Building capacity to improve air quality in South Asia

Organisers: Atmospheric Watch Initiative – ICIMOD and Duke University, USA

About the event

This workshop builds upon our workshop on low-cost sensors for air quality monitoring, which we hosted in May 2022. This two-day workshop will bring together scientists from seven South Asian countries and subject matter experts from USA to share progress on visualising and analysing data from the large network of TSI BlueSky sensors that have been deployed throughout the subcontinent. We will also discuss progress made on ingesting such data into the ICIMOD’s regional air quality dashboard.

Background

ICIMOD’s Regional Programme on Atmosphere aims to improve understanding of air pollutant emissions, atmospheric processes and change, and impacts and promote mitigation and policy solutions while building awareness, capacity, and collaboration in the HKH and upwind regions. The programme aims to promote the adoption of effective measures and policies to reduce air pollution and its impacts within the HKH through improved knowledge and enhanced capacity of our regional partners.

Duke University is a private research university in Durham, North Carolina, USA. The university has been working on air quality issues mostly related to observation, machine learning, and data analytics in South Asian countries (Bhutan, Bangladesh, India, Maldives, Nepal, Pakistan, and Sri Lanka). Their project ‘Building capacity to improve air quality in South Asia: Reducing PM2.5 through low-cost sensor network driven policy decisions’ (October 2020–September 2023) is funded by the U.S. State Department. The project implementing partners are university research groups in each of the South Asian countries: Dhaka University (Bangladesh), Sherubtse College (Bhutan), IIT Kanpur (India), Central Department of Environmental Science – Tribhuvan University (Nepal), and NUST Islamabad (Pakistan).

The main goal of their project is to develop and implement plans to reduce PM_2.5 to more healthy levels in highly polluted regions in each country through a combination of low-cost satellite image-enhanced PM_2.5 sensor networks, integrated with meteorological modelling and source apportionment.

Agenda