 RAL is an environmental NGO in Brussels, our baseline citizen action in Brussels. And what I'm going to talk about is a bit how to engage as a citizen in air quality. I'm going to talk through different experiences that we had in what we call citizen science. Because we believe that citizen science is an element of policy making, of an engagement of citizens towards cleaner air policies for all of Brussels. Our first experience that we had at that time already taught was citizen science was the expert project in which we engaged with Brussels, where they had like this small Italo meters which measure black carbon and we were in contact with them to engage citizens in this project. So what I wanted was to have citizens walk around with these devices to measure exposure to black carbon. It's important to also make the difference between exposure and ambient air quality. So the black carbon device is something that measures your exposure and is very related to the source of pollution. So it's best to measure that at street level by citizens walking around with it. Our goal in this project was, okay, Brussels and Véron-Mont wants to have data, but they needed citizens, they needed participants to carry around these devices. So we, as Brawl, we thought it was a good opportunity for citizens to get in touch with science, to get in touch with how knowledge on air quality is produced and so on. But during the process we understood that this is not really citizen science, this is scientific crowdsourcing. A bit as the shadow that was showed by Carina, the volunteers or the citizens were asked to walk around with a device which was owned by the government, by the administration. The data that were produced by this device went to the administration. The graphs, the results that came out were produced completely by the administration. The questions that were asked were completely produced by the administration. All this has its validity. I'm not saying that this is not valid, but we thought we needed something more. So what did this device do? It measured black carbon, which is in Brussels very much related to the diesel cars in traffic. And so by walking around with this device, you could see and your personal exposure, you see it in the back, and you have here a typical graph of someone exposed to black carbon who is working. So you see in the morning when he gets to work, he has a high exposure because that's the moment of time he or she is outside in traffic. Then all day through work, at work, you are not exposed or not much exposed because certainly if you work in a building with good filtration, good air conditioning and so on, then you don't have a problem. And then at night, when you go home, you're exposed yourself once more. But this kind of mobile data also allowed to create maps of this exposure in Brussels. And so that is what Brussels environement took out of it. They collected all this data gathered by all these individuals walking around in the city and they produced this X-Pair map of Brussels, of the black carbon exposure of people in Brussels. Now how do they produce this map? They used the measurements which they combined with the source of the emission being traffic. So it's a kind of a modernization. But as I said, while this exercise is very valid and it produces very good knowledge on the problem of air quality in Brussels, it is not something that is really in control of citizens. It's not really in the hands of the citizens to define what you are going to do with this data. How are we going to treat this data? What kind of questions are we going to treat with this data? For example, Brussels environement very much focused on the map and they did not focus a lot on the experience on the graphs. For example, comparing the different experience of different users in the city, because this is a typical graph of someone who is working. But we saw other graphs, people that were poor, that lived in the city center who exposed themselves all of the time because they did not have the opportunity to work in an office that was clean and so on. So comparing this kind of data is something that is not being done for the moment, whereas a lot of the people with whom we worked had quite some different questions about that. And so one of our participants, he opened the eyes to us because he said we need something that's more participatory. We need something that is accessible to everyone, that shows direct data, that shows direct feedback to the users and so on. Because if we can, well, Brussels environement, they had eight devices of these because they are very expensive. We need something that we can have more and more devices, just like what Influencer is doing, just like what the hacker is doing, trying to have a lot of sensors because the number of data can also produce quality. So we said we need something that we go a bit more towards citizen science in which citizens can really take into hand the whole framework, the research question, the things we want to know, do we want to know something about air quality in general? Do we want to know something about our exposure? Do we want to know if we can have something in hand by changing our routes? Can we explore which routes towards our work, for example, are cleaner than others and so on? Why? Because we believe that citizen science is part of policy making in Brussels. If you do collective knowledge production, we can get to collective awareness and by raising collective awareness, we can push policymakers towards other policies. We think through research, research is a lot at the moment still at the level of the city. And as an individual, we have a lot of questions about that. But we can also gather these questions into a community and get the answers which are not only at the individual level, but answers which are also comparing our individual exposure, our individual experience with others. And by doing that, creating collective knowledge about air quality and about what is my exposure, what is the exposure of my neighbor. And as such, gathering new questions, new insights, and new pushing governments towards action and towards political measures. We organize then, because we want to do something about it, we organize an event which was a smart citizen air quality meter. Because we want to know, well, is there a possibility to do this trade-off? The expensive devices of the administration, the real scientific devices, they are called expensive in hands of the administration. And at the other side, the sensors, which were said by a lot of scientists, but also other people from the administration that were not valid at all. And so we want to see, can we do something about this trade-off between participatory value and the devices that are very accessible and the need for scientific rigor, which is asked by our governments. And we saw, well, at that point, we concluded the middle ground was not really there in terms of that was accepted by all that, and the citizens would accept that this really participatory and the governments would accept that it is really valid. But the technology was developing, and it was time to give this technology and to give the awareness also by the administration a push to say that, well, there's something developing, and we can do something about it. The device that we found and the organization that we found that was mostly covering this middle ground for us was the air beam made by air casting. Why did we go for this device? Because we are not technological. We are not civic lab. We don't have this capacity to build our sensors ourselves, but also because the organization who developed us in New York, air casting, Habitat Map, they were very much in the same line as they thought we need an emancipatory device where people can measure themselves. It was also completely funded by NGOs. It was about open data, open source software, direct feedback to the users, and so on. So that's why we choose this device. We are still talking exposure. And so the first thing that the individuals, the groups with whom we work, the first feature that you have with this device is measure your individual experience. A bit the same as with black carbon, where you have these kind of graphs, what is happening to me with air quality throughout the day. But you have the direct feedback from the device because it's connected to your mobile phone, and so you see immediately how your air quality is at that point. You can also put it on a map, and you see, for example, the effect of a park where you bike through. You can put it on the graph. And this was a very nice graph because this was actually the day before the pollution peak. So individual users, they saw the pollution peak coming. They said, oh, it's raising. It's raising with me what is happening. And so one of the strengths of this is that you know for yourself that this pollution peak might become. But also, if you want to do something about it, the call from the government about the pollution peak came the next day, whereas if we already see the day before and a lot of people have this device, we can already start doing something about it. We can say, OK, we see it's raising. Maybe we need to, I do not need to take the car today because I will then also contribute to this. Or if you have asthma, you can say, OK, maybe this day I have to be a bit more careful. I can stay in and so on. But for us, even more important is building collective knowledge, bringing all these experiences together, all these individual experiences together. And that creates, on the website of Aircasting, creates a crowd map in which you can see all the traces of people measuring. And so you build a map, but most of all, and what is most useful of these kind of tools is to talk about exposure, when are we exposed more. And for example, putting graphs together of what people thought were quicker or cleaner routes to the city. And so for example, learning there was that there was not much difference between what people thought was quick and what people thought was clean. So these kind of things, bringing all these experiences together creates collective knowledge about air quality and about our exposure to air quality, to bad air. And so what we think with this device is that you can really become a citizen scientist. And this is also an appeal to everyone here, because well, we have a lot of people gathering data, but you need to do something with the data. And so what we propose to our volunteers is to, when you register a session, you can put tags to the session. And so for example, people can put the tag tram, the tag metro, the tag on foot, the tag bike, and so on. And so you can start comparing, when are you more exposed? Are you more exposed when you use the metro? What is the difference between using a car or using a bike, and so on? So these kind of questions can be started treated by the data that we have gathered with a lot of volunteers for the moment all over Brussels. And so we see we are now at the point that we have a lot of data gathering. We start to do some first analysis, but we are not very experienced in that. So it's also an open call for everyone who has knowledge about how to produce analysis out of it, how to use these tags, but also other people that might have questions like say, oh, I'm interested in this and propose to our community to say, hey, can you not use this tag? For example, I want to have a tag jogging in the park, and that a lot of people who have a device can start tagging their sessions with this kind of jogging or park or so on, and that we can start analyzing this kind of questions. So in the process that we're doing, it's really, we want to have the question, the research question, the kind of things that we want to get out to the citizens, to the people that work with us, to the people that use this device, but also crowdsource this completely. We have a Facebook page for the moment, it's mostly between the groups, which is open to everyone to also ask questions, hey, the people who have this device, I have a research question which I'm playing with, and so on. So coming back to why do we do this? Because it's not just about technology, it's not just about knowing, but it's about changing policies. And so we believe that citizen science can co-produce knowledge and feed democratic debate and democratic action. People who measure they know, they start to know, but they also wanted to let know, what have I measured? Not only the analysis, the scientific data and so on, but also the storytelling, the individual experiences, like the guy that crossed the park and saw the PM drop. This is a story, this is scientific data. Well, it's only one sample, but it is a story and it shows something and science can build on a lot of individual data and individual points, and so bringing this all together advances the scientific knowledge, but also advances the knowledge within society. But most importantly, we also think that bringing these science and citizens together, we can influence air policy in Brussels, and we really want to come to co-construction of air policies in Brussels in which academia and citizens work together to have better air policies to guarantee or right to clean air in Brussels. We see for the moment that we and a lot of citizens, but also we have sometimes the feeling that there's an iron coalition between academia and policy making and that we as citizens, we are a bit out of it. And so by becoming scientists ourselves, by engaging with the academic debate, and by exchanging with them, starting to understand how academia works, but also by getting citizens as a self, get our research questions on the scientific agenda, we believe that we can, instead of having this iron engagement in the academia and policy maker that we can make it into really a triangle in which that works for society and to co-construction of air policy in Brussels. So this is my final slide, and this sums it up. There was an article in the standard about our project this week, and I think the title says it's all, who measures air pollution or fine dust, he has influence. And so this is why we do it. Any questions or research questions for us? I wondered, I heard that there is a link between the HEKARE project and the data that will be collected by Influencer and the data of the Airbnb. Could you explain us a bit more about that? Is there already a plan? How will the data be integrated? And what is the synergy between the different types of data? So, well, just a general question with respect to that. I don't think for the moment that there's really a plan to integrate, well, we as Brau, we dream of, and I think it's also a bit the ambition of the HEKARE project, but also the air casting project. They have possibilities to integrate on the platform different measurements from different sensors, from different data sources, and so on. And so what we as Brau dream of is to have a platform page in which we gather all kind of data that are available for Brussels. It does not need to be on the same layer, on the same geographical layer because there's a lot of difference between, for example, the exposure data and data from stationary sensors because it's a different kind of measurement. It's a different kind of analysis that you would do, but having this kind of bringing them all together in one platform and that you can say, okay, I want to know something about mobile data that you have a layer. You want to know something out of stationary data that you have a layer that will be for us really a step forward. Because I understood that they also gather mobile data with one device, so maybe there's a possibility to do some normalization based on more detailed observations. Absolutely, and this also was the question before. There's a big difference between mobile data and stationary data. And I think with the advantage of mobile data is that you talk about exposure and you can really talk about experiences. You can compare using different modes of transportation. You can compare different times of day where you pass, but it is about your personal experience and getting, it's not very useful to really go into a geographic debate about air quality. It might be that in some streets, for example, you can say, well, if I walk through the street, most people that walk through this street are more exposed than people walking through another street. There's a geography in it, but you need to know that you're talking about exposure and not about the air in this street is polluted because the experience can be very different if you bike through Rüttetron and you are stuck behind the bus. You have a different experience than the one that goes at another time of day and you can bike the street completely fluently. So this is another way of thinking about air quality data and about analyzing them. Thank you for... You spoke twice about an iron coalition between authorities and academia. Could you develop a little bit on that? What it does mean? Well, the thing is that the knowledge projection for the moment is a lot within the administration. It's a lot within academia and so there's the... Well, academia, they have their own independence still. They have their own funds and so on, so they can develop their own, but a lot of academia is also subsidized by the state and so the state poses the research question. Ideally, via democracy, via our elections, we influence what kind of questions that the state asks towards academia. But by citizen science, by this kind of stuff, we can do this more directly because we put new questions, for example, about exposure on the political agenda. A lot of air quality and all the legal framework is based on ambient air quality. So all the norms about the European norm, World Heritage Organization norms, they're all based on ambient air quality because this is the debate in academia, how to measure ambient air quality, how to have a geographical spread of... And so there is some research on exposure, but it's not really taking into account in the whole legal debate. And so by bringing this question about our exposure, well, our statement is always, no one lives in a measuring station. So if the mean over Brussels is good, but you happen to live in a street where you have a street canyon, well, you have no message with this mean in Brussels. If in general you live somewhere in the outskirts of Brussels and you will have the feeling that you have a good air quality because you live in the green, but in fact you spend every day, one hour in traffic exposing yourself to bad air quality, then it might be that you are more exposed and you have more bad air than someone living in the city center. So bringing new questions into the debate and trying as citizens to, by measuring ourselves, by doing little analysis ourselves, by storytelling, by pushing governments to ask new questions to academia, but also pushing academia to bring to account the questions that we as citizens have. This is something that for us is the most important aspect of citizen science. And can you say that at the moment there are already a big difference, significant, significant differences between the authority measurements and the citizen ones? You mean in the results? Yes, in the results of the air quality. That's one of the things that I always find a bit ironic that most of the time our measurements are more or less in line with what they show. So there's a lot of fear about certainly, I think less from academia, but more from policy kind of view because they think in a legalist kind of way about this. So they have a lot of fear about what these sensors can show. But most of the time it shows that, well, there's not that much discrepancy between both. And sometimes I think there was debate and influence there last night also. The sensors, the civic data are first to really see that the pollution peak is coming. And so I think this is a good thing. And we don't always need to frame it in the legalist debate, but about just knowing as citizens and getting the right policies about air quality. It's not only a legal question, it's just also a democratic question. Okay, thank you. I'm not sure whether this question is for you, but I wonder if somebody is going to give an overview of air quality, what are the different kinds of particle, different kinds of gases, the relative importance. Said that we have some kind of context as to whose sensor is measuring what. Well, for the moment, and I think the others can also say something about it. Most people are measuring PM because it's sensor-wise this is very accessible, but there's a lot of pollutants around and everyone, every pollutant has its own behavior, it has its own consequences for health and so on. So there's also something that we think that needs to be, this knowledge in society needs to be broadened. And so it's, well, you can find this kind of things on, for example, the website of Irselin, of the different organizations, of administrations measuring air quality, about the pollutants, about the effects, but it's not very accessible. So we need more accessible data for everyone. And I agree there with what you say. You need to, people need to know what is the difference between NO2, between PM and how they interact and so on. And so, well, for example, about ozone in summer, we have, well, that's something that's now very common and people know about ozone because it's on the weather forecast that they talk about this. And so people start to know what is ozone and when does it occur and so on. And so we need same kind of accessible knowledge and spreading of information about all the other pollutants. PM is a particle. Yeah, PM is find dust. So I remember when there was, well, there's an ongoing debate in China about levels of pollution in cities. And I seem to remember that the American embassy was distributing a set of statistics that was different from the one that the Chinese were providing, that's no surprise, but the particular difference was the particle size that they were measuring. And they argued that the particles that they were measuring were of a size that was far more relevant to human health than that which the Chinese authorities were offering. For the moment, but you really need to talk to the specialist about the size that is taken by the World Health Organization as the indication for health issues is PM two and a half. So the one that influence air is measuring, the one that the air beams are measuring and so on. So I'm not familiar with the case of SIRNA, but it might be that indeed I measured PM 10, which also has health issues, but other health issues than PM two and a half. The American embassy measured two and a half. Okay, yeah, thanks.