What if you could measure how fast the entire world economy is learning to do more with less? This paper applies Wright’s Law — the observation that costs fall predictably with cumulative production — to the global economy itself, treating 60 years of GDP, energy, carbon, and material data as one enormous experience curve. The results: the world’s energy learning rate is 18.3%, its carbon learning rate 22.2%, and its material learning rate 6.5%. Every doubling of cumulative economic output makes us measurably more efficient.
But the Paris Agreement demands a carbon learning rate of 52% — more than double the historical pace. Closing that gap requires not just incremental improvement but a fundamental acceleration, including gigaton-scale carbon dioxide removal. The paper quantifies the CDR investment needed ($1.7T–$12.1T through 2050, or just 0.17% of annual GWP in the base case) and maps the policy levers most likely to bend the curve. With 25 original figures and a novel “inclusive learning rate” that accounts for environmental damage costs, this is the first systematic attempt to give the planet a single performance metric for sustainability.
5 publications
Treating the global economy as a single super-technological system, this paper estimates Wright’s Law experience curves for energy intensity (18.3% learning rate), carbon intensity (22.2%), and material intensity (6.5%). With every doubling of cumulative GDP, the world systematically learns to produce more output per unit of energy, carbon, and materials. A novel “inclusive” learning rate incorporating environmental damage costs yields 12.4% — substantially below the 52% rate required to meet Paris Agreement targets.
Includes 25 original figures, CDR cost scenarios ($1.7T–$12.1T through 2050), and policy analysis showing the gap between historical learning and the acceleration needed for 1.5°C. Available as PDF with embedded figures and Word document.
The first systematic experience curve estimates for carbon removal technologies and AI, alongside 150 established technologies. Median learning rate across all technologies: 20.9%. The analysis provides a quantitative basis for understanding how technology costs decline with cumulative deployment — essential knowledge for investors, policymakers, and anyone betting on the future cost of clean energy, carbon capture, or computing.
The arithmetic of net zero is unforgiving. Achieving gigaton-scale carbon dioxide removal demands deployment curves that dwarf anything the energy sector has managed, and the policy architecture to finance them barely exists. This restructured analysis maps the scaling pathways, cost trajectories, and institutional mechanisms needed to close the gap between climate ambition and removal capacity.
The 2026 update incorporates fresh data on technology learning rates, revised cost curves, and an expanded treatment of the procurement mandates and advance market commitments most likely to accelerate deployment. For policymakers debating carbon-removal targets and investors sizing the opportunity, the central finding is clear: the ramp must steepen considerably, and the window for building it is narrowing.
Well-intentioned climate policies have a way of producing unintended consequences. This paper examines how regulatory interventions — carbon pricing floors, technology mandates, subsidy regimes — create both windfalls and dead weight across the carbon-removal landscape. By modelling project viability under a matrix of policy scenarios, the authors expose the fault lines where good intentions collide with economic reality, forcing errors that distort capital allocation and slow the very transition they aim to hasten.
Yet the picture is not uniformly bleak. The analysis also identifies "forced gains" — instances where cleverly designed policy constraints unlock latent economic capacity that markets alone would leave stranded. The distinction matters enormously for regulators drafting the next generation of climate frameworks: the difference between a forced error and a forced gain often comes down to a few well-chosen design parameters.
Carbon markets suffer from a structural irony: instruments designed to harness the efficiency of decentralised exchange remain stubbornly fragmented, illiquid, and opaque. This paper argues that the missing ingredient is network capital — the self-reinforcing value that accrues when market participants, registries, and verification bodies form dense, well-connected webs of trust and information flow.
Where conventional approaches to carbon-market reform focus on price signals and compliance thresholds, this framework redirects attention to the connective tissue — the standards, data protocols, and interoperability agreements — that determines whether a market functions as a coherent whole or a collection of isolated pools. For policymakers seeking to link regional carbon markets into something resembling a global system, the network-capital lens offers both a diagnostic and a blueprint.
6 frameworks
Carbon data is everywhere but none of it speaks the same language. COMET is a free, open, community-governed meta-ontology that maps product-level carbon footprint data, supply chain verification endpoints, Environmental Attribute Certificates, and market-pricing signals into a single interoperable knowledge graph. Seven semantic layers from core identity primitives to market pricing signals, aligned with ISO 14067, PACT v3, GHG Protocol, EU CBAM, and more.
The ontology is accompanied by a 200-step Master Build Plan across 10 expert panels, a 30-slide stakeholder deck, and a 36-month roadmap to v1.0 stable. COMET builds on the Carbon at Risk (CaR) framework, extending risk measurement into a full ontological infrastructure for treating carbon as a financially tradeable, risk-adjusted asset class. Licensed CC BY 4.0 + Apache 2.0.
Originated by Nick Gogerty at Carbon Finance Labs, Carbon at Risk applies Value-at-Risk methodology from financial markets to carbon removal. Rather than binary classifications (permanent vs. non-permanent, nature-based vs. engineered), CaR provides nuanced risk assessment across different removal methods by quantifying two critical dimensions: delivery risk (whether promised removal occurs) and storage risk (whether removed carbon remains sequestered long-term).
The framework enables portfolio-based climate strategies, allowing institutions to diversify across carbon removal technologies with quantified risk profiles. Developed in collaboration with the University of Exeter and LSE's Grantham Institute, with backing from 20+ financial institutions, insurers, and standards bodies. Includes an interactive CaR Calculator for comparing risk profiles across removal methods.
Institutional buyers of carbon removal face a portfolio problem not unlike that of asset managers: how to diversify across technologies, geographies, and risk profiles while meeting a specific performance target. CaRPS offers a capacity-scaling tool that helps institutions move beyond ad hoc credit purchases toward strategic portfolio construction, complete with integrated risk assessment and technology diversification models.
Version 2.1 refines the framework's metrics and extends its applicability to a broader range of institutional contexts, from corporate net-zero commitments to sovereign climate funds. The standard is deliberately pragmatic — less a theoretical exercise than a working instrument designed to be adopted, stress-tested, and improved upon. In a market awash with pledges but short on delivery mechanisms, that practicality is its chief virtue.
Switzerland occupies an unusual position in the global climate landscape: a small, wealthy, services-oriented economy with ambitious emissions targets, a sophisticated financial sector, and a long tradition of regulatory precision. This framework translates the general principles of carbon-market design into the specific context of Swiss law, institutions, and economic structure.
The result is less a theoretical blueprint than a practical implementation guide, mapping the regulatory interfaces between Swiss environmental law and financial regulation, and identifying the institutional arrangements needed to ensure that carbon credits traded in Zurich meet the same standards of integrity demanded of any other financial instrument. For other small, open economies considering similar frameworks, the Swiss case offers a useful — if characteristically meticulous — template.
Trust is the scarcest commodity in carbon markets. Buyers cannot easily verify that a credit represents a genuine, additional, and permanent tonne of CO₂ removed or avoided. Sellers struggle to differentiate high-quality projects from dubious ones. The resulting information asymmetry depresses prices, deters institutional capital, and undermines the market's claim to environmental integrity. CarbonGrade addresses this deficit head-on with a standardised grading system modelled on the ratings frameworks that underpin bond and equity markets.
The analogy with financial ratings is deliberate — and instructive. Just as credit ratings compress complex default probabilities into an accessible signal, CarbonGrade compresses the multidimensional quality of a carbon credit — its additionality, permanence, measurement rigour, and co-benefits — into a transparent, comparable score. The framework's ambition is structural: not merely to rank individual credits, but to provide the trust infrastructure on which a liquid, scalable, and credible carbon market can be built.
Corporate balance sheets have long treated the atmosphere as a free dumping ground — an accounting convention that is becoming untenable. The concept of environmental liabilities proposes that the carbon emitted in producing goods and services should be tracked through supply chains and recognised on financial statements with the same rigour applied to debt, lease obligations, or pension commitments. This illustrated guide walks readers through the mechanics of how E-Liabilities would be measured, reported, and ultimately priced.
The implications extend well beyond accounting standards. If environmental liabilities were recognised with the same discipline as financial ones, the effects would ripple through procurement decisions, capital allocation, and corporate strategy. Products with high embedded carbon would carry visible costs; supply chains would face pressure to decarbonise not from regulation alone but from the internal logic of the balance sheet. CarbonGrade provides the measurement architecture to make this tractable.
1 publication
For legislators and regulators pressed for time — which is to say, nearly all of them — this policy brief distils the CarbonGrade framework into its essential elements: the problem of information asymmetry in carbon markets, the proposed grading methodology, and the regulatory interventions needed to embed standardised quality signals into market infrastructure. The aim is not academic completeness but actionable clarity.
The brief makes a pointed argument for regulatory engagement rather than laissez-faire. Left to their own devices, carbon markets have shown limited capacity to solve their own quality problem — a finding consistent with decades of experience in financial markets, where rating systems emerged only through a combination of private innovation and regulatory mandate. The implication is that credible carbon-credit grading will require not just good methodology but institutional backing.
1 resource
A picture, as the saying goes, is worth a thousand tonnes of carbon — or at least a thousand words of framework documentation. This infographic condenses the CarbonGrade methodology, its grading criteria, and its implementation architecture into a single visual narrative, designed for the conference panel, the boardroom presentation, and the policy brief annex where decisions are shaped as much by clarity of communication as by depth of analysis.
The visual format serves a strategic purpose beyond mere convenience. Carbon markets are notoriously opaque, and one of the chief barriers to adoption of quality standards is the difficulty of explaining what they measure and why they matter. By rendering the CarbonGrade framework in accessible, visual terms, this resource lowers the barrier to understanding — and, by extension, to the institutional adoption on which the framework's credibility ultimately depends.
1 interactive explorer
An interactive research tool for exploring experience curves across 155 technologies — from solar PV (20.5% learning rate) to GPU compute (88.5%) to nuclear electricity (−88.1%, the original “anti-learner”). Search, filter, and compare learning rates with Plotly-powered scatter plots, log-log experience curves, and time-series projections to 2036. Includes the Global Learning Rate section showing civilization-scale learning efficiency.
Built on the Santa Fe Institute Performance Curve Database (Nagy et al., 2013), extended with 93 new technologies including carbon removal (DAC, BECCS, Enhanced Weathering) and AI/ML. All data CC BY 4.0 licensed with 100+ documented sources. Export charts, download datasets, and embed in your own work.
2 videos
The mechanics of scoring a carbon credit are, by necessity, multidimensional — spanning additionality, permanence, measurement uncertainty, and co-benefits — and not easily reduced to a single number without losing something important. This video walks viewers through the CarbonGrade scoring methodology step by step, explaining how each dimension is assessed, weighted, and aggregated into a composite score that balances comprehensiveness with usability.
For market participants accustomed to navigating carbon credits by instinct and reputation, the presentation offers something more systematic: a transparent, replicable process for evaluating credit quality. The intended audience is broad — from compliance officers at multinational firms to fund managers evaluating carbon-removal portfolios — and the format reflects an awareness that trust in a rating system depends not just on its methodology but on how clearly that methodology is communicated.
Before carbon can be priced, traded, or offset, it must first be counted — a task that sounds straightforward but is anything but. This introductory video covers the foundational principles of carbon accounting: the protocols for defining organisational boundaries, the distinction between Scope 1, 2, and 3 emissions, and the methodological choices that determine whether a carbon inventory is a meaningful management tool or a compliance exercise of questionable value.
The presentation is aimed squarely at practitioners — sustainability officers, finance teams, and operations managers — who need a working understanding of carbon accounting without the luxury of a postgraduate course. It emphasises the practical choices that matter most: where to draw system boundaries, how to handle data gaps, and which reporting frameworks are best suited to different organisational contexts. The fundamentals, properly understood, are the bedrock on which everything else — from internal targets to market participation — is built.
