Environment Variables

TWiGS host Chris Adams is joined by guest Savannah Goodman from Google, to bring you the latest news and updates from the world of sustainable software development. They discuss insights from Google’s Sustainability report, the need for a fossil fuel free internet by 2030 and the importance of microgrids and nanogrids. They also highlight Google's sustainability tools including Cloud Region Picker, ActiveAssist and  Carbon Footprint.Learn more about our people:Chris Adams: LinkedIn | GitHub | WebsiteSavannah Goodman: LinkedInFind out more about the GSF:The Green Software Foundation Website Sign up to the Green Software Foundation NewsletterTopics:We need a fossil fuel free internet by 2030  | Branch Magazine [6:38]Tesla Megapack | Microgrids & Tesla [12:27]Google Sustainability Goals | Google [21:19] Google & Fervo Geothermal Partnership | Google  [22:58]Google Cloud Region Picker | Google [26:44]Google Active Assist | Google [29:20]Google Carbon Footprint | Google [30:13]The Realtime Cloud Project | Green Software Foundation [32:15]Resources:Octopus Energy  [15:04]The Week in Green Software: Modelling Carbon Aware Software | Environment Variables episode with Iegor Riepen at TU Berlin [20:07]UN Global 24/7 Compact | UN [24:46]Vincent Poncet LinkedIn | Linux Foundation [32:08]If you enjoyed this episode then please either:Follow, rate, and review on Apple PodcastsFollow and rate on SpotifyWatch our videos on The Green Software Foundation YouTube Channel!Connect with us on Twitter, Github and LinkedIn!TRANSCRIPT BELOW:Savannah Goodman: [00:00:00] While it's important for us to reduce our own carbon footprint, we think the opportunity to provide these flexibility services to the grid will actually help drive broader system decarbonization and allow for broader carbon emission reduction.Chris Adams: Hello, and welcome to another episode of This Week in Green Software, where we bring you the latest news and updates from the world of sustainable software development. your host, Chris Adams. when we talk about green software, whether you're diving into papers about carbon aware computing. or hearing someone talk about GreenOps, a new [00:01:00] variation of the term DevOps, or even as a consumer, looking at the work that the company's been doing to make it easier to understand how you can reduce the carbon footprint of things like flying. It's hard to escape the work of Google when you look at climate and tech. be honest, it's not that surprising. They operate at a scale that's hard for many of us to really comprehend. Alphabet, the holding company for Google, has a market capitalization of 1. 75 trillion dollars these days. And they use enough digital infrastructure to really care. Their own sustainability report in 2023 shows that Google used something in the region of 22 terawatt hours of electricity last year. This is not a small company. Since 2007, they've generally been one of the leaders when it comes to decarbonizing infrastructure. And recently, they set a public goal to match every hour of power they use with an hour of generation from carbon free sources by 2030. This is something we've seen a [00:02:00] number of organizations get behind, and even the UN with their recent 24 7 compact. So we know there's a lot of smart people working at Google, working on the greening of digital. And today, I'm joined by Savannah Goodman from Google to talk about the finer points of doing green software at scale. Hi Savannah, the floor is yours to introduce yourself.Savannah Goodman: Thanks, Chris. Hi, everyone. I'm Savannah Goodman. I lead the data and software climate solutions team at Google, and I'm super excited to be here. I'm an energy nerd at heart, and I've been studying and working in the climate space for the last decade.Chris Adams: Thank you, Savannah. Okay, so if you are new to this podcast, here's a quick reminder of how it tends to work. Uh, When we mention projects or papers or any links like that, we'll add them into the show notes. And if there's a thing that you heard us talk about that you'd really like to learn more about, please do leave a comment.It really helps other people who are trying to actually learn things about this as well. The other thing I should probably do is introduce myself. My name is Chris [00:03:00] Adams. I work at the Green Web Foundation, a nonprofit focused on reaching an entirely fossil free internet by 2030. And I'm also one of the chairs of the policy work group inside the Green Software Foundation, which Google is also a member of. All right. I think that's pretty much it. Savannah, if you're happy for us to go and sitting comfortably, shall we start?Savannah Goodman: Yeah, let's go for it.Chris Adams: All right. Okay. So we're going to talk about some of the cool carbon intelligent computing stuff that Google does shortly, but before we dive into there, I figured it might help to talk a little bit about how you got here first, because as I understand it, you've worked with technology that interacts with grids at various scales in your career.And if we start at the small end, I realize that if you're going to be talking about data centers, it helps developers to understand some of the principles that are behind the kind of power grids in the first place. And this is something you worked on before. And I think what I learned about was there was a project that you worked [00:04:00] on previously with the idea of an off grid internet cafe in a box.This seemed too cool to not ask you about basically. So I should ask, how did this come about before you worked at Google?Savannah Goodman: Yeah. Yeah. Thank you for asking. It was a super interesting project and happy to get the chance to start small and then go all the way to data centers. But yeah, I was in grad school and I was interning at a company that was focused on improving energy access in East Africa. And they were working on a couple of different products for pretty specific applications and they were really tailored to the needs of the local communities that we were working with.So just a few examples, they had very small microgrids, you'd maybe almost call it a nanogrid to provide lighting at night or to charge a few cell phones. So really small kind of mobile solar and storage. And during their research they identified one of the other kind of key pain points in these [00:05:00] communities was the need for better and more reliable internet access.And while some internet cafes existed in the cities, they could be cost prohibitive, they may be very far from some of the local communities, and oftentimes they were actually unreliable because of grid reliability issues in the region. And so my job was essentially to do the research and propose what an off grid internet cafe in a box might look like as a product, and how it could actually solve the pain points in thesefrom these local users. And so I did a lot of really interesting landscape research, developed some product specs, and ultimately also came up with the business case. And I think what I really liked most about this project was the fact that it had a ton of potential impact. I was really excited about the idea of enabling information access for everyone, not just folks in developed countries and big cities, and especially through more [00:06:00] reliable clean energy access.Chris Adams: It's actually timely that we're having this conversation now, just after COP28, because we've seen a few specific announcements that tie into this, actually, things like this goal of tripling renewables globally, for example, by 2030. And there's actually, it's interesting that you talk about some of those things there, because T that was maybe a few years back, and I want to ask you, if you were to come back to this, were there any trends that you saw back then that you might have seen playing out that you'd probably look for immediately, or you'd probably want to dive into if you were coming back to this?Because you mentioned some things like nanogrids, and the idea of moving past basically fossil based generation, because we know in lots of places, like for example Nigeria, You still have two thirds of the power is coming from generation rather than the grid. So it's extremely dirty power compared to what you have now. Maybe I'll just give it a bit of space for you to say what you would be looking for, what you're excited about seeing over the next few years in this particular field.Savannah Goodman: Yeah, thank you. It's definitely some really interesting trends and a [00:07:00] lot has changed even since I was in grad school. And I think one of the first things I remember thinking about is how big, right? What is the optimal size of a microgrid? I mentioned this term nanogrid, which was, like I said, a few solar panels, a small battery that was very mobile.I think that that sort of solution can target a few very specific and acute pain points, but didn't necessarily, I think, scale to the level that these companies were looking to have, especially given the impact that they wanted to drive. So I think one of the interesting trends we've seen is maybe moving from these nano grids towards more true micro grids that can enable multiple applications and are not necessarily mobile, but actually require more robust grid infrastructure.And so that's something very interesting and especially in the context of the developed region, especially in the U. S. where I'm from, grid infrastructure is a very big focus right now. And I think it'll be [00:08:00] really interesting to see how we can take some of the learnings of how we've grown our own grid infrastructure and hopefully leapfrog in some of these areas that don't quite have the existing distribution or transmission build out.Certainly a challenge as I don't think we've fully figured it out for ourselves, but there's definitely a lot of lessons learned along the way. So I think that's . Something really interesting that will play out. Another area that always really stood out to me was the energy and water nexus. And this is something that is really important in a lot of developed countries where there's also a lack of clean water access.And there's been a lot of kind of technology development over the last decade, and I'm sure there will continue to be. And I think the challenge with this is more, again, the kind of go to market of those products. How do we actually ensure that these products fulfill really specific needs and have an appropriate business model that actually meshes well with the type of [00:09:00] communities that need it most.So that's an interesting one that I'm really curious to see how this will continue, especially as there's more and more focus on the global south and adaptation for climate change, which is closely tied both to water and energy as well. And then the last thing. Chris Adams: Oh if I can just stop you there, you said you introduced this term, which some other listeners might not be so familiar with. You mentioned the energy water nexus. Could you maybe expand on that a little bit? This is the idea that basically generating water uses energy, but there's also a flip side to that.Could you maybe expand on that? Because I think that's quite an interesting topicSavannah Goodman: Yeah.Chris Adams: up some people's ears actually.Savannah Goodman: Yeah, definitely. And, um, I think there's, yeah, this sort of exciting concept of the fact that energy and water are two absolutely necessary resources for thriving communities. Like you said, you can, you need usually energy to make water accessible, especially to make it clean and to make it drinkable and portable, right?There's usually some sort, usually using [00:10:00] electricity to do that can be really effective. There's other ways to do it without electricity, but it's a lot more challenging to have infrastructure that scales and is robust enough. The flip side too is water can be a really great energy source. We think of pump storage and hydro, and that's really important for providing clean, dispatchable resources.Of course, hydro is very dependent on the weather and the climate, and as climate changes, it can become actually a less reliable resource. And so there's just a lot of interesting intersections there. We can also think about the climate impacts and droughts and how that might impact both water access for drinking, but also for energy.So, it's a generic term, but it's intended to capture the fact that there's actually a lot of intersection and dependencies between these two fields both ways, and I think it's a really important focus area, right, as we think about you know, impacts on the climate and how communities are going to need to adapt.Chris Adams: Thank you. That's really useful. I [00:11:00] didn't, I've been looking for a term to describe some of this and this immediately makes me think of, say in France or in Germany, where we saw in the heat wave last year, for example, we saw some of this, we saw the reliance on water from things like say nuclear power stations in France, for example, which were essentially. They end up having to come offline in some cases simply because they didn't have enough access to water to actually keep them cool, for example. And this is something that a lot of us don't really think about necessarily in the first place. Okay. It's power, but where does the water fit into this? But flipping, that's actually a really good example of some of this. Okay, cool. So we spoke a little bit about grids. You mentioned that there's like nano grids and say slightly larger grids, like a micro grid. It's worth moving to there, actually, because I understand that when you were working at that company, then you've also worked at Tesla working with microgrids. And when most of us think about, say Tesla, they might think about electric cars more than microgrids. And in fact, I suspect that most developers might not have heard what a microgrid actually is. So for people who are not familiar [00:12:00] with the term, you maybe just explain what a microgrid might actually be? And just to give people some context, because we'll talk about how this relates to data centers a little bit later, but in the short term, maybe you could just briefly provide a kind of microgrid 101 and why you might care about it, why an electric car company might care about some of this, because that will probably be useful context when we talk about data centers and how they integrate with grids and stuff like that.Savannah Goodman: Yeah, absolutely. So a microgrid is a localized group of energy sources and loads that can typically operate independently of a larger grid system. And so this sort of independent network of resources can be useful for a few reasons. First, microgrids can improve energy security and reliability. They tend to be less vulnerable to large scale outages because they can usually kind of disconnect or what we might call island and continue to [00:13:00] operate even if the main grid system goes down.So this is especially beneficial for critical loads. So oftentimes hospitals or emergency shelters may have their own kind of generators and may be able to create their own sort of micro grids. Further, microgrids can actually help reduce, you know, the cost in carbon, uh, depending on the situation. So, for example, a lot of island nations typically have some form of microgrids.Because they're not physically connected to large land areas that have the privilege of having these large scale grids and a lot of infrastructure and robustness. And so while a lot of these island microgrids have historically relied on diesel generators, they can instead integrate wind, solar, and batteries, which can then actually reduce the cost compared to diesel, importing diesel, and will actually reduce the carbon emissions.So that's another big advantage of, or opportunity for microgrids. And to answer your other question on [00:14:00] why companies like Tesla might have incentives to build batteries for the grid, it's really a way for them to scale their battery production for EVs. So Tesla Energy was created actually a while back and it really helped drive down the costs of manufacturing batteries at scale, and it also has the, you know, added benefit of actually creating new business value, new business lines for the company. And the other thing I would say is there's also some really interesting synergies between electric vehicle charging and using grid connected batteries to manage consumption spikes and, and some of the charging costs.So when Tesla deployed the supercharger network, they also looked at deploying grid scale batteries at those charging networks to help manage the costs that they were paying to the electric utilities. So it not only can be a business line, but batteries for the grid can be used to help manage their overall kind of infrastructure costs for the [00:15:00] EVs.Chris Adams: Ah okay, so that makes it a bit clearer for me to understand, and also this makes me think of some of the stuff we've recently seen in the UK, for example, there's a company called Octopus Energy, they're an energy company, and they basically They have this new deal working with people who are building homes and they have this kind of this deal basically if you have batteries or renewable energy fitted into the house when it's being built they're offering zero energy bills for the next for the first five years as long as you're able to make the house integrate into the grid and it seems to be like you said because sometimes energy is expensive when there's, it might be cheap when there's lots of renewables on the grid.For example, it's taking advantage of some of that and storing energy when it's cheap and then using it locally rather than having to buy expensive energy from the grid and vice versa. Ah, okay. That helps me understand that now. Thank you. you said something else, actually, about the fact that you've got grids which are interconnected.So they're independent, but they're connected in some ways because there's a larger thing. This made me think a lot about the internet, actually, how the internet is [00:16:00] basically made of a series of smaller networks which are interacting with larger networks. So there's some parallels there. And I can imagine how some of these ideas might scale all the way up to something like a large hyperscale data center. I suspect there's probably a bit more to it than that. And I guess this is probably where the work that you've been doing with Google might come in, actually. So for folks who are following along for the ride, when you're talking about, say, hyperscale data centers versus micro grids or small grids here, what are the differences when you're working at that different kind of scale, for example?And is this idea that, okay, you've got a series of small grids connected. That's a little bit like the internet. Is that a comparison that you could really make? Well, maybe you could just expand on that a bit more. Cause that's what I immediately think about when you talk to me about series of grids connected to each other, for example.Savannah Goodman: Yeah, I think that's a great analogy. Like you said, the internet is made up all of these different kind of nodes and is really a network of nodes and connection points. And that's [00:17:00] exactly what the grid is. And some areas are better connected, right? They have more interconnectivity and nodes, and that can make them more reliable than others.Also similar to the internet, because there's this network and different demand and supply pockets. There can be congestion of just like there may be network congestion for internet or data transfer. There can be grid congestion for the flow of electrons. And so keeping this in mind, as I alluded to earlier, there are a lot of opportunities to really better optimize the grid when you have flexible resources, whether it's EV charging or storage for the grid. This flexibility makes it a lot easier to manage the grid during peak times. The example you, you mentioned with Octopus, I think is a great one, where they're fully recognizing the value of having flexible grid to the point where they won't even charge you for the energy because they know that's really important for the way they manage their portfolio.And so for data centers, the way that we [00:18:00] contribute to this load flexibility is we can actually shift our compute load. And we can do that in response to signals from the grid in specific locations, where there may be congestion or during kind of the peak times of the grid. And this is what we would typically call demand response.And just,Chris Adams: Ah, okay.Savannah Goodman: yeah, and it's- Demand response has actually been around for a long time, but what's really, I think, new and innovative about what we're doing at Google is leveraging compute demand to be able to participate in these demand response programs. Historically, demand response has typically been from industrial factories who are turning down their manufacturing or from thermostats, right, who are turning down the heating.But what's really great about compute load is that it's a virtual load. And so the fact that we can shift it not only in time. But also in space is really, um, the unique part of, of, um, compute. And we've [00:19:00] actually been shifting compute at, at Google for a few years now. Historically, we were shifting in response to a carbon intensity signal from the grid.In order to minimize our own carbon emissions. And for demand response, we do it a little bit differently. We will typically receive a notification from the grid operator, or we'll agree on the local peak time. And then we dispatch our kind of global compute planning system to overwrite that existing schedule that was carbon optimized.And that basically limits non urgent compute tasks for the duration of that event at the data center. And I think we're really excited about these capabilities because while it's important for us to reduce our own carbon footprint, we think the opportunity to provide these flexibility services to the grid.Will actually help drive broader system decarbonization and allow for broader carbon emission reduction through enabling the increase in clean [00:20:00] energy and just being able to turn down load when the grid is being supported by gas peakers, for example.Chris Adams: I see. Okay. So for people who may have listened to this before, we, we did a podcast with, I think, I believe his name is Igor Repin at the Technical University of Berlin. He was talking and going into quite a lot of really nerdy detail about how some of this stuff was modeled on the European grid to explain this and saying, if you're able to smooth out these kinds of spikes, then you don't need to actually have quite so much infrastructure in the first place.Or it may be that you don't need to have things like, say, as many peaker plants, often tend to be very carbon intensive and tend to burn a lot of fossil fuels. I see now. All right then. So maybe we can actually just talk a little bit about this being part of a of broader strategy. So we spoke a little bit about there being a kind of target to be entirely fossil free by 2030, for example. Is it a chance we could maybe just dive into some of that a bit more? Because for most of us U understanding [00:21:00] why you'd have a target to be running entirely a fossil free energy by 2030 might not be obvious to everyone. And sorry, I think the term that Google uses is carbon free, but basically this idea of you want to have things running 24 7 rather than just saying, having an annual kind of claim, for example. Could you talk a little bit about some of that and what some of the thinking behind that might have been?Savannah Goodman: Yeah, definitely. So As you mentioned, Google has two main climate goals. One of them is to be net zero by 2030. The other is to be running on 24 7 carbon free energy by 2030. And just to clarify too, 24 7 carbon free energy is much more complex. Than the annual matching schemes that have been most common to date, because we're essentially moving from global annual matching to local hourly matching.And so you can imagine how, especially over a global, uh, system, how complex that gets and there's no playbook. But we see these goals as a way to actually help scale new [00:22:00] global solutions that drive broader system wide decarbonization because we're actually aligning our own goals with what the grid needs.Through these hourly local matching, that's how the grid operates, right? It operates, you have to have local constraints. You have to match supply and demand every hour. And so we've seen research from folks like TU Berlin and Princeton and the IEA that show 24 seven procurement is one of the best ways.For corporates to help accelerate the energy transition towards grids operating on clean energy every hour, every day. And for 24 7, load flexibility is really complementary because it provides this nhe gew sort of flexible resource that can help us better match the clean energy that's on the grid or the clean energy that we procure on a local hourly basis.So we're also looking, besides load flexibility, at other new next gen technologies like geothermal. We've [00:23:00] announced the starting operations of our geothermal plant with Fervo in Nevada. We're also really excited about battery storage. And there's a lot of other technologies that we're looking at, and research shows that having this diverse portfolio, both of Load flexibility and next gen technologies is what can make 24 7 more cost effective and more accessible and actually meet the grid needs, especially when we consider rising demand in electricity from things like electrification and data center growth.So, so yeah, all of this demand response effort is really a key part of our kind of sustainability strategy, and we've recently announced a couple of pilots to prove out that this is real, this can work, it has benefits for us, it has benefits for the grid, and we're going to continue to evolve our capabilities and work with our utility and grid operator partners to make sure that we're maximizing the shared impact [00:24:00] of this system.Chris Adams: ah, okay. So it sounds like rather than just we're saying I'm going to buy a green energy tariff and that, it's all more I want to shift the entire paradigm that the grid actually operates on. And I know that Microsoft have also come on board, but they're not going to call it 24 7, of course, because that's what's called by the competitor.So they're using the term 100, 100, 0. I think it's 100 percent of the time. Coming from a hundred percent renewable energy or zero carbon. It's something like that. It's not as easy to remember as 24 seven, but that's one thing we've seen. And we've also seen the federal government. I believe they've made us, they made it last year, actually saying they're aiming to have by 2030, 50 percent of all of their power. And that's the entire federal government, not just a single company, for example. So that was like another example of this. Okay, cool. And I think we might have alluded to this. This is actually a kind of wider scheme. The UN has this global 24 7 compact that any organization can sign on to and get on board with as well, I think, right?Savannah Goodman: Yeah, exactly. And we're really excited to see during COP that the US government officially also [00:25:00] signed on to the compact. There's over 100 signatories at this point. And I think what's most exciting to me is that it is really a community of different kinds of companies and organizations from all across The energy sector that need to come together.So there's some energy buyers. There's energy suppliers. There's governments. There's cities. There's software and data providers. There's hardware providers. And I think we're not going to do this alone. But what we're really excited about is creating this ecosystem And developing technologies to advance that ecosystem so that we can all collectively work together to meet the ambitious decarbonization goals for the grid that are really needed to enable the broader climate targets for 1.5 degrees.  Chris Adams: I see. Okay. All right. Thank you for that. So we've spoken a little bit about data centers and how flexibility there can actually have some kind of impact inside this. And we spoke also a little bit about, [00:26:00] uh, the kind of wider context of why you might think about this in terms of decarbonizing a grid. This gives a bit of visibility there, and you spoke about some internal things. Maybe we could talk a little bit about some of the things that end users of services that, say, Google might offer, might use, because we've got a lot of developers who use, say, Google Cloud Platform or even other such platforms as well, and I know that I've used some of Google's tools previously, and I know that there's some projects inside the GSF, the Green Software Foundation, that talk about this and are contributing to that, but maybe you could just tell touch on some of the tooling that you've seen in use or made available for end users, because there's a couple of cool things, which I think are worth develop, worth some of our listeners not knowing about.Savannah Goodman: Yeah, absolutely. And just to set the context right now, as part of our Carbon Intelligent Compute or our demand response programs, we're not actually shifting customer workloads. We're focused first on shifting some of the internal workloads that operate Google [00:27:00] products like YouTube videos and things like that.However, we're very keen on exploring with customers who are interested in reducing their footprint to shift their customer workloads. In the meantime, we've developed some tools that can help these cloud customers reduce their carbon footprint themselves. And so, just to talk through a couple of the different tools, one of the first ones we launched was called the Region Picker.The Region Picker allows customers to look at all of the different kind of characteristics that they may want to optimize for, in particular, latency, cost, and then carbon footprint. And based on,Chris Adams: Hmm.Savannah Goodman: you can essentially adjust the weighting of those different Aspects, depending on what is most important for you and your business.And based on that, the tool will actually provide you a optimal region or a set of optimal regions to site your new workloads in. And this tool, we've also embedded [00:28:00] the essentially green leafs into the cloud platform. So when customers are choosing regions, they can actually see which ones are cleaner.by based on meeting a certain threshold of carbon free energy. The reason we started with the region picker tool is through our own analysis and data we've seen that one of the most, pretty much the most impactful factor when siting workloads is location. So, eventually we'd love to be able to shift workloads in time as well for customers, but this spatial sort of shifting or site selection is really impactful because customers can move their workloads from a dirty to a clean grid, and that makes a really big difference.Chris Adams: So the region picker, for people who haven't seen this before, as I understand it, when you're using this, it basically gives you an idea of saying if your audience is in Germany, rather than running it in say, one part of there, you might want to consider looking at Switzerland. Who are still in the same place, but have much, much cleaner power, for example, [00:29:00] and still would be staying inside your latency requirements is tools like that.And that's the kind of stuff that I, uh, that I saw. And I think that's the first time I've ever seen any large organization sharing some of that stuff. So that is included in active assist now, or some of the tools inside Google. Is that what you were saying?Savannah Goodman: Yeah, that's exactly right. That's part of our region picker tool. The active assist tool can help customers reduce their footprint in a slightly different way. So the focus of the active assist tool is, let's say customers have some projects that have just been running in the background. The ActiveAssist tool can recommend automatically certain optimizations, could turn down a project, or minimize the runtime of a project, which will not only help reduce cost, but also reduce carbon.So the ActiveAssist tool is using machine learning and AI to serve predictions and recommendations for cloud customers.Chris Adams: So the active assisting, so it's a bit like, so yes, there's AI and things, but it also just tells you, by [00:30:00] the way, mate, you've left your computer on, or you've left this project running. Maybe you want to turn it off if it's not serving any traffic, because this is one thing that comes up. It'll basically do some stuff like that, as well as providing some specific, much more tailored recommendations as well.Yeah? Savannah Goodman: Yeah, exactly. That's right. And then the last tool that we've developed is called Carbon Footprint. And this is really a reporting tool. There's also some kind of insights that customers can glean to optimize how they're setting up their infrastructure. But this is the rounding out the suite of tools we developed.It helps customers understand what their actual carbon footprint is from the use of cloud services. So as they make changes, They can see how that impacts the trends of their carbon footprint over time, and they can also use the data for their own corporate reporting. Usually the use of cloud falls into a customer's scope three, indirect emissions, and so this is an important, an important [00:31:00] reporting tool for our customers to be able to meet their reporting needs.Chris Adams: I see. Okay. And this is something that is just built into the system from day one, or is it part of something you need to purchase separately, for example?Savannah Goodman: So this tool is available and free for everyone in the cloud console, can access it directly and it's organized per billing account. You can see pretty granular data too, per month, per project, per region. So there's a lot of different ways you can slice and dice the data. There's also a data export, right?If you want to integrate that data directly into some of your own dashboarding and marry it with other kind of cloud operations data. So yep, it's free and available for everyone on Google Cloud.Chris Adams: Cool. Thank you for that, Savannah. All right, then. So I know that you work for a specific vendor, and I am mindful of us spending too much time talking about this, because I know that, I can see why it's useful for one company to share this visibility. And from the perspective of a non profit, I'm glad that there's one company pushing this stuff and has been. forthcoming sharing this information compared to some of the other providers in this [00:32:00] kind of space. And I know that from speaking to one of your colleagues, I think Vincent, I never pronounce, I'm going to pronounce, mispronounce his name, Ponset or Ponset. He's also, he's been involved in some of this as well.And I met him at the Linux Foundation at LF Energy Summit in, in, in Paris, basically. I understand that there's a project called the Green Software Foundation Real Time Cloud Project, which is, being led by both Adrian Cockcroft and Pindy. I, oh, Pindy, I totally forgot your surname, but there's, we have a couple of people inside the GSF who are members who are leading on this, maybe we could talk a little bit about why that's important and why as a member of GSF, you've been involved in some of these projects to create some kind of consistency and conventions around this data that gets exported or exposed to customers.Savannah Goodman: Yeah, definitely. So we've heard from our customers that the data we're providing is super helpful, but they also need more, more transparent data that's consistent and comparable across their cloud providers. [00:33:00] Often customers will have multi tenant use cases and will have multiple cloud providers. And so it's really important that we can provide more accurate data, more transparent data and comparable data to help them, like I mentioned, with their reporting needs.And to also make better informed decision for taking action within the cloud environment on how to reduce their carbon emissions. And so we're really excited to be working on the cloud project with Green Software Foundation. Um, that's looking at two main use cases for the project. The first one is this emissions reporting, and the second one is really carbon optimization.Ideally, these two use cases would be tied closely together, but in reality, because of the way the current accounting and auditing systems work, the reporting Use case typically has a significant lag in the data. And so we're hoping that this project will enable better standardization across metrics for better comparability for reporting.But at the same [00:34:00] time, we think there's a lot of opportunity to provide more real time, more accurate data for the optimization aspects. And so we're hoping to develop methodologies and tools that can enable cloud providers to offer this more granular and realtime Data. That will support the carbon optimization use case in the near term and then ultimately with the goal of reducing the lag of carbon reporting in the long term . So we're super eager actually to explore working with our cloud customers and seeing what tools are most useful for them, what metrics, how can we help them optimize their carbon footprint, whether it's in an automated way.Through our own carbon intelligent compute system or through the tools that we're providing through the console.Chris Adams: gotcha. Okay. Thanks for clearing some of that up. And I know that because I'm also in that working group right now, I can actually speak to you and say, quite honestly, that some two years ago, Google started publishing some of the information at a kind of region by region basis, showing [00:35:00] like the carbon intensity or like the amount of power that is considered carbon free for every single region, um, sharing it as like a CSV on GitHub. This has actually been really helpful to provide a kind of starting point for sorting out some kind of consistent metric, consistent way of reporting this or requesting this from different providers. Cause we know that Amazon has a cloud calculator and Google has a cloud one and Microsoft have one, but having a consistent thing to refer to has been really helpful for this and it's made it quite a bit easier to then say. For example, I'm glad that Google has been one of the earlier companies to talk about information, emissions across all three scopes, scope one, two, and three. And this is something that we don't have from all the providers right now. So being able to point to an example and a data set has been really helpful in this scenario here. I wanted to ask you, coming to the end of the time for this chat, and we've spoken a little bit about like changing some of the kind of paradigms around, rather than basically just buying green energy, like essentially changing how [00:36:00] people think about using power to actually incentivize more carbon aware or approaches for reducing the emissions associated technology, for example. I want to ask you, is there anything that you'd like me to draw attention to? Or you, you reckon we should talk about as well, because we've covered quite a ssions ssions lot of ground from like nanogrids all the way up to ginormous data centers that use as much power as small cities, basically. So what else are you looking at or what else would you like to draw people's attention to right now in this field?Savannah Goodman: Yeah, I think overall we're super excited about the potential for green software to reduce emissions. I think there's a lot of different ways that we can go about making software more green, whether it's through our hyper scale carbon intelligent compute type platforms or even individual developers choosing cleaner regions for their workloads.We're really optimistic about how these solutions can come together to enable broader capabilities across the GSF community and beyond. [00:37:00] We think that load flexibility is such an important part for the future of the grid and we think software has some really unique Flexible capabilities that other kind of loads don't necessarily have.And so, that's why we're really thrilled to be part of this community to see how we can really maximize the, you know, level of flexibility that green software can offer to really help drive the energy transition at the broader grid scale and reduce carbon emissions.Chris Adams: Brilliant. All right, then I think we're coming up to the end of our time. So I just want to ask if people have, if their interest has been peaked by any of this, where would you suggest people look, or if people were interested about what you're doing specifically, where would you suggest people look to follow on for updates about what's taking place in this field, beyond the projects we just mentioned, like the real time cloud thing in GitHub, or like Google's account on GitHub, for example, or some of the other things. So maybe, let's say I'm a developer. I'm [00:38:00] curious about some of this. I don't know where to look. Where should I be looking to learn more about this or continue my research?Savannah Goodman: Yeah, definitely. So we publish quite a few updates through the sustainability topics in the Google Cloud blog where you can see the updates on the latest work and not just for green software, but a lot of the different sustainability areas that we're developing new technologies for. If you're interested in learning more about kind of Google's overall strategy, not just cloud specific, Sustainability work, then google.com/sustainability . It's a good place to start. That's where we publish all of our papers and annual reports. But yeah, otherwise, we definitely recommend the Google Cloud blog and following the sustainability topic. Lots of exciting updates to come.Chris Adams: Brilliant. Okay. And what we'll do now is we'll just try. And if, if you're a listener and you've listened to some of this and you caught your eye, we're going to take a moment now to just get as many links as possible to all this stuff that we've spoke about, because we've covered a lot of ground. All right. Savannah, I've enjoyed this. I've learned [00:39:00] a lot and I think our listeners probably have as well. I want to wish you have a lovely week and yeah. Have a lovely winter break. If you're, if you celebrate your time away over winter.Savannah Goodman: Thank you so much. Have a good one.Chris Adams: Okay. Cheers.​[00:40:00] 

From the recent Decarbonize Software 2023 event, this episode showcases a fireside chat on Responsible AI with Tammy McClellan from Microsoft and Jesse McCrosky from ThoughtWorks. Jesse shares his thoughts and experiences from years of working in the field of Sustainable Tech on the topics of risks, sustainability, and more regarding AI, before answering some questions from the audience. Learn more about our people:Sophie Trinder: LinkedInJesse McCrosky: LinkedIn | WebsiteTammy McClellan: LinkedInFind out more about the GSF:The Green Software Foundation Website Sign up to the Green Software Foundation NewsletterEvents:Decarbonize Software | GSF Resources:AI Transparency in Practice | Mozilla Foundation [04:19] Reducing bias and improving safety in DALL·E 2 | OpenAI [09:31] Responsible AI: Fireside Chat | Decarb 2023 [18:41]If you enjoyed this episode then please either:Follow, rate, and review on Apple PodcastsFollow and rate on SpotifyWatch our videos on The Green Software Foundation YouTube Channel!Connect with us on Twitter, Github and LinkedIn!TRANSCRIPT BELOW:Asim Hussain: Hello, and welcome to Environment Variables brought to you by the Green Software Foundation. In each episode, we discuss the latest news and events surrounding green software. On our show, you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software.Chris Skipper: Welcome to Environment Variables. Today, we've got another highlight from the recent Decarbonize Software 2023 event. We'll be showcasing the fireside chat on Responsible AI from Jesse McCrosky, Head of Sustainability and Social Change and Principal Data Scientist at ThoughtWorks, and Tammy McClellan, Senior Cloud Solution Architect at Microsoft and Co-Chair of the Community Working Group and Oversight Committee at the Green Software Foundation. They are introduced by our very own Senior Technical Project Manager for open source projects, Sophie Trinder, so it will be her voice that you hear first. So, without further ado, here's the Fireside Chat on Responsible AI.Sophie Trinder: Hi everyone, I'm Sophie, the technical project manager for our open source projects at the Green Software Foundation. Today I'm going to introduce a special fireside chat to our Decarbonize Software event. We're continuing the conversation that began on the 5th of October at our panel on responsible AI. The conversation surrounding responsible AI is dynamic, oscillating between optimism and skepticism. one side, practitioners believe that AI has the potential to drive sustainable development goals, from responsible consumption to waste management and energy conservation. The promise lies in our improvements in measuring software's environmental impacts, and innovation across energy-efficient algorithms, hardware optimizations, and the growing use of renewable energy sources. On the other side, the rapid expansion of AI, particularly large learning language models, and the insatiable demand for this technology, are raising concerns. If left unchecked, the energy consumption and resource utilization associated with AI make many feel like we're endangering a future where software causes zero harmful environmental impacts. To help us explore the path forward, I'm thrilled to introduce Tammy McClellan, Senior Cloud Solution Architect at Microsoft, and Jesse McCrosky, Head of Responsible Tech and Principal Data Scientist at ThoughtWorks. Thanks, both. Take it away.Tammy McClellan: Thanks, Sophie. And a hello to all you sustainability addicts. Jesse, hello. Let's start the question with, how do you see the relationship between responsible AI and sustainability?Jesse McCrosky: Hey Tammy, great question and nice to see you all. So at ThoughtWorks we use a framework that I like which we refer to as the greening of tech and greening by tech and I think this is the best lens through which to view that question. Greening of tech refers to the fact that these systems and especially generative AI as we're talking about now have serious energy consumption, they have serious sustainability issues that need to be tackled.The other side is greening by tech and recognizes the potential that this technology has to actually improve sustainability of other processes, either within or outside of the tech world. And I think what ties these, these two questions together is issues of transparency and information and ensuring that people have the information they need to make the right decisions for our environment.Tammy McClellan: I like that, greening of tech and greening for tech. It's my new mantra now. So how can, uh, we use this to make more sustainable solutions?Jesse McCrosky: So it's a big question. To begin with, I think that I refer to transparency, and when we talk about transparency, a lot of people think that means you share your source code, or you share your model weights, and then you're transparent. Or it means you have to explain the decisions the AI is making, and that's transparency. Transparency is more than that. There's a report I did with the Mozilla Foundation on AI transparency, and we talk about meaningful AI transparency that needs to be legible, auditable, and actionable. And this means that we have to consider the specific stakeholders that the information is being provided to, what are their needs, what are they going to do with this information. So it comes down to the old adage that you can't manage what you can't measure. So for example, in order to support meaningful policy, meaningful regulation, we need to have information about the sustainability characteristics of these systems.Tammy McClellan: So talk to us a little bit about some possible solutions in this area.Jesse McCrosky: Yeah, absolutely. So when we're looking at solutions, especially using the kind of transparency lens, we can think about who is the transparency being provided to. So, for example, we can talk about consumers. And right now, consumers are very excited about ChatGPT or whatever else, Stable Diffusion, DALL-E, and everything like that. It's a lot of fun to play with. And they do not have meaningful information about the carbon implications of that play. So someone was suggesting to me that ChatGPT should have a real-time counter across the top somewhere that's telling you how much carbon have you emitted so far in your session, how many, you know, gallons of water have been consumed, whatever else. And it is not a matter of just shaming people, but it's helping people make the right choices, because there might be applications for which ChatGPT is really worthwhile to use, but there's other times that somebody's just idly playing or something like that, and if they realize the implications of doing, they might make other choices. This becomes more interesting when we talk about communication between, for example, model developers and model deployers. So, for example, if somebody is using the OpenAI APIs in their product, they need to be able to have information about what the implications are of those API calls so they can make good choices in how they build their software.Tammy McClellan: So awareness is key, absolutely. So Jesse, what is the potential for Gen AI to support greater sustainability?Jesse McCrosky: Yeah, it's an exciting question, and I think there is some potential here. There's a case that ThoughtWorks took, it's a couple years back now, I think, in which we worked with a international manufacturing and services company. They were interested in finding solutions to meet their sustainability goals, and they just weren't sure which way to go.They weren't sure, "should we start sourcing our energy from a different place, or using different sorts of transportation, or using different industrial processes or offering different products?" And so what we did for them was built a mathematical model of their operations and their supply chains. once we had that mathematical model, we were able to build a sort of scenario modeling dashboard where we could show them like, "hey, if you switch to delivery trucks that are using electricity instead of gas, this is what happens to your emissions, this is what happens to your bottom line, this is what happens to your customers."And likewise, depending on / considering different product mixes, considering different sourcing, whatever else. So the mathematical model here was not rocket science, to be honest, it was fairly simple stuff. The hard part of this engagement was really understanding the business at the level that we needed to in order to build that model. There were many hours of interviews and poring over notes and internal documents and everything else, as well as actually some basic desk research to determine the necessary carbon emissions factors, that sort of thing. I'm excited at the potential of generative AI to make this sort of process more accessible and more scalable. And I think that we've seen evidence so far that these models do a very good job of looking at these sorts of documents, looking at recordings and interviews, and it may be possible that you could create this model semi automatically with far, far less of the kind of very heavyweight and expensive all sorts of interventions. As well, it was challenging to understand the exchangeability. And so, for example, if the company is buying cotton in one particular country, it might be obvious to us that they can instead buy the same cotton from some other country, and that's the only possible change that could be made. But it's not so simple for the model to figure that sort of thing out automatically.Whereas GenAI, I think when we connect to these sorts of emissions factors databases, has the potential to make this process much easier. Tammy McClellan: Yeah, awesome. Let's move a little bit and talk about risks. How do you think businesses can manage the risks of AI? Jesse McCrosky: Yeah, it's it's a big question. I think everybody's talking about this. And I think what I would say is it's critical to understand that risks must be mitigated, not removed. I think a lot of people are talking, for example, about bias and discrimination, and they say, okay, we're going to produce a model that's perfectly fair and perfectly unbiased, or we're going to eliminate this bias from our model or whatever else. And this is just not the way things work. We live in the real world, and these systems are based on data from the real world. And the real world is unjust, and so we need to be able to be ready to tackle that. So, one example that I like is OpenAI with their DALL-E interface generation system. For a while, maybe some months ago, I think, if you asked it for pictures of lawyers, it was going to give you eight pictures of white men, basically.And OpenAI recognized that there was a problem there, as did the community, of course. So eventually, OpenAI had a short blog post where they talked about how they were going to fix this. And it was apparently fixed, so when people tried to get pictures, they would see pictures of lawyers, and some of them would be women, and some of them would be of different ethnicities, and everything else. So People were curious how this had been fixed and it turned out that all that OpenAI was doing was just randomly appending words like women or black or Asian or whatever else to these prompts and people were not super impressed with this solution but I think it's an important illustrated example, because it's a mitigation, there was a problem with a model, there was a problem with the data, this is not a problem that can be solved fundamentally, it needed to be mitigated, and they found a way, they said, "here's the harm that's going to come from the system. It's going to not be producing an adequate representation, and we found a way that we can show more representation." So this is the sort of mitigation that companies need to take. So when there's issues, and this is where transparency comes in around the carbon impacts as well, so that they can be mitigated, so that if I'm an engineer sitting in front of my laptop writing some software, I need to have awareness that if I call this Gen AI call or whatever else, I have to understand this is going to spike the carbon emissions of my product, and I need to find another solution.Tammy McClellan: Gotcha. Yeah, that makes sense. Tell me. So are you optimistic or pessimistic about Gen AI at this point?Jesse McCrosky: I think I'm mixed. I think that ultimately solving the climate crisis means simultaneously solving a social crisis. And I think it's very hard to solve climate change without also solving issues of social justice globally. And I think that Gen AI is a tool that might enable some of these conversations to be tackled in a more interesting way.So I think as long as we're mindful and honest and clear eyed about how we apply this technology, there can be some optimism there. We need to ensure that we have adequate transparency so that people understand the carbon implications of the choices they're making when they're using these systems, but given that, there is potential to do better.Tammy McClellan: Gotcha. So I know when you and I chatted before, you said that you had a fun story of AI. Did you want to tell us what that is?Jesse McCrosky: Ah, so actually, I think there's a misunderstanding. The fun story was an expanded version of what I was talking about before, butTammy McClellan: Gotcha. Jesse McCrosky: if we have a moment, I think one thing I want to add when we come back to the idea of how, how transparency can help Gen AI be used more responsibly. So, a lot of people are familiar with the concepts of DevOps or MLOps or CD4ML, these sorts of processes. And I think this is a really critical place for transparency around carbon emissions to be integrated. I think the point I would make is that right now, a software developer that's working in kind of a modern setup has the ability, as they're writing code, to see immediately if the code that they're changing is causing some test to fail, or is causing some performance degradation, or is introducing some bug or whatever else. And I think we need to have the same process for carbon so that it if an engineer is making a choice and for any devs out there, maybe you have a case where you need to use a regular expression, but it seems like too much work to figure it out. "Hey, I can just call a Gen AI model and it'll do it for me as well."It'll work just fine. And you might make that choice because it saves you a couple minutes or whatever. But if you then see that all of a sudden your dashboard turns red and says, okay, your carbon has just increased like 100 percent or whatever, you're going to come back and you're going to revisit that decision. And also your team is going to see that, the trail of what's happening because of what you've done. And so it creates this sort of accountability in the development process.Tammy McClellan: All right. So I'm curious. What are the top three recommendations you would give to people who are interested in reducing carbon emissions of AI?Jesse McCrosky: Good questions. And yeah, I think that's something I didn't really touch on so far, but there are a lot of choices that can be made when applying AI. So we don't need to use the biggest general purpose models for everything. I think that there are cases where a general purpose model is really needed. But um, I think that in most cases, no. And so we can talk about using much simpler application-specific models. We can talk about using a smaller model and fine tuning it for the particular task. There's processes like quantization and distillation that can make models much more carbon efficient and nearly as effective. So investigating these options, and again, I think this kind of hinges on the MLOps setup where you need to be ready to evaluate performance. You need to be able to say "how small can I make this model and still actually meet the requirements in my product." Beyond that, I think it's a matter of providing transparency to the end user. So if you're producing something, if users understand the choices that they're making when they're using that product, there's a lot of different ways this can play out, and this can mean some Gen AI chatbot or something like that, but this also can be, maybe you have an e-commerce product. platform and you're using AI to make recommendations to your users and the recommendations that you make can influence their behavior and it can encourage them to buy more products that are disposable or made in very carbon-intensive ways, and so considering these sorts of externalities as well is really critical.Tammy McClellan: Gotcha. I'm curious, do we have any questions from the audience at this point?Sophie Trinder: Yes, we do. And thank you so much, Tammy and Jesse. It's been a really great session on AI here at Decarb, and it really shows the passion in the industry for these technologies, plus the responsibility that we all must take when it comes to AI. I know we'll be hearing a lot more in the coming months. But yes, we've got a few questions from the audience. I just want to shout out first, Jesse, thanks for the fun story on OpenAI, how they were mitigating the problem with data to show more representation through mitigation. It was a really interesting insight, thanks. So one question from the audience, how important is prompt engineering for improvement of AI efficiency?Jesse McCrosky: Great question, yes, and it's it's really extremely important, because the energy being consumed by the model is going to depend in some complex ways, depending on how many tokens are coming into it, and in quite a direct sense, how many tokens are coming out of it. So if we can reduce the number of tokens going through the system, we reduce the carbon emissions. And this again, I know I'm sounding like a stuck record, but it really depends on the MLOp setup, where we should be able to test and see how short can we make our prompts and still accomplish what we need to do. And this is both the length of the prompt itself and the length of the output. So for example, go back to that example I was talking about where maybe ChatGPT has a little indicator at the top telling you how much carbon has been emitted in your session so far. Maybe if you see that number growing as you're chatting with it, you're going to say, "hey, ChatGPT, please be a little bit more brief with your answers. I don't need the whole kind of colorful language and going on and on about everything." So yes, it's very important.Sophie Trinder: Super interesting. Thank you. We've got another one on training the AI ML model, which obviously takes a huge amount of data and processing, which in turn causes a lot of emissions. How do you think that we could best counterpart the same?Jesse McCrosky: Yeah, good question. And I think that I have an article out where I actually talk about how the comparisons are a little bit overwrought, talking about how training a model is equivalent to driving a car some distance or whatever. I think that, um, the comparison, at least so far, thankfully, is not quite accurate because we have many cars on the vehicle and a relatively small number of models being trained. I think the important thing is to keep it that way. I think the important thing is that we need to encourage use of open models and shared models rather than every single organization in the world trying to train their own LLM. And this is why I would be a strong supporter of open-source models. I think it's nice to see that movement.I think it's potential. It means that organizations, first of all, save their money, but also save their carbon when they want to be able to explore elements in their business. And there's always the potential for fine tuning, for whatever other tools need to be applied to open models to make them suit people's applications.Sophie Trinder: Amazing. Thank you. And jumping back to sort of problems on data and representation, we've got another question centered around that. So do you think we should promote digital humanism and ethical AI to raise awareness about the need for sustainable AI?Jesse McCrosky: Yeah, absolutely. I think we're existing at a moment where responsible AI and such is being discussed everywhere. There's very active regulatory work in many different regions of the world. There's many people in academia, in civil society, and in industry doing this sort of work. And I think that green AI should come along for the ride, so to speak, and it should be an important part of how we think about the risks and the potentials of these models.So, yes.Sophie Trinder: Amazing. Thanks very much.Chris Skipper: So that's all for this episode of Environment Variables. If you liked what you heard, you can actually check out the video version of this on our YouTube channel. Links to that as well as everything that we mentioned can be found in the show notes below. While you're down there, feel free to click follow so you don't miss out on the very latest in the world of sustainable software here on Environment Variables. Bye for now!Asim Hussain: Hey everyone, thanks for listening. Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts. And please, do leave a rating and review if you like what we're doing. It helps other people discover the show and of course, we want more listeners. To find out more about the Green Software Foundation, please visit greensoftware.foundation Thanks again and see you in the next episode.

Guests Sophie Trinder and Adam Jackson discuss the recent Decarbonize Software 2023 event and the unveiling of the GSF Impact Framework. Topics include driving climate change solutions with AI, high-quality energy data for emission optimizations, and engineering excellence with GSF principles. They also talk about the surge in interest in Green Software Practitioner courses, responsible AI and environmental sustainability, and the benefits of Carbonware SDK and carbon awareness for reducing emissions. They announce upcoming events, including a hackathon focused on the impact framework, and provide information on where to watch talks from Decarb 2023.

Ines Akrap, an experienced web designer specializing in sustainable and energy-efficient websites, joins Chris Adams to discuss the challenges of green coding in frontend development. They explore the nuances of designing energy-efficient websites, common mistakes in optimizing sites for carbon efficiency, and highlight exciting projects in the field of green software. The episode offers practical tips and explores new research horizons in the quest to decarbonize the digital world.

Asim Hussain, Speaker on the Green Software Foundation's newly introduced Impact Framework, discusses the capabilities and objectives of the framework. Project leads join to delve into its applications and potential. The Impact Framework aims to revolutionize the way we assess and mitigate the ecological footprint of software development and use.

This podcast explores the benefits and trade-offs of load shifting, modeling the European electricity grid, 24/7 carbon-free electricity matching, unbundling renewable energy generation, and optimizing energy usage through load shifting.

Anne Faubry and Alexander Dawson from the W3C Community Group discuss the Web Sustainability Guidelines, Content Accessibility Guidelines, and their roles in the group. They talk about the differences between standards and guidelines and what the Web Sustainability Guidelines aim to achieve.

TWiGS host Chris Adams is joined by special guest Tony van Swet from Electricity Maps, to talk about the mapping of the carbon intensity of electricity grid. Tony shares some of the work that Electricity Maps has been doing to make it easier to understand how clean or dirty electricity is around the world, as well as how they’re making this data more accessible and usable to consumers. Join in on this candid conversation discussing the uses of such data and how to access it, as well as Tony talking about carbon intensity, open data, and open source.Learn more about our people:Chris Adams: LinkedIn | GitHub | WebsiteTony van Swet: LinkedIn | WebsiteFind out more about the GSF:The Green Software Foundation Website Sign up to the Green Software Foundation NewsletterNews:How to trace back the origin of electricity (Smoothie Blog Post) | Electricity Maps [06:16]The value of space-time load-shifting flexibility for 24/7 carbon-free electricity procurement | Zenodo (TU Berlin’s Study with Google, using PYPSA) [12:11]Electricity Maps | Client Story: Monta (EV Smart Charging use case) [15:41]GitHub - electricitymaps/electricitymaps-contrib: A real-time visualisation of the CO2 emissions of electricity consumption [21:01]Electricity Maps | Reports - Hourly Residual Mix Methodology [27:13]Resources:Electricity Maps | Data Portal [18:29] Electricity Maps Methodology If you enjoyed this episode then please either:Follow, rate, and review on Apple PodcastsFollow and rate on SpotifyWatch our videos on The Green Software Foundation YouTube Channel!Connect with us on Twitter, Github and LinkedIn!TRANSCRIPT BELOW:Tony van Swet: Looking at Google's use case at their data centers, they have the huge potential to shift their computation based on time or location, so this enables them to manipulate their energy consumption through using our API to increase their consumption when the sun shines and the wind blows. Chris Adams: Hello, and welcome to Environment Variables, brought to you by the Green Software Foundation. On our show, you can expect candid conversations with top experts in their field who have a passion for how to reduce the greenhouse gas emissions of software. I'm your host, Chris Adams. Hello, and welcome to another episode of This Week in Green Software, where we bring you the latest news and updates from the world of sustainable software development. I'm your host, Chris Adams. When we talk about green software, it's often common to talk about energy efficiency, and one of the reasons we care about it at all, is that right now we burn a lot of fossil fuels to generate electricity used in data centers, networks, and end-user devices. But how much of that comes from fossil fuels? And is that changing? This data exists all around the world, and sometimes the data is open, but it's often very messy. In 2017, the Electricity Map project was launched to make it easier to understand how clean or dirty electricity was all around the world. And as the name suggests, it took the form of a map showing the carbon intensity of electricity in as many places around the world as possible. Over the subsequent years, an open source project has grown with hundreds of developers around the world, contributing open web scrapers for data in their parts of the world to make the data more accessible. And earlier this year, the company behind the project released a new open data portal for historical data about how clean electricity was for anyone to use how they wish. So, what does this have to do with green software? Having access to this kind of data makes it much easier to understand the carbon footprint of your software. And this week, we're joined by Tony van Swet from Electricity Maps to talk about carbon intensity, open data, and open source. Hey there, Tony.Tony van Swet: Hi, great to be here.Chris Adams: Okay, Tony, before I get ahead of myself, I think we should give you a bit of space to introduce yourself properly. So can you tell us a little bit about what you do at Electricity Maps? And for folks new to the field, what Electricity Maps does these days, please?Tony van Swet: Yeah, of course. I'm a senior software engineer in the advocacy team at Electricity Maps, and I'll give you a bit of background on what we do at Electricity Maps. So our mission is to organize the world's electricity data to drive the transition to a truly decarbonized electricity system. And as part of the advocacy team, my focus is enabling climate action with transparent insights.We do this with the help of the open source community, building products such as our map visualization and the data portal that we're here to talk about today.Chris Adams: Cool. Thanks for that, Tony. Okay. So if you're new to this podcast, um, my name is Chris Adams, as I mentioned before. Um, I work as the executive director at the Green Web Foundation, a Dutch nonprofit focused on an entirely fossil-free internet. And I also work as the chair of the policy working group inside the Green Software Foundation. And before we dive in, here's just a quick reminder, everything we talk about, we'll link to in the show notes below. So if there's a paper that caught your interest, or there's a story you've heard about, we'll do everything we can to make sure there's a helpful set of links that you can follow up for your own research a little bit later. But back to Tony. Tony, I've got to have to ask you, I know you're working in Denmark, but... I suspect you might not be coming from Denmark in the first place. What does a Kiwi end up doing on the opposite side of the world in Denmark, working for a company like Electricity Maps? I'm sure there's a story behind that.Tony van Swet: Yeah, absolutely. It's definitely a bit of a career shift for me. So I started out about 10 years ago as a truck driver in New Zealand. I was full of self doubt, a bit depressed, struggling to find my place in the world. And to lift myself up out of this, I made it my mission to create technology to combat climate change, and I identified that software was the most powerful way to effect change at scale.And this led me to enroll in a computer science degree. From there, I worked at a few cool startups in New Zealand, eventually looking to integrate electricity maps data when I saw their job postings and applied, and within a few months, I had the job and was waving goodbye to my friends and family to fly across the world to Denmark.It's definitely been full of challenges, but it's been amazing to find a company that really shares my values and aligns so perfectly with my mission.Chris Adams: Wow. So you, when you say you're a truck driver, you're talking about the massive, like 18 wheelers crossing from city to city, right? Something like that.Tony van Swet: Yeah, I actually worked with the HIAB trucks, which have a crane on the back. So I was delivering building supplies around Auckland. It definitely gave me a lot of time to think about the world and take in the kind of sights and sounds of the city.Chris Adams: Wow. Okay. So I think you may be the first former truck driver we've ever had onto this podcast. So yeah. Wow. Thank you for, thank you for coming along. That's also a fun story. I, it's, it's quite nice to hear something like that because, uh, I myself, there's a lot of us who are self taught technologists and to hear a nice story about switching careers you're going, "that's cool, actually." All right, before we digress, let's go back to what we were supposed to be here talking about, which is open data and carbon Intensity. So one thing you mentioned is that we're here to talk about open data and there's some recent work at your end that's made that visible. But before we do that, could we briefly just cover what carbon intensity means at your end, because this is something that isn't obvious to most people.And I remember there being a kind of nice introduction on your website using metaphors like blenders and so on to explain that there's more to electricity to it being just gray versus green, for example. So maybe you could just. provide a bit of a background or how you explain this to people, then we can dive into some of the details about open data.Tony van Swet: Yeah, the blender analogy is really great. We even did a smoothie maps version of our app for April fools, renaming all of the power sources to different fruits and vegetables to illustrate that. So yeah, carbon intensity to us seems like it's relatively straightforward, but if you're not familiar with this idea, it's quite hard to understand.And in this case, we refer to carbon intensity as the CO2 equivalent for a given zone where energy is being consumed. We calculate this by determining the carbon intensity for each generation type and then weigh it according to its proportion of the grid mix. We also then calculate the neighboring zones and account for all the imports and exports of the connected zones to figure out a final number for the carbon intensity where you plug into the wall and consume it.Chris Adams: So basically, if I understand that correctly, you're, what you're saying is you look at all the various parts of the world, and when you say zone, you're referring to maybe a country or a part of a country, depending on how a grid is designed. And then when you're talking about the kinds of generation, you're talking about, say a coal fired power plant or a gas fired power plant or a solar farm or something like this. So these have different levels of CO2 that get emitted for each unit of electricity and you're mixing those together, something like that. Is that correct?Tony van Swet: Yeah, definitely. When we take a look at a coal plant, it's going to emit a lot more carbon than the equivalent solar or wind farm.Chris Adams: Okay, cool. So that talks about the consumption, the how, where the electricity comes from. So maybe we can talk a little bit about, okay, how we experienced that and how, like, when I plug something into the wall, for example, what happens next?Tony van Swet: Yeah, so when we, um, plug into the wall, the energy we consume is, um, considered a mix of all the generation types of the grid you're connected to, um, and it's almost impossible to determine whether an electron comes from a wind farm or a coal plant, even though this will have a significant change in the carbon intensity of the energy you consume.So this is where it's really useful to consider the grid as a giant blender, mixing together all those generation types. And then we can evaluate the true carbon intensity of the energy that you consume.Chris Adams: Okay. If we're going to continue this blender analogy, if you put lots and lots of, say, strawberries in a blender, it's going to look one color. And if you had lots of Kiwi fruit in a blender, it's going to look another color. So that's a little bit like what you expose to people and how that might change over theday.Right. Okay, cool. I believe what we'll do is we'll share a link to the blog post, becauseI found it one of the clearest ways to actually help people get their head around this kind of concept, because it is a bit of a leap when you're first starting to get into this field. So with that, we've got a kind of grounding there. Maybe it's worth talking about this from the point of view of a software engineer. So. Let's say you do know this and you have access to this information. Why is this helpful if you're a software engineer? Like where does this fit into what you might do, for example, or affect your job?Tony van Swet: I think it's super useful as a software engineer to, to have this information and I see a few main categories where you can apply this data, particularly around raising awareness of when to consume energy. We want people to use power when the sun shines and the wind blows. So I think that there are ways to present this information so people can make decisions in their everyday lives.But particularly for me, I find it interesting of automating solutions where we can get carbon-aware products that will shift their consumption or the load of the power consumed based on how sustainable the power is available to them.Chris Adams: Okay. So in this case, this scenario here, you're basically saying, if you have an abundance of power, which is very green, you might kind of tune or change your usage to use more of that, and when the power is particularly dirty, for example, you would try to use less of it so that you're shifting your power through time or possibly through space so that the average carbon intensity might be lower than it otherwise would be.That's what I think you're saying, right?Tony van Swet: Yeah, exactly. So the two main ways to optimize your consumption here is over time or via location. Um, so we know that different grids are much cleaner and, um, some people have the luxury to be able to shift their consumption via location as well.Chris Adams: Okay, cool. So. We've got the kind of general concept for this. Are there any kind of favorite examples that you might point people to of people using this to actually demonstrate their behavior, either at a personal level or an organizational level? Because yeah, having a concrete example would be really helpful for people who are listening to this for the first time.Tony van Swet: Yeah, I think, um, my favorite example is, um, looking at Google's use case at their data centers. They have the huge potential to shift their computation based on time or location. So this enables them to manipulate their energy consumption through using our API to increase their consumption when the sun shines and the wind blows.Chris Adams: Okay, so if I understand it correctly, they're like a client of yours or a customer of yours, they pay for this, and then they use it then to essentially either scale things up or down, depending on the amount of power they might be using, depending on where the data centers are. That's, that's what it sounds like, what you're suggesting there, correct?Tony van Swet: Yeah, definitely. So there is the location aspect and we see a huge variation of the carbon intensity throughout the day. So they also do time-based or scheduled computation based on the carbon intensity available to them.Chris Adams: Cool. Okay. I'm glad you mentioned this because this is something we've had people come on the show before to talk about some of this, but since we have spoken about this, there's actually, uh, some interesting data. Uh, there was a study published with TU Berlin where we're, I'm based in Berlin so we've, I found out about this study and, uh, there's. I found this actually quite a nice example of this to talk about, because a lot of the time, when you see companies talking about this, it's quite hard to actually find meaningful numbers to say, does this actually translate to a saving in carbon? Or does it translate to a saving in even money, for example? And this is the first time I've seen with really detailed information, which has been modeled through this. Um, we'll share a link to this paper, but there's a few kind of headlines that I saw from this. And as I understand it, one thing that Google is doing, for example, they've basically set a commitment to say, "we want to have the average carbon intensity of our power to be this much." So we want to have a certain percentage coming from what they call is like carbon-free or fossil-free sources of generation. And, uh, the study that I saw basically showed that by moving the load around, it reduces the amount of renewable energy, renewable kind of generation that needs to be deployed in the first place for this.So there's an embodied carbon saving in the, in not needing to have a bunch of wind turbines or solar all around the globe. And this study that I see, it was modeling five data centers. So five out of say 14 data centers that are around there. And there were. The savings are pretty good, or actually like measurable.I think with the combination of moving things through time and moving things through space, so moving a compute load to where it was going to be greener, the figures that I saw, some of the headlines were that they're able to reduce the cost of doing this by something in the region of a third of the amount of investment that would need to be possible. And, uh, they also, this is one of the first examples I've seen, which even explains like what the costs on a yearly basis might be for this. And, uh, I think the. There was a couple of scenarios inside this. So there's maybe with zero load shifting or moving, say, about 40 percent of the compute loads that to to different parts of the data centers, where maybe one part of the world might be particularly windy or sunny. When I look at the figures here, I see something in the region of, if you, the savings that are here and we need to, and I will share a link to this, to the actual study for this, so that people can look into this a bit more detail, but with the five data centers modeled in, I think, Germany, in Denmark, in Portugal, in Ireland, and in Finland they were basically able to model savings of around at least 200 million US dollars each year by, in terms of the amount of power that you would need to be, the amount of like generation you would need to match this, to actually hit those targets. Now this is, I think this is actually useful to understand because this actually speaks to the fact that there's economic drivers as well as actually just environmental drivers for this. And this kind of speaks to the wider kind of trend, but. I think it's useful to, for this to be, people to be aware that there's actually something in the public domain to interrogate and look at some of these numbers and see how some of these are modeled and what some of the assumptions are. So we spoke about that. Are there any other use cases that you might point to that may be a little bit more closer to home, for example, or something that you might, that people might experience on a more kind of daily basis or close to themselves, for example?Tony van Swet: Yeah, absolutely. Yeah. We have a few customers in the EV smart charging space, and we have also done some research with the Frederiksburg commune here in Denmark about the benefits of smart charging. And we... We were quite impressed to see a 10 to 15 percent reduction in carbon emissions if we have grid-aware smart charging products.So this is plugging your car in the evening and letting it decide when the best time is to charge the car overnight. And even with a small shift in that load, we see a significant reduction in the carbon emissions of the energy consumed. So we were really positive with the results of that. And particularly find it a very nice use case that you put the decision-making power in the hands of the consumers here.So people can choose whether they want to use these products or not.Chris Adams: Okay, cool. All right. If you're in the UK, I believe there's a number of companies that do things like this. Octopus is one of the better known examples of this. And I think under some of the tariffs, there are scenarios where you can actually be paid to charge up a car rather than pay to charge a car or to use a car.So the cost can go negative. Because there's maybe an abundance of power in the grid or like we have here. So that's actually, okay. That's quite useful. So we've covered a couple of use cases now. Maybe it's worth talking a little bit about, little bit about what kind of software supports the use of this data. So I know that at the Green Software Foundation, there's a carbon aware SDK, which is designed to allow people to embed this in some of their software. And where I work at my nonprofit, the Green Web Foundation, we have a library, a Golang library, which is used in a project called Carmado, which is a kind of federated Kubernetes operator. Could you talk a little bit about some of your experiences of what you've seen people use for some of this stuff? For example, maybe you could talk a little bit about some of the pieces of software that you've seen in the wild using some of these tools or using some of this data, for example.Tony van Swet: Yeah, definitely. Firstly, yeah, we're hugely appreciative of the Green Software Foundation and their work to make it easier for developers to use data like this. We do our best to enable developers and hobbyists with our free data through our API. Previously, it was known as CO2 Signal and we've now incorporated that into the Electricity Maps API.And we see lots of amazing tools being built. We see people building dashboards so they can make decisions around which data centers they use. And we do see a big community from Home Assistant also integrating our data. So people can connect their smart homes to become carbon aware and give information on the carbon intensity of their homes.Chris Adams: All right. So we've got some, some stuff like that. And I think we've done a decent job of now establishing what carbon intensity is and how some people might be using it so far. And, uh, we spoke about this idea. There's a, like a free tier, which basically implies that people pay for a data service. But one of the things that we're here to talk about today is open data and this open data portal.And as I understand it, this is your baby, so to speak, right? So maybe you could talk a little bit about, okay. What is this that we, that that's actually gone live because I've got a history with open data, but I suspect it'd be useful for people who are coming to this to understand what this data portal is and why it's useful and what it lets people do, for example.Tony van Swet: Yeah, I was super excited to take the lead on the Data Portal project and really happy to come on the show today to talk about it. Providing free and open data really motivates me. And the Data Portal is a product on our website where anyone can download free carbon intensity data for over 50 countries in hourly, daily, monthly, and yearly for both 2021 and 2022.Chris Adams: Okay. So let me just check if I understand that. So, uh, if people want to start using or experimenting with this data, there's a free tier which you, which folks like yourselves provide. Uh, there's another provider called Watttime that does a, of a free, a free tier. And there's commercial kind of real time feeds from both yourself.And, uh, this part here is this high resolution historical data that has typically been quite hard for people to give access to. And this is openly licensed in the sense that people are free to use this how, however they wish, is that the case or is there any, or maybe we could talk a little bit about the licensing part so people understand how they could use some of this.Tony van Swet: Yes, so we have provided the data free for anyone to use. We particularly look at Carbon Accountants and researchers to use the data. People are welcome to use it under our license, as long as they, if they're building a new product with our data, then they'll be required to open source that new product, but if you're using this data for Carbon Accountant, then you're fine to use it and charge for that accordingly.Chris Adams: Okay, cool. All right. Uh, what we'll do is we'll share a link to the message, to, to the licensing. So people have an understanding for this. So I think when I looked at it was the open database license. So you're able to use it for free in any, in any form, as long as, uh, you're prepared to share under similar terms yourself.That's basically the kind of general approach that I understand for that. And you, you spoke a little bit about there's an intended audience of people who might be carbon accountants or researchers or energy geeks. Can you talk a little bit about how this data gets published in the first place, where it comes from? Because as I understand it, the data can be quite messy to actually put into a kind of API for someone to consume.Tony van Swet: Yeah, yeah. It's, it's a huge challenge to collect all the data. So we have an open source repository full of parsers that collect this data from TSOs and data providers around the world. We have an incredible open source community that helps us to maintain those parsers. We then process this raw data with the kind of smoothie idea that we talked about earlier, run data quality checks on top of the data, and then present it in a way that's easy to navigate and consume.Chris Adams: Okay. So you've used a bit of jargon that I'll need to unpack on there. So you said that you're getting data from a few places and you mentioned a TSO. I'm assuming a TSO is a transmission service operator, like someone who operates part of the grid and they publish information. So that's where some of the data might be coming from.Is that correct?Tony van Swet: Yeah. Yeah. Spot on.Chris Adams: Okay. And one of the challenges is that not every, so maybe I, as I understand it, when I've looked at this data, the data comes out in like grams per kilowatt-hour, what I would typically be paying for, but different places might have different ways of reporting it or different units. Is that the kind of stuff that you, that ends up having to be munged so that there's a kind of clean interface for people to consume?Tony van Swet: Yeah. So the data providers, the TSOs tend to give the data in the format of a energy breakdown. So the various production types, whether it's wind, solar, coal, gas, and we then process this data and apply emission factors. So we add a direct and life cycle emission factors to each of the generation types, and then compute that to give a final carbon intensity number for each zone.Chris Adams: Okay. All right. So if I understand that correctly, you're basically saying we know what this kind of coal power station is likely to be doing for each unit of coal. And because we might have some information about it being an old machine, old one or a younger power station. So you'll have some figures like that, and you essentially run through every single form of generation so that you've got a kind of up-to-date, accurate number for that based on what, what people are doing rather than have to look that up because yeah, it's quite hard to find.So. You've, you've created this data portal. People are able to download it for a set of countries or different parts of the world, and you said that there's data for 2021 and 2022, and this kind of begs the question, what happens next? Is this, is the idea, is the intention to keep having this available on an, on a, on a annual basis so that next year there'll be data for 2023, for example?Tony van Swet: Yeah, absolutely. I listened to your podcast a few weeks ago and I heard you mention that we were looking to raise the bar of energy data available out there. And I really like that term. It's exactly what we want to do. We plan to release new data early 2023. We want to enable carbon accountants to do granular carbon accounting based on our data.And we really hope that providing this data for free gives the industry a push to be more open and transparent around what energy data is available.Chris Adams: Okay, cool. All right. So for the energy nerds here, I, it might be worth just briefly talking about the fact that this currently provides average carbon intensity data. Is that correct? So that's basically the kind of location-based figure. So there, this isn't trying to take into account water or anything to do with market-based figures at present.That's something that might be on the horizon in future. Could you maybe talk a little bit about what things are on the wishlist or what people are asking about What would they like to use in future from here? Because you alluded to some things about, uh, the life cycle intensity of, of, of energy, for example, and there's a whole other set of footprint impacts that people often ask about when they talk about carbon intensity, or even just the environmental impact of the use of electricity in any kind of service.Tony van Swet: Yeah, absolutely. So carbon accountants are most interested in the direct emissions that we provide in this data because they're doing their accounting based on the Scope 2 emissions of a company. Um, we do also provide the life cycle analysis emissions for each zone as well. And this is taking a cradle to grave approach of the emissions.We use the numbers from the IPCC and the,Chris Adams: So IPCC in this case is the Intergovernmental Panel on Climate Change.So that's one thing. And then the UNEC, so I'm guessing it's United Nations.Tony van Swet: United Nations Economic Commission for Europe. Chris Adams: Okay, great. Okay. So, so that's basically the kind of bona fide place where you're taking some of these numbers from. And when you talk about the life cycle emissions there, that means that let's say you're talking about solar or wind, for example. That includes the fact that someone has to make the panels in the first place, and there's going to be some pollution that may be caused there, carbon pollution from making the kind of silicon panels or the turbines.Is that correct? And then the dispose disposal.Tony van Swet: Yeah, exactly. Yeah. And even in the case of nuclear, the lifecycle analysis takes into account the storage and disposal of nuclear waste over hundreds of years and applies the costs of that to a carbon equivalent.Chris Adams: Okay, cool. All right. So we've spoken about carbon and we will talk about carbon a bit more, but. It's very, one thing that has come up when people talk about the environmental impact of digital services, there's this term called carbon tunnel vision, where people only look at the one figure, or the one kind of dimension. Is this actually something that, is this on your wishlist, for example, because we know there's a, say, there's a water impact. People talk a lot about machine learning and AI and tools like that, having a water impact, and there's also an impact from the actual generation, for example. Could you maybe talk about a little bit like that?Is that something that you'd like to be heading towards, or is that on the roadmap, for example, in the, in the long run?Tony van Swet: I think we'd love to take a step back and, and have a broader look at the impacts. We're relatively limited with our capacity, so, so we do focus on what we know and what we're experts in. But I would love to see us work with partners to be able to provide our data alongside other sources to take a bigger picture approach to this.Chris Adams: Okay, cool, Tony. So back to carbon then. You spoke a little bit about working with other providers and I realized just as I was doing some research for this recording, this podcast, there was a new paper that came out from Electricity Maps specifically about, this is a, this is a really nerdy, I'm afraid, residual carbon emissions when you look at the environmental impact of electricity and If I understand it, I'm just going to try and run my understanding by you if I can, and then if you can give me an idea about if it's in the right direction, that'd be really helpful.So, as it stands, electricity maps gives you figures for location-based data. So you look at the carbon intensity of the generation all around the world through, and like dams or wind or solar, uh, you'll look at that part, green energy, they often talk about, say, using green energy in some parts of the world where they've purchased essentially certificates to count electricity as green.And this is a kind of like a market-based approach that people use. And this is the basis that various companies use to say, "we're using a hundred percent green energy," for example. Now, if I understand it, this paper that goes into this and basically says, if you're going to look at the carbon intensity of electricity, you need to account where these certificates that people use, where they're actually being used in various parts, because that's going to have an impact if, because if someone is claiming green energy in Ireland, for example, and they're claiming that on the basis of certificates that were traded from Norway, that's going to have an impact on how green the power might look in Norway compared to Ireland, for example. This is what I think some of the research is that was in this paper. Is that directionally correct? Is that moving in the general direction of correctness for this stuff?Tony van Swet: Yeah, absolutely. Yes. I think a lot of companies are buying renewable energy certificates and it has to be a zero-sum game. So the residual mixed paper that our policy team has just released goes into a huge amount of detail into how you calculate the carbon intensity after you have sold those renewable energy certificates for each zone.Chris Adams: And as I understand it, this is something that's on the roadmap that will be looked at is A, a thing that is unsolved right now, but people are looking to figure out how to incorporate into how they work. I know that in the Green Software Foundation, there's a group called Realtime Cloud, who are working to come up with hourly figures to make it possible to provide this kind of reporting. This seems to be one thing that comes up because when I was looking through this paper just last night, actually, there was a few things which are really eye opening for me. So Ireland and Germany are two large markets in Europe, for example. And as I understand it, something like eight times the certificates were consumed as were issued in Ireland, for example.So this basically means as I understand it, that eight times as much green energy is being claimed as is generated in Ireland. So therefore you've got a bunch of generation in somewhere else in the world that needs to be accounted for when you look at the carbon intensity of say, a place like Iceland or Norway, for example, but the same things seem to be in Germany as well. Germany has something like seven times the certificates consumed as were issued in Germany. So that suggests to me that seven times as much green energy has been claimed as is being generated. So if Germany had to have an entirely green grid, you would need something like a sevenfold increase in order for them to be saying, "yes, we're running entirely on green energy." That seems, this is pretty eyeopening. I'm really glad this is actually out there because I haven't seen this data provided in this resolution, particularly in hourly level before.Tony van Swet: Yeah, I think it's really fascinating and definitely highlights why we need the transparency around this market based approach. And it's very early days, so we are hoping to inform the methodology of how we approach this in the future.Chris Adams: Great. Okay. So what we'll do, we'll share a link to that. The things I've just shared are in the first 10 pages of this paper. It's about 80 to 90 pages long, and it's a really impressive tour de force. So Cyril, I'm really impressed with this work. Really mad props for you to actually get this together. Cyril is the policy lead, Electricity Maps, and he's also on some of these working groups, which is why it really caught my eye. So Tony, we've just spoken a little bit about Open data, different ways of measuring the carbon intensity of electricity here for informing your decisions as a software developer. Is there anything that you would like to draw people's attention to? Any projects or things that you are particularly interested or that you're excited about right now?Tony van Swet: Yeah, absolutely. Yeah. First off, I'd welcome people to jump on and take a look at the data portal and I would appreciate any feedback around that. And. If anyone would like to contribute to our open-source work, we're also always looking for contributors there. To find out more, jump on our website at electricitymaps.com.Chris Adams: And if I understand it correctly, you folks are still, it's still mostly Python scrapers and a kind of React app that you had before. Is that still the case for people?Tony van Swet: Yeah, definitely. Yeah. Python and JavaScript.Chris Adams: Okay. So common languages that people know their way around. Okay. Brilliant. I think that's pretty much it. I've, I've really enjoyed this, actually. Thank you so much for giving us your time and diving into some of the finer points of carbon intensity of electricity and, uh, some of the nerdery there. And, uh, Tony, thank you so much.I've really, I've really enjoyed this. Cheers, mate.Tony van Swet: Yeah. Thank you, Chris. It was really great to be here. I also wanted to say I went digging through our open source repo and found your name on there. So I want to give you a personal thank you for contributing in the past.Chris Adams: Thank you very much. Um, there, I think there'll be more PRs coming in future when I find the time. Okay. Cheers, Tony.Tony van Swet: Amazing. Thank you.Chris Adams: Hey everyone, thanks for listening. Just a reminder to follow Environment Variables on Apple Podcasts, Spotify, Google Podcasts, or wherever you get your podcasts.And please, do leave a rating and review if you like what we're doing, it helps other people discover the show, and of course, we'd love to have more listeners. To find out more about the Green Software Foundation, please visit greensoftware.foundation. That's greensoftware.foundation in any browser.Thanks again, and see you in the next episode! 

Dr. Daniel Schien from the University of Bristol, UK, joins host Chris Adams to discuss digital sustainability. They cover topics such as streaming's environmental impact, the carbon footprint of digital services, and the importance of reducing carbon emissions in ICT. The conversation explores different approaches to measuring carbon intensity and emphasizes the need for long-term decision-making in green software.

Join host Chris Adams and Tereze Gaile, global Sustainability SME at MuleSoft, as they discuss sustainability tools, resources, and bringing sustainability into organizations. Topics include the Green Code initiative, Developer Carbon Dashboard, generating customer demand for sustainability, change models, measuring organizational emissions, and self-care in the sustainability space.