 Drew is a systems dynamic model or facilitator trainer and designer of simulation based learning environments. He's focused on helping individuals and teams solve problems by applying systems, dynamic modeling and systems thinking in the areas of corporate sustainability, diabetes and public health, global climate change and land use policy. He's joined by his colleague, Janet Tchaikowski. Janet is a program associate at climate interactive. She's also a Stanford alum. She has her bachelor's degree in human biology or humbio as it's known here with a concentration in environmental health. So welcome, Drew and Janet. Thank you so much for being here and I will turn it over to you. Great, great. All right, everybody. This is going to be a time to roll up your sleeves and dive into a challenge. And as you probably understand, the challenge is to create the best scenario to address climate change, meeting a whole range of goals. You're going to be doing it with this simulator, N roads, that we built here at climate interactive along with MIT Sloan's sustainability initiative. And the way this is going to work is I've got a really short amount of time to get you from zero to say 20 miles an hour on using the model. And you're going to then go forward with your team, learn how it works and create the scenario that you really want to see for the future. Along the way, right into chat, questions that you have, Janet is ready to direct you to the FAQs on our website, to the resources or answer them if she can in a really short amount of time. But the way that we're going to go about this is really dive into the simulator itself. So this is going to be interactive and that I'm going to take you through how to use the simulator. And the basics you can see here, the basics of what you're doing is kind of as simple as this, you've got this simulator, you and your team are going to be figuring out how you could imagine, say, I don't know, renewable energy. And the way the simulator is set up is that it can test very quickly what is the impact, say, of more renewable energy. And you're seeing this over and over, you can see that lines change, the temperature changes, 4.1 goes down to 3.9. And you're going to be making a scenario by changing lots of things to say, can you electrify and have less deforestation and hurt coal, whatever you think it's going to take in order to get you down to 2 degrees, 1.5, or if you don't think that's possible, 2.5, 2.8, 3.8, 1.4, create the scenario that you really want to see. How am I going to teach you how to learn how to use it? Well, we're going to just start with a case study of the experience I had starting eight years ago was when we really got engaged in this. We talked to just call him a very prominent vocal tech person who had a strong opinion about addressing climate change. We want to call him Mr. X. Mr. X said that energy efficiency is cute. And when someone says cute about an energy source, that means bad, that energy efficiency was not going to really help the climate enough. Renewable energy, inconsequential, it's never going to add up to doing much wind and solar and other sources like that. The only real answer, zero carbon energy technology. And Andrew Yang's been talking about this lately. This is like thorium fission, fourth generation nuclear, nuclear fusion. We don't really know what it looks like, but what if the labs, like what if you brilliant people at Stanford could come up with a new source of energy cheaper than coal, figure out it takes a while to commercialize it, spread it around the world. That would do it, right? That was the idea. So this technology person was saying that a philanthropist came to climate interactive. We had done a bunch with our models for the Paris Agreement for the Copenhagen Accord. By that it was used by the US State Department and the Chinese government. Both used the model, our previous model in 2014 as part of the bilateral negotiations that set up the Paris Agreement in 2015. So the models that we were built were pretty mainstream in use in global climate negotiations. So this philanthropist said, hey, I don't like that this guy is saying the only real answer is zero carbon technology. Build a model to test his thinking on this. That's what led to the creation of En-Road. So I'd like you to do a thought experiment to introduce this whole idea to you. What if we did have thorium fission? What if we had some zero carbon energy source cheaper than coal that shows up in the world here in 20, like in a few months out of the lab and it takes some time to commercialize, then it starts competing with coal and gas and you get more electrification. And so you're getting more capacity being invested. And that's mean less coal and less, and I mean less coal and that's natural gas carbon dioxide emissions. And there's a another graph here you can look at, greenhouse gas net emissions perhaps would go down and temperature would go down. So my question to you, what do you think would happen to global temperature? And I mean literally, and along the way why, what do you think 4.1 degrees goes down to 1.5, 2, 2.53, 3.54, like where would it go if we had an energy supply that coming out of the lab cheaper than coal? Now I'm serious about this being interactive. So I'm going to look down in the chat. So start writing in chat and if you have, I'm going to look and see you must have chat here somewhere. So right into chat, what is the number? You got to put yourself on the line. Write down a number. 1.5, 2.0, 2.3, 2.8, 3.4, 4.0. I don't see anyone writing yet. Come on, you're at Stanford. Do this. There it is. 3.0, 3.7, 2.9, 2.0, 2.0. Wow, this is great. Oh my god, so many opinions. This is great. Okay, I come out of MIT Sloan and at MIT Sloan, we cold call. You guys do that here? I hope you do that. So Andrea Cotto, 2.0. So what's your thinking, Andrea Cotto? Unmute if you would and tell us what do you think, why? How do we get 2.0? Someone tell the story of why this does, what's happening in the world? Give me one sentence. I'm going to ask a bunch of people. So one sentence and I'm looking to see your, I want to see, so Andrea, what do you think? Why 2.0? Why did you say 2.0? So I envisioned this new technology to be completely disruptive to what we have right now. So I would go for a new technology. Absolutely. And it's so disruptive that it brings us all the way to 2.0. Great. So someone else in that range of 2.0. Charles Stone, you said 2.0. It's disruptive, Andrea said. What else? It's disruptive and therefore what is happening in the real world that leads you to limit warming to two degrees? Yeah, so I base it on the fact that coal is maybe around 20% of energy consumption, but disproportionately more in terms of carbon emissions. So half felt like half of this band of four degrees seemed like a good reduction. Coal is half, so maybe half the temperature. Cool. Great. Let's hear, so Francis Palmer, 2.0, add something to what you just heard. Some more resolution of what's really going on in the real world. Yeah, I think switching to 100% renewable energy and also at the same time as that, electrifying the transportation sector and increasing the manufacture of electric vehicles. Fantastic. So let's just note, thank you. That was great. We're starting to talk about like what else we would do manufacturing electric vehicles at this. So we're going to do that. That's your assignment. At this moment, I'm asking you one question though. If we had zero carbon thorium fission or something like it, zero carbon, what would it do to temperature? So don't assume other than electricity gets cheaper perhaps and that leads to more electric vehicles. Don't assume other things going on in the world. All right. So a lot of you wrote this 0.5, Carson Tucker, holy cow, 0.5 degrees C. All right. So a lot of visions of what could happen. So now join me in how would you think this through? Like imagine you had to build a mathematical model. That was our team's challenge. You have to imagine, well, it's not just like imagine the diffusion of a new technology. It's in the context of the world that we have, the world that we have with coal, oil, gas, biofuels, with growing population, growing GDP with energy efficiency, energy intensity in different sectors and not just energy, right? We've got to talk about methane and agriculture. We've got to talk about wastewater and we've got to talk about carbon removal and other things. So it would compete with a lot of things that are going on in the world. So here's the basics of some of the assumptions we had to make and under view. And as I do this, I'm talking about the issue, but look at the graphs that I'm showing you because you're going to want to find these graphs later. View. Chia graphs. Chia is the Japanese guy who came up with a really great equation, which is population times GDP per capita, that is growth of goods and services per person. Multiply the two together, you get GDP. Multiply it by the energy intensity, how much energy it takes to deliver a dollar of value. As that line, see that number falling, that's because we get more efficient with technologies. Also it's the shift to a service economy. Multiply the three together and you get total exajoules, all the energy used on earth. Then you have to multiply it against the carbon intensity. How many megatons of CO2 per exajoule? That's a function of where do you get your energy? Is it this thorium fission? Is it renewables? Is it nuclear? Or is it the higher carbon? Coal oil and gas. You can see, so you multiply the four together and you get CO2 energy emissions. That's the Chia identity or Chia graph. In this world, we assumed population growing up to about 11 billion. You can change it by the way if you want to envision it lower or higher. See that? GDP per capita growing. You can change that if you want as well. Energy intensity falling. Carbon intensity slowly falling. Little less coal, we're going to get some more gas, but not falling a whole lot. This is the world that we're going to drop the thorium fission into. The other part of the world you need to understand is over here, global sources of primary energy. I'm going to show you stacked. Look at it stacked. One note, you just saw what I did here. This is really a great view. You can see what we think are the top 12 graphs and you change them. Of course, you get to see everything change. Why? Because computers are really fast and system dynamics models are amazing. That's the approach that we're using here, system dynamics modeling. Here's the view that I really think is good. Look at the primary energy, global sources stacked, coals and brown, oils on top. You have natural gas, renewables, bioenergy, nuclear. There's no new tech in orange because it doesn't exist. We said into this world in 2020, we're going to envision this new energy source cheaper than coal. Watch what it does. You already said what you think it's going to do. You ready? Here we go. First of all, which line, which wedge is going to move the most? Think which of these wedges in the top left are going to move the most. Are we going to see the biggest change in renewables and coal or gas? Think, think, think. This is electricity so it's not going after the internal combustion engine and oil is directly, so probably not the red oil. Let's check it out. The second guy who spoke talked about coal. Let's watch what happens to coal. Here it comes, new technology and I'm going to first, I'm just going to do the full. You click here and then you see the growth of it in the top, the orange line. I'm going to run it a couple times again. You see that? So huge growth and this is growing faster than any energy source has ever grown in history, like much faster. I'm going to show it with not stacked but as a line. Watch that orange line grow up. Now, which one moves the most? Coal. Coal is the most carbon dense. It's the most on the edge economically and it falls a good bit. So notice that what it does is it grows. We get the growth in Thorium fission and as you would guess, greenhouse gas net emissions goes down because we're not burning as much gas and coal. We have less emissions. The blue line is the new run. The black line is the old run. The wedge between the two is the avoided emissions. I'm going to show you again and then temperature goes down from 4.1 to 3.8, not two degrees, not 0.5 degrees. And I did say some of you guessed this close, you said 3637. Oh my God. When I saw this, I was so surprised and we had a number like this when we got a meeting with this tech team and I went out, met with them and all of their climate advisors showed them an early version of the model with a result like this and they said, no, I don't believe you. Your model stinks. Make it better. It's got to have this and this and this and this and this. So we went back, took us three months, we improved the model, came back and we still had a similar result. Only 3.8 degrees. Only a cut of 0.3 degrees. What's going on? Does anybody think? Now this is not why in the world, don't think about the real world. Well, think about the real world, but it's got to be what's in the model. Anybody think by looking at what I've got right now and actually, you know what, I'm going to share this scenario. See if you can figure it out. And when you do this, by the way, and you come up with a scenario like, hey, this is all we're going to do. By the way, when you do make scenarios, go share it to Twitter, Facebook, LinkedIn and say, here's my scenario right here. But if you copy the scenario link, you go here, I'm going to go into chat and I'm going to send you the link. So go look at it, click on it and see if you can figure out why it didn't do nearly as much as we had hoped. What's going on? If we had more time, I would ask all of you, we could have a long discussion, but frankly, I'm just going to cut to the chase. When you look at En-ROADS results, I want you to focus a lot on when things help. When do you see results? So in this case, when do you see coal, oil and gas staying in the ground? When do you see emissions not being emitted? Look over here, greenhouse gas net emissions identical 2020, 25, 2030, 2035. It's really not till 2040 that these two lines depart from each other. Why does it take that long? Well, it takes about 10 years to commercialize. A new, it took 12 years for uranium nuclear to commercialize. We assume 10. And by the way, if you don't like 10, you can go test the same thing. You'll notice that when you click on these, see those three dots, click on the three dots and then you say, I want to use detailed settings here. And I want to have new tech years to commercialize these B5 years. We make the assumptions transparent. You can change many simulation assumptions and many of the assumptions that are important are here. Progress ratio, which really matters a lot for these technologies, how fast they learn the climate sensitivity to a doubling of carbon. A lot of the important assumptions are up here. But you can change in this case, if you don't like five years, 10 years, make it five years, change it if you like, but still it's 10 years to commercialize. And then it starts to compete with gas and with coal. Slowly then it starts to gain market share and displace the burning of coal, oil and gas. It does spark some electrification. Oh, so you can go to look at electrification. There could of course be, wait, let me see. I'm going to redo the next new technology. It sparks some new electrification, not very much. You may want to test it in the future. Other scenarios that electrify more, but the main reason that it doesn't help as much is that it doesn't help until 2040. And if you've read any studies about climate, you'll know we need to reduce emissions of greenhouse gases within the next five to 10 years. There's been a lot written about the urgency of emissions reduction in the near term. So if we wait that long, then we only get a really modest reduction in what's going on. Now, why does that not grow faster and displace other things, other sources? Well, there's something I want you to understand about inroads and it really has to do with a second kind of delay. One delay is here. And can you see a little thing as a new tech, someone just confirmed that you're able to see the slides? Okay. You have the 2020 R&D success here, commercialization over 10 years. And then it starts to develop new capacity being developed. There's a development delay. There's a construction delay. But the big delay is in the long lifetime of existing capital, in existing refineries, existing mines, existing coal-fired power plants. And mostly, don't think of the United States. Think of India, China, Mexico, Brazil, Indonesia, South Africa, Australia, all around the world, all of that capacity being built. And it lives for 30 years. So it takes a long time for capital stock to get retired away and for new capital stock to get built up. So there are those delays exist. That's the main reason it takes so long and why you don't get as big a result. A second question though, if you had cheap thorium fission electricity around the world, what does that do to global price of energy? Someone, unmute yourself. What happens to global price of energy if we have thorium fission, cheap thorium fission around the world? And mostly think of India, China, the developing world, the global South Africa. Someone unmute, what happens to it? What happens to the cost of energy around the world? Would it decrease? Yeah, it's going to go down. So look over here at cost of energy. Exactly. So there's the blue line. It gets cheaper. If it gets cheaper, someone who just unmuted, what happens to energy demand if we have cheap energy? Exactly. It's called the rebound effect or the Jebens paradox. And it's not huge, but it's non-trivial. We would actually see cheap energy leads to more energy consumption. Now this is good in many developing countries. People have more light bulbs and all that can be better and just boost the energy consumption a little bit at the exact time that we need energy demand to go down. So I'm going to go back over here. Those are the reasons. And I walked through that team at the tech company and said, here are the reasons why those results would be so modest. And here's what happened. Two weeks later, Mr. X gave a public talk and he emphasized the need for investment in research in five areas, carbon capture, nuclear, solar wind, and biofuels. So he'd said no longer renewables are inconsequential and a concurrent focus on efficiency. And because of this explanation about the turnover of infrastructure in the long lifetimes, they said that energy moves slowly by its nature. Unlike IT, like software, software could get swapped out in a year or two. You just get rid of the old and load your new software. I mean, how recently were we all using Zoom? Skype has gone, Zoom is in. Boom. Unlike IT, it's underlying hardware, infrastructure, refineries, coal-fired power plants takes decades to swap out. So engaging with a simulator, helping people improve their mental models. And that's why this simulator is here for you. It is here to help you improve your mental model about what it's really going to take to get down to two degrees. And I think you can see, and I hope I've convinced you that there's no silver bullet, right? This exercise is not going to be you and your friends and your team thinking, oh, I've got 18 levers here at the bottom. And there really are 18 levers. It's not going to be just look and this is the sheet where you can see all 18. Fighting over which one is it? Is it methane, or is it deforestation, or is it, I don't know, direct air capture, ag, soil carbon, eating vegetarian? Is it going to be Teslas all around the world, electrifying transport? Is it going to be wind and solar? Is it defund or get out of oil? It's not one thing, carbon pricing. You'll see. And I hope you learn that it's not one thing. There's no silver bullet. Even zero carbon-thorium fission is not a silver bullet. Your challenge is to figure out what is the combination of actions that is the best path to getting to well below two degrees. And you're going to be doing that by clicking on things here and testing different scenarios. Now, along the way, some tips. Do not just click lots of stuff and go, oh, play it like a video game. Say, okay, click, click, click, okay. Don't do what I'm doing right now. That's not how this works. Okay? That's not the point. I want you and your colleague, your team members to think before you run it. This isn't an answer machine. This is a thinking tool that's designed to complement the other tools that are out there. Now, one note, other tools that are out there, they're fantastic ones. And I want to make sure I get to this also just to make sure you understand how we build confidence in this. At Stanford, you have the energy modeling forum. John Wyatt and team, they all manage the group of people who manage the integrated assessment models. And one thing that's really cool is that they publish all of their results in a way that we can compare against them. So this is a very different type of model from those models. Those are research models in those study. And they have disaggregated economic regions and disaggregated physical, you know, impact regions that you can watch. But they publish their results so that people like me can take all our simplified models that are designed for students, for policy makers, for online use by non experts. And then we can compare our results against them. So this is a map, a graph that actually Janet made 2000 to 2100 greenhouse gas net emissions. They have graphs like this for another 29 variables. And it shows different scenarios for a story called SSP two, which is one of the stories out there for the way the future develops. And then it has different levels of warming a baseline. And then the emissions going down, down, down more and more. These are the results from six integrated assessment models over on the right. And then we can explore how did we match against them. So you can see here, I'm showing our match, we calibrated to those models as a way to build our confidence that when carbon price goes up, emissions go down about as much as the envelope of the other models that are out there. So I can show you a lot more testing we tested for other scenarios such as SSP one and SSP three and other variables as well. There's a lot we can go look at, not just greenhouse net emissions, but also oil, if that would be interesting. That's not the point right now, there's a whole video on that if you want to go understand more about it. We're here, because those models are fantastic, go read their papers. But we want you to improve your understanding through iterative testing, where you're not going to just be using it as an answer machine, you're going to be thinking and then doing a test and seeing if you can learn what's going on in the model. Okay. Actually, here's Diego has raised his hand. I see Diego. So while I look around, I'm going to let you ask one question. Go ahead, Diego, what do you got? Yeah, just a quick question regarding the assumptions behind the model. When was it built so to know if it includes all the COVID pandemic effects like a slower economic growth and that kind of stuff? Yeah. So it's been built and iterated upon over the last eight years. And we revise it and release new things every month. So it happens that in a few days, we're going to release it in Spanish. Right now it's in Portuguese, but it turns out that in Spanish and we're releasing air quality. So we constantly are revising it and updating it. That said, what we've done about GDP per capita growth and allowing to test a recession, I tested last week, but it's not here. We'll probably be here October 1st, I hope. But if you want to imagine a future that says, Hey, I don't think this is the one near thing. I think your starting temperate, your scenario you have here, and I'm looking to see it, at 2.5% GDP per capita growth, it actually slows over time, but that's too high. This recession is sticking around, folks. If you want to test a scenario like that, don't just run it, think where does temperature going to go? Why? You want to look at things like what is energy demand going to do? Think about it and then think, all right, I want to imagine 2.3%. 0.2% drop in GDP per capita growth over the next 80 years would be enormous. Let's see. So 2.3 think, talk to the others. 4.1 is going to get me down to, I don't know, 3.9, 3.0, 2.0, test it. Here we go. Consumption drops a little bit 0.1 degree. So a 0.2 decrease in GDP per capita growth, there's GDP over on the right. That's the scenario you get. So do what you can to test what you can with the model given what it is today, because that's all you've got access to until we release a new version. I see other people raising hands, but I think I just got to show you more stuff. And actually, I think we have a session tomorrow after you play with the model sum, where you're going to get to answer, ask all the questions you want to ask. And if it's something quick, write it in chat, and Janet's going to show you, answer it if she can. I know you have a lot of questions, but let me just show you some more of the features that I think are going to be really important for you to look at. And so here we go. Here's some other things. Right now I'm showing you greenhouse gas net emissions. And this is all the emissions, but you guys are smart enough. You can handle stack graphs. This is really important. Look at this stack graph. This has the same line. The top of this line is net emissions. But underneath it, it shows you where those gases are coming from. Land use is in green. So if you change deforestation, you see it shrinks. See that green area? And it actually goes negative. See that? It changes those. On top of it is the black area is energy CO2, coal, oil, and gas. So if you keep coal on the ground, it goes down. You keep oil on the ground, it goes down. You have a big old carbon price. It goes down a lot, actually, you can see there. That's what shrinks that middle area. On top of it, F gases, HFCs, SF6. Then on top of it, methane. Methane is big. See that blue area? Wastewater, coal, excuse me, oil and gas industry, landfills, cattle. These are some of the sources of methane. And then on top of that, nitrous oxide and fertilizer. And some of those things you change over here, methane and other. By the way, you're like, wait, wait, wait, methane and other, what's in there? Click on it, click on the corner, see the little I button, and it tells you what are we talking about. What are the examples? Decreased meat consumption, agricultural practices, some of the dynamics. Oh, this is really cool. I'm actually learning. What do the levers do? See what's underneath here. It even has a case study of something that's in here. You can learn more about it too. If you hit this little button, it'll pop up the whole user guide that has all the assumptions. So go dig into that. You'll need it to understand what's actually behind what you're simulating. You'll also find related graphs in this corner that I'll show you in a minute. So methane and other, see how it shrinks that top area. My point though is how helpful this graph is, it's going to help you figure out why you still have the warming that you have. It also has a key distinction, which is it shows negative emissions or carbon dioxide removal. And those are shown over here. There are some imagined technologies. They don't really exist at scale, but they're under here. There are five different types where you can say, well, what if we have this idea of bioenergy with carbon capture and storage? And here you have 96% of that potential. Here it is. It gets us all the way up to 5.7 gigatons a year pulling it out of the atmosphere. 5.76 gigatons a year by what, 2035 or so. That is shown in this graph as negative. It goes, see that silver area? It goes down to exactly 5.76. So in this scenario, you've got everything above the line going into the atmosphere and then everything below the line getting pulled out of the atmosphere. So it's important to look at that negative area and see what you've got here. Other things like growing trees, afforestation will give you even more. So see that on top of there. We can grow some trees. By the way, there are other related graphs. You can go see, well, how much land did that take? Oh my God, that took over two Indias. It took over two Indias of growing trees to get that, what, 11 gigatons a year. Just so you can start, we're going to ask you questions about equity. Is that like, how would that happen if we had two Indias of land? Who's living on that land? How would we do that in a way that preserves biodiversity that doesn't dump the problem into other areas? And under the I button, there is what we call equity considerations. Don't just optimize for the climate and sub-optimize for other things that we all care about, such as people, such as other species, such as things that your group really cares about. And there's some tips here about what those might be, but you can imagine them as well. So those are some important graphs that we find really help you understand what are all the drivers that are here? What are some of the things that I'm doing? Another one that's related, I showed you with assumptions. You know, before I said, oh, we have bioenergy, carbon capture, and storage. What if you don't like my numbers? What if you thought I limited it too much? In that case, carbon dioxide removal maximum, you can click on this little button and say, well, where did they get that number? Well, the Royal Society 2018 geoengineering report, they thought it was about six and it could go up to higher or lower. If you thought it could be higher, make it 9.5. You think it'd be lower, make it 1.5. Don't just change it though, because you're trying to get to two degrees, change it because you think that's what the way the world really works. And it is an appropriate way to look at this problem. I'm going to pause for a second. I'm really giving you just a sip from the fire hose, but I really want to make sure you see all of the coolest features and the things that are out there. Oh, there's another dynamic. We're going to call squeeze the balloon. And I want you to watch when you start getting mysterious behavior and we wonder what is going on in the model. There's some dynamics that reveal how we modeled this system. Check this out. There are some things that you can do such as underneath coal. You can tax coal, but you could also just say, no, we're going to stop building coal infrastructure. And we're going to stop the plans from running. We call that reduction in coal utilization. Just say, no, no more coal. But imagine what's going to happen to gas? What's going to happen to gas if we stop building coal? Yeah. So someone speak up. What happens to the use of natural gas? Goes out. Yeah, it goes up. We're not saying the world still wants its energy. And there's time to build new infrastructure. So that we modeled that in the system. We work really hard to make sure and watch what happens. So here I'm going to turn it on and watch the brown line of coal go down and then watch. Let's see if I do it again. Brown line. Here we go. Do it again. Brown line of coal goes down. We'll do it again a couple more times. Watch the blue line. We have the blue line of gas goes up. It's compensating feedback. Compensating feedback. There's still energy demand. It's got to go somewhere. There's no more coal being built. It goes to wind and solar as well. See that green line right there? Wind and solar goes up. We can actually see how much. Let's see how we do with renewables. It went up a good bit. That's the squeeze the balloon challenge or dynamic we'll call it. One note, someone mentioned 100% renewables. There are a lot of cool graphs that we buried in here that you may want to look at like final energy consumption types. You may want to see, well, how did we do with 100% renewables? What is the percent of electricity from renewables? And you can then test it. You can see here, oh, here we are at 50% renewables. Test more. We want to get up to, oh, we got up to 70% renewables, for example. A lot of graphs buried under here that might be really interesting. Another one that's related to all this that's really popular right now is a carbon price. Let's look at carbon price for a second. Over here is carbon price. Note that you can change it to be $49 a ton, $100 a ton, $166 a ton. Pick your price. Go research what's being proposed out there. If you want to explore much higher levels than these over here, you can actually over and you can figure it out. But basically, you can make it going up all the way to $785, so you can imagine much higher carbon prices. And then you can also explore what happens to revenue and cost, because there's going to be a lot of revenue generated. In that scenario I just made, it generates $5.5 trillion per year. Imagine, hey, how would we use that? Do we dividend and send it back to citizens? Because in this case, talk about equity, we got to be concerned about people who rely on energy to get to their jobs or heat their buildings. Lower socioeconomic status, people spend a higher percentage of their income on energy. So if that price went up, or see the cost of energy like, wow, carbon price would make it go up a lot, how do you make sure those people are okay and the world doesn't rebel against your policy? Kind of happened in France a bit last year. So think about what to do with that dividend. Of course, the oil companies say that they want it back. Saudi Arabia and other countries should say and Exxon say that the money should go back to them. Governments would love to say that it goes back to them. You might help their budgets. So decide what you might do with this money. Okay, so these are some of the other graphs that I wanted to make sure you saw. I'm going to flip to others that are out there. One of them is when you get stuck, we have under here, under the, I think it's under the I button. No, it wasn't under the I button. Under help, general FAQs. Janet, who's on the call right now. It's been working really hard. Before you go and ask Janet the question, go here to general FAQs and ask the question here. And it may give you a good answer. For example, coal, why? Why does coal grow so large in enroads? So some people might like going back here, people would say, oh my gosh, I thought coal was dead. Drew, what the heck? Why is coal growing up that much? Well, here's why we think coal is going up that much. There's a nice little article that Janet wrote that says what's going on and it shows our calibration of coal against the other integrated assessment models that show where we sit relative to Scholl's Shells forecast and the IEA forecast and where we sit next to the SSPs, etc. So there are lots of information under that site. Go to the support site in order to find out those things. Also, we have a bunch of videos. Go to the video tours if you want to learn more about what's out there. Go watch some of the training videos. And on the main site, we actually have a good number of videos that you could go. This is climateinteractive.org. A lot of the information about the model is here on this page. So I just mentioned these videos. If you go on here and you look at En-ROAD's videos, you'll see them on different topics like, I don't know, population, slowing population growth. Here's one of our explanations about what's going on in the model on a range of topics. I did a bunch of them on egg soil carbon and carbon removal. So if you want to learn more, there are a lot of videos on the website that will teach you that will inform your use of the model. The other thing is that once you make your scenario, you're going to want to share it and input it when you send it to the team. And you send it to Kate and Arpita and everybody. So here we are. And you say, you know what I'm going to do? I'm going to electrify everything. I'm going to electrify. And I believe in renewables. And I believe in nuclear. And we're going to cut methane. And we're going to cut deforestation. No, we're not going to grow trees. That's it. 2.9. You're going to say, that's my scenario. Here's why you all agree. And then one thing you can do is look at, I think it's called actions. That's it. Actions and outcomes. This view, actions and outcomes will show you everything you've done so that when you submit it to the team and says, well, we set renewables to a tax of 5 cents per kilowatt hour, nuclear, 6 cents, 3.7% per year. Those are explicitly what you did. And it'll show you exactly your temperature, CO2 concentration, how many tons of CO2 you avoided by 2100. All of your outputs are there in the actions and outcomes view. There's some other key interesting things that I think are kind of cool that underneath that you may not know if you don't look around, but I want to make sure you knew are there. There's a lot of talk about gas, carbon capture in storage, it's technology or coal carbon capture in storage. End of the smokestack, capture it, the carbon dioxide, liquefy it, pipe it, shove it underground. You can encourage those technologies. Here's coal CCS and you can say, well, what if it got cheaper? I'm going to make a subsidy and boom, you can test it and improve it under there. So you're able to change some of those things. The other thing is that what we do in coal, oil and gas is connected to methane and other. So I just reduced coal and gas, look over here to methane, and you'll see that methane emissions went down. Why? A lot comes from actually not the coal industry from the gas and oil industry. Those things are connected across the system. If you love renewable energy, you may say, oh, I think that storage of renewable energy is going to get a lot better. I'm going to go under here and I want to encourage renewables, see the green line go up, and I want to have it do even better. Underneath, look at this, you're going to have a breakthrough cost reduction that has renewables grow even more. You're able to change some of those storage costs. Looking to see other things that are particularly interesting or helpful. Oh, there's a lot of talk about net zero. You may in your team say, oh, we need to be net zero CO2 emissions by a certain year. Can you explore that? Yes. What we're talking about is carbon dioxide net emissions. So there they are. The black line is the business's usual future. The blue line is the scenario that we're creating. So the year of net zero, well, let's create it. We're not zero net zero yet. We would need more energy efficient. So we need to electrify. We would need to grow some trees. We would probably need a big old carbon price. Oh, we're almost net zero. What are we going to do? We're going to electrify some more. And there we are net zero in 2082. So explore net zero, if you like. That's another framing that's particularly interesting or helpful. I'm going to pause. Janet, you've probably been answering a lot of questions, but if there anything that you would want to add that are other important features that you see, or actually Kate or Peter, anyone on the team that you say, hey, Drew, you haven't shown that cool thing. There's another cool thing. Show it because it's really helpful. We had a couple questions and one was about how much uncertainty there is in the model. Yeah. So how much uncertainty? As a user of the model, there's a lot of uncertainty. You should approach this as a thinking tool. And when we handle uncertainty, the first thing to accept about a use of a model like this is that we want it to be better than the model that we use every day, just between our ears, which is an imperfect way of thinking about the future, the one that our mental model. So what we're trying to do is supplement our mental models with a simulation that does a better job of keeping track of a lot of the dynamics that I've been talking about. The way to explore uncertainty about the future is to do real-time sensitivity testing. So you know models like this often when they show temperature or even CO2 emissions, sometimes we'll have a band around it. And we used to have a version like that, but we didn't find that was as helpful as allowing our user to do real-time sensitivity testing. For example, look here we are. I just made this 2.3 degree scenario. Go under simulation, one of the biggest areas of uncertainty. The biggest number that gets debated is the climate sensitivity to a doubling of carbon. Many of the times you see a band of uncertainty around a temperature result is because we don't know exactly how much warming we'll get with a doubling of atmospheric carbon. In fact, there was a really important paper recently that was published just two weeks ago that said maybe it's, well, we've chosen three degrees. Here's the source. You click on the dots and you can see why we got that number. That study said, you know what, it actually is likely within a range of 2.6 and 4.1. So if you and your team want to explore uncertainty, say, well, if that study is right, it could be 2.6. So imagine what's it going to do? There's less warming with a doubling of carbon. We already got 2.3. I hope you're thinking temperature is not going to go up as much if that is the deal. Oh my gosh, that's scenario. All those actions get us all the way down to two degrees if that's the case. Now, if on the other hand, there's more permafrost melting and release of CO2 and methane, if there are more feedback effects like the albedo effect, if those are stronger, we're more towards the upper end of the climate sensitivity. 4.1 is a possible scenario. So that 2.3, let's walk and say, now in your head think, huh, went down 0.3, 2.3 to 2, it'll go up to what, 3, 4, 3, no, 2.4, 2.5, 2.9, I was wrong. It's even higher. So explore your own sensitivity by testing and varying things. And you can explicitly expand or increase the effect of temperature on methane emissions from permafrost and clathrates and things like that. So you can explore a lot of these other things. That's how we like to think about sensitivity. The other way we like to think about sensitivity is to look back to a lot of our testing. And because you're at Stanford and the home of the Energy Modeling Forum, I'll come back to looking at these results where we tested a wide range of scenarios that I showed you before here. And there's a whole video that we made on our video page that shows you much more about confidence building in the model. I think it's way down here. You can go and look and see some of the videos about, it's way down here, confidence building and how we did the testing of the model. Okay. Other good questions. I think we have five minutes left. So what's another good question? Someone's asking about the assignment and whether the submission should be based on what we personally think is the absolute best way to achieve two degrees independent of current political or business climate, or should we be trying to focus on more realistic goals based on current government policy? Great question. I know in this session, I should shift it over to Kate and Arpeta, you guys probably want to answer this. But because I wrote this section and this is the assignment that I gave my students, maybe I'll just answer this one and then pass it over to you about the logistics of it. But I think this is, I hope I have the right version. This shows you, this is the assignment. And you'll see there are five goals. One is to limit global warming. We didn't say you have to get two degrees or 1.5 or you have to get 2.5 or three. We said limit warming. You get to think about where you want to aim there, but also preserve and create a healthy economy. If you think that turning on all of these levers too fast is too much, you got to like space things out and you'll notice many of the levers I move, you can start in 2025, 2030, 2040, promote equity and adjust transition. Remember what I showed you about? Don't hurt poor people whom we're trying to help immediately. Try to make the world more equitable. Don't dump the problem into, don't maximize long-term climate health by hurting people in the near term. Four, protect the environment. If you don't think nuclear power is good for the environment, then don't do it. That's like don't create, don't solve one problem and create one another somewhere else. You also said what's realistic. Here's the crucial words. Number five, be realistic but not cynical. I'd like you to think about human civilization at its best. Realistic but not cynical. You can't just get in there and say, oh, we're going to just have unicorns everywhere. It's just going to be easy. No, realistic but not cynical. Okay. I think I need to turn it over for talking about the assignment. Kate, right? Yes, I can talk a little bit more about the assignment. There were some questions in the chat that I can go over just to make sure everyone's on the same page. So yes, I agree with Drew about being realistic. I think in general, if you want to make certain decisions about how you're going about it, what your strategy is, that's fine. You can make those decisions and that's just what we want to see when you turn in your assignment is what your strategy was and what you're thinking about. So we had a couple of questions kind of to that end about what the evaluation criteria are going to be. If you'll just be a little bit patient with me, I'll try to get you something kind of set and written down soon, but the sort of short answer is that we want you to be thoughtful about some of these things that we've been talking about. There is a big long list in the assignment after what Drew just showed you. And we get that you can't answer all of those questions in the time you have. But just if you can pick one or two in terms of like, who are the winners and losers? What are the effects of your scenario? Have there been any surprises? Again, you don't have to say all of those things, but just kind of tell us about your process and be thoughtful about what you're doing and what scenario you're presenting. The deadline someone asked, so that is Wednesday at 3 p.m. Pacific via Canvas. It is a video submission, but what we mean by that is have your team or at least one person from your team record a Zoom presentation and just do that. We're not looking for anything fancy in terms of editing or special effects or slick production values when it comes to the assignment. And then Arpa is reminding me, so just to give you a sense of what will happen during the breakout session tomorrow, so you guys will be in your own Zoom rooms. We have three helpers, Janet, who you met today, John Lent, who's a professor here at Stanford, and Diana Gregg, who's a lecturer here, will be circulating through the rooms to see if you have any questions. Drew will also be joining us at 10 p.m., so kind of towards the end of the session. He'll be the main Zoom room, so you'll want to come into the main room out of your room if you have questions for Drew. And then if you guys get stuck or have a question and no one's coming to you or you just want to ask it right away, your two options are to either leave your room and come into the main room to ask me or we'll also be having Riley and Jenny keeping an eye on the Slack, so you can ask questions via the Slack and we'll try to redeploy one of the helpers to help you answer your question. We'll also have a fourth or fifth, I forgot, I've lost track, another helper, Jenny Milne, who couldn't join us for tomorrow's session, but she's agreed to do breakouts or office hours on the tomorrow afternoon and that'll be from two to three. And again, I'll send you all this in Slack and Canvas so that you have it in writing. So with all of that, does anyone have any questions so far on the assignment or something else for Drew that you just thought of now? On the presentation, when you say record the presentation, do you want to go through the slides and effectively provide commentary as if you were presenting? Yes, so I would treat it like a presentation, but instead of giving it in real time, we just record it and upload it to us. So yeah, it's just sort of like a short, it's just three to five minutes so you don't have to go into any great detail, but just sort of kind of tell us the story of what you did in the last few days at that point, what you will be doing so that we can assess your scenario and your thinking. All right, so with that, what I'm going to ask you all to do is to head into your team Zoom rooms just to at least say hi and introduce yourselves to each other. You can stay for longer. We sort of envision this as kind of today's lunch hangout. So stay longer if you want, but if you've got other things to do, that's fine. And if you want to start working, that's cool too. And we'll keep the, we'll keep this main session open for a while and we'll be available to answer any questions or chat about anything in the meantime. So thank you so much, Drew and Janet, for being here. You're welcome. You're welcome. Good luck. Go save the world, you guys. Go save the world. You can do it. Yes, and Drew, both Drew and Janet will be joining us for the final session as well. So we'll get to see what the finalists are up to.