Regional training: Air quality monitoring and prediction: Leveraging advanced remote sensing and numerical modelling techniques

Date 7 May 2024 to 8 May 2024
Venue ICIMOD, Lalitpur, Nepal
Contact Persons Bhupesh Adhikary Arshini Saikia
Type Training
Programmes SG1, SG3


About the training

The SERVIR-HKH Initiative of the International Centre for Integrated Mountain Development (ICIMOD) is organising a two-day training on multi-satellite and model air quality data products on air quality (AQ) and their applications to understand the air pollution issues and challenges in the Hindu Kush Himalaya (HKH) region. The training includes a combination of theoretical and practical knowledge, incorporating sessions that cover discussion on advanced technologies and data analytics for AQ data products. Additionally, this training aims to provide a platform for networking and knowledge sharing/learning from different research groups across the HKH region.


This training aims to create a platform for participants to acquire insights into various data accessibilities and develop an understanding of utilising model and satellite observations for monitoring, predicting, and assessing air quality. This will further facilitate informed decision-making.

Expected outcomes

After the training, participants will gain a more precise grasp of satellite, model, and assimilated data products and their practical applications. They will utilise this knowledge to support decision-making in the region. Furthermore, they will have access to a vast AQ data platform for capacity building, training, and other purposes. Participants will actively engage in using the satellite-derived AQ data to understand air quality challenges in their region and will present their work to the group.

Expected participants

25 participants from Bangladesh, Bhutan, India, Nepal, and Pakistan representing universities, government organisations, and development agencies are expected to join the training.

Resource persons/facilitators


Arun B Shrestha, Strategic Group Lead: Reducing Climate and Environmental Risks

Bertrand Bessagnet, Action Area Coordinator, Stimulating Action for Clean Air

Bhupesh Adhikary, Senior Air Quality Specialist, Stimulating Action for Clean Air

Birendra Bajracharya, Chief of Party, SERVIR-HKH

Rajesh Bahadur Thapa, Senior Remote Sensing and Geoinformation Specialist, SERVIR-HKH

Arshini Saikia, Air Quality Modelling Analyst, Stimulating Action for Clean Air

Suman Sanjel, Air Quality Application Development Associate, Stimulating Action for Clean Air

Poonam Tripathi, Geospatial Training Analyst

NASA-Applied Science Team (AST)

Dan Irwin, Head-Global Program Manager, SERVIR

Aaron Naeger, Principal Investigator, Research Scientist at NASA Marshall Space Flight Center

Jonathan Case, Co-Investigator, Research Meteorologist at ENSCO, Inc.

Kevin Fuell, Co-Investigator, University of Alabama Huntsville (UAH) Research Scientist / Transition/Training Specialist at NASA Short-term Prediction Research and Transition Center (SPoRT)

SERVIR – Science Coordination Office

Alqamah Sayeed, Air Quality Scientist, Universities Space Research Association (USRA)

Meryl Kruskopf, SERVIR Science Coordination Office


Air pollution is a significant threat to the environment and public health in the HKH region, exacerbated by robust emission sources and widespread pollutant transport. The Kathmandu Valley in Nepal faces particularly high levels of air pollution due to its geographical features, which trap pollutants, leading to adverse health effects. In addition, other major cities such as Delhi, Dhaka, and Lahore in the HKH region also grapple with air pollution challenges driven by vehicular emissions, industrial activities, and agricultural burning. Traditional ground-based sensors are commonly used for air quality monitoring but often lack coverage, hindering the characterisation of pollutant gradients. Space-borne remote sensing from low Earth orbit (LEO) and geosynchronous equatorial orbit (GEO) satellites can provide high spatiotemporal information on trace gases and aerosols, improving AQ monitoring and forecasting capabilities and enabling better-informed decision-making. Integrating high-resolution satellite observations into model simulations enhances air quality forecasts, facilitating timely alerts for the public.