This paper is based on ethnographic research of data practices in a public health project called Weather Health and Air Pollution. I examine two different kinds of practices that make air pollution data, focusing on how they relate to particular modes of sensing and articulating air pollution. I begin by describing the interstitial spaces involved in making measurements of air pollution at monitoring sites and in the running of a computer simulation. Specifically, I attend to a shared dimension of these (...) practices, the checking of a numerical reading for error. Checking a measurement for error is routine practice and a fundamental component of making data, yet these are also moments of interpretation, where the form and meaning of numbers are ambiguous. Through two case studies of modelling and monitoring data practices, I show that making a ‘good’ measurement requires developing a feeling for the instrument–air pollution interaction in terms of the intended functionality of the measurements made. These affective dimensions of practice are useful analytically, making explicit the interaction of standardised ways of knowing and embodied skill in stabilising data. I suggest that environmental data practices can be studied through researchers’ materialisation of error, which complicate normative accounts of Big Data and highlight the non-linear and entangled relations that are at work in the making of stable, accurate data. (shrink)

In this article, I materially situate air pollution exposure as a topic of social and political inquiry by paying attention to the increasing specificity of spaces and sites of exposure in air pollution and health research. Evidence of the unevenness of exposure and differential health effects of air pollution have led to a proliferation of studies on the risks different environments pose to bodies. There are increasingly different airs in air pollution science. In this research, bodies are often relegated to (...) passive objects, exposed according to the environments they move between. Yet exposure implies a blurring of bodies and environments which also challenges the idea of a discrete body that is distinguishable from its material context. By studying the process of modelling indoor air pollution, I highlight how air pollution, buildings and bodies are co-implicated with one another in ways that demand new ways of materialising human exposure in science. (shrink)

This article traces an emergent tension in an interdisciplinary public health project called Weather Health and Air Pollution. The tension centered on two different kinds of data of air pollution: monitored and modeled data. Starting out with monitoring and modeling practices, the different ways in which they enacted air pollution are detailed. This multiplicity was problematic for the WHAP scientists, who were intent on working across disciplines, an initiative driven primarily by the epidemiologists who imbued the project with meaning and (...) value as the protagonists of “health.” To work collaboratively implies a stable, singular, and shared research object, however: one kind of data, one version of air pollution. In detailing two attempts by researchers to address the inadequacies of modeled and monitored data, this article explores the ways in which difference and multiplicity were negotiated and transformed. In doing so, this article suggests that it is the mobility and instability of data that are particularly fruitful for exploring the facilitation and enactment of new realities, while also making explicit the emergent problematics and partialities which inevitably result. (shrink)