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There is no dearth of advice on the internet about how to lower your personal carbon emissions, but if we had found any of it completely satisfying, we wouldn’t have embarked on this project in the first place.
Our goal with Decarbonize Your Life is to draw your attention to two things — the relative emissions benefits of different actions, as well as the relative structural benefits. (You’ll find everything you need to know about the project here.) For the first, we needed some help. So we shared our vision with WattTime, a nonprofit that builds data-driven tools to help people, companies, and policymakers figure out how to reduce emissions, and lucky for us, they were excited to support the project.
“So many people out there feel helpless when it comes to addressing the climate crisis, but we believe that anyone, anywhere should have the tools and information they need to make a difference,” Henry Richardson, a senior analyst at WattTime, told me as we were wrapping up this project. “So we love the idea of helping average consumers understand which actions actually available to them can meaningfully contribute to reducing climate pollution. We want to help people prioritize those higher-impact activities that can mitigate climate change faster.”
WattTime’s claim to fame is building an API that calculates the emissions impact of using the grid at a given time and place. Users can then shift their energy consumption to times when the grid is cleaner or to build renewables in places where they will reduce emissions the most.
In an ideal world, we would have taken a similar time- and place-based approach in calculating the emissions savings of each energy-related action on our list. Switching to an EV if you live somewhere with very clean power will reduce emissions more than if you live somewhere with lots of coal plants, and likewise, getting rooftop solar if you live somewhere with coal-fired electricity is more effective than in areas with a cleaner grid. But when we started to game it out, we realized that level of exactitude would be, if not exactly impossible, certainly insanity-inducing.
Instead, WattTime helped us calculate the effect of each action if it was undertaken by an “average American household” — that is, one that consumes an average amount of electricity per year, drives an average number of miles in an average car per year, uses an average amount of energy for space heating, et cetera. WattTime also pulled data from publicly available sources like the Environmental Protection Agency, the Department of Energy, and the Energy Information Administration, to estimate the baseline emissions and savings of a given action. We ultimately made two calculations for each action to account for two different ways of estimating the emissions from using the electric grid:
While the first method gives us a picture of how much good each action can do in an immediate sense, the second gives us a picture of how much good it can do over time. For example, using the first method, buying clean power came out on top, with rooftop solar offering the potential to cut CO2 by about 5.7 metric tons per year, while switching to an electric vehicle would cut about 3 metric tons per year. But using the second method, car-related actions won out, showing EVs cutting CO2 by 4.6 metric tons per year, and rooftop solar cutting 1.4 metric tons per year. The truth is probably somewhere in the middle.
To calculate the emissions savings from dietary changes and food waste management, we turned to two more partners: HowGood, a data platform for food system lifecycle analysis, and ReFED, which collects similar data for food waste. As with energy, we used federal data from the U.S. Department of Agriculture to estimate the average American diet and ReFED’s estimates for the average American food waste mix (though note that those are for an individual, not for a household). From there, WattTime helped us determine that, for instance, just by replacing the beef in your diet with chicken, you could save nearly 2.5 metric tons of emissions each year — almost as much as you could save by going vegan.
Because we used averages and sought to simplify our list with actions like “electrify your space heating system,” rather than estimating the impact of every permutation like “switch from a propane furnace in Colorado with X efficiency to a cold climate heat pump with Y efficiency,” our estimates of emissions reductions are rough approximations and not reflective of real-world scenarios.
You’ll see that while these calculations certainly informed our ranking, they were not the sole metric we used to arrange this list. A quantitative analysis alone could not answer our question about the most “high-leverage” actions, so we used our reporting and expertise as climate journalists to fill in that last, crucial gap. Car-related actions and rooftop solar were neck-and-neck by the numbers, but we are confident that getting an EV (if you need to have a car) is more unambiguously necessary for the energy transition than getting rooftop solar. Similarly, while eating less meat can hugely reduce the carbon tied to an individual’s diet, the ripple effect it has on agricultural carbon emissions is less direct and harder to parse than the effect you can have by electrifying all your appliances and shutting down your natural gas account.
Getting an EV:
WattTime — 2.9 mtCO2/yr
Cambium — 4.5 mtCO2/yr
Structural benefits: Destroying demand for oil; increasing demand for charging stations; improving local air quality and chipping away at the social license for operating an internal combustion engine.
Getting rooftop solar:
WattTime — 5.7 mtCO2/yr
Cambium — 1.4 mtCO2/yr
Structural benefits: Get clean energy on the grid faster than utility-scale projects; influence neighbors; reduce electric demand in your neighborhood; reduce strain on grid if paired with a battery and part of a “virtual power plant”
Air-sealing and insulation:
WattTime — 1.2 mtCO2/yr
Structural benefits: Reduce strain on grid and need for grid investment; level out electricity demand to avoid the need to activate dirty “peaker” gas plants; prepare your home for cheaper, more even, and efficient heating and cooling
Switching to a heat pump for space heating:
WattTime — 1.4 mtCO2/yr
Cambium — 1.6 mtCO2/yr
Switching from a gas stove to an induction stove:
WattTime — Roughly even
Cambium — 0.1 mtCO/yr
Switching to a heat pump for water heating:
WattTime — 0.8 mtCO2/yr
Cambium — 1.6 mtCO2/yr
Switching from a natural gas-powered dryer to a heat pump dryer:
WattTime — Roughly even
Cambium — 0.1 mtCO/yr
Structural benefits: Increase demand for and reduce price of electric and efficient appliances; build a case for policies that wind down fossil fuel use; if fully electrifying, sends signal to downsize gas system.
Getting rid of your car:
WattTime — 5.17 mtCO/yr
Structural benefits: Supporting public transit and bike lanes, enabling others to use their cars less, too.
Switching from an omnivorous to a vegetarian diet:
WattTime and HowGood — 2.8 mtCO2/yr
Switching from an omnivorous to a vegan diet:
WattTime and HowGood — 2.9 mtCO2/yr
Replacing the beef in an omnivorous diet with chicken:
WattTime and HowGood — 2.5 mtCO2/yr
Structural benefits: Reduce demand for high-emitting food products, which has the double-pump benefit of reducing the amount of land required to cultivate high-emitting products; if replacing beef with chicken, increase demand for more carbon-efficient proteins; add to the business case for developing efficient plant-based proteins.
Cutting food waste in half:
WattTime and ReFED — more than 0.1 mtCO2/yr
Structural benefits: Reduce demand across the food system; send less food waste to landfill, which helps reduce methane emissions.
Composting all food waste:
WattTime and ReFED — 0.03 mtCO2/yr
Structural benefits: Encourages the build-out of municipal composting programs; encourages responsible farming practices by lowering the cost of compost; reduces demand for nitrogen-based fertilizer.
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SoftBank’s error and Nvidia’s scandal suggest data centers may have already peaked as an economic and energy trend.
This is Heatmap Daily, a weekday digest written by our executive editor. Subscribe here.
Covering energy and climate change sometimes means seeing certain stories in a different light than others. And a particularly vivid hue illuminated The Wall Street Journal’s report today that the Japanese conglomerate SoftBank Group is taking a $3.7 billion loss on several gigawatts’ worth of natural gas turbines.
For the Journal, the big news is that SoftBank and its billionaire founder, Masayoshi Son, are failing to capitalize on the artificial intelligence boom. But at Heatmap, we’re thinking about the turbines.
The data center boom and the return of electricity load growth has depleted the world’s supply of natural gas turbines. SoftBank had purchased reservations for about 13 gigawatts of turbines, according to the Journal. That’s a staggering amount of electricity — it could meet New York City’s maximum power draw on the hottest part of a summer’s day. The conglomerate now seems set to dump reservations for about four gigawatts’ worth. Keeping a reservation, it turns out, really is harder than making it.
Most of those rotors were reportedly from GE Vernova, one of the world’s largest producers of gas turbines. GE Vernova’s order list for gas turbines has been filled for nearly two years and the waiting list now stretches into 2031. That has led data center developers, hungry to get power as soon as possible, to reach for ever dirtier forms of electricity generation, including diesel generators and even old jet engines.
On that front, SoftBank’s failure to sell the turbines to a higher bidder suggests (albeit weakly) that demand for energy-producing assets might not be as strong as the AI boom’s backers once thought. SoftBank was already set to send about 9 gigawatts of turbines to the enormous Trump-backed OpenAI data center in Pike County, Ohio. The roughly remaining four gigawatts will be released back their manufacturers. (One thing this news can’t quite tell us, alas, is what type of turbine set-up will be used in the Pike County facility, which will be the world’s largest gas-fired power plant if it is build to completion. Recent public filings have suggested the facility isn’t planning on using any turbines in the more efficient combined-cycle configuration, which would mean the plant’s carbon intensity will be worse than most other new natural gas plants. But we’d love to hear any tips on this front.)
To zoom out for a second, I’m struck by how the AI bubble has been replaced by an AI muddle. As I wrote this, news emerged that Nvidia is preparing to fire its CEO, Jensen Huang, for his affair with a Chinese woman who is alleged to be a spy. (He had at least one more affair with another Nvidia executive, according to The New York Times.) Under Huang’s leadership, Nvidia has invested in a sprawling and sometimes circular network of energy-related companies, including Emerald AI, a startup that helps data centers flex their electricity consumption, and Redwood Materials, a battery recycler and producer led by the former Tesla executive J.B. Straubel. Huang has used Nvidia’s enormous balance sheet to buy down the risk of other AI and AI-related companies, propelling the overall AI trade to become the biggest story in American markets.
Now that balance sheet is in peril: Nvidia’s stock is already down 11% over the past five days, and it has fallen another 8% in after-hours trading since news broke of Huang’s ouster. If the chip designer’s financial network began to fray — or even if the next CEO had a lower risk appetite than Huang — then its demise could impact a much larger set of firms.
Even before the Huang scandal broke, companies at the center of the AI trade were showing signs of weakness. Alphabet, Meta, and Microsoft are all down on the month. Nvidia was already lagging by about 10% on the month before its hebdomas horribilis began, too. The memory and chip makers Micron and Applied Materials are both down more than 25% in about the same period, and GE Vernova and Oklo have fallen nearly 20%. Although the data center company Coreweave rebounded on an earnings beat today, it’s still down 24% on the month and nearly 50% since May.
The market rout isn’t total — Anthropic seems likely to enjoy one of the largest IPOs ever in the next week (although perhaps not with quite as large a valuation as its investors once imagined). And the underlying technology of AI seems to be getting worryingly better all the time. But even though the politics of data centers and AI seem set to dominate the new Washington, I’m wondering if data centers as a mainstream economic trend might have already peaked. Americans voted for a more subdued AI boom in the midterms. Now it seems like they might get it ahead of schedule.
Lunar Energy’s latest AI-powered system aims to integrate EVs into the automated demand response mix.
In theory, it’s straightforward to assemble the smart energy home: Solar panels, home backup batteries, and electric vehicles, plus smart thermostats, heat pumps, and water heaters — all the individual pieces can be had for the homeowner who can afford the up-front cost. The challenge is getting all those pieces to talk to one another.
Bay Area-based Lunar Energy is one of the tech firms that’s been trying to crack this problem. Today, it announced an upgraded version of its artificial intelligence-powered home energy control system, which not only integrates all those separate systems but also responds tactically to energy markets. CEO Kunal Girotra told me Lunar AI saves its users money by monitoring their home 24/7 and making decisions to charge, not to charge, or discharge so that they save the most money.
“Utilities are all moving to almost-real-time changes of rates,” he said. “You need software to handle that for you. I think that the race is on for who has the best AI machine learning algorithms to save the most amount of money. And so far, we seem to have a head start.”
Lunar’s first-generation system focused on generation, storage, and control. In other words, it connected elements like a home’s rooftop solar panels with the backup battery the residents might keep in the garage, using the AI to decide when to meet the home’s real-time energy needs with solar versus grid energy versus stored power. What it didn’t have was the ability to work with electric vehicles to manage charging and use the car’s battery as a bonus source of energy.
To fix this, Lunar has built its own bidirectional EV charger — one that can charge up the battery or discharge the car’s battery for a secondary use, like backing up the home’s power supply. Girotra, formerly the head of Tesla Energy, told me the problem with that functionality to this point has been the connection point between the car and the home electrical system. Carmakers and other companies in the space didn’t have the deep experience with electrical certifications to make the process seamless, he tells me. That led to setups like the original Ford Charge Station Pro, which required several different wall-mounted electrical boxes to connect the F-150 Lightning EV to the home.
Lunar’s charger is built to connect to its customers’ existing home Lunar energy system, which includes a microgrid interconnect device they call Lunar Bridge that islands the home in case of a power outage on the grid. In that way, the power stored in the EV battery is ready to back up the home in case of a blackout without any additional work — or to be optimized as part of a fully smart home that’s making money as part of a virtual power plant.
The company’s setup allows for another fun feature: “slow” charging that’s not slow at all, but actually two or three times as fast as the Level 2 charging most EV owners use to recharge their batteries overnight. Electric cars in the U.S. can typically take on only about 11 kilowatts of AC power from one’s home because of the limitations of their on-board hardware. Because Lunar’s system is fully DC, however, Girotra said the company decided to build a DC home charger, one that — like a Tesla Supercharger or other DC fast chargers out in the world — isn’t limited by that power cap. Lunar said it could use a combination of power from the grid, home solar, or home batteries to charge an EV at up to 25 kilowatts. That’s enough to recharge an EV in three to four hours rather than six to eight.
“If the standards get high, and if everybody sees cars can get charged in three hours, then all of a sudden people are like, ‘Wow, this is how I want it,’” he said. “Especially for 25% of the users who are like me, who always are running low on charge and they don’t mind a boost every now and then.”
Some of the other improvements in the second-gen system are more incremental. An inverter that’s 40% more powerful helps Lunar get its system up to enterprise scale. That’s crucial, as the world moves toward a place where more homes and businesses employ battery backup systems. Lunar’s new batteries come in modular 5 kilowatt-hour blocks ranging from 10 kilowatt-hours to 30 kilowatt-hours in a single unit and scale up to 300 kilowatt-hours for home or small commercial use; there’s also new pad-mounted configurations with capacity up to 1 megawatt-hour.
Batteries, though, are the simple part. Everyone from EV makers like Rivian to utilities like Octopus Energy is racing to make a person’s or a business’s batteries and solar panels and electric cars work for them, using the power of AI to account for moment-to-moment changes in energy prices and supply. Lunar’s new tech makes the case that the most important element is a single brain to integrate every last smart, electrified thing in your house.
The fundraise comes on the heels of a $50 million grant from the Department of Energy.
Almost all lithium-ion batteries on the market rely on graphite for their anodes, more than 90% of which is processed in China. That concentration has created a chokepoint in the Pentagon’s supply chain as the military increasingly turns to batteries to help its transportation network operate more quietly and reduce reliance on complex refueling logistics.
So when Congress passed the latest National Defense Authorization Act at the end of 2025, barring Chinese-linked battery materials from military use starting in 2028, Coreshell saw an opening. While the California-based silicon-anode battery startup had previously focused on automakers as its beachhead customers, it’s now shipping its first battery cells to the military for use on Navy ships and Army ground vehicles. On Wednesday, Coreshell announced a $30 million Series B to scale up manufacturing operations to meet the needs of this growing customer base.
“We’re entering a new stage where we’re no longer, I would say, demand limited,” Coreshell’s CEO Jonathan Tan told me. “This year we’ve had to put on second and third shifts, work nights and weekends, just to get the product out the door.”
Coreshell sets itself apart by going a step further than the NDAA requires. The law doesn’t make suppliers trace battery materials all the way back to the mine, which would be exceedingly difficult given China’s dominance across the battery supply chain. But Coreshell has nevertheless eliminated Chinese sourcing from its anodes by replacing graphite with silicon mined and refined in the U.S. by Ferroglobe, one of its Series A investors.
Ferroglobe and global investment firm Access Industries led the latest round, with defense contractor ADS also joining as a new strategic investor. The financing comes on the heels of a $50 million Department of Energy grant that Coreshell secured in August as part of a program to strengthen the domestic battery supply chain. That funding will support the company’s first commercial-scale facility, a 2-gigawatt-hour factory.
That’s about 20 times the size of the 100-ish-megawatt-hour plant the startup had originally envisioned, as the DOE grant has allowed Coreshell to “expand much further than we were originally expecting,” according to Tan. The company is now evaluating several potential U.S. sites and expects to announce its selection early next year. For now, it relies on unnamed contract manufactures, along with its small pilot line in San Leandro, to produce its cells. But once the gigafactory gets up and running, the startup plans to bring electrode production in house by 2028, followed by full cell assembly in 2029.
Building this plant will ultimately require significant additional capital. But Tan believes this latest vote of confidence from the federal government will help Coreshell to diversify its capital stack as it continues to fundraise. “That’s one of the great things about having such a notable DOE award is that it also allows us to attract multiple forms of capital,” he told me.
Silicon has long been recognized as a promising alternative material for battery anodes, as it can store far more energy than graphite. The catch is that it tends to swell during charging, causing it to break down quickly and ultimately leading to a much shorter cycle life. Coreshell says it’s extended its anode’s lifespan by giving it a proprietary coating, which Tan told me back in April essentially means “painting the inside of your battery” with an ultra-thin protective layer.
Other companies, such as Sila Nanotechnologies and Group14 Technologies, are also working to commercialize silicon anodes. But Coreshell says many of its competitors rely on more highly engineered, expensive forms of silicon, such as silane gas. By contrast, Coreshell uses metallurgical silicon, a cheap, raw commodity already widely used in aluminum alloys. That, Tan argues, gives the company a cost advantage not only over its competitors, but potentially Chinese graphite too.
Coreshell hasn’t yet demonstrated that its cells can meet the performance demands of the automotive industry, however. When the company raised its Series A in early 2025, it said it expected its automotive cells to exceed 1,000 charge cycles while retaining 80% of their original capacity. But Tan told me many defense applications don’t require such demanding performance targets, as Navy ships and ground vehicles are “not intending to have as many miles or missions or use cases on that same battery” as a consumer EV would.
That doesn’t mean the company is abandoning its automotive ambitions. As Tan pointed out, electric vehicles remain by far the largest source of global and domestic battery demand. “It’s natural for us to obviously utilize the security supply chain first,” he told me. “That allowed us to really get to commercialization, revenue, and production faster, because automotive qualification is this longer journey. But ultimately, we want to do both of those and more.”