In this episode, host Kristin Hayes talks with Valentina Bosetti, a Bocconi University professor and a senior scientist at the RFF-CMCC European Institute on Economics and the Environment, who has closely studied air quality in Northern Italy. Bosetti finds that, while air pollution decreased in the region during the pandemic lockdowns, pollution did not fall nearly as much as expected, largely because lockdown measures hardly impacted agricultural emissions. In addition, Bosetti warns that the public health benefits of improved air quality pale in comparison to the lives lost from COVID-19, and unless governments take action, pollution will surge again once economic activity returns to pre-pandemic levels.
Listen to the Podcast
- Lockdowns do little to stop agricultural pollution: “The big question is: Why didn't we [see] a larger effect [of the lockdowns reducing air pollution]? And the answer we find is agriculture … When the real shutdown came, basically nobody was allowed to go out ... But the activity that was not affected was activity related to agriculture, mostly because, obviously, this is a source of food for the local community. So, they kept doing their business.” (11:31)
- Harm from COVID-19 dwarfs benefits from reduced air pollution: “If you want to have a sense of comparison, how much is 20,000 years of life saved [from reduced air pollution]? You should consider that, due to COVID in the same period, we have lost 190,000 years of life. So, basically, the reduction in NO₂ gave us 10 percent in terms of lives saved than the loss we had due to COVID.” (21:54)
- Local pollution, while solvable, rarely drives people to action: “I care about pollution, mostly because I live in a polluted area. I don't have to change anything in China ... [or] in India to solve the local air pollution in Italy. So, it must be simpler as a problem to be solved. And on top of this, people that live in the area and that could solve the problem also perceive the damage. So why are we not able to solve a simple problem when it's so evident and in front of the eyes of everyone?” (4:28)
The Full Transcript
Kristin Hayes: Hello, everybody. Welcome to our second Resources Radio Live recording. I am once again your host, Kristin Hayes. As another reminder, Resources Radio is a weekly podcast from Resources for the Future. This week, for the second time, we're recording the podcast in front of a live, albeit virtual, audience.
As a reminder, we'll mostly stick with the regular format of our podcast series, where I'll ask our guests a range of questions for maybe 20 minutes to half an hour. But the nice thing about the live recording format is that it allows us the opportunity to take some audience questions. One more note: in addition to being edited lightly for the podcast, the public webinar is being recorded and will be posted on our website afterwards.
So this Resources Radio Live series focuses on topics that lie at the intersection of the COVID-19 pandemic and energy and environmental issues. In our last webinar, we covered electricity demand during the pandemic, and now we're going to be talking about another very important topic: air pollution.
There's been a tremendous amount of both anecdotal and empirical evidence that air quality improved considerably during the lockdown in a number of locations, and particularly as vehicular traffic was reduced. So today I'm very fortunate to be joined by Valentina Bosetti, who is a professor in the Department of Economics at Bocconi University and a senior scientist at the RFF-CMCC European Institute on Economics and the Environment.
Valentina is based in Milan, which, of course, was one of the early epicenters of viral spread, and she's going to be talking about research she conducted with colleagues about what happened to air quality in Milan during the height of the lockdown and what that meant for human health. She'll also give us some insights into air quality impacts in other parts of the world, as well as to what extent air quality has reverted to pre-pandemic levels at this point.
So thank you again for joining us in this Resources Radio Live recording, and with that, let's kick it off. So Valentina, welcome. Thank you so much for joining us on Resources Radio. It's very nice to see you again. How's everything going over in Italy?
Valentina Bosetti: Well, finally, much better. Thank you for having me here, and good morning to everyone, or good afternoon. Yes, everything is now finally looking much better. I'm sorry. Maybe that's not the case there, but there is light at the end of the tunnel. So let's hope.
Kristin Hayes: Yes. Thanks, and we're very happy for you guys. We really are. It is nice to see, as you said, light at the end of the tunnel. Well, let's start with some introductions. So can you tell our audience just a little bit about your background and how you started working on environmental issues? I guess I wondered as well if air quality is a particular interest of yours. Is it something that you've regularly studied over the years?
Valentina Bosetti: So I am an environmental scientist as background, and I study environmental economics, and then my PhD in computational math. And I'm that kind of nerd person who builds climate change economics models. So not really air pollution, which is a local problem, but more looking into long-term dynamics of the economy and how that affects the climate.
But I live in one of the most polluted areas in Europe. I live in Milan, Lombardy. As you mentioned, this was one of the first places to be hit hard by COVID after China. But it's also an important region in Italy where most of the national GDP is generated, and it's where most of the economic activities are. And so for these reasons, together with the fact that the geography is crazy, so we have the Alps and then the Apennines, and basically there's mountains all over, all around Lombardy and the Pianura Padana, and that makes circulation of wind more difficult.
So all this together makes Lombardy and Pianura Padana, which is the plains within which Lombardy sits, a very polluted area. So to give you an example, the area exceeded the recommended air quality by the European Union multiple times. We are regularly fined by the EU. And Milan in particular has very high concentration of PM2.5 pollutants. And before COVID came, it was very, very bad, particularly bad. We had the worst season ever.
So why do I care? I care about our pollution mostly because I live in a polluted area. And I think if we cannot solve a problem that is local—and it's much more simple. I don't have to change anything in China, nor in India. I don't have to change the power system in India to solve the local air pollution in Italy. So it must be simpler as a problem to be solved. And on top of this, people that live in the area and that could solve the problem, also perceive the damage. So why are we not able to solve a simple problem when it's so evident and in front of the eyes of everyone?
So the first question that came to me and the group I work with is, is it because people don't notice? Is it because we don't have enough information? So people might read in the newspaper that Milan air quality is bad, but maybe they don't have enough information. They don't really realize where it comes from, what are the causes, what are the damages and the potential risks for their life? So what is it that people don't understand that is preventing them from going in the streets and asking for greater regulation or whatnot.
And so we started to monitor. So there are a lot of stations. There is a great system in Milan that provides information on only the day afterwards. So you only know what air quality was the day before. There's no real-time information. And so we thought maybe, behaviorally, if people have real-time information, then this will change things.
And so we were very much with our eyes on the monitors, and at the same time, we are collecting information on people's perception in the city when COVID comes. And what I was expecting is, well, from tomorrow, air quality is going to be fantastic. But then we were struck by the fact that air quality wasn't as good as we were expecting. What was happening?
People were talking about seeing the sky from, you know, seeing everything until the sea. And there's, I don't know, moose in the street, the whatever animals, and that's a fantastic part of COVID, and we didn't see air pollution going down as much as we expect. And so that's why we started to study the problem. And we started looking more into this, basically. I think that's where everything started.
Kristin Hayes: Hmm. Fascinating. Well, I think that's exactly what's so great about having empirical research related to this because, as you noted, there were a million anecdotal stories about people being able to see mountains that they had never seen before. And you could see Mount Everest from places in Nepal. And so I think people did have a sense that air quality was improving in a more tangible way, but exactly how to put numbers on that is kind of a mystery to most of us who aren't really thinking about these issues. So yeah. So let's talk about the numbers.
Valentina Bosetti: It has improved, and it was improved. I have to tell you something, also. Most people were appreciating not only the air quality, but the fact that cars were not around. So there were a lot of stories of people really, finally enjoying the city. I don't know if it was the same as-
Kristin Hayes: Mm-hmm.
Valentina Bosetti: It's the same there, but in Milan, we were not allowed to get out of our house. So we were really close indoors, no way of appreciating anything of this lower traffic and so, we only had one thing that we could do. That was doing research. We had a lot of time. A lot of time for the kids, but also a lot of time to do research and trying to figure out what was going on. So I think that we had a part of a lot of research on COVID came out from the fact that people were stuck in house and didn't know how to use their time.
Kristin Hayes: Yeah. That's a good point. Well, before we turn to more conversation about the study in particular, I am curious, though. Did you—Well, also, you were stuck in your house, so maybe this was hard to judge—but, do you feel like you had any sense that air quality was improving anecdotally in your personal experience of it? Was it changing in ways that you felt?
Valentina Bosetti: So most people did. I was biased because I had the monitor and so I could see—I do monitor air quality also in house. And so I was seeing some days it was going much better than usual. Some days it wasn't. We were still above the required level for safety. And so that was when I started to wonder.
Kristin Hayes: Yeah. Well, great. So that's a good lead in. Why don't you tell us a little bit more about what you and your colleagues found and how you went about conducting the research that you did?
Valentina Bosetti: So we did find, obviously, as everyone expects, a reduced average daily concentration, both in PM2.5 and NO₂. Okay. So these are the most important pollutants. And we did find the reduction that is in the range of 15 percent for PM2.5 and 34 percent for NO₂. So these are numbers that we calculated, what are called background station, and background stations are basically stations that are located in places that are not influenced by anything in particular. This is the general exposure that you would have in any day.
Then we also went to traffic station where we found a much bigger reduction, around 30 percent in PM2.5 and 37 percent in NO₂. So we find a larger reduction when you really look at stations that are nearby, big roads and heavy transport. And then at industrial station a decline in PM2.5, even bigger, 70 percent bigger than what you had. So it was a huge reduction at industrial station.
So the question is: does this matter? I mean, how much is it, because most people do not work with this number. I'm not even giving you the micrograms because most people, but the point is that if you think of the days we normally exceed EU regulation average limits that are defined by what is safe for humans, then the average limits that we were exceeding this threshold fell down by 55 percent or 70 percent. So in general, the city of Milan and Lombardy as a whole was much more compliant with the limits. So we had a big reduction, but still, some days, although the number of days where we were exceeding the EU average came down by so much, we were exceeding, in some days, the limits.
And so the big question is why didn't we have a larger effect? And the answer we find is agriculture. So the one activity—so, there was a shutdown, total. First schools closed. Second, activities were ... most people were required to work from home. But then, when the real shutdown came, basically nobody was allowed to go out, very similarly to what happened in New York. But the activity that was not affected were activity related to agriculture, mostly because, obviously, this is a source of food for the local community. So, they kept doing their business. So the period of February, March, and April is where there is a dispersal of animal liquids on open fields. Okay. This is a very common practice. And that releases a lot of ammonia. And that ammonia is a precursor of PM2.5.
What that means is that with ammonia in the air, basically, some chemical reactions happen, and secondary PM2.5 is formed. So the reason why we didn't see reduction that we expected was mainly due to agricultural activity. And that really led us thinking about the fact that this is a huge source of PM2.5. I looked it up, and that's as important in the US. But although it's a widespread problem, there's very little monitoring. For example, we don't have agricultural station. Okay. There is much less monitoring of this kind of pollution.
So we can talk about this later, maybe at the very end, but I think this was a very important finding for us, the fact that the traffic was off, shut down, and most of industrial activity off, and a little bit of heating was still going on, but it was a very warm spring. So that was not really important, but we can assume that that was as usual. We still have these days with exceedance of safety limit.
So you asked me, how did we do it? Basically, we took all the pollution stations we have and weather stations. Most of the numbers you've seen out on the press are what are called year-on-year study. So you take the average of air pollution in one, for the last five years in February, and then you compare this to February 2020, and then you say, "Well, it's less." Okay. And it is already an important number, but it's not taking into account a lot of things that might affect, are they real numbers?
As I told you, for example, in Lombardy, what is very important is weather. Weather can really affect the concentration of air pollution, and it is a big determinant, the most, the largest determinant.
So what we did was basically to use machine learning to train in a system that was reproducing the pollution stations, but only using weather and information about past emissions. And then we generated a fake and unreal February, March, April, and May. So four months that didn't happen in terms of air pollution that we’re generating through machine learning. And we compare that with what happened in reality.
So basically we had a real exogenous quantification, the possibility of really exogenously quantifying the amount of emissions, the concentration change, only using something exogenous, which is the weather. So the big difference with respect to these other studies is that instead of using year on year, you might have a lot of biases with this. We're using this system.
Kristin Hayes: Hmm. Interesting. Do you know if anybody else has tried to do anything similar? Is this fairly pioneering as far as you know?
Valentina Bosetti: So there is a study somewhat similar, not entirely similar study done for China, which, I'm happy to discuss the results if you want. But they use a slightly different method. They use a comparison with non-treated cities. So they compare, for example, cities where the lock-in came in first, one in the Wuhan area, for example. And they compare that area with areas where lockdown kicked in afterwards. And so they basically generate a synthetic one that is a mix of these other cities, where they were not treated, and they compare treated and untreated. So it's somewhat better than, year on year, which is the very basics. But I think the idea of having this machine learning system of training and generating an unrealistic or a realistic month that would have happened without the lockdown. I think that's the best that you can do.
Kristin Hayes: Very interesting. And I do want to talk a little bit more about China. So thank you for bringing that in, although I want to come back to that in just a second. I had one more curiosity question for you. Do you feel like the research that you have done during this period has really helped you understand more what the proportions of contributions to air pollution are? I guess I'm wondering, was this a chance to sort of dial down transportation and industry and really understand better what agriculture was doing? Or did folks pretty much understand before what was contributing to overall air quality, and this just sort of confirmed that? Does that make sense?
Valentina Bosetti: Yeah. So we discussed a lot with people at the regional environmental protection agency. They always had a suspicion because when you have this particulate matter, you can put it in the lab, and then you can see whether there's sand, and then particulate matter is coming from, say, a sand storm from Africa. Or you can see where there is organic components. Then it's going to come from different types of activities. So they tend to do that. And they had an idea that in some periods of the year, the effect of agriculture was more important also because, obviously, this process of ammonia affecting or generating secondary PM is obviously not known, but they really were never able to pin it down as well as you can with an experiment, like the one we have, if we can call it experiment, and they were thrilled.
We started cooperating because it might be stupid, but the Lombardy region gets fined many, many times because of exceeding safety levels. And if you can show that basically, even if you shut down everything, okay, everything, then you are still exceeding, that really shows how much important is the geography, the orography of the region. So for them it's very important.
And the other part is that when you have these, you can really go and see it with farmers and say, "Now you have a very important role, because even if we were to shut down everything else, you're doing this. You're harming people in the Lombardy region. So let's find a way to reduce those emissions." And technologies are out there, available. So now we could quantify how many lives saved you would have with the introduction of these technologies. And we can justify, even a subsidy to help them using these technologies that avoid leakage of ammonia in the air.
So I think it was important because when you really need, the air pollution is a tricky problem. There's dispersion. There's a lot of chemical reactions happening in the air. So it's very hard to bring it to court. Now we really have a study where everything else was, you know, you have no excuses, so you can really see the direct effect and indirect effect of agriculture. So I think that is important. They were thrilled of having this study.
Kristin Hayes: Yeah. Yeah. That's so interesting. And you mentioned something that in my mind was actually one of the most interesting pieces of your research, too, in which you compared the years of life saved, essentially, by these improvements in air quality, compared to the years of life lost, given the terrible nature of the pandemic and the region. So how did you go about making that comparison, and what did you find? What did you find there?
Valentina Bosetti: So basically you can do this many, many different ways. And so that's the one part we really need to work now, which is the part that is less interesting for non-technical folks because it's really, then you come up with a range rather than with a number, but you have to do it because it's not that you're adding one apple. It's not that simple, but the idea is that the European Environmental Agency has guidelines that says, now an increase in all-cause mortality risk by 6 percent for an increase of 10 micrograms per meter cubic increase in PM2.5. So basically we use the decrease in PM2.5 concentrations to calculate how much years of life were saved in the months of February and particularly in March, April and May. And the number, which, if you look at the number, it doesn't tell you anything. It's 8,000 years of life saved.
If you consider PM2.5 and 20,000 years of life saved, if you consider the reduction in NO₂. Now you cannot simply sum the two because there are a lot of interactions between the two pollutants and their effects on health. So you cannot really sum the two, but if you want to have a sense of comparison, how much is 20,000 years of life saved, you should consider that due to COVID, in the same period, we have lost 190,000 years of life. So basically the reduction in NO₂ gave us 10 percent in terms of life saved than the loss we had due to COVID.
Early numbers, very early on in the pandemic, back of the empirical calculation for China, gave numbers that were different. They were showing much greater effect of a life saved due to lesser pollution than losses because of COVID. But I think that was because we were very early on, you know, they wanted to get into newspapers. So they wanted to have a punchline. So we are saving more lives with the air pollution avoided deaths than we are with the deaths we are having with COVID, but it was very early on.
Then the number of lives that we've lost due to COVID has increased as we have not expected. Most people had not expected, I believe. It is still important, though, to consider that it is estimated that we lose something like 60,000—we have 60,000 premature deaths in Italy because of air pollution. And people are very much afraid of COVID, but they don't consider or fear air pollution. So that remains a big reason for showing this number and repeating these numbers, because most people don't realize it. I'm still puzzled why that's the case. I'm still puzzled why now everybody's wearing a mask, but with very bad air pollution, you would see people running around in Milan, running without a mask with nothing, in a day with very bad air pollution. So I'm still puzzled why that's the case. Maybe if we can find a way to, to bring attention to this problem, it's going to save a lot of life more.
Kristin Hayes: Yeah. That's interesting. I have to wonder, too, if, like so many things during the pandemic, I feel like I just sort of accepted things as the way they were. And it was only when things changed dramatically that I thought, oh, I guess there is a different, some obviously extremely negative and some, oh, well, actually we could give more city roads over to bicyclists instead of cars.
And so, I think sometimes it takes a change or a shift of this magnitude to really reiterate for people what they've just accepted as the background conditions of their life. Maybe that's getting too psychological, but I think there is a case to be made that we're all realizing a little bit more about what our baseline was compared to what can change.
Valentina Bosetti: But I think that people now sometimes—I have no final answer to whether that's good science or not—but there's been a lot of rumors that air pollution can increase the morbidity of COVID. So we tried to pinned it down with rigorous science and we couldn't, and I don't think anybody has done that well yet. But it is weird that people started to pay attention to air pollution because then you might die more of COVID rather than paying attention to the pollution, because you might die because of the pollution. So, I don't understand that. And I think, again, it's a problem that people don't notice and we have to put monitors everywhere. People have to know when it's a risky day, when you should not do your walk with your kids at the park because there's very bad air quality.
Kristin Hayes: Hmm. Interesting. Well, let's talk a little bit more about China because I know that's obviously another country of very great importance in the pandemic conversation. Is there anything else that you would want to mention to us about your initial work or others' initial work, looking at these air quality trends in China? You've described a little bit of it, but other findings that have come out of that other important epicenter that you would want to share with the audience?
Valentina Bosetti: Yeah. I think the most, again, not to give you numbers because it will bore you to death, but I think the big bottom line of the studies that are out there—there is a very good one by Cole, Elliott, and Liu, on China—is that while NO₂ concentration really came down. So, it was a pollutant that really came down two levels that were very close with safe limits by the World Health Organization. PM10, because most of the studies look at PM10, not PM2.5. So this is a little larger particulate matter. PM10 fell from a level way beyond the safe limit. So, it was super high, but didn't fall below the safe limits. So the bottom line is that although there was a big, big, big reduction in NO₂, particulate matter fell a lot. It came down even by 35 percent, but it was so high before, it was still above the safe limits.
The other interesting elements that were discussed in some of these papers is that when NO₂ comes down, because NO₂ reacts with ozone and destroys ozone. Ozone is good when it's up there, it protects us, but it's bad when it's a level where we all walk and breathe. So NO₂ reacts with ozone and destroys it. When you have less NO₂, ozone goes up. And so, although NO₂ was going down, because of the fact that NO₂ was going down, ozone went up to unsafe limits.
So, good and bads of the effect of the COVID in China. But some of the studies suggest the number of life saved, and here most of the study report, not years of life saved, but the lives saved, which I think is not a good metric, but it's not my study. And the numbers are in the range of 10,000 for all China, but some studies say 30,000. So it really depends where these studies are year on year how precise they are. But generally, I mean, nobody has a doubt that NO₂ and PM fell. It wasn't enough. Even the lockdown wasn't enough for China to bring down PM, at least PM10, to levels that were safe. So there's still a long way to go.
Kristin Hayes: Yeah, it really does illustrate the magnitude of the challenges that I think a lot of places are up against when it comes to both the kinds of emissions we're talking about here, but also CO₂ emissions. A lot of people commented as well about that same phenomenon where no matter how much we reduced activity, we still didn't really make a significant dent in CO₂ emissions too. So we have a lot of work to do.
A few months have passed since the most strict lockdowns. And I asked this question of our last guest, but I want to ask this to you as well. What have you read or seen or experienced, or, again, seen in your own datasets about how air quality levels have rebounded, in this case, in a very negative way, but rebounded where they were before. Is there any continuing change, or have things really kind of gone back to previous levels?
Valentina Bosetti: So China, total rebound, most studies. You mentioned also greenhouse gases, and certainly in greenhouse gases, we had a total rebound in China. I would say the rest of the world is not back to normal. And so we cannot say yet, what will be when we will be back to normal because, for example, it's now considered unsafe to take public transport, which was one of the main way to get around in big metropolis in Europe. And so, for now, most people are using cars. So how's that going to play out in the fall when people are going to come back working is a big question.
So there was a spike in the use of bikes. That is good, but overall, it's yet unclear how it will end. I've seen today the numbers from Copernicus. If you want to have fun, Copernicus Atmospheric Monitoring Services shows you what's going on in every seat in Europe and in the world. And it's still the case that NO₂ is lower than average than previous years in most cities in Europe. But I don't know whether, I mean, I'm sure that's because we're not back to normal.
I would not see why we get out of this COVID crisis and are suddenly better. And hopefully we won't be worse. We have to do it fast enough to get back from the crisis and be worse, but it's implausible that we're going to be better and more willing to cut our emissions, et cetera.
Kristin Hayes: Yeah.
Valentina Bosetti: Am I depressing? Sorry.
Kristin Hayes: No, it's okay. It's all right. But it does make me wonder, I really don't want to imply that this situation has been good in any way. I know it's largely been disastrous along a range of dimensions, but I do think that as you pointed out, it has provided, you know, researchers had both the time and natural experiment, for lack of a better term, to ask a lot of questions that are difficult to ask without these kinds of shocks to the system. So, it has provided some interesting learning in the short term. And of course it will provide additional learning in the long term. And I guess before I turn to the audience, I just wanted to ask, are you going to continue this line of research over the years? What are you hoping to sort of study next related to these questions?
Valentina Bosetti: So I mentioned we wanted really to pin down the COVID, the relationship, the PM2.5 exposure, and the higher morbidity with COVID, but it's too difficult. You would need data we don't have although we have very good data on information about the people who unfortunately got the disease, et cetera. We don't have enough good information about air pollution. So I think this is where we have to move next. We have to put monitors everywhere. We have to use citizen science to get much more granular information on how much we're exposed to this air pollution for two reasons. One is that we can then study much better how much exposure affects anything in our daily lives. Apparently, it affects diabetes. Apparently, it affects even the mood. It affects our performance in any task, even mental tasks. So it is important to get better data.
Two, if you get all these data, people will know. People will finally see it. And so they will maybe want to support policies to cut emissions. So I think the one thing that I'm really moving back to is this big survey we are doing in two US cities, two Chinese cities, and two Italian cities, where we are continuously collecting information on how people perceive climate change, but also how people perceive air pollution risks, and how they perceive other things. We did it because we didn't want to, we did the survey this way. We designed it this way. We didn't want to give out immediately the fact that this was a survey about climate change. And so we were putting questions about fears of other things. So now we have good indications, for example, of how fear of air pollution change throughout time, and when our deaths, for example, actually correlated with PM2.5.
So do people change their perception on the basis of what's going on or do they change the perception on the basis of what happens on Twitter, which we're also monitoring, or do they change their perception because of what happens on the news? And we were running this when COVID happens, so we have a great opportunity also to study how a new fear entering the picture has affected how much people feared other things. So studying people's attention to air pollution and how that's affected by various factors is where we want to go.
Kristin Hayes: Hmm, great. Oh, Valentina, this has been such an interesting discussion. Thank you so much for joining us.
Valentina Bosetti: Thank you for having me.
Kristin Hayes: Oh, it's been a pleasure. So let me close the recording today with our regular feature, which we call Top of the Stack. And I'd like to ask you, if you have anything you'd want to recommend to our listeners and viewers. It could be a book, an article, another podcast, again, either on this topic or, frankly, just on something of interest to you that you'd want to recommend. So Valentina, what is on the top of your stack?
Valentina Bosetti: So I have two books. One is Spillover. I understand that everybody's talking about this, but it's an important book too. There's a lot of detail, maybe too much detail. Maybe you don't want to read it like a novel, but you want to skim through, but it's an incredible book by David Quammen and really tells you a lot of the stuff that you want to know. And you want to correct people when they're not being precise about all of this. So I think Spillover is a great read.
And then something that is sort of related, but unrelated, which is a beautiful book called When Breath Becomes Air. It's a nonfiction autobiographical book written by an American neurosurgeon. His name is Paul Kalanithi, and this is his memoir because he died of lung cancer. But this is an amazing book that makes you remember why we are doing this. And it's very well written. It's very, very beautiful. And so in some ways related because it talks about breathing and air and some other ways is a little because it talks about giving meaning to life, which is what we're all trying to do.
Kristin Hayes: Hmm. Well, what a wonderful way to close. So thank you again. This has been a really great conversation. Thanks again to all of our viewers. Thanks again, Valentina, and hope to talk to you again soon.
Valentina Bosetti: Thank you all. Bye-bye.
Kristin Hayes: Bye.
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