Visualising historical changes in air pollution with the Air Quality Stripes

Pringle, K. J. ORCID: https://orcid.org/0000-0003-2190-5258, Rigby, R. ORCID: https://orcid.org/0000-0001-9554-6054, Turnock, S. T. ORCID: https://orcid.org/0000-0002-0036-4627, Reddington, C. L. ORCID: https://orcid.org/0000-0002-5990-4966, Shayakhmetova, M., Illingworth, M., Barclay, D., Chue Hong, N. ORCID: https://orcid.org/0000-0002-8876-7606, Hawkins, E. ORCID: https://orcid.org/0000-0001-9477-3677, Hamilton, D. S. ORCID: https://orcid.org/0000-0002-8171-5723, Brain, E. and McQuaid, J. B. ORCID: https://orcid.org/0000-0001-8702-0415 (2025) Visualising historical changes in air pollution with the Air Quality Stripes. Geoscience Communication, 8 (4). pp. 229-236. ISSN 2569-7110 doi: 10.5194/gc-8-229-2025

Abstract/Summary

This paper introduces the Air Quality Stripes, a data visualisation project which presents historical changes in outdoor particulate matter air pollution (PM2.5) concentrations across major cities worldwide. Inspired by the popular Warming Stripes image showing trends in surface temperature, the Air Quality Stripes aims to make complex information about air quality trends understandable and engaging for a broad audience. A historical PM2.5 dataset (1850–2022) was created by integrating satellite observations with model simulations (with a bias correction step to ensure a smooth time series and address known model biases). Images were produced in collaboration with a visual design specialist and revised after informal feedback from potential audiences. The images show that trends in PM2.5 are varied across the globe; recently there have been significant improvements in air quality in much of Europe and North America but worsening air quality in parts of Asia, Africa, and South America. By showcasing historical data in easy to interpret images, the project aims to inspire dialogue among individuals, communities, and policymakers about proactive strategies to combat air pollution.

Item Type	Article
URI	https://centaur.reading.ac.uk/id/eprint/124789
Identification Number/DOI	10.5194/gc-8-229-2025
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > NCAS Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher	Copernicus
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