Over the weekend the Washington Spectator published my essay, Diary of a Transit Miracle, recounting the arduous march of NYC congestion pricing from a gleam in a trio of prominent New Yorkers’ eyes, to the verge of startup at the stroke of midnight June 30, the startup time announced by the MTA last Friday.
I’m cross-posting it here — the third post on the subject in this space in the past 12 months (following this in December and this post last June) — because the advent of congestion pricing in the U.S. is “a really big deal,” as a number of friends and colleagues have told me in recent weeks. As my new essay makes clear, charging motorists to drive into the heart of Manhattan isn’t just a rejection of unconstrained motordom, it’s a new beachhead in “externality pricing” — social-cost surcharging — of which carbon taxes are the ultimate form.
The essay features two governors, two mayors — one of whom I served a half-century ago as a lowly but admiring data cruncher — a civic “Walter Cronkite,” a Nobel economist, raucous transit activists, a gridlock guru and yours truly, plus a cameo appearance by Robert Moses. It includes footage of the historic 1969 press conference in which Mayor John Lindsay and two distinguished associates enunciated the core idea of using externality pricing to better balance automobiles and mass transit that animated the arduous but ultimately triumphant congestion pricing campaign.
— C.K., April 29, 2024
Diary of a Transit Miracle
A miracle is coming to New York City. Beginning on July 1, and barring a last-minute hitch, motorists will soon pay a hefty $15 to enter the southern half of Manhattan — the area bounded by the Hudson River, the East River and 60th Street.
An anticipated 15 percent or so of drivers will switch to transit, unsnarling roads within the “congestion zone” and routes leading to it. The other 80 or 90 percent will grumble but continue driving. That is by design. The toll bounty, a billion dollars a year, will finance subway enhancements like station elevators and digital signals that will increase train throughput and lure more car trips onto trains.
The result will be faster, smoother commutes, especially for car drivers and taxicab and Uber passengers, who will pay a modest surcharge of $1.25 to $2.50 per trip. Drivers of for-hire vehicles will benefit as well, as lesser gridlock leads to more fares.1
The miracle is three-fold: Winners will vastly outnumber losers; New York will be made healthier, calmer and more prosperous; and that this salutary measure is happening at all, after a half-century of setbacks.
Obstacles to congestion pricing
Congestion pricing, as the policy is known, faced formidable obstacles even beyond the difficulty inherent in asking a group of people to start forking over a billion dollars a year for something that’s always been free.
Congestion pricing also had to contend with: an ingrained pro-motoring ideology that casts any restraint on driving as a betrayal of the American Dream; a general aversion to social-cost surcharges (what economists call “externality pricing”); exasperation over the region’s balkanized and convoluted toll and transit regimes; and, of late, a decline in social solidarity and appeals to the common good.
The advent of congestion pricing in New York is, thus, cause not just for celebration but wonderment. How did this wonky yet radical idea advance to the verge of enactment?
Origins
The trail begins in the waning days of 1969, when newly re-elected mayor John Lindsay recruited two well-regarded New Yorkers to devise a plan to fend off a 50 percent rise in subway and bus fares.
William Vickrey, a Canadian transplant teaching at Columbia and a future Nobel economics laureate, was a protean theorist of externality pricing. New York-bred mediator Theodore Kheel was admired as a civic Walter Cronkite for his plain-spoken common sense.
Lindsay, too often dismissed as a lightweight, understood mass transit as key to loosening automobiles’ spreading chokehold over the city. He had made combating air pollution a pillar of his first term and was fast becoming an exemplar of urban environmentalism. From his municipal engineers, Lindsay knew that technology to clean up tailpipes still lay in the future. A transit fare hike that would add yet more vehicles to city streets imperiled his clean-air agenda.
The triumvirate proposed a suite of motorist fees to preserve the fare. Their program ― higher registration fees and gasoline taxes, a parking garage tax, doubled tolls ― though mild in today’s terms, threatened powerful bureaucracies and their auto allies. Newly dethroned “master-builder” Robert Moses opined that Kheel, in his zeal to save the fare, had “gone berserk over bridge and tunnel tolls.”2 The program went nowhere.
L to R: Kheel, Lindsay, Vickrey. Click arrow to view (please excuse two brief garbled passages toward end).
Moses was right to be alarmed. From a City Hall podium on Dec. 16, 1969, Mayor Lindsay showcased Kheel’s and Vickrey’s respective reports, “A Balanced System of Transportation is a Must” and “A Transit Fare Increase is Costly Revenue.” (Click link in still photo above to view 27-minute video.) The trio propounded a new urban doctrine rebalancing automobiles and public transportation: “Automobiles are strangling our cities… Starving mass transit imposes costs that are difficult to measure, yet real… Correcting the fiscal imbalance between transit and the automobile is key to enhancing our environment and quality of life…”
Their remarks set generations of urbanists on course toward congestion pricing.
Setbacks
Quantifying those precepts became my research agenda 40 years later. In the interim, two creditable attempts to enact congestion pricing crashed and burned.
The central element of Lindsay’s 1973 “transportation control plan” was tolls on the city’s East River bridges, a measure designed to eliminate enough traffic to satisfy federal clean-air standards. Though the plan’s formal demise didn’t come until 1977, in legislation written by liberal lawmakers from Brooklyn and Queens, the toll idea never stood a chance. Electronic tolling was 20 years away, and adding stop-and-go toll booths seemed more likely to compound vehicular exhaust than to cut it.
Three decades later, in 2007, Mayor Michael Bloomberg asked Albany to toll not just the same East River bridges but also the more-trafficked 60th Street “portal” to mid-Manhattan. Predictably, faux-populist legislators saw Bloomberg’s billionaire wealth as an invitation to denounce the congestion fee as an affront to the little guy.
The mayor may have hurt his cause by presenting congestion pricing primarily as a climate and pollution measure. The pollution rationale was no longer compelling in the way it had been in Lindsay’s day, as automotive engineers had slashed rates of toxic vehicle exhaust ten-fold. Appeals tied to global warming also fell flat; remember, congestion pricing contemplated that most drivers would stay in their fossil-fuel burning cars.
This isn’t to say that congestion pricing confers no climate benefits. Rather, the benefits are subtler ones that can be hard to convey to voters, such as making climate-friendly urban living more attractive. A further benefit may come as congestion pricing demonstrates the unique power of externality pricing, as explained below.
From the Rubble
Even as Bloomberg’s toll plan was faltering in Albany, new loci of support were germinating in the city.
Changing times demanded not just the intellectual leadership of think-tanks like the Regional Plan Association and the good-government Straphangers Campaign, but gritty, grassroots transit organizing. Enter the newly-minted Riders Alliance.
2017 subway handbill exemplified new militancy targeting Gov. Andrew Cuomo for failing transit.
As subway service began cratering in 2015, the inevitable result of budget-raiding by a skein of governors, the Alliance posted crowd-sourced photos of stalled trains and jammed platforms alongside demands for improved service from “#CuomosMTA.” Before long, the papers were pointing the finger at the governor not just in “Why Your Commute Is Bad” explainers but in tear-jerkers like the Times’ May 2017 classic, “Money Out of Your Pocket”: New Yorkers Tell of Subway Delay Woes.
The drumbeat was deafening. Cuomo finally blinked. On a Sunday in August 2017, he phoned the Times’ Albany bureau chief and handed him a scoop for the next day’s front page: Cuomo Calls Manhattan Traffic Plan an Idea ‘Whose Time Has Come’.
The “traffic plan” was congestion pricing.
Data Cruncher
Two months later, Cuomo’s staff summoned me to the midtown office of the consulting firm they had retained to “scope” congestion pricing ― essentially, to compute how much revenue tolls could generate. They wanted to see if an Excel spreadsheet model I had constructed and refined over the prior decade could aid their scoping process.
The model was called the Balanced Transportation Analyzer, a name bestowed in 2007 by Ted Kheel.
Ted, in his nineties, had recruited me to determine whether a large enough congestion toll could pay to make city transit free. The idea worked on paper but foundered politically. Nevertheless, Ted saw in my Excel modeling a way to capture phenomena like “rebound effects” (motorists driving more as road space frees up) and “mode switching” between cars, trains, buses and taxicabs, that he and Prof. Vickrey had identified in their 1969 work but lacked the computing ability to quantify.
Ted’s philanthropy enabled me over the next decade to expand, test and update my transportation modeling. With a hundred “tabs” and 160,000 equations, the “BTA” can instantly answer almost any conceivable question about New York congestion pricing, as well as these two central ones: how much revenue it will yield, and how much time will travelers save in lightened traffic and better transit.3
The BTA model aced its 2017 audition and became the computational engine for the congestion pricing legislation the governor’s team enacted into law in 2019. Its impact has been even broader.4 “Having the model helped make the case with the public, journalists, elected officials and others,” Eric McClure, director of the livable-streets advocacy group StreetsPAC, wrote recently, in part by helping congestion pricing proponents push back on opponents’ exaggerated claims of disastrous outcomes and their incessant demands for special treatment. The model may also have influenced the detailed toll design adopted by the MTA board earlier this year, which hewed close to the toll design I had recommended last summer.5
The BTA also provided sustenance during congestion pricing’s seven lean years ― the 2009-2016 period in which the torch was kept lit by a new triumvirate known as “Move NY” ― traffic guru “Gridlock” Sam Schwartz, the very able campaign strategist Alex Matthiessen, and myself. The model helped our team evangelize congestion pricing’s transformative benefits to elected officials and the public. This, I believe, was a key element in mustering the critical mass of support that ultimately swayed not one but two governors.
The Hochul Factor
New York Lieutenant Governor Kathy Hochul’s ascension to governor in August 2021 could have been congestion pricing’s death knell. The toll plan was adrift in the federal bureaucracy, and its latter-day champion Andrew Cuomo had exited in “me-too” disgrace. His successor, from distant Buffalo, wasn’t beholden to New York or congestion pricing.
Hochul, who as governor controls city and regional transit, could have disowned congestion pricing as convoluted, bureaucratic and tainted. Instead, she became a resolute and enthusiastic backer. Her spirited support, both in public and behind the scenes, became the decisive ingredient in shepherding congestion pricing to safety.
Why the new governor went all-in on congestion pricing awaits a future journalist or historian. Had she spurned it, the opprobrium from downstate transit advocates would have been intense; but there doubtless would have been cries of “good riddance” as well. Vickrey, Kheel and Riders Alliance notwithstanding, it’s not clear how closely New Yorkers — including transit users — connect congestion tolls to improved travel and a better city.
What makes Hochul’s embrace especially impressive is that congestion pricing is, in a real sense, an attack on a jealously guarded entitlement: the right to inconvenience others by usurping public space for one’s vehicle. The classic lament about entitlements’ iron grip is that “losers cry louder than winners sing.”6 Yet in this case, it seems, potential losers — actual and aspiring zone-bound drivers — are being out-sung by transit interests seeking, in Kheel’s 1969 words, a better balance between public transportation and automobiles.
Credits and Prospects
Let us now praise Andrew Cuomo’s crafting of the legislation that teed up congestion pricing’s successful run.
Rather than specifying a dollar price for the tolls, or a precise traffic reduction, his 2019 bill established a revenue target: sufficient earnings to bond $15 billion in transit investment — which equates to $1 billion a year to cover debt service. This device trained the public’s focus on the gain from congestion pricing (better transit) instead of the pain (the toll). Equally important, with this deft stroke, any toll exemption that a vocal minority might seek would mathematically trigger higher tolls for everyone else. The effect was vastly heightened scrutiny of requests for carve-outs.
Which cities will follow on New York’s heels? No U.S. urban area comes close to our trifecta of gridlock, transit and wealth. Sprawling Los Angeles or Houston, or even Chicago for that matter, might be better served by more granulated traffic tolls than New York’s all-or-none model.
Perhaps Asia’s megalopolises will be swept up in our wake. In the meantime, my focus will be on the holy grail of externality pricing: taxing carbon emissions. Every economist knows that the surest and fastest way to cut down on a “bad” is by taxing it rather than subsidizing possible alternatives. Yet that approach remains counter-intuitive and even anathema to nearly everyone else.
A huge and important legacy that New York congestion pricing could provide is to prove that intelligently taxing societal harms need not be electoral suicide. This proof could help unlock a treasure-trove of prosperity-enhancing pricing reforms including, most prominently, robust carbon taxing.
The author, a policy analyst based in New York City, worked in Mayor Lindsay’s Environmental Protection Administration in 1972-1974. He met Bill Vickrey in 1991 and worked closely with Ted Kheel from 2007 to 2010.
Endnotes
- The new passenger surcharges of $1.25 for taxicabs and $2.50 for “ride-hails” (principally Ubers) apply to trips touching the congestion zone. These will be partially offset by lower fares owing to shorter wait-time charges due to faster travel speeds.
- Quote is from Moses’ August 23, 1969 guest essay in Newsday, “Is Rubber to Pay for Rails?” (not digitally available).
- The current version of the BTA is publicly available at this link: (18 MB Excel file).
- See Fix NYC Advisory Panel Report, Appendix B, 2019.
- A Congestion Toll New York Can Live With, July 2023, by Charles Komanoff, co-authored with Columbia Business School economist Gernot Wagner.
- As pronounced by University of Michigan economist Joel Slemrod, in Goodbye, My Sweet Deduction, New York Times, by Eduardo Porter and David Leonhardt, Nov. 3, 2005.
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.
-
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.
-
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.
-
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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