Blue carbon has emerged as a popular climate solution, with offset marketplaces like Verra and Gold Standard eyeing blue carbon methodologies and Salesforce and the World Economic Forum teaming up to announce their own blue carbon credit framework at COP27 last year.
Crediting for blue carbon usually means protecting ecosystems like mangrove forests, seagrass beds, and salt marshes. It can also include restoring these ecosystems when they’ve been degraded or destroyed.
A recent paper published in the journal “Earth Science Reviews” titled “Remote Sensing for Effective Blue Carbon Accounting” reviewed the potential for new technology to improve the remote sensing of blue carbon ecosystems.
Carbon markets continue to grow, and billions of dollars will likely flow toward blue carbon projects. So how well can scientists even tell when ecosystems are sequestering CO2? And what is the promise of new technologies to improve those estimates?
Joining Radhika on this episode are Holly Jean Buck and Shannon Valley.
On This Episode
Shannon Valley
Resources
Article about Gold Standard Blue Carbon Project
Salesforce Blue Carbon initiative
Paper: Remote Sensing for Effective Blue Carbon Accounting
Bloomberg NEF Report on Potential Growth of Carbon Markets
Vox Article about Palm Oil Industry
WSJ Article about Indonesia Deforestation
Inside Climate News Article on Satellite Monitoring of Flood Zones
Report on 50 Years of Endangered Species Act
Connect with Nori
Join Nori’s Discord to hang out with other fans of the podcast and Nori
Nori’s other podcast Reversing Climate Change
Nori’s CDR meme twitter account
Full Transcript
Announcer: You’re listening to Carbon Removal Newsroom, a weekly show about current events in the world of carbon removal, from technology and innovation to policymaking and job growth. Brought to you by Nori, the carbon removal marketplace.
Radhika Moolgavkar: Well, everyone, welcome to the March 2nd, 2023 Carbon Removal Newsroom. Today we’re focusing on science. And I’m happy to welcome Holly Jean Buck, Assistant Professor of Environment and Sustainability at the University of Buffalo. Pinch hitting for Jane today. Hi, Holly.
Holly Jean Buck: Hello.
Radhika Moolgavkar: And then we have Shannon Valley, Paleo Oceanography and Marine Biogeochemistry Researcher, who is currently a AAAS Science and Technology Policy Fellow at USAID. Shannon, welcome.
Shannon Valley: Glad to be back.
Radhika Moolgavkar: And as always, Radhika Mugafkar, Head of Supply and Methodology here at NORI. So today we’re going to talk a little bit about blue carbon. Blue carbon has emerged as a popular climate solution with offset marketplaces at Vera and Gold Standard. And Salesforce and the World Economic Forum teaming up to announce their own blue carbon credit framework at COP27 last year. Blue carbon crediting usually means protecting ecosystems like mango forest, seagrass beds, and salt marshes. It can also include restoring these ecosystems when they’ve been degraded or destroyed. A recent paper published in the journal Earth Science Reviews titled Remote Sensing for Effective Blue Carbon Accounting reviewed the potential for new technology to improve the remote sensing of blue carbon ecosystems.
As carbon markets continue to grow and billions of dollars will likely flow towards blue carbon projects, this kind of innovation is important. And to tell scientists and the rest of the world how much these ecosystems are sequestering in carbon dioxide. So let’s get started to talk about the promise of these of these technologies and what these papers had to say. So, Holly. Beginning with some more broader context, can you tell us the importance of satellites overall in climate science?
Holly Jean Buck: Well, it’s huge. It’s almost hard to encapsulate. I mean, obviously, satellites have been really important in developing the physical science basis for understanding how our climate is changing in terms of understanding the atmosphere, the oceans, and land. Land use change, ice melt, all of this. And we have now 50 years worth of data on how our planet is changing from satellites. Then increasingly, I think they’re important too in adaptation in terms of understanding impacts from climate change and what we can do to address them. Thinking about understanding local heat islands or developing early warning systems for extreme events, helping to guide our adaptation practice.
And finally, More and more, they’re gaining importance in mitigation too. So monitoring and reducing emissions, both methane and CO2, as well as helping us do things like optimize shipping or other form of transport to reduce our emissions. So a big role across the portfolio of climate response.
Radhika Moolgavkar: Yeah, that’s very, very broad. So we will narrow it down a little bit right now and talk about this paper, which examined how remote sensing can help monitor blue carbon systems. So Shannon, what are the current methodologies for tracking these kinds of ecosystems?
Shannon Valley: In blue carbon ecosystems, the carbon storage is measured in two ways, in the plant biomass and then also in the soil carbon. The majority of blue carbon is stored in the soil, And then that can be measured or modeled down to different depths kind of depending on what kind of methodology you want to use. So then the paper describes a couple of different approaches for estimating the rate of change in carbon accumulation or loss. And so that’s either done by sampling from different land use types over time, so different coastal ecosystems.
Which you can sample directly if you have access. Or by kind of multiplying the carbon flux of a land use type versus that coastal area that’s involved. And that estimate can be like a global, regional, or site-specific calculation depending on the granularity of the data that you have. Of course, the higher the specificity or the higher the granularity you have, the higher the resource requirement is involved. And so that second type of not just directly measuring, but kind of taking a calculation based on area and our understanding of flux in a given type of ecosystem, that’s where remote sensing can really be a big help.
And so the paper then goes into describing a bunch of different advancements in remote sensing tech that’s available to scientists, land managers, and other folks now.
Radhika Moolgavkar: So can you give us, Shannon, an overview of sort of the different Advancements and also if you see any advantages to these new techniques and how they might differ from the past.
Shannon Valley: Yeah, so as Holly was saying, remote sensing has really changed and grown over time and so. If you’re talking specifically about satellites, that we go back to the 70s with Landsat data. Landsat has been kind of the workhorse of earth science or just earth observations and satellites. And that’s kind of, it’s great continuous data from that period, but a lot of that is lower resolution. Landsat’s still in operation, but we’ve had other satellites and other types of remote sensing. Um, tools that have come on board that can get you much higher resolution.
So that’s going from a difference of understanding just like the presence or absence of, um, a marsh environment and mangrove, um, or seagrasses to going to more into detail about kind of, um, Parsing out the structures and the heterogeneity of these systems. So you can tell even at higher resolution, you can look at things like leaf chlorophyll, canopy height of these environments, the health and the productivity and the maturity of these systems. So that’s something that for maybe greenhouse gas accounting at a national level is too detailed, but it’s great for monitoring stocks if you want to include them in the carbon market, for example.
They also talk about innovations to the analytical side of things, including machine learning, different techniques of combining data from both passive sensors and what they call active sensors, those that are using like LIDAR and radar, that help again kind of get to more of the differences in the structure and the densities of these different ecosystems.
Radhika Moolgavkar: So Holly, you know, a favorite topic of ours across all these shows is how do you estimate the amount of carbon dioxide stored? How trustworthy are these carbon dioxide estimates? Because obviously, well, maybe, I mean, obviously these are used for crediting systems and for net zero pledges. So how difficult is it to translate this data into estimates of carbon dioxide storage and how comfortable do you feel with these estimates?
Holly Jean Buck: So the short answer is it’s getting easier all the time because of machine learning to translate the data from the satellites into estimates. In terms of how trustworthy it is, I think it depends a lot on the ecosystem. And so, you know, we’re focused a little bit on the satellites, but there’s really three parts to this. There’s the satellites or the other sensors, there’s field measurements on the ground, and then there’s an algorithm that Makes the correspondences. So those algorithms are one part that’s really been improving a lot. Although the satellites have too.
I actually used to work for a remote sensing company back in 2005, 2006, 2007. And we had a modified Learjet that we were flying. With a radar that would send pulses down and information would bounce back. And you’d have to fly this plane overnight just in lines back and forth. And that’s fantastically expensive for the jet fuel and to pay me to sit in the back of this plane and press a button every 15 minutes. And now you have a satellite. You’d never do it that way now. Everything has become a lot cheaper.
So I know I sound like I’m An innovation hyper at this point, but it’s been really cool to see this field mature. And the thing is, you still have to think about the field measurements, though. That’s still like a thing that you want to get correct, and you’re going to need that for the whole thing to be trustworthy. And in terms of the ecosystems, like I think forest carbon is probably the most developed. And this paper talks a lot about like, Mangroves, they feel pretty good about, but like tidal marshes are more challenging.
I mean, there’s different things about like looking under the water and the light glint that bounces back and all these different factors that it doesn’t seem from my read of this paper that we’re quite there yet with regards to like seagrass meadows, for example.
Radhika Moolgavkar: Which dovetails nicely into the next question I was going to ask Shannon, which is, you know, We’re talking very generically about blue carbon ecosystems, but I’m sure there’s obviously detail in how much carbon can be stored within different of these various ecosystems. So generically, how much can a blue carbon ecosystem store within it? If you can like think about maybe just a mangrove or a seagrass or whatever one you’d want to choose and what impacts its ability to hold carbon dioxide?
Shannon Valley: One of the reasons why we’re so excited about blue carbon as a field, why it has its own kind of moniker is because these systems, because they’re partially, at least partially underwater, these are anoxic environments that allow for greater carbon storage kind of per unit area than like a land, like a typical land-based forest. But the rates of that carbon storage do vary. Some of that has to do with changes in like species distribution, kind of things with the like local hydrology that can impact the self sediment regime. There can be single seasonal or longer term changes that impact the productivity of the system.
I think the paper talks a little bit about kind of light resources and nutrient availability specifically in the case of seagrasses. And then human intervention, of course, is always a big one. So kind of impacting all of those different things that I already described. But then to speak to my parochial research interests, I think a lot about our interactions with marshes and how If we change those hydrologies of tidal marshes such that they go from kind of predominantly salt, water, estuarine environments to more fresher environments, then those can switch over from kind of net sequestering to net carbon emitting systems because there’s methane produced and that kind of changed an insect environment.
So a number of different things can affect that level of carbon storage.
Radhika Moolgavkar: All right. So now I want to pivot a little bit to the applied use of remote sensing. And obviously, as Holly was just alluding to, the space is maturing. It’s changing a lot so that there’s a growth of private Earth observation satellites, companies and small satellites. Shannon, I’m curious what you think of this trend and if you are positive, negative, neutral about it.
Shannon Valley: Mostly positive. I’m pretty excited about the availability of data to larger groups of people, especially if you can bring that price point down for different groups, whether it’s students, universities, companies that need it for various reasons, and for lower and middle income countries to have access to a lot of the data, but also the tech and the in-between parts that Holly was talking about before. It’s important to remember when you’re talking about low and middle income countries, you’re not just talking about like frontline fishers and farmers. You’re also talking about students and researchers and professionals who have built expertise or building expertise, but they may not always have expertise.
Kind of the technical resources locally to apply their skills to those issues that they’re trying to address. So lower costs, kind of smaller satellites and data can help kind of bring down those barriers of access to allow folks to get involved in that space from where they are and not have to contribute to brain drain and so on. Now, that’s all kind of dependent on that really being accessible and equitable, because everything, like you were saying, it’s not just small sets, but there’s a lot of companies that have a lot of data that are producing it for cost, and that is not always accessible to folks.
So I’d say super positive on small sets and cube sets as a trend in terms of data accessibility, but only if it’s really accessible to the broadest number of people possible.
Radhika Moolgavkar: Yeah, just by coincidence, today on the front page of the New York Times, there was a headline that said the Hubble telescope is being disrupted by these small satellites because they’re encroaching on its pictures, which, you know, talk about unintended consequences. I found that interesting.
Shannon Valley: Yeah, that’s not the kind of small stats I was thinking about, but yeah, I know what you mean.
Radhika Moolgavkar: Yeah, it’s just, you know, you never know.
Shannon Valley: There’s a lot of clutter out there. That’s true.
Radhika Moolgavkar: There’s a lot of clutter. So Holly, lots of recent articles have been finding that the palm oil industry, surprisingly, in Southeast Asia is not causing as much deforestation after decades of doing so. It’s mainly being discovered through satellite data. So what is the implication of the improved monitoring of potentially in destructive industries, you know, and is it in the same vein as what Shannon said was timeout, like more data is just good news for us overall.
Holly Jean Buck: More data is good. I think in the palm oil situation, I mean, they also had a pathway to kind of put pressure and take action once they had the data. So that’s the thing. Like we have these cool initiatives and platforms coming online, like Climate Trace, which uses satellites plus other sensors to give an accounting of emissions or Carbon Mapper, which is a nonprofit organization and program collaboration with Planet and the state of California and JPL and some other universities and NGOs. It’s really cool. They’ll be able to Pinpoint specific CO2 point source and methane emissions.
But I think sometimes in the tech world, we get so excited by the data that we don’t put enough attention on who’s going to be able to use this data to do what. There’s this tendency to mistake monitoring or amassing data for action. So as long as we’re clear that somebody has to be willing to take action on all this data, That’s my one cautionary note among the good news here.
Radhika Moolgavkar: Well, I mean, the flip side was there was some bad news about satellite data in the sense that countries who have less ability to access satellite data, their flooding estimates were way under. And the US has accurate estimates because it’s been using satellites. So how do So we think about that for climate adaptation for these developing countries. How do we get them better data? And are these technological advancements enough if we get them the data? Or do we need to do even more in terms of advancements to get them the right information?
Shannon, if that question made any sense, I turn it to you.
Shannon Valley: No, it definitely made sense. I think you know where I’m going to go with this too. Yeah, so actually the report was saying that it’s not the satellites, it’s some of the other tools, like Holly was saying. There’s aerial data that the U. S. had that was complementing some of our satellite data that allowed us to have more refined funding estimates. But then there’s this other satellite program, ISAT-2, that’s normally used For to understand changes in ice cover was then turned on over land and then it was found to be useful to provide estimates for potential flooding and sea level rise in areas that are less kind of well studied.
So like before I even read this article fully like my I just based on the title I was thinking like man I spend a lot of time thinking about data for climate mitigation but. For adaptation, too, it’s so important. And so just with the rising seas and increased variability and intensity of precipitation that we’re seeing in a lot of developing countries, like flooding mapping is some of the most vital information that countries can have, not just to avoid harm, but also to build for the future. And I don’t know how this study came together.
One of the great things about some of these larger kind of government satellite programs is that the data can be open for researchers to kind of jump in to what kind of applications they want to use it for. But I think we definitely need to see more intentionality about how lower and middle income countries are involved in some of the prioritization of research and studies like this or how they’re done. I think because like inequitable access to these data and how they’re used is a great way to just ensure that populations that are already ahead are going to stay ahead and countries and economies that are developing will continue to struggle.
I think lastly, so the report also talks about loss and damages, which is a term that I was unfamiliar with until recently, but it made a big reappearance at COP in Egypt this past year. I’m kind of talking loss and damages is referring to like the transfer of funds from historic high emitting countries to historic lower emitters to support their adaptation to climate change. I think that’s a really sticky conversation, but you cannot resolve it equitably at all if the information is not equally accessible and is not kind of held in, you know, by those countries that are experiencing the worst impacts.
I said last thing, last, last thing, because this is what happens when you get me in my wheelhouse, right? There’s a great project between NASA and USAID called SEVERE that works with different hubs of geospatial specialists in different parts of the world. And it is specifically looking at applying Earth observations for disaster management, for air quality, water planning, et cetera. It’s a great program. But it is a program kind of among a broader environment that’s not alone is going to kind of bridge the information gap that’s between countries like the U.
S. and then really growing but vulnerable populations like those in Nigeria and Pakistan and places like that.
Radhika Moolgavkar: I love it when you’re in your wheelhouse, Shannon. You always have so much interesting to add, but that was particularly interesting. And obviously USAID is your wheelhouse. So Holly, last question for you about this is, you know, I was just talking about unintended consequences with the Hubble and telescope and these small satellites. But when you think about the world of real-time satellite data, improved monitoring, are there other ramifications that are not positive that we should be thinking about from a carbon removal perspective? Or do you think generally this is a good development that will lead to better carbon removal.
Holly Jean Buck: Yeah, I think overall it’s really good. And just to echo some of what Shannon said, I think the need is just to make sure it’s accessible. And that’s not just like having an open data set, although that’s like a baseline action that we should do. It’s also thinking about The computing power in different countries to be able to process that data and do something with it. It’s making sure that the electrical grid is reliable enough that they can do that work without interruption. Some things that maybe we don’t always think about.
And also, obviously, the human capital, like training early career scientists in these places to help them do the work. Locally, so I think that there’s a huge gap there. So not a downside, just a gap that we need to step up and fill.
Shannon Valley: Yeah, sorry, I was just going to add to, I think the, also not a downside, but important to remember kind of caveats in the data that we get. I know that, for example, there is increasing usage of remote sensing for emissions and even point source emissions. But some of those algorithms are kind of based on a lot of machine learning and a lot of AI in other sectors. It’s based on training it over a certain kind of set. And so if you’re looking, for example, at like emissions from a certain type of land use change or a certain type of agricultural practice, if that set is trained kind of based in one area or one set of countries, that may not look the same for other places too.
So I think it’s just kind of a caveat and thing to be aware of when you’re kind of looking at those data to understand kind of what was that What does that model kind of trained on and kind of what could be missing there is an important thing to keep in mind and to continue research and expansion into in the future.
Radhika Moolgavkar: Yeah, I think that’s a good caveat for the CDR industry in general, right? Like models, satellite data, it all is so very ecosystem specific and land use specific and soil specific. Anyway. I will be ending with some good news today. So oftentimes within the environmental justice community, and I think within like society generally, there’s maybe mixed feelings about some of the different environmental regulations that have been put forward having both positive and negative impacts. I think of like NEPA as an example of maybe preventing housing or SEPA, preventing affordable housing in places.
However, This week I want to celebrate the 50th anniversary of the Endangered Species Act because it has been a relative success. It has saved 227 species from extinction and 110 have made what we call remarkable recoveries like the bald eagle, the American holigator, and the humpback whale. It hasn’t been as favorable to all types of species, but it’s always nice to celebrate the return of some iconic And I am happy that the Endangered Species Act was able to do that within the U. S. at least. With that, I am going to say thank you to Shannon.
As always, we are so happy you’re able to join us every month. And Holly, so appreciate you coming for the second time this month. We’ll talk to you next week as well. And we will see you next time.
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