Good morning, good afternoon, good evening. Thank you for joining our third and final day of the IBM Research Horizons Future of Climate event. I'm Haik Peter, Manager of the IBM Client Center Think Lab here in Zurich, IBM Research, and your host for today. We are streaming this event live from around the world. Our Horizons event invited to gain insights to IBM Research and engage with our world-class scientists. Today, we will be continuing the conversation around the future of climate with a focus on governments and NGOs' response to climate change. Please use this unique opportunity to ask your questions. On the right of your browser, you will see the chat section. Throughout the event, our scientists will address your questions. With that, and without further ado, let's start. I'm delighted to introduce our first speaker for today, Wayne Balta. Wayne is the Vice President of Corporate Environmental Affairs and Product Safety and Chief of Sustainability Officer here at IBM. Wayne, over to you. Hey, thank you. Hello to everybody all over the world. I am thrilled to open today's session of the IBM Research Division's Future of Climate event. And I mean that. I don't say that generically. And the reason I mean it is because I'm always thrilled when I get the opportunity to speak with the group of not just talkers, but doers, innovators, people who have the ability to create and drive constructive positive change. So thanks for asking me to open the session today. Let me look back for a moment in time on the environmental issue. So the modern day environmental movement is considered by many to have really become started in the 1960s and the early 1970s. Rachel Carson's book named Silent Spring, the first Earth Day, the creation of the US EPA in that era, among other milestones. And since then, I have observed some distinct eras in the modern day environmental movement. First came an era of control. And I think that was followed by an era of prevention. Today, I think we're on the cusp of another era. And I would call that an era of innovation. In the early 1970s, our collective challenge around the world, it was to get control of pollution that was already occurring all around us. We had uncontrolled pollution to the air, to the water, to our land. Some of you in the US may recall iconic things like the Cuyahoga River catching on fire or the recognition of waste that a place named Love Canal in New York. And as a result of that, in the US, in the early 70s, we saw major federal and environmental statutes become enacted, the Clean Air Act of 1970, the Clean Water Act of 1972, Resource Conservation and Recovery Act of 1976, the Toxic Substances and Control Act also of 1976. Imagine all that federal legislation getting done in a short number of years. And as we got better control over pollution at a societal level, well then the policy imperative quite logically shifted towards prevention. We had in the US the Federal Pollution Prevention Act of 1990, the European Union enacted the restriction of hazardous substances directive in 2003 and the European Union enacted a regulation named Registration Evaluation Authorization and Restriction of Chemicals in 2006. What did both of those things do? They limited the materials that industry could use in commerce in order to prevent pollution at its source. But that was all about 20 years ago. 20 years is a generation. So what about today? Today, I see an era of genuine innovation in front of us and it's there for the taking. Now, why do I say that? Let's look at our lives today. Today, our lives in our world are flooded with data and it's increasing exponentially. We're all aware of this. Much has been said and published about it. Now, when I was in school, data was mostly numbers and they were pretty orderly and they had some structure to them. That's not just the case today. Now data means words and a PDF file, words from a scanned document, texts, tweets, photos, videos, and these things aren't necessarily orderly. They're unstructured. They come in different forms and contents. And furthermore, devices like sensors, well, they're enabling us to collect exponentially more data all the time. And in the midst of this, people are trying to figure out, well, what do these data mean? Who owns these data? Where can the data be found? Who has access to it? What can I do with the data? What other data should I collect and how should I do that? With whom should I share my data? I think by now, most of us are increasingly familiar with these essential questions. Meanwhile, and not surprisingly, several different tools have been developed to work on the data and many of them come from the IT industry. And Internet of Things can be created to connect devices and wirelessly share information quickly across time and space. Analytic software can sift through data and detect patterns that we humans have a harder time seeing. Machine learning, an aspect of artificial intelligence, that can be used to ingest continually large and lots of data sets so the machine gets smarter about it and it does this on its own with natural language processing, another aspect of artificial intelligence. The device can listen to human language, conversation and accurately understand it and turn it into data from which the device can learn and even reason. Then there's blockchain, another relatively new tool which can create an immutable shared record of trusted information among all parties who choose to be on the blockchain. It means radical transparency. So we have a lot of data and we have these IT tools. What are people doing with it? Wow, people have been doing some amazing things and some of it's really important. People are advancing healthcare, increasing safety, improving disaster response and recovery. These things are really important. At the same time, some of what people have been doing with data and IT tools is frankly a little bit more geared towards consumerism. Open the garage door, dim the lights, play Free Bird, whatever. My personal favorite send me hundreds of advertisements for a bicycle just because I looked at a bike on a website or I spoke about it with my wife during dinner in our device-enabled home. Oh yeah, these are things that people have also been spending a lot of time on with data and IT tools. Largely the luxuries of first world living. Now I'm not suggesting there's anything necessarily wrong with that but I do have this to say. Not enough people are using data in today's information technologies to repair and protect the environment and to address climate change. So my message is simple. There ought to be an emphatic call for these technologies to get applied to environmental problems with the same fervor and the same passion as they get applied to marketing things, selling things and to the desires of individuals in their personal lives. And I think they will. And I think it'll be innovators like people on this call who make that happen. Take a look at some of the less desirable aspects of modern living. Plastic waste across our land and in our coastal oceans. Particles of pollution throughout the era of mega cities, damage to sources of fresh potable water, shrinking habitats and species and a climate that is increasingly unfamiliar, changeable and dangerous. We need to fix these things. So let me ask, if you had to fix something at your home or apartment, would you go to the store looking for an old hammer and a box of rusty nails or an old hacksaw? Would you say, hey, I'd like to buy a drill from the 1950s please? Or some plumbing supplies from the 1970s? No, you wouldn't say any of that stuff. You'd want the best tools you could get today. So why aren't we constantly demanding that the best available tools get applied to fix the place where we all live? Now, many of these tools are technologies and they exist today, right now. And they're relatively as affordable as ever. And I think many of the best and brightest people working in technology would really like to apply their PhDs in computer science to solving big problems that matter for many people, like carbon capture and removal, like integrating more electricity from renewable sources onto global electric grids, okay? Rather than just enabling us to buy more and more consumer things that get moved around the world. What's the challenge? I think the challenge is we collectively need a buyer who demands enough of these technologies for a grand large-scale environmental problems like climate change. Plenty of entities buy these technologies today to make operations more efficient or effective, whether they're businesses or governments. But there isn't a business named the environment. There isn't a government named the environment. So I think we all need to play a role. It reminds me of the Lorax. I speak for the trees, for the trees have no tones. Now, I don't mean to imply there aren't any existing uses or buyers of these technologies for environmental sustainability. There are increasing examples and they are very impressive. They reveal what's possible, but this needs to become more pervasive. I increasingly see bright intelligent people focused on what it takes to make sure the best tools get applied to today's big environmental problems to help improve this place called planet earth where all of us live. And that's why after majoring on areas of control and prevention, I do think we're entering a new era of innovation. And the imperative climate change, the imperative of climate change will propel it to the mainstream. People on this call are the people who will make this happen. You chose to be here. I don't think we have to wait for policy. Yes, we need research funding. I understand that and I agree with it. But we also have the ability to drive policy through discovery and invention. I'm optimistic, the glass is definitely half full. I wish all of you a most productive session today that the IBM Research Division's future of climate event. And I thank you for your interest in convening with IBM. Thank you, back to you. Thank you so much, Wayne. Our first keynote session is titled the science of our changing climate, getting onto the pathway to sustainability. For that, let me introduce to you Donald Wiebels. Don is a professor of atmospheric science and director of the Center for Urban Resilience and Environmental Sustainability at the University of Illinois. From 2015 to early 2017, Dr. Wiebels was assistant director with the Office of Science and Technology Policy at the Executive Office of the President in Washington, DC where he was the White House expert on climate science. Don, it's a pleasure to have you with us over to you. Thank you, appreciate the introduction. Because I'm a scientist, I'm gonna start out with an overview of the latest science or some of the latest science, but then we'll try to get into more of the policy questions. So could we have the next slide please? So every day, almost every day, we're hearing about some kind of disaster, what I've begun to call unnatural disasters because these are extreme weather events that are happening, whether related events in some cases, that are happening now, that would not have happened in the same way 20, 30 years ago. And it's because of the fact that our climate has changed. So whether we're talking about record wildfires, record heat waves, record droughts, extreme rainfall and associated flooding are very intense hurricanes, including recent ones that have gone from category one to four within a day in the Gulf because of this energy they're able to pick up from the very warm Gulf temperatures. So these are an indicator that climate change is affecting us all and we'll get more into that as we go through this. Next please. So every year there's about somewhere between 12 and 20,000 papers published relating to the Earth's climate and the changes that are occurring in it. And so it's not surprising starting in about 1990 that scientists were asked to assess the state of the science on a regular basis. We do it here in the United States through the National Climate Assessment, which started then. And in 1988, the Intergovernmental Panel on Climate Change was started by the UN and the aim of all these kinds of assessments whether it's those by the National Academy of Sciences are in various countries and so on and so forth. It's always the case that we try to bring together the top scientists to try to understand what is happening to our system. I just led two very recent assessments that are more focused because now we need to be worried about resilience and adaptation and we need to get that very localized. So I led one a few years ago on the Great Lakes and this year we have published one on the effects on the state of Illinois. And some of the things are being done by other groups around the world as we try to focus in on all of the science and what it means to us. Next please. So what do these climate assessments tell us? They tell us our climate is changing, it's happening now, it's happening extremely rapidly. In fact, let me make a comment about that. It's happening about 10 times more rapidly than nature tends to change the climate, Earth's climate system. And that's based on looking back to the end of the last ice age and what has happened since that the climate around the world now is changing much, much more rapidly than either humans or natural systems are used to. And that's what really makes this a problem. It's not just about a small temperature change, it's about very large impacts on our society. And those changes in the energy in the Earth system is resulting in the changes in the severe weather, it's becoming more intense in many cases. Sea levels are rising and the oceans are being affected in various ways. Both of those were probably much more important than looking at just the average temperature change yet we tend to focus on the average temperature change. It's largely happening because of human activities and associated pollution, burning of fossil fuels, land use change, et cetera. And one thing I can say for sure is the climate will continue to change over the coming decades because of what has been happening with human activities and how much that changes really depends on us. Next please. So let's look for it very quickly at the temperature change. So this is globally average to annual average temperature. It's changed about a little over one degree centigrade over the last century. A lot of these graphs I'm gonna show you were done for the US National Climate Assessment. So they're shown in Fahrenheit for that reason. But 2016 was the warmest year in record, followed by 2019, 2020, 2017, 2015. We can safely say that this last decade was the warmest decade on record. And that the decade before that was the warmest decade on record up to that point. And the decade before that was the warmest decade up to that point.  We find that climate changes did occur naturally, but they were very, very small compared to the kind of changes that are happening now. And yet if you look at that record that we get from various proxies of temperature around the world, you can still see things like the medieval warm period where the Vikings were living in southern Greenland. And the Little Ice Age, which was a very important phenomenon in the 1600s, 1700s. Next please. So if we look at the map of the change happening across the planet, we see that the land masses are having the largest changes, and that the polar region is the largest of all, that we're seeing two to three times the change in the polar region that were compared to what is happening elsewhere. The oceans have a very large heat capacity, so they're changing a little bit slower than the land is, but 90% of the energy, 90 plus percent of the energy is ending up in the ocean, and that's having an impact. If you look at this map, everything is warming except for a few places. There's some very minor cooling in Antarctica, but there's an interesting phenomena happening in South of Greenland, and that is because of the changes in the ocean circulation, where the ocean circulation is actually slowing down because of fresh water from all the melting ice in both sea ice and land ice, that is helping slow that ocean down and leading to less changes in circulation such that we actually have a cooling in that one little area. But overall, we're seeing this very significant warming happening around the world. Next please. So I've mentioned extreme events. Heat waves are generally increasing in number of intensity. Cold waves are generally decreasing. Doesn't mean we don't have a cold wave once in a while, and in part those can be related to climate change too because of changes in the jet stream that are occurring, that sometimes they're being extreme cold down things like Texas like we saw this past winter. More precipitation is coming as larger events. I've published papers on that myself and very clearly shows that that is happening and throughout the world and that the models are tending to underestimate actually how much that change is compared to observations. As a result, we're seeing an increased risk of floods in some regions and an increase and we're also seeing an increased intensity of droughts in others where they're not getting as much overall rainfall. And wildfires are becoming a major problem, not only here in the US, particularly in the western half of the US, but also in many other parts of the world. We've got major wildfires this summer in Greece and watch out for what happens in Australia as they enter their summer because they had really major wildfires last summer. And increasing intensity of hurricanes is expected and there's some indications that maybe that's already happening. And I won't talk about tornadoes here, it's a little more complicated. Next please. So one of the ways we know that humans, all of humanity basically to be inspected by climate change is looking at severe weather events. In the US, the National Oceanic Atmospheric Administration is tracking such events since 1980 and find as an ever-increasing number of such events and they do take into account the GDP, et cetera, in doing this. So we're going from a few events to now as many as over 20 events in a single year. And the net cost here to the Americans and people is dramatic. But if we do the same thing globally as has been done by a number of re-insurance and company analyses, we find a very similar conclusion for the rest of the world as well. Next please. Now, what is causing climate change? Many lights of evidence demonstrate that human activities, especially the missions of what are called greenhouse gases, heat-trapping gases like carbon dioxide and methane are primarily responsible for the observed changes in climate. For the period extending over the last century, there are no credible alternative explanations supported by the extent of the observational evidence. It's clearly not the sun. You still see that in media sometimes that, oh, it's just the sun. No, it's not. The measurements clearly show that's not the case. And it's not natural cycles. There is no known natural cycles that can explain what we're observing now. And very, very large changes can only be explained as shown in the graph on the right by the effects of including these changing concentrations, missions and concentrations of these greenhouse gases in the analyses that tried to look at the Earth's climate system. Next please. So to look at the future, scientists have developed a range of scenarios that we tend to look at. They range from a very low scenarios that tried to say, well, we'll do enough to really hold the temperature changed down extensively in the future to what are almost business as usual, continuing in the pathway we have been. We don't wanna call any of these business as usual scenarios, but we do try to look at the situation where maybe we largely keep the overall impacts on climate continuing at a large extent. And that doesn't just require human activity. Some of the feedbacks actually can result in getting us to those very high scenarios. So I maintain that we need to keep looking at the higher scenarios like SPS, I mean, SSP 8.5, which is the highest tier. Next please. So if we look at these range scenarios, these are five of them, the ones that mostly been run by the models, the large climate models that try to analyze all the physics and chemistry and biology that's happening in the Earth's system. The lowest case is 1.9, so SSP 1.9 is really aimed at trying to keep us below 1.5 degrees, which was a goal of the Paris Agreement. And in that case, the range in the models is 1.0 to 1.8 degrees centigrade by 2100. So in the whole idea here is what can we maintain by 21? For 2.0, which was the former UN goal and also is also discussed extensively in the Paris Agreement, gives us an average of about 1.8 degrees from the current models. These are the very latest models from the latest IPCC assessment. And the higher scenarios then go up to 2.7 on average, 3.6 or 4.4. Now those don't sound like a lot. I've had a number of people tell me, oh, who cares if we just have a change of a few degrees? Well, to give you an indication, the last ice age was about five to six degrees centigrade colder than now, 10, 11 degrees Fahrenheit. And that resulted in thousands, the feet of ice above where I'm sitting, and depending on where you're at in the world, it really had a dramatic effect, especially on the Northern Hemisphere. And it was a very different climate than humanity has ever experienced. And it's not all that far different as a cooling relative to this kind of warming. So we have not experienced this kind of level of warming. And it will really play havoc with our society because our society has adapted to the climate we have now or have had in the recent past. Next place. So if we take those scenarios for missions and then we put them into the models so we can look at the global changes. And in this case, rather than looking at the time rate of change of the model, we're just gonna take a look at what if we have, what if you did have a world by 2100 that was 1.5 degrees or two degrees or four degrees and currently we're at one degree. We continue to kind of follow the same pathway that the largest impacts are on land compared to the oceans. And that the largest impacts overall are at high latitudes, especially in the Arctic. And the larger the global change, the larger those impacts will be in those particular areas. Next place. If we look at precipitation, similar kind of following the same path as the way we are currently seeing trends that generally the wetter getting wetter and the drier getting drier. That isn't totally true, but we're seeing significant patterns in the changes in precipitation that are likely to continue as we look towards the future and depending on which of those particular scenarios we follow determines the intensity of that change. Next place. So we're corresponding to those changes in temperature and precipitation or increasing impacts from severe weather, like I mentioned before, where precipitation is like to come is even larger precipitation events when it does rain or snow. At the same time, other areas are gonna see major droughts. And so, and heat waves are gonna continue to increase, et cetera. Next place. The oceans are also changing dramatically. We've already seen an increase in the oceans of ocean sea level rise of about eight inches worldwide. And it's currently at the highest rate of change as it has been in the last 2,800 years based on looking at proxies of ocean levels. Corresponding to that, we're seeing a significant increase in nuisance floods and also we could see an increase so when there's a high tide you get what's called a nuisance flood. We're seeing that becoming much more significant than it's been in the past. By the end of the century, we could see up to another meter of change, somewhere between a half a meter and meter is likely. But we can't for sure say because of things, some things instabilities particularly in Antarctica in the Western Antarctic sheet, ice sheet that couldn't be higher than that. Could be up to two meters almost by the end of the century. And one meter would be devastating. I don't know how humanity would deal with two meters. And at the same time, because that increase in carbon dioxide, we're seeing a certification of the oceans. The oceans becoming less basic, which is resulting in potential impacts on shellfish and other lives and life in the ocean. We don't know the full ramifications of that yet. And that's still developing as a major concern. And we have this changing ocean circulation that I mentioned before. Next place. Sea levels will continue to rise though beyond 2100 and the analysis and the new IPCC assessment, you know, depending on which scenario we follow, because as you know, it could be as much as seven meters by 2300. That's just unfathomable in terms of what that would mean to humanity. Next place. So what can we do? The only three real options at this point, mitigation, taking measures to reduce the emissions that are driving these changes, adaptation, taking measures to reduce the impacts, adverse impacts on our society and on ecosystems, or we can suffer. And right now we're doing a little bit of all three. So to minimize suffering, that can only be achieved by doing a lot of mitigation and a lot of adaptation. There is a fourth possibility and that's to use geoengineering. And I didn't want to get that into that much here, but the removing of carbon from the atmosphere at this point is just too expensive. So that doesn't really seem feasible on a large scale yet. Maybe it will be by the end of the century. In fact, some of the scenarios depend on it. And the other is that we reflect sunlight in various ways or cause a cooling effect in some ways by various options, putting sulfur dioxide in the upper atmosphere example. And we should have like the sulfuric acid or particles would then reflect sunlight. And we really don't know enough about what kind of impacts those kind of geoengineering would have. And I get very worried about trying to play around with Mother Nature in terms of trying to how we solve a problem that we've caused because of our own emissions. Next place. So Paris Agreement was signed in December of 2015 while I was at the White House. And all the nations have joined it. The US withdrew for a while and is now back in it. And it caused for what are called intended nationally determined contributions from each country to towards reducing the emissions. And that's just that it's a contribution. It doesn't mean that there is real action being taken worldwide to prevent the kind of changes that could occur. And right now what is planned up to 2030 is really insufficient to make much of an impact. If we're gonna get down to one and a half degree centigrade or two degrees centigrade, we have to have much larger emission reductions than what that version of the Paris Agreement costs for. I'm hoping that the meeting later this year will start to put us on the pathway to getting the kind of emission reductions that need to really happen. Next place. So I look at the Paris Agreement as establishing a bridge between the policies and the science so that we can have climate neutrality before the end of the century. Next place. So I wanna very quickly look at what other options we have looking forward including ourselves. So as you looked at those scenarios I showed you, we need to get a decrease in emissions by mid-century of 20 to 30 terawatts of energy and yet allow for energy production in the world to increase. And so the low carbon contributions, the renewable emissions as projected right now are just way too small to achieve that. So how can we try to actually change that? And I'm gonna take a look at that in a few minutes. Next place. There's a lot that we can all do personally in terms of reducing those emissions but also probably most important thing we can do is to speak up to our representatives, our policy makers that can really put forward the kind of policy that we need to have and to really have an impact. And I'll leave it there for now. Next place. I do want us to maintain a sense of the hope if we look at the changes that are projected to occur, they're quite depressing. And our future does depend on how we act to limit climate change but I also feel that we can respond to the changes that are occurring.  Next place. We'll quickly look at the energy sources. So as you all know, today's energy is largely based on fossil fuels and we do have some other contributions, nuclear fission, biomass burning, wind power, solar, which is the yellow, which I'm kind of leaving out of this initial discussion, hydro power, et cetera. But the vast majority of our energy comes from fossil fuel burning. Next place. But if we look at the sun and if we were to account for only that we want to account for the amount of sun hitting the solar input affecting land, we still got 28,000 terawatts per year that is available. Now, if we were to take 2% of the land and say, okay, we're gonna use that to create solar power, then we're down to 560 terawatts. And the average efficiency, and this is a good efficiency right now, but my guess is it'll be a lot better in the future. You readily get the 67 terawatts. Now, let's go to the next graph please and look at 2050. So if we look at the energy demand for 2050, something like 30 terawatts, and you look at maximizing all the other potential sources of power besides fossil fuels, you can't reach that. But if you include solar and that 2% land mass converted to solar and 12% efficiency, then you easily can account for that. So it tells us we can solve this problem. Next place. So I'm gonna conclude with that. This is from the IPCC assessment that the climate we experience in the future does depend on our decisions now, but I feel confident that we can solve this. Thank you. Well, thank you very much, Don, for these great insights. And there's quite a few questions actually in the chat. So we're gonna go ahead and actually pose these questions. So I need to read them out from the chat. Were these rapid changes predicted by climate models, say 10 years ago? And could long-term climate projections, even worst case scenario, possibly be under estimating future changes? So yeah, those are both questions that I spent a lot of time on myself. So I started, I first started working on climate change. I first, I started my career looking at the stress rate goes on layer and studying atmospheric chemistry and air quality. I developed one of the very first major air quality models as one of, as well as one of the first major models to study the stratosphere. And the module agreement shows that we as humans can come together to do something. And so I have to go back to the models in the 1990s. We were already showing that humans could have a huge impact on our climate. And I have no it's, or actually media newspaper things where I'm quoted back in the early 1990s saying that we can solve this problem, but we need to get our x-ing gear and get to reducing emissions. It's funny that all these years later, I'm still saying exactly the same thing. So yeah, that aspect of the predictions, the models have greatly improved over that time period. And so there's so much more we understand, but yet the same basic conclusions are still there that we had that our understanding of severe weather is so much better now than it was even 10 years ago. So, but all this has amplified what we were saying there. Okay. Well, Dan, could long-term climate projections, even worst case scenario, possibly be under estimate future changes? This was another question actually. Yeah. So, yeah. So the big concern that I have, and I kind of alluded to this a little bit, I think we're gonna be smart enough to not follow the highest scenario that we're gonna move away, enough away from fossil fuels by mid-century. We probably won't be totally away from fossil fuels, but at least enough away that I don't think we'll follow a high scenario. But my big concern is that the melting of permafrost, the fires that are helping, wildfires occurring in the Arctic tundra, the wildfires that are occurring in the West and in Europe and Australia, and could happen in other parts of the world, could put enough extra carbon back in the atmosphere that we still end up following that high scenario. It's gonna be hard to follow much higher than that highest scenario, but it's possible. And so, yeah, I have great fears about those things, but scientists really tend to be purely conservative, so we don't like talking about our big fears. And so, we're trying to try to not express, we're already expressing enough distress and as it is, so I kind of hesitate to go there. Okay, Tom, well, we have time for one more question. And the question is that you mentioned that the role of methane in climate change, at the same time, there was a lot of discussions about methane and sustainable efforts to control the methane emissions. Would that actually help us? Yeah, I did papers on this almost 20 years ago with one of my students. So, if we control methane, there's some immediate effect in reducing the climate forcing because of the fact that methane has a relatively short lifetime compared to CO2. So, methane lifetime is about 10 years. It's a little more complicated that because of feedbacks in the atmospheric chemistry, but roughly 10 years. Whereas carbon dioxide, the first e-folding lifetime as we talk about it is about 100 years and the second e-folding is thousands of years. So, if you work on methane, you can have an immediate impact. In the long run, you still gotta deal with CO2, but you could get in the short term get a reduction in the forcing, which would help the rate of climate change in the near future. So, there are good reasons for going after methane and in fact, the new IPCC assessment actually does put some emphasis on methane, which I agreed with and I'm happy to see. Ladies and gentlemen, Don Wiebels. I wanna thank you again for taking the time to be with us this morning. Very good insights. Thank you very much. Thank you for being with us. Yes, happy to, thank you. All right, let's now move on to our next keynote, which will be presented by Lux Research. I'm delighted to introduce our next speaker, Arish van Bakkel. Arish is vice president of Lux and leads the energy research team. Arish and his team provide strategic insights in the rapidly changing landscape of energy supply to mobility, residents, and industry. With that, let me hand it over to Arish. Of course, I do the traditional for getting to unmute things. Thank you very much for the kind introduction. Just a question to the technical people. Am I sharing slides or are you? So you are sharing, I believe. Okay, good. So I can control my own slides. So thank you and welcome. And thank you, Don, for a wonderful and pretty scary overview. And that's actually where I want to start, where you left off, right? If we believe all that, and I think the majority of people do take the IPCC reports very seriously, then of course the question is, why don't we do more? This is really serious, isn't it? So why is climate policy so far behind? Why are those nationally defined contributions to the Paris Agreement lagging behind what's actually needed? And how can we change that? And that's what I wanted to talk about. What you'll find is that it has a lot to do with the triple helix or maybe even a different helix. And climate policy is not a matter of governments alone. But first let's take a look at those NDCs, right? The nationally defined contributions or the intended nationally defined contributions, as they're also called sometimes. We've been reading those documents. Not all of them, I'll grant that, but we've been reading the majority of them, looking at what governments actually plan. And if you start reading them, this can be a pretty confusing experience. For example, China writes that it actually intends to increase its carbon emissions. A country like Turkey similarly is going to increase carbon emissions. So that cannot be the right direction, can it? So it looks like countries are all over the place. Until you plot it like this, if you just look at what countries are actually trying to achieve, then what they're actually trying to achieve is two things at once. They're actually trying to achieve, to reduce the carbon intensity of their economy, while at the same time growing their economy. Economic growth is another thing that kind of matters to most countries. And some countries are also at the same time growing their population. So if you take all of that into account and you look at the country GDP per capita and you look at the carbon intensity of the economy, so the amount of kilograms of CO2 that's being emitted per dollar of GDP, then you arrive at a very interesting conclusion, which is that everyone's more or less on the same track at different positions on that same track, but everyone's more or less on the same track. Equally, you can arrive at the conclusion that everyone's on the wrong track. This red line, that's my drawing, that's not a scientific picture here, going through a kind of median of all the numbers, but just showing you that there is a pattern here. But this track doesn't quietly tune at zero. It doesn't get us where we need to be by 2050. A track that would get us there would look much more like this. And as you can see, it goes through zero. We actually need carbon negative technologies. We need to extract carbon from the atmosphere and especially the countries that have a high GDP per capita, the rich countries or countries that are going to be rich 10 or 20 years from now need to be doing that. So there's a big gap between where we are today and where we need to be. And as mentioned already, COP26, the Glasgow conference in November, may well have a good impact on that. So that may be the change that's needed at COP26, but it still begs the question, why did we wait so long after the Paris Agreement to change the plans? Why did we make the wrong plans in the first place? And they're not entirely wrong. They're moving in the right direction, but they're clearly not fast enough. So why is that happening? Well, a lot of things are being done by governments. And if you look at these different levels of carbon intensity, you can kind of make a ranking of the type of measures that would be needed to drive down or that would be optimal to drive down your carbon intensity. If your economy has a very high carbon intensity like Congo, for example, you can see Congo moving along there, then the best thing you can do is focus on energy efficiency. It's a low-cost measure. It's often low-hanging fruits. Just reduce your energy demands, reduce your energy consumption and make everything more efficient. But at some point, if you're driven down your energy intensity of your economy far enough, that will no longer work. You will still need to do energy efficiency, but you need to add other things as well. The next best thing, the next optimal thing is to add renewable energy sources. And Don has shown us the potential of solar energy. There's a lot of potential in wind energy as well. Some areas have great potential in geothermal. There are many options for renewable energy. So as you are going down and passing, let's say that five or four kilograms CO2 per dollar of your GDP type of carbon intensity of your economy, you need to start investing in renewable energy. And in fact, we are seeing that a lot of governments are doing that. India switched from coal-fired power, from investing in coal-fired power and planning to build additional coal-fired power plants to predominantly planning to build solar power, for example. China more or less at that mark of the four or five kilo per dollar. That's more or less the time when China started to switch and invest much more into renewable energy. If you drive the carbon intensity down even further, then even just looking at renewable energy doesn't really help anymore because now you are hitting the limits of a couple of processes in your economy that don't really work with renewable energy or at least don't yet work with renewable energy. For example, you may want to make steel, you may want to make glass or cement or aluminum. Lots of those processes naturally and inevitably at the moment, the way they are designed means that they are going to emit CO2. But you can change those processes and there's a lot of developments going on already and that's where you need to introduce electrification. The first step of electrification in many countries today, of course, is introducing electric vehicles. And you can see that already happening and you can see that countries have now also announced policies to prohibit the sale of non-electric vehicles of internal combustion engine-based vehicles. In some cases as early as 2035. And UK is an example. So, and of course, you need to start investing in carbon capture, utilization as storage. So there's a merit order to these type of investments and the interesting thing is governments are actually acting on all of these different investments, but they're not acting swiftly enough. They could do a lot more or could they? And I think that's an important realization. If you look at regulation, regulation is actually opportunistic. Regulation requires an opportunity to regulate. Let me give you one simple example. Nowadays, there are quite a few countries that have some policy in place either to incentivize the use of electric vehicles or even to completely prohibit the use of internal combustion engine vehicles after a certain date. Not right now, but these are quite drastic and quite ambitious policy measures and they're really quite drastic. You could imagine that people could get angry over those. How come they're in place now? Well, it's because of course Tesla created the opportunity. If there are no credible electric vehicles on sale, if no one can imagine that in 2035 you can actually go to a garage and buy an electric vehicle, then no government is going to publish a policy that is going to prohibit the use of the other type of vehicles. The alternative needs to be there. It needs to be credible in order for regulation to kick in. If there's no opportunity, regulation will not happen because the impact of having no alternative on society is tremendous. How are you going to regulate as a government? How are you going to regulate the steel industry? If there is no credible alternative for making steel, if the only way of making steel is emitting CO2, how are you going to regulate that industry? There's no possibility. It's not even possible to imagine that governments will say, well, we'll just not produce steel anymore. That's not an option. You have to create the opportunity. And that's exactly also where the opportunity for industry lies. It means that if you're investing in technologies that maybe are too expensive today or maybe are a little bit out of the ordinary, like Tesla, when they were building their first electric vehicles, they were ridiculed by the industry. But they created the opportunity and then things move along. So if it's the industry's job to create the opportunity, then can you just create any opportunity? Certainly not. What you have to do is you have to work in the triple helix. And Don showed his slides about academia. The triple helix is the coordination of innovation, activities between universities or academia at large, industry and government. So government can regulate, government can create conditions under which new innovations can flourish and can be deployed. Government can also invest in universities, for example. University can create both the knowledge, the kind of new knowledge that's needed to develop new technology, but also feed and inform policy. And we've seen an excellent example of that by the previous speaker, by Don, where the IPCC is really having a tremendous influence on policy. An industry, of course, needs to align with what universities and governments are doing and needs to start producing in accordance with that's general trends. And in fact, nowadays, even a triple helix has proven to be a very strong innovation theory, in particular for system changes, for transformational changes in society. I think nowadays, you actually need to talk about the quad helix because what we've seen now is that civil society is very active indeed and really keeping both government and industry very honest about what they're actually doing about the problem. And one example, of course, which caught a lot of attention here is the fact that Shell got taken to court by a group of NGOs, actually. And the court actually ruled that Shell was not doing enough against climate change. And this is a very interesting case because it also, it shows a perhaps unexpected side effect of the Paris Agreement. So let's linger a little bit and see what happened here, what the court actually ruled. Basically, and this is called the so-called cellar hatch principle. So if you have a cellar hatch out on the street and you leave it open and you don't take any precautions so that people don't fall into it and then someone trips and falls into it and hurts his leg, maybe breaks his leg or something. In most countries, you'll be liable. And why will you be liable? Not because there's a specific law saying it's prohibited to open your cellar hatch or that opens out on the street. You'll be liable because you didn't take a precaution that you could have expected to be normal. A precaution that everyone knows you should take like just putting a sign next to your cellar hatch. Watch out, you can follow it. This principle was now applied to Shell through the Paris Agreement. So the court ruled Shell is not doing enough against climate change. This is evidently dangerous. And we have a common understanding about what is doing enough about climate change. We have a common understanding about what good care against climate change looks like. And that common understanding, in fact, is the Paris Agreement. You cannot get it much more common than that. Almost every country in the world has signed the Paris Agreement. So I'd say it's common and the judge actually did say it's common. So now the Paris Agreement is actually affecting industrial policy and that's the action of the Quad Helix. So let me finish by sharing some examples of creating opportunities and creating opportunities. And thereby in the Quad Helix or in the Triple Helix kind of proactively anticipating future policy changes or even creating the opportunity for future policy changes so that your investment even though it's unprofitable today is going to start your new business tomorrow because you are aligned and you're actually enabling governments to act faster towards climate change. Here's one example about carbon pricing. So carbon pricing, as you can see today, is not too big and I do apologize. My PowerPoint has thrown me a curveball here. Series one is the carbon price but Series two is anyone within the European training scheme. So carbon pricing today, just the level set is roughly $130 per ton in a country like Sweden, but in most countries it hoovers around between $30 and $50 per ton perhaps. Now the ETS, for example, is a system where the EU is priming the system every year with so-called carbon allowances and if you are a certain type of company, basically a company that has big enough CO2 emissions, you need allowances in order to emit CO2. So you start the year with zero allowances for that year but then the EU will release allowances and will auction allowances to you which is priming the system and at the moment this year there are 38 million allowances. So that's an allowance for 38 million tons of CO2 to be emitted.  So if you just want to do a bilateral deal, one-on-one deal with a neighboring company, you can do that. If you want to auction them off you've got some allowances from an auction, you want to sell some allowances maybe because your production got more energy efficient this year so you don't need everything that you bought initially so maybe you want to sell some. You can do all of that in any way you like and there's a registry that keeps track of it. And at the end of the year, the registry will look how much CO2 you actually emitted that year, that's something that you will need to submit to the registry of course with independent verification. The registry will look at the allowances that you have, all of the allowances that the allowances are matched with your emission. If you have more allowances than you actually emitted then the surplus is just gone, it disappears. If you have not enough allowances then you have to pay a fine and the fine currently is 100 euro per tonne so that puts a ceiling to the CO2 price as well. Today, CO2 prices are around 55 euro per tonne in this system and what will happen and this is in the triple helix what is the general expectation in the system. The general expectation is that EU will start to shrink at a longer certain path, this 38 million. So next year there will be less, the year after there will be even less and so forth. And that of course should drive prices up again up until the ceiling of 100 euro per tonne unless that ceiling is changed at some point. So what does it mean for businesses? Well, we looked at that and we identified the so-called critical carbon price. What is a critical carbon price? Well, if you're a business and part of your production means that you're emitting CO2 then today you probably have a certain margin, a certain profit that you make from your operations and that margin and profit will diminish as you have to pay for emitting carbon. So you can imagine that as the price of emitting carbon is going to increase your profit is going to decrease and there will be a price where your profit will have gone completely. And that's what we call the critical carbon price and that's what you can see on the horizontal axis here. And on the vertical axis we put the cash flow, the cash position essentially for companies as an indication of how easy it would be for companies to invest their way out of a predicament, out of for example, emitting too much carbon. You can see all the different industry sectors here essentially anyone who's in this box and in this box you have a lot of steel companies, you have a lot of aluminum companies, couple of fertilizer companies, the occasional utility, not much. So there's one or two utilities that predominantly own qualified power, they're in trouble and one or two oil and gas companies. Those companies are extremely vulnerable to CO2 pricing and they need to act now. And the other thing that's important to note about those companies is they cannot rely on carbon capture and storage. They need to truly decarbonize their process because even carbon capture and storage is too expensive for them. And that's why we put this line here at $200, that's roughly beyond the $200 critical carbon price. Those companies can afford carbon capture and storage. Whether that's desirable or whether governments will permit it, that's an entirely different story and I won't go into that today. But they have a way out, they can tell themselves at least we don't need to decarbonize, we just need to build a carbon capture unit. But these companies cannot. And that's why you see a lot of those companies acting now, so you see steel companies are very actively investing in hydrogen green hydrogen in order to completely replace their blast furnaces. Swedish steel is demonstrating a unit today that will turn iron ore into steel without using any coax or anything carbon related just using hydrogen and in this case green hydrogen. Fertilizer companies likewise are investing to get away from emitting carbon and they're looking to invest in green hydrogen to produce green fertilizer. Aluminum companies are looking to get away from carbon-rich sources of electricity and maybe cosides with hydropower or cosides with geothermal power or maybe even buy green electricity or green credits or even carbon offsets. So I won't talk about oil and gas companies that that's an entirely different story. Of course, they have some other issues in their business model in terms of climate change, of course. So you can see there's a group of companies that really has an urgent need that cannot afford to switch to carbon capture. Cement companies is another one where cement companies are actively working to reabsorb CO2 that they emitted during the production of cement. And it's inevitable that they cannot do what the steel companies are doing because the chemistry of cement-making prescribes that you will emit CO2. If you don't emit CO2, you're not making cement, period. So no cement if you're not making CO2, but you can reabsorb the CO2 in the cement. And so they're trying to do that. So all of these companies are creating opportunities. Now, there's a necessity for them to create opportunities clearly because they can see that already at current carbon pricing, they have an issue. Here's another example where a company is creating an opportunity for a longer-term necessity. And this is about synthetic aviation fuel. So again, we know the policy. The policy backdrop is we nowadays really like electric vehicles. And again, you can have a whole debate about batteries and recycling and lithium and all that. But let's say we really like electric vehicles. What it means is in about 20 years, a whole lot less people will be buying diesel and gasoline, which means that a whole lot of refineries will really be in trouble, which means that those refineries will no longer be producing gasoline and diesel, but they will also no longer be producing aviation fuel, which is an issue because the airplane you buy today as an airline will still hopefully be operational 20 years from now or even 30 years from now. So that thing needs aviation fuel. Where are you gonna get it? Well, here's a company called Nordic Blue Crews. They awarded a front-end engineering and design study. And now that's really important to note because a front-end engineering and design study is not cheap. A front-end engineering and design study will cost about 10% of the investment that you eventually have to make into a full-scale factory. So this is a significant investment. They're actually doing stuff. They're spending real money and a lot of it. So they awarded a contract to Acre Solutions, engineering company in May this year, to design a unit. And that unit will use direct air capture. So we'll grab CO2 from the air to make aviation fuel by combining it with hydrogen. And the hydrogen will be produced from hydro power. So it's renewable hydrogen from renewable electricity. Now, if you look at that, that's just way too expensive. There's no sane airline is going to use this fuel because that fuel is going to be so much more expensive than the current airline fuel. On the other hand, if this works, it shows governments and that's where you get into the dense. That's where you get into the dense and the triple helix. It shows government that there is a possibility to outlaw aviation fuel from refineries. So in top of outlawing internal combustion engine vehicles, governments could decide to also require that airlines are using this synthetic fuel, this carbon neutral fuel. And they're not doing it today because it doesn't exist. How can you prescribe? How can you insist that companies are using something that doesn't exist? But once it exists, they could enforce it, of course. Last example, looking at the carbon capture and storage projects in the UK. So here, these are just a couple of the projects because there are more projects, but I don't have, I don't want to talk about all of them. I want to talk about these three. This is a consortium of companies. You can see BP is there, E&I, Equinor, the Norwegian Oil Company, Total Energy, formerly known as Total, but they are switching towards, away from oil towards energy. Shell was there and UK National Grid, which is the operator of the energy infrastructure in the UK. So they're all there and they're looking to build three major infrastructure projects. When I say major, you should imagine that the eventual investment in this project, in the combination of these projects, could add up to $40 billion. That's major, but it's still not as major as what Exxon has been suggesting lately, which is that the US companies plus government should be investing $100 billion in the used and canal area for building a similar infrastructure. Just a bit bigger. So what are they going to do? They're going to build a 10 million ton per year CO2 pipeline so they can move CO2 around. They're going to build a 2.1 gigawatt power plant with carbon capture. And that power plant will be the launching customer of the CO2 pipeline. So we'll use about 10% of the pipeline, maybe 15% if they have a very productive year. Same thing here. So this is T side, then there's on the Humber side. They're going to build an even bigger pipeline. They're going to build a so-called blue hydrogen production facility, which turns natural gas into hydrogen and then stores the CO2. That is the result of that production. And they're going to do bioenergy, carbon capture and storage at an existing power plant there, which is owned by Drax. So that is burning biomass to generate electricity and then storing the CO2. So that's an actual carbon negative technology. Trees are growing, the trees are absorbing CO2. The absorbed CO2 is released if you burn the biomass for energy, but the released CO2 is then not emitted into the atmosphere, it's actually stored underground. So you're taking CO2 out of the system. And to top it all, they're going to build an infrastructure on the North Sea because after all, all of this CO2 needs to make it into those reservoirs, needs to be stored somewhere. And the idea is to store it in depleted gas wells. Again, these people are doing real stuff. They're doing a feed study. They're not yet building, but they're doing a front-end engineering and design study. And the front-end engineering design alone is costing about $318 million. And there's some government support there. It's 30% government support, but it's 70% funded by these companies. Now, why is this a good idea? This is a losing business proposition because everyone agrees that moving CO2 around like this, capturing and storing CO2 like this will cost roughly $80 to $90 per ton. And the current price of emitting CO2 is $50 per ton. So nobody's gonna pay for this, right? Who would want to pay $30 extra to solve a problem that you can solve at a lower price? Why would businesses do that? Well, they would because they anticipate that the CO2 prices will increase. And actually the UK government intends to increase CO2 prices even faster than the EU. They want to be ahead of the EU. That's one of the perks of having Brexit. But also the UK government has announced a substantial plan to convert the entire UK gas grid to hydrogen. So they're going to connect every home in the UK to hydrogen and the hydrogen that they need for that will at least initially, and initially means for the next 30 or 40 years be blue hydrogen. So these companies also know that this will create a huge demand for carbon capture and storage. So if they trust this resolve of the UK government, then their current investment, even though it is a foolish investment at the moment, is going to be a really smart investment in the near future. And that's why they're doing it. And it also works the other way around. And this is the dense again. It also means that the UK government is emboldened in their initiative to change the entire gas grid to hydrogen because they know that companies are working to create the necessary infrastructure to actually make that happen. So with that, there's a couple of summary notes. You need to invest proactively. And if you're a business, you will also need to take investment decisions into something that you would never normally, according to your own investment norms, invest in. You will need to fund losing business cases. But you'll do that because you can prove or assume, or at least be reasonably certain that that currently losing business case will be profitable in the near future. And to do that properly and to have that confidence, there's a dense between governments and industry and academia. And so you have to be at the dense, go to the prom. You have to really be there and participate in it, which means a lot of talking between industry and governments as well. And everyone needs to be participating in that and exchanging ideas and get a reasonable confidence in the direction we're all going. And then finally, the quad helix is really important. And that's not a triple, that's the quad helix. So there are NGOs, there is civil society that is chiming in right now. And you need to listen to them and you may well end up in court like Sheldit. And that is actually also another way of emboldening and reinforcing that strategy and making sure that you are certain that the business case that you are reluctant to invest in today because you are going, everything shows that you will lose money on it, is actually the right path to take for the future. So I'll leave you with that and I'm of course open to questions. Thank you. Back to you, Peter. Thank you so much, Arish. Thank you for this great insight and great presentation. We do have a question in the chat. So let me ask you this question right away. It says here, do government policies also talk about training and incentivizing the workforce to help them gain relevant skills to pivot to these newer industry trends? Can you share any examples? Yeah, so that's a very good question and it's, I don't know how to ask the question but it's very relevant indeed. And let me give you two examples. Now, first of all, training, yes. So governments need to start changing their universities as well. One example is a big investment in the EU right now to boost the electrochemical knowledge of universities. So we need more electrochemistry professors, essentially. And that will trickle down into the rest of the workforce as well. So you'll have that at university levels but then also at polytechnics, et cetera. Why is this really important? Because employment is another big limit, is imposing a huge break on regulation. And there's two examples here. One is Poland. Poland in the EU has been resisting the Green Deal a lot. Is that because the Polish are somehow immune to climate change or something like that or maybe they like it a bit warm in their country? No, the problem there is Poland has still a substantial reliance on coal mining. And if we're going to change that within less than a generation, within 15 years, and that means you're putting all of those people out of work, and that's a big problem. And that's a big problem that one should not neglect. We need a solution for that problem. So Poland is willing to move if they can figure out what all of those people are going to do. And that's the problem we're trying to solve right now. You need to have those other skills and you need to identify what kind of retraining you can provide to those people. Exactly the same story is happening in Canada. And I actually was at the Berlin energy transition dialogue earlier this year, where a representative of the Canadian government actually made that very remark and said, look, when the cult was disappearing from the Atlantic, I saw that all of the fishermen were being put out of business. And it was no fun. So now if we're going to switch away from oil, we'll see the same thing again. So now all the fishermen that became workers in the oil industry are going to be put out of business. And I don't want that. So I need to have something else to offer them. I need to be able to retrain them before I can start really putting the heat on for the oil industry and changing that industry. So this is really important. Governments are working on it. I think they're a little bit behind. We need to, again, if there's no opportunity, if we don't know what to train those people for, we're kind of stalled. Again, we need companies to move in and say, hey, I could use those people because if I can train them to do this thing, build solar panels, whatever, then this would be really good. So already with all the initiatives that we are started and all the efforts that the governments are making, we really need to also to consider on what will be the next step and what type of education we'll have to provide to them. Well, I want to thank you once again. This is all the time we have, unfortunately. Again, Adish, thank you very much for being here with us today. Much appreciated. All right, thank you for having me. Thank you. Okay, so now we're going to go for a little break. We're going to take a five-minute break and we will continue with our next keynote speakers. Thank you. Welcome back. I'd like to just refer back to day one when Solomon was talking about the accelerated discovery for climate. Now we saw that we have this cycle where we learn from what we've learned, we build on hypotheses, which bring us to models, which allow us then to iterate. And this is a cycle that goes on. Now, we've looked at two areas in day one and day two, which one was on mitigation, where we looked at the discovery for carbon capture and carbon performance, which actually leads us then to applications that we can apply on that. We also looked at how we can do the adaptation of it. And here we looked at analytics on the climate impact, the climate informatics and climate-aware applications. Now, this leads us very nicely into our next session, which will talk about carbon-performing innovations, which is presented by a team of climate researchers we heard on day one with Shantanu. So I would like to hand it over now for the next presentation to Shantanu. My name is Shantanu Gorkulay and I'm a senior manager and theme lead for IBM Research's Future of Climate Initiative. Today, I will talk to you about enterprise carbon performance. Climate change is turning out to have a double-vammy effect on enterprises. Enterprises cause climate change primarily due to their greenhouse gas emissions, more generally called just carbon emissions, but they're also affected by climate change when severe extreme weather events happen. The two main technological strategies for combating climate change are mitigation and adaptation. In our talk today, we will focus on mitigation. If you look at carbon responsibility and the aim that organizations are setting themselves to decarbonize and reach net zero emissions in say 10 years time or 20 years time based on the complexity of the organization, this has become a movement all over the world. There is increasing consumer, regulatory and investor pressure to act on enterprises now. When I say enterprises, I'm covering built infrastructure, assets and the supply chains that these enterprises are part of and responsible for. Look at some of these announcements from the EU, which is for example, phasing out palm oil from transport fuels.  Many companies are also being put on notice and being asked to pull up their socks when it comes to decarbonization. Very big enterprises like Walmart have started Project Gigaton which aims to eliminate one gigaton of greenhouse gas emissions from their supply chains by 2030. What are some of the main questions that these enterprises across industries are worrying about when it comes to decarbonization? First, they're asking, how do I accurately report my emissions? How do I incentivize my vendors, partners and suppliers to repair their own emissions? And how do I for example, bridge the carbon level gap between my suppliers and my consumers? Let us break carbon emissions down in terms of the organization's carbon footprint. This is something which is very well understood but it is worth spending a few seconds on. An organization's carbon footprint can be broken down into what are called three scopes. This is as per the greenhouse gas protocols definition that we follow and we implement throughout the rest of our work. Scope one is the direct emissions that a enterprise is responsible for by assets, vehicles, you actually own by the enterprise. For example, these are fugitive emissions, these are mobile combustion emissions and stationary emissions. Next is scope three. These are indirect emissions of the enterprise which come from the purchase and use of electricity, steam for heating and cooling purposes, whether in your office buildings or in your factories and process plants, et cetera. Finally, scope three are the indirect emissions that a company is responsible for but which occur outside your organization's boundary. These are typically supply chain emissions from your vendors and partners and suppliers which could be upstream or downstream from you. Scope one and scope two are the two kinds of emissions which are reliably measured and can be inferred and calculated based on primary data which is typically available in building management systems, ERP systems, et cetera. Scope three is a very hard beast because all of these emissions are occurring outside your organizational boundary and you typically don't have control over the other players in the supply chain whether for competitive reasons or otherwise. Nonetheless, there are a few subcategories of scope three emissions where some reliability and some kind of estimation of emissions can be accurately done. At the end of the day, the scope one, scope two and scope three emissions are reported to organizations like the CDP or the carbon disclosure project and pretty much 90% plus of enterprises have been doing this reporting now over the last few years and this is only going to accelerate over time. So how do we go from carbon accounting to carbon performance, which is what we are really here to talk about today? We can look at an enterprise or we can look at the business processes that the enterprise engages in. Let us look at this three layer stack diagram from top to bottom. At the top, you have the enterprise scale, enterprise reporting and these goal settings of carbon emissions, right? Reaching net zero by say 2030 and things like that. One level below are the organizational units where the reporting rollups happen and the finance and execution and the strategies are set in those organization units. At the bottom, you have the base business processes which is your built infrastructure, your assets. These could be your factories, your machines, your equipments and finally the supply chains that you operate in. These could be transport networks, logistics networks. These could be the flow of inventory and spare parts across the supply chain all the way to end consumer depending on the industry that you may be in. If you look at the same diagram bottom up, you can see that you can start with a process-centric view and aggregate it upwards towards your enterprise, scope one, scope two and scope three emissions, whether for reporting purposes or to take decisions around carbon optimization, carbon reduction and carbon performance. So as over the next few years, business performance will help companies grow, change in size and shape and footprint. So also accounting and carbon reporting go hand in hand with that, which is what we call carbon performance to say that it's not just important to accurately account for your carbon emissions but also you need to optimize it, reduce it and eventually be carbon performance in all your applications, your supply chains, your data centers, et cetera. So the cycle of carbon emissions reporting and performance is that first you gather the data, you collect it from your primary data systems wherever you can or you estimate it using averages but this needs to be done transparently. You report this, you benchmark it against your others in the industry and then you try to optimize it by running programs for optimizing your building energy consumption or purchasing more renewable energy, et cetera. And then you go back to the loop of gather, report, benchmark and optimize. Let us see an example of this three layer diagram where you can start at an enterprise level or at a business process level and either go up to down or down to up. In this case, let us start at the bottom and let us look at one specific category of an enterprise's emissions, which is for example, say a vehicle fleet that it owns. So this could be a logistics company or otherwise. So in a vehicle fleet, the primary greenhouse gas emissions will come from the burning of fuel, which is used and these vehicles are then used to transport people, equipment, finished goods, et cetera. So the primary data in this case is going to be the amount of fuel consumed, the distance traveled in miles depending on the data availability, et cetera. Now, if this is there at a fleet level and you aggregate it upwards, you can then start identifying hotspots and see whether it is maybe the kind of fuel used and this of course varies from country to country. As you aggregate and do it at the enterprise level, you can immediately start identifying these hotspots and those will become your targets for investment where you may choose to purchase cleaner fuel and things like that. At the end, all of it rolls up at the top layer at your enterprise scale, maybe there's a dashboard or there's a way where you are kind of, this will be your scope on emissions. In some cases it could be scope three emissions, which is your vehicle fleet and how is that contributing to your overall organizational footprint and do you need to do something about it and all those kinds of things. So with this example pattern, this can actually be used in other kinds of asset classes. So for example, the retail industry or the supermarket industry, for example, in the US has hundreds or maybe thousands of stores and there are refrigerators in the stores which are responsible for fugitive emissions. So the usage of refrigerants, et cetera, leaks some very potent greenhouse gases into the atmosphere which are a few hundred to a few thousand times more potent than carbon dioxide in their global warming potential as it is called. So this example of having this enterprise scale view, operational view and business process view with this example of vehicle fleets, you can extend it to say refrigerants, you can extend it to built infrastructure, you can extend it to energy consumption, electricity consumption across say your, how many of our office buildings you have, et cetera. So this drives insight and action across the organization and you can take this view scope one at a time, scope two at a time, scope three at a time or you can slice and dice it through your asset classes as per this example. Next, let us look at the technical strategy that we have been developing from a carbon performance perspective. Keep the previous example in mind and we'll build up some more interesting technical strategies around that. So we have a few building blocks at the bottom of this slide which are our carbon accounting APIs. This is table stakes and this is an implementation of the greenhouse gas protocol which as I mentioned, pretty much is the reporting standard that 90 plus percent of companies over the world use. So the carbon accounting APIs that we have our own custom implementation of contains scope one direct commissions, scope two indirect commissions, scope three indirect commissions, but not all scope three, we limit to the travel and transport kind of categories. We obviously use reference data from IPCC, IEA, EPA, et cetera, these kind of regulatory government trusted sources. So these carbon accounting APIs are not just a simple calculator. They have a lot of data quality checks and AI built into it which can figure out missing data and improve the data quality and make the carbon accounting more accurate. And then that becomes a building block which we then feed into the next layer which is the AI driven data augmentation. Obviously, along with the carbon accounting APIs, another important building block for us is geospatial and weather data which again we have a large depository and an engine which can ingest it at scale and make it a scalably available for various applications. The next layer on top is as I was talking about the data quality enhancement and in some cases when we do GHG downscaling using spatio temporal data, say remote sensing satellite data, et cetera, there's a lot of AI driven data augmentation that we do in this second layer. Next comes a differentiated technology layer where we have three parts to it, but today I will talk specifically about emission hotspot identification which is really anomaly detection problem and I will talk about building model ensembles for greenhouse gas emissions across space and time resolutions. Let's look at these examples one by one. The next layer on top is the differentiated technology layer where we are using multi-objective optimization with explicit carbon constraints in addition to monetary and other cost constraints which are typically in optimization problems around supply chains and asset management. We are doing emission hotspot identification using AI algorithms across assets, operations, parts of your supply chain and infrastructure. And we are also building a model ensemble for accurately estimating GHG emissions across say the energy and agriculture industries which are responsible for half of global emissions and across the spectrum and help you choose an operating point across the spectrum of data availability and accuracy. All of this technology helps us go after use cases and offerings around enterprise level carbon accounting and reporting, carbon optimized operations, carbon aware inventory optimization and asset carbon performance including your data centers and your cloud tenants as you will see presently. Let us look at some carbon performance supply chain applications. So let us for example see order fulfillment and inventory optimization, classical supply chain operational problems and we are seeing how we can explicitly account for your carbon emission savings today and help reduce them and optimize them further by introducing a knob around carbon emissions and we have some very interesting early results in this space. On the left you see order fulfillment and the order management problem which is that we buy say t-shirts and shoes from a store and through e-commerce and they are fulfilled from maybe retail stores or distribution centers or warehouses in various locations and the problem to solve there the optimization problem to solve there is how to efficiently at least lowest cost get them over to the customer within the specified time periods. We are finding that by adding explicit carbon emissions which accounts for whether the motor transport is truck or air and so on how can you actually give an optimization knob and a choice to a customer to say that they are willing to wait for another day but they would like to reduce carbon emissions while also ensuring that the retailer and the e-commerce company meets their carbon emission SLAs while keeping customers happy. On the right hand side you see inventory optimization where there are these large heavy industries for example have a lot of assets and spare parts in their inventories and warehouses as they get used beyond a particular reorder point a certain reorder quantity needs to be ordered so that these are replenished and they will come over various modes of transport traveling various distances but what we are now finding as a very interesting new use case is that if you start explicitly accounting for and optimizing for carbon emissions through the emissions of the vehicle fleet as we have already seen or the emissions of the act of storing inventory in a warehouse all of that can also start explicitly be optimized at for a very delta additional cost as the case may be. Next, let us take a look at another interesting emerging workload or business process for enterprise level carbon accounting and performance. Cloud tenant carbon accounting has become an important issue as more and more enterprises across industries are moving to the cloud for their IT workloads whether it be public cloud, private cloud or hybrid cloud and there are some very specific cloud characteristics that we are working on to extend the GHG protocols ICT guidance to account for multiple tenants multiple services, resource sharing all of that which happens say within a data center where of course scope to emissions are well understood but even cloud tenant carbon accounting the goals that we have set for ourselves are being able to calculate the energy and the carbon footprint per tenant per application per service and this should be programmable and dynamic with insight and ability to optimize and improve your carbon performance over time. Our vision is an environment aware hybrid cloud. So on the left you see that today the hybrid cloud is heterogeneous distributed and open and on the extreme right hand side you see that our vision is to make it environment aware using technology innovation that I'm briefly mentioning in the middle which is to have carbon aware controllers which can dispatch jobs across data centers based on renewable energy, carbon intensity, carbon footprint coordinating the placement of VMs and containers to optimize the utilization and the PUE which is like get the same performance for less carbon footprint and having energy efficient data centers by using AI techniques to deploy intelligent dynamic cooling heat extraction and offsetting and similar technologies. One of the things that also we have started building is tools and services for quantification transformation and migration practices for helping clients move to the cloud in the first place again across the entire gamut of hybrid cloud. With that I will pause here today and I'll be happy to take questions and thank you for the opportunity to talk to you it has been a great pleasure. Thank you once again. Thank you so much Shantanu. Now let's hear from the rest of the team with Stacey, Matthias and Rodrigo who will be talking about accelerating the discovery of carbon materials. As we have discussed over the past couple of days even if we could stop emitting carbon dioxide and other greenhouse gases today the planet will continue to warm for at least another decade because of the carbon dioxide that is already there. To avoid the worst outcomes of a changing climate we need to combine an efficient local carbon capture process with a global initiative to store it for the long term. One of the most promising approaches is storing carbon dioxide in geological formations. Governments and businesses are called to action for jointly exploring the best geological storage conditions. Potential for carbon dioxide storage varies widely depending on geolocation and reservoir conditions. So better scientific discovery tools are needed to optimize carbon dioxide sequestration based on the existing geophysical conditions. At IVM research we have developed discovery technology for exploring carbon dioxide storage based on simulation of fluid flow in rock and microscopic scales. It is at these small length scales where the physical and chemical processes of carbon dioxide trapping and mineralization actually occur. With a better sequestration science at the poor scale of geological formations it will be possible to design and optimize storage methods before they are applied at large scale. This approach will save time and money and greatly improve our chances to convert and store carbon dioxide efficiently, safely and for the long term. Rodrigo Neumann from our research lab in Rio de Janeiro, Brazil will show you how we can investigate carbon dioxide underground storage with our scientific discovery and simulation tools. Today I'll be discussing the geological storage of carbon dioxide which prevents it from being released into the atmosphere. We can store CO2 by injecting it into abandoned oil and gas reservoirs, selling aquifers and other rock formations or use it in industrial processes that have a net negative carbon footprint meaning that they store more CO2 than they release. There are several microscopic mechanisms which we can exploit to trap CO2 inside the geological formation. In structural trapping, CO2 is injected below an impergable capped rock layer that prevents it from floating up to the surface and escaping into the atmosphere. Residual trapping occurs when CO2 manages to permeate the rock but it remains trapped as isolated bubbles. The third mechanism is solubility trap and is driven by the fact that when CO2 dissolves in water it becomes denser than pure water and therefore sinks below the surface. Finally, mineral trapping occurs when CO2 is dissolved in water and reacts with other minerals to form carbonates which can store CO2 indefinitely. Mineral trapping is the most stable geological storage mechanism for CO2. Our contribution comes in the form of a cloud-based prototype that lets you simulate the interactions between the relevant materials and accelerate the discovery of new CO2 storage strategies. We simulate rocks and other materials down to the level of individual pores because that is the scale in which the fundamental physical and chemical phenomena take place. We start by taking a rock sample like this one and performing an x-ray micro-tomography to generate a three-dimensional image of the pore space. This shows all the pores, channels and pockets within the rock on a microscopic scale. We then upload this micro-tomography image to our platform alongside image properties such as size and resolution. In this case, we are using a carbonate rock sample which is 100 by 100 by 400 voxels in size and each voxel corresponds to a four micron cube. Once we load this image onto our platform, we can visually inspect the rock microstructure here represented in grayscale levels. Darker grays represent the pore space while lighter grays represent a solid rock. You can also use the distribution of grayscale levels to help you pick the algorithm that will interpret what is pore and what is rock. This is called image segmentation. Once the image is fully segmented into pore showing black and rock showing white, we launch an algorithm that extracts a capillary network representation of the pore space. Our tool shows the pore structure color coded by the capillary diameters so the purples are narrower channels and the yellows are wider channels. The tool also shows relevant information like the distribution of capillary diameters across a rock which can be useful for understanding whether this rock is a good candidate for CO2 storage. This connected network of capillaries is the fundamental geometric representation on top of which we deploy the physics simulations. The physics simulation takes as input the properties of the fluid and the driving forces that are used to impose flow. In this case, we are simulating CO2 subject to a pressure equivalent to hundreds of atmospheres. Once the simulations are completed, we can visualize and compare the pressure fields, the flow rates and flow speeds at each point inside the rock. This allows us to find the most favorable points to inject carbon force sequestration. We have extended this methodology to enable the simulation of two fluids such as water being pushed by supercritical CO2 as you see in the video. We are also incorporating the effects of chemical reactions that can alter the pore structure to simulate the mineral carbonation process. With that, we will be able to simulate the full range of physical and chemical processes that can enhance CO2 geological storage and accelerate the screening of mineralization additives. This simulation ability will allow users to optimize the CO2 storage efficiency. If you want to test the tool with your own rock data, please reach out to us. Thank you so much, team, for that great presentation and very good demo. So we have now our experts with us to take any questions. So I encourage you to pose your questions in the chat. In the meantime, I have a question. And the question is, what is the importance of materials discovery in the context of carbon capture? I can take that one. So imagine that you're pumping tons and tons of CO2 down the reservoir and you want it to be stored there as fast as possible for as long as possible and as safely as possible. So if you have a material, an additive, that is able to accelerate the reactions that turn CO2 into the mineral, you can change what nature would take a couple of years to a couple of months or maybe even shorter in order to accelerate the storage and increase the safety. So that's where material discovery comes in, selecting the additives that can shorten the timescale for the most secure kind of CO2 storage. If I can add to that too, I think the capture portion, there's a lot of opportunity for materials discovery there as well. So there are a number of different technologies that can be used for carbon capture from amine-based solvents to solid sorbents like metal organic frameworks and zeolites to membranes, which can separate out CO2. The only one that's really been demonstrated at scale are amine solvents, which are not a sophisticated technology to put it lightly and they come with significant challenges, which include things like high energy penalties for generating them, they're caustic, they degrade readily over time, usually due to oxidation and so there hasn't been an application of AI to accelerate discovery of these and we've reached a point in time now where time is of the essence, we have to do it quickly. We can't rely on typical discovery times on the order of decades. So I think now is really a good opportunity for us to apply these technologies and this is a space where there is urgency of time to come up with new technologies that can outperform what's there today. The previous speaker talked about sort of threading that needle of, it costs $50 per ton to release CO2 into the atmosphere, we need to get the cost of storage down to be competitive and this is one way to do that. That's great. Another question is around AI systems and the question is can AI systems suggest solutions far faster than that can be experimentally tested and how do you choose what predictions are worth experimentally verifying? It's a very good question. That's an excellent question. So I'm happy to take this one. It's one of like the biggest challenges that we are having today within the thousands and millions of materials candidates to select which are actually worth our while because experimental confirmation is very time consuming and expensive. So we are using AI in the research that we are doing. So we are the best customers as scientists for AI applications and system in order to help us narrowing down the number of potential candidates and materials to get the best out of it. So for the optimization and the screening, AI is fundamental importance and for us doing the research, creating these systems is as much important as for the application at scale. Great answer. Thank you, Matthias. Well, I keep repeating myself but I encourage everybody to ask your questions in the chat. Our experts will be there to answer them. Right now, that's all the time we have for the questions. So I want to thank the team again. Thank you so much. Stacy, Matthias and Rodrigo for being with us today. Thank you so much. All right. So now let's move on to our next session. Our next speaker is Comey Veldemariam. Comey is a technology leader and innovator with broad concept to research to market experience acquired through numerous advances in technology research projects across systems, data and analytics, ecosystems, artificial intelligence, supply chains, healthcare, climate change and related areas.  Thank you, Heg. Thank you for a nice introduction. So again, I'm Comey. So I'm part of the Climate and Systems Research Leadership Team at IBM Research. So today I will just talk specifically on AI and cloud-based technologies for climate risk and impact and modern prediction in more context of the public sector. So if you go to the next slide, please. So by now, I think I don't need to repeat again. You heard enough about the warming planet due to the climate change and also its visible consequences that continued to increase the intensity and frequency of the climate hazards. And on top, you see some examples, the heat wave, followed by the wildfire, et cetera. These are really sort of that creating direct impact in our communities, in our infrastructure, in our food systems and supply chain. So just if you look at them, this chart really, what they see, the chart shows the multi-billion dollar economic impact from the weather and climate disaster just in the United States over the last few years. So the point I wanted to make here is if the current trend continues like this in the next 20, 28 years from now, the climate change could really catch the world economy more than by more than $3 trillion dollars. This essentially means that climate change could take approximately 11 to 14 percent of the world economy by 2050, which is kind of really scary, right? So we need to ensure our socioeconomic systems, like in our communities, our civil infrastructure, and so forth, are resilient to climate change by designing adaptation and strategies against these extreme even disruptions. So if you go to the next chart, please. So I think most of you agree with me. One of the aspects of designing climate change adaptation, strategy is really to deal with this massive, massive and complex data where the spatial and temporal information is coded within it. So this data comes from different sources, including the traditional satellite or the station, drones and names, and the different formats, quality resolution and representation as well, right? So even if you look at the current trend as well, the data continues to spoil in size and complexity, including mixing data from a vast and really growing area of this air's atmospheric ocean sensors and also is a booming public and private sector satellite, right? So the big question for us is how to really to manage and analyze and also maintain the data scale also to support critical societal and business problems, right? Go to the next chart, please. So, and again, as I said, we have a wealth of this data, right? For environmental geospatial data, right? So it also causes a fundamental problem for us, right? How to make, this is how to tame the data to do and how best to leverage it in order to make the better decisions, right? For one of the good examples you see here is the data comes by itself in different modalities, I've been in the roster form, in the vector, 3G, time series. So we need really technology to integrate these different data and different modalities and make available to accelerate research in climate risk and impact modeling also to improve the dissemination of this environmental or climate related data product as well as to enable businesses to build on top of these data products and localize the solution. So if I add a few other examples of the complexity of this data because the next chart, what really you see is a lot of these environmental related data, just geospatial temporal data actually has this data gravity within it, right? So which implies that the data become much harder to be moved and this can cause complexity and slow our effort also to design detailed tools for climate change adaptation goals which really start also creating this information in silo and ultimately also challenging our ability to really respond to climate hazard disruption. So as you heard from our keynote speaker yesterday I think the gentleman from the UN and the Africa Risk Map so in particular in the resource constrained countries this situation can further actually prevent digital transformation from occurring in the climate change adaptation resilience goals. So overall what we see is the factor of the data is too big to move and the context is really key to explore means we have started, the big data that are affecting this and more data, more compute, more analytics that really calling each of us here, the scientists, the developer and also modelers to really start thinking about new tools, new architectures to be designed in order to address these complexities, right? So in the next chart I will talk about some of IBM's technologies which we have been developing and for the last couple of years. So we are really developing this noble data and AI tools and technologies across four dimensions. So the first dimension is really building this large scale geospatial data analytics platform. Second we are building this climate informatics toolkits for enabling a mid to the long term climate addiction and weather extremes. In the third area we are working on is building this general purpose modeling framework to accelerate the way in which we basically develop climate risk analytics services. And the last one we are focusing on tools that allow us to integrate weather and climate information into applications so that we can actually enable climate our decision making. So the next chart I will highlight some of these tools and technologies. In brief and maybe some of you already heard in the previous and the yesterday also in another forum. So one of our flagship technologies is the IBM pairs technology which is a big geospatial data analytics platform which is designed to solve some of the key data and analytics. As I mentioned earlier it allows researchers and analysts to accelerate to the exploration of the environmental and climate data and model at scale. So if I go from the bottom up in the technology stack here so what you see is through the data and the data curation ingesting tools at the bottom the pairs able to ingest and curate more than 10 terabytes of the new data every day and also integrate different data models as I mentioned earlier be it a roster or vector a 3d times this and so forth so that at the end what you see is that the data being integrated and linked in a sort of in space and time while also managing this data pipeline with major content providers across the globe. So through if you go after a little bit in the stack you see this through this a distributed compute and the data search capability that pairs has so we are actually exposing more than six petabyte of the data which are really AI webby and also enabling downstream analytics operations so users could use the underlying programming where programming will clearly see on top and the energy capability either at the batch or at real time mode to perform the desired queries or machine learning tasks. So if you look at also in the vertical in the full stack so pairs support the data governance module for the purpose like provenance and data data provenance and so inter-privilege and so forth. So also data marketplace is an essential so that pairs enables this through its digital to an exchange in order to enable data sharing and collaboration. Finally what they would like to make here is also if you look at the top sort of then the stack of the software stack so if you are really playing a role of a developer or or a scientist or analyst pairs is ready for you through its well documented APIs SDK and US services and also I am happy to share that as of now pairs has been used in hundreds of critical applications and also used by several clients in lots of machine critical applications. If you go to the next chart so our second flagship technology I would like to highlight here is what we call the climate informatics AI toolkits. This is just sort of a mix of climate science and noble machine learning techniques actually to solve three fundamental parts. One is really to extend existing environmental and climate data and two sort of predicts the impactful climate even from weeks to several months ahead and serve to generate what we call this a what if extreme climate scenarios for organizations to basically explore their own risk exposure in resilient strategies. So one of the climate informatics AI toolkits is the IBM weather journalist you can see here in the chart basically it allows to generate a higher resolution weather data from low resolution forecast conditions on a future climate trend and what is very interesting here is when combined with our modeling from which I'll come back to it in a minute the weather generator why this probabilistic models like the chart could be the flood risk modeling or wild risk modeling for a different extreme weather and climate scenarios right so for example if you think of like risk cases in a given organization could could ask for what is the storm generated 25 percent of more rainfall than usual how would my community or assets be impacted so this has some of really examples of how our climate informatics AI toolkits can actually solve and if you go to the next chart please so the other technology I would like to highlight here is our flagship framework is what you call it the climate environmental climate impact modeling framework which this is a journal in the journal purpose modern framework that really accelerates and improves the way in which we do environmental and climate impact modeling at scale scale here this means really we are not limited by geographic boundary which is special we are not we could do impact of hazard modeling in the past and current or the future which is we have more temporal nature but also we support this across different impact of hazard modeling types so we are not limited just in one type so impact model the impact actually seems already offers pre-built hazard models like you see there floods wildfire drought renewable energy models etc these models are actually ready to be used or extended by leveraging our library of AI algorithms that we can see there and for better quantification, calibration and predictions and also seems comes with highly configurable AI based workflows that ideally eliminates routine TDS and earphone impact modeling task features how do you with the onboard how do you run models how do you calibrate how do you fit computing for structure so these all are really packaged in our AI based workflow that takes care of that the primary goal here is that to reduce the impact modeling time and effort by a magnitude of 10x so that modellers or scientists or decision makers could just focus on more discovery or decision tasks than just working on this routine tasks so finally we are also working to explore and also expose the underlining capabilities in order to encourage collaboration with partners and with a larger committee so I encourage you all to stay tuned on that I will be back on that in a couple of weeks so next chart please so just this is a just another illustration example how simp and pairs gently provide access to this massive environmental climate data and models and tools for anyone who requires them and they are configured with with the library of AI models as I said earlier to support this advanced analytics without actually downloading the data and also enable analytics insights integration with the business processes so this is really interesting and very powerful in a way that you don't need to worry about now data gravity and also good save actually money by integrating this data and the modeling capabilities together in a nice way so next please this is just yet another example just to illustrate how the two simp and the pairs technologies work together where simp basically pulling the right data and AI tools to model predict and also valid and join the hazard map for a given hazard type target location target here and other parameters are basically set by the user and the guided by the workflow as I mentioned earlier so if you go to the next chart so go to the next chart please so this is just just putting all together the software stack so you see from what I mentioned the discoveries of the bottom basically underpinning the most of the highly differentiated services as I mentioned built on top of the latest computing infrastructure htc hybrid cloud and ai4 models and also by taking advantage of our hundreds of terabyte of this real time curated analytics ready cubed and geospatial and temporal data already available and the frameworks are actually taking advantage of on this one to run the the model and also we provide this lots of accelerated tools that can be explainable as well that can help on the weather generation and in the time series for casting all of these are really available through APIs and SDK so as a final remark what I would like to make here is that the way really the the idea behind our technologies and frameworks is that no one actually solved the climate problem alone right so but this whole question with like-minded part not like some of you in the call already like we really need to create this a heretic health technology board maps and the technology capabilities we can actually work together to solve some of the toughest problems in the climate change in particular in this case in the climate adaptation problems if you look at if you go to the next chart please I think so if you are if you really like to learn more about the climate risk and impact technologies and please reach out I put some of the names there in the links I'm happy to take if you have any questions thank you so much Komi for that great presentation Komi we do have a question coming from the chat let me just read it out to you at what layer of technology stack is there the most opportunity or need for innovation so I would say I think at each level we need innovation so at the if you look at the really the data level I mean as I mentioned the data is vast complex right so you need new waves it's not typical large big data processing right this is really climate data or environmental data you are talking about right that requires a domain understanding requires really understand the physics law understanding also the fundamental question about what we have in our environment right so you need the data level innovation and also you need how do you interpret this data how do you with the analysis how do you really require that at the accelerator level you need right and also at the level of what if you go one up really what future to really matter for you right so you need this futureization technologies that do whatever future for example future for problem a could be agriculture is different from future from let's say infrastructure resilient right so if you look at the insurance is different so how do you really come up with this novel AI or machine learning techniques really to automatically pick up and this feature and then again we have talked a lot in the last couple of days about all this uncertainty comes with this climate environmental data really understanding the uncertainty quantifying them translating them into huge huge problem also requires a lot of deep investigation and innovation and then a lot of people really not understand not really taking enough time and the aspect of how do you really integrate this into business processes that is actually one of the fundamental problem few people really understand in the domain and it just you don't just create insights or create predictions but how do you actually make decisions on top of that when you basically get integrated with assets of this population of this financial decision making so so in a short I mean you need innovation of every staff in the software that's excellent very clear and thorough answer thank you so much that coming that's all the time we have for now so I want to thank you again for being with us today great discussion and great great answers thank you so much coming our next session is a panel discussion on research science challenges for battling climate change moderating this panel is Bruce Emil Green an IBM research staff member Bruce over to you thank you Hague I'd like to start by introducing our four panelists Bob Allen is senior research fellow in polymers and composites with a circular economy at the national renewable energy laboratory NREL Bob joined NREL last year his role is to co-lead NREL's circular economy strategy and to lead a transformational project on new high performance polymers and composites with designed circularity for energy applications he's also part of the department of energy's bottle consortium leadership team Bob came to NREL with 35 years of industrial experience at IBM's Alamedin research center where he recently led IBM's polymer science program as senior department manager and distinguished researcher his contributions in polymer technology for manufacturing semiconductors were recognized with his election to the national academy of engineering he's also an inventor of IBM's wallcat pet catalytic recycling technology Jeremy Gregory is executive director of the climate and sustainability consortium at the massachusetts institute of technology he studies the economic and environmental implications of engineering and system design decisions particularly in the areas of material production and recovery systems research topics include product and environmental foot printing manufacturing and lifecycle cost analysis and characterization of sustainable material systems Jeremy has applied these methods often with industrial partners to a range of different products industries including pavements buildings automobiles electronics consumer goods and waste treatment and recovery Stephen Ward is section head of geospatial data science in the geospatial science and human security division of Oak Ridge national laboratory he has over 20 years of experience in the geospatial technology industry and is responsible for designing and executing strategy and operational research programs focused on geospatial AI remote sensing resilient communications and autonomous systems for government sponsors across the department of defense and the department of homeland security in a previous role Dr. Ward reported directly to the chief science officer at Bayer climate as senior director of data insights and discovery at the climate corporation responsible for leading all geospatial remote sensing weather AI and sensor robotics research across the organization Martin Visbeck is head of the research unit for physical oceanography at the GMR Helmholtz Center for Ocean Research in Kiel and professor at Kiel University in Germany his research interests revolve around the ocean's role in climate systems integrated global ocean observations digital twins of the ocean and the ocean dimension of sustainable development Martin serves on national and international advisory committees including chair of the world meteorological organizations research board and the joint scientific committee of the world climate research program his past president of the oceanography society and fellows at the american geophysical union the american meteorological society the oceanography society and the european academy of sciences welcome bob jeremy steven martin to our panel on research and climate challenges for battling climate change first bob a question for you and could we see bob's charts marcel i think you have them to share here we go bob you've been working on plastics and polymers for decades now at nrel what can you do to stop plastic pollution and reuse that carbon yeah our thanks thanks bruce our real focus and goal is to reduce the carbon intensity of plastics production through two means actually develop sustainable feedstocks for example from biological sources and couple that with advanced development of advanced chemical recycling processes for today's plastics and if we can do that and we're off to a wonderful start i think we're in for a revolutionary change in the transformation of 21st century plastics production and we're real excited about it so i put together a couple charts that show what we're doing in the bottle consortium if i can have five minutes to describe it bottle consortium is a department of energy financed multi-laboratory consortium that seeks to really transform the way plastics are produced and plastics are recycled can you go to the next chart george uh we're all fairly familiar i think with the fact that the proliferation of plastics and mismanagement has generated a global pollution crisis if you ever want to read a very interesting paper science 2020 so-called plastic rain obviously bottles and litter are everywhere but even very very small micro plastic particles are getting in the ocean as well as the landmass and part of the reason for this is the big push we are creating globally almost one trillion pounds of plastics annually which is shocking i used to say billions of pounds it's almost one trillion pounds of plastics manufactured so if you go to the next chart what's less well understood it's also an energy and climate challenge something like six percent of the world's fossil fuel consumption is used to make polymers it's about the same as the amount of that of petroleum products that the global aviation sector uses annually this is projected to increase obviously with the world population and the global GDP so we're talking about 20 percent of the global fossil carbon consumption by the year 2050 next chart please so here's what we are focused on in the bottle consortium and as i said it's a it's a consortium of five national labs and five universities with pis at each one extremely multidisciplinary biology enzymology chemistry polymer science chemical engineering computation really focused on two things develop robust chemical recycling processes and develop new materials that are what we call recycled by design from very interesting feedstocks not just relying on the tried and true petrochemical feedstocks next chart this is a great example of where the industry is today this is the number one polymer you're all familiar with the PET polyethylene pterothalate also known as polyester bottles drink bottles for example clothing similar polymer almost the same currently industrialized is something called mechanical recycling where after exhaustive sorting and chopping and washing there's virtually zero contamination tolerance in this sort of process you can chop the material up and remelt it mix it with virgin polymer and you're off to the races in terms of having five ten fifteen percent recycle content and for example a new water bottle the problem is the all the other materials that come into a recovery center that are not pristine looking clear plastic go either in downcycling landfill or in the future our hope is they will go into a chemical recycling process so what you're talking about is every every polyester containing material be it bottle or a clamshell some sort of package maybe even textiles which is the real the real grand challenge could be deconstructed all the way back down to monomer the problem there is on the next chart the challenge there I should say and this is a slide from IBM this is the Volcat project a process which is a selective digestion of pet using a very special catalyst the challenge will be the materials that are available in high quantity are going to be extremely low quantity hopefully extremely low cost input so you're going to be running a factory with variable extreme low quality input the output and this is the the grand challenge of the whole the whole process the output has to be pristine very high quality so-called polymerization grade meaning 99 plus percent pure and this is a great example this is a curbside waste smells bad looks bad that was converted in that reactor behind Greg Breda's right elbow into this monomer which is 99.9 percent pure and able to make virgin PET from this special monomer called BHET so this is the kind of process that really will catalyze pun intended catalyze the whole industry behind this transformation that I talked about at the beginning thank you very much thanks Bob Jeremy as director of MIT's climate and sustainability consortium what kind of consortium like yours do to accelerate research and climate change yeah thanks very much Bruce I'm delighted to be here to talk to you about some of the work we're doing in the consortium it was just started this year and it's a new kind of industry academia partnership right now we're made up of 13 members including IBM and also companies from a variety of different sectors including Accenture, Apple, Boeing, Cargill, Dow, Wholesome, the materials company, Inditex, an apparel company, Mathworks, a software company, Nexplore, HockTF, a construction company, PepsiCo, Rand Whitney container board, and Verizon so that's one of the things you might notice is those companies are all from different sectors and that's kind of the the the point behind this we know there's a lot of different technological challenges to advancing climate solutions but what we're trying to do is take a step back and say what are the challenges that would affect all those companies that are not necessarily specific to their individual sectors so we're trying to get those companies to work with each other to identify what are common challenges and then also engage with the MIT community and so in our first year we've already identified a few key themes that are important to all of them and those include sustainable supply chains and decarbonizing freight transportation in particular, also circular economy of both plastics like Bob just talked about and also metals and minerals and then nature-based solutions to carbon removal including like forestry and agriculture and lastly engineering-based solutions to carbon removal like carbon capture utilization and sequestration so those are the topics that we're focused on and we're trying to get those conversations happening between companies from entirely different sectors about how can they join forces with each other and also with MIT to look at challenges around data or scaling in particular I think is something that we want to talk about and I'll discuss a bit more throughout the panel but like I said it's a new model that we're looking forward to expanding. Thanks Jeremy. Steven at Oak Ridge National Laboratory how will your group use geospatial and population data to help us mitigate and adapt to climate change? Yeah thanks Bruce and building on what Jeremy and Bob noted earlier and you know they both touched on this idea of the climate problem and potential solutions now evolving into something beyond atmospheric sciences beyond sort of just this siloed scientific discipline and really taking all sectors and all portions of industry and academia to solve what we really are looking at quite a bit within our division is not as much the impact humans are having on on climate but what is going to be the downstream impacts of climate change on humans this is a big problem this is a scale problem this is something when you're looking at the nexus of the built in human environment which is largely what we do here within the human dynamics and geographic data sciences group we have to do this at scale and we have to do this at scale both spatially and temporally to understand what those downstream effects are going to be so we're really concerned with answering questions about where people are you know what people are in that location and where can they safely be moved to if if impacted by physical environmental conditions associated with climate change of course these sort of environmental refugees if you will and this environmental refugee crisis is also going to trickle down and and have impacts on political stability on economics on food security uh and and so what we're doing is is working to build up the data sets that we believe are going to be necessary to help model and mitigate some of the impacts associated the human impacts associated with climate change and we're of course looking at this through a spatial lens you know spatial data remote sensing data has the ability to be collected at scale be collected in a in a non-intrusive manner and and done so in a way and it's regardless of environment whether you're looking at oceans whether you're looking at terrestrial environments urban environments and so we're we're building up this large data set an understanding of who is where and who is going to be at greatest risk it's our belief that the hardware the methods and models these are somewhat ephemeral they're always going to be improved they're always going to change but we have to have this baseline collection of data in order to really be able to unravel a lot of this problem thanks even martin and uh you have some charts which uh they're going to put up in your research on oceans at the germart helmholtz center in keel what are the oceans telling us about climate change and our new future yes thanks bruce and thanks colleagues for allowing me to be here i'm going to take a little bit of attack i'll speak about the ocean a little bit but also really want to bring out what the international community is doing and what international frames we can use to look at this problem i think bruce just mentioned about the scale element of the challenge and there's also a scale element of how we do the science that we do so the next chart gives you one actor in this space that is the world meteorological organization is a un body that really connects the or the world meteorological centers of the world in the u.s that would be the national oceanographic and atmospheric association and it's well known for meteorology for weather forecasting but it actually has the mandate both on water climate and weather and the weather that's what we know a lot it's an old organization but it's really important still next chart and what you see here what do they do so they coordinate globally all the observations that are relevant for weather first and foremost but also climate and water then they bring these data together do quality management but then provide services to the national member states that is and that certainly can only be done globally if you have the capacities and capabilities but they're also engaged in research the topic i will discuss next chart and just as an example just today they released a report at the beginning of the the general assembly meeting at the u.n new york called united in science and you see here eight key messages that are important for last year and if you look at them you can't read them right now but there's six of them are about the environment one is around cobit and and so i think it just shows you that that organization is also very present in the politicus we are next slide and here bruce what you ask is the ocean and climate connections i think most of you would sort of know this as the planet warms also the ocean warms that means it's getting warmer we have more ocean-based heat waves but also sea level rises and we have changes in the chemistry of the ocean things like ocean acidification loss of oxygen are the topics that the oceanographer study in but i want to go not too much deep into that next slide and and really think about what the what more the purpose of this conference is so given that challenges and given but also we just heard from steven that on the one hand the research is showing us you know the the the threats or the changes that the human have on our planet we talk sometimes about the entropocene the humans are changing the face of the planet but the question really now is so what do we do about the solutions and i heard i think we heard some good examples not only about climate but other industry solutions just in this panel but before next slide so that sets us into new motions at the world meteorological organization typically we use some sort of value chain thinking we have societal needs say weather forecasting but now also climate assessment and climate change then we have research observations data processing and services that then get to the benefits next slide and i want to focus here on the couple of different elements a key element and i think that's steven where also you are benefiting from is the observing system these are space based system in situ system but increasingly also massively social systems things like smart bombs links like what people do and i think that's a new opportunity that we can think about these observations of our planetary environment not only in the technical experts that for example spaces but also other observing systems and how to bring them together next slide and here i think in particular how can we use this information in a forecasting mode is what of the big challenges is it's easy for weather because we've learned how to do that but it's much harder for climate because of all the societal dimension that steven alluded to next slide but what i want to more speak about is how can that get organized so how can we go from the data from the research from the innovation the information down to actually talking to the users and i'm going to give you two examples next slide first example comes from where does the science get organized it's the world climate research program it is almost 40 years old by now and it has been really instrumental in really determining that humans are a force in the climate system and also trying to understand how will climate change as we go into the future next slide so it's really the vision of that program is that the world that uses that sound and relevant and timely climate science for its operation and i think we're seeing some progress but there's still more to do next slide so we're really talking about fundamentally understanding the climate system but increasingly bridging that science society gap that's the point four here which i think is more in this debate next slide so and it's really about how can we go from a weather prediction system to a climate prediction system to a climate impact prediction system where for example carbon cycle is there seasonal forecasting not just the next few days but what the next seasons look like and maybe even out for decades next slide and i think the way we're going to do that that's really want to spend just my last two minutes on is we're using an old hat of engineering that is digital twins of something the engineering community is very aware of digital twins of say infrastructures of airplanes and alike but i think the geospatial industry steven you guys and the climate community is thinking about we should really build digital replicas of the environmental system of the earth system not just about technology and i think these digital twinning really allows us to go from the observations through the lens of data to provide knowledge to people