paris Agreement by INFCCC entered into force in late 2016 was aimed to strengthen the global response to the threat of climate change by keeping a global temperature rise this century well below 2 degrees Celsius above pre-industrial levels and to pursue efforts to limit the temperature increase even further to 1.5 degrees Celsius.
To achieve this goal lot of international protocols and mechanisms were signed in the past like the Kyoto protocol, the Emission Trading mechanism but none of them gave any significant results till today.
The biggest problem to collectively achieve this is the socio-economic gaps between the developed and developing/underdeveloped nation.
Clean air is a fundamental right, integral to the idea of citizenship.
The SDG 3: Health and well being and SDG 11, Sustainable Cities and Communities providing attention to air quality were ignored globally in a race to achieve self economic development targets.
This has created a situation of race among nations and hence less collaboration to fight global climate challenges.
The inspiration to this came once I saw that the Air Quality Index of my nation's capital New Delhi is below 50 (Good) and I saw this much low first time in my lifetime and I think from the day these AQI stations are installed across sites in India. From the last few years, the AQI in New Delhi was one of the worse among all the cities in the world. This gave us an opportunity to think about how we have leveraged this opportunity to achieve something which was impossible without such massive economic lockdown.
The approach is to solve the existing problem of countries (specially developed) by providing them fresh lookup guidelines to achieve a trade-off between development goals and at the same time fight climate change targets.
We have analyzed the pollution level data before, during, and after the lockdown across countries, it gave us a picture of how much transportation has an effect over the pollution levels in urban areas.
The tools/existing analysis data used are:
1. Analyzing Data at WorldView reference sources mentioned below
2. Giovanni
3. Manual Analysis
References:
1. Analyzing Data at WorldView from source:
- MODIS Aqua/Terra Combined Algorithm AOD
- VIIRS Level 2 Deep Blue Aerosol Productand Level 3
- TROPOMI NO2 from Earthdata Search, ESA TROPOMI NO2
- AIRS CO data from Earthdata Search, TROPOMI CO data from Earthdata Search
2. https://iasi.aeris-data.fr/covid-19/
- Specially analyzing China and the USA the conclusion was that if we don't look at the problem of climate change now then we might not get another such a chance. China after lockdown shows the same emissions as before the lockdown. Another noticeable thing was that the NH3 emission was higher during the lockdown period across the globe due to the harvest session.
- By comparing the pollutants emission across big economies USA, China, Russia, and Europe, it has given insights on the decrease in the pollution levels in the environment during the lockdown period
3. https://airquality.gsfc.nasa.gov/
- Analyzing SO2 data in the Indian subcontinent:
https://airquality.gsfc.nasa.gov/slider/omi-detected-so2-change-over-india-after-national- lockdown
4. https://fluid.nccs.nasa.gov/cf/totcol_geos_cf/
5. https://www.epa.gov/air-trends
6. https://earthdata.nasa.gov/learn/pathfinders/covid-19/environmental-impacts