Climate Confident

Using Data And Analytics To Reduce Emissions In The Chemicals Industry - A Chat With Carbon Minds MD Arne Kätelhön

July 28, 2021 Tom Raftery / Arne Kätelhön Season 1 Episode 35
Climate Confident
Using Data And Analytics To Reduce Emissions In The Chemicals Industry - A Chat With Carbon Minds MD Arne Kätelhön
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Show Notes Transcript Chapter Markers

One of the most difficult industries to reduce emissions in is the chemicals industry. I recently came across Carbon Minds, a company focused on emissions data specifically for the chemicals industry.

I was intrigued to know more so, I invited Arne Kätelhön, Carbon Minds co-founder and Managing Director to come on the podcast to tell me all about the industry, and how they're helping clean it up.

We had a fascinating conversation and as always, I learned loads, I hope you do too.

If you have any comments/suggestions or questions for the podcast - feel free to leave me a voice message over on my SpeakPipe page, head on over to the Climate 21 Podcast Forum, or just send it to me as a direct message on Twitter/LinkedIn. Audio messages will get played (unless you specifically ask me not to).

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And remember, stay healthy, stay safe, stay sane!

Music credit - Intro and Outro music for this podcast was composed, played, and produced by my daughter Luna Juniper

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Credits
Music credits - Intro by Joseph McDade, and Outro music for this podcast was composed, played, and produced by my daughter Luna Juniper

Dr Arne Ktelhn:

An example that I always like to use this polypropylene production China, you have an average carbon footprint, around four kilogram of co2 equivalent per kilogram if I remember correctly but the individual supplier carbon footprints they went from one to 11. So that's a factor 10 in between.

Tom Raftery:

Good morning, good afternoon or good evening wherever you are in the world. This is the climate 21 podcast the number one podcast showcasing best practices and climate emissions reductions. And I'm your host, global Vice President for SAP. Tom Raftery. Climate 21 is the name of an initiative by SAP to allow our customers calculate, report and reduce their greenhouse gas emissions. In this climate 21 podcast, I would showcase best practices and thought leadership by SAP, by our customers by our partners on by our competitors if their game in climate emissions reductions. Don't forget to subscribe to this podcast in your podcast app of choice to be sure you don't miss any episodes. Hi, everyone. Welcome to the climate 21 podcast. My name is Tom Raftery with SAP and with me on the show today I have my special guest on our show. Would you like to introduce yourself?

Dr Arne Ktelhn:

Yeah. Hi, everybody. I'm Arne Ktelhn. I'm one of the cofounders of carbon minds. We're the data analytics company based in Cologne, and we provide environmental data for chemicals and plastics.

Tom Raftery:

Okay, super. And, you know, this is the climate 21 podcast. So the reason we've invited carbon minds onto the podcast is because the data analytics you're running for the chemicals industry is particularly suited to climate emissions data. Is that correct?

Dr Arne Ktelhn:

Yeah, definitely. So climate climate impacts a huge part of it, of course, an environmental assessment. It's not always only about the climate. So water toxicity is eutrophication as important impact category, but it's true climate is probably the most pressing problem at the moment.

Tom Raftery:

And for for the foreseeable future, I gotta think I was looking today, the amount of co2 as measured from Moanalua is at 419 parts per million, which is a record, it's this, this is a serious issue. Anyway, tell me about carbon minds. I mean, you've given me kind of very high level, but what kind of data analytics and why is that important?

Dr Arne Ktelhn:

Yeah. So basically, the companies who use our data, they use it for environmental assessment. So if you want to solve the climate problem, and I couldn't agree more with you that it's such a pressing problem, we need to know how to do it. And the first step in this process is always understanding the status quo. Where are we now, where does reduce the emissions of my company or a certain product come from, and this is exactly where data is needed. Because these environmental assessments, they can be quite complex or intuitively, when thinking about the climate impact of a specific company, people tend to look at the last production set. So they might look at the chimneys of this company, and see how much co2 is coming out of there. But reality is much more complex and these so called direct emissions from a company, they are often only a tiny part of the climate impact, weather much bigger part it comes from the supply chain, both up and downstream. So this depends on what resources or fossil resources have been used throughout the entire supply chain, what are the production steps, that gets your arm from the resources to the final product, or these production steps, they will need energy there direct emissions that we need materials, as you can see a huge amount of data on that if needed, but it doesn't even enter because it also depends on how products are used. How are they disposed off? Can you recycle them? So in summary, we went understanding the climate impact or environmental impacts on Channel, it's important to look at the entire lifecycle not only through this holistic view, you can really understand what are the entry points of when you build materials, renewable energy? How can you improve some tile system?

Tom Raftery:

Okay, and who are your customers? What What are you? What problem? Who are they and what problem are you solving for them?

Dr Arne Ktelhn:

Yeah, that's a good point. So our focus is on the chemical industry and our customers. They basically along the entire chemical value chain that starts from oil and gas, because those are the main resources on which plastics and chemicals are built on today. Then of course chemical industry itself. Many of our clients, but also those companies who use chemicals in the product. So for example, one of our clients is one of the biggest and biggest high tech company, because he also made a lot of polymath for, for computers, for phones and so on. And I think for these, these these companies say, basically, they have two problems. First of all, they don't necessarily know what their emissions are, where the emissions hotspots are often. And there are only a handful of products that dominates the entire climate impact. So yeah, thanks, one. And the second point as how can they improve it?

Tom Raftery:

Okay, and where does the data that you have, you know, where does it come from? How is the data set that you have different from, you know, me sticking my finger up in the air and going seven kilos?

Dr Arne Ktelhn:

Yeah, I hope it's a bit more precise. No, where does it start? It's a lot of stuff that basically starts already six, seven years ago, as a co founder, cofounders of our companies, and they were in academia at this point. So I was leading them team for life cycle assessments, assess environmental assessment methodology at Aston University. And we just often had the problem of data availability. So we wanted to find a nice solution on how to improve the climate performance of specific chemicals. But often, we just couldn't find for supply chain, chain data. And if you think about this, it's a huge problem. Because if you're, if you don't have this data, you don't know how to improve it. So what we did at this time, as we said, we started building our own model. So basically, we started building crops, the entire chemical supply chains, from the oil through the refinery processes for all the different different plants and to do our analysis. And first, we just did it for scientific paper to solve the problems that we had at hand. But then we realized, it's basically a bottleneck for a lot of climate action, also in industry. So we started building these models, bigger and bigger, and combine also different data sources, from technical data to trade data, market intelligence data, what about production plans are used at what place in this world. And then basically, this is the input data that we use for our, our model, and we grew it over time, until we spun it off to run to the company. And this was one point our minds was born.

Tom Raftery:

Okay, if, if I, someone who is somewhere on the chemical value chain, so a potential customer of yours, and I sourcing some chemical materials, some from some factory that may be in China, for example, because lots of stuff is made in China these days. So why not? How do I then through you get the information I need? Or how do you get the information to give to me, I mean, they could be using utility x, they could be using process y, you know, all these kinds of factors come into come into place to create the carbon footprint and the emissions implications of my purchase.

Dr Arne Ktelhn:

Yeah, yeah, exactly. So there is one thing that the industry did for decades, and Qantas is trying to understand the costs of suppliers and offset competitors. And in order to understand the costs of these actors, you need information on the technologies, production capacities that they are running. So this is information that is available. And that can also be purchased from from different sources. But it's cost information. So I think the metrics that we did is that we use this data combined with our technical modeling and enter trade data in order to calculate emissions from us. This is something that data was never intended for. But some pieces of this puzzle, were already out there. But we had to put it together and this one model that is focused on emissions and not and not on costs anymore.

Tom Raftery:

Okay. But even even still, I mean, surely different processes in forming chemicals will have different emissions implications, and how do you get access to those kinds of data?

Dr Arne Ktelhn:

Yeah, absolutely. So we modeled on the Tennant University. We were at the Institute of technical thermodynamics and thermodynamics. It's, it's always a buzzword for for complex and melodic, but what these groups are focused on was on process modeling. So we need to understand these these processes in detail and this is where we got A lot of the technical technological knowledge that we needed in order to, to understand the technical part. So in the end, you need to understand the technology that is used in a plant, you need to know where the plant is, and so on. And basically the information, what technology we're looking at. And you need to understand how the plants are clustered, because it makes a huge difference. If a plant gets its raw materials, from plant a compared to plant, Plan B, and I think this is what we put together, maybe to understand that a bit better is what was the status quo before this. So what is used today, a lot is country average data for environmental assessments. So if you use, let's say, probably probably one of the major, major plastics, what is often done is that your, if you buy it from, let's say, Spain, and that you would use the country average, on the footprint of this material from Spain, or from a specific technology for your accounting. But in reality, if you look at the different supplier, in Spain, or in any country in the world, they might choose with a different technology exactly as you as you just said, and these technologies, they might use different raw materials and lead to completely different impact. So an example that I always like to use is polypropylene production, China, you have an average carbon footprint, around four kilogram of co2, equivalent per kilogram iPhone, remember correctly, but the individual supplier carbon footprints, they range from one to 11. So there's a factor of 10 in between. So what happens with Europe, you use the average for your assessment, but also imagine what a huge potential there is for impact reduction if you choose your suppliers wisely. And I think this is this is what keeps us going. Because we believe that this is how you can get data that is actionable, in the sense that it helps you not only to document the problem, but it also gives you gives you steps throughout the direction how to solve it.

Tom Raftery:

Yeah, I know that that's a very good point, because there's going to be in the next eight and a half years initially. And then in the two decades after that there's going to be massive pressure on countries and companies organizations to reduce their carbon footprint. I mean, here in the EU, the EU has passed into law legislation, mandating that these 27 countries of the EU reduce their emissions 55% by 2030. So that's eight and a half years from today, you know, so that's a huge challenge. It's a really ambitious goal, and it's passed into law. So there will be fines associated with not complying with that. So companies will need to be able to, first of all measure, and secondly, then reduce their carbon footprint. And to your point, exactly, if you have the data from your suppliers, or of your suppliers have the carbon implications of choosing supplier a over supplier B, I think the figures you gave a second ago were one kilo per kilo polypropylene versus 11 kilos per Quito polypropylene. I mean, that's an enormous saving right there in terms of emissions, if that's what you're trying to reduce. So without that data, you don't know. But with that data, you can document and reduce your emissions, which is hugely, hugely significant.

Dr Arne Ktelhn:

And if you think about it isn't a huge problem that source potential climate benefits. They are also hidden right now. So imagine you as a supplier, with the best carbon footprint within a certain national market, and no one can see that it can see it for it's a huge problem. So it's not only about pointing fingers of the atom, more polluting suppliers. It's also said benefits are currently hidden. And maybe what is important, those are also cause and benefits. Now, these differences, they are among the technologies that are using fossil resources today, and so even in this fossil space have such huge differences. So no question that we need to end up with renewable, but they're also also shorter term on term options. So we calculated for all the chemicals that we looked at, on average, you can reduce about 30 I think it was 38% of your plant footprints by choosing the best supplier in your market.

Tom Raftery:

That's a long way towards that 55% goal right there. It won't be enough yet good enough, but it's a long way towards it. It is Yeah. Know that. Fantastic. It strikes me as well, though, that if I am someone in that chemicals value chain, who is going to you looking for advice on my suppliers? That, you know, you could also help me reduce my processes carbon footprint as well. So, you know, it works both directions is what I'm trying to get out, I think is that correct?

Dr Arne Ktelhn:

Yeah, yeah, that totally makes sense. I think what is tricky with emission reductions is, again, this complexity of supply chain. So if you want to use recycled material, it doesn't mean that the best entry point of recycled material is your process, it could be your tier one supplier. So they're basically the ones that you're buying your product from, or it could be the supplier from this supplier called tier two, or tier three, or tier four. I think by by having this full model of supply chain, we can look into more integrated options. Also, our companies could work together, in order to improve the carbon footprint, I'm together because imagine, like to start at the very beginning of the supply chain, chemical supply chain, it's, it's awesome, like cracking processes, and you're managed to get recycled material or renewable material biobased sealed co2 as renewable feedstock in there, the benefits, they propagate through the entire supply chain. And this is also an advantage. So it's funny when you're not when you talked about it on polypropylene production, China. So some of the more polluting technologies on so called technology say they are based on coal. And they produce methanol and stack from methanol to olefins don't want to use too many technical terms here. But what I want to say is that those are technologies, which we cry are hydrogen, right? And hydrogen could be an entry point on for renewable energy. So if you produce it from wind turbines, for example. And so by switching the supplies there, and then didn't do the calculation on much at what cost to be honest, but it could be it could be also a good entry point to improve the entire system.

Tom Raftery:

Okay, very good. Now, you are based very much in the chemicals industry, are there other industries as well, that you're thinking you're branching out into or that you can help today?

Dr Arne Ktelhn:

I think a lot of interconnections recently listened to the podcast was for Catholic, for example, your works on co2 utilization, and there you have a problem and that you're new to renewable energy to make your processes one to understand these processes in which you understand the energy sector, so it's very much interlinked to energy sector would be something which is very close to us, I think very important sectors that we didn't work with that much so far would be cement industry would be steel. So basically, the emission intensive industries. And when we are rather young company, also, we can't do everything advanced, advanced, but I hope that similar solutions will come up in the different sectors.

Tom Raftery:

Okay, that was something else I was going to ask as well. Who Who is your competition in this space? If there is any ru market making? Or what how does that work?

Dr Arne Ktelhn:

Yeah, of course, environmental assessments have been done for quite a long time. The data that is available, and that is used right now is exactly this country average data that I was talking about. And there are some databases, and also some great databases out there. But I think in terms of level of detail, some modeling on a supplier specific level, and to my knowledge, really the first and so far only company who does these calculations on a really large scale for the chemical industry?

Tom Raftery:

And aren't Can you speak to any customer examples that you can talk to?

Dr Arne Ktelhn:

Yeah, um, yeah. So which one to pick? Let's take, let's take this one company. It's a huge polymer producer. And this company, they use a lot of chemicals, of course, as feedstocks because they're not fully integrated to the, to the refineries. And they are publishing their so called scopes. We mentioned some scopes we emissions include, so supply chain emissions that I was talking about, and they're at the stage of using a bit and giving out the baseline. So they are status quo word now, but they know that they have targets for the future. They want to reduce by X percent until 2030. And they want to continue with using it and by 2050 So, how we could help some is, first of all, giving more realistic baseline. So not based on country average data, but based on the supplier so that they that they know where their emission hotspots are today and where they are doing quite, quite tiny compared to to the status of the carbonization where we are currently in. And I think going starting from the Spaceland, we offer the data and where they see and perspective for like some concrete actions, how they, how they can improve it. So for some products, they might have a huge mix of different suppliers and shifts this entire mix towards a more sustainable one. And some of the cases they might have used the same supply for decades now. So it's not always always that easy to change your supplier in this area. But but still with this, so data comes in as a basis for the discussion. Because if you have concrete data on the table, where you can see what is possible where the competition is, it's much easier to define two different targets. And that since this is a typical data driven use case, another one I mean, it's another company, but it's different would be to start from this and to build scenarios on how the entire system could look like if it were a renewable if it were based on co2 as a renewable carbon feedstock, if it were based on recycled materials, and truces, it's never only one or the other. It's always a mix, it makes it more more complicated to understand where the meets and so where where do you use, what new technology and so on. So this could be basically looking for data driven use case, and starting from this young mazi improvement consulting 2 trillion use case.

Tom Raftery:

And in the in the case that you referenced there, for example, where maybe you have a supplier for 10 or 20 years or something? And it turns out, you discovered that they've got this enormous carbon footprints that you were unaware of? Would it be possible then to potentially approach this supplier with suggestions on how and work with them to help them reduce their carbon footprint so that you are then reducing yours?

Dr Arne Ktelhn:

Absolutely, absolutely. And also these improvement options along the supply chain. So one steps that I see quite a lot in the industry is, first of all, using renewable energy for some processes, which use a lot of electricity. This might change a lot for some other processes, and they were on a gas or electricity supplies. not that important. But to justify as an example, we could show how this could change. But we could go further, we could could show what would happen if they use part of renewable feedstocks, maybe themselves or ask their supplier to do it, for them, and so on. So basically, it's with this integrated view, you can better understand what the options are. And to be honest, sometimes the options are a mix of actions that you can take yourself, but the actions that you need to do and collaboration along the entire supply chain. This is what makes it I think, more complicated, of course, sure. But at the same time, there's also a lot of potential. I mean, if companies work together a bit more if they share more data, what is needed in these cases, often you find some completely different potential that you have that you have never looked at before. So it can be can be really beneficial, I think for for many dimensions. Very good.

Tom Raftery:

Very good. Okay, Arnett we're coming towards the end of the podcast. Now, is there any question I've not asked that you wish I had? Or is there any aspect of this that we've not touched on that you think it's important for people to consider?

Dr Arne Ktelhn:

That's a good question. I was I was expected that you could fail the question. Maybe, maybe questions that would be quite relevant. If someone is interested, how can they find out? That was my next question.

Tom Raftery:

Next one, so that study simply follows I don't have any other questions. Okay, so then we'll go on to the last question. If people want to know more about yourself RNA or about the company carbon mines, or any of the topics that we discussed today, where would you have me direct them?

Dr Arne Ktelhn:

Yeah. I think the easiest way would be of course, our website. So carbon miners minds.com. And there you also find direct there with email addresses, which which goes to me and to my and my colleagues. The other way we have a strange name, so anecdotal interview, if you find an article and somewhere on LinkedIn or Twitter, it's quite likely that you found me.

Tom Raftery:

Great. Great. That's been fantastic. Thanks so much for coming on the podcast today. Yeah, thank you very much. Okay, we've come to the end of the show. Thanks everyone for listening. If you'd like to know more about climate 21, feel free to drop me an email to Tom raftery@sap.com or connect with me on LinkedIn or Twitter. If you'd like to show please don't forget to subscribe to 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.

(Cont.) Using Data And Analytics To Reduce Emissions In The Chemicals Industry - A Chat With Carbon Minds MD Arne Kätelhön

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