Visualising historical changes in air pollution with the Air Quality Stripes

Air pollution poses a major public health risk, contributing to approximately 4.7 million premature deaths each year, the majority of which occur in low and middle-income countries. Effective public communication of air quality data is essential to drive policy action and address health inequalities, yet translating complex environmental data into an accessible format is always challenging.

This contribution presents findings from the Air Quality Stripes project (https://airqualitystripes.info/, Pringle KJ. et al, Geoscience Communication, 2025), which aims to raise public awareness and understanding of outdoor air pollution by visualising historical changes in fine particulate matter (PM₂.₅) in major global cities from 1850 to 2022*  in a clear and engaging manner. Inspired by the widely recognised Warming Stripes (https://showyourstripes.info/) images, the Air Quality Stripes project combined data from satellite observations and model simulations to create a continuous historical PM₂.₅ dataset, which was then displayed as a series of vertical stripes. 

The resulting visualisations reveal divergent pollution trends: there have been substantial improvements in air quality in many cities in Europe and North America, contrasted by persistently high or worsening pollution in parts of Asia, Africa, and South America. 

The project received significant public and media attention, including coverage in major national newspapers and broadcast media, demonstrating a strong appetite for accessible representations of air pollution data. They have also been used by a major philanthropic funder which funds observational networks to highlight gaps in global air quality data, especially in developing nations. In addition, major advocacy groups such as the C40 cities program are also using the images in their visualisation toolkit as part of their campaign for transparent air quality data to improve public health and policy.

What lessons have been learned?

Beyond describing the Air Quality Stripes visualisations, this contribution reflects on broader lessons for environmental data communication, drawing on audience engagement, media uptake, and practitioner feedback including:

• Collaboration with visual experts. The colour palette was developed with a design expert, drawing on imagery of air pollution to create a tangible link between colour and pollution.
• Informal feedback and review. Iterative feedback from colleagues, friends, and family helped improve the images; for example, early versions showed concentrations only, and feedback led us to add indicative labels (e.g. “good”, “poor”) to provide health-related context.
• City-specific focus. We chose to present images from individual cities as regional averaging would blur historical trends, but this city focus was popular with viewers as it allowed the viewer to connect with the information on a more tangible and often personal level.
• Selected annotations. Narrative annotations on a subset of images made the data more relatable, providing context and highlighting significant points. They also helped viewers better understand the overall structure of the images.

Lessons from the Air Quality Stripes project apply broadly to science communication, highlighting the value of interdisciplinary collaboration, iterative engagement with non-experts, and careful use of colour, context, and narrative. These insights extend beyond the project to inform environmental data visualisation and public communication more widely.