Nearly 15 years after journalist David Owen and I tangled — and then united — over Jevons Paradox, the New York Times today published a guest essay on that subject by a Murdoch-employed London journalist. David and I went deeper and did better, as you’ll see in a moment.
Jevons Paradox denotes the tendency of economies to increase, not decrease, their use of something as they learn how to use that thing more efficiently. Its 19th-century archetype, observed by Britisher William Stanley Jevons, was that “as steam engines became ever more efficient, Britain’s appetite for coal [to power them] increased rather than decreased,” as Sky News editor Ed Conway put it today, in The Paradox Holding Back the Clean Energy Revolution. Why? Because the “rebound” in use of steam as its manufacture grew cheaper more than offset the direct contraction in use from the increased efficiency.
Illustration by Joost Swarte for “The Efficiency Dilemma,” in the New Yorker magazine’s Dec. 20, 2010 print edition (Dec. 12 on line).
Where does David Owen come in? In October 2009 he published an op-ed in the Wall Street Journal claiming that congestion pricing could never cure traffic congestion, on account of the bounceback in car traffic due to lesser congestion. (Funnily enough, the Journal never runs opinion pieces maintaining that induced demand prevents highway expansions from “solving” road congestion.) My subsequent rebuttal in Streetsblog, Paradox, Schmaradox, Congestion Pricing Works, changed David’s mind. The disincentive of the congestion toll, he told me, could probably stave off enough of the rebound in driving to allow congestion pricing to fulfill its promise of curbing gridlock.
A year later, when David revisited Jevons Paradox in a full-blown New Yorker magazine narrative, The Efficiency Dilemma, he made sure to point to “capping emissions or putting a price on carbon or increasing energy taxes” as potential ways out. I was thrilled. and I published a post in Grist riffing on “The Efficiency Dilemma.” I’ve pasted it below. I hope to comment on Conway’s NY Times essay in a future post soon.
If efficiency hasn’t cut energy use, then what?
By Charles Komanoff, reprinted from Grist, Dec. 16, 2010.
One of the most penetrating critiques of energy-efficiency dogma you’ll ever read is in this week’s New Yorker (yes, the New Yorker). “The efficiency dilemma,” by David Owen, has this provocative subtitle: “If our machines use less energy, will we just use them more?” Owen’s answer is a resounding, iconoclastic, and probably correct Yes.
Owen’s thesis is that as a society becomes more energy efficient, it becomes downright inefficient not to use more. The pursuit of efficiency is smart for individuals and businesses but a dead end for energy and climate policy.
This idea isn’t wholly original. It’s known as the Jevons paradox, and it has a 150-year history of provoking bursts of discussion before being repressed from social consciousness. What Owen adds to the thread is considerable, however: a fine narrative arc; the conceptual feat of elevating the paradox from the micro level, where it is rebuttable, to the macro, where it is more robust; a compelling case study; and the courage to take on energy-efficiency guru Amory Lovins. Best of all, Owen offers a way out: raising fuel prices via energy taxes.
Thirty-five years ago, when the energy industry first ridiculed efficiency as a return ticket to the Dark Ages, it was met with a torrent of smart ripostes like the Ford Foundation’s landmark “A Time to Choose” report — a well-thumbed copy of which adorns my bookshelf. Since then, the cause of energy efficiency has rung up one triumph after another: refrigerators have tripled in thermodynamic efficiency, energy-guzzling incandescent bulbs have been booted out of commercial buildings, and developers of trophy properties compete to rack up LEED points denoting low-energy design and operation.
Yet it’s difficult to see that these achievements have had any effect on slowing the growth in energy use. U.S. electricity consumption in 2008 was double that of 1975, and overall energy consumption was up by 38 percent. True, during this time U.S. population grew by 40 percent, but we also outsourced much of our manufacturing to Asia. In any case, efficiency, the assertedly immense resource that lay untapped in U.S. basements, garages, and offices, was supposed to slash per capita energy use, not just keep it from rising. Why hasn’t it? And what does that say for energy and climate policy?
A short form of the Jevons paradox, and a good entry point for discussing it, is the “rebound effect” — the tendency to employ more of something when efficiency has effectively cut its cost. The rebound effect is a staple of transportation analysis, in two separate forms. One is the rebound in gallons of gas consumed when fuel-efficiency standards have reduced the fuel cost to drive a mile. The other is the rebound from the reduction in car trips after imposition of a road toll, now that the drop in traffic has made it possible to cover the same ground in less time.
Rebound effect one turns out to be small. As UC-Irvine economics professor Ken Small has shown, no more than 20 percent of the gasoline savings from improved engine efficiency have been lost to the tendency to drive more miles — and much less in the short term. Rebound effect two is more significant and becoming more so, as time increasingly trumps money in the decision-making of drivers, at least better-off ones.
Rebound effects, then, vary in magnitude from one sector to another. They can be tricky to analyze, as Owen unwittingly demonstrated in an ill-considered 2009 Wall Street Journal op-ed criticizing congestion pricing, “How traffic jams help the environment.” He wrote:
If reducing [congestion via a toll] merely makes life easier for those who drive, then the improved traffic flow can actually increase the environmental damage done by cars, by raising overall traffic volume, encouraging sprawl and long car commutes.
Not so, as I wrote in “Paradox, schmaradox. Congestion pricing works”:
When the reduction in traffic is caused by a congestion charge, life is not just easier for those who continue driving but more costly as well. Yes, there’s a seesaw between price effects and time effects, but setting the congestion price at the right point will rebalance the system toward less driving, without harming the city’s economy.
Rebound effects from more fuel-efficient vehicles, as depicted in “Energy sufficiency and rebound effects,” a 2018 concept paper by Steve Sorrell, Univ. of Sussex, and Birgitta Gabersleben & Angela Druckman, Univ. of Surrey, UK.
More importantly, as Owen points out in his New Yorker piece, a narrow “bottom up” view — one that considers people’s decision-making in isolated realms of activity one-by-one — tends to miss broader rebound effects. On the face of it, doubling the efficiency of clothes washers and dryers shouldn’t cause the amount of laundering to rise more than slightly. But consider: 30 years ago, an urban family of four would have used the washer-dryer in the basement or at the laundromat, forcing it to “conserve” drying to save not just quarters but time traipsing back and forth. Since then, however, efficiency gains have enabled manufacturers to make washer-dryers in apartment sizes. We own one, and find ourselves using it for “spot” situations — emergencies that aren’t really emergencies, small loads for the item we “need” for tomorrow — that add more than a little to our total usage. And who’s to say that the advent of cheap and rapid laundering hasn’t contributed to the long-term rise in fashion-consumption, with all it implies for increased energy use through more manufacturing, freight hauling, retailing, and advertising?
Owen offers his own big example. Interestingly, it’s not computers or other electronic devices. It’s cooling. In an entertaining and all-too-brief romp through a half-century of changing mores, he traces the evolution of refrigeration and its “fraternal twin,” air conditioning, from rare, seldom-used luxuries then, to ubiquitous, always-on devices today:
My parents’ [first fridge] had a tiny, uninsulated freezer compartment, which seldom contained much more than a few aluminum ice trays and a burrow-like mantle of frost … The recently remodeled kitchen of a friend of mine contains an enormous side-by-side refrigerator, an enormous side-by-side freezer, and a drawer-like under-counter mini-fridge for beverages. And the trend has not been confined to households. As the ability to efficiently and inexpensively chill things has grown, so have opportunities to buy chilled things — a potent positive-feedback loop. Gas stations now often have almost as much refrigerated shelf space as the grocery stores of my early childhood; even mediocre hotel rooms usually come with their own small fridge (which, typically, either is empty or — if it’s a minibar — contains mainly things that don’t need to be kept cold), in addition to an icemaker and a refrigerated vending machine down the hall.
Air conditioning has a similar arc, ending with Owen’s observation that “access to cooled air is self-reinforcing: to someone who works in an air-conditioned office, an un-air-conditioned house quickly becomes intolerable, and vice versa.”
If Owen has a summation, it’s this:
All such increases in energy-consuming activity [driven by increased efficiency] can be considered manifestations of the Jevons paradox. Teasing out the precise contribution of a particular efficiency improvement isn’t just difficult, however; it may be impossible, because the endlessly ramifying network of interconnections is too complex to yield readily to empirical, mathematics-based analysis. [Emphasis mine.]
Defenders of efficiency will call “endlessly ramifying network” a cop-out. I’d say the burden is on them to prove otherwise. Based on the aggregate energy data mentioned earlier, efficiency advocates have been winning the micro battles but losing the macro war. Through engineering brilliance and concerted political and regulatory advocacy, we have increased energy-efficiency in the small while the society around us has grown monstrously energy-inefficient and cancelled out those gains. Two steps forward, two steps back.
I wrote something roughly similar five years ago in a broadside against my old colleague, Amory Lovins:
[T]hough Amory has been evangelizing “the soft path” for thirty years, his handful of glittering successes have only evoked limited emulation. Why? Because after the price shocks of the 1970s, energy became, and is still, too darn cheap. It’s a law of nature, I’d say, or at least of Economics 101: inexpensive anything will never be conserved. So long as energy is cheap, Amory’s magnificent exceptions will remain just that. Thousands of highly-focused advocacy groups will break their hearts trying to fix the thousands of ingrained practices that add up to energy over-consumption, from tax-deductible mortgages and always-on electronics to anti-solar zoning codes and un-bikeable streets. And all the while, new ways to use energy will arise, overwhelming whatever hard-won reductions these Sisyphean efforts achieve.
I wrote that a day or two after inviting Lovins to endorse putting carbon or other fuel taxes front-and-center in energy advocacy. He declined, insisting that “technical efficiency” could be increased many-fold without taxing energy to raise its price. Of course it has, can, and will. But is technical efficiency enough? Owen asks us to consider whether a strategy centered on technical and regulatory measures to boost energy efficiency may be inherently unsuited for the herculean task of keeping coal and other fossil fuels safely locked in the ground.
I said earlier that Owen offers an escape from the Jevons paradox, and he does: “capping emissions or putting a price on carbon or increasing energy taxes.” It’s hardly a clarion call, and it’s not the straight carbon taxers’ line. But it’s a lifeline.
The veteran English economist Len Brookes told Owen:
When we talk about increasing energy efficiency, what we’re really talking about is increasing the productivity of energy. And, if you increase the productivity of anything, you have the effect of reducing its implicit price, because you get more return for the same money — which means the demand goes up.
The antidote to the Jevon paradox, then, is energy taxes. We can thank Owen not only for raising a critical, central question about energy efficiency, with potential ramifications for energy and climate policy, but for giving us a brief — an eloquent and powerful one — for a carbon tax.
Author’s present-day (Feb. 22, 2024) note: I overdid it somewhat in belittling energy efficiency’s impacts on U.S. energy use in that 2010 Grist post. Indeed, in posts here in 2016 and again in 2020 I quantified and enthused over improved EE’s role in stabilizing electricity demand and slashing that sector’s carbon emissions.
More than 60 global companies, including Apple, Amazon, BYD, Salesforce, Mars, and Schneider Electric, are pushing back against proposed changes to global emissions reporting rules. The group is calling for more flexibility under the Greenhouse Gas Protocol (GHG Protocol), the most widely used framework for measuring corporate carbon footprints.
The companies submitted a joint statement asking that new requirements, especially those affecting Scope 2 emissions, remain optional rather than mandatory. Their letter stated:
“To drive critical climate progress, it’s imperative that we get this revision right. We strongly urge the GHGP to improve upon the existing guidance, but not stymie critical electricity decarbonization investments by mandating a change that fundamentally threatens participation in this voluntary market, which acts as the linchpin in decarbonization across nearly all sectors of the economy. The revised guidance must encourage more clean energy procurement and enable more impactful corporate action, not unintentionally discourage it.”
The debate comes at a critical time. Corporate climate disclosures now influence trillions of dollars in capital flows, while stricter reporting rules are being introduced across major economies.
The Rulebook for Carbon: What the GHG Protocol Is and Why It’s Being Updated
The Greenhouse Gas Protocol is the world’s most widely used system for measuring corporate emissions. It is used by over 90% of companies that report greenhouse gas data globally, making it the foundation of most climate disclosures.
It divides emissions into three categories:
- Scope 1: Direct emissions from operations
- Scope 2: Emissions from purchased electricity
- Scope 3: Emissions across the value chain
The current Scope 2 rules were introduced in 2015, but energy markets have changed since then. Renewable energy has expanded, and companies now play a major role in funding clean power.
Corporate buyers have already supported more than 100 gigawatts (GW) of renewable energy capacity globally through voluntary purchases. This shows how influential the current system has been.
The GHG Protocol is now updating its rules to improve accuracy and transparency. The revision process includes input from more than 45 experts across industry, government, and academia, reflecting its global importance.
Scope 2 Shake-Up: The Battle Over Real-Time Carbon Tracking
The proposed update would shift how companies report electricity emissions. Instead of using flexible systems like renewable energy certificates (RECs), companies would need to match their electricity use with clean energy that is:
- Generated at the same time, and
- Located in the same grid region.
This is known as “24/7” or hourly or real-time matching. It aims to reflect the actual impact of electricity use on the grid. Companies, including Apple and Amazon, say this shift could create challenges.
According to industry feedback, stricter rules could raise energy costs and limit access to renewable energy in some regions. It can also slow corporate investment in new clean energy projects.
The concern is that many markets do not yet have enough renewable supply for real-time matching. Infrastructure for tracking hourly emissions is also still developing.
This creates a key tension. The new rules could improve accuracy and reduce greenwashing. But they may also make it harder for companies to scale clean energy quickly.
The outcome will shape how companies measure emissions, invest in renewables, and meet net-zero targets in the years ahead.
Why More Than 60 Companies Oppose the Changes
The companies argue that stricter rules could slow climate progress rather than accelerate it. Their main concern is cost and feasibility. Many regions still lack enough renewable energy to support real-time matching. For global companies, aligning energy use across different grids is complex.
In their joint statement, the group warned that mandatory changes could:
- Increase electricity prices,
- Reduce participation in voluntary clean energy markets, and
- Slow investment in renewable energy projects.
They argue that current market-based systems, such as RECs, have helped scale clean energy quickly over the past decade. Removing flexibility could weaken that momentum.
This reflects a broader tension between accuracy and scalability in climate reporting.
Big Tech Pushback: Apple and Amazon’s Climate Progress
Despite their push for flexibility, both companies have made measurable progress on emissions reduction.
Apple reports that it has reduced its total greenhouse gas emissions by more than 60% compared to 2015 levels, even as revenue grew significantly. The company is targeting carbon neutrality across its entire value chain by 2030. It also reported that supplier renewable energy use helped avoid over 26 million metric tons of CO₂ emissions in 2025 alone.
In addition, about 30% of materials used in Apple products in 2025 were recycled, showing a shift toward circular manufacturing.
Amazon has also set a net-zero target for 2040 under its Climate Pledge. The company is one of the world’s largest corporate buyers of renewable energy and continues to invest heavily in clean power, logistics electrification, and low-carbon infrastructure.
Both companies argue that flexible accounting frameworks have supported these investments at scale.
The Bigger Challenge: Scope 3 and Digital Emissions
The debate over Scope 2 reporting is only part of a larger issue. For most large companies, Scope 3 emissions account for more than 70% of total emissions. These include supply chains, product use, and outsourced services.
In the technology sector, emissions are rising due to:
- Data centers,
- Cloud computing, and
- Artificial intelligence workloads.
Global data centers already consume about 415–460 terawatt-hours (TWh) of electricity per year, equal to roughly 1.5%–2% of global power demand. This figure is expected to increase sharply. The International Energy Agency estimates that data center electricity demand could double by 2030, driven largely by AI.
This creates a major reporting challenge. Even with cleaner electricity, total emissions can rise as digital demand grows.
Climate Reporting Rules Are Tightening Globally
The pushback comes as climate disclosure requirements are expanding and becoming more standardized across major economies. What was once voluntary ESG reporting is steadily shifting toward mandatory, audit-ready climate transparency.
In the European Union, the Corporate Sustainability Reporting Directive (CSRD) is now active. It requires large companies and, later, listed SMEs, to share detailed sustainability data. This data must match the European Sustainability Reporting Standards (ESRS). This includes granular reporting on emissions across Scope 1, 2, and increasingly Scope 3 value chains.
In the United States, the Securities and Exchange Commission (SEC) aims for mandatory climate-related disclosures for public companies. This includes governance, risk exposure, and emissions reporting. However, some parts of the rule face legal and political scrutiny.
The United Kingdom has included climate disclosure through TCFD requirements. Now, it is moving toward ISSB-based global standards to make comparisons easier. Similarly, Canada is progressing with ISSB-aligned mandatory reporting frameworks for large public issuers.
In Asia, momentum is also accelerating. Japan is introducing the Sustainability Standards Board of Japan (SSBJ) rules that match ISSB standards. Meanwhile, China is tightening ESG disclosure rules for listed companies through updates from its securities regulators. Singapore has also mandated climate reporting for listed companies, with phased Scope 3 expansion.
A clear trend is forming across jurisdictions: climate disclosure is aligning with ISSB global standards. There’s a growing focus on assurance, comparability, and transparency in value-chain emissions.
This regulatory tightening raises the bar significantly for corporations. The challenge is clear. Companies must:
- Align with multiple evolving disclosure regimes,
- Ensure emissions data is verifiable and auditable, and
- Expand reporting across complex global supply chains.
Balancing operational growth with compliance is becoming increasingly complex as climate regulation converges and intensifies worldwide.
A Turning Point for Global Carbon Accounting
The outcome of this debate could shape global carbon accounting standards for years.
If stricter rules are adopted, emissions reporting will become more precise. This could improve transparency and reduce greenwashing risks. However, it may also increase compliance costs and limit flexibility.
If the proposed changes remain optional, companies may continue using current accounting methods. This could support faster clean energy investment, but may leave gaps in reporting accuracy.
The new rules could take effect as early as next year, making this a near-term decision for global companies.
The push by Apple, Amazon, and other companies highlights a key tension in climate strategy. On one side is the need for accurate, real-time emissions reporting. On the other is the need for flexible systems that support large-scale clean energy investment.
As digital infrastructure expands and energy demand rises, how emissions are measured will matter as much as how they are reduced. The next phase of climate action will depend not just on targets—but on the systems used to track them.
The post Apple, Amazon Lead 60+ Firms to Ease Global Carbon Reporting Rules appeared first on Carbon Credits.
Carbon Footprint
Mastercard Beats 2025 Emissions Targets as Revenue Rises 16%, Breaking the Growth vs Carbon Trade-Off
Mastercard says it has exceeded its 2025 emissions reduction targets while continuing to grow its global business. The company reduced emissions across its operations even as revenue increased strongly in 2025.
The update comes from Mastercard’s official sustainability and technology disclosure published in 2026. It confirms progress toward its long-term goal of net-zero emissions by 2040, covering its full value chain.
The results are important for the financial technology sector. Digital payments depend heavily on data centers and cloud systems, which are energy-intensive and linked to rising global emissions.
Breaking the Pattern: Emissions Fall While Revenue Rises
In 2025, Mastercard surpassed its interim climate targets compared with a 2016 baseline. The company reported a 44% reduction in Scope 1 and Scope 2 emissions, beating its target of 38%. It also achieved a 46% reduction in Scope 3 emissions, far exceeding its 20% target.
At the same time, Mastercard recorded 16% revenue growth in 2025. This shows that emissions reductions continued even as the business expanded. Mastercard Chief Sustainability Officer Ellen Jackowski and Senior Vice President of Data and Governance Adam Tenzer wrote:
“These results reflect a comprehensive approach built on renewable energy investment and procurement, supply chain engagement, and embedding environmental sustainability into everyday business decisions.”
The company also reported a 1% year-on-year decline in total emissions, marking the third consecutive year of emissions reduction. This is important because digital payment networks usually grow with higher computing demand.
Mastercard says this trend reflects improved efficiency across its operations, better infrastructure use, and increased reliance on cleaner energy sources.
The Hidden Footprint: Why Data Centers Drive Mastercard’s Emissions
A large share of Mastercard’s emissions comes from its digital infrastructure. According to the company’s sustainability report, data centers account for about 60% of Scope 1 and Scope 2 emissions. Technology-related goods and services make up roughly one-third of Scope 3 emissions.
This reflects how modern financial systems operate. Digital payments, fraud detection, and AI-based analytics require a large-scale computing infrastructure.
Global data centers already consume about 415–460 TWh of electricity per year, equal to roughly 1.5%–2% of global electricity demand. This number is expected to rise as AI usage expands.
Mastercard’s challenge is similar to that of other digital companies. Higher transaction volume usually leads to greater computing needs. This can raise emissions unless we improve efficiency.
To manage this, the company is focusing on renewable energy procurement, hardware consolidation, and more efficient software systems.
Carbon-Aware Technology Becomes Core to Operations
Mastercard is integrating sustainability directly into its technology systems rather than treating it as a separate reporting function. Since 2023, the company has developed a patent-pending system that assigns a Sustainability Score to its technology infrastructure. This system measures environmental impact in real time.
It tracks factors such as:
- Energy use in kilowatt-hours,
- Regional carbon intensity of electricity,
- Server utilization rates,
- Hardware lifecycle efficiency, and
- Data processing location.
This allows engineers to design systems with lower carbon impact.
The company also uses carbon-aware software design. This means computing workloads can be adjusted to reduce energy use when carbon intensity is high in certain regions.
This approach reflects a wider trend in the technology and financial sectors. More companies are now including carbon tracking in their main infrastructure choices. They no longer see it just as a reporting task.
Powering Payments: Mastercard’s Net-Zero Playbook
Mastercard has committed to reaching net-zero emissions by 2040, covering Scope 1, Scope 2, and Scope 3 emissions across its value chain. The target is aligned with science-based climate pathways and includes operations, suppliers, and technology infrastructure.
To achieve this, the company is focusing on four main areas.
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Increasing renewable energy use in operations
Mastercard already powers its global operations with 100% renewable electricity. This covers offices and data centers in multiple regions.
The company has also achieved a 46% reduction in total Scope 1, 2, and 3 emissions compared to its 2016 baseline. It continues to use renewable energy purchasing to maintain this progress.
In 2024, Mastercard procured over 112,000 MWh of renewable electricity, supporting lower emissions from its global operations.
-
Improving energy efficiency in data centers
Data centers account for about 60% of Mastercard’s Scope 1 and 2 emissions. To reduce this, Mastercard is upgrading servers, cutting unused computing capacity, and improving workload efficiency. It also uses real-time monitoring to reduce energy waste.
These improvements helped keep operational emissions stable in 2024, even as computing demand increased. Efficiency gains combined with renewable energy use supported this outcome.
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Working with suppliers to reduce emissions
Around 75%–76% of Mastercard’s total emissions come from its value chain. This includes cloud providers, technology partners, and hardware suppliers.
To address this, Mastercard works with suppliers to set emissions targets and improve reporting. More than 70% of its suppliers now have their own climate reduction goals.
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Upgrading and consolidating hardware systems
Mastercard is reducing emissions by improving its hardware systems. It decommissions unused servers, consolidates infrastructure, and shifts to more efficient cloud platforms.
Technology goods and services account for about one-third of Scope 3 emissions. By reducing unnecessary hardware and extending equipment life, Mastercard lowers both energy use and manufacturing-related emissions while maintaining system performance.
Renewable energy procurement is central to its strategy. It’s crucial for powering data centers, as they account for most of their operational emissions.
Mastercard works with suppliers because a large part of emissions comes from the value chain. This includes technology manufacturing and cloud services. By 2025, the company exceeded several short-term climate goals. This shows early progress on its long-term net-zero path.
ESG Pressure Hits Fintech: The New Rules of Digital Finance
Mastercard’s results come during a period of rising ESG pressure across the financial sector. Banks, payment networks, and fintech companies must now disclose emissions. This is especially true for Scope 3 emissions, which cover supply chain and digital infrastructure impacts.
Several global trends are shaping the industry:
- Growing regulatory focus on climate disclosure,
- Rising investor demand for ESG transparency,
- Expansion of digital payments and cloud computing, and
- Increased energy use from AI and data processing.
Data centers are becoming a major focus area because they link financial services to energy consumption. In Mastercard’s case, they are the largest source of operational emissions.
At the same time, financial institutions are expected to align with net-zero targets between 2040 and 2050. This depends on regional regulations and climate frameworks. Mastercard’s early progress places it ahead of many peers in meeting short-term emissions goals.
Decoupling Growth From Emissions
One of the most important signals from Mastercard’s 2025 results is the separation of business growth from emissions.
The company achieved 16% revenue growth while reducing total emissions by 1% year-on-year. This marks a continued pattern of emissions decline alongside business expansion.
Mastercard attributes this to improved system efficiency, renewable energy use, and better infrastructure management. In simple terms, the company is processing more transactions without a matching rise in emissions.
This trend is important because digital payment systems normally scale with computing demand. Without efficiency gains, emissions would typically rise with business growth.
Looking ahead, demand will continue to grow. Global payments revenue is projected to reach around $3.1 trillion by 2028, according to McKinsey & Company, growing at close to 10% annually.
Global data center electricity demand might double by 2030. This rise is mainly due to AI workloads, says the International Energy Agency. Mastercard’s results show that tech upgrades can lower the carbon impact of digital finance. This is true even as global usage rises.
The Takeaway: Fintech’s Proof That Growth and Emissions Can Split
Mastercard’s 2025 sustainability performance shows measurable progress toward its net-zero goal. At the same time, major challenges remain. Data centers continue to be the largest emissions source, and global digital activity is still expanding rapidly due to AI and cloud computing.
Mastercard’s approach shows how financial technology companies are adapting. Sustainability is no longer a separate goal. It is becoming part of how digital systems are designed and operated.
The next test will be whether these efficiency gains can continue to outpace the rapid growth of global digital payments and AI-driven financial systems.
The post Mastercard Beats 2025 Emissions Targets as Revenue Rises 16%, Breaking the Growth vs Carbon Trade-Off appeared first on Carbon Credits.
China is backing a Beijing-based startup called Orbital Chenguang with about 57.7 billion yuan ($8.4 billion) in credit lines to build space-based data centers, according to media reports. The funding comes from major state-linked banks and signals one of the largest known investments in orbital computing infrastructure.
The move highlights a growing global race to build computing systems in space. It also puts China in direct competition with companies like SpaceX, which is exploring space-based data infrastructure, too.
Orbital Chenguang Builds State-Backed Space Computing System
Orbital Chenguang is a startup in Beijing supported by the Beijing Astro-future Institute of Space Technology. This institute works with the city’s science and technology authorities.
The company has received credit line support from major Chinese financial institutions, including:
- Bank of China,
- Agricultural Bank of China,
- Bank of Communications,
- Shanghai Pudong Development Bank, and
- CITIC Bank.
These are credit lines, not fully deployed cash. But the scale shows strong institutional backing.
The project is part of a wider national strategy focused on commercial space, AI infrastructure, and advanced computing systems.
China’s state space contractor, CASC (China Aerospace Science and Technology Corporation), has shared plans under its 15th Five-Year Plan. These include ideas for large-scale space computing systems, aiming for gigawatt power.
Space Data Center Plan Targets 2035 Gigawatt Capacity
According to Chinese media reports, Orbital Chenguang plans to build a constellation in a dawn-dusk sun-synchronous orbit at 700–800 km altitude. The long-term target is a gigawatt-scale space data center by 2035.
The development plan is divided into phases:
- 2025–2027: Launch early computing satellites and solve technical barriers.
- 2028–2030: Link space-based systems with Earth-based data centers.
- 2030–2035: Scale toward large orbital computing infrastructure.
The design relies on continuous solar energy and natural cooling in space. These features could reduce reliance on land-based power grids and cooling systems.
China has proposed two satellite constellations to the International Telecommunication Union (ITU). These plans include a total of 96,714 satellites. This shows China’s long-term goals for space infrastructure and spectrum control.
The AI Energy Crunch Pushing Computing Into Orbit
The push into orbital data centers is closely linked to rising AI demand. Global data centers consumed about 415–460 terawatt-hours (TWh) of electricity in 2024, equal to roughly 1.5%–2% of global power use. This figure is rising quickly due to AI workloads.
Some industry projections show demand could exceed 1,000 TWh by 2026, nearly equal to Japan’s total electricity consumption.
AI systems require massive computing power, which increases energy use and cooling needs. In many regions, electricity supply—not hardware—is now the main constraint on AI expansion.
China’s strategy aims to address this by moving part of the computing load into space, where solar energy is more stable and continuous.
Carbon Impact: Earth vs Space Computing Trade-Off
Data centers already create a large carbon footprint. In 2024, they emitted about 182 million tonnes of CO₂, based on global electricity use of roughly 460 TWh and an average carbon intensity of 396 grams of CO₂ per kWh. This is according to the International Energy Agency report, as shown in the chart below.
Future projections show even faster growth. The sector could generate up to 2.5 billion tonnes of CO₂ emissions by 2030, driven by AI expansion. This is where orbital systems come in. They aim to reduce emissions during operation by using:
- Continuous solar energy,
- Passive cooling in vacuum conditions, and
- Reduced dependence on fossil-fuel grids.
However, space systems also introduce new emissions. Rocket launches used about 63,000 tonnes of propellant in 2022, producing CO₂ and atmospheric pollutants. Lifecycle studies suggest that over 70% of emissions from space systems typically come from manufacturing and launch activities.
In addition, hardware in orbit often has a lifespan of only 5–6 years, which increases replacement cycles and launch frequency. This creates a key trade-off:
- Lower operational emissions in space, and
- Higher lifecycle emissions from launches and manufacturing.
Research suggests that, in some scenarios, orbital computing could produce up to 10 times higher total carbon emissions than terrestrial systems when full lifecycle impacts are included.
China’s Expanding Space-Tech Ecosystem
Orbital Chenguang is not operating alone. Several Chinese companies are working on similar in-orbit computing systems, including ADA Space, Zhejiang Lab, Shanghai Bailing Aerospace, and Zhongke Tiansuan.
These firms are developing satellite-based computing and AI processing systems. This shows that orbital computing is not a single project. It is part of a broader national push across government, industry, and research institutions.
China’s space strategy combines commercial space growth with national technology planning. It aims to build integrated systems that connect satellites, cloud computing, and terrestrial networks.
The Space-AI Arms Race: China vs SpaceX vs Google
China is not alone in exploring space-based computing. Companies in the United States are also developing orbital data infrastructure concepts. These include early-stage research and private sector projects by firms such as SpaceX and Google.
SpaceX is building one of the largest satellite networks through its Starlink constellation, with thousands of satellites already in orbit. While its main goal is global internet coverage, the network also creates a foundation for future edge computing in space. The company’s reusable rockets, including Starship, are designed to lower launch costs, which is a key barrier to scaling orbital data infrastructure.
Google, through its cloud division, has been investing in space data and satellite analytics. It partners with Earth observation firms to process large volumes of data using cloud-based AI tools. This work could extend to hybrid systems where data is processed closer to where it is generated, including in orbit.
Other players are also entering the field. Amazon is developing Project Kuiper, a satellite internet network that could support future space-based computing layers. Microsoft has launched Azure Space, which connects satellites directly to cloud computing services and supports real-time data processing.
Government agencies are also involved. NASA and the U.S. Department of Defense are funding research into orbital computing, edge processing, and secure data transmission in space. These efforts aim to reduce latency, improve data security, and enable faster decision-making for both civilian and defense applications.
Together, these developments show that space-based computing is moving beyond theory. While still early-stage, both public and private sector efforts are building the foundation for future data centers and processing systems in orbit.
However, these systems face major challenges:
- High launch costs,
- Heat and thermal control issues,
- Limited data transmission bandwidth, and
- Hardware durability in space.
Despite these challenges, interest is growing because AI demand is rising faster than Earth-based infrastructure can scale. The competition is now moving toward who can solve energy and computing limits first—on Earth or in space.
Market Outlook: AI, Energy, and Space Infrastructure Converge
The global data center industry is entering a period of rapid expansion. Electricity demand from data centers could double by 2030, driven mainly by AI workloads and cloud computing growth. Power supply is becoming a limiting factor in many regions.
At the same time, the global space economy is expanding into a multi-hundred-billion-dollar industry, supported by satellites, communications, and emerging technologies like orbital computing.
- Orbital data centers sit at the intersection of three major trends: rapid AI growth, rising energy constraints, and expansion of space infrastructure.
China’s $8.4 billion credit-backed push through Orbital Chenguang signals confidence in this convergence. However, key barriers remain, such as high cost of launches, engineering complexity, short satellite lifespans (5-6 years), and regulatory uncertainty in orbital systems.
Because of these limits, orbital data centers are unlikely to replace Earth-based systems in the near term. Instead, they may form a hybrid system where some workloads move to space while most remain on Earth.
Space Is Becoming the Next Data Center Frontier
China’s investment in Orbital Chenguang marks one of the most significant moves yet in the emerging field of space-based computing. Backed by major Chinese banks, municipal science institutions, and national space contractors like CASC, the project shows how seriously China is treating orbital infrastructure.
The strategy connects AI growth, energy demand, and climate pressures into a single long-term vision. But the trade-offs are complex. Orbital data centers may reduce operational emissions, but they also introduce high lifecycle carbon costs and major technical challenges.
The global race is now underway. With companies like SpaceX, Google, and Chinese tech firms exploring similar ideas, space is becoming a new frontier for digital infrastructure. The outcome will depend on whether orbital systems can scale efficiently—and whether their carbon benefits can outweigh the emissions cost of building them.
The post China’s $8.4B Orbital Data Center Push Sets Up Space-Based AI Showdown With SpaceX appeared first on Carbon Credits.
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