This rapid literature review surveys academic and grey literature on air quality monitoring in low-income (LICs) and lower-middle-income countries (LMICs). It draws heavily on three key sources of information. The World Bank (Awe et al., 2017) led report ‘Filling the Gaps: Improving Measurement of Ambient Air Quality in Low and Middle-Income Countries’, the Health Effects Institute’s (2019) report on the ‘State of Global Air’, and the interdisciplinary work of the University of Birmingham led ‘A Systems Approach to Air Pollution’ (ASAP). It also profiles the work of Air Qo in Uganda as an exemplar of the rapidly evolving, locally-led, air quality monitoring work underway in the global south.
Key Findings:
- Air pollution is a global environmental health threat, contributing to an estimated 3-7 million deaths per year (Lelieveld et al., 2015; WHO, 2014). Whilst various types of air pollution exist, particulate matter air pollution contributes most to the global burden of disease.
- Despite links between exposure to indoor and outdoor air pollution and negative health impacts, there is a paucity of long-term, appropriately calibrated data measuring air quality in LICs and LMICs. In particular, the apportionment of different pollution sources, e.g. vehicular emissions, industrial sources, and dust, to the overall pollution burden is often lacking. There is also a lack of evidence as to how these contributions vary between urban, peri-urban and rural environments and, indeed, within these as well as overtime.
- A number of methods of air quality monitoring are utilised to assess levels of air pollution. This includes ground-level quality monitoring, which is well established in the global north, however, coverage in the global south is more variable. Other approaches are also available. A description of these is included below:
- Ground-level Monitoring: Air pollution is traditionally monitored by reference or regulatory grade monitoring stations that take accurate measurements, are used to build a long term understanding of air quality, and show compliance with national air quality standards.
- Satellite Remote Sensing: Satellite-based remote sensing of air quality offers the prospect of daily observational information for most locations in the world. Satellite sensors measure interference in the light energy reflected or emitted from the Earth, which is used to calculate concentrations of air pollutants, such as particulate matter, nitrogen dioxide, carbon monoxide, and ozone.
- Air pollution modelling: It is possible to model air pollution over larger geographic domains via the combination of ground-level monitoring data and the application of modelling systems, such as WRF-CHIMERE, which simulates weather and the main pollutant dispersion patterns.
- Visibility as a proxy for air pollution: Long term visibility measurements can be used for a proxy for air pollution. Visibility data is routinely collected at airports globally (in some cases from the 1950s to present day).
- Air pollution affects all regions of the world, in a context of rapid urbanisation, the WHO estimated that between 2008 and 2013, urban air pollution levels increased by 8% and are expected to rise further given rapid urban development.
- In 2017, 3.6 billion people (47% of the global population) were exposed to household air pollution from the use of solid fuels for cooking. These exposures are most common in SSA, South Asia, and East Asia (HEI, 2019: 8).
- Despite concerted efforts to manage air quality globally, air pollution remains one of the world’s largest environmental health risks (Longhurst et al., 2016). A holistic approach is required for effective intervention that considers different sources of air pollution and addresses the related socio-economic and health problems.
