👋 This is the final Carbon & Energy PodSnacks of 2021.
✨ Happy Holidays and see you in the new year!
Host: Gavin McCormick
Category: ☁️ Carbon Reduction
Podcast’s Essential Bites:
[1:22] “We've known for decades that emissions are rising in the atmosphere. So the famous Keeling Curve is based on what we can actually see from space. But what you can't easily see from space is how did they get there. It still boggles my mind, but even in the year 2021 in most countries and most sectors of the economy, our process for actually answering where all those emissions are coming from, is still to ask polluters, how much they polluted. Just […] hope nothing is missing in that inventory, and then add up all those numbers sometimes manually on paper. It's actually amazing that every single country in the world has agreed to this process. But it is such a stopgap solution. If we are really, really serious about stopping climate change, you can only manage what you can measure and we need to have more information. […] There are countries that haven't had an emissions inventory in 20 years.”
[2:52] “If we want to get really serious about fighting climate change, we need better tools. We need to have some way to get information in ideally real time, not years later, that doesn't rely on just asking the polluters, that has really detailed information about where those emissions came from, not just country level, that is open and transparent, so everybody knows they can trust it and ideally that's free, because we can't just have a situation where only those who can afford to pay know how much is being emitted.”
[3:24] “We have started to work as a cluster of small NGOs on training computer vision AI algorithms to look at hundreds of thousands of photos to recognize what a power plant looks like when it's polluting a certain amount of pollution from space. The reason we can do this is that there are so many free and public satellite images available now from sources like NASA […], it's possible actually to get photos every few days of every major power plant in the entire world. And so my organization WattTime and a number of other small NGOs have teamed up to build an artificial intelligence algorithm that can scan visual imagery every few days and look without asking the polluters to see how much they're polluting for every power plant in the world.”
[5:04] “We were starting to get pretty good results, measuring all the power plants in the world. But then Al Gore […] encouraged us to dream bigger. And so we got the challenge from him […] to not just think small in terms of power plant emissions, but to see if we could do all human emissions from all major sources on the planet and make that available and free to everyone. And […] with a whole lot of teaming up with other organizations, collectively, all of us have been able to do just that.”
[5:40] “A really exciting example of this is Transition Zero. So they are a UK based organization that is able to monitor the emissions of steel mills. And they can do that even when those emissions are invisible to the naked eye. Because one of the really important, interesting things about artificial intelligence is with different forms of signals from satellites, we can look at very specific chemical processes in different parts of the supply chain.”
[6:00] “You also have the ability to measure factory farms. So did you know even the United States EPA, in charge of regulating them, does not have a complete inventory of how many highly polluting factory farms are in the United States? But a startup named Synthetaic has been able to apply computer vision to build an inventory of them. And it is now scaling it up to expose every factory farm worldwide.
[6:20] “RMI is monitoring oil and gas emissions from production and refining. Blue Sky Analytics based in India is monitoring crop fires and forest fires. […] Johns Hopkins University is modeling all the ground transportation and looking at the road networks worldwide. Each one of our organizations has learned to specialize in one or two forms of particular emissions, but we're sharing them all in a giant database known as Climate Trace.”
[6:51] “It used to be the case that only rich countries can afford to look at their emissions in great detail. [With Climate Trace] we are talking about properly global systems that are available and free for everyone. The reason of course we can do this is because satellites have come down so much in cost. There are now literally thousands of eyes in the sky up above us. And many of them are actually free and open to anyone to use that information. But you know what’s come down in recent years even more in cost and satellites, big data, and AI. […] We now live in a world where if a certain meme is trending on Twitter, there are automated marketing algorithms that know that worldwide in minutes. We suspect there are stock market algorithms that know it in seconds. […] So we actually exist as a society, spending more resources on monitoring funny cat video views on the internet than a civilization threatening crisis.”
[8:25] “We were approached early in the project by a former climate negotiator, who told us that […] the heart of the Paris Agreement is supposed to be that the countries are able to see what everybody else is doing. They can learn to trust each other. And that's why they're willing to hold hands and leap together. But the problem is, there's a lot of self reporting going on and a lot of countries don't have the resources to do this very expensive, old form of monitoring. And so what we've tried to prioritize for Climate Trace Version 1 [which was] releas[ed] […] [in] September 21, a version […] that is free and available to everybody, that has the emissions for every country, every sector, and every year on the planet.”
[9:09] “So far, one of the things we've been able to measure is what does this compare to what countries have been reporting? So we can't say that our methods are completely perfect yet. But one of the questions we get is should countries trust each other? And one of the most surprising things I think I've learned from this project is that I think the answer is yes. I mean, we've definitely found some missing emissions. There's a few industries that we need to go have some hard conversations with. But by and large, what we've been really struck by is the vast majority of countries appear to have been able to get away with murder, but negotiating with each other in complete good faith. But I think it'd be a waste of AI if we stopped there.”
[9:45] “For our next step, for Climate Trace Version 2, what we're working on is making every single emitting asset in the world visible. And what that's going to mean is not just national totals, but giving tools. I've spoken with governments that are interested in knowing where in our economies the emissions are coming from. I've spoken with companies who'd like to green their supply chains, but they have to know which factories are cleaner than which other factories. I've spoken with asset managers who are investing $43 trillion in net zero. But to actually achieve their goals, they need a way to manage and measure, are those emissions reductions really happening? So I think it's pretty exciting that we can now ensure that if anybody in the world is trying to hide emissions, they can just forget about it. Those days are over. But the part that really excites me the most is giving tools to others in the climate fight to get the job done faster.”
Rating: ⚡⚡⚡⚡⚡
🎙️ Full Episode: Apple | Spotify
🕰️ 11 min | 🗓️ 12/07/2021
✅ Time saved: 9 min
Additional Links:
Video: TED Climate - “Tracking the Whole World's Carbon Emissions”
