This site is using cookies to collect anonymous visitor statistics and enhance the user experience.  OK | Find out more

Skip to content
Natural Environment Research Council
Grants on the Web - Return to homepage Logo

Details of Award

NERC Reference : NE/P020941/1

RCUK-SEA - High Density Air Quality Monitoring in the Klang Valley (Malaysia) - A New High Resolution Observational Capability.

Grant Award

Principal Investigator:
Dr MI Mead, Cranfield University, School of Water, Energy and Environment
Co-Investigator:
Professor A Abu Samah, University of Malaya, Institute of Ocean and Earth Sciences
Co-Investigator:
Professor NRP Harris, Cranfield University, School of Water, Energy and Environment
Co-Investigator:
Professor D Oram, University of East Anglia, Environmental Sciences
Co-Investigator:
Professor M Latif, National University of Malaysia (UKM), Sch Environmental Science & Nat Resource
Co-Investigator:
Dr M Ashfold, University of Nottingham Malaysia Campus, UNLISTED
Science Area:
None
Overall Classification:
Unknown
ENRIs:
None
Science Topics:
Earth & environmental
Land - Atmosphere Interactions
Tropospheric Processes
Climate & Climate Change
Pollution
Abstract:
South East (SE) Asia is one of the most densely populated regions in the world with widespread rapid industrialisation and population growth (with an urban shift). 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 a spectrum of scales ranging from street to regional 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. The Greater Klang Valley (GKV) area includes the city of Kuala Lumpur (KL) as well as the surrounding municipal areas. It has a population of approximately 7 million and contains significant industrial activity as well as a number of ground, sea and air transport hubs including one major international airport. An emerging and important opportunity in the UK and globally is how to merge emerging low-cost sensing technologies with existing high resolution networks. Studies are needed to establish the scales (time and space) of measurements needed to fundamentally understand the distributions of pollutants in and around urban areas in the context of the Energy-Food-Environment nexus. Fine scale distributions of pollutants are not well studied in the horizontal with even larger uncertainties in the vertical. 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. 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. 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. This project will use low-cost miniaturised sensors to augment and expand existing relatively sparse monitoring networks. They will be deployed in a case study in Malaysia, specifically in KL and the surrounding GKV area. The results will be analysed using dispersion modelling tools widely used by regulatory bodies.
Period of Award:
14 Feb 2017 - 13 Aug 2019
Value:
£180,050
Authorised funds only
NERC Reference:
NE/P020941/1
Grant Stage:
Completed
Scheme:
Newton Fund
Grant Status:
Closed
Programme:
Newton Fund

This grant award has a total value of £180,050  

top of page


FDAB - Financial Details (Award breakdown by headings)

DI - Other CostsException - Other CostsDI - StaffDI - T&S
£64,821£99,258£8,077£7,896

If you need further help, please read the user guide.