“We’re starting to see a globally consistent system to track [carbon] emission changes take shape,” says atmospheric scientist John Lin.

Faculty in the University of Utah's Department of Atmospheric Sciences, Lin is co-author of a paper in the journal Environmental Research Letters about a new satellite-based system for measuring CO₂ emissions in support of global collective climate mitigation actions. As nations and cities continue to state their intentions to decarbonize for the purpose of becoming, in their activities, carbon-neutral, “we want to be able to see it happen from space.” 

Now we have a system to do so. 

That system is the culmination from standing on the shoulders of previous data scientists. It’s a story about how data is collected, interpreted and expanded through new technologies. It’s also about how this recursive process — now turbocharged with the advent of machine learning and AI — creates a space for potential application, innovation and policy that can change our world for the better, including mitigating carbon emissions that are warming our earth at a startling and deleterious rate.

But before any attempt can be made to save the planet, scientists have to secure a consistent measurement framework to better understand what’s happening as well as where it’s happening and how much.

The Backstory

John Lin

The backstory to this tale first begins in the Pacific Ocean. Tracking carbon emissions dates back decades to a single site in Hawai’i where, on a largely inactive volcano on the Big Island, instruments measured carbon dioxide in the atmosphere. At a high elevation, the site was very good at characterizing broad scale changes in carbon dioxide, globally, a “poster child for climate change because over time,” explains Lin who is also associate director of the Wilkes Center for Climate Science and Policy, “we know that from these Hawai’i  measurements, CO₂ has this distinct cycle, seasonally, but then this upward trend due to all of us burning fossil fuels.”

Human-caused carbon emissions are not only leading to CO₂ buildup everywhere in the atmosphere but the issue is widespread in public discourse. Whether it’s on the micro level of mitigating one’s personal “carbon footprint” by taking the bus, or on the meta level of international initiatives like the Kyoto Accords or the United Nations-brokered Paris Agreement, the effects of carbon emissions are on everyone’s mind. A cascade of cities and whole nations have established goals for mitigating emissions, but their estimates of carbon emissions have been relying on data that are inconsistent and sometimes missing altogether in parts of the world. 

That cities have singly established and even accelerated their carbon-neutral goals is a good thing, considering that over 70 percent of human-emitted CO₂ into the atmosphere stems from cities around the globe.

Tracking progress toward city-scale emissions reduction targets is essential by providing “actionable information for policy makers,” the paper states. This while the authors acknowledge that earlier measurements and claims from municipal entities are based on “self-reported emissions inventories,” whose methodology and input data often differ from one another. These practices hamper “understanding of changes in both city-scale emissions and the global summation of urban emissions mitigation actions.”

Orbiting Carbon Observatory

This is where outer space in general comes into play and, in particular, the Orbiting Carbon Observatory (OCO). The NASA mission is designed to make space-based observations of carbon dioxide in Earth’s atmosphere to better understand the characteristics of climate change. After a literal “failure to launch” in 2009, NASA successfully placed a satellite (OCO2) in 2014 with equipment measuring CO₂ emissions from space. Satellite-transmitted data promised to be an independent way to calculate, globally, emissions from cities. Not surprisingly, it has taken a while to learn how to use the data. In 2020 a graduate student in Lin’s research group, Dien Wu, developing early methods, did exactly that, looking comprehensively at a total of twenty cities around the world.

Based on essentially the same data set used by Lin and Wilmot in their current paper, but with fewer years, Wu was able to get estimates of the amounts of human emitted CO₂ from OCO2 satellite transmissions. Separating out what carbon human activity is emitting to the atmosphere versus those from urban vegetation has now been determined through an expansion of the analyses over the additional years by Lin’s team of researchers, including a later graduate student by the name of Kai Wilmot, co-author of the current study.

In this round, four times as many urban areas as Wu studied and distributed over six continents, have now been assessed. This plant/human conundrum is further complicated by vegetation outside the city which has very different characteristics from vegetation inside the city. The difference creates patterns of CO₂  that have to be taken out to distill the human component.

Strangely beautiful animations

Kai Wilmot

In short, Lin and company’s findings, published in Environmental Research Letters, represents a new capacity based on recent developments in modeling. And the animations of the assembled and interpreted satellite CO₂ data delivered by the team are startling, even strangely beautiful. In one chart the left side displays latitude vs CO₂. “This narrow swath,” explains Lin, indicates “each time … [the satellite] orbits. There's this narrow slice of data that becomes available.”

Using that data, he continues, “the NASA scientists can construct this nice animation of CO₂ change in each latitude band over time.” Lin points to what he calls “ridges and valleys” on the the chart that represent the seasonal cycle, and he personifies the entire Earth as if it is “breathing in the carbon dioxide through photosynthesis during the summer growing season and then releasing it in the winter. They have these very sharp ridges — high CO₂, low CO₂, higher CO₂ [the breaths] — but overall, the rug is going up, because we're emitting carbon dioxide into the atmosphere.”

Here, researchers are only looking at a small fraction of data points, the ones that intersect the targeted cities. They then do a more detailed look at whether they’re seeing a signal or not and whether they’re getting enough data.

“Personally,” says Wilmot, “I think the particularly neat aspect of this work is the capacity for global application. Leveraging satellite data and atmospheric modeling, we are able to gain some insight into urban emissions at cities around the world. We can see interactions between these emissions and socioeconomic factors, and we can identify large changes in emissions over time.”

The possibilities of creating more rigorous models, and more revealing data about how much cities emit carbon to the atmosphere are tantalizing. And so are the findings of the research. “This kind of information can be used by cities and the UN process,” Lin says. “But I’m pretty sure what they want is something more dynamic through time, how these emissions evolve. And also, probably more frequent updates.” As it was in this study, researchers had to aggregate multiple years of data to get enough points for each city. “So the challenge, I think, is to be able to track more dynamically these emissions over time.”