According to Net Zero Tracker data as of September 2025, approximately 140 national governments have adopted net-zero targets, covering around 74% of global greenhouse gas (GHG) emissions and 77% of global GDP. The Science Based Targets initiative (SBTi) reached its 10,000th validated company in January 2026, with more than 10,263 validated targets recorded by February 2026, according to the SBTi dashboard. Net-zero pledges now cover 92% of GDP and 88% of emissions worldwide, according to SBTi. The scale of stated ambition is, by any historical measure, without precedent.
The gap between that ambition and what is actually happening in the physical economy is equally striking: BCG's 2024 climate survey found that only 11% of surveyed large enterprises were reducing emissions at a pace consistent with their stated climate ambitions. Understanding why requires looking past the targets themselves to the measurement infrastructure they rest on.
That infrastructure was never built for global comparability. It was built incrementally: national inventories constructed to satisfy UNFCCC reporting requirements, corporate emissions programs designed around the GHG Protocol but interpreted with significant local variation, and regional disclosure frameworks that use similar language and different methodologies. The World Economic Forum described the result plainly in November 2025: organizations navigating this landscape face a confusing maze of guidelines, methodologies, and expectations. The fragmentation leads to hesitation, inconsistency and greenwashing, and adds reporting and compliance costs that further hinder action.
The Emission Factor Problem That Sits at the Foundation
The most fundamental comparability problem in global emissions accounting is the emission factor. An emission factor converts an activity: burning a litre of diesel, consuming a kilowatt-hour of electricity, applying a tonne of fertilizer, into an equivalent mass of carbon dioxide or other GHG. These factors vary significantly by country, by grid, by technology vintage, and by the underlying measurement data used to construct them. The International Energy Agency (IEA) publishes annual emission factors for electricity generation across countries, and the spread is large: a kilowatt-hour consumed from a coal-heavy grid carries far more embodied carbon than one from a hydro-dominated grid, and the national factor changes as the generation mix changes.
GHG calculators relying on standard Tier 1 emission factors (the global default values used when local data is unavailable) may produce estimates that exceed direct measurements by a factor of two or more in tropical developing countries, and incorrectly predict the direction of emissions change 41% of the time. Those Tier 1 factors remain widely used when facility-level or region-specific emissions data is unavailable because locally derived Tier 2 data simply does not exist for most regions and emission sources. The GHG Management Institute has documented that even direct stack measurements carry an uncertainty of 5% to 12% from measurement of concentration, velocity, moisture, and temperature alone. Aggregate that uncertainty across a global supply chain and the reported figure can diverge from reality by a margin that makes year-on-year progress claims unreliable.
How Framework Fragmentation Compounds the Measurement Problem
The same underlying emissions data may need to be tagged and organized differently across disclosure systems: digitally tagged under the ESRS XBRL taxonomy for EU filings, reported under IFRS S1/S2-aligned requirements where adopted, and mapped into separate questionnaire structures for CDP and GRI. These are not just formatting differences. The EU's double materiality framework requires companies to assess both how sustainability issues affect enterprise value and how the company affects people and the environment. The ISSB baseline is narrower, focusing on sustainability-related risks and opportunities that could affect a company's prospects. When the same company prepares disclosures for both markets, the reporting boundary, materiality test, and level of required detail may not be the same.
As the SBTi has noted, net-zero has been interpreted in different and inconsistent ways, a problem that is partly about ambition and partly about what the underlying measurement systems can support. A company with operations across the EU, Southeast Asia, and sub-Saharan Africa is constructing its emissions inventory from data systems of radically different quality, applying emission factors of radically different precision, and filing disclosures under frameworks with materially different scope requirements. The reported number at the top of that process carries implied precision it does not actually have.
Where the Gap Is Largest and Why It Matters Most
The emissions data quality problem is most acute in the markets where emissions growth is actually occurring and where net-zero commitments are newest. According to the 2025 Africa Sustainable Development Report, produced by the African Union, UN Economic Commission for Africa, UNDP, and African Development Bank, data gaps prevent a full picture of the continent's development performance, a finding that extends directly to emissions tracking. BCG and CO2 AI's 2025 climate survey found that globally only 7% of companies fully disclose GHG emissions across all three scopes, with regions like Africa showing even lower rates. Africa holds 17% of global population but less than 1% of data center capacity, a structural constraint on the digital infrastructure that modern emissions tracking requires.
Asia presents a different version of the same problem. China's 2026 Corporate Sustainable Disclosure Standards and the ISSB-aligned frameworks adopted across Japan, Australia, Singapore, and South Korea use similar architecture but differ on materiality scope and data requirements in ways that make direct comparison difficult. A multinational company consolidating emissions from operations across these jurisdictions is not producing one emissions figure. It is producing several, built on different assumptions, and then presenting them as a single number to investors who assume they are comparable.
What the Accountability Gap Means for Corporate Climate Commitments
The credibility of corporate net-zero commitments depends, at its foundation, on the credibility of the baseline from which reduction is measured and the precision of the annual figures showing progress against that baseline. When the baseline was constructed using Tier 1 default factors in some regions and meter-level primary data in others, the reported reductions are not all equivalent. A 10% reduction in a well-measured European operation and a 10% reduction in a supply chain segment measured through regional averages represent different levels of actual progress, but they consolidate into the same corporate total.
This is not a problem that additional reporting frameworks resolve on their own. It is a measurement infrastructure problem, and it is most concentrated in the markets that global supply chains depend on most heavily. Investors and regulators who are tightening their scrutiny of net-zero claims are asking the right question. The answer they get back will only be as reliable as the measurement systems that produced the numbers they are scrutinizing.
