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Rob checks in with Lauri Myllyvirta, an expert on China’s clean energy economy, on the country’s emissions goals and how the Iran War factors in.

The new draft of China’s five year plan is here, and the news isn’t all good for climate advocates. Although China vows to expand its gigantic “clean energy bases” in the plan, it has actually walked back some of its biggest climate goals since 2021. The new plan also contains a mysterious — and politically convenient — change to one of its most important emissions estimates.
On this episode of Shift Key, Rob is joined by Lauri Myllyvirta, the lead analyst and co-founder of the Centre for Research on Energy and Clean Air and one of the world’s top experts on Chinese emissions outside China. Rob and Lauri discuss whether China is creating a new kind of energy hegemony, what really drives the country’s energy strategy, and how the new war in Iran could affect its plans.
Shift Key is hosted by Robinson Meyer, the founding executive editor of Heatmap News.
Subscribe to “Shift Key” and find this episode on Apple Podcasts, Spotify, Amazon, or wherever you get your podcasts.
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Here is an excerpt from their conversation:
Robinson Meyer: Let’s get into this question about the Chinese emissions target. So China, I think, has a reputation internationally for always meeting its emission targets, and for setting emissions targets that it can hit. And when it’s sometimes conservative in its targets, there’s a sense that, okay, well, it is being conservative, but that’s because it’s very focused on setting targets that it can hit. But it sounds like in the run up to this report, it became clear that China was not going to hit its 2030 target under the Paris Agreement. And so, as you write, it basically revised its own accounting metric. Can you just describe what happened there and how it was able to change its accounting midstream, basically?
Lauri Myllyvirta: I’ll start with what is known. China has been reporting on reductions in carbon intensity. Carbon intensity is the amount of CO2 per unit of GDP. And so if emissions stay flat, GDP goes up by 5%, carbon intensity falls by a bit less than 5% in a year.
Meyer: My understanding — and maybe this is wrong — is that up until 2030, the bulk of its emissions targets under the Paris Agreement, its nationally determined contributions, are phrased in the terms of carbon intensity, not in the terms of like, here’s what our national emissions target is going to be. They were primarily talking about, our big target is reducing the carbon intensity of our economy, rather than hitting some kind of tons per year goal that the U.S. and Europe and a lot of other countries adopted.
Myllyvirta: For sure. So for 2020 and 2030, China has had a few different targets, but the one that is most closely related to emissions — and in that sense, the cornerstone target — is carbon intensity. And so until 2020, China was overachieving that target. But then during the COVID and Zero COVID period, China went through a period of very energy-intensive and carbon-intensive growth with the service industries and other less energy-intensive industries were obviously not doing great. So that meant that carbon intensity started falling much more slowly. CO2 emissions grew faster during that period, at least according to the numbers that China had reported.
So they had been reporting carbon intensity reductions every year. And if you take the numbers from 2021 to 2025, they add up to a reduction of about 12% in China’s carbon intensity over that five-year period. And the target was 18% — that’s what they needed to get on track to, or stay on track to the 2030 carbon intensity target, and so that means that if you have a shortfall of six percentage points during these five years, then the target for the next five years becomes very demanding.
But so then along comes this new five-year plan, and it says that we achieved a reduction of 17.7% instead of the 12-point-something percent. So that is a huge revision. If you rephrase that in emission terms, it means that earlier China had said that their emissions over this five year period had increased about 13% in absolute terms. And now they say the increase was only 6%. So half of the emission growth disappeared. So this is what we know for a fact. The less clear part is what is this revision based on?
You can find a full transcript of the episode here.
Mentioned:
Previously on Shift Key: Have China’s Emissions Already Peaked?
China’s 15th Five-Year Plan — Implications for climate and energy transition, by Lauri Myllyvirta and Belinda Schäpe
China Can’t Decide If It Wants to Be the World’s First ‘Electrostate’
This episode of Shift Key is sponsored by …
Accelerate your clean energy career with Yale’s online certificate programs. Explore the 10-month Financing and Deploying Clean Energy program or the 5-month Clean and Equitable Energy Development program. Use referral code HeatMap26 and get your application in by the priority deadline for $500 off tuition to one of Yale’s online certificate programs in clean energy. Learn more at cbey.yale.edu/online-learning-opportunities.
Music for Shift Key is by Adam Kromelow.
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The data center boom is everywhere you look in U.S. economic and emissions data.
This is an edition of Heatmap Daily, an evening review of the day’s news written by our executive editor. Sign up for it here.
It isn’t exactly a new thought, but I’ve been struck recently by how many trends in America’s economic and environmental data are fundamentally about the data center boom and the return of electricity demand:
First, the Energy Information Administration reported this week that U.S. emissions grew by more than 2% last year, driven by surging electricity demand and an increase in coal-fired generation. What caused that higher power demand? New factories and data centers — as well as record summertime cooling demand.
Second, many of the new factories driving that higher power demand are themselves producing goods that are … let’s say … data center-adjacent. There are the enormous new semiconductor fabs, of course. But Ford and General Motors have also set up new production lines (or repurposed old ones) to manufacture grid-scale batteries to meet power demand.
Third, take a look at the recent U.S. spending on private non-residential construction — in other words, everything American companies are building that is not houses, condos, or apartments.
The construction industry’s spent almost $60 billion on data centers over the past year, which is more than it spent on all other office buildings combined (and more than it spent building warehouses, too). Just a handful of categories — data centers, power plants, electricity infrastructure, and certain kinds of electronics manufacturing — now make up a third of all U.S. private non-residential construction investment. They’ve never made up such a large share of construction spending since data collection began in 2014.
As The New York Times recently noted, the American economy is unusually dependent on the American stock market right now — and the stock market is unusually dependent on artificial intelligence. This week, investors started to balk at the enormous spending hyperscalers are planning to keep building out the AI boom; Alphabet’s shares dropped 8% this week after it boosted its planned 2026 capital expenditure and signaled 2027 will be even bigger. If the data center boom started to slow down in earnest, then more than just that budget will change.
Speaking of which, my colleague Emily Pontecorvo wrote earlier this week about how many businesses are struggling to even estimate their carbon emissions from artificial intelligence. The carbon accounting startup Watershed recently unveiled a new formula to help companies get a sense of their AI-related emissions.
But even that formula is still limited by the amount of data hyperscalers publish — and they don’t publish that much. Google, for instance, is the only AI company that has (laudably) provided estimates of its emissions on a per-prompt basis. Yet no company has published its per-token emissions, or how emissions sync up with particular models or regions.
So Emily asked Google: Why aren’t you — or any other model provider — disclosing this kind of data yet?
The tech company didn’t get back to us until after we’d published Emily’s story. But its response was interesting enough that I wanted to quote some of it here.
The problem is “industry consensus,” Cooper Elsworth, a Google spokesperson, told us. “There is currently very little consensus on how to comprehensively and fairly measure the serving environmental impact of generative AI (such as text generation),” he wrote. “Without standardized, ‘apples-to-apples’ frameworks, it is difficult to compare different providers accurately.”
That’s partly because energy use — and emissions data — can vary from site to site and depend on “custom-built hardware, software compilers, and advanced inference techniques.” And he claimed Google doesn’t always have the measurement hardware in place to provide such specific estimates: “Providing precise, repeatable data requires highly advanced measurement infrastructure,” he said. “For example, software-based energy monitoring tools often suffer from sampling biases. For our study, we had to step away from top-down averages and directly measure actual energy at the physical power supply unit (PSU) level across our deployed fleet. Not all providers have the telemetry or data sets required to benchmark their operations at this level of granularity.”
Read Emily’s story to understand the other reasons why estimating — or even “guesstimating” — AI-related carbon emissions is so challenging.
A conversation with Emma Uridge of the Kansas Health Institute.
This week’s conversation is with Emma Uridge, analyst with the Kansas Health Institute. Uridge spent copious hours analyzing state and local laws on data center development to best understand how policymakers are responding to the potential environmental public health impacts of large AI infrastructure, including power and water. The report, which came out this week, also goes in depth into those health impacts. I reached out to her to discuss what she sees as must-watch territory for our readers on this emerging policy arena.
Our conversation was lightly edited for clarity.
What is actually being done on policy when it comes to data centers — beyond moratoria of course?
So first I’d like to just talk about the point of moratoria. It’s helpful to talk about how these policies emerge in the first place. One area where moratoria are helpful is when a data center is proposed but the county has no approach for how they’d like to potentially regulate them. That’s temporary, most of the time. It lets local governments conduct research on the various impacts and also negotiate community benefits, ones that can mitigate any potential negative impacts — like Lancaster Pennsylvania, which instituted a community benefit agreement that maximized the potential benefits of development while mitigating what large data centers can do. That agreement looked at capping municipal water use at 20,000 gallons per day and requiring 100% clean energy. It had financial penalties for non-compliance. The company also committed $20 million to their local economic development and clean energy fund. There are ways to negotiate with developers.
We also see amendments to existing zoning. Data center proposals are increasingly popping up in rural areas, many of which are unzoned, so there’s no way a county can negotiate unless there’s a moratorium in place.
Other policy solutions include different performance standards or requiring on-site renewable energy, like what Jefferson County, Missouri, looked at. Also setback requirements, mandatory noise buffers, ending by-right zoning.
Where are local governments getting ideas for regulating data centers?
A lot of the technical information comes from developers. That can in cases be seen as a biased source of information. I wouldn’t say there’s a dedicated group providing assistance to local governments when a project is proposed — which is a similar story to wind industry development, where we have only a handful of consultants who provide technical advice. It can be really helpful to get a multi-disciplinary approach to hearing information. It can be helpful to have the utility commission, public health folks, those in academia, as well as the developer.
As of right now, especially in rural areas, local governments have a hard task of balancing pushback while getting the most accurate, evidence-based, neutral information to make decisions. That balance can be contentious.
What is the federal government doing on data center policy? How is the Trump administration approaching it?
A few things there. In the early days, the drive was for AI expansion and to be competitive with foreign adversaries. Now due to the amount of public pushback in red and blue localities and a more cautious approach.
I’m not seeing a lot of actual policy movement at this time.
I know the EPA is looking at the chemicals used in cooling data centers because when that water is cycled through the system, some of it is discharged into the water system, so they’re looking at the Toxic Substances and Control Act for monitoring that.
How much of an impact does this minimal federal role have on industry behavior?
Y’know, this isn’t specific to data centers. This is true for all kinds of large-scale development: there’s a need to require some sort of federal monitoring and regulation.
That’s where I see an emerging role for public health. At the federal level, there could be policy movement towards requiring some sort of environmental monitoring at data centers to make sure they’re operating responsibility. Looking at specific water use relative to water availability and what happens when there’s a time of severe, persistent drought. With air quality too — we’ve seen areas where the grid isn’t as reliable so their diesel generators are kicking on more and affecting air quality for residents.
We’re just not seeing all of that right now. We need corporate disclosure.
What do you see as the most important public health impacts from data center development?
It varies by localities. The most discussed obviously is water usage. One thing I’d note about my conversations with folks enthusiastic around emerging tech is, there are still questions that need to be asked about the capacity of localities to support a data center. Like a small town in Kansas may only be using 40% of their water for their utility needs. If a data center came online, how much of that water goes to the data center?
One area underexplored within the public health discipline is energy poverty and energy security. The ability of a household to meet the needs of everything energy provides in our lives. It’s known we have an aging electric grid but we’re not talking enough about large-scale blackouts when the grid is not sufficient to support some of these new data centers.
Plus more of the week’s big development fights.
1. Laramie County, Wyoming — Meta is fighting the fine it received in the Cheyenne data center water pollution controversy, and the conflict between the tech giant and the city’s small board of public utilities is continuing to spill out into the public.
2. Niagara County, New York — This county just rejected a solar project’s highway work permits in a show of retaliation against the state’s Office of Renewable Energy Siting.
3. Barron County, Wisconsin — The anti-solar protest is the new campaign stop in deep red Wisconsin.
4. Chesapeake, Virginia — A large battery storage project on the Virginia coastline is on the rocks amidst rampant local opposition.
5. Lewis County, West Virginia — West Virginia is now a key battleground in the fight over transmission, as a line spanning all of West Virginia and Maryland — and cutting through Data Center Alley in Virginia — causes compounding consternation.