Monthly mean PM2.5 surface concentration across Europe. Calculated using the ensemble median from CAMS Europe air quality forecast (0.1°x0.1° resolution; available via the Copernicus Atmosphere Data Store).

The term particulate matter (PM) refers to particles made of dust, dirt, smoke, or liquids that are suspended in the air. In the AD4GD project, we primarily focus on particles with diameters of less than 10 microns (PM10) and 2.5 microns (PM2.5). These particles pose a significant risk to human health because they can deeply penetrate the lungs, and PM2.5 has the potential to enter the cardiovascular system (Source: US EPA).

Regional distribution of estimated annual excess mortality rates from cardiovascular diseases (Lelieveld et al., 2021).

The challenge of using low-cost sensors for air quality monitoring lies in their accuracy and reliability, which is not comparable to more expensive devices. These sensors are generally less durable, which can result in false signals or drifts over time, requiring their frequent replacement. Moreover, as these devices are maintained by non-professionals, there is a concern that measurement standards may not be consistently met, thereby affecting the quality and reliability of the measurement.

The opportunities of using low-cost sensors for air quality monitoring are significant. They enable the establishment of dense measurement networks that provide real-time, localized data on air pollution levels. These data can help in identifying pollution hotspots and trends, serving as a foundation for early warning systems that alert communities to unhealthy air conditions. Additionally, the extensive data collected over time supports long-term medical studies, offering insights into the impacts of air quality on public health. Thus, these sensors can inform mitigation and policy strategies, facilitate public health decisions, and contribute to more informed environmental and health research.

A goal of this pilot is to evaluate their usefulness and how they can be complemented by existing standard systems as reference sensors or model data.

Engaging with citizen communities in urban air quality monitoring involves enhancing the distribution of low-cost IoT sensors to citizens and thereby enabling them to contribute to air quality data collection. This initiative fosters community involvement by educating and empowering individuals to monitor and understand local air pollution levels. For instance through accessible data platforms, citizens become informed participants and advocates for air quality improvement, enhancing both local engagement and environmental awareness.

Advocating for a proper air quality is crucial to achieve the Green Deal goals of zero pollution in air, water and soil which targets “ improving air quality to reduce the number of premature deaths caused by air pollution by 55%” and “aligning the air quality standards more closely to the latest recommendations of the World Health Organisation”. (Source: European Commission).

Addressing this issue is also key for achieving the Sustainable Development Goals (SDGs). On one hand, the SDG target 3.9 aims to “substantially reduce the number of deaths and illnesses from hazardous chemicals and air, water and soil pollution and contamination” by 2030. Equally, the SDG target 11.6 ambitions to “reduce the adverse per capita environmental impact of cities, including by paying special attention to air quality and municipal and other waste management”

Tackling air pollution also benefits SDG target 13 on climate action in a scenario of complex interactions and local idiosyncrasies. Compliance with climate change mitigation policies could reduce PM2.5 emissions by 17% and prevent more than 74,000 premature deaths annually in Europe. (Source: WHO).