 Good afternoon, everybody. My name is Megan Lowry. I am a media officer with the National Academies of Sciences, Engineering, and Medicine. Thank you for joining us this afternoon for a webinar on the report that was just released this morning titled Greenhouse Gas Emissions Information for Decision Making, a Framework Going Forward. You can now download a copy of the report and other supporting materials at www.nap.edu and we'll also chat that link out to you. A recording of this webinar will be available on our website in the coming weeks. For those of you who are not familiar with the U.S. National Academies of Sciences, Engineering, and Medicine, we are private nonprofit institutions that provide independent objective analysis and advice to the U.S. to solve complex problems and inform public policy decisions related to science, technology, and medicine. For each requested study, panel members are chosen for their expertise and experience and they serve pro bono to carry out the study statement of task. The reports that result from the study represent the consensus view of the entire committee and must undergo external peer review before they are released, as did this report. Before I introduce a few members of the committee that are joining us today, I want to just go over a few reminders. Please note that this webinar is scheduled to last one hour, so we'll start off with a presentation summarizing the report by the committee and then we'll open it up any questions you may have after they're done. For questions, we will be using Slido, so you can ask a question by typing it into the box that is either underneath or to the side of your video player and you can submit a question at any time during the presentation. So now I'd like to introduce the members of the committee that wrote the report for joining us today. We have Don Leppels, chair of the committee and emeritus professor of atmospheric sciences at the University of Illinois. Gabrielle Dreyfuss, Chief Scientist Institute for Governance and Sustainable Development. Ann Marie Elderling, retired from the Jet Propulsion Propulsion Laboratory. Fiji George, Senior Director of Climate and Sustainability, Senior Energy. Kevin Gurney, professor of School of Informatics, Computing and Cyber Systems, Northern Arizona University. And Angel Shue, Assistant Professor of Public Policy and the Environment at the University of North Carolina at Chapel Hill and founder and director of the Data-Driven Environmental Policy Lab. And with that, I will turn it over to Dr. Leppels. Good morning, everyone. We're going to go into the slides here. So the next slide, please. The science is clear. Climate change is one of the most important issues facing humanity and its impacts are being felt already around the world in many different ways. These changes in climate are almost internally caused by the emissions of certain gases and particles into the atmosphere that are increasing the resulting concentrations. Particularly important are what are called the greenhouse gases. We will particularly focus this report on the well-mixed greenhouse gases like carbon dioxide and methane, but it's also important to recognize that there are many shorter-lived gases and particles that also have an impact on climate and need to be considered in future inventories. And many of these gases also have an impact on their quality. Next, please. The temperature in the planet, as we all know, is increasing dramatically by roughly 1.1 degree centigrade, 2 degrees Fahrenheit, over the time period since 1900. So now, next, please. The cause of this, as I mentioned, is the forcing that is driven by these gases and particles in the atmosphere. The graph on the right just kind of indicates that. And it is the emissions of those gases and information that is needed by policymakers in order to make the right decisions about how to reduce future climate changes. Next, please. So there's a number of motivations for this report that kind of led to the National Academy deciding to do this. One is that there is an increasing demand for a range of users, from a range of users for trusted information about greenhouse gases, because multiple sectors and geographic scales, going all the way from local cities, industry to regional levels, states, and so forth, and national and global. And the report attempts to cost all these different scales and looking at these questions of emission inventories. New approaches for quantifying greenhouse gas information are being developed all the time that aim to address this increasing demand. And we want to make sure that this report addresses those. And there's a growing and rapidly evolving institutional landscape, including public, private and academic entities seeking to provide better greenhouse gas information. Next. So the committee that was developed by the Academy is charged with developing or considering approaches that are already being used to develop the Virginia greenhouse gas emission inventories to discuss the potential uses and limitations of these approaches. And then to develop a framework to evaluate emissions information and inventories that includes guidance for policymakers about their use and decision making. Several case studies are considered to demonstrate how the framework could be applied to evaluate emission information and inventory approaches and to identify strengths and opportunities for improvement in each case studies. The focus is on approach and data sets here. The committee was not at task to evaluate the accuracy or the utility of individual data sets in these analysis. To the extent possible, we identified ways to improve methodological, methodological, transparency, sustainability and continuity of relevant observations and product confidence in global anthropogenic greenhouse gas emission inventories. I want to mention the study sponsors, the Benovicus Foundation, the Heising Simons Foundation, and the National Academy of Sciences, Arthur L. Dayfun. Without them, we could not have accomplished this report and we greatly appreciate their support. Next, please. We have 10 members on the committee, including myself. Most of them are here today. And are available to address questions. I want to thank all of these members for the extensive amount of work they put into this bass track report. We basically had two months to write this entire report and then have it reviewed and revise it again before it was published. So this is an extensive amount of work at a very short amount of time and in a very significant effort. The committee gathered input for this report from a variety of other scientists and organizations that are written submissions and community meetings that were important in this process. Now I'm going to turn it over to Kevin Gurney for the next part of the presentation. Thanks, Don. So GHG inventories, greenhouse gas inventories represent a broad collection of efforts and approaches aimed at best estimating greenhouse gas emissions at varying scales from the globe to nations, cities and even down to individual factories and buildings. They're used by a range of stakeholders, including policymakers, the scientific community, businesses, the public and the media. Among their many uses, they're critical elements in the establishment of greenhouse gas emission reduction plans, tracking those emission reduction efforts and then assessing those emission reduction efforts when they're completed. This report reviewed and assessed three very broad approaches that are currently used to develop greenhouse gas emissions information. And on this slide you can see on the left activity based approaches, the most common approach currently used by practitioners and policymakers and probably most familiar to the public. But there's also in the middle here atmospheric based approaches, which have been pioneered in the scientific community and are seeing increasing use within the broad GHG emissions information landscape. And then finally on the right are a collection of very new approaches that we refer to as hybrid or integrated approaches, which combine the previous two and also avail of new methods such as machine learning and many nontraditional data sets. So I'm going to describe each of these in detail in the next three slides. Next slide please, thank you. So the activity based approaches comprise a wide variety of different techniques and methods, but share a very common general form in which data representing human activity leading to emissions are operated on by a factor that turns that activity into an emitted amount. A simple example of this would be, for example, a power plant. You could take fuel consumption at a facility that would be the activity data, multiply that by the carbon content of the fuel to give rise to an estimate of the CO2 emissions coming out of that activity at that power plant. Activity based approaches are increasing in complexity, such as the use of vegetation models estimating the net CO2 emissions from photosynthesis and respiration, or for example building thermodynamic models which estimate heating and cooling requirements from building and occupant parameters. So even though this very general common framework is used, it is increasing in complexity. The best known activity based greenhouse gas emissions inventory is the reporting by countries to the United Nations as part of the international climate change negotiating process, something we refer to as the UNFCCC inventory process. However, there are over a dozen global national greenhouse gas emission inventories developed within the scientific community, some using advanced techniques and offering a greater breadth of information and data. Activity based approaches are known for their actionable detail, functional detail that includes things like the sector emitting greenhouse gases, identification of individual fuels, and a lot more detail on the emitting assets themselves. Next slide. Now atmospheric based approaches are distinct from activity based approaches in that they critically rely on atmospheric measurements of greenhouse gases and how they're moved and transformed through the Earth's atmosphere. Because it's difficult to measure greenhouse gases everywhere in the atmosphere, atmospheric based approaches are often supported by activity based estimates to help guide outcomes. As with activity based approaches, there are a wide variety of atmospheric measurement techniques and measurement platforms used in quantifying atmospheric amounts, including satellite based measurements, aircraft, and ground based instruments. Sometimes atmospheric measurements can be used more directly to estimate emissions, but they're often interpreted through a model system. The most common of those is an atmospheric transport model that will move those emissions through the atmosphere and transform them where needed. Next slide please. Finally, these hybrid approaches or integrated approaches. These are newer with only a few early examples. Hybrid efforts attempt to more deeply integrate the two previous approaches, including integration within activity based approaches because there are many or integration within atmospheric based approaches because there are many, but also across and combining both of them together. We also include here new work using non traditional data such as satellite optical imagery, new modeling techniques represented by machine learning approaches and dispersed activity data such as from handheld electronics or crowd source data sets. All of the early integrated attempts suggest considerable benefit by recasting greenhouse gas emissions information production design, whereby a more central generalized model system would ingest a large variety of observed quantities and arrive at the best estimate of emissions possible, reflecting the detail and information rich qualities of the activity based approaches, the accuracy and integrative ability of the atmospheric based approaches and the global reach and efficiencies presented by non traditional data and some of the new machine learning style modeling systems. Next slide. So here I'll hand off to my colleague, Dr. Gabrielle Dreyfuss. Thanks, Kevin. So with that overview of the approaches, it's important to recognize that there are a number of structural and institutional challenges in the current greenhouse gas information landscape that have limited the usefulness of emissions information and decision making. For example, the institutional landscape on local and national levels lacks coordination with independently produced information being housed in different locations and organizations. And this lack of a framework for users to easily navigate and find relevant useful information puts the onus on users to know what resources exist and how to find them. In addition, each of the three approaches has its own technical challenges limiting their usefulness. Activity based approaches, for example, rely on activity data and emissions factors that may be out of date or not representative for particular sources or geographies. Atmospheric based approaches depend on measurements and models, each with their own potential gaps and errors. Additionally, these approaches may not be able to separate and attribute different emission sources. Hybrid approaches are newer and have a lot of promise and potential, but the use of some digital technologies face challenges of interoperability, transparency, data quality and bias. Next. So the committee developed a framework to evaluate greenhouse gas emissions information that consists of six pillars or criteria. These are intended to help users assess the relevance, credibility and usefulness of greenhouse gas emissions information writ large. This is from the data individual data sets and inventories to larger systems of information. And these pillars, six pillars are really a way to think about and assess how that information meets users' needs of our essentially fit for purpose. So for example, the first is usability and timeliness, how responsive, relevant and timely is the information to decision maker needs. Next is information, transparency, really a bedrock pillar. So it's how available and traceable is the information, including the sources, the data and the methods. Next is evaluation and validation. This is really a quality metric, but taken at this again, a larger level to ask really have the approaches and data been appropriately evaluated and validated for their intended use. Are they fit for purpose in terms of accuracy, for example? Next is completeness. This is again with respect to the particular product over what time period, geographic domain and for which sources was the information collected. Were multiple data sources or approaches used to support the conclusions about greenhouse gas emissions? And are the sources, gases and particles and the geography complete in the context of the intended use? For example, a city inventory versus a national scale inventory. Next, and this is a really important one to differentiate from communication, is this concept of inclusivity. It's really asking who was involved in generating the data? Have the approaches and the resulting data involved locally based researchers and have they benefited from stakeholder input and expert review? And finally, communication. This is really a question of how this information, what it can do and what it can't and how it should be interpreted. Are the underlying data of methods and uncertainties clearly communicated is a really critical issue here in the communication. So this framework is not just for users, but also can provide guidance to researchers for designing more useful and trusted data and information. Next. So here we provide a summary of how the current capabilities of the three approaches that Kevin described generally perform relative to the pillars. I really want to emphasize that this is taking this high level based on the qualitative rankings based on the committee's expert judgment for each of these approaches, noting that taking into consideration that how they're applied at global or national scales and really noting that there are a number of individual products and information products that use these approaches at all sorts of scales. But we thought that the rankings would be useful to provide a kind of comparison of these different approaches and identify the strengths and opportunities for improvement. And we use kind of a tough love approach here. So it's intended to be constructive criticism where if something was ranked as a low to medium, we might put low just to emphasize the opportunity there. Next slide. So when applying the framework and pillars to assess greenhouse gas information, it really is important to consider the context of the intended purpose of each case and asking questions like is the information clearly described and communicated in a way that fits the intended purpose of the information product? Is the information usable and timely for its intended audience? And does the quality, reliability and accuracy of the information meet the needs of its intended purpose? That's really the evaluation and validation pillar. In the report itself, it includes several case studies that demonstrate how the framework and pillars can be applied to different information products. And it's really done in a case, again, does a product fit its purpose? I want to emphasize that this is a really small sample. There are many examples out there. And it also represents a snapshot in the very short time in the information that was available during the time that this committee was doing our task. We selected these cases to consider a range of spatial scales, use cases and approaches. So I encourage you to take a look at the report next to hand to Anne-Marie. Great. Thank you, Gabby. Hi, everyone. We want to take a moment here to step back and look at these pillars in the context of the full process of using information and decision making. So just to remind ourselves that these pillars are critical, but they may be applied in different ways at different moments of this iterative process. We have the development of these greenhouse gas emission inventories and information that feed into decision making, which itself is iterative planning, tracking, assessment and verification. These should feed into mitigation and action. And once these actions have taken place, we'll want to go back and reassess where we are with the greenhouse gas emissions inventory. So the pillars that we've described in this report may be applied to different levels at different stages in this larger process. And at this point, we'll go to the next slide and we'll start introducing the recommendations that were made in the report. The report includes eight distinct recommendations. The first one here is just to remind ourselves that all of the work in the development of this information and evaluation should strive to align with the pillars. So we want to think about this, not just in terms of the data evaluation and the validation of the data example, for example, but in the process development, as you develop processes, think about these pillars. Am I developing a process that's as complete as possible? How do I enhance the inclusivity and even institutions that are institutions are designed in ways that help us align with the pillars we've described? And the second recommendation I want to discuss is about this concept of a clearinghouse. The committee agreed that information being in disparate places can make it quite hard to find and hard to compare. There's as we discussed many barriers identified and we believe that some sort of a coordinated repository or federation of repositories could help address this weakness. As you'll see in this set of text on the right, there's ways we could design such a repository to really help align with the pillars. For example, traceability should be improved as well as standardization. Once we have a repository, it could be an opportunity to have good documentation and include evaluation metrics both qualitative and quantitative. Updating the input data as it brought into the repository could be valuable. And we're not saying here we should toss aside everything that exists, but we should build on the institutions and the tool sets that we have enhance them so that they can meet this goal and become more coordinated and perhaps look to lessons that we have from the air quality and weather communities who built tools and institutions that meet some of these needs. So with that, I'm going to leave it to my colleague Fiji to pick up on the next recommendations. Thank you. Thank you. And Murray, I'll continue with the committee's recommendation on transparency and communication of data and methods. So decisions based on GSC admissions information will have significant implication for government policymaking, business and financial outcomes and community and household planning's arguments about validity of data sources could delay action and also inaccurate information could lead to costly errors in determining how to mitigate emissions. Hence, to foster trust in GSC admissions information, data providers should clearly communicate the data and methods underpinning their work as well as the uncertainties in the findings, in particular transparency is essential for knowledge and resource sharing in the global community and specifically to capacity building in regions with less GSC information, example, the global south. The repository, as mentioned earlier, could be the place where GSC information is hosted, documented and clearly characterized, maximizing the use of GSC information. This clearinghouse could establish the standards and practices aligned with the pillars for users to quickly grasp the quality of data sources, such an effort through the support and and integration of information from existing efforts, as Anne Marie mentioned, should not replicate established efforts. Next slide, please. So our next two recommendations deal with a granularity and accuracy in the development and presentation of GSC data to meet the GSC inventory needs of cities, states, provinces and corporations. These entities are in need of GSC information at a much finer granular scale to enact mitigation policies and business planning. Enhancing source level details, for example, characterizing the full distribution of the emission sources would also strengthen the completeness of the inventories, especially with respect to methane emissions. Information at a finer space and time scales has the potential to improve methods, pilot new observational capabilities that could be scaled up. The federated repository or clearing house recommended by this committee would be intended to bring information across all spatial scales into a central location or coordinated set of locations. Now, there is a need to improve representativeness and global resolution of the underlying GSC input input data to ensure and strengthen the accuracy of GSC information. Many of the underlying data to estimate GSC emissions are based on large spatial averages or sometimes outdated or unrepresentative data from high capacity parts of the globe. The lack of dynamic updating of emission factors hinders the opportunities to ingest new data from novel technologies or approaches into the inventory level. More specified and granular information that relies less on broad averages or data collected from other parts of the world could generally improve data accuracy and serve local decision makers. Next slide, please. So the next recommendation deals with the urgency to operationalize institution capabilities. The current pace of operationalizing new research and approaches is too slow to support decision useful information to meet climate goals with urgency. Accelerating the transition to operations will require lowering existing barriers, making new data products more immediately usable. These include efforts to collect more activity data in countries and regions with limited research, enhancing inclusivity and training of local stakeholders and scientists, and improving the infrastructure on high volume data injection and processing. Engaging decision makers and stakeholders is an iterative process, and this will lead to data and findings that are more useful to the climate mitigation policy. The Clearing House or the coordinated mechanisms recommended about, along with the alignment with the pillars, should make new GHG information more useful more quickly. With that, I handed over to my colleague, Angel. Thank you so much, Fiji. I'll continue along with the committee's recommendations if we can. Oh yes, the next slide. So the committee found a lot of promise out of the three approaches that Kevin described, the atmospheric base, the activity base, as well as the hybrid approach. We found a lot of promise in this hybrid approach, but yet they're the newest and there are still few examples, and so more research and development is needed. So we recommend striving for hybrid approaches to produce greenhouse gas information that could possibly be more accurate and comprehensive. And so these cross-techniques or hybridizations of traditional approaches could provide more granular, more complete GHG information. For example, bringing together traffic data, fuel consumption information, vehicle fleet data, along with atmospheric observations could help yield more granular estimates of transport-related emissions. And some of this work has already begun with data assimilation, data fusion and machine learning, but we find that there are more opportunities to enhance synergy, particularly between the greenhouse gas monitoring communities, the air quality and meteorology communities to enhance data collection and analysis to facilitate the development of these hybrid approaches. And so integrating more traditional activity and atmospheric-based approaches could overcome the weaknesses of each approach used in isolation. Striving for hybridization would entail improving holistic greenhouse gas monitoring across various scales and capacities. So we mentioned that there are just a few examples, and it's largely because it's difficult to bring together the right data providers and scientists who can do this type of integration. And so that brings us to our next recommendation. In order to improve the timeliness and usability of information, the committee recommends that information generators, stakeholders and decision-makers engage in an iterative process to develop greenhouse gas emissions information. And so this cycle of co-production of iterative communication is illustrated here on the right. The current time lag for integrating research developments into decision-making has hampered sound decision-making, and incorporating decision-maker input is critical to develop information that is responsive to their needs. And since the primary aim for improving GHG quantification is to guide decisions across all scales, information has to be made available in ways that decision-makers can readily use. And while this may sound obvious, what we're seeing and what we heard from the various stakeholders we consulted is that there are huge time lags and gaps. And so sometimes the most recent inventory data that might be available is already a year out of date. And that really limits its utility for policymakers who may need to have more real time or up-to-date information to guide decisions. And so improved communication between communities of scientists and end users would enhance the utility of greenhouse gas information and data. And we think that our other recommendations, such as the clearinghouse or a federated repository, having different data nodes connected together could help facilitate investments and systems to support an iterative process and to bring these disparate communities closer together. If we go to the last slide please. And so just in conclusion, the report examined both current efforts and future opportunities with the goal of pushing the global community forward to make decisions about greenhouse gas emissions. We highlight the important role that new approaches and innovations should play in the development and the use of greenhouse gas information. And we really see this as just a starting point to spark conversation with the global community because there are many different potential directions to explore. And again, we had a very tight time to develop this analysis and develop these recommendations. And so it only reflects a very narrow snapshot in time. And we know that the landscape is rapidly changing. There's more data and new methods that come on every single day. And so this is really just meant to to spark some conversations about where to guide future efforts. And so with that, I'll pass it back to Don to close this out. Thank you, Angel. So thank you all for attending today. And before we go into the question and answer part of this, I do want to mention that you can download the report at NAP.edu. And I want to once again, provide a special thanks to my fellow team members, committee members for all the extensive amount of work they did on this report, and also to the National Academy staff who we could not have done this without them. They were they were wonderful to work with and and and also put in a great amount of time in in completing this report. So now I'll hand it off to the staff to facilitate the question and answers. Well, thank you all so much for that great presentation. As Dr. Raul said, we're going to now open it up to questions. So as a reminder to submit a question, you can just type it into the box that is below your video player or perhaps the side. And while you're typing your questions, I'll just note that you can access the report if you haven't already using the link that is pinned to the top of your video player. Thanks. So our first question today is as the COP 27 meeting approaches, what are you hoping that leaders and scientists attending the conference or watching it closely will take away from your report? If just opening it up to any of us to talk. So a number of things were mentioned in the slides that really will be very useful in that aspect, particularly the six pillars and how they can be used to strive to look at the existing data sets and and provide a way for the COP 27 member countries to all kind of align themselves relative to those those criteria. And let me I'll just add a couple of thoughts on this. I think that by providing a framework that can be used to evaluate the many, many existing inventories that are out there, we hope that COP 27 leaders that gives them support for being both better consumers of that information more discerning consumers of that information and understanding which of the many inventories out there offer what aspects. And that I think leads to this idea that, you know, better data, more open data, more diverse data leads to better decisions ultimately. And if I could just add right now is a particularly critical time for the COP and the UNF triple C process and that six months ago we started the global stock take efforts and that's a once every five year exercise by which all the parties in the UNF triple C and now increasingly the group of non state and subnational actors that have also pledged their own climate efforts to submit data to demonstrate what they've done what progress that they've made. And so we're also hoping that this report and recommendations can lay out some areas of needed investment, particularly at the subnational and non state levels where data is particularly heterogeneous and it's not necessarily centralized and disparate and difficult to pull together. Great, thank you both. Anyone else from the committee? All right. Our next question is how is the recommendation for a clearinghouse complementary to the UNF triple C? Is there a specific body or agency that could coordinate such a repository and how would capacity building take place for this? Sure, I'll start us off. We want to make clear that a clearinghouse doesn't necessarily mean a single entity. It could be a federation of many different entities, but funneled through maybe a central node such that users can more simply access the data. But I think we imagine it being supportive of the UNF triple C process, but obviously clearly separate from it since the UNF triple C process is fundamentally a political process or repository in our archive would be independent of that, but could be very supportive in that, for example, countries that currently struggle to submit inventories to that process could find both the information needed to assist them in that process. And to your point about capacity building also find aspects of capacity building by having lots and lots of information about how the how these data sets are put together, what are the necessary ingredients and methods? Great, thank you. Another question about the clearing house recommendation. Can the clearinghouse be adapted to identify the increasing risks stemming from an action and recently deliberate climate counteraction? So I'm just going to take a step back and say that the benefit of the clearinghouse is bringing together more information so that there can be that broader look at all of the different forces responsible for the climate change that we're experiencing now and to inform the types of mitigation strategies by the different actors. I think this is one of the things that you're hearing about the different scales of actions that was highlighted in the report and the need for granularity in terms of the actors, but also in terms of the pollutants that they can that they could act upon to have more mitigation impact. And I think the other point that was raised several times in the report in this presentation is the value that a federated clear or clearinghouse organization could have it in drawing on existing networks and types of frameworks where this is work, for example, in the air quality and neurological communities as well. So there there are a lot of potential benefits and functions that we lay out in the report of such a structure. Great. Thank you for clarifying that. And one other clarifying question from the audience, when you talk about decision makers in the report, who is it that you're talking about? Who do we expect to be using this climate information? Well, as I tried to mention early on, I think the decision makers will go across a range of different scales from industry representatives, city leaders, state leaders, national leaders and and then the global agreement. So I think there will be, you know, a very wide range of different decision makers involved in and how they want to look at data sets and inventories is going to be important to what's really important is meeting their needs. And we wanted to make sure that we looked across that entire range. Great. Thank you. The global carbon project uses both activity and atmospheric data to produce their GHG budgets. Would you call this a hybrid approach also or something else? Maybe I'll jump in here. Yeah, I would I would consider the integration of the atmospheric monitoring and bottom up the GCP engages is as as a good step towards hybridization, you know, hybrid approaches are not some fixed target. There's a continuum and I think what we're seeing is a lot of the inventory developers and atmospheric scientists moving towards it. And I think GCP is an example of that movement towards a more integrated system. Great. Thank you. Our next question is one of your tasks was to utilize case studies. Can you highlight one or more of them that helps bring out the importance of one or more of your recommendations? OK, I'll jump in. Sorry to hog the mic. But let me let me one case study that I'm particularly familiar with is the is the city effort that we've done in Indianapolis called influx. And influx is a very thorough experiment. It's fundamentally scientific. And so it shows an example of two extremes of this of our recommendation pillars. On the one hand, it was fundamentally based or fundamentally intended to be an exploration scientifically of the way you go about measuring the atmosphere in a city doing a bottom up effort in the city. And therefore, it's often not very accessible to decision makers so far because it's fundamentally a scientific effort, though it's transparent by putting lots of information in the peer reviewed literature that still is not very accessible to decision makers. But one of its great strengths is both its transparency. And on the other hand, it's its thoroughness and its completeness within that domain, where it's measuring many, many gases. It is a very detailed activity based system associated with it. So it's it's got real strength in that that thoroughness trying to estimate uncertainty and trying to at least be transparent, though challenging in terms of being accessible and relevant to the decision making community. And Megan, if I may, I'll give the case study related to the methane emissions estimates and giving the EPA as an example. So EPA has two inventories. One, the National Inventory called the GSGI, the Greenhouse Gas Inventory. And the other inventory is called the Greenhouse Gas Reporting Program, which is a regulatory regulatory rule, a rule by which operators meeting a certain threshold, file their annual admission reports. So when we look at the different criteria from from a time in this perspective, the the GSGI, the National Inventory, has got a time lag of about 18 to 24 months. So if you were to use information today, you're essentially using information that is about 24 months out. Transparency is very high because the national and the reporting program goes to public review with comments. There is a validation issue which is good in terms of the GSGI goes through expert review, public review, public comments. But however, the issue we find now is research has shown emissions, measured emissions are different or higher, usually higher than estimated emissions. So part of that reason is its lack of completeness of these inventories. They exclude certain emission sources from the oil and gas value chain. And and and these are some of the issues that we walk through in the report comparing specific case studies against the pillars. In a more general sense, the case studies really provide a basis for for people looking forward to grading other inventories and be able using the pillars in the way that we intended them to be able to be able to help evaluate moving forward on how well we are we doing and really understanding the emissions coming from greenhouse gases. Great, thank you both. Our next question is, can you throw more light on how the global south will collect and report their GHG inventories? What approaches might work best for them? Kamal, you may want to start off this one. Yeah, I think that's a very good question. And and I think this report is going to be particularly useful for global south in terms of what the possibilities are, what the opportunities are. And it is imperative you know, the policy makers take a due note of the report. And I think the report outlines what needs to be done and where the assistance might be available for our countries in the in the south, Global South. Anyone else have anything to add about? Yeah, I'm happy to add in. I think another takeaway for global south countries and decision makers in particular is the recommendations on the hybrid approaches. And so with these global datasets that are generated from atmospheric based approaches or activity and then combining nontraditional data sources or other data proxies that have relationships with greenhouse gas emissions. The promise is that these hybrid approaches could utilize all of this information and then be able to estimate emissions in areas where it's perhaps trickier to get on the ground emissions data or capacities or lower resources are scarce. And so I think that that's something to watch out for. But of course, a lot of these models are only as good as the underlying data that's used to train these models. And so what we're really hoping in this report is that the community of startups and researchers and other organizations that are developing these hybrid approaches can work together directly with global south actors to help get the necessary representative data that we need to enhance the spatial coverage and sector representativeness that are attuned to global south conditions so that we can improve upon these models and make them more relevant for global south. And hopefully they can leapfrog then over traditional data inventory collection techniques. And so that's I think one of the promises for in particular, the hybrid approach that we recommended. As we recommend in the report, the iterative process is going to be extremely important for everyone. But I think but especially for the global south where we need to work together towards helping get better information on their emissions. Yeah, just to pick up on that, one of the reasons I think the inclusivity pillar is so important here is as Angel was saying, there is a need to have the ground truth information, the better data that is localized. There are a lot of evolving and new remote sensing platforms that can improve coverage geographically. But there's also commensurate need to make sure that researchers from those areas are involved to help provide the additional information to validate those other sources of information and also provide information on potentially practices and changes that take place in those areas that may otherwise be missed without that local knowledge. Great, thank you all. Angel touched on this a bit in her response to the last question. But what is the process by which the sufficiency of current GHG information is assessed? What is the process for prioritizing additional investment? I want to take that on. I'll start. Break the ice. Yeah, I think it does go back to the pillars. They were an attempt to at least start to prioritize six things anyway. But we want inventory developers, scientific community and practitioners to start to strive for. We didn't necessarily prioritize in the report, you know, which is more important than another. But hopefully they offer and especially through the case studies where we walk through examples of, you know, here's an instance of a case study that succeeds on some of these and does not succeed on others, that that starts to give some prioritization to what, let's say, an individual developer might be focused on. So we do think the pillars are becoming the minimum set of what we want to see, not necessarily in doing science, but in trying to make this information relevant to the decision making environment, which is often a different set of requirements than what we might think about within the scientific community. Great. Thank you. How do recommendations position the US to be a leader in global greenhouse gas information systems for the first global stock take for 2030 halfway to net zero and for 2050 net zero? So, you know, first of all, I think, again, you know, if you look at all the recommendations and what we say about the pillars, the fact that the United States and other nations can use these as a basis for looking at their own data sets and perhaps in more detail than even have in the past and and and to look at. Alternative information and in the application of the iterative approach we mentioned are all things that can can contribute to our potential leadership within the United States as we as we look forward to even more accuracy in the understanding the emissions from greenhouse gases. And, Tony, if I may, so if you look at the United States regulatory structure, there is already a tremendous amount of expertise that is built up at the EPA, DOE and other agencies with respect to GSC inventories and, of course, other stakeholders like academics NGOs, corporations and others. So there is built up capacity. It's already there. New hybrid techniques that we mentioned in the report are coming or are already here. A lot of technology development is already here, especially with remote sensing and continuous emission monitoring systems, which which puts us in a good shape and form relative to many countries of the world to assess where we are and also remember the report talks about barriers and about our current systems and international systems. And if we focus on both strengths and barriers, we think we're in a good shape. We have a good regulatory structure over here to take advantage of to meet all those pillars that we have blind. Great, thank you. So we've already had a few questions about how to build a clearinghouse and how it might relate to existing efforts, both in the U.S. and internationally. Can the committee discuss they're thinking about a clearinghouse or what a federated repository might look like? So I'll just take I'm sorry to go ahead, Debbie. Well, I think it's the analogy in terms of this federated sense that one of the examples that we were looking at when thinking about this is the way that the meteorological community works currently as something to look at to learn from in terms of how there are a number of weather services around the world. They each have their data collection and curation processes and then assimilation and models for forecasting. And so it's not as though there's a single entity that does all that, but there's a lot of exchange. And so that's one model that we point to in the report that could be could be could be learned from. And then Don, you were going to say something. So I'll pass it back to you. But I was just going to say that, you know, we looked at the criteria that should go into a clearinghouse, but we did not really try to say, well, who specifically should be doing this? And, you know, who who would be what agency or what agencies might be considered in in doing it? That's kind of left to the governments to kind of organize how a how a clearinghouse might be developed and and and thus organized across the planet. And I just want to add that we didn't also want to prescribe or constrain this recommendation to speaking only specifically about intergovernmental institutions like the WMO, the World Meteorological Organization or the UNFCCC or a government agency or institution. We can also think about it in a decentralized way as well. And so there's a huge crop of new technologies that are coming online, blockchains, distributed ledgers, Web three, where they're using digital technologies to interface seamlessly between different data nodes and providers. And so we also didn't want to preclude and constrain and say, oh, we're thinking about this exactly in terms of this model or that model, but to leave open the possibility for further innovation and these types of efforts that are ongoing right now to think about data storage and working together in a different way than has traditionally been thought of. Great, thank you. I think we have time for probably two more questions. We've got about five minutes left. The first, collecting more data is a recommendation heard often by purse holders. Is that something the committee recommends too? And did you identify any particular priorities in your report? Well, I think it's clear we do not have enough data to really understand the emissions of greenhouse gases adequately for future policy needs. So yeah, I guess we do need more data, but it's also what type of data and doesn't meet the needs of the decision makers. And that's why we came up with the framework and the pillars, et cetera, and the recommendations that came out of this report. Yeah, and one of the specific, I mean, Don's exactly right. More data volume is always welcome, and particularly in the global South where we know we don't have enough, but it's welcome everywhere. But it really is, I think we emphasized it's the quality of the data and how it's being used and how it's being interpreted. That is actually a focus. We have a lot of different data systems out there and inventories out there, but they're often, they're very different. They're different, the difficult to get to. And we want to focus them and enhance the quality of that data and its nature so it can be used better. One of the specific recommendations we made was increasing granularity. It's clear from the decision-making world that increasing the granularity of data so that it is both aggregated at large scales, but also detailed enough to assist decision makers at the subnational scales or more granularity, more functional detail is really, really needed to engage in real practical world mitigation policies. Anyone else? Well, we have a few minutes left, so I will just open it up to the committee. Are there any last thoughts that you want to leave with our audience as they read through your report in the coming weeks? Any priorities you want them to have top of mind or maybe next steps to be thinking about? Anyone want to take a shot at that or should I? I was just gonna say that this is, as Angel said in our closing, really intended to prompt the discussion that pushed the community towards thinking about this approach with these pillars, looking at the requirements for more than just the scientific need, but understanding from the end of what the user needs are and to be able to meet those needs. So I think that would be one takeaway that we really do see this as kicking or pushing, I think was the word used, the community to have a discussion. Yeah, I think a bit from two sides, we wanna make the decision-making world better consumers of the information and push the inventory developing world to develop information more relevant for those decision-makers. And I think as one of our earlier speakers commented, we're in a world that's rapidly evolving. We have new measurement systems, these hybrid approaches are being adapted. So we really do see a lot of change ahead in the future. And so this report in these pillars are meant to help us think about the right category. What's the behavior we need a new system to look like? And to my mind, we're really gonna see a lot of change and move it forward in the years ahead. Yeah, I wanna just add that decision-makers are to emphasize that decision-makers are just not the policy makers. It can be at all levels. Policy makers, whether you're a banker, whether you're a corporation, whether you're a city leader, whether you're an NGO, you need right information to make your right decisions. And this is the first time that I'm aware that we have concretely put key pillars for consideration. And one pillar may owe away another depending on where you sit in the decision-making realm. So we hope this will be helpful in making the right decision. You know, the time has come where it's really important to recognize that accurate knowledge of human emissions is required for climate-related policy decisions. And it's across all scales as Fiji was just referring to. And our aim in this report was to try to set up a better approach for people going forward to be able to look at those issues. I'm amazed, you know, our several months together of working on this that we were able to do what I think was really an excellent job in looking at those issues and trying to come up with useful recommendations for the future. And so I'm really hopeful it will be helpful to policy makers that they can use this and be able to carry this forward. Yeah, I just wanted to add, you know, this is a really a global problem. And I think in order to solve this, we are going to need leadership at different levels in different regions. I want to go back to the comment about the leadership by no means we are trying to demonstrate here that US is going to play a leadership role in organizing this effort. US can lead by example as to what can be done. So I think what we are looking at is the opportunities in many, many countries, many, many regions to take advantage of the report and really exercise leadership in organizing mechanisms for better information on greenhouse gas emissions. Well, thank you all so much for those closing thoughts. The audience had so many great questions for us today, but unfortunately we are out of time. I'll note that a recording of this session will be available on the National Academies website in the coming weeks, so you can find it there. The link to download the report for free and in full is above your video player. And once you exit this webinar, you will also be redirected to our report page. So with that, I would like to thank the committee for their time today and thank you all again for joining us.