My brother is coming to visit London. He wants one thing: beer. Apparently a lot of it. If there is one thing I don't know much about, it's beer and pubs. I'm Gen Z. I'm up at 6:30 for a sunrise run. My idea of a Saturday well spent is an 80-mile ride followed by a flat white. My brother, a Gen Y edge case, considers this a character flaw.

So I did what every little sister would do: instead of finally getting my payback for two decades of him beating me at every sport imaginable (…he was just taller), I opened VS Code. One evening later, I have 49,840 pubs in a dataframe, an NLP classifier on pub names, a pub vulnerability model, and an interactive tool that lets you check whether your own local looks structurally at risk.

His requested pub crawl - my original goal - is in there somewhere. But first: what I found isn’t really a story about beer. It’s a story about what happens to a country when the places where people belong become assets on someone else’s balance sheet.

I’ve lived in four countries in the last few years. I am not, by temperament, a pub person. But some of the most at home I’ve ever felt has been in exactly the kind of places this piece is about.

In Brooklyn (not New York), a tiny town north of Sydney on the Hawkesbury River, the kind of place with one pub and one opinion about outsiders, we entered the quiz as "The Wookies" (yes, that's a Star Wars reference) and somehow, against all odds, narrowly beat the local elderly ladies from Mooney Mooney. When we passed our prize back to them, something shifted. They started talking and suddenly we weren't tourists. We felt at home.

Or in Tuscany, just after I’d moved and didn’t speak a word of Italian, I was cycling behind a local club ride and held the wheel for 40km, eventually pulling on the front for them. After the ride, with some very Italian hand gestures, they invited me to a bar in a tiny village on the piazza. Over a vino rosso we exchanged a few broken sentences about the best routes. I felt at home.

Neither moment was planned. Neither required an app, a membership, or a booking. They happened because a place existed - open, informal, cheap enough that the price of entry was just showing up.

Ray Oldenburg called these spaces third places: not home, not work, but the pubs, cafés, and piazzas where community happens without anyone organising it. Robert Putnam, in Bowling Alone, measured what happens when they vanish: trust collapses, civic life withers, democracy frays. No places, no trust. No trust, no society. But neither asked the question that matters most for Britain in 2026: who is doing the dismantling of these third spaces, and why?

First, let’s put some more numbers to this. I pulled the UK business register snapshots for SIC 56302 (public houses and bars), from 2009 to 2022. Britain went from ~54,000 registered pubs to under 40,000. Over 14,000 gone. A quarter of the total. The trend is relentlessly downward.

(The ONS methodology captures businesses registered for VAT and/or PAYE. Very small pubs below the VAT threshold, the kind of micro-local that matters most, may be undercounted. In other words, the real number is probably worse.)

The timeline is a political economy in miniature: the beer duty escalator (scrapped 2013 after years of above-inflation hikes), the 2017 business rates revaluation, COVID, the 2022 energy crisis. But the point is: the decline predates the shocks. This isn’t one bad year, it’s structural.

Every region is losing. The North East, North West, Yorkshire, and the Midlands fastest - 25-30% of their stock. London least. The correlation between regional pub decline and the 2016 Leave vote is r = 0.67. I won’t claim causation with twelve data points, but the comfortable reading is Putnam's passive erosion of social capital. I’ll soon come to the harder reading of this.

The Brooklyn pub quiz happened because the pub existed. The cycling club aperitivo happened because the village bar existed. What happens in a town where neither does?

So I took all surviving pubs and every pub that has closed since 2016, and asked a simple question: what's structurally different about the ones that died?

I trained a random forest model (an algorithm that builds thousands of decision trees and asks each one what matters most) on several structural characteristics of every pub in the dataset to predict which pubs closed between 2016 and 2024. Then I decomposed the feature importances to see what mattered most. The overwhelming winner was spatial isolation: how far a pub stood from its nearest neighbour and how many other pubs existed within walking distance. The model was telling me something simple. Pubs don't die because of what's inside them. They die because of what's around them.

How exactly did I measure isolation? I calculated the distance to each pub’s nearest neighbour using a haversine BallTree. Translation: straight-line distance over the Earth’s surface and not walking time. (And yes, I used a BallTree instead of a KDTree. The curvature of the Earth matters when your dataset spans from Cornwall to Caithness. I will not be taking questions.) Then I did the same for every pub that has closed since 2016, using archived snapshots of the same dataset.

The pattern is as follows: median nearest-neighbour distance for a surviving pub: ~280 metres. For a pub that closed: ~640 metres. Simply said: pubs that were isolated died while pubs in clusters survived. The red dots on the map are the next to go. They are disproportionately rural, disproportionately northern, disproportionately in the same communities that have already lost the most.

And it’s not just correlation in a static picture. It’s dynamic. Every pub that closes increases the isolation of the remaining pubs, pushing more of them into the danger zone. This is the spatial death spiral.

As promised, the harder reading of the decline of pubs. Brett Christophers (Rentier Capitalism) and Grace Blakeley (Stolen) can offer an answer. The UK economy increasingly extracts value from assets such as land, housing, infrastructure, rather than producing it. The pub is a perfect case study: it sits on land, it has a freehold, it generates modest cash flow. For a private equity firm, that’s not a community asset, it’s a leveraged buyout opportunity. Acquire, load with debt, extract, underinvest, and when the pub becomes unviable, sell the land to developers at a multiple.

We have already seen that isolated pubs die. But pub isolation isn’t a coincidence, someone creates it. When a pubco owns thirty pubs in a region and decides to cut the five least profitable, the remaining twenty-five don’t just lose neighbours. They lose the clustering effect that was keeping them alive. In other words, the just identified spatial death spiral has an author.

The regions that lost most pubs are the regions where ownership was most consolidated under leveraged pubco models. When Ei Group raised rents to service its debt, it was tenants in Sunderland and Burnley who couldn’t pay, not tenants in my dear Islington.

Britain’s largest pub company is called Stonegate: roughly one in eleven falls under this. You know the brands: Slug & Lettuce, Yates’s, Walkabout, all owned by TDR Capital, a private equity firm that also owns Asda. Its corporate structure runs through the Cayman Islands.

Stonegate carries over £3 billion in debt, mostly from its leveraged acquisition of rival Ei Group in 2019, completed months before the pandemic shut every pub in Britain. In 2024: £455 million in interest payments, a £214 million loss, and a citation from the Department for Business for failing to pay minimum wage to 3,650 workers.

It’s not alone. Greene King (~2,700 pubs) was taken private by Li Ka-shing’s Hong Kong property empire for £4.6 billion. Punch Pubs (~1,300 pubs) was bought by Fortress Investment Group, a US private equity firm formerly owned by SoftBank; now majority-owned by Mubadala (Abu Dhabi). Between them, PE-backed and overseas-owned companies control roughly a quarter to a third of every pub in Britain.

So here’s the political economy of pub closures. It is not: people stopped going. It is: pubs became collateral in leveraged buyouts, debt costs were passed down as higher rents and lower investment, and the pubs that couldn’t sustain the extraction closed, while the ones that could were reshaped into higher-margin branded concepts serving a wealthier clientele.

The Bricklayers Arms didn’t die of natural causes. It was killed by a balance sheet in George Town. And if you think London escaped this, look closer…

London looks like the success story. Smallest decline nationally. If you live in Hackney or Peckham, you might think the pub is thriving: new taproom on every corner, natural wine bar where the laundrette used to be.

London didn't lose its pubs. It swapped them. And this is where the spatial story meets the ownership story. In Burnley, private equity closes a pub and nothing replaces it since the land isn't worth enough. In London, the land is worth plenty, so the site reopens: refitted, rebranded, repriced. The count stays stable. But the name changes, and so does who walks through the door. This is why the random forest flagged spatial isolation as the dominant predictor: it's not geography acting alone, it's the financial logic of extraction expressing itself spatially. PE firms don't close pubs at random. They close the ones that sit on cheap land with thin margins and replace the ones that sit on expensive land with higher-margin concepts. The map of pub death is a map of where extraction was profitable and reinvestment wasn't.

I used the pub names to expose it. I classified every surviving London pub as either traditional: such as Red Lion, Kings Arms, Bricklayers Arms, names encoding centuries of heraldry, trades, and coaching roads or as modern, such as The Yard, The Social, Tap Room, names that strip away history for something brandable. Then I mapped them.

Traditional pubs scatter across all of London: inner, outer, rich, poor. Modern pubs cluster in zones 1-2 and the gentrification corridor from Hackney through Peckham. London's count looks stable because craft taprooms in gentrifying postcodes replace closures in outer boroughs. But a £7.50 hazy IPA in Dalston is not the same third place as a £2.50 pint in a working men's club in Barking.

I didn’t want to rely on my own keyword list, so I ran a sanity check using machine learning. (ML people: TF-IDF on character n-grams of every London pub name, K-means clustering projected via PCA. I know, TF-IDF on character n-grams is not state of the art. But when your unsupervised model rediscovers the same class structure that took historians centuries to document, you don't need BERT/ fancy fine-tuned LLM). Simply said, I fed every pub name into an algorithm that breaks words into small character fragments, think of it as teaching a model to recognise the texture of a name rather than its meaning. Then I asked it to sort all names into groups, with no information about history, geography, or what “traditional” even means.

It found the same divide I did. And when I plotted those algorithmically-discovered groups back on the map, they had geography: old-textured names in the suburbs, new-textured names in the centre. The algorithm sees what the eye sees - naming eras are a spatial signature of class.

Teal: the old Britain: heraldic, royal, rural, trades, naval. Pink: the new Britain: bars, kitchens, tap rooms. The countryside is teal and the cities are turning pink. Both are valid places to get a drink. But only one is a third place in Oldenburg’s sense: a space where the full cross-section of a community meets without requiring a particular income, education, or cultural fluency to walk through the door.

So what do you do with this information? I built a companion tool: Is Your Local At Risk?

The model behind it is deliberately simple and that's the point. For every one of Britain's pubs, I calculate two things: how far away is the nearest other pub (nearest-neighbour distance, via haversine BallTree), and how many pubs exist within a walkable radius (pub density). Those two spatial signals get combined into a continuous risk score, then bucketed into green (clustered, resilient), amber (thinning), and red (isolated, vulnerable).

That's it. No pricing data, no opening hours, no operator quality scores. Just structure and space. Because the finding from the closure analysis is stark: the single strongest predictor of whether a pub closed between 2016 and 2024 is how alone it was. Not how good the beer was or who owned it. But whether it had neighbours.

Enter your postcode and see every pub within walking distance, scored green/amber/red by the vulnerability model. The risk scores, not coincidentally, map onto the worst loneliness scores in the ONS wellbeing data.

The tool won't tell you btw whether your local does a decent Sunday roast (I’m working on that model, it just requires some more field research). But it will tell you whether the spatial conditions around it look like the conditions that preceded every closure in the dataset.

The fatalist reading of this all is that: pubs close because economics, because supermarket alcohol, because young people don’t drink as much (pls don’t blame Gen Z for this one, we inherited the wreckage). These are real factors. But they’re the cover story for a series of reversible policy choices. Britain chose to tax a pint in a pub more heavily than wine in a restaurant. Chose permitted development rights that let landlords flip pubs into flats without planning permission. Chose to cut council budgets by 40%, hollowing out the only institution that could have said no.

So here’s my policy brief. I’ll keep it short.

Map it. Build a national Third Place Index. Every neighbourhood scored by density, diversity, and walkability of its social infrastructure. I built a version with free data and a laptop. The ONS has better resources than I do. Presumably.

Protect it. Use the vulnerability model to fast-track the 500 most isolated pubs for Asset of Community Value status (a legal designation that gives communities 6 months to bid when a pub goes up for sale). Require planning permission for any pub conversion, not just where communities have the lawyers and the social capital to fight. The current system protects pubs in Richmond and lets them die in Rochdale.

Fund it. The government spends serious money treating loneliness downstream: social prescribing, befriending services, community connectors. Good programmes. But it’s like funding ambulances while defunding the road barriers. Redirect 10% toward keeping existing third places open. A pub costs less to save than a community centre costs to build, and it comes pre-loaded with something no government programme can manufacture: centuries of accumulated meaning.

Measure it. Add third place access to the Index of Multiple Deprivation (IMD). What gets measured gets managed. Right now a neighbourhood can score perfectly on the IMD while having zero places for its residents to sit together.

Tax it. If TDR Capital wants to own 4,500 British community assets from the Cayman Islands, it can fund the mechanism for communities to buy them back. A levy on offshore-held pub freeholds, ringfenced for community ownership.

Because the counter-model already exists. Community-owned pubs have grown 63% in five years. The model is simple: a community raises shares to buy the freehold. Ownership stays local. Profits get reinvested. No absentee landlord, no debt servicing, no Cayman Islands. The Ivy House in Nunhead became the first pub in Britain listed as an Asset of Community Value, saved from developers by locals who crowdfunded the purchase. It’s still open. The people who own it are the same people who drink in it.

So, the Asset of Community Value framework exists and the co-op model works. What’s missing is money and a government willing to ask where it should come from.

Oh right. My brother.

After all that, here’s what I’ve actually built him: a pub crawl through London that traces the naming eras. I start at a medieval heraldic pub in the City (there are still a few that have served beer since before the Great Fire). Walk east to a Victorian trades pub in Whitechapel - a Bricklayers or a Carpenters. Cross into Hackney for a modern craft spot to see what’s replaced the old guard. South to a coaching inn in Borough. End at a proper South London local that hasn’t changed its name or its prices since Thatcher.

Five pubs. Five centuries. One brother who doesn't know he's about to get a lecture on the financialisation of community infrastructure with his fifth pint. I’ll let you know if he ever forgives me.

Oh, and next month I'm cycling through Australia for six weeks. I want to see whether a country that built its third places differently has built something more durable than what England is losing. Australia's social infrastructure runs on not-for-profit clubs such as RSLs, surf lifesaving clubs, bowls clubs and leagues clubs, all member-owned, community-governed, and structured so that profits stay local. It's essentially the co-op model that Britain is only now discovering, except Australia built thousands of them. The trade-off is that many are funded by poker machines (“pokies”), which is its own political economy story. But the basic architecture of community ownership, democratic governance, no Cayman Islands balance sheet, is what I've been arguing Britain needs. I want to see how it holds up in person. I’ll promise that I’ll bring the dataframe to the pub quiz.

Team name: still The Wookies.

If this was useful, share it - especially with your MP who loves a pint. Hope they love the data too. Also consider buying me a coffee to keep the project alive:)

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The UK government makes a lot of money from cars. It taxes car ownership, it taxes the fuel, and it is about to charge drivers of electric vehicles by the distance they travel.

But Britons’ reliance on their 34 million cars also comes at great expense to the economy. Heavy traffic and congestion costs £7.5 billion a year in wasted time. An estimated £17 billion is needed to fix the worn out road network.

In the last 30 years, as the UK population has grown by 19%, the number of cars has exploded by 56%. Outside of London, 81% of British households own at least one car.

Fitting all of these vehicles into a fairly small country means that driving has clear priority over other forms of transport. In Germany, 90% of people living in large cities have access to a tramway or underground train system. In France, it’s 80%.

In the UK, the figure is less than 20%, a similar level to the US.

But the US has vast amounts of space, where brand new roads are regularly built to ease congestion. And so the UK has to deal with a population density comparable to the Netherlands (at least for England) and the urban transport choices of Texas.

This lack of decent public transport is expensive to sustain for all sorts of reasons – like the councils forking out £2.3 billion a year transporting 470,000 children to school, mostly in taxis. Or the cost of subsidising 800,000 motability vehicles, which accounted for one in every five new cars sold in 2024.

While the government should absolutely support the travel needs of people with disabilities and help children get to school, in a strange case of state-provided individualism, the UK has become a country where only cars can deliver these vital public services.

Designated drivers

Yet urban design is ultimately a choice. While the UK has a system which allows for 560 cars per 1,000 people, other places have taken a different route.

In Singapore, there are 146 cars per 1,000 people. This came about after the government implemented a quota system to release a limited number of (expensive) car-ownership licenses to limit congestion and finance public transport.

A ten-year “certificate of entitlement” to own a car in Singapore now costs more than US$100,000 (£76,000) on top of an additional congestion tax.

The result? Singapore’s public transport is cheap, fast, reliable and efficient.

People without cars are fine, because the number of overall cars is so small that buses and taxis don’t get stuck in traffic. People with cars subsidise the buses and trains, while enjoying smooth traffic.

The Netherlands used a different strategy. In the 1970s, Dutch streets were dominated by cars and had become dangerous for pedestrians and cyclists. Protests led to a reorganisation of cities to become far less car friendly.

My research with a fellow economist demonstrated that if you decrease the space given to cars, they go slower, public transit goes faster, and walking and cycling become safer.

Then, as more people turn to public transport, the higher uptake makes it a faster and more reliable form of transit. It gets to a point where people who would never have taken public transport end up using it and getting to their destination much more quickly than when the car was dominant.

So for the UK to be more like Singapore, the government needs to make motorists pay much more for their car use. To be more like the Netherlands, it must take away their space.

The UK, and especially England, which invented the railway and used to be full of electric tramways, has the population density to make a dramatic switch away from cars actually work. In fact, it’s hard to think of a country better suited to public transport, or where it is more needed. It just hasn’t been built.

Or at least, it has not been built outside of London, the only place in the UK where most households don’t own a car.

So London is rich, well connected and people don’t need cars. Elsewhere, people park on pavements in derelict high streets and drive to supermarkets and places of work.

With stretched public finances, doing nothing about this state of affairs is a risky option. The UK has been described by the Local Government Association as a “country in a jam”, where productivity is held back by car traffic, with no hope for improvement. Lost time on roads is set to increase by 27% in the coming decades.

Moving to a situation where cars are not considered the fastest and most convenient mode of transportation will take ambition and imagination. But the alternative is a very expensive dependency, which clogs up the UK economy.

Choosing the “least expensive” healthy food options could cut dietary emissions by one-third, according to a recent study.

In addition to the lower emissions, diets composed of low-cost, healthy foods would cost roughly one-third as much as a diet of the most-consumed foods in every country.

The study, published in Nature Food, compares prices and emissions associated with 440 local food products in 171 countries.

The researchers identify some food groups that are low in both cost and emissions, including legumes, nuts and seeds, as well as oils and fats.

Some of the most widely consumed foods – such as wheat, maize, white beans, apples, onions, carrots and small fish – also fall into this category, the study says.

One of the lead authors tells Carbon Brief that while food marketing has promoted the idea that eating environmentally friendly diets is “very fancy and expensive”, the study shows that such diets are achievable through cheap, everyday foods.

Meanwhile, a separate Nature Food study found that reforming the policies that reduce taxes on meat products in the EU could decrease food-related emissions by up to 5.7%.

Costs and emissions

The study defines a healthy diet using the “healthy diet basket” (HDB), which is a standard based on nutritional guidelines that includes a range of food groups with the needed nutrients to provide long-term health.

Using both data on locally available products and food-specific emissions databases, the authors estimate the costs and greenhouse gas emissions of 440 food products needed for healthy diets in 171 countries.

They examine three different healthy diets: one using the most-consumed food products, one using the least expensive food products and one using the lowest-emitting food products.

Each of these diets is constructed for each country, based on costs, emissions, availability and consumption patterns.

The researchers find that a healthy diet comprising the most-consumed foods within each country – such as beef, chicken, pork, milk, rice and tomatoes – emits an average of 2.44 kilograms of CO2-equivalent (kgCO2e) and costs $9.96 (£7.24) in 2021 prices, per person and per day.

However, they find that a healthy diet with the least-expensive locally available foods in each country – such as bananas, carrots, small fish, eggs, lentils, chicken and cassava – emits 1.65kgCO2e and costs $3.68 (£2.68). That is approximately one-third of the emissions and one-third of the cost of the most-consumed products diet.

In comparison, a healthy diet with the lowest-emissions products – such as oats, tuna, sardines and apples – would emit just 0.67kgCO2e, but would cost nearly double the least-expensive diet, at $6.95 (£5.05).

This reveals the tradeoffs of affordability and sustainability – and shows that the least-expensive foods tend to produce lower emissions, according to the study.

Dr Elena Martínez, a food-systems researcher at Tufts University and one of the lead authors of the study, tells Carbon Brief this is generally true because lower-cost food production tends to use fewer fossil fuels and require less land-use change, which also cuts emissions.

Ignacio Drake is coordinator of the fiscal and economic policies at Colansa, an organisation promoting healthy eating and sustainable food systems in Latin America and the Caribbean. 

Drake, who was not involved in the study, tells Carbon Brief that the research is a “step further” than previous work on healthy diets. He adds that the study “integrates and consolidates” previous analyses done by other groups, such as the World Bank and the UN Food and Agriculture Organization.

Food group differences 

The research looks at six food groups: animal-sourced foods, oils and fats, fruits, legumes (as well as nuts and seeds), vegetables and starchy staples.

Animal-sourced foods – such as meat and dairy – are typically the most-emitting, and most-expensive, food group. 

Within this group, the study finds that beef has the highest costs and emissions, while small fish, such as sardines, have the lowest emissions. Milk and poultry are amongst the least-expensive products for a healthy diet.

Starchy staple products also contribute to high emissions too, adds the study, because they make up such a large portion of most people’s calories. 

Emissions from fruits, vegetables, legumes and oil are lower than those from animal-derived foods.

The following chart shows the energy contributions (top) and related emissions (bottom) from six major food groups in the three diets modelled by the study: lowest-cost (left), lowest-emission (middle) and most-common (right) food items.

The six food groups examined in the study are shown in different colours: animal-sourced foods (red), legumes, nuts and seeds (blue), oils and fats (purple), vegetables (green), fruits (orange) and starchy staples (yellow). The size of each box represents the contribution of that food to the overall dietary energy (top) and greenhouse gas emissions (bottom) of each diet.

Prof William Masters, a professor at Tufts University and author on the study, tells Carbon Brief that balancing food groups is important for human health and the environment, but local context is also important. For example, he points out that in low-income countries, some people do not get enough animal-sourced foods.

For Drake, if there are foods with the same nutritional quality, but that are cheaper and produce fewer emissions, it is logical to think that the “cost-benefit ratio [of switching] is clear”.

Other studies and reports have also modelled healthy and sustainable diets and, although they do not exclude animal-sourced foods, they do limit their consumption.

A recent study estimated that a global food system transformation – including a diet known as the “planetary health diet”, based on cutting meat, dairy and sugar and increasing plant-based foods, along with other actions – can help limit global temperature rise to 1.85C by 2050.

The latest EAT-Lancet Commission report found that a global shift to healthier diets could cut non-CO2 emissions from agriculture, such as methane and nitrous oxide, by 15%. The report recommends increasing the production of fruit, vegetable and nuts by two-thirds, while reducing livestock meat production by one-third.

Dr Sonia Rodríguez, head of the department of food, culture and environment at Mexico’s National Institute of Public Health, says that unlike earlier studies, which project ideal scenarios, this new study also evaluates real scenarios and provides a “global view” of the costs and emissions of diets in various countries.

Increasing access

The study points out that as people’s incomes increase, their consumption of expensive foods also increases. However, it adds, some people with high income that can afford healthy diets often consume other types of foods, due to reasons such as preferences, time and cooking costs.

The study stresses that nearly one-third of the world’s population – about 2.6 billion people – cannot afford sufficient food products required for a healthy diet.

In low-income countries, primarily in sub-Saharan Africa and south Asia, 75% of the population cannot afford a healthy diet, says the study.

In middle-income countries, such as China, Brazil, Mexico and Russia, more than half of the population can afford such a diet.

To improve the consumption of healthy, sustainable and affordable foods, the authors recommend changes in food policy, increasing the availability of food at the local level and substituting highly emitting products.

Martínez also suggests implementing labelling systems with information on the environmental footprint and nutritional quality of foods. She adds:

“We need strategies beyond just reducing the cost of diets to get people to eat climate-friendly foods.”

Drake notes that there are public and financial policies that can help reduce the consumption of unhealthy and unsustainable foods, such as taxes on unhealthy foods and sugary drinks. This, he adds, would lead to better health outcomes for countries and free up public resources for implementing other policies, such as subsidies for producing healthy food.

Separately, another recent Nature Food study looks at taxes specifically on meat products, which are subject to reduced value-added tax (VAT) in 22 EU member states. 

It finds that taxing meat at the standard VAT rate could decrease dietary-related greenhouse gases by 3.5-5.7%. Such a levy would also have positive outcomes for water and land use, as well as biodiversity loss, according to the study.

If we put solar panels on that land, we could produce roughly 32,000 terawatt-hours of electricity each year.

These comparisons might seem surprising at first. But they can be explained by the fact that growing crops is a very inefficient process. Plants convert less than 1% of sunlight into biomass through photosynthesis.⁹ Even more energy is then lost when we turn those plants into liquid fuels. Crops such as sugarcane tend to perform better than others, like maize or soybeans, but even they are still inefficient.

By comparison, solar panels convert 15% to 20% of sunlight into electricity, with some recent designs achieving as much as 25%.¹⁰ That means replacing crops with solar panels will generate a lot more energy.

Now, you might think that we’re comparing very different things here: energy from liquid biofuels meant to decarbonize transport, and solar, which could decarbonize electricity. But with the rise of affordable and high-quality electric vehicles, solar power can be a way to decarbonize transport, too.

You could power all of the world’s cars and trucks on this solar energy if transport were electrified.

That’s less than one-quarter of the 32,000 TWh that solar panels could produce on biofuel land. Consider those options. The world could meet 3% or 4% of transport demand with biofuels. Or it could meet all road transport demand on just one-quarter of that land. The other three-quarters could be used for other things, such as food production, biofuels for aviation, or it could be left alone to rewild.

It’s worth noting that in this scenario — unlike using solar for bulk electricity needs — we would need much less additional energy storage solutions, because every car and truck is essentially a big battery in itself.

The world could meet 3% or 4% of transport demand with biofuels. Or it could meet all road transport demand on just one-quarter of that land.

What we do want to challenge is how we think and talk about land use. People rightly question the impact of solar or wind farms on landscapes, but rarely consider the land use of existing biofuel crops, which do very little to decarbonize our energy supplies. Whether we’ll run out of land for solar or wind is a common concern, but when we run the numbers, it’s clear that there is more than enough; we’re just using it for other things. Stacking up the comparative benefits of those other things allows us to make better choices, if they’re available.

In this article, we wanted to run the numbers and get some perspective on how we could use that Germany- or Poland-sized area of land in the most efficient way. What’s clear is that we could produce a huge amount of electricity from solar on just a fraction of that land. We could power an entire global electric car and truck fleet on just one-quarter of it.

• Methodology

  If you’re interested in digging deeper, we provide a methodological document where we go through our sources and calculations in detail.

Acknowledgments

We would like to thank Max Roser and Edouard Mathieu for editorial feedback and comments on this article. We also thank Marwa Boukarim for help and support with the visualizations.

Endnotes

1. Other options didn’t rely on switching fuels, such as improving car efficiency and expanding public transport, but these only go so far.

   Here’s a quote from the Intergovernmental Panel on Climate Change in 2007: “Within the transport sector there are five mitigation options with a clear link between sustainable development, adaptation and mitigation. These areas are biofuels, energy efficient, public transport, non-motorised transport and urban planning.”

2. In 2024, the International Energy Agency estimates that 1.8 billion litres of liquid biofuel were for “biojet” fuel. Total production was 118 billion litres. That means biojet fuel was only 1%.

   Most of this biojet fuel comes from waste fats and oils, which also don’t have the same land use dilemmas as bioethanol and biodiesel used for road transport.

3. Carbon savings for sugarcane feedstocks tend to be much larger than they are for corn, wheat, and palm oil feedstocks.

   This can vary a lot, depending on location, crop type, and production system. But this meta-analysis finds that some, such as sugarcane ethanol from Brazil, can achieve more than 60% savings (if no land use change is involved), but some crops produce almost no savings at all.

   Jeswani, H. K., Chilvers, A., & Azapagic, A. (2020). Environmental sustainability of biofuels: a review. Proceedings of the Royal Society A.

   These results can be very sensitive to the methodology and life-cycle assessment tools.

   Pereira, L. G., Cavalett, O., Bonomi, A., Zhang, Y., Warner, E., & Chum, H. L. (2019). Comparison of biofuel life-cycle GHG emissions assessment tools: The case studies of ethanol produced from sugarcane, corn, and wheat. Renewable and Sustainable Energy Reviews.

4. Searchinger, T. D., Wirsenius, S., Beringer, T., & Dumas, P. (2018). Assessing the efficiency of changes in land use for mitigating climate change. Nature, 564(7735), 249-253.

   Fehrenbach, H., & Bürck, S. (2022). Carbon opportunity costs of biofuels in Germany—An extended perspective on the greenhouse gas balance including foregone carbon storage. Frontiers in Climate.

5. Sandford et al. (2024). Diverted harvest: Environmental Risk from Growth in International Biofuel Demand. Cerulogy.

6. They estimate that 8% of global croplands supply feedstock for biofuel production. Using their estimate of 1.4 billion hectares of total cropland, this would be 112 million hectares.

7. This is based on the power density of modern solar panels — how much energy can be produced for a given area. For more details on these calculations, see our full methodological document.

8. This 1424 TWh is based on data from the Energy Institute. We converted this from petajoules (EJ) to TWh using a conversion factor of 0.27778.

9. Croce, R., Carmo-Silva, E., Cho, Y. B., Ermakova, M., Harbinson, J., Lawson, T., ... & Zhu, X. G. (2024). Perspectives on improving photosynthesis to increase crop yield. The Plant Cell.

10. Oni, A. M., Mohsin, A. S., Rahman, M. M., & Bhuian, M. B. H. (2024). A comprehensive evaluation of solar cell technologies, associated loss mechanisms, and efficiency enhancement strategies for photovoltaic cells. Energy Reports.

11. For example, global biofuel land is not located precisely where solar electricity or electric vehicle demand is expected to be.

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Hannah Ritchie and Pablo Rosado (2026) - “Putting solar panels on land used for biofuels would produce enough electricity for all cars and trucks to go electric” Published online at <a href="http://OurWorldinData.org" rel="nofollow">OurWorldinData.org</a>. Retrieved from: 'https://archive.ourworldindata.org/20260113-111630/biofuel-land-solar-electric-vehicles.html' [Online Resource] (archived on January 13, 2026).

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@article{owid-biofuel-land-solar-electric-vehicles,
    author = {Hannah Ritchie and Pablo Rosado},
    title = {Putting solar panels on land used for biofuels would produce enough electricity for all cars and trucks to go electric},
    journal = {Our World in Data},
    year = {2026},
    note = {https://archive.ourworldindata.org/20260113-111630/biofuel-land-solar-electric-vehicles.html}
}

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