Machine learning-based country-level annual air pollutants exploration using Sentinel-5P and Google Earth Engine

Area of Science:

• Environmental Science and Remote Sensing
• Atmospheric Chemistry and Air Quality Monitoring

Background:

• Anthropogenic activities are driving climate change and global warming, leading to increased air pollution.
• Key air pollutants such as Nitrogen Dioxide (NO2), Carbon Monoxide (CO), and Aerosol Optical Depth (AOD) pose significant risks to environmental and human health.
• Effective monitoring of atmospheric conditions is essential for understanding and mitigating these risks.

Purpose of the Study:

• To monitor and analyze atmospheric air pollutants and chemical conditions from 2018 to 2021.
• To assess the impact of anthropogenic activities on air quality using satellite data.
• To investigate spatial and temporal variations in NO2, CO, and AOD across major Indian cities.

Main Methods:

• Utilized Earth observational Sentinel-5P satellite data for atmospheric monitoring.
• Employed the Google Earth Engine (GEE) cloud computing platform for data processing and analysis.
• Analyzed variations in NO2, CO, and AOD levels in key urban areas including Delhi and Kolkata.

Main Results:

• Observed significant increases in NO2 and CO levels, directly linked to anthropogenic activities.
• Air Quality Index (AQI) showed higher fluctuations in 2020-2021 compared to 2018-2019.
• High NO2 concentrations were recorded in Delhi and Kolkata, with substantial fluctuations noted in Mumbai, Pune, and Chennai; Uttar Pradesh showed high AOD in 2020.

Conclusions:

• Anthropogenic factors are demonstrably increasing harmful air pollutants, necessitating urgent attention.
• The study highlights the critical need for continuous air pollutant investigation for effective future planning and management.
• Failure to address air pollution risks severe consequences for the planet and the existence of life.