International beyond Europe

Societal challenge

Air pollution is one of the leading causes of illness and premature death in Sub-Saharan Africa. Rapid urbanisation and industrialisation are worsening ambient air quality, posing a growing threat to public health. The economic toll of increased illness and lost productivity can account for around 5% of GDP.

Vulnerable communities in low- and middle-income countries (LMICs) bear the brunt of poor air quality, with reduced access to clean energy and higher exposure to pollution sources such as industry and open fires. Children under five are disproportionately affected: household air pollution is a leading cause of death in this age group.

Monitoring is essential for effective health interventions, environmental justice, policy development, and sustainable development. Yet many countries in the region still lack robust air quality monitoring systems, making investment in this area both pressing and overdue.

Rising temperatures due to climate change are also affecting LMICs severely, despite their historically low contribution to global emissions. Those with the least adaptive capacity are hit hardest.

Our vision

SAMSA (Sustainable Atmospheric Monitoring Service for Africa) is a proposed service to continuously track and predict air quality and heat stress across Africa. It will deliver free, high-quality data for a wide range of applications, providing regional and local insights into pollutants such as short-lived climate pollutants (SLCPs), ozone, particulate matter, and reactive gases (nitrogen and sulphur oxides). Data is delivered near real time, with forecasts up to three days ahead.

The operational service is inspired by the EU Copernicus Atmospheric Monitoring Service (CAMS). Within CAMS, an ensemble of advanced models is used to simulate atmospheric chemistry, of which TNO’s LOTOS-EUROS is one of the leading models. At the start, SAMSA will be powered by LOTOS-EUROS, but later on, the SAMSA initiative should be powered by a similar ensemble, with addition of local models and expertise.

Monitoring consists of both modelling and measurements. Many initiatives already exist in Africa to measure air quality with low-cost and reference sensors. SAMSA builds on these sensor networks through data assimilation, while also providing air quality information for locations without a sensor through accurate modelling. SAMSA can also disentangle contributions from different sources and locations, offering insight into the origin of pollution (see figure for an example).

A key aspect of SAMSA is its local ownership. Capacity building is central to the implementation phase of SAMSA. Students are trained in operating the modelling tools and interpreting the system output. Implementation starts in Kenya, creating a strong foundation for South-South learning with neighbouring countries.