Thomas Kiessling: 0:03

If 40 percent of total human CO2 emissions are buildings, and half of that, so 20 percent of all human emissions, is the operations of buildings around the world, and I reduce that 20 percent to just a few percent, down from 20 to just a few percent, that's massive. That is real impact for all of us, for humanity

Tom Raftery: 0:28

Good morning, good afternoon, or good evening, wherever you are in the world. This is the Climate Confident podcast, the number one podcast showcasing best practices in climate emission reductions and removals. And I'm your host, Tom Raftery. Don't forget to click follow on this podcast in your podcast app of choice to be sure you don't miss any episodes. Hi everybody. Welcome to the Climate Confident Podcast. My name is Tom Raftery and with me on this special edition of the Climate Confident Podcast today is Thomas. Thomas is from Siemens. Siemens are sponsoring this episode. Thomas, would you like to introduce yourself?

Thomas Kiessling: 1:07

Hi, Tom. Great to be on this podcast. My name is Thomas Kiessling CTO of the Smart Infrastructure Division, which is the sustainability decarbonization division of Siemens, I would say. My background is software, IOT systems. I live in California. German national originally. So I spent most of my life in the U. S. and Europe and in multiple countries. I'm a, I'm a serial entrepreneur Siemens invested in my last startup. Siemens has an, has an amazing vision to become a sustainability focused technology company. And that attracted me. To now having spent the last three years helping the leadership team to achieve that vision and to help our customers to decarbonize, to become more sustainable and to accelerate the energy transition. So, that's pretty much my background. PhD in operations research long time ago. And I love building companies and, and help our customers achieve their, their company goals, you know, their sustainability goals, their decarbonization goals.

Tom Raftery: 2:14

Okay. And Thomas, just for people who might be unaware, when you say infrastructure and Siemens, what aspects of infrastructure do Siemens take care of, because infrastructure can be anything from building bridges to railroads to et cetera, et cetera, et cetera, where does Siemens infrastructure slot in there?

Thomas Kiessling: 2:34

Right, right. Thank you for the question. We call it Smart Infrastructure, which is even more nebulous, you know, what, what is this? You know, so good question. When we say infrastructure, it is mostly commercial and industrial infrastructure to provide the power, the energy we're all consuming to operate the buildings, mostly commercial buildings we're not so much in residential the commercial and industrial buildings and factories that we're all using to build our products we all use. We're also active in public infrastructure in the sense of, you know, big renewable plans or, you know, streets and the like, and we provide the tools, the technology to operate those mostly and to make them more sustainability and decarbonize sustainable and decarbonize them.

Tom Raftery: 3:27

Ok, fantastic. And obviously Siemens, large company is going to have a significant footprint of its own in terms of emissions, for example. How do you, or do you help Siemens with their own decarbonization mission?

Thomas Kiessling: 3:46

Yeah, so as you would expect, we have a pretty ambitious ambition sort of targets for the next 5 to 10 to 15 years. And we consider ourselves a leader in setting these targets. So just to give you a few data points here for the discussion. We already halved our co2 footprint by 2020 in a few years. That all started about 5 to 10 years ago, right? But there was a massive program that just cut down the obvious sort of, carbon based emissions. But by 2030, we are on track to become net zero, and that's much more difficult. I'll give you a few examples now in this podcast. But, but that is, that's a mouthful. That's very ambitious. And that includes our factories. It includes our fleets of vehicles we're using to provide service to our customers. And we will achieve that by, by 2030, which, which I think is, you know, sets a signal and it's, it's it's, it's quite ambitious.

Tom Raftery: 4:46

And how are you going to achieve it? Is it, you know, I mean, will you be buying massive amounts of offsets? Will you be switching to renewables? What, what are the plans and the strategies for getting there?

Thomas Kiessling: 5:00

Yeah, yeah, no, so Siemens is a big industrial conglomerate. We have many different domains, and decarbonisation really goes domain by domain. You know, and then you add it all up, right? Then you, you become, you know, net zero. So I just want to give you a few examples. So let's, let's talk about products. We create electrical products. So, anything from fuses to switches to actuators and the like, core electrical products. Now, obviously, the footprint here, the eco footprint is the ingredients, the materials you, you you use to create that switch, for example. So, so we have committed on a rope as what we call robust eco design, which is looking at all the products we use to create that end product we sell to a, to a commercial building operator, for example, when it comes to the actuators, sensors and the like. And so that end to end footprint, everything from the raw materials all the way to recycling a switch, for example, that constitutes the full carbon footprint. That's the way how we should calculate it. Okay. So, so we commit on, you know, we, we now we're now at a rate of something like a quarter. So it's 26 percent of our products are already following the robust eco-design, and thus are decarbonized, but we will achieve a hundred percent of that eco design standards for all the relevant Siemens product families by 2030. Again, pretty ambitious target. So that's just one example. That's one domain. A very different domain now is factories. Our own factories and their carbon footprint. And just to give you a few examples We have several factories that are lighthouse, sustainability lighthouses as per the World Economic Forum, and we're very proud to have achieved that. So we have that designation. For example one of our factories, Siemens Electronics factory in Chengdu in China, you know, one of our lighthouse factories, I would say. We did cut total greenhouse gases there by 93 percent in absolute terms since 2019 which, which is a lot and at the same time we increased the output by 90 percent or whatever the number is. So, you know, if you look at this, if you look at the factory, you know, in a holistic way, end to end, you're able to get the net zero in the kind of factories we're running. It's a little harder if you're in the chemical process industry and you need, you know, a heat intensive processes for to create chemical products, for example. That's a little harder, right? The kind of factories that Siemens is running. Well, we're creating products, electrical products, charging stations, right? Switch gear and the like. And so, you know, if you apply a holistic approach to get to a max percentage of renewable input and production of the energy you're using if you follow very stringent eco design standards without, you know, the example I just gave, right? You know, the products that are actually coming out of the factory, right? And if you use electric vehicles you know, both on the truck and on the service vehicle side to for everything that goes out and goes into the, that factory. You know, if you do all that in a very systematic way, if you then reduce the energy consumption of this factory by 30 to 40%, which is totally doable in the, in the, in the typical settings, we're in, you put this all together and you can actually achieve net zero. So that's another example, right? And there is, you know, I can give you more examples of you know, all the different areas of what Siemens does, but you put this all together and, you know, we were able to, we will be able to achieve, you know, net zero by 2030.

Tom Raftery: 8:48

Okay. And when you talk about the eco design principles for your products, that's not just, I'm guessing correct me if I'm wrong, that's not just for the manufacture of the devices, but I'm assuming that also applies to their utilization by your end customers.

Thomas Kiessling: 9:07

That's, that's correct. And that's the famous scope three you know, carbon emissions which is just to remind everybody on this call, right? Because scope one is what you actually emit While you're producing something or while you're operating a building, right? So that's the sort of the carbon that actually is emitted from the building during operations. Scope two is, you know, take all the ingredients to produce it. So, for example, the energy you use in the building, does it come from renewables? And then scope three is all the downstream. You know, what is the knock on effects of your product that, that are, that are, you know, doing carbon emissions? So it's, it's hard to put all three together, right? You know, that's what we're all working on. You know, that's, you know, the kind of metrics and measurement systems we're doing, That's very important.

Tom Raftery: 9:49

Ok, and speaking of your customers are you working with your customers to help them reduce their emissions?

Thomas Kiessling: 9:59

Yeah, I mean, that's, that's obviously the core value of what, what Siemens provides and, and there I'd like to mention a, a report we're doing every year, which I, you know, invite everybody to take a look at, we call this the Infrastructure Transition Monitor. And so, the, the, the last version that we published there suggests that progress is basically too slow. We would be able to accelerate all of us the path to climate reverse to climate change, reversal and decarbonization because the technology, by and large. I know it's a general statement, but by and large, the technology is there to do it. We just need to apply it, invest, and then, you know, deploy, execute these technologies. So, the last version of our Infrastructure Monitor stated that only 44 percent of organizations expect to meet decarbonization targets by 2030. That's what the organization, our customers, say. Right. And then only 47 percent believe that their country has an effective decarbonization strategy. So, well, decarbonization strategy means regulatory environment, investment environment and the like. It doesn't mean the technology is lacking, you know, it's got, you know, you got to apply that technology. So, so that's, you know, I think just one data point that I'd like to, you know, sort of state here. Now just to give you a few customer examples, which I personally find really exciting, you know, when it comes to, you know, how we help our customers decarbonize. Buildings you know, represent about 40%, a little less, but about 40 percent of total human carbon emissions around the world. It's the largest, you know, the other four are industry, transport, agriculture, the energy system. Right. So that's like these five, the fifth one, the, you know, it's buildings and buildings is the biggest one, right? So building decarbonization has two aspects. There is embedded carbon. So all the materials you use to construct the building and then you run that building during 30 years or whatever the lifetime is. And so, Okay. Both is like both constitute 50 percent you know, the embedded carbon roughly a little less than 50 percent but roughly 50 percent. And then the operations of the building another 50 percent of the total lifetime output. That operational 50 percent of the carbon emissions of buildings. That's what Siemens mostly focuses on helping our customers. So building owners, operators, tenants to number one. Achieve energy efficiency savings up to 50%. So the average is somewhere between 20 and 30%. But as soon as you put in low cost digital IOT based systems to run your cooling and heating systems just a little bit more intelligent than most, you know, most of the systems are on today. You are saving an average of 20 to 30 percent and sometimes going up to 50 percent and even higher. And we provide the technology. The, the industrial IOT systems, the digitalization but also the retrofits to go to a much more modern heat pump system to do LED retrofits, better access control systems, solar on the roof, storage systems, whatever is necessary to achieve these energy efficiency savings. So, you know, average 30%. If you combine that with 100 percent renewable input. So solar on the roof or a car canopy if you have parking around it. And you connect this building to the grid in a much more intelligent way. I'm going to talk about this you know, a little later. You, you easily decarbonize your building completely and get to net zero. And there's many examples around the world of, of buildings or fleets of buildings that have already achieved that. So, so that's a very exciting example. Now, you know, in the grand scheme of things. Imagine, I mean, you can, you know, all of us, we can do the numbers, right? If 40 percent of total human CO2 emissions are buildings, and half of that, so 20 percent of all human emissions, is the operations of buildings around the world, and I reduce that 20 percent to just a few percent, down from 20 to just a few percent, that's massive. That is real impact for all of us, for humanity. So that's just one example. And many other examples I could give you, right? Because Siemens plays in industry decarbonization, transport decarbonization, e mobility, building decarbonization. We do less in agriculture, you know, a little bit. We, you know, sort of have a few solutions there as well, but that's not the core of what we're doing. But then one of the really big ones is the energy grid itself. So the energy systems. And that, you know, you know, we have a whole division doing nothing else than, you know, building the software that utilities need to squeeze out more capacity from their networks and to decarbonize their networks, right? So sort of switch on way more renewables in a faster way, and we could sort of deep dive there, Tom, as well, if you like. But I gave the examples of, I just did a deep dive, right, on buildings, you know, what, how much you can achieve there. And I could tell the same story in e mobility and the same story in industry and the same story in, in, in grids and energy networks.

Tom Raftery: 15:32

Fantastic. Well, talk to me a little bit more because you alluded to it, but connecting smart buildings or smart connections to the grid. How does that work?

Thomas Kiessling: 15:42

So, that's a initiative that we created quite recently as part of the World Economic Forum, where we felt that the industry actors are looking at this question of how, how do we get into 100 percent renewables and energy grids? Often in a isolated way. You know, the, the, the utilities, the energy companies, they are scrambling to get in more capacity to achieve the famous doubling or tripling of capacity of electricity networks due to the historic wave of electrification we're all in to decarbonize, right? So they're focusing on that. The regulators of utilities are focusing on, you know, getting that capacity out the door. But the what we have shown also in a recent research paper, which we discussed widely at the World Economic Forum is if you now in a smart way, connect the the management, the operations of the building to the grid. So the grid knows how much the building is consuming in the next 15 minutes, one hour next day and so on. You can squeeze out a lot more capacity from the grid, doing two things. One, you can switch on more renewables in the, in the energy grid faster. And two, you use the buildings as a sink and source of storage of energy because it, you know, buildings have solar roofs. They, you know, many of the industrial buildings have storage systems and the like, which by the way, also goes for vehicles. You know, batteries of electric vehicles and trucks and the like, over time, this is all very new and recent, right, will be used to store energy and help the grid to stabilize as well. And we call this GIBs Grid Interconnected Buildings. And we have shown that you know, the connection of these buildings to the grid. So the grid knows how to, you know, how to control and manage the buildings in some way has the potential to save billions. We've done that study for the, for the US grid and to accelerate the rollout of renewables fundamentally. Sounds a little abstract, Tom, I want to just give you one use case. So, you know, the, our audience sort of gets, gets what I'm talking about. So let's take the example. Let's take an example of how the thermal mass of a building can be used intelligently. So if you know that between 5 p. m. and 7 p. m. You have a peak in the usage of the energy grid, and thus, you know, that's where the bottleneck is. And that's where we have problems, stability problems in the grid. And we simply have, you know, you know, that creates, that, that peak between about, you know, 4 to 8 p. m. roughly, and depending on the country, creates a bottleneck, which then leads the grid operators, To either curtail the demand or to increase the prices, you know, you know, around that, that time charging peak tariffs in order to, to control that, that, that demand. It also leads to delay to switch on more electric vehicle charging stations, more heat pumps and the like, because the grid simply can take it, you know, in particular during that time, because that's the sort of the peak of demand. Now, if you pre cool or pre heat, in particular commercial buildings, in order for that building between 5 and 7 p. m. to use less heating or cooling energy, that will get you a few percent of capacity in the grid. That is a typical use case of using buildings, you know, as in an interconnected way. So the grid actually steers these buildings. You don't have to do this all the time, but in particular in the summer, you know, the worst, the worst peaks are, you know, happen in the summer between five and seven. When the grid is, is has a hard time to cope, you know, with the massive peak, you know, demand and then so that's, so that's an example, right? That's a great example of using buildings you know, to, to act in a smart way. That's why we call it smart infrastructure, by the way, you know, to act in a smart way and react to signals from the grid to preheat, pre cool, or next use case to use storage systems

Tom Raftery: 20:10

Right.

Thomas Kiessling: 20:11

and many buildings have storage systems, right? Battery storage to charge up the batteries when the sun is up between 9 a. m. and 3 in the afternoon and then to discharge that capacity into the peak demand in the afternoon, which again reduces that peak. And increases the capacity on that. So you get the idea, you know, that smart interaction, you know, between supply and demand, between grid interactive buildings and the grid will allow us to accelerate the rollout of renewables, to decarbonize faster and to save billions of, of hardware investment in the grid.

Tom Raftery: 20:47

Okay, so the buildings are acting almost like batteries. They become a form of storage themselves, and they're doing demand side management. So they're, they're matching their demand to the supply on the grid is basically. And of course, you mentioned peak pricing so that if the pricing is going up during peak demand, and they're reducing their demand at the same time, then the buildings energy costs are dropping as well as their demand. And the other, I think the other aspect of this, which is interesting is that in times of peak demand, it's not just that the costs go up. But it's also at that time that the energy companies bring on more fossil fuel typically generation. So at times of high demand, you typically have higher emissions on the grid as well. So if you're reducing your demand at that time, you're making the grid more sustainable. You're making your, you're dropping your emissions and you're dropping your costs. Would that be a fair summary of it?

Thomas Kiessling: 21:48

Absolutely. Yes. Plus today, the grid operators are curtailing renewables all around the world. In particular, during that peak, because in particular, the distribution grid, because of that peak demand, you were, you were just summarizing, you know, can't take the sort of the interconnection of these renewables, which, which is an adverse effect, which is, which doesn't make sense intuitively at all. Right? But if you're, if you're able to use certain configurations like storage systems, you know, utility status storage, to, you know, to, to use that renewable production, store it, and then interact with the buildings to optimize the, you know, the, the building's demand. We have shown that you can switch on more renewables faster with the existing, you know, energy grid and don't have to wait for expensive upgrades, which is, which are going to take three to five years.

Tom Raftery: 22:46

Sure. Because not alone can you reduce your demand at times of peak demand on the grid, but you can also do the opposite increase your demand when demand is low and therefore typically when demand is low, that's when there's more renewables on the grid anyway. So you are again pulling in a higher percentage of low emissions energy, but you're also sending a demand signal for that low, low emissions energy. So again, it's, it's a win, win. It's a win for the building operator and it's a win as well for the grid operator and allows greater penetration of renewables on the grid, right?

Thomas Kiessling: 23:24

That's it. That's exactly it.

Tom Raftery: 23:25

Okay.

Thomas Kiessling: 23:27

So that was another example, right? Another response to your question. How do we help our customers decarbonize faster? You know, reap the energy efficiency potential, right? That was the example of helping the grid, okay? Helping the building, helping the grid, right? Transport would be another example. Industry are more examples.

Tom Raftery: 23:45

Okay. Fantastic. And what kind of innovations in infrastructure are you seeing or are you seeing are most promising for shifting the, the the world towards sustainability?

Thomas Kiessling: 23:59

So, just a few examples. Right? Because again, it just depends on the domain, right? There is no one. There's a, you know, there's like dozens of domains. We have to watch one by one. Let's talk about transport, right? You know, e mobility. Because that, that, that's, that's an example of you know, sort of high, high innovative, a lot of innovation intensity. So we're all moving to fast charging, you know. DC charging, you know, sort of 100, 200, 300, 400 kilowatt charging which is needed to convert our truck fleets to electric trucks. There you're talking about very large batteries because these are vehicles that need, you know, much more power compared to a passenger vehicle. Now, these fast charging systems They need, there's a lot of innovation that's going on there, right? We're able to now, you know, charge a truck in an hour or two with a, you know, fast charger that allows the charge at a rate of 300, 400 kilowatt or higher. But megawatt charging is going to be the next frontier. Well, these are, you know, these are massive power electronics devices because you're pumping megawatts into a, truck, which allows you to reduce the charging time then even further, you know, onto closer to what many of us are already experiencing, experiencing in electric vehicles where it takes the famous 12, 15, 18 minutes to charge a Tesla at a supercharger. So We gotta do this with a truck, you know, with the, with the you know, commercial electrical with a commercial fleet, with a truck fields around the world. And this is one in one area of innovative activity of many players. Siemens is one provider, right, of, of these kind of charging stations. One example. Another example is the, the grid interaction, which we already discussed, right, the, the kind of use cases, you know, to balance out renewables and, you know, thermal masses of buildings, et cetera, they need real time control systems. Again, which manage the grid in a, in a seamless way in a real time controlled way forecasting the next couple of minutes of what's going on, what's happening, you know, everything from weather to production to demand and abilities and the like. These are again, massive control systems, a lot of innovation happening there. You know, the buzzwords here are virtual power plants and micro grid controllers and the grid edge and the like. I don't want to, don't even want to get into the buzzwords here, but that's. The systems, the control and, you know, digital systems that are, that are managing, you know, the interaction between the grid and these new these new demand areas. Many more. We haven't talked about hydrogen, so we haven't talked about power to X, which is, which is a very interesting area of innovation. There's a lot happening there as well. Industry, you know, let's talk about that. Siemens is pioneering what we used to call digital factories, or, you know, sort of autonomous digital factories based on digital twins. So what is this famous digital twin? What is this buzzword, right? Which, you know, many of, many of you have heard. Well, it is. the design of a factory digitally in a model, you know, a simulation model. And that is the blueprint of this factory, which you use to actually build the factory. Well, if that blueprint then is, is still the same and up to date when you operate the factory, what you would do is you design the next robot in the conveyor belt into the digital twin, and then it gets deployed automatically into the real factory. So that's why at Siemens we call sort of one of our mission statements is combining the real and the digital world. Because we might design a factory digitally and then deploy it in the real world, but much faster. Much in a much more productive way than, you know, in the past, where you had lots, lots of media breaks between the various steps of construction, so that increases the productivity, it allows to put up decarbonized net zero factories much faster around the world, which is what we're doing with our own factories, right? We've built several factories like that, But that's the kind of software we provide to our customers to build their decarbonized factories much faster around the world. Once you have the digital twin and you have built one of them, you just reconfigure the same digital twin. To build the next factory in another country, because that, you know, you need to comply with different regulations with different standards, but you can all configure that into your digital twin, and then you build the next factory. So, you know, rolling out factories now, right? Much faster, much productive way. That's sort of, you know, one of the innovation areas, you know, using simulation and digital twins.

Tom Raftery: 30:17

Interesting. Interesting. And obviously, IOT plays a massive part in digital twins, but we're seeing as well the rise recently in AI. Is that, is that coming in as well to the likes of digital twins and having a significant uptick in effect?

Thomas Kiessling: 30:33

Yeah. So, I mean, AI is further pushing the efficiency of running assets, you know, and the asset could be a building, a charging station, a factory, a hydrogen electrolyzer. And I just want to give you a couple of examples. This is, this is the you know, we discussed this recently at the World Economic Forum. Sort of groups focused on, on, on, on AI and what, how AI can help us accelerating decarbonization even faster. So in the case of a building, let's just take that example again. The job of a facility manager today. So the, the, the folks that run the building that make sure that the heating works and that you know, the, the, the, just the basic operations of the building, you know, it's just works and it's effective that that job today is, is subject to a serious talent crunch since COVID it is very hard to find talent for, for, for these kinds of jobs. So there is a strong automation push to enable the folks that run buildings, facility managers to not only run three or four buildings, but a 100 buildings at a time. How do you do that? Well, through IoT, automation, digitalization and AI. So the job of a building manager, and again, this is some real down to earth discussion here, right? You know, would be to come to the office, find a few tickets that some heating system doesn't work, that some access control system doesn't work, that somebody doesn't find their access card. And then you go one by one, you know, doing your job. What about, you know, what if an AI based co pilot App would tell you that the highest value actions that you can do as a facility manager today, i. e. achieving more and more energy efficiency in your fleet of buildings, are these five things. It is to take a look at your solar roofs because AI found out that you are below benchmark when it comes to the efficiency of how your solar systems run on your roofs, which might be the result of soiling, you know, lack of maintenance. Maybe the shading isn't right. Maybe an inverter is down, whatever it is. And the AI copilot gives you the areas you should look at. You look at that close that ticket, get a, you know, repair team up and you increase the output of your solar roofs in a hundred buildings by 3%. That's massive.

Tom Raftery: 33:19

Yeah.

Thomas Kiessling: 33:20

As opposed to, I use the same time to take my car, drive to a building, go in a basement, lock myself into an HVAC system to understand that some fan handler is broken. Right? So AI can help. And why is that? Because in particular, Gen AI is very effective in analyzing unstructured documents. So if I now run all the information I have on buildings, which is left, right, center, you know, which sits in PDFs, and then maybe a BIM document and maybe somewhere on a manual and lots of emails, I just run all this stuff through Gen AI, then

Tom Raftery: 33:58

Yeah.

Thomas Kiessling: 33:59

Then I can actually define patterns of how I should run my fleet of buildings in a much more effective way. Does that make sense? This is such a nice, down to earth example. We often use very sophisticated examples when we talk about Gen AI, but, you know, just the structuring of words, of, you know, of phrases, of documents, right, of language, this is a language based model, is super effective to help us doing that. Obviously be using AI then for our own call centers because that enriches the information of a customer who calls in, but that's, that's a generic use case. Everybody's doing that out there. And then just to give you a third, sort of a last one, AI is, is highly effective in our own products we provide to our customers. The example is a recent launch we did what, you know, in a, in a building product. This is our Building X platform that we rolling out globally now helping building operators to decarbonize, you know, where we would take in weather information, comfort information, preferences of tenants. So the whole environment of, you know, how do people feel comfortably comfortable in a building at the same time? How far can I go changing the shading, changing the heating and cooling? You know, changing the humidity, changing any kind of these parameters with the objective to reduce my energy consumption. So again, these are AI models that are training, you know, that are, that are learning the preferences of tenants, you know, working and living in, in, in buildings to squeeze out even a more couple of percent of energy usage, which in the grand scheme of things, because buildings are 40 percent of the, of the CO2 problem, you know, result in massive savings in the system. So that's, you know, just another example,

Tom Raftery: 35:47

Yeah, yeah, yeah, no, fascinating. I I have solar panels on my roof here at home. And one of the things I did recently was I, I installed the solar panels in 2018. So I went to my portal for my solar panels. I have an online portal where I can download the data. Downloaded the data for the last six years of solar production. Came out in a CSV file. I gave it to ChatGPT, I had it analyze that data, and one of the questions I was curious about was, has there been a reduction in the efficiency of the panels over the last six years? Because they're on the roof. They're not easy to clean. Birds sit on top of them all day and soil them, to your point. So I wanted to know, should I go up on the roof? Should I scrub them to make sure they're clean? And it turned out no. It turned out over the last six years, month on month on month on month, the output hasn't dropped significantly. Probably wouldn't hurt if I did clean them, but it's not, they haven't lost, you know, they haven't lost any, noticeable output. So AI has, has, has been able to just in this very simple analysis, tell me I'm fine. I can imagine in a far more complex situation, the, the outputs are going to be far more nuanced, but also far more helpful.

Thomas Kiessling: 37:13

wonderful example. So what I, so now, you know, in the commercial and industrial world, this would be the, the, the sort of the jump from preventive maintenance to predictive maintenance. And then the next step would be prescriptive maintenance. You know, intelligence based prescriptive maintenance, but just that jump. Do I need to send out that maintenance crew twice a year to sort of clean the solar panels on a thousand buildings? Does that really help? Maybe not, right? If I had that data, right? And that's exactly what this is. The kind of use cases that that that we're running, you know, this makes the whole system more efficient because that crew obviously comes with cars, goes on the building, spends time and the like. So, you know, great example, right? You know, the movement from this is a mega trend, right? To go to, you know, to go from from purely preventive, scheduled based preventive, you know, onto predictions and then autonomous operations. Right off of a building, you know, or a electrical depot with electric trucks and the like.

Tom Raftery: 38:22

Sure, sure, sure, sure, sure. The the monitor, the monitor report, the Infrastructure Transition Monitor report that you talked about earlier. It also points out various challenges and divides in the path to net zero. So, in your view, what are the most significant barriers and how can we overcome them?

Thomas Kiessling: 38:43

So there is no silver bullet. Obviously. I think there is big stones. There's clusters. And the clusters, they are structured around these five major areas of emissions. Buildings follow a specific logic and need and requirement of decarbonization, which is very different from electrifying our vehicle fleets. So you have to argue by domain. And then there is overarching trends and discussions. An example would be hydrogen. What is the role of hydrogen? Which use cases make sense in an industrial setting, in an e mobility setting? You know, what is the role in our, in the production of energy, you know, Power to X kind of use cases, sector coupling use cases using hydrogen, for example. That's an overarching question. So there's a few fundamental technology, you know, and then let's not talk about nuclear fusion, right? If we ever get there, you know, and that is, you know, obviously, another, you know, total game changer if we ever get there. So a few big overarching areas and stones that we just need to continue to push and invest to clarify where exactly, you know, does hydrogen have the economics and the use case to help us accelerating the path to net zero and the reversing climate change for example, right? But otherwise you are very domain specific, you know, we could talk about agriculture, you know as an example That's a completely different ballgame right of how to you know, make sure that plants sequester more carbon than they emit, you know, and, and and the like, we can talk about that as well, right? But that's a completely different, you know, discussion that, that, you know, needs, needs to happen there, you know, compared to process industries and chemical.

Tom Raftery: 40:41

Yep, yep, yep. We are coming towards the end of the podcast now, Thomas. Is there any question that I didn't ask that you wish I did or any aspect of this we haven't touched on that you think it's important for people to be aware of?

Thomas Kiessling: 40:56

I, I think not, not so, not, not so much an aspect you didn't ask, but I think maybe a remark you know, or sort of a comment I'd like to make, which is, often in these kind of discussions on sustainability and decarbonization, there is a, there is an assumption that we're not going to get there as humanity. It's the underlying assumption, right? You know, when I talk to my friends, you know, on panels and professional settings and whatever it is, the majority of people, I think it's fair to say, think that humans are not able to organize themselves in such big systems, you know, which, you know, we're talking about a global system here, right? To take the right decisions together across political, ideological, geographical boundaries to get there fast enough. And I absolutely want to break that perception because yes, we will be too late. Yes, we will see catastrophic impacts of climate change, but ultimately we'll get there and you know, so, and so, you know, maybe that's, you know, now we're on a philosophical level, but we're also on a level of concrete behavior change of all of us every single day because if you decide for an electric vehicle as your next vehicle, even if it, you know, charging still don't works a hundred percent and it's a little more expensive and it's a little more cumbersome and all that, right? If you do that, you know, obviously your neighbors take notice and obviously you talk to your friends about it. So you have a multiplier effect of maybe a hundred people at least So just think about that. If we systematically configure our Uber or whoever ride sharing apps with the now available option that I always prefer low carbon or electric vehicles. Well then guess what's happening? More drivers are going to buy electric vehicles. So, you know, let's, I just want to put in sort of, I want to suggest a positive, fundamentally positive, can do attitude in reversing climate change and to actually get there as humanity if we all multiply the efforts that's really sort of you know, I think the

Tom Raftery: 43:32

Yeah, yeah, yeah,

Thomas Kiessling: 43:33

the spirits I'd like to instill

Tom Raftery: 43:35

no, it's, it's a good point. And I'm actually on my third EV at the moment. And my car before that was a hybrid, a Prius. So I, I, I'm doing my bit and in fact, because I've got the solar panels, it means very often I'm driving for free and gratis because I've charged the car. I tend to plug it in more on sunny days. And so it charges directly from the solar panels. So, driving on sunshine. It's great. It's great.

Thomas Kiessling: 44:00

can't can't wait for the for the option that airlines are gonna put out pretty soon that obviously I per definition in my traveler profile. I prefer biofuel based you know decarbonized fuel trips with airlines just as I just did in my Uber app. So, you know, we got to go step by step

Tom Raftery: 44:24

yeah. Fantastic. Thomas, if people would like to know more about yourself or any of the things we discussed in the podcast today, where would you have me direct them?

Thomas Kiessling: 44:34

so, so that we mentioned the, the Infrastructure Monitor that we put out once a year and it's very comprehensive. It has a lot of material, a lot of data points for the reading. So it's a real ecosystem sort of publication. I recommend that. And, you know, I would recommend to just put it in the link and, you know, sort of publish that. Look at my LinkedIn. You know, we're regularly publishing together with all of the leadership team of, of Siemens, you know, updates, you know, on that whole end to end question. And yeah, that's, that's pretty much it.

Tom Raftery: 45:07

Fantastic. Okay, great. Super. I'll put those links in the show notes. Thank you, Thomas. It's been really fascinating. Thanks a million for coming in the podcast today.

Thomas Kiessling: 45:16

Thank you, Tom. Appreciate it.

Tom Raftery: 45:19

Okay, we've come to the end of the show. Thanks everyone for listening. If you'd like to know more about the Climate Confident podcast, feel free to drop me an email to tomraftery at outlook. com or message me on LinkedIn or Twitter. If you like the show, please don't forget to click follow on it in your podcast application of choice to get new episodes as soon as they're published. Also, please don't forget to rate and review the podcast. It really does help new people to find the show. Thanks. Catch you all next time.