I’d like to introduce the LUNGS project briefly now, then come back to details later:
LUNGS is an activist research project that critiques outdoor air pollution policies – first by interrogating how pollution data/information is collected and analyzed, then by incorporating geo-spatial histories of discrimination, and finally, by creating low-cost, open access sensor kits to enable more informed decision-making by communities in relationship to local, real-time pollution and health.
The idea is that the kits will be placed, and measurements will be collected hourly and sent in ‘real-time’ via text message to a centralized database. The SMS is important because it is the one thing that all phones have, and outside of the US, it is actually fairly cheap to use. There will also be a simple ‘traffic light’ set-up on the kit- similar to the air pollution warnings we see in our weather alerts: showing green for OK, yellow for possibly harmful for people with lung diseases, and red as dangerous for all.
Each kit will also have a texting code: you send an SMS message with the code to a number, and it responds with real-time data for that location.
Additionally, you will be able to see the trends over half-day, full-day, week, and month, giving a better representation of your hyper-local area over time- and will hopefully be able to forecast the near-future as well.
The central database will be available to anyone – with certain privacy measures for those who are placing them outside of their homes- and will hopefully be used by concerned citizens, activists, journalists, and local governments to create policy change as well as to prove that large companies are polluting when they say they are not. So while they can provide individual real-time air-pollution data, the power is in deploying them as a community in larger quantities along a disputed area or major road.
We are also planning on building out lesson plans – from basic circuits and soldering to how to analyze and use the data for various purposes. This will be freely available as well for anyone to use, and we also hope to work with local communities to build and deploy the kits to gather information about our own county, which sits in one of the most polluted regions of the country in terms of air pollution.
The purpose of this project is to better understand how injustice is organized – and to address that injustice through critical production practices and to create alternative “life” practices that will work not only in the spaces where the sensors are placed, but also in finding and understanding larger patterns that hopefully will inform government and business practices, as well as allow everyday citizens to make informed decisions.
This project enables us to understand how knowledge is produced and shaped: learning about how data is collected shows us what is considered meaningful, what and who counts, and who and what doesn’t count. By trying to fill that void of really important, hyper-local data, we are producing ‘counter-knowledges’ – or new forms of knowledge that can help prove that there is pollution and hopefully enable individuals and communities to pro-actively test locations and analyze data before taking corporations to court.
But how does this work?
Outdoor Air Pollution is a major health risk. According to the World Health Organization, “in the year 2008, urban outdoor air pollution was responsible for 1.3 million annual deaths, representing 2.4% of the total deaths worldwide” . As a major public health risk, the WHO and the US’s EPA take air pollution seriously and have pinpointed six major chemicals that are dangerous to human health with the intention of trying to reduce exposure by reducing the levels in the air.
To do so, the World Health Organization collects daily averages on these individual pollutants worldwide for their Urban Outdoor Pollution Database. Their primary aim is to “capture representative values for human exposure” so that they can not only track pollution levels, but also to create policies to reduce air pollution levels to “help countries reduce the global burden of disease from respiratory infections, heart disease, and lung cancer” .
This is an admirable goal, and though they work to gather detailed data to create these policies, the ways in which they collect the information guides public policy from representative data, not detailed real-time pollution levels. Their sources are ONLY official reports and web sites, regional networks and in some cases, data from UN agencies, development agencies and articles from peer reviewed journals .
They leave out what they call ‘known hot spots ,’ and industrial areas, by which they recognize that “omitting them may have lead to an underestimation of the mean air pollution levels of a city” . What this means is that the city data is a daily average taken from particular data sets that disallow known pollution areas, and is not collected in real-time for people living, traveling and working in and around these areas.
Additionally, “there is significant inequality in the exposure to air pollution and the related health risk: air pollution combines with other aspects of the social and physical environment, creating disproportional disease burden in populations with limited incomes and with minimal local resources to take action” . Given the serious health issues for known pollutants, we feel that by looking directly at ‘hotspots’ or places NEAR where known pollution is coming from, we will be able to identify and map particular pollution levels in real time in proximity to known locations.
Although recognizing that it is a huge task to collect and analyze pollution data worldwide, the ways in which information is collected guides public policy, and therefore needs to be considered carefully within the matrix of pollution-reduction policies and public health implications worldwide. Because public health focuses on the overall health of a population, it looks at averages and representative data to understand the direction it is taking, not how it affects individuals
‘making’ practices as collaboration or collective
that not only addresses critical questions,
but is itself a critical intervention
“People living in low- and middle-income countries disproportionately experience the burden of outdoor air pollution with 88% of the 3.7 million premature deaths occurring in low- and middle-income countries.
Additionally, in the United States, a 1983 US General Accounting Office study determined that hazardous waste facilities were more likely to be sited near communities with a majority population of racial minorities and/or low-income populations.
Therefore, the way the data is collected causes an uneven understanding of who is affected and how, leaving racial minorities and low-income populations bearing the brunt of pollution-based diseases worldwide.
Generally only once a community complains and files suit, is any attention paid, if at all. Meanwhile, the politics of pollution plays out through subsidies and the promise of jobs making the siting of factories and plants in particular neighborhoods LOOK like it is a benefit, when in actuality it is a harm.
Pollution is part of a larger system of raced, gendered, and classed conditions that maintain the status quo, that prevent a ‘level playing ground,’ and that subjugate & discriminate against minority populations. Environmental racism is founded in the geo-spatial histories of slavery and the Jim Crow Laws.
In order to combat the matrix of policy, corporate tax relief and discrimination, there is a need to look directly at ‘hotspots’ or places NEAR where known pollution is coming from, in order to identify and map particular pollution levels in real-time in proximity to known pollution sites. This will enable people living and working in areas that are currently excluded from monitoring to know what they are facing in real-time, as well as look at averages over time, and potentially compare to other nearby areas also using the same sensors.
This is where the LUNGS project enters the conversation.
How might we ‘get’ at the intersections of injustice, illness, & pollution to make change?
How do standards and categorizations come to be (and continue to become)? What/who does the current practice of representative data leave out, and what harm/benefits are there to creating knowledges in this way? How else might we create this knowledge? How else might we come to understand the nuances of meaning, of decision making, of standardization?
Given that public health initiatives focus on representative air pollution levels to understand overall levels for a city, region, and country, what happens if we enable communities and individuals to place their own low-cost pollution sensor kits to collect (and later analyze) hyper-local data? Can we use these pollution kits to produce hyper-local knowledge that will enable communities to create local change as well as to prevent more toxic sites from being built in their neighborhoods?
What does it mean to ‘do’ this work as a queer & feminist project?
Can this project be a collective, collaborative one, using critical race theories & activisms alongside feminist and queer pedagogies to co-produce knowledge while at the same time not trivializing communities’ very real, lived concerns?
Taking these questions into account, how might we ‘do’ public health better to take into account race, class, gender, ability, and geography?
The ‘maker’ movement itself is problematic in its technology-driven focus for solutions to “pressing” social issues, and I’d like to argue that there is a bit of cultural hegemony in the overall community – that’s not saying that individual projects are hegemonic – but that the focus on technological solutions without queer, feminist, and critical race approaches, means that the maker movement is replicating current hierarchies without questioning their approach.
Stakes & Risks
The first year of the program was an experimental and organizational year- first, to organize the project’s overall design- what we want to do, and how to go about doing it; then to attempt to garner funding support, and finally, to build a low-cost, remote deployable prototype in order to prove concept. Once the prototypes are completed, they will then be taken as a baseline object to communities where interested parties (city council, the average activist citizen, journalists, policy makers) will join us to design and develop the actual ‘product’.
managing the challenges of creating tech, working with local communities
negotiating difference without (white) savior / missionary complex
But also, running this project as non-hierarchical allows students to become teachers as well as students (knowers & learners), able to teach and learn from each other as we research, design & deploy the project. We share skills – from soldering & paper-prototyping to writing blog posts and solving differential equations- allowing each person on the team to be the expert as well as the one learning – which makes it easier to make decisions because everyone has something different to contribute.
While this type of co-learning and collaboration is really important both in the classroom and in real-world design projects, it also comes with concerns. First, it can be challenging to get students to share skills and to accept that I don’t know everything, or have all the answers. And second, working with a limited self-selecting group of undergraduates means that the project begins with a set of ideas about the world that, given our mass media claims, is not at the outset inclusive in their understanding of environmental justice in terms of racism and poverty and not just preventing trees from being cut down.
These discussions are part of the design process – deciding to create the kit as hyper-local, easily installable, weather-resistant, with real-time results means that folks already living in known hot-spots can monitor their local air to protect themselves health-wise, but also to enable them to take action when needed.
Given the current make-up of our team, cost-effectiveness, and ability to transfer knowledge and skills sets, we are currently building one prototype with Arduino and another prototype with Raspberry Pi, as each platform has its own proclivities / tendencies.
More Stakes & Risks
Part of what is so complicated about the participatory design process is that when you come up with an idea to design something – it has to begin somewhere- and including non-designers is important and necessary – so the question is – at what point do they join the process? The project has to be possible to a certain extent prior to reaching out to possible partners. But it can’t be so far along that partners don’t feel equal in the design process. Their voices need to be heard and acted upon. By building two basic prototypes we hope to begin a conversation that results in a different, better kit that is truly a collective design & development effort, where everyone feels they are equal partners.
But how does that work when local communities already have a tense relationship with the university? How do we work within the power dynamics of young predominantly upper-middle class white college students designing/working with predominantly middle-aged, minority, and working class local communities? This project is not about ‘helping’ or being white saviors- so how do we build trust? These are questions that we will need to discuss and resolve in some way with the communities we are working with.
Funding, Academic Labor & Coursework
Asking students to put time in (b/c it is all outside of typical class structure) means that they set the calendar more than I do. So things take longer.
These are my talk notes from the American Studies Association Conference in Los Angeles, California, November 6, 2014. It was part of the ASA Women’s Committee and Digital Humanities Caucus: Feminist Making II: Producing Cultural Critique
 In order to present air quality that is largely representative for human exposure, urban measurement characterized as urban background, urban traffic, residential areas, commercial and mixed areas were used. Stations characterized as particular “hot spots” or exclusively industrial areas were not included, unless they were contained in reported city means and could not be dissociated. This selection is in line with the aim of capturing representative values for human exposure. The location of hot spots, often measured for the purpose of capturing the cities’ maximum values, and industrial areas, were deemed less likely to be representative for the mean exposure of a significant part of a city’s population. “Hot spots” were either designated as such by the original reports,or were qualified as such due to their exceptional nature (e.g. exceptionally busy roads etc.). Omitting them may have lead to an underestimation of the mean air pollution levels of a city. (http://www.who.int/phe/health_topics/outdoorair/databases/Methods_OAP_database_2011.pdf)