After years of deep scientific research, extensive media coverage and high-profile celebrity attention, reducing CO2 emissions to prevent climate change is deemed almost exclusively the most pressing global threat to humanity.
Yet alongside this, another invisible threat deeply linked to our way of life has gone unnoticed. With some 4.2 billion people living in urban environments today, the health impacts of air pollution are intensifying on a global scale. Airborne pollutants lead to cardiovascular and respiratory diseases such as lung cancer, pulmonary fibrosis and acute asthma. It’s predicted an additional 10 million unnecessary deaths across the globe – almost double that of COVID to date – will take place this year alone. The OECD predicts outdoor air pollution could cost 1% of global GDP, around 2.6 trillion us dollars by 2060.
So with these significant concerns and spiralling health costs, how can we make the changes necessary to clear the air in our cities?
Welcome to Racing Green
The podcast that explores the ideas, innovations and influencers making waves in the journey towards a sustainable future for our planet. In each episode, we investigate the new challenges, ingenious solutions and the undiscovered opportunities that lie at the heart of our rapidly changing world. We aim to accelerate a new era, founded on optimism and impactful collective responsibility.
Today we chat with Dmytro Chupryna, Sales and Business Development Director at AirLabs, to explore how the rollout of a revolutionary dense network of air quality sensors in our own local area of Camden, north London, could provide the vital data needed to ensure the future health of our cities around the globe.
Thank you so much for the invitation. I’m glad to be here.
I wonder if you could tell us a little bit about what, what is air pollution actually? What are the main pollutants that we look to when we’re discussing air pollution?
Air pollution is considered to be one of the biggest threats to wellbeing across the globe for millions and millions of people. And it’s considered by WHO that over 8 million people die each year because of air pollution. And it causes long-term and short-term diseases for hundreds and millions of people across the globe. So, it became a health problem, number one, and a death rate even higher than COVID of any known disease. So millions and millions of people and scientists are trying to find a solution to this problem. And we want to be part of that, and we want to help communities, help governments, help scientists to understand air pollution and tackle it.
Great. Well, you know, you are involved in this incredible project called AirScape. I wonder if you’d tell us a little bit about AirScape.
The key problem we’ve found out, and the roots of our solution AirScape, came from long-term scientific research, led by our R&D team in Copenhagen, and led by our Chief Science Officer Matthew Johnson.
The system of air quality monitoring which currently exists in London, Camden, and also globally, refers to very dispersed reference stations. If we compare that to, for example, a situation in hospitals, where you have all the patients, and you measure only the average temperature for all the patients they have, which is nonsense. We have the same situation with air pollution. So, for example, in Camden, there are only four reference stations, dispersed kilometres away from each other. And they calculate average air pollution levels in Camden, for example, and broader in London, of course. But eventually, you’ll receive the same data on Euston Road as in Hamstead Heath, which of course doesn’t make sense.
So AirScape is a solution where we try to deploy denser networks of air pollution sensors, an average distance of 10 square metres, so we can understand the air pollution level on each particular street, in each particular corner and in many, many places around Camden. So our model provides people with real-time, street-level data on air pollution, available to everyone.
So, what are we measuring? And what, what types of pollutants are we actually measuring?
A very wide range of pollutants exist in our world, but the key drivers of pollution in London are four components which our system is monitoring. So it’s Ozone, NO2 and two types of particulate matter, 2.5 and 10.
These are the main drivers of air pollution. Each has its own characteristics, and each of them concerns different types of diseases. And of course, all of them contribute more generally to climate change and see problems with CO2. They come from different types of human activity. Mostly, of course, from fuel from cars, construction sites, different types of businesses and activities of industry activities. So, it’s a combination of different factors. London and Camden is a very dangerous place to live. And that’s something we need to, tackle for our children, for our generations and for ourselves as well.
So how did this idea for AirScape come about?
So the key idea takes its roots from the problems we had with different air quality monitoring projects. Because we have plenty of them across the globe and plenty of them in London, but there’s no real one data point and they use different models, which can of course create results, you know, for a particular territory, for particular schools or for particular roads. But we can’t really detect the whole picture. So the idea came about that you can’t tackle something if you can’t measure it. And there was a process to understand how we can measure. And the only solution which was really practical and sustainable is to create these dense networks of air quality monitors. This kind of solution provides us with sustainable data, as well, we took four years of research and development of particular sensors, so they’re not so expensive. And secondly, they create the most spatial resolution and more time frequent data measurement. Classical sensors, or reference stations, do calculations and take data only once an hour. So, yes, of course, you can understand something from that data, but if you particularly want to tackle a solution of a number of buses coming from a particular street, at a particular time, you can’t really measure it and work with the data if you only take it one hour. So our sensors take data every single minute. It’s not only about sensors and hardware. AirScape is a data solution. So, last week, we launched a beta version of our map, which is available to everyone on the website airscape.ai. Currently, our pilot project is covering only Camden, but we of course have ambitions to create this network in other boroughs of London and beyond London as well.
So it’s a real-time system, every minute?
It’s real time, every minute. And everyone who goes to the map on laptops or on their phones can see the level of pollution, and they see the resolution of it. So you can see actually how it changes from street to street. And as well, there’s a mostly permanent spot at Euston Road, of course, because it’s one of the most polluted streets, considered to be even in Europe. You can also search for the location. You can choose your school, for example, the place where you live. And then for each location, you’ll have a history of the data, for the whole period of those sensors operating, and for the previous hour, previous day or one week or one month, so there’s a different timeline. And also there’s a drop-down by pollutants. So you can see which pollutant dominates in your particular area. And on top of that, to make it user-friendly, we developed AQI, which is AirScape Quality Index and a leaf rating. So you can always, for each location, understand how bad it is in general and compare it to other locations as well.
Oh, AQI that sounds fascinating.
How do these sensors themselves actually work? I mean, I wonder if you can describe to our listeners what does this sensor look like and what’s inside it and how does it actually measure? How does it work?
Yeah, difficult within the podcast because you can’t show them, but it’s actually quite a small device, which will fit in your hand, less than one kilogram. And it’s a device which has a combination of different sensors for each pollutant, combined together with data transmission components which use a 4G signal to send the data to our hubs and servers. Therefore, of course, it needs electricity and it’s located currently on lampposts, but the solution can be put on walls as well. The lamppost solution was the most feasible because it needed height and an open area. And of course, they have electricity, and you can create this kind of grid type of network. And based on the data we’ve seen from all these sensors; we interpolate them and understand the real-time data in each particular location in between those sensors.
And, and there’s AI built into this system?
Some bits of it. It’s mostly maths models which consider because air pollution also depends on multiple factors. It’s like a landscape; the height, the wind, and the temperature outside (if is freezing cold or it’s super-hot) so you need to consider all of these elements to receive realistic data so it’s not corrupted by any of this. But also you need to understand the geographic model for this particular territory. So it will be different because, if you have houses and different kinds of obstacles, you need to consider how air flows through the streets. So that’s also a big part of the development of the system and a big part, a big component of it is actually that’s in the model. It has taken a couple of years to finesse it, but now it’s stable, live and it’s proven within different research and pilot projects.
I’ve had a chance, lucky enough to have a chance, to have a look at the online site. And it looks incredible because you can zoom in and zoom out and you can look at the history and you know, for those that might be listening that live in the borough of Camden, it’s amazing. You can check your own street out. You can check your own school out. As you mentioned earlier. What are some of the uses? What are the actual practical uses that businesses or the community can actually make of this network?
Yeah, the key thing to understand is that data and air pollution and data on different environmental problems will be the most demanded data in years ahead. Cause as I mentioned before, you need to solve the problem, and do it by small actions. Sometimes it can be bigger, but if you look at your community, at the place where you live, even small activities, small things can change the situation radically. If all parents stop driving their kids to one particular school, the air quality will be improved during the hours they drop the children, for example. Or if you navigate the traffic in a better way, or if you put some kind of restrictions in this particular manner. But to understand whether your step is successful or not, you need to measure it before and measure it after.
So our system allows local authorities, families, community groups, and community activists to actually have the data, to work with it and to understand how their actions, or potential actions, could improve the situation. So this is the key thing that we provide this data for free for everyone, and then people can act on it and make some very important life decisions. Relocating for example, or, you know, limiting some kind of activities in the peak hours, being outside. Or taking safer routes while cycling or walking in their neighbourhood. And of course, businesses, businesses will be required to decrease the amount of pollution they produce. And therefore these data can be used, first of all, to put pressure on businesses, but secondly, for them to monitor themselves and to actually report to communities, to people that they are improving, so they can have proof of it.
So that’s the key idea that it’s not only having this data, it’s also doing something, and using this data. And the big thing is that researchers, academics, and health professionals, will all need this data for their particular research on air pollution, and all health problems related to that. And our system allows having this kind of really high-resolution data
To bring something together like this, you’ve obviously gotta have a very highly skilled team of engineers, data scientists, and project managers. So how has all this come together? Logistically?
Yeah, so we need to deploy sensors, operate them, power them up, and locate them in particular locations. So therefore we need first, local government or local authorities for each particular borough, or it can be a citywide solution, to get all the approvals and their support of it. But we see boroughs and local governments being supportive of that because it’s a very important part of their strategy and commitments. So usually they’re receiving that really well.
Secondly, you need to produce the devices. The first part of it was developed in our labs in Copenhagen and there have been five generations of those sensors, to create the most reliable one.
And of course, there’s a software team, a very professional one, which creates the data modelling and data mapping on top of the data received from hardware.
This type of system, which connects hardware, software, and data-focused platform, doesn’t exist anywhere else. There are many companies that produce sensors. There are many kinds of crowdfunding/crowdsourcing campaigns on their solution. There are sporadic research projects. There are data platforms which try to use reference stations’ data, but you can’t get any resolution from that, so the data you have is very, very average. So the combination of [AirScape] is the only one solution that exists. Therefore, we’re really keen to spread it across London and go to other cities in the world, and to the most problematic cities in the world which are, of course, the biggest capitals.
Well, it’s amazing to have probably the densest real-time network of air quality sensors in our own borough of Camden, in our own city of London. Who pays for all this and how can it be financially supported?
So we invested in deploying the network. But, uh, if you come to our map, you’ll see the map of sensors and you see a map of sponsors. We encourage local businesses and bigger companies to support us because, to maintain the network, it needs resources. So therefore we have sponsorship prices, quite small ones, and everyone can come to our platform and sponsor one, two or 10 sensors. And for these sponsors, for the users, we will provide more access to the platform with different features. Plus their logo can be seen so the community and the users will see which of the companies are really taking care of it and supporting it.
Also, we work with bigger companies. We only launched our pilot model here in Camden, but we see that the big companies, and those companies that are the drivers of air pollution, should be responsible, and support the maintenance of such networks – to keep them alive and to keep this data available to everyone. So we see them and foundations, and maybe sometimes governments as key sources who need to support us and provide this data to people, citizens, community groups, activists, and everyone because we can only estimate how many lives this data can save a year. People with special conditions need to know air quality data right now, and also be alert of any kind of incidents or higher pollution levels happening. So we truly believe that if we do it together, and people will join more and more and support the network, we can at least decrease this 8 million dramatic number of deaths from air pollution. And effectively everyone will save their own lives because, as long as you live in a very air polluted area, the higher chance you’ll have of long-term diseases or just shorter, shorter life. So no one wants that. We see it as a collective action and we encourage everyone to go to the map, check the project and, either support or bring companies and businesses who can support this network.
So, Camden, you’ve got the prototype. It’s amazing what you’ve achieved so far. What are the next steps?
Among the next steps, we have the ambition to go to the five major cities in the world and deploy a network or pilot project there by the end of the year. But our key goal is to cover 200 major cities around the globe, in a five, 10-year time perspective.
And the history started in Camden. There was a combination of factors, of course. Big support from The Camden Clean Air Initiative, from activists from the community, and from local borough authorities. London, I think at the end of March, had the highest pollution, even bigger than in Beijing. So London is really a critical city to start with. I think it brings a lot of visibility and credibility to our solution. So we thank everyone who supported this idea and who keeps supporting it. And we also look forward to multiplying this experience and actually getting London covered. Because if you look at the data, it doesn’t look really good for London. So we need to actually deploy it, and create those big movements and community actions to change the situation. Otherwise, London will become a city that you can’t live in or create long, long, long, long problems for many of its citizens.
Great. Well, sounds like we might need an Elon Musk or someone to invest in this project! So in the future 5/10 years’ time, you’re in five major cities or you’re or a lot more by that time?
A lot more. We have a preferred list, of course, but it’s a very opportunistic approach because we also have a current pilot project in Milan, where we’ve installed, 10 sensors and created a small network to show the results to the local authorities and environmental agencies. So they see the difference, and they see how it works. And of course, the Camden platform helps us with that. So we have a lot of conversations about different cities and, our air quality network is already installed and working in Cork, a city in Ireland. There was a big demand because of the big port of Dublin – a lot of ships are coming and highly polluting the air inthis small town. So we see Ireland and Dublin as potentially one of the next cities. But we also of course go wide. The globe is big and the problem is huge. So it’s a matter of which locations, which cities are ready, and the potential sponsors who will be willing to invest in that.
Well, what great work being done by AirLabs with their AirScape project. Thanks so much Dmytro for joining us here today.
Thank you so much for the invitation. And again, thanks a lot to everyone who supported us and who keeps supporting us.
|cookielawinfo-checkbox-analytics||11 months||This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Analytics".|
|cookielawinfo-checkbox-functional||11 months||The cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional".|
|cookielawinfo-checkbox-necessary||11 months||This cookie is set by GDPR Cookie Consent plugin. The cookies is used to store the user consent for the cookies in the category "Necessary".|
|cookielawinfo-checkbox-others||11 months||This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Other.|
|cookielawinfo-checkbox-performance||11 months||This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Performance".|