Following the article, the author J. Kenens has published another paper "Changing perspectives: tracing the evolution of citizen radiation measuring organizations after Fukushima (2020)" DOI: 10.1051/radiopro/2020041 (link) that draws on the research on citizen science in Japan with a new focus on the comparison of their practices directly after the nuclear accident and today.
It is interesting to see how citizen science in Japan is enacted and how the concept of citizen science is dependent to the social and cultural context. Also looking at it not only from a top-down perspective, where universities or organizations are involved, but also the bottom-up perspective that includes only those practices that are done by citizens alone opens up a new space. As I am currently engaging with research on air pollution in different sites, I could build from this text in considering the link between "citizen-driven approaches and institutional imparatives in the governance" (p. 7) of issues with air pollution.
The text is an article about citizen science in the aftermath of the Fukushima disaster in 2011. The first noteworthy detail about this text that struck me is the inclusion of Japanese words and even their original spelling. This creates a kind of closeness to the field that the authors did their research in.
The authors engaged in multi-sited ethnographic fieldwork that took place in and around Fukushima but also in other geografical sites like Tochigi, Miyagi, Aichi, Tokyo and Kyoto. There, they conduct semi-structured interviews with various organisations that are all somehow involved with citizen science or radiation measurement. To learn about the citizens that measure radioactivity and create their own data on radiation because of a lack of provided data by the government, a literature review of policy documents and workshops with those citizen scientists is performed.
So the main 'slowdown' of the economy as well as the 'lockdown' of people appears to come to an end. It's been three exceptional months, as for instance emphasized by altered mobility patterns. (See https://www.covid-19-mobility.org/current-mobility/) However, what do we make out of this?
I would like to propose the following argument: The global health crisis of SARS-CoV-2 triggered a new public engagement with the polluted world produced and inhabited by humans. Media reports and preliminary scientific studies showed how pollution parameters decreased significantly and people visited public parks to a previously unknown extent. A debate on healthy clean air popped up, which was further strengthened by measures to contain the pandemic. Publicly discussed scientific studies suggest a correlation between COVID vulnerability and air pollution; and through hygiene measures, the mask has become popular as an object of protection, which in many societies was previously known primarily as protection against air pollution in public spaces. A few authors even claimed that air pollution should be indentified as a pandemic as well, a non-communicable pandemic with a significant toll.
We know perfectly well that air pollution is a slow disaster that is hard to account for. Threshold limits are not enough. The unequal consequences are not well appreciated, let alone translated into sufficient action. The pandemic experiences might help cherish clean air; it could help in producing clean and healthy air as a common good.
This is just a start, but I'm thinking about doing more research on that topic. One possible approach would be to discuss the "clean air experience" cross-culturally (like we do during the calls), while analysing and drawing on public (social media/media) discussions to enact clean air as a value. In turn, this could help bring pollution prevention and accountability to the forefront.
Science-study wise, it's interesting to see that based on sensing and modelling scientists find it challenging to carve out a "Corona effect". The weather is just very unique this year. However, a new assessment by the German Aerospace Center claims to have "proven" it. In the Italian Lombardai (the North), for example, the effect boils down to 45 percent. This is the main finding of this link (which has some nice gifs, but otherwise is written in German).
Is there any ethnographic science study of how global pollution data is made and processed? Jennifer Gabrys get's pretty close with her work, plus Paul Edward's research on climate data. But there might be more to it. Doing such a study now might produce interesting insights.
I also came across a compelling clip by the Delhi based Centre for Science and Environment, where they explain current Delhi data. They show an explicit interesting in a state of zero/low-pollution, which otherwise can never be observed, as well as its consequences. https://www.cseindia.org/covid-19-lockdown-60-drop-in-air-pollution-in-…
Just to begin the discussion for this particular question: here's the Harvard study that is being cited in various newspapers on the apparantly direct link between air pollution and Covid-19 vulnerability. van Donkelaar, A., R. V. Martin, C. Li, R. T. Burnett, Regional Estimates of Chemical Composition of Fine Particulate Matter using a Combined Geoscience-Statistical Method with Information from Satellites, Models, and Monitors, Environ. Sci. Technol., doi: 10.1021/acs.est.8b06392, 2019.
See e.g. how it is picked up by the NYT. I also find it interesting to link this data with more critical race-ish reports, such as this by Vice.
So, how to draw on this to develop what kinds of ethnographic studies?
Reading lists appear to play an important role in the distribution of knowledge. They might help follow discussions, but they also make things complicated, especially when one is facing non-curated long lists. For example, I am trying to follow the daily updates provided by the The Syllabus -- especially its Anthropocene and Economy parts. I intend to read the articles (and at times listen to the podcasts) that discuss the intersection of Corona and Climate. Or at least safe the important ones to Zotero. Yet, there is a lot to digest. Many repetitions.
Are these lists a data infrastructure 'for us'? What do they mean for 'others'? Might it be helpful to share the workload of reading the updates, and invest a bit of time in some sort of curation process?