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Early Adopter

Madhusudan Anand
Madhusudan Anand
Datair Technology Pvt Ltd

Applied Research Topic

India & Global Micro Air Quality & Pollen Monitoring & Alerting System
Co-Is: Pareekshith US Katti, Datair Technology Pvt Ltd; N Nithin Srivatsav, Datair Technology Pvt Ltd

Potential Applications Data distribution, visualization, and utility application to support decision-making tools


Air pollution continues to threaten public health around the globe, yet India faces higher than average pollution than any other country, with over 90% of its population living in areas where air quality is below World Health Organization (WHO) standards. Air pollution in India comes from several sources, including biomass burning (e.g., agricultural residue burning), vehicle emissions, industry (including brick kilns), natural sources such as mineral dust, pollen, and other sources. Depending on the source and pollutant, air pollution has different impacts on public health as well. Addressing air pollution requires an awareness of pollution levels across local, sub-national, national, and international scales, which enables more effective management, regulation, and communication to the public. Sharing real- or near real-time information allows the public to understand health risks and take preventative measures. However, India continues to face a gap in air monitoring networks or equipment. To improve air quality in India and globally, there is a clear need for additional sources of high-quality data. The use of satellite data can contribute to this data gap, particularly in places with insufficient ground-based data. Further, polarimetric and hyperspectral satellite imagery can provide information on particulate matter composition and altitude across the region observed.

The objectives of this Early Adopter project are: (1) to provide additional data on air pollution in India and internationally using cloud and aerosol data provided by PACE and (2) to ultimately understand the aerosol pollutants present for improved public health and risk management. Using hyperspectral and polarimetric data from PACE, Datair Technology will improve and expand their offering by utilizing aerosol data from the satellites to increase data coverage and quality, including analyzing the present data with that of data offered by PACE, and derive correlations and risk mitigation strategies, and climate risk assessments. Understanding these pollutants aids in several important functions, including calculating emissions, forecasting visibility, understanding extreme temperatures, accounting for carbon emissions and climate risk, predicting health impacts.

This Early Adopter project will be led by Datair Technology, a private company based in Bengaluru, India with a mission of improving air quality using data from various sources and models that consider several environmental factors. Output from this Early Adopter project will be incorporated into Datair Technology's air quality API and weather API (by place and by latitude/longitude). More information can also be found online: https://www.getambee.com/.


The availability of air quality data across India is critical for improving public health. Data on air pollution extent, scale, and geographical spread enable the governmentÂ’s ability to manage that pollution, communicate to the public about risk reduction, and ultimately address it to reduce pollution. According to Greenpeace, 22 out of 30 world's most polluted cities are in India, however, there are only ~160 Air monitoring stations in India while WHO recommends there should be 4000 stations. This lack of adequate monitoring means a lack of adequate data or insight into air pollution in the country. This offering tries to solve this issue by combining satellite sources and station data and using our algorithms to give hyperlocal data.


PACE will provide Datair Technology with continuity of aerosol retrievals. Aerosol data from the PACE mission will advance air quality models by improving and expanding scope with respect to features as well as coverage. Aerosols, air quality, and weather data will be used to forecast the long-term impact on climate, as well as help build out better products or improve existing products. PACE also has better resolution of data over land and oceans than other mission data utilized. Additionally, PACE will provide more detailed information on the properties of aerosols compared to most other satellites. PACE, as a single source of data, will provide NDVI, AOD, and cloud properties.

Involvement in the PACE Early Adopter program allows Datair Technology to become familiar with the pre-launch simulated hyperspectral and polarimetric atmospheric data datasets and metadata, post-launch L1B-L2 data, and to understand how best to incorporate these data into Datair Technology API infrastructure and data monitoring systems. It will also provide opportunities for feedback on pre-launch data file formats and metadata, user needs, the design, and general utility of PACE data products. Datair Technology will contribute user feedback to the PACE Mission given their existing applications and end users.

End User(s)

  • Public users such as pollution control agencies or researchers
  • Private companies across industries such as healthcare, weather, app developers, logistics, air purification technology developers, advertising agencies

Example end users include: NIKE (identifying the best AQI route), Brigade Group (providing air quality analysis), Bayer (supporting their sales and marketing strategy), InkRepubliq (providing data driven analytics).

SAT Partner(s)

Alexei Lyapustin, Lorraine Remer, Snorre Stamnes
Dense air pollution at India Gate, New Delhi.
Dense air pollution at India Gate, New Delhi. Pollution level generally rises in autumn due to agricultural burning and stagnant winds.
Screen capture from the Live Emissions air quality app for carbon dioxide in Mumbai, India.
Screen capture from the Live Emissions air quality app for carbon dioxide in Mumbai, India.
Flow chart diagram of data input, processing, and output for the air quality app.
Flow chart diagram of data input, processing, and output for the air quality app.