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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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Average U.S. gasoline prices have slipped back above $4 a gallon.
A decade ago, the Princeton economists Alan Blinder and Mark Watson published a paper about a fact that they called “not nearly as widely known as it should be”: The U.S. economy has done better under Democratic presidents than Republican presidents.
Blinder was not a completely impartial observer — he served on President Bill Clinton’s Council of Economic Advisers, and Clinton later appointed him vice chair of the Federal Reserve — but he and Watson compiled a lengthy list of statistics to back up their claim. The U.S. economy has grown faster, produced more jobs, had a lower unemployment rate, seen higher corporate profits and investment, and experienced better stock market performance under Democrats than Republicans. While the original paper described this divergence from 1947 to 2013, recent research has shown that it held through the subsequent Obama, Trump, and Biden administrations.
The only metric where the two parties come close is inflation, but Democrats still seem to have a tiny edge there, even after the Biden-era inflation.
Why? Blinder and Watson found that it didn’t entirely come down to timing. (Other observers have disputed this, arguing that Republicans tend to get elected at the peak of economic booms, while Democrats win during or just after recessions.) Instead, Blinder and Watson found that a few factors — oil shocks, productivity growth, a more favorable international growth environment, and perhaps better consumer confidence — could explain much of the divergence.
Of course, these factors can’t be entirely separated from a president’s record in office. Oil shocks, for example, tend to drag down global growth, which in turn slows the U.S. economy. And as Watson and Blinder write, some of those oil shocks “may have been induced by [American] foreign policy.” By that mechanism, presidential bellicosity in the Middle East can translate into poorer economic outcomes. This belligerence may even be, as the writer Matt Yglesias contended earlier this year, Republican presidents’ “worst economic policy.”
Why am I recounting all this? Because average U.S. gasoline prices have slipped back above $4 a gallon, according to AAA. (As I write, they stand at $4.01.) The collapse of the ceasefire with Iran — and President Trump’s inability to figure out how to end a war he started — are once again driving up fossil fuel prices.
The numbers add up. Defense Secretary Pete Hegseth told Congress today that the Iran War has cost $37.5 billion so far, but according to a tracker from Brown University researchers, Americans have already paid nearly double that — $71 billion! — on more expensive gasoline and diesel fuel. A billion here, a billion there, and pretty soon you’re talking about real economic underperformance. That estimate suggests the burden of higher energy prices from the Iran War has wiped out the expected $65 billion consumer boost from the One Big Beautiful Bill Act’s expanded tax refunds.
Of course, from a decarbonization perspective, higher gas prices are good, in theory. They encourage people to drive less and to switch to more fuel-efficient — or even fully electrified — vehicles, reducing carbon emissions. (This is part of why I joke about Degrowth Donald, raising fuel prices as he goes.) But short-term oil shocks are the second worst kind of emissions reductions after recessions: They are unlikely to last; they will probably not lead to real decarbonization; and they produce a lot of human misery along the way.
Perhaps this oil spike won’t persist. Perhaps Trump will find a way out of the quagmiring conflict in the Persian Gulf. Perhaps Republican presidential underperformance really does all come down to luck, too. (Or maybe, as a 2020 paper argued, Democratic presidents benefit from a “pre-election growth surge” just before a Republican wins.) But I think it’s worth noting that the recent trickle of news — and the recent and less noticed surge in gas prices — is how an oil interruption results in slower growth overall. If oil shocks really are responsible for GOP presidential underperformance, this is what it would look like.
The irony is that technology finally exists to make the American transportation sector — and the overall economy — less dependent on oil. This technology was developed at the American public’s expense to help manage a scenario much like this one. And the administration has undermined it at almost every opportunity.
The latest forecast from BloombergNEF raises its estimate for AI electricity demand by 83%.
Energy analysts at BloombergNEF predicted last year that U.S. data center electricity demand would reach 106 gigawatts within the next decade. In its latest outlook, released Tuesday, the group increased its forecast by 83%, to 194 gigawatts — enough to light up 150 million homes, or roughly every single household in the country today.
Even that may be a conservative estimate. If data center developers were to max out the total number of the high-powered chips used to train and operate AI models forecast to be delivered by 2035, electricity demand would reach 229 gigawatts.
Over 100 gigawatts of that demand has entered the development pipeline since the beginning of this year, the result of both rising demand for artificial intelligence and shortened construction timelines for data centers. Some developers have oriented their site selection around energy availability, redeveloping brownfield energy generation sites for quick access to electricity and developing relationships with utilities. Others have eschewed grid interconnection entirely and instead relied behind-the-meter power generation.
As Mark Daly, head of technology and innovation at BNEF and a co-author of the report, pointed out to me, a growing share of the project pipeline comes from first-time developers. He and his colleagues project that non-hyperscaler data center capacity will nearly quintuple over the next decade, as hyperscaler capacity almost triples. That could ultimately create pipeline risks, however, as small-scale developers lack the capabilities of more experienced developers to optimize around pre-construction bottlenecks and navigate rapidly growing local opposition. Although local opposition to data centers has become prevalent, historic trends and predictions on how quickly developers are able to navigate hostile environments are built on the proficiency of experienced developers. Because first-time developers may face more challenges, Daly told me that data center projects overall “would see an increase in the number of delays.”
All of this, of course, comes with a big asterisk. The data center sector is rapidly evolving, and therefore highly uncertain. Among leading market research firms, BNEF said, there is a 100-gigawatt spread between the lowest and highest predicted electricity demand from data centers in 2030. Driving this spread are differences in assumptions about the average development timeline for a data center project. Daly told me that BNEF’s “project-based estimate is middle-of-the-road to bearish compared to other outlooks,” but also acknowledged that the fickle nature of local opposition on development timelines may place more constraints on future data center development than currently modeled.
No matter which prediction turns out to be most accurate, hourly U.S. electricity demand will come under intensifying pressure. BNEF predicts that average hourly U.S. electricity demand from AI workloads will grow five-fold over next nine years, reaching 120 gigawatts by 2035. That will put data centers at 12% of total electricity consumption on average by 2030, and 20% in 2035, up from 5% in 2025, according to figures from the International Energy Agency. This will put particular strain on electricity prices in markets like the Mid-Atlantic’s PJM, where data centers already comprise nearly a third of electricity consumption, and Texas’ ERCOT, where data centers currently consume a fifth of the market’s electricity.
Even the most conservative bet on future data center electricity demand is a scenario we’re not prepared for. If the Electric Power Research Institute’s prediction that just 56 gigawatts of new data center capacity will be up and running by 2030 — the lowest estimate BNEF cited — that would still consume the equivalent of Sweden’s total energy supply. Absent investments from utilities into grid resilience and intensive permitting reform to speed up renewable energy siting and development, PJM and ERCOT customers will not be the only ones feeling a serious squeeze in their wallets when their monthly utility bills arrive.
Current conditions: Tropical Depression Two strengthened into Tropical Storm Bertha yesterday, recycling the name of the 1996 Atlantic hurricane season’s first major storm • Floods from the monsoon season killed at least four people in Vietnam and left as many missing • Lightning in Utah sparked the state’s latest wildfire, the Meeks Fire, near the Strawberry Reservoir.
President Donald Trump’s on-again, off-again feud with America’s northern neighbor is, as of Monday, back on again. The White House imposed 50% tariffs on most Canadian goods, accusing the nation’s geographically nearest ally and closest cultural bedfellow of unfairly discriminating against American automotives, alcohol, and dairy products. The move threatens to unleash what the Associated Press called “a new wave of economic chaos, with risks of higher inflation and further fraying of relations between two nations that had been closely woven together before Trump’s return” to office.
In its announcement, the Trump administration said the new tariffs would “apply to all covered goods regardless of whether a good originates under the U.S.-Mexico-Canada Agreement,” referring to the Trump-negotiated North American free trade agreement, which the U.S. opted this month not to renew. This struck my colleague Robinson Meyer as ominous. “If the White House now thinks it can levy taxes despite that pact,” he wrote in yesterday’s Heatmap Daily newsletter, “then the risks for Ford, General Motors, and their suppliers have increased.”
Perhaps the only thing growing faster than voters’ antipathy toward data centers is the market’s desire for more of them. Demand for data centers is ballooning at such a rapid clip that BloombergNEF just raised its total forecast for 2035 by a jaw-dropping 83%. The latest data outlining the best-case scenario from the energy consultancy, released Tuesday morning, shows the total installed capacity of U.S. data centers reaching 194 gigawatts in the next nine years. The surge reflects how quickly new server farms are flowing into the project pipeline. In a bid to hedge against the continued expansion, BNEF created a new scenario based on the implied power demand of forecast shipments of microchips for AI computers up to 2033. This scenario implies an even greater need for power: 229 gigawatts of demand from data centers in just the next seven years. And that doesn’t count the continued growth of demand from data centers carrying out non-AI functions, such as traditional cloud computing workloads. This comes as the latest Heatmap Pro polling shows that seven in 10 Americans now oppose data centers in their backyard, a marked shift from last September, when the same survey showed voters evenly split in support and opposition.
That ballooning demand is already showing up in power markets. Of the $16.4 billion in charges from PJM Interconnection’s most recent capacity auction, $6.3 billion — some 38% — stems from data centers. That’s what Joseph Bowring, president of PJM’s independent market monitor Monitoring Analytics, told Utility Dive last week. In the last four base capacity auctions the nation’s largest grid operator held, 46% of capacity charges were driven by data centers. “PJM is continuing to act like it’s business as usual,” Bowring told the trade publication Friday. “You have to open your eyes and recognize that it is really a paradigm shift, and failing to do that imposes costs on other customers.”

On a logical level, it’s a simple supply and demand problem. The supply of electricity is not growing as quickly as demand, all while the Trump administration eliminates subsidies that once buoyed investments in new supply. As a result, corporate electricity deals look poised to increase in price. But not for every generating source. New estimates from LevelTen, a marketplace for power purchase agreements, found that solar PPAs were 5% cheaper in the second quarter of this year compared to the first quarter. In a piece by my colleague Matthew Zeitlin, LevelTen attributed the decline to an especially steep drop in prices in California’s electricity market. Excluding CAISO, solar PPA prices nationwide dropped slightly less than 2%. While hyperscalers are still buying solar, LevelTen found that commercial and industrial buyers are pulling back, creating a “continued softening in the market’s buy-side.” “We saw a lot less corporate energy buyers in the space in 2025 — 40% less — and that is just due to the increase of hyperscalers and data centers getting projects and snapping them up quickly,” Sarah Wolf, LevelTen’s director of North American transactions, told Matthew.
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Ah, Germany. The land of the Autobahn. Diesel-powered industry. The purring engines of BMWs, Porsches, and Mercedes-Benzes. The nation’s automotive might makes its latest milestone particularly important: Electric vehicles just outsold gas and diesel cars for the first time. New data from the Federal Motor Transport Authority shows that Germans registered 84,057 new electric vehicles in June, a more than 78% year-over-year increase. Traditional hybrids, meanwhile, saw 83,315 registrations, followed by gasoline-powered cars with 60,796, diesel with 33,862, and plug-in hybrids with 32,212. “The automotive history books will need a new page sooner rather than later, after electric cars outsold every other fuel type in Germany for the first time,” InsideEVs reporter Iulian Dnistran wrote. “It’s a huge shift in Europe’s biggest car market, which has traditionally been associated with diesel-powered cars that could travel hundreds of miles at highway speeds without breaking a sweat.” The Tesla Model Y was by far the best-selling EV in Germany, with nearly twice as many registrations as the No. 2 vehicle, the Volkswagen ID.3.
Putting on my Mesopotamian metal merchant hat again: Copper prices are back up. The price of the metal needed for virtually all electrical infrastructure rose 1.3% to just under $14,000 per metric ton, according to Mining.com. The price ultimately hovered at the red metal’s record set in early June. The spike stems from data showing rising tightness in the Chinese market, namely a hike in the premium buyers will pay in Shanghai for shipments of the metal. The price hiked further after a series of storms halted production in Chile for a few days.
While the West dithers on hydrogen, China is making huge strides. It already may be too late to catch up to Beijing on manufacturing the key machinery needed to produce the zero-carbon fuel. The latest data point, via Hydrogen Insight: China just shipped its largest electrolyzer order yet to Europe, via Romania.