Transcripts For CSPAN2 Energy 20240703

Buckeye broadband support cspan as a Public Service along with thesether television providers. Giving you a front row seat to democracy. [background noises] [inaudible conversations] [inaudible conversations] [inaudible conversations] good morning everyone. Welcome to the launch event for 202323 Agency International outlook. The director of the Climate Change program and i cannot tell you how excited i am for todays event. This is an event on a biannual basis. One of the things we get most excited about not just in the United States but the world. As we try to consider plans for our Energy Future. I have to say our colleagues at the eia gets harder and harder each year to think about the pace of Prospective Energy and think about the challenges. And im obligated to buy you ice cream. So thank you very much for joining us today. If youre watching live, there should be a question live on the event page. We will see some of the key outputs this morning from director and colleague angelina. We will talk about how policymakers, industry people, how Civil Society should look where it fits into the broader constellation. Thank you again for joining us and director, if you would like to come up. The podium to you, sir. All right. Yeah. All right. Good morning, everyone. Its an honor to be able to kick off our presentation of the International Energy outlook for 2023 and before i get started i just want today give a huge thanks to the eia staff, theres just enormous amount of effort that goes into doing the analys delivering, delivering reports so i want to thank them and i also want to thank joseph and the csis staff for hosting this event. I want to talk a little bit about what eia does. Among other things that means that we ar vested with the unique authority to collect energy data fm u. S. Industry and that data published. Its used by skeholders. One of the things that we do is use data intnally to inform our model projections and so we view our data as a critical source of infortion within the United States. The other thing is that by law all of our products are independent of approval by any other officer or member of the u. S. Government and we really prize that independence, its very important to us. The Energy Outlook explores longterm trends and Energy Supply and demand around the reworld. Okay, so whats new in this years report, well, youll see similar looking field. Youre going to see improvements in the narrative so i have a background in modeling myself and i think its really important that analysts and modelers be able to explain results and translate into a realworld context and the oy way to do that is to foc on e narrative. So theres that. You will see technical notes appear in the light blue boxes within the narrative and thats an opportunity t te a deeper tenical diver on particular subjects for readers who might bee interested. Inhiwe have 3 technical notes, there one focused on our electric vehicle projections, representation storage in the Electricity Sector and then our representation of global refineries we also emphasize the range of results around the cases that we that we model, again, similar to the adl and this idea we are also introducing new cases that focus on examining the capital cost societied with associated with zero Carbon Technologies. We have 16 different regions and we think they offer better geographic alignment. We have a brandnew oil and natural gas supply module thats been incorporated into our modeling framework so you will be seeing the results from that. We have increased the resolution in our electricity model. So we nowtr model Electricity Supply and demand across 288 separate time slices and thats really important to model wind, solar, battery and dispatch and russia whole scale invasion of ukraine. you will see a whole appendix where we go sector by sector and what assumptions we have made and how we informed our analysis. I want to talk a little bit about the case that is we model in the ido. The first thing i want to poi out is that we only model current laws and regulations and we freeze our consideration of current laws and regulations as of march of 2023. Okay,his isas looking at policiund the world. For United States in particular the resultst we present are from our annual gy outlook. The results will be same and those policy assumptions frozen in november 2022. These assumptions about policy carry through all of the cases that we model. Okay, getting onto the specific cases. We have our reference case. In the reference case we are assuming that gdp grows at 2. 6 annually. We assume that the prize of crude start at 102 a barrel. Varies a bit and ends up close to 102 a barrel again in 2050. We also assume that there are reductions in the cost of zero Carbon Technologies and i should mention those technologies are wind, solar, batteries and nuclear. And they can achieve Cost Reduction up to 20 in the reference ca the way we handle this is t technological learning, so e time the capacity of one of those technologies doubles, theres theres a reduction theres a red in cost. So second set of cases focuses on Economic Growth. High case its 3. 4 and i will say the macro cases have a big impact on the results because when you have high macro both that leads to high enduse demand and in turn requires higher supplies of energy and then the congress is true when you have lower macro growth it means lower enduse demand and, before, less Energy Supplies is required. Next we have our Oil Oil Price h trajectory. We have low and a high. These are formulated outside of the model framework and they become an input. So on the low case we assume that brink crude, high case, 187 a barrel in 2050. And then finally, again, the zero Carbon Technology cost assumptions, this is new to this ido. In the low case we at what the cost that was achieved for each of those technologies in reference case and then we look at a trajectory that t us 40 below that cost. And then the high case we just assume constant constant cost through the projection horizon. These are the highlights from this years report. The first is that increase in population and income offset the effects of carbon and emissions and i will providing details in a moment on tha regional Resources Technology s costs an policy and finally, Energy Security concerns, transition from fossil fuels in some countries although they drive increase consumption in others. Im going to give, you know, some highlevel view of that and angelina is going to add some additional detail. Theres some things that i want you to keep in mind. It looks like okay. Theres some things that i want you to keep in mind as you as youu look at these at these results. When we model these cases we take a deliberately restrictive approach in the ieo and the way i would characterize cases that are plausible but silver. Here are some of the assumptions we have made. As i said we only account for current policies and we are looking at policies that are legally enforceable, right, we dont model aspirations or targets unless theres a legally enforceable policy that backs backs it up. Second, we look at evolutionary rates of technological change that are based on recent history and then third, we dont consider sweeping changes and Consumer Preferences or major geopolitical event that is can produce change or shift trajectory of the system. Now, its certainly possible that those things can happen, entirely policy, we could get newsi policies, there could be unforeseeable events that we dont model and thats exactly why you should not think of the ieo as a forecast. Were trying to do something here. What we are doing is providing a set of policy neutral baselines that focus on the current trajectory of the Energy System and i think that that actually provides a really useful point of reference for decisionmakers against they canhi judge future acts and developments. Okay. The so this brings us to our first set of results. Across most of the cases we find that Energy Related to admissions continue to rise through 50 under current laws. So,h again, we have regional models, 16 h regions. Im showing the results aggregated to the global scale and the bands around the reference case show the full rangecross all of the cases that we model. So moving left to right, we have global versus domestic product rowhich is which is you cn tell its growing very rapidly, okay. H in the mide we havein primary energy usage, ain, you can see upward trend a then finally into the rig we have energyrelated co2 emissions in each of the 3 panels are due to high a low macro cases. They are setting the bounds on each of these. One thing thats interesting is as you look from left to right you notice that the slope of the the cone keeps decreasing, right, so gdp is growing the fastest and then primary energy and finally Energy Related co2 has the least slope. So to get some more insight we can further break this those 3 panels down into four panels and some of you might immediately recognize this as the terms inhe identity so, again,oving from left to right,e have global population, you notice theres no gray band therere because we assume oops, sry. One population projection that carries through all the cases that were that were melg. Next gdp for capita which is a rough measure of per capita annual income. Next Energy Intensity and next Carbon Intensity whi i the amount of carbons you get f unit of energy. The uncertainty bounds inhe two middle panels, again, are being set by the high and low macro cas and for Carbon Intensity not surprisingly by zeroCarbon Technology cost cases. If you take the product of the first 3 terms you get total Global Energy consumption. If you take thehe product of the four terms which is the way the identity is designed you get total global co2 emissions. You can see clearly that population perla capita they are increasing at a pretty fast rate and this makes sse. You can see at the same time we are getting we are able t use less dolrer value and for every unit of erg we consumer with admitting less Carbon Emissions and that brings us to the insight of the title which is the upward pressure of population and gdp tends downward pressure from reduced energy Carbon Intensity over time. Again, we can disaggregate further. This is looking att gdp growth rates by region in the model. Again, 16 regions. We have the highincome countries on the left. We have the lowincome countries on the right. And i will just point out that india has the the highest average gdp growth rate but it vari quite a while by region, so when i prese results at a global scale remember that theres all of this detail under the surface. We can also look at total energy and break that disaggregate that a little bit. Here we are looking at fossil fuels versus nonfossil fuels and what we find is that increase in demand in current policies drive steady growth and fossil energy but even faster growth in ennonfossil sources. So, again, you can see the reference cases aligned, the bands represent the the range across the cases. With fossil which is the black and gray, it start at 505 quads in 2022 and then it grows anywhere from 1 to 40 depending on the case and then with nonfossils, this would include all of the renewables and nuclear, we start at 133 quads but that grows anywhere from 70 to 125 by 2050. So wind and solar in particular are growing at a remarkably fast rate and, again, you can see that by this increase slope associated with the blue line. Okay. We can break it down a little bit further here. So we are looking at fossil versus nonfossil but we have broken that down to specific fuel types. So you see the stacked bar for 2022, the black outline represents all the fossil sources t gray outlines represents all of the nonfossil resources so weveot 2022 all the way to the left and a the other bars represent a snapshot across the cases i 2050. How eh of these fuel types is is chaing over over time. Generally what we find is that fossil fuels hold onto the share throug time but the renewables really pick up and and most of that Renewable Development is taking place in the Electricity Sector sopm we find that if you look at the Electricity Sector renewables plus nuclear combined represent roughly 55 to to 65 of global Electricity Supply in 2050 across, again, across the cases. Now, obviously theres a lot going on here at the regional level. There are regional pat herbs patterns and that will depend on trade patterns and the cost of global resources. Okay. With that, im going to go back to the highlights and turn it over to angelina la rose who is stour assistant administrator. Good morning. Im going to keep on with the trend of breaking things down and go into more details surrounding our highlights. I do encourage you all to take a deeper dive into our website following this event where we have a lot of data and analysis that we will be posting. But for now im going the walk you through some of the interesting finds that were made highlights starting with the first one about increasing population and income driving the growth and consumption Energy Related emissions despite energy and carbon intensities. So what this slide is showing Energy Consumption by sector. As joe orient today you all, the solid line reference case in a range the the area represents the range of productions from our side cases. So any Energy Consumption growth across all sectors through 2050 and across all cases. As you can see on this slide, the industrial sector shown in green which includes manufacturing, refining and other sub sectors has the largest share of Energy Consumption and also has the largest share of growth through 2050. The industrial sector hashe widest range of consumption across thes cases due to the broad range of industrial output assumptions across the cases and sectoral sensitivity to economic drivers. Ke the highest growth we see in the industrial sector comes from our highest case reaching 1. 7 year but even in our low Economic Growth case we see increasing windustrial Energy Consumption. So this slide is very similar to what we just saw but its looking at liquids consumption across cases and sectors. Similar to what we saw in the last chart, liquid consumption also continues to rise through 2050. And the fastest growth in liquid consumption comes from our industrial sector. Following use of the industry, like chemical production as well asas diesel fuel, construction d agricultural equipment. So those transportation still maintain largest share of liquids consumption. Its growth is tempered by efficiency gains and the shift toward electric vehics, however, overall theres growth in theal liquids consumption driven by the growth in industrial and transportation. So im going to take a closer look at the industrial consumption. This slide is looking focusing on industrial consumption in china and india in particular. So across the goal while we are projecting increasing Energy Consumption in the industrial sector we a seeing declining Energy Intensity. At a regional level there are two prevailing drivers of Energy Consumption in the industrial sector. These are industrial growth outputs which is a measure of Economic Activity and Energy Efficiency or eney intensity. So we see different trajectors in china and india. As you can see on the left, in china some cases industrial sector consumption declining or leveling off compared to india where we have growth in all the cases. In china, slowing industrial growth output aft 24 combined with Significant Energy deficiency gains slows and decreases industrial Energy Consumption in some cases. In particular, china is projected to significantly increase its production of recycled fuel which is significantly less than Energy Intensive. In india the growth and industrial growth output which more thanh triples in most cases and even quinttuples, its the main driver of that sectors increase in india. India specifically sees growth and Energy Intensive industries so primary metals, chemicals and not metallic minerals. Im shifting to the transportation sector. Theres a lot on thislide. On the right travel demand by mode in 2025. Index 20250. When we project travel demand its prepandemic levels. Loing at the graph on the left the tvel demand is growing, travel demand isov highly sensitive to changes in disposable income per capita as well as employment and there are several interesting findings at the regional level. Much of this growth is concentrated in india where both disposal income and employment has grown over the projection period. Regions with slower Income Growth such as africa continue to see growth and travel demand because off increases in inemployment but to a less degree. A in regions with both Slower Growth in income and employment such as western europe and japan per capita travel demand growth is limit. Globally travel demand p capita growth across all cases nearly doubles inwt the high Economic Growth case. To combine with growi population, this is a stron upward pressure on energy consumion. So now the graph to the right, travel deman for less efficient modes of transportation particularly air travel growth in regions as incomes increase. So rising income in several regions enables travelers to shift fro inexpensive but more efficient modes of transportation like two or three wheelers or buses to more convenient but less efficient modes like electric vehicles. You can see this particularly in china, india and other asiapacific regions and you can see on the graph of the right where we have growth like vehicles, first twoas panels and Slower Growth in buses and threewheelers which you can see in third and fourth graph. Aircraft travel which is highly sensitive to changes in income, increased in regions. SlowerIncome Growth such as africa. You can see in the yellow. Persistent growth compared to aircraft and travel. Efficiently within each of these modes of technology offset significant portion of energy anconsumption from the travel demand growth as well as the shifting towards less efficient modes of transportation. My next slide. Inimagine it. [laughter] okay. Here we go. Just as you all imagined im sure. Vehicles to grow from 1. 4 billion in 2022 to more than 2 billion vehicles by 2015. Wen see technological shift from combustion engines to electric vehicles. Globally evs will count for 29 to 54 of new vehicle sales by 2050 across cases in our projection and continued increase in ev adoption leads to peak between 2027 and 2033 in all cases. Looking at the ev adoption, battery electric vehicles in blue, hybrid electric vehicles in yellow pretty early in the Production Period and that kind of makes sense as plugin hybrids make more sense in the interim and battery costs drop out, battery electric are much more competitive. China and europe, largely range of results. The building sector shows a lot of interesting stories atse the region level. So this slide is showing residential and commercial per capita in india. India with significant gdp growth and population increase exemplifies the relatiohip between energies,ncome and Service Sector growth. Disposable income, extending Service Sector, increased in overall Building Energy use whh almost tripled by 2050 relative to 2022 across cases. Increasing more than any other Energy Source in residential and commercial sector. So to meet increase global electricity deman increases reaching total of 1 and a half to two times what it was by 20250. 20. You can see in the yellow shares. From 2022 to 2050 zero Carbon Technology thes make up between 81 to 95 of new global generating. So what this slide is showing Electricity Generation by fuel, so as expected given the capacity built i just showed you in the previous slide solar and wind show the highest levels of generation growth however, the last slide showed changes for 2022 levels and important t note that existing coal and natural gas, per plants continue to operate. Combine more than half of the worlds Electricity Generation capacity. By 2050 the fuel ander generation decreases t 27 to 28 of the capacity across cases so its the still aoteable share. While its ft or declining, decline in most of the cases we model. Natural gas is rising. Nothing compared to what we are seeing in solar and wind but bothth gas and coal are stable. That brings us to our last highlight and the role of Energy Related photo sill fuels. The first two panels even Carbon Technology is projected to accompany flat six line change. China and africa showed the third and fourth panels to growth and zero carbon and fossil based technology. Western Europe Energy secit situation favoring thera use of locally available resources such as wind and solncrease installationin and plan to build for these technologies earlier in the production. And andy at rapid growth in zero Carbon Technology is seen after 20 heavily influenced by assumptions of Economic Growth. In a china colt fire generation mix up 62 of electricity generated in 2022. Deeases less than 10 thughout the production. In all cases except theow zero Carbon Technology in the low growth case. Local resources are key in the asiapacific region overall. Electricity demand growth is the most rapid and local coal is cheap and abundant. And so will africa see significant increase in installations of zero Carbon Technology projection has been accompanied by increasing share of fossil fuel. As the region takes advantage locally available one fossil fuel in particular natural gas is an important part electricity generated in several regions of the world are projected to 2050. Power dissector continuing need for natural gas is a key component of the global trade and dynamic. Which is seen on the next slide. This slide showing net natural gas trade above the zero access net natural gas import below the zero access is not natural gas export. Notable on the slide is the range of imports from asiapacific and the range of a net export out of the middle east. These differences are largely driven by macroeconomic consumptions total Global Demand for natural gas differ significantly between the reference case by 2050 Global Natural gas reach 200 tcs and a reference case and grows to over 242 in the high Economic Growth case aboutco a 20 difference. Most of the demand occurs in china or consumption rises across all sectors particularly power sectors in lateric years n india drive significant natural gas import growth in the asiapacific region overall because of the growth in its industrial sector. So, as regions run out of costefficient resources theyls not import natural gas to regionsthat have the cheapest resources. As mentioned earlier in his remarks the ito uses our most recent annual Energy Outlook for the u. S. Projection. The u. S. Which is part of the north america grouping in this graph supply of natural gas on the chart is what we have published in march. Although north america is the te second largest source of plan a net basis from all of the regions only limited growth in supply between the reference case the High Economic case is published an annual Energy Outlook. Given the lack of Significant Growth from United States and the macro case the limited growth from russia the middle east role is a natural gas a player increases significantly in the High Economic risk case. Im going to leave us with her three highlights. I want to thank youou all for yr attention. Thank you again for hosting this event thank all of her analyst and modelers for all their work in making this the bestng yet. Thank you. [applause] as we get settled please let me thank angelina for a very helpful description. I said at the beginning of this, this document tells stories and it is so hard. That alighted the fundamental and quantitative work that comes into modeling these different sectors of the economy. These different regions. Thank you so much for coming today. Our colleagues online or colleagues here in the room if you want to use the event page to print questions were happy to incorporate those on a rolling basis. But i want to start with your early message. This is not a projection precooked is not a t forecast. It is a set of projections. In particular eia has always had a practice of saying base Case Scenario with those laws on theg books today. Which is separate from the ambitions of the governments around the world related to Economic Growth. The composition of the vehicle fleet or Greenhouse Gas emissions. When i look at the results i say old man, this is kind of you and Energy Addition and not a transition scenario is that the right key take away . How do you guys recommend Global Public policy makers do you look at the scenarios or interpret the outcomes has crafted . Looks great question that always come back to the context any time to look into modeling exercise or outlook its very important to understand what were the assumptions that went into it . We are taking very particular approach here where we are assuming a strict interpretation of current policy. We are again assuming evolutionary rates of technological change. No major surprises that informs thems projections. If i were to make an analogy the global Energy System is a car were basically looking at what happens when you shifted into cruise control. Where did we end up . We do explores the key sensitivities and models to different cases. But looking at it, as a whole that is the perspective we take. Cooks the other weekend i was reading emersons a lecture on the american scholar. Hes got this great line in there the duty of the scholar to guide by showing facts. Which facts are coming out of this that you think are important for the general public and policymakers to understand the Economic Energy future . The biggest thing is we think about energy we all think about perspectives our own Life Experience when we are interpreting that news a receive whats goingin on. With an exercise like this is informed by data. Its a very careful exercise to look across the world and to see what is happening. Sometimes i think in developed countries we forget about how muchab development is actually taking place. For me, one ofe the key takeaws is as governments explore the loop carbon futures just know there is a backdrop of continued development. That is putting pressure on energy demand. That informs ourng projections. We are seeing steady or increased use of fossil fuels. But also rapid growth of renewable energy. I think the clean energy story is taking place in the Electricity Sector is being driven by solar and wind. There are other groups that look at global g forecasts. Do not want to get into a modeling debate but help us understand even if you take from this a presentation as well as our conversations the character of the Energy System Going Forward is changing rapidly in your results as well. It is just there is this around the world for energy in a costeffective way. Help us understand help the audience understand if another modeling exercise another set of projections is going to be this decade, going to be the next decade. What differences are those what difference is that showing us . One thing to keep in mind we should expect to see big differences across outlooks. I cannot emphasize enough how much uncertainty there is. I think there is always a lot of uncertainty when you produce an outlook like this. I think we are entering higher uncertainties. The expectation should not be look across outlooks and see the same thing. I think when you see differences thats healthy. I would be concerned that they all converge to the same number. I spent a lot of time over the last year going back and looking. Weki have done a lot of history without a lot of projections. It requires humility. I think. Of all the outlets are saying the same thing. We actually have a problem. I think diversity which you see across the outlooks is healthy. Just to give you an idea of what drives some of those differences. Even if you are looking at another outlook and there is a scenario that looks similar to eia, you have to look at how its policy interpreted. I go back to what we did strict interpretation of existing policy thats legally enforceable. What did they assume about Economic Growth . What did they assume about Technology Innovations question at one of the cost pathways for renewables and other technologies lookwa like . What do you assume about technologies that might be on the horizon that are highly uncertain . It also Consumer Preferences. We are largely doing Economic Modeling here. Theres a big piece of this with existing policy we are incentivizing consumers and nobody knows exactly how the going to respond. I want to touch uncertainty in a couple ways. As a hard version of what to ask. When i look at the various projections you give us this a shaded envelope. I look at that and go on about this enough uncertainty. I do not know if that is it wide enough ban in particular on the downside of Greenhouse Gases. As an external. Maybe we can dive into an example . Theres a rapid growth 40 the Chinese Market is now ev. The u. S. Is five 7 . Some people will tell you somewhere around 10 is eight tipping o points consumer will ship rapidly. If that happens you might see a lot less fossil fuel. Might have to go down a lot. How does this structure model those dynamics . One thing i want to acknowledge upfront as we do show those uncertainty bands. Thus on a full scope of the uncertainty. Theres a wide universe of things that can happen. We are very clear how we approach it what assumptions we have across the cases. We are taking a narrow path through this pretty wide universe. Just as you are not making a forecast that is not a probability . Correct. Absolutely. There are wider than that it depends what you touch. If i was trying to interpret our outlook in the context of others think it of the projections on the same chart because different outlooks make different assumptions you are exploring different parts of the future. Thats healthy exercise. Let me get to ev. Park site learned a lot. Sure. I want to give a little bit of perspective. Im going to cite some of the numbers she already gave but its really important to understand. First of all passenger travel demand is going to increase by Something Like 65 to over one 100 by 2050 across the cases. That is because theres more people but also they were to travel more miles as theyth gai. Angelina also mentioned right now we areig at 1. 4 billion ligt duty vehicles on the road it. Thats going to grow to about 2 billion by 2050 and most of our cases. You have to and with electric vehicle its not pure economics. Theres also Consumer Preferences. We have some representation of that in our model. Policy interpretation also matters a lot in terms of what you project from where we are right now. As angelina said what we are finding is evs are projected to make up about 30 55 by 2050. But theres a lot of uncertainty. Islo it possible things can unfd in a way where we end up with higher projections . Absolutely productive you one example we assume again evolutionary rates of technology innovation. We lookof very carefully at the prevailing cost of batteries. We look at how the cost of those lithium ion batteries has declined over time the project and for the future. If theres a new battery ugchemistry, some new breakthroh all bets are off. Things can change. Week think about modeling, here you doing something youre modeling Consumer Choices, right . Like i dont think we really know. What dynamics go into like around the cost curves, performance, social track. International Energy Modeling system with her Energy Outlook we have more of a Consumer Choice model we have a simplified version and the model used to produce international outlook. Its not a full Consumer Choice model but its also not just about cost. The four factors that go in and this is and when the technical notes youve got the cost of the vehicle. Theres the cost to drive it. There is also a model model availability. , ev models are out there relative to internal combustion engines and fuel availability. As people see the availability of more models they see theres more infrastructure available to charge or refuel they are more apt to make that purchase. This is a standard methodology to look at vehicle update. I always wonder i dont think a Car Dealerships a place to make a rational decision. Lets maybe i shift its good to talk about specification but were running short on time a lot of people want to know about your call on production. Let me put that in a different context. To energy cases that affect oil prices high and low. I did not see any big differences in the m results. Can you help us understand what we learn from those two cases withre respect to oil market and u. S. Producer . The insights helps us is important in this policy conversation were having in washington. Sure. As far as oil demand goes, what we see is total liquids right now is rent 99 Million Barrels per day. What was see by 2050 across the cases we model very roughly 10 40 im increase in demand r liquids. The u. S. A piece of that remember the u. S. Results are fixed we have the animal the annual Energy Outlook. What we found there is we remain a net exporter of petroleum across all of the cases but theres a pretty wide variation its anywhere from half a Million Barrels a day all the way up to nine. Okay. Let me ask you about the future of these exercises. So over that last or had the real honor of hosting a lot of people different forecast products or different projection products. Some they are calling for. How do we of all these tools . From your academic background youve worked out a model. I am interesting how are you thinking about involving these tools to inform Public Policy conversation and better understand what you think about these critical mineralth challenges that are really important for the solar and wind you see in this. How do you think about making these results more transparent, more available to the public or policymakers we get a better understanding of what these models and sinners can teach us unlikely open thoughts how we keep innovating make sure we are meeting information. Its a huge questiongu how mh time do we have . [laughter] i guess a few thoughts for the Energy System is in a period of pretty rapid changete. That creates a challenge as Energy Modelers but we need to make surers our model stay uptodate with what we see happening. Very quickly i will so that modeling exercises we do we try to be as transparent as possible i do want to say that upfront. If you want to dig into what we have done you can read the narrative you can download the data table you can read all the documentation for the modules you cant request a source code and planning to make the source code publicly available over a hundred open license but were trying to be as transparent as we possibly can. So there is that. We are in the process of retooling our model. I announced earlier we are taking a break from the annual Energy Outlook so we can add the low carbon pathways we need to model we are going to be doing that. But, on eight separate effort we have a nextgeneration model. The key is by time to internal and external stakeholders we need modeling to be nimble and flexible. We need to be able to look at a wide range of scenarios and the consideration we now need to bring to the model are increasing you mention Critical Minerals. That is something we are looking at. I can go into Critical Minerals a little more or if you want to pivot . There is with Critical Minerals were currently working with u. S. Geologic survey. Theyve done a lot of work look at supply chain risk so we are collaborating with them. We view ourselves as experts in producing the energy projections. They understand supply chain better we are working collaboratively to figure how we can build critical mill mineral supply into our models. I would say trying to build the supply chain into the modeling framework would be part of this effort to build a new extra generation model. Do we have enough information . It is the information keeper for oil and Gas Production in the u. S. Do theyy demand a . We do not have an analog on the mineral side. We have enough information to do a meaningful analysis the way its used on the gas side . Is something we have to evaluate. My sense is you always work with the data that you have. It helps to highlight where there could be particularly important risk to consider than that is valuable. I think we have to look at it more carefully as we build it. Is the next question from online thats really interesting. Especially about learning. How do you embark every year taking a pause on the ato to view the tools that we have. How do we make sure you are learning from past successes and past failures . Quickset is a goods ur question. We are in contact with stakeholders but we often have workshops with her nextgeneration modeling effort we are actually about toowe hava series of engagements with external stakeholders so we can learn fromm them. We also do model benchmarking worked with the Energy Outlook we have the retrospective report will be go back and look and see how welo did. We are actually in the process of trying to expand that work ourselves. I personally tried to go back and look across past projections and see whatec do we get right . What did we get wrong and how can that inform our projections moving forward . You see that being a process that can get formalized . Theres lots of fancyth models d tools that allow us to take in quantitative information or change projections. Based on what we learn about over time. You think that something to formalize . Yes absolutely. One of the things we did in the annual Energy Outlook is we had uncertainty cones. You can come up with different projections by changing input in your model what they do is look at the difference between what was in the reference case and what actually happened. Once i hear are the errors you can distribution and you can use that to derive that says you may or may not believe a reference case. But if you look at past differences this is where things could head. So that is just one example. Theres a lot of different ways you can formalize that, the consideration of that. As you think about putting these scenarios together you think about the numerous i dont know whether i buy the simulation or not and that in the source code you need to learn one thing with absolute precision and accuracy to inform making better projections for our Energy Future what would it be . I get access. We can get access to the matrix. Exactly. I think the biggest challenge we faceig is the human behavioral piece of it. We can characterize cost data that is uncertain. I think we do not have a good sense for as we offer novel technologies both consumers take them up. How can personal preferences influence political movements. You know, like how does all of that aggregate up in a way that informs whether we are going to when we end up with the policy . Do consumers prefer these technologies . I think that is a really huge challenge we struggle with. We do the very best we can with the data we have we do not have a good understanding of how human beings are going to respond to external events. Two new technologies and so forth. Quickset kind of a great one thing weve been thinking a lot is ours Tech Innovation is probably going to come from the bipartisan infrastructure lot in the ira. How quickly it does that defuse around theou world is it at an economics question is a Public Policy . And there is just a huge veil of uncertainty around that question. Absolutely. That just brings me back to the earlier point that isar why it s important we should not expect to see outlooks conforming to the same results. G there is all this uncertaintye make different assumptions that you get this array of outcomes. We all get surprised by things right . We are running up against our time window. I just want to say we are very pleased to talk about this today. Its an interesting in some ways a provocative set of results that you found. Its going to inform the conversation not just here in washington but around the world so thank you joe, thank you angelina also those online know many subject matter for what is unfortunate that lamest lunch party i can possibly imagine. [laughter] but allow me too extend our appreciation for your hard work and your dedication and Public Service. Thank you all. [applause] and i wish you well. Everyone is joining us here in person as well as online. 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