This project will use low-cost miniaturised sensors to augment existing (and relatively sparse) air quality monitoring networks. The results will be analysed using dispersion modelling tools widely used by regulatory bodies. The lessons learnt will be valuable in applying these technologies and methodologies across SE Asia, which has shown to be routinely affected by episodes of very poor air quality, as well as in the UK and developing economies.

At a glance

South East Asia is one of the most densely populated regions in the world with widespread rapid industrialisation and population growth. In air quality (AQ) terms, pollutant emissions and exposed populations are both increasing. In addition, regional land use change, deforestation and biomass burning are all occurring within an atmospherically turbulent and energetic region.

AQ monitoring is needed on from street to regional level if distributions and levels are to be understood and modelled effectively, and policy most efficiently designed and implemented. The emergence of new low-cost miniaturised sensor technologies in the environmental sciences has led to a huge increase in both available data and a potential for collecting new data. AQ observational studies can therefore be undertaken at higher resolutions and be coupled with numerical models resolving at finer scales.

Existing AQ monitoring at national levels is undertaken using networks of static pollution monitoring sites which due to their cost, size and logistical requirements tend to be relatively sparse.

A developing and important opportunity in the UK and globally is how to merge transformative low-cost sensing technologies with existing high resolution networks. Studies are needed to establish the scales (in time and space) of measurements needed to fundamentally understand the distributions of pollutants in and around urban areas in the context of energy, food and the environment. As new sensor technologies are deployed, models need to adapt to use high resolution multi capability sensing to optimise the information content derived from adding high density network data.

Kuala Lumper (KL) is an established regional megacity with a regional emissions footprint and its successful economic and growth pattern is being replicated across SE Asia. Understanding AQ distribution in KL and defining best practice for AQ monitoring and modelling in KL will have broad implications across SE Asia and beyond.