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Total Carbon Data, Analysis, and Insights

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说明

Buildings and construction generate nearly 40% of annual global CO2 emissions. Of that 40%, building operations account for 28%, while building materials and construction (a.k.a., embodied carbon emissions) are responsible for 11%. Achieving zero emissions in operations requires a continued focus on energy efficiency, avoidance of the use of fossil fuels, and use of renewable energy systems. Unlike operational carbon emissions, which occur throughout the life of a building, embodied carbon emissions occur “up front” and so play a bigger role in the global carbon budget in the more immediate future. As such, it is more imperative than ever that architects and other project stakeholders start to employ total carbon analysis at all stages of every project. In this session, you’ll join Autodesk Product Development and Impact team members to learn about new data, analysis, and insights into total carbon to help make effective reductions as part of a more integrated, building information modeling (BIM)-based design process.

主要学习内容

  • Discover what total carbon is, why it matters, and how it can be analyzed as part of a more integrated design process.
  • Learn how to use Revit for establishing a basis for total carbon analysis (location, quantities, materials, systems, operations data).
  • Get insights into embodied, operational, and total carbon with interactive breakdowns and tradeoffs.
  • Learn about viewing and modifying data, analysis, and insights to meet different regional or project needs.

讲师

  • Marta Bouchard
    Marta leads the sustainability strategy for Architecture, Engineering and Construction (AEC) within Autodesk's ESG & Impact team. Within this role, Marta seeks to position and extend Autodesk and Autodesk's technology to transform the AEC industry to realize more sustainable outcomes. Prior to joining Autodesk, Marta practiced over 15 years in the Architectural Design and Planning industry, providing sustainability consulting and design analysis for the built environment.
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      Transcript

      IAN MOLLOY: Hi, everyone, and welcome to our class, Total Carbon Data Analysis and Insights. As you're joining us online, we're going to assume that you've read the class description. If not, you can pause here and read it for yourself. Same also goes for the learning objectives.

      Now because you're going to be hearing from some Autodesk employees here, we need to highlight this safe harbor statement. Again, you can read it for yourself, but the short version of it is that we will be making forward-looking statements. And as such, while everything we present here today is correct to the best of our knowledge, plans and information do change over time, so please do not base any purchasing decisions on what you hear. Thank you.

      OK, so who are you going to hear from today? So my name is Ian Molloy and I'm the Product Manager for both Insight and MEP Design through Fabrication. You're also going to hear from Marta Bouchard who's our AEC Sustainability Lead. And also Corina Marinescu who's one of the product owners for-- at Next Gen Insight.

      So I'm going to hand it over now to Marta who's going to provide you with an introduction on total carbon.

      MARTA BOUCHARD: So let's start with defining total carbon. The construction and operations of buildings notoriously contribute to 40% of annual global greenhouse gas emissions. Collectively we're setting targets such as net zero to reduce our emissions and impact on our planet because many global leaders have signed the Paris Agreement, which is a commitment to mitigate climate change with a target to limit global temperature rise to a minimum 2 degrees C.

      So what is in this 40%? It's comprised roughly of 12% embodied carbon emissions attributed to the upfront activities of extraction, transportation, and manufacturing of building materials and construction. And 28% is attributed to the operations of all buildings over a year.

      That means over the course of one year, a third of our total carbon is associated with new construction and major renovation activity, while the other two-thirds is operations of all our existing buildings. Traditionally our focus is on reducing operational energy, and therefore, carbon, because it's the obvious bigger potential for impact here. Embodied carbon has largely been ignored, but we really need to look at both.

      So let's take a look at just our new building and renovation activity. Starting today and assuming business as usual-- that means no interventions, no improvements, when we build new today, the upfront emissions dwarfs the first year of operational emissions.

      Assuming this rate of new activity, by our 2030 target, more than 70% of our total carbon emissions is actually attributed to just those upfront emissions. As the number of new buildings accumulate, the operational emissions accumulate. And if we want to get to the global warming limit of 2 degrees by 2030, then we need to act on our upfront emissions now.

      And, as we look at emission attributions over time and forecast new building activity through to 2050, for example, both embodied carbon and operational carbon become nearly a 50/50 split in relative importance. And this is why we need to look at both of them together.

      We can start one building at a time, by first understanding carbon impacts across a building lifecycle. The embodied carbon emissions are basically locked in place for the life of the building and may even increase over time through repairs and maintenance, upgrades, or renovations.

      Those upfront emissions are a big piece of our global carbon budget that we can influence today while concurrently mitigating operational carbon before it accumulates year after year. We can drive impact by addressing the total carbon for which we can analyze and design today, as well as predict the interrelated effects and trade-offs with future operations.

      So our biggest opportunity on a path towards zero is for architects, engineers, builders, and other building stakeholders to accelerate total carbon analysis at all stages of every project.

      For many of us, our commitments to zero are pretty high. For example, of the AIA membership comprised of American as well as multinational firms doing projects around the globe, they're signing on to the AIA 2030 commitment to adopt targets for net zero emissions in the built environment.

      These commitments are rising, as is the use of predicted energy performance necessary to track and report emissions data. Over the last 10 years, the numbers have shown, commitments have grown to over 1,000 firms, of which less than 50% are actually reporting data, and of those, less than 25% are submitting full energy analysis. Adoption of analysis tools remains relatively low.

      And this low adoption is not entirely surprising given the industry faces a variety of complex and multifaceted challenges. So first, let's unpack this. There's business and cost risk. Energy and carbon analysis is typically outside the scope and fee of a project. There are soft costs associated with adopting new methods and tools, as well as business risk if the analysis is incorrect.

      Second, the design process varies by firm, project, and customer. Energy and carbon analysis requires continuity across stages of design, the meeting of different stakeholder needs, and has cross-disciplinary impacts. And lastly, the tools and the data, energy and analysis tools can be difficult to use with varying degrees of control over the inputs and outputs and difficulty scaling those workflows to repeat on future projects.

      So let's just focus for a minute on the conventional design process and toolkits, and let's just visualize three typical roles required for a building project. Conventionally, each building system is led by a specialist planner or a designer.

      Each uses a special set of tools with separate workflows. They coordinate at key milestones to exchange information. External tools and specialists often overlay this process, providing additional analysis and information, which means the most informed project coordination occurs later in the detailed construction documentation phases.

      This also runs the risk of missed opportunities, such as earlier discovery of sustainable solutions and greater potential for impact.

      But we know the greatest environmental impact to meet our climate commitment is to reduce carbon earlier in the design process. An unrealistic scenario is to build nothing. Then we could focus entirely on decarbonizing our existing building stock, which we absolutely must do, but if we're going to build new, we must build as lean and smart as possible and mitigate our carbon impacts.

      And as already introduced, especially with new building activity, it's in early planning and design when we have the greatest carbon reduction potential.

      We can start by leveraging a more integrated design process. Instead of siloed work streams, stakeholders can engage in earlier collaboration and information exchange. And then establish a process with a more coordinated toolkit, enabling integrated analysis from a common data source in a collaborative and open BIM environment at any project stage.

      And most importantly integrate feedback throughout the process and build upon that shared data in order to get total carbon insights and to explore and share feedback on embodied and operational carbon impacts.

      Quantifying carbon across the building lifecycle is influenced by both the design process as well as the toolscape Today, there are a variety of design tools to calculate the embodied carbon of the upfront activities for material extraction processing, transporting, and manufacturing. And there's tools to predict or measure operational carbon of the building lifecycle.

      So together with end-of-life assumptions, cradle-to-grave lifecycle assessments can be scoped at different stages of the building lifecycle.

      Navigating the landscape of embodied carbon tools is as challenging as our design processes, because the level of complexity ranges. At its simplest, we can refer to external references and proxies of our building materials. [INAUDIBLE] spreadsheets perform manual calculations based on floor area and combined carbon calculations, or export a bill of materials or quantities with material-specific carbon factors, but both of these require manual referencing of external databases.

      And then there are package software tools that links to either the project's architectural model or a proxy model, or perhaps a custom solution using bespoke coding and data mapping and algorithms. And of course, there's full lifecycle assessment software, which may or may not link to BIM or the project's architectural model.

      When it comes to operational energy, the spectrum of analysis tools is yet another example of our industry challenges with tools and data. First, we can explore external references and proxies to explore and set building performance targets.

      Then we can use conceptual analysis to estimate operational carbon or use more advanced detailed solutions that can enable analysis, as well as benchmark-predicted performance. These solutions can inform operational energy well before the building is built in order to estimate carbon emissions and understand the impacts of design decisions today.

      The landscape of carbon analysis tools evidence is the varied disconnected tool perpetuating the use of different models at different points in the design process. For effective total carbon analysis, we need more integrated tools and a common source of building information in order to provide better data, analysis, and insights.

      IAN MOLLOY: So thank you, Marta. So Marta's talked about the why, how, and what of total carbon, the importance of an integrated whole systems approach, and an overview of the toolscape today.

      Now I'm going to start by explaining, what exactly do we mean by data analysis and insights? And the principles behind this that really influence what we're going and how we're doing it going forward. Then I'll outline where tools like Revit and Insight fit in and what you can do with them today and where we're going with them. And then as a highlight, you'll see a demo of what we're working on with Next Gen Insight, especially for embodied carbon.

      So the simplest view of this is they're just three separate words, and we look at them that way in a minute. At the very highest level, though, it's important to think of them together as parts or steps in an interconnected process. The way they're written going left to right mainly reflects the way software works or how an expert thinks about the problem.

      That is, they start by establishing some data, using it in an analysis, which creates more data, all of which is then used to present an insight to answer some specific question or questions. The way humans typically consume information, however, is really in the other direction.

      That is, they start with some question, get an initial answer, then look into the data analysis behind that so that they can trust it and they can use it to make decisions.

      Essentially, these differences create a lot of friction in how humans actually interact with and experience data analysis and insights. And therefore, a key goal for us is to make this journey in both directions as frictionless and flexible as possible.

      Now that this isn't specific to total carbon, of course. It applies to anything, really. And you'll see similar kinds of ideas like in the modern data science engineering space.

      Now often, a good way to help describe an abstract concept like this is to contrast with something more familiar, and we can do this by considering what typically makes up the traditional toolscape just as Marta summarized earlier.

      In very general terms, if you look at these solutions, they can be broadly characterized as being very specialized point solutions built on closed proprietary IP, often using desktop file-based technology, or if they're in the cloud, they're still closed proprietary file-based. And this has essentially been the mode of software development from the beginning, but that's very much changing now.

      Data analysis and insights, on the other hand, challenges this by generally seeking to be more open and transparent. This makes it easier to establish trust and encourage greater collaboration and decision-making beyond just the specialists. Also being cloud-native with APIs, they're more extensible, making them more adaptable for evolving needs at both the organizational and individual project level.

      Now this isn't necessarily advocating any specific tool or product today. Some existing tools already exhibit some of these principles. It's just an outline of core principles we're adopting as we look to deliver on our vision for the future going forward.

      So let's break them down one by one now starting with data. Now if there's ever a word at the top of its peak hype cycle, it's data. No doubt you'll have heard expressions like "data is the new oil" and so on, and we find it a little funny to think about that in the context of total carbon, but that's not the point here. The point is everyone sees value in it.

      And the reason is really simple. Because if you ask people what data is, they probably say something like, it's what they use to base decisions on. That's really just an expression, though, but the problem is that humans typically don't do well with data in its raw form, which is what we're talking about here.

      And so as such, it leads to situations like the answer is 11. But what was the question again? So we see a lot of that. Now in our context here, data is really a means to a few different ends. One of them is a means of exchanging information between different applications, and the other is as an input to an output from analysis. I going to get to that in a minute.

      Now when we talk about total carbon in buildings and the actual data that that relates to, I just mentioned that data mainly relates to the inputs to and output from analysis. When you look at it that way, you'll see, on the input side, it comprises a pretty complete description of a building-- its location, materials, the systems, internal operations, and so on.

      And on the output side, we can see perhaps obviously total carbon, but in order to get that, you need what that comprises, which is embodied carbon, operational carbon, and all the things that inform-- contribute to that, like energy use. Even things like occupant comfort have an impact on operational energy.

      Now this is just a high-level summary, and in practice, it is a lot of data. And we're not even just talking about a single building or design option, but potentially hundreds of thousands of different design options and other assumptions, as well as the ability to aggregate data and cut and splice it for multiple buildings or analysis at different scales.

      Then with analysis this is easily the most common term used, especially today amongst engineers or other technical personas. For our purposes here, it mainly relates to the wide and varied mathematical and algorithmic routines each of which takes certain input data and then create further output data. So calculations, simulations, predictions, optimizations, and other words that sound like that.

      They effectively capture anything from rough rules of thumb to complex, interconnected behavioral models. For many types of complex analyses like energy, structural, airflow, lighting, acoustics, and so on, their actual workings mainly are a mystery to the majority of users who use those tools. Their trust of those tools is mainly built on their own learned experience over time.

      And this really forms the majority of IP today that's in the traditional toolscape, and there's a mountain of knowledge that's just locked up in them. So we're looking at new approaches and technologies that can help reuse some of this, as well as open possibilities for creating entirely new analysis solutions in more open, transparent, and extensible ways.

      Now when we look at the core of what analysis we're talking about in total carbon, there's really a couple of key technologies that were-- and data sources that we're looking at. On the embodied carbon side, we have EC3 by Building Transparency, which is a relatively new totally open database of environmental project disclosures and tools for calculating embodied carbon in design and procurement.

      For operational carbon, we have EnergyPlus, which is the world's leading whole building energy simulation engine, and OpenStudio, which is essentially a middleware to EnergyPlus for managing the creation of EnergyPlus inputs and outputs.

      Together they provide really incredible analysis of the complex interactions and dynamics that make up a building-- its exterior climate, its interaction with internal processes, and its ultimate energy environmental systems. This is developed by the Department of Energy and is also completely open and extensible.

      Finally, insights, this is a somewhat newer term, but you've likely heard it used frequently. Not only because of Autodesk's own Insight product line, which we'll be talking about later, but the word "insight" sort of differs from data and analysis by generally speaking to some aspect of enlightenment or a light bulb moment.

      This is effectively where data analysis is presented in some visual ideally interactive form to help answer specific questions. Typically the focus for these revolve around insights that help improve a building's design operation, but what's very often overlooked is that a lot of the time is actually spent on improving the data analysis and insights themselves.

      So there's a critical feedback loop there, that's one of the reasons why we want to be able to make that seamless. Because what we want to be able to provide is the right insights for the right people at the right time based on the right data analysis.

      And then just to close on this metal model, for total carbon insights, we're really talking about the culmination and combination of a few different products, features, technologies that we've been developing at Autodesk for the past decade or more. For operational energy and carbon, today we have Insight Energy, and the more recently added Revit Systems Analysis.

      And for embodied carbon as part of our Next Gen Insight development you're going to see a little later, we're adding embodied carbon.

      OK. So now that we've outlined the key principles behind data analysis and insights-driven approach to total carbon, the big question for any architecture-- architect or engineer is, where do I start? Well, given we're talking about buildings, the obvious place is arguably building information modeling.

      That's certainly where a lot of people are today, but of course, what that means really depends on your level of sophistication or understanding of what that really involves. For the most part, though, in the simplest terms, models are what people create with BIM.

      Interestingly, the word model, it has its own meaning in modern data science and engineering, but to us, a model in AC is really what most people look to as the source of truth for current design information on which they'd want to base data-- any sort of data analysis and insights.

      So how do models typically work as a starting point? Well unfortunately in most cases, not very well. Models certainly contain a lot of data, but in general, modeling or the act of and the freedomness that it gives and-- the data is not in a structured manner or complete enough to provide frictionless data analysis and experience. There's ways to deal with this, which we'll get into, but you can see the logic of our approach by understanding this.

      The short way to explain this is that as model complexity increases, data inconsistency or the structure of the data inconsistency also increases, and it scales very rapidly. And the best way to illustrate is just with an example.

      Is that if you take a typical Revit architectural model and actually start to break it apart, you'll actually see, what we start with as seeing a building is actually made up of hundreds or thousands of separate individual parts.

      And across all the different people who use tools like Revit and Model, they'll have different modeling styles, different content with different detail. They'll model to different tolerances, different levels of completeness, and embed different data in those elements in different ways.

      And this isn't just specific to architecture, but structure MEP, any other subdiscipline model has the same kind of challenge related-- the openness of the modeling environment creates a challenge when you want to actually try to extract data in a structured way.

      Now this problem isn't new to us. This is effectively being a barrier to whole building energy analysis for a very long time, and it's something we've been working on developing over the years and continuing to improve what we call the Revit Energy Analytical Model.

      The aim effectively takes any architectural model from concept to massing to detailed at different-- with walls, floors, roofs, and different levels of tolerances and completeness, modeling styles, and so on. And effectively, it scans the model to extract and collate the data that's necessary for a building energy simulation.

      Now historically we've been using this information for energy analysis with Insight and Systems Analysis, but if you actually look at the data, you'll see it contains some of the key information that's also relevant to embodied carbon.

      It doesn't contain everything we need for a complete detailed total carbon analysis like physical structure and MEP systems and sheet metal and pipework and things like that, but those things tend not to exist at early stages anyway. Plus, we can deal with that in other ways and then also have ways to add that information in later when it becomes available.

      So the main thing now though the key takeaway is that for a holistic early-stage analysis of total carbon, the EAM provides a really good starting point for total carbon analysis and insights and a lot of what we need to do that.

      Furthermore for the future, while it doesn't contain structural and MEP geometric information today, in line with where we're going with other Autodesk efforts to break down the Revit desktop file silo and move that data into the cloud and sort of into a granular form, we'll have the ability to then reaggregate that data back into our total carbon data analysis and insights.

      So this is something for the future, but it really provides-- the EAM is a great place to start today and we'll be able to build and aggregate data-- further data on top of it in the future as well.

      So the EAM has actually been around for quite some time, but we found it's one of the least well-understood capabilities. And maybe having heard me talk about it now, you're tempted to jump into Revit and give it a go and press the button.

      And I certainly wouldn't discourage you from doing that, but it is worth considering that it is an automagical operation. It'll do a translation straight away. And it is worth understanding what actually goes behind that, and critically, the different workflow options that you have for actually using a feature like this.

      And there's really some key questions that you want to ask yourself about how to use this and you should consider this relative to your learning curve. Most people want to dive in and use an existing model, which is totally understandable.

      But if you do that, you've got to ask yourself things like, do I want to use it as a link or use it as directly? If I use it as a link, do I use it as non-room bounding or as room bounding? What elements am I going to use? What energy settings and am I going to use? What actually makes an accurate, reliable EAM and so on?

      There's lots of information online that have to do this and learn this, but the thing I always encourage people is that if you're new to it, you've got to walk before you run, and it's worth exploring how this feature works from a sort of from scratch. Model something simple, start to understand how elements are translated.

      And then when you learn that, you can learn how to work in a more integrated way. Or then if you take somebody else's model make a separate copy of it, and you can hack away on that, you're not worried about upsetting anybody's work-sharing or anything like that.

      And then when you really understand how models in their entirety can be translated, you're there in a better position and then work in a trusted environment like with work-sharing and linked models and so on.

      So with all that covered now, now we can put the four of these things together. We can now say, we have data analysis and insights, and models are really an input to that in the form of structured data. So how does all this work in practice? What have we got today and where are we going with all of this?

      Well, brings us to Insight. It's been around for quite a while, but we're going to-- so I'm not going to go into it in detail. I'm going to summarize it here and it'll help you appreciate where we're going with it and where we're taking it.

      So Insight today essentially provides whole building energy analysis directly from Revit using the Revit Energy Analytical Model. Somewhat uniquely, it doesn't just run a single analysis, but simulates hundreds of different design options and operating scenarios, and is then able to compute an energy range, which then the user can then compare its relative to different benchmarks like actually 90.1 in architecture 2030, so they in relative terms how well they're doing.

      But also explore different design options in real-time and get real-time feedback and understand the biggest factors that make a difference on reducing energy consumption.

      Now over this time that it's been out, we've had a lot of feedback from customers both on the positive side and on things that they'd like to see it do next.

      And I just wanted to point out like on the positive side, it's really validated what we intended it to be, which is to provide mainly architects at early stages or who are new to energy analysis a big-picture view of what the major issues--

      What the main metrics and benchmarks you need to look at are, and what the major drivers for building energy are and things like orientation, window-to-wall ratio, balance between internal loads and system efficiencies, as well as use of renewable energy and so on. So you can sort of hit different targets with that.

      And the feedback that we've had has really validated that, and what I like to highlight is that it's across a number of different firms at different sizes. You don't have to be just a big firm to use this. In fact, it's been very effective at smaller firms getting involved in AIA 2030 and starting to do analysis as part of every project.

      And we're also very proud of the fact that it's also highly accurate. You can certainly build the wrong model or use the wrong inputs and so on like any tool, but once you know how to use it, you find that any comparison with any existing or traditional tools, more complex tools generally compare very well, both in terms of actual numbers and in terms of directional feedback relative differences with new energy-saving measures and so on.

      So as much as we've had lots of positive feedback, we also know where the gaps are, where the key things are customers would really like to see to take it to the next level, and these cover things like-- it really only focuses on-- provides these two key metrics of energy use costs and intensity. There's no breakdown of energy use.

      There's also very limited HVAC system definitions. It's just broad efficiencies so that you can see how they play off relative to other moves and things like the envelope and the internal loads. And ultimately, the benchmarks, the factors, everything that's in there is all fixed. It's you take your model and you analyze it against a range of fixed options. You've no freedom. So if you're not interested in changing orientation, you don't get the option to turn that off, it's always there.

      And then for us, at least under the hood, it's built on some legacy technology like DOE2. And it's built on older AWS technology. That doesn't sound bad on its own, but Autodesk has really advanced in the way it builds on the cloud and we've got this concept now called Built with Forge that improves things like performance and security and scalability in lots and lots of ways.

      So when we looked at actually trying to address these, one of the things we realized, part of the legacy technology challenge was that we couldn't just continue to build on that framework. So what we did is an interim step was that we developed and released a feature called systems analysis, which basically complements Insight in terms of its where insight is, that early-stage big-picture systems analysis is more like traditional detailed energy analysis.

      And it provides a number of things that were key customer requests. So it provides more breakdown other than just energy use or cost, end use breakdowns-- really, an unlimited amount of output if you want it. You can go to any level of detail on the different HVAC system definitions.

      And we're replacing the DOE2 engine with EnergyPlus an OpenStudio, that's really a key enabler for us. Just to be really clear, Systems-- Insight runs in the cloud, Systems Analysis currently runs on your local desktop and it will run one analysis at a time.

      But the reason for doing this is that that capability and that technology is essentially what we're moving into the cloud for Next Gen Insight.

      So when you look at these together, what we have today is that you have Insight for early-stage big-picture, getting started with energy analysis and systems analysis for the more experienced user. And they both share the exact same energy analytical model.

      So going forward, our development of Next Gen Insight really looks like this. We're basically taking everything that was good and what we knew from original Autodesk Insight and we're taking the technology behind systems analysis like EnergyPlus and OpenStudio and moving that to the cloud.

      And then the key goal that we're trying to solve for with Next Gen Insight is really total carbon. And so that brings-- involves bringing everything about Insight today and Systems Analysis on the operational side, but also supplementing with the embodied carbon piece, which is what we're going to share with you in a minute.

      The other aspect as well is also improving the user experience and workflow and that flexibility around the ranges and benchmarks that people want to analyze. Everyone wants to ask different questions about their building, and these are the things that are really core to the key pieces of early-stage targeting.

      And then examining trade-offs or different technologies and design measures, and then ultimately tracking a project and how it progresses, making that really seamless. And like I mentioned, we're building it on an entirely new stack, EnergyPlus, OpenStudio, data from EC3 all built with Forge.

      So now, for the highlight of this session, I'm going to hand it over to Corina who's going to share a quick demo of Next Gen Insight, the beta that's currently in development. And in particular, the embodied carbon aspects of that which are entirely new.

      She's actually going to give two worked examples just to demonstrate what can be done with it. One is a mass form analysis which basically assesses the role and impact that walls have based on changing mass form. And the other is an analysis that compares the new construction to keeping existing facade in place and what the savings in embodied carbon will be.

      CORINA MARINESCU: With insight, you can now start as early as the urban massing stage to understand the embodied carbon impact of your proposed design with a focus on exterior walls. Given a site model and a simple mass, you can go to Energy Settings under Analyze tab and review the energy analytical model's configuration.

      Go to Other Options to specify details about the architectural elements that will be associated with your mass. Create other massing options to explore their exterior walls' embodied carbon in Insight.

      Notice how the embodied carbon of the brick veneer frame wall decreases as the building becomes more compact like in the initial design scenario. The examples we used show very different form factors to illustrate that the efficiency of the building shape is key.

      Do not be deterred from calculating embodied carbon at an early design stage because of uncertainty in material quantities and their specifications. No material or design changes in the facades will be able to compensate for the form factor. Use Insight to make carbon-smart design decisions from the very beginning of your project.

      Now let's explore the embodied carbon of two design scenarios, building and construction versus keeping the existing facade.

      We start with the new construction scenario. Fast forward into the future to a more detailed design stage, imagine you've already established the programming of the proposed design. Subsequently, you've set the grid size, you've identified vertical and horizontal circulations, and you set a design for the facade.

      The energy analytical model is capable of reorganizing the building components in your model to match the corresponding function needed for a total carbon insight. It basically simplifies complex building components' geometry to a cleaner surface containing relevant structured data from your model.

      In order to have a detailed representation of your wall types and their constituent materials in Insight, please make sure that you've assigned thermal assets to materials. Next, go to Analyze tab and open Energy Settings.

      Here is where we can view the analytical models configuration. Please ensure that the Detailed Elements box is checked. This will enable the Insight to retrieve your building elements constituent materials and their parameters, including the thermal assets.

      Once you've uploaded your model to Insight, you can expect that the data is represented correctly. Isolate the exterior walls in the 3D view to get context about their placement in the model. You can also use the legend to look at the structured analytical data through different lenses by surface type, by detail level, or by construction.

      Notice the warning signs and missing embodied carbon results. In order to calculate the embodied carbon in your exterior walls, you should proceed to quickly assign embodied carbon definitions. The coefficient and its declared unit will be multiplied by the corresponding quantity.

      Notice how embodied carbon assignments are propagated to identical materials in different exterior walls. In case you're not sure about the results of your query, you can always access advanced search and get more details about embodied carbon definitions looking at nodes, source, and labels.

      We use EC3's database with statistical average values for the main product categories. In case you don't find the right entry to match the material layer from your model, you can create your own. In this particular case, we did an estimate of the embodied carbon impact of standard metal studs over a 10-by-10-foot sample wall, and then normalized to 1 unit of the area.

      Keep your custom embodied carbon definitions organized and assign labels or add your own. Be creative. Explore. You can always come back and edit or delete your definitions. Once you get to know your database, you can proceed to quickly map the next materials.

      Notice that embodied carbon results are starting to populate the stacked bar chart above. Here is where we can visualize the embodied carbon outcomes to understand and decide how to improve its impact on your exterior walls. You can inspect the most carbon-intensive materials, and you can also see if the embodied carbon in a particular wall type is due to its material's high embodied carbon intensity or the fact that it's widely used in your facade.

      Next, let's have a look at the other design scenario, keeping the existing facade. Notice that the existing wall constructions are named according to the building block they belong to. Follow the same steps to ensure that your model is represented correctly and skip assigning embodied carbon definitions to existing walls.

      Now that you've got your embodied carbon result, you can see that by keeping the existing facade, you will save approximately 10% of embodied carbon only on exterior walls. Browse different charts to understand how you can lower your embodied carbon even more.

      IAN MOLLOY: OK. Thanks, Corina. So hopefully everybody liked that. It was a little short, but it gives you a good sense of what we've been working on today. And the good news is that we plan to release this very soon as a technology preview in Revit.

      As a technology preview, this means that anyone with Revit 2022 or 2023 will automatically see a new carbon Insights button appear on Revit. Now we're not done with development. The whole purpose of a technology preview is to get real-world testing and feedback. and so we really look forward to that.

      But in the meantime, if you would like to learn more, have questions or thoughts, please feel free to reach out to the Insight development team here at insight.support@autodesk.com. So I'll hand it over to Marta now to close off.

      MARTA BOUCHARD: Thanks, Ian. Thanks, Corina. So in closing, we've introduced total carbon, the fact that the built environment, especially the embodied and operational carbon, is a large portion of our global carbon footprint. We also acknowledged some industry-specific challenges, such as our conventional processes and existing toolkits which could hinder our ability to adopt and integrate energy and carbon-specific analysis tools.

      So if we want to address our industry's carbon emissions, we need to better leverage data and analysis from our building models to create insights about our building design decisions and how they affect embodied and operational carbon.

      With the next generation of Insight, we're creating a solution for total carbon analysis which will bring earlier insights to architects, engineers, and building stakeholders to more easily explore, iterate, and integrate sustainable solutions for the built environment.

      Thank everybody so much for joining our presentation. Thank you.

      ______
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      我们通过 Twitter 在 Twitter 提供支持的站点上投放数字广告。根据 Twitter 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Twitter 收集的与您相关的数据相整合。我们利用发送给 Twitter 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Twitter 隐私政策
      Facebook
      我们通过 Facebook 在 Facebook 提供支持的站点上投放数字广告。根据 Facebook 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Facebook 收集的与您相关的数据相整合。我们利用发送给 Facebook 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Facebook 隐私政策
      LinkedIn
      我们通过 LinkedIn 在 LinkedIn 提供支持的站点上投放数字广告。根据 LinkedIn 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 LinkedIn 收集的与您相关的数据相整合。我们利用发送给 LinkedIn 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. LinkedIn 隐私政策
      Yahoo! Japan
      我们通过 Yahoo! Japan 在 Yahoo! Japan 提供支持的站点上投放数字广告。根据 Yahoo! Japan 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Yahoo! Japan 收集的与您相关的数据相整合。我们利用发送给 Yahoo! Japan 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Yahoo! Japan 隐私政策
      Naver
      我们通过 Naver 在 Naver 提供支持的站点上投放数字广告。根据 Naver 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Naver 收集的与您相关的数据相整合。我们利用发送给 Naver 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Naver 隐私政策
      Quantcast
      我们通过 Quantcast 在 Quantcast 提供支持的站点上投放数字广告。根据 Quantcast 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Quantcast 收集的与您相关的数据相整合。我们利用发送给 Quantcast 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Quantcast 隐私政策
      Call Tracking
      我们通过 Call Tracking 为推广活动提供专属的电话号码。从而,使您可以更快地联系我们的支持人员并帮助我们更精确地评估我们的表现。我们可能会通过提供的电话号码收集与您在站点中的活动相关的数据。. Call Tracking 隐私政策
      Wunderkind
      我们通过 Wunderkind 在 Wunderkind 提供支持的站点上投放数字广告。根据 Wunderkind 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Wunderkind 收集的与您相关的数据相整合。我们利用发送给 Wunderkind 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Wunderkind 隐私政策
      ADC Media
      我们通过 ADC Media 在 ADC Media 提供支持的站点上投放数字广告。根据 ADC Media 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 ADC Media 收集的与您相关的数据相整合。我们利用发送给 ADC Media 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. ADC Media 隐私政策
      AgrantSEM
      我们通过 AgrantSEM 在 AgrantSEM 提供支持的站点上投放数字广告。根据 AgrantSEM 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 AgrantSEM 收集的与您相关的数据相整合。我们利用发送给 AgrantSEM 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. AgrantSEM 隐私政策
      Bidtellect
      我们通过 Bidtellect 在 Bidtellect 提供支持的站点上投放数字广告。根据 Bidtellect 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Bidtellect 收集的与您相关的数据相整合。我们利用发送给 Bidtellect 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Bidtellect 隐私政策
      Bing
      我们通过 Bing 在 Bing 提供支持的站点上投放数字广告。根据 Bing 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Bing 收集的与您相关的数据相整合。我们利用发送给 Bing 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Bing 隐私政策
      G2Crowd
      我们通过 G2Crowd 在 G2Crowd 提供支持的站点上投放数字广告。根据 G2Crowd 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 G2Crowd 收集的与您相关的数据相整合。我们利用发送给 G2Crowd 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. G2Crowd 隐私政策
      NMPI Display
      我们通过 NMPI Display 在 NMPI Display 提供支持的站点上投放数字广告。根据 NMPI Display 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 NMPI Display 收集的与您相关的数据相整合。我们利用发送给 NMPI Display 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. NMPI Display 隐私政策
      VK
      我们通过 VK 在 VK 提供支持的站点上投放数字广告。根据 VK 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 VK 收集的与您相关的数据相整合。我们利用发送给 VK 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. VK 隐私政策
      Adobe Target
      我们通过 Adobe Target 测试站点上的新功能并自定义您对这些功能的体验。为此,我们将收集与您在站点中的活动相关的数据。此数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID、您的 Autodesk ID 等。根据功能测试,您可能会体验不同版本的站点;或者,根据访问者属性,您可能会查看个性化内容。. Adobe Target 隐私政策
      Google Analytics (Advertising)
      我们通过 Google Analytics (Advertising) 在 Google Analytics (Advertising) 提供支持的站点上投放数字广告。根据 Google Analytics (Advertising) 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Google Analytics (Advertising) 收集的与您相关的数据相整合。我们利用发送给 Google Analytics (Advertising) 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Google Analytics (Advertising) 隐私政策
      Trendkite
      我们通过 Trendkite 在 Trendkite 提供支持的站点上投放数字广告。根据 Trendkite 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Trendkite 收集的与您相关的数据相整合。我们利用发送给 Trendkite 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Trendkite 隐私政策
      Hotjar
      我们通过 Hotjar 在 Hotjar 提供支持的站点上投放数字广告。根据 Hotjar 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Hotjar 收集的与您相关的数据相整合。我们利用发送给 Hotjar 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Hotjar 隐私政策
      6 Sense
      我们通过 6 Sense 在 6 Sense 提供支持的站点上投放数字广告。根据 6 Sense 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 6 Sense 收集的与您相关的数据相整合。我们利用发送给 6 Sense 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. 6 Sense 隐私政策
      Terminus
      我们通过 Terminus 在 Terminus 提供支持的站点上投放数字广告。根据 Terminus 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 Terminus 收集的与您相关的数据相整合。我们利用发送给 Terminus 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. Terminus 隐私政策
      StackAdapt
      我们通过 StackAdapt 在 StackAdapt 提供支持的站点上投放数字广告。根据 StackAdapt 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 StackAdapt 收集的与您相关的数据相整合。我们利用发送给 StackAdapt 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. StackAdapt 隐私政策
      The Trade Desk
      我们通过 The Trade Desk 在 The Trade Desk 提供支持的站点上投放数字广告。根据 The Trade Desk 数据以及我们收集的与您在站点中的活动相关的数据,有针对性地提供广告。我们收集的数据可能包含您访问的页面、您启动的试用版、您播放的视频、您购买的东西、您的 IP 地址或设备 ID。可能会将此信息与 The Trade Desk 收集的与您相关的数据相整合。我们利用发送给 The Trade Desk 的数据为您提供更具个性化的数字广告体验并向您展现相关性更强的广告。. The Trade Desk 隐私政策
      RollWorks
      We use RollWorks to deploy digital advertising on sites supported by RollWorks. Ads are based on both RollWorks data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that RollWorks has collected from you. We use the data that we provide to RollWorks to better customize your digital advertising experience and present you with more relevant ads. RollWorks Privacy Policy

      是否确定要简化联机体验?

      我们希望您能够从我们这里获得良好体验。对于上一屏幕中的类别,如果选择“是”,我们将收集并使用您的数据以自定义您的体验并为您构建更好的应用程序。您可以访问我们的“隐私声明”,根据需要更改您的设置。

      个性化您的体验,选择由您来做。

      我们重视隐私权。我们收集的数据可以帮助我们了解您对我们产品的使用情况、您可能感兴趣的信息以及我们可以在哪些方面做出改善以使您与 Autodesk 的沟通更为顺畅。

      我们是否可以收集并使用您的数据,从而为您打造个性化的体验?

      通过管理您在此站点的隐私设置来了解个性化体验的好处,或访问我们的隐私声明详细了解您的可用选项。