Properly equipped racing pigeons can gather continuous real-time air pollution data while moving through the air at key heights not accessible to the official instruments, as well as from the ground where they are released for their homing flights' (Haraway, 2016).
Grasping the airExposure to air pollution and its health risks varies greatly according to the place where one lives (Kelly & Fussell, 2015; WHO, 2013). Not only differences between countries, cities or towns matter, or between cities and countryside, but also, and maybe even more importantly, within each of these settings. A vast amount of literature has aimed at linking these spatial differences to socio-economic indicators demonstrating environmental injustice in terms of class, ethnicity, age, race and other social stratifications (Fecht et al., 2015;Mitchell and Dorling, 2003;Mitchell et al., 2015). Whereas most of this research has started from representations of bad air as spatially fixed, the dynamic, elusive and unstable character of air pollution exposure has increasingly been foregrounded in recent research (Nyarku et al., 2018), as too variations at the microscale (see e.g. Fecht et al., 2016; Tenailleau et al., 2015;Tonne et al., 2019). Technologies for measuring air have simultaneously proliferated, shifting from government-led scientific monitoring and global-scale computer models towards participatory (citizen science) modes of data collection and analysis using simple diffusion tubes and mobile phone apps (Garnett, 2016; see also Kelly & Fussell, 2015;Tan and Smith 2021).These shifts have been paralleled by a shift towards a much higher activist and artistic engagement with the topic, exemplified by both a much higher citizens' involvement with science, and increasing calls for a 'more than science' approach (Hulme 2021), opening up new investigations of our embodied and affective engagements with air (