Trend analysis: Data interoperability & climate APIs — where the value pools are (and who captures them)

The climate data ecosystem generates an estimated 40 exabytes of structured and unstructured environmental information annually, spanning satellite imagery, IoT sensor networks, corporate emissions disclosures, supply chain records, and weather modeling outputs. Yet less than 15% of this data flows seamlessly between the systems that need it. The result is a $4.2 billion annual cost burden across the global sustainability reporting supply chain, driven by manual data reconciliation, format conversion, and quality assurance processes that could be largely automated through standardized APIs and interoperability protocols. Understanding where value concentrates in this fragmented landscape is essential for policymakers, compliance teams, and technology buyers evaluating platform investments.

Why It Matters

The UK sits at the intersection of several regulatory forces that make climate data interoperability an immediate operational priority. The Financial Conduct Authority's Sustainability Disclosure Requirements, building on the International Sustainability Standards Board's IFRS S1 and S2 frameworks, require listed companies and large asset managers to report climate-related financial information using standardized metrics by 2026. The UK Green Taxonomy, currently under consultation, will impose additional classification requirements that demand granular, auditable data linking financial activities to environmental outcomes. These mandates cannot be met efficiently without machine-readable data flows between corporate ERP systems, emissions calculation engines, verification platforms, and regulatory filing systems.

Beyond compliance, climate data interoperability unlocks significant economic value. McKinsey estimates that improved data sharing across climate value chains could generate $100-150 billion in annual economic value by 2030 through reduced transaction costs, faster capital allocation, and more accurate risk pricing. The challenge lies in the fragmented nature of the current ecosystem: over 300 climate data vendors operate globally, using proprietary schemas, inconsistent taxonomies, and incompatible API architectures that force downstream consumers to build expensive custom integrations.

Three structural trends are reshaping the landscape. First, mandatory disclosure regimes are converging around ISSB standards, creating demand for interoperable reporting pipelines that can serve multiple jurisdictions from a single data source. Second, financial regulators are beginning to mandate machine-readable filings (the FCA's Digital Regulatory Reporting initiative being a prominent example), requiring structured data outputs rather than PDF-based disclosures. Third, the proliferation of climate-adjacent data needs, including biodiversity metrics under the Taskforce on Nature-related Financial Disclosures, social impact indicators, and physical risk analytics, is expanding the scope of interoperability requirements beyond carbon accounting alone.

Key Concepts

Climate Data APIs are programmatic interfaces that enable automated exchange of environmental data between software systems. These range from simple REST APIs serving emissions factor databases to complex streaming APIs delivering real-time satellite-derived methane monitoring data. The quality of a climate API is determined by its coverage (number of data points and geographic scope), latency (how quickly new data becomes available), standardization (adherence to common schemas such as the Partnership for Carbon Accounting Financials or the Carbon Disclosure Project formats), and reliability (uptime and error handling).

Data Interoperability in the climate context refers to the ability of diverse systems to exchange and use environmental data without manual transformation. True interoperability requires agreement on data models (what fields exist and what they mean), serialization formats (how data is encoded for transmission), semantic standards (shared vocabularies and taxonomies), and governance protocols (who certifies data quality and resolves disputes).

Value Pools describe concentrations of economic returns within a value chain. In climate data, value pools form wherever friction exists between data producers and consumers: at the point of data collection, during transformation and enrichment, in verification and assurance, and at the interface with decision-making systems. Identifying which value pools are growing, shrinking, or shifting is critical for strategic technology investment.

Where the Value Pools Are

Emissions Factor Databases and Calculation Engines

The foundational layer of climate data infrastructure, emissions factor databases, represents a $600-800 million annual market that is consolidating rapidly. Companies like Ecoinvent, the US EPA, and the UK's Department for Energy Security and Net Zero maintain reference databases that feed into virtually every carbon accounting calculation. The value capture opportunity lies not in the raw factors (many of which are publicly available) but in the enrichment, contextualization, and API delivery of these factors for specific use cases.

Watershed has built one of the most comprehensive carbon accounting platforms, combining proprietary emissions factor libraries with automated data ingestion from enterprise systems. Their API-first architecture enables integration with financial planning, procurement, and supply chain management platforms, positioning Watershed as an interoperability hub rather than a standalone tool. The company's $100 million Series C funding in 2024 valued it at $1.8 billion, reflecting investor conviction in the API-centric business model.

Climatiq takes a different approach, offering a pure-play emissions factor API that developers can embed into any application. By providing over 70,000 emissions factors via a standardized REST API, Climatiq enables software companies to add carbon calculation capabilities without building their own factor databases. Their pricing model, based on API call volume, creates recurring revenue that scales with customer growth. This infrastructure-layer positioning captures value from the entire ecosystem rather than from individual enterprise accounts.

Supply Chain Data Exchange

Supply chain emissions (Scope 3) represent 65-95% of total corporate emissions for most sectors, yet obtaining accurate supplier-level data remains the single largest challenge in climate reporting. The value pool here is enormous: the Carbon Trust estimates that companies collectively spend $3.5 billion annually on Scope 3 data collection and estimation, with the majority of that expenditure producing unreliable results based on spend-based approximations rather than actual activity data.

Altruistiq provides a supply chain sustainability platform that enables automated data exchange between buyers and suppliers through standardized APIs. Their platform connects procurement systems to supplier emissions data, replacing manual survey processes that typically achieve less than 30% response rates. Altruistiq's approach of embedding data requests into existing procurement workflows rather than requiring suppliers to adopt new platforms significantly improves data coverage and quality.

Carbon Chain focuses specifically on commodity supply chain emissions, providing API-based carbon intensity data for oil, gas, metals, and agricultural commodities. By combining satellite data, shipping records, and refinery-level processing information, Carbon Chain calculates asset-level emissions intensities that enable traders and financial institutions to differentiate between high and low carbon commodity flows. Their data feeds directly into trading platforms and risk management systems through standardized APIs, capturing value at the intersection of commodity finance and climate compliance.

SINE (Sustainability Information Exchange) represents an emerging industry consortium approach to supply chain data interoperability. Backed by major UK retailers and manufacturers, SINE provides a standardized data exchange protocol that enables suppliers to share environmental performance data once and distribute it to multiple buyers through a single API integration. This network model reduces the "survey fatigue" that undermines data quality while creating a shared data asset that appreciates in value as network participation grows.

Verification, Assurance, and Audit Trail

As climate disclosures become mandatory and financially material, the verification and assurance layer is emerging as one of the fastest-growing value pools. The International Auditing and Assurance Standards Board's International Standard on Sustainability Assurance (ISSA 5000) establishes requirements for limited and reasonable assurance of sustainability information, creating demand for auditable data trails that current systems often cannot provide.

Certivity (formerly part of SGS Group's digital division) provides API-based verification services that integrate directly with corporate sustainability platforms. Rather than conducting periodic manual audits, Certivity's continuous assurance model monitors data quality, flags anomalies, and maintains cryptographically secured audit trails that satisfy both regulatory requirements and investor due diligence needs. This shift from episodic to continuous assurance fundamentally changes the economics of verification, reducing per-engagement costs while increasing the frequency and reliability of assurance outputs.

Normative combines an AI-powered carbon accounting engine with built-in audit trail functionality that meets the requirements of CSRD and ISSB reporting. Their platform generates machine-readable disclosure documents that regulators can process automatically, positioning Normative at the convergence of calculation, reporting, and assurance. The company's partnerships with major accounting firms including PwC and EY embed their technology into established assurance workflows.

Physical Risk and Scenario Analytics

Climate physical risk analytics represents a value pool that is growing at approximately 35% annually, driven by regulatory stress testing requirements and insurance market demand. The UK's Prudential Regulation Authority requires regulated firms to assess physical and transition risks under multiple climate scenarios, creating persistent demand for high-resolution, forward-looking climate data delivered through production-grade APIs.

Jupiter Intelligence provides hyper-local climate risk analytics through APIs that deliver property-level flood, heat, wind, and wildfire projections under multiple warming scenarios. Their ClimateScore platform processes petabytes of climate model output, downscaling global projections to resolutions of 90 meters, and serves results through APIs that integrate with insurance underwriting, mortgage origination, and real estate investment platforms. Jupiter's $54 million in venture funding reflects the high value that financial institutions place on embedded climate risk data.

Moody's (formerly RMS) acquired climate analytics capabilities through its purchase of RMS and subsequent integration with its credit rating and risk assessment infrastructure. By embedding physical risk data into existing credit analysis APIs, Moody's captures value by positioning climate data as an enhancement to established financial data products rather than as a standalone offering. This bundling strategy gives Moody's significant distribution advantages over pure-play climate analytics providers.

Who Captures Value and Why

The distribution of value across the climate data ecosystem follows a clear pattern: companies that control integration points between data producers and decision-makers capture disproportionate returns. Pure data providers, regardless of data quality, face commoditization pressure as emissions factor databases proliferate and satellite data becomes more accessible. Conversely, platforms that aggregate, normalize, and route data between systems command premium pricing because switching costs increase as integrations deepen.

Three strategic positions generate the strongest value capture:

Interoperability hubs that connect multiple data sources to multiple consumers through standardized APIs benefit from network effects. Each additional data source makes the hub more valuable to consumers, and each additional consumer makes it more attractive to data providers. Watershed and Climatiq exemplify this model in different market segments.

Embedded analytics providers that deliver climate data within existing financial or operational workflows capture value by reducing adoption friction. Jupiter Intelligence's integration into mortgage origination platforms and Moody's embedding of physical risk into credit analysis demonstrate how climate data becomes most valuable when it reaches decision-makers without requiring them to learn new tools.

Verification infrastructure providers that create auditable, tamper-evident data trails capture value from the regulatory requirement for assurance. As sustainability disclosures achieve the same legal standing as financial statements, the audit trail becomes as valuable as the underlying data.

Action Checklist

• Audit your organization's climate data flows to identify manual touchpoints where API integration could reduce cost and error rates
• Evaluate whether current vendors provide standardized API access or lock data into proprietary formats
• Assess compliance readiness for machine-readable disclosure requirements under FCA and ISSB frameworks
• Prioritize interoperability when selecting new climate data platforms, testing API documentation quality and integration support before signing contracts
• Engage with industry consortia developing shared data exchange standards relevant to your sector
• Build internal API governance capabilities to manage the growing number of climate data integrations
• Map your Scope 3 data collection processes to identify where API-based supplier data exchange could replace manual surveys
• Establish data quality benchmarks and monitoring protocols for climate data received through APIs

FAQ

Q: What is the primary barrier to climate data interoperability today? A: The lack of universally adopted semantic standards. While technical connectivity (REST APIs, JSON formats) is well established, the absence of shared data models for climate information means that integrating data from different sources still requires significant mapping and transformation work. Initiatives like the ISSB taxonomy and the Partnership for Carbon Accounting Financials data model are beginning to address this gap, but full convergence is likely 3-5 years away.

Q: How should UK compliance teams prepare for machine-readable disclosure requirements? A: Begin by ensuring that underlying climate data is stored in structured, machine-readable formats rather than in spreadsheets or documents. Evaluate sustainability reporting platforms based on their ability to generate XBRL-tagged or API-accessible outputs. Engage with the FCA's Digital Regulatory Reporting initiative to understand emerging format requirements. Budget for integration work connecting sustainability platforms to financial reporting systems.

Q: Which climate data value pools are most likely to grow over the next 3-5 years? A: Verification and assurance infrastructure will see the fastest growth as mandatory disclosure regimes take effect globally. Supply chain data exchange will grow substantially as Scope 3 reporting accuracy requirements tighten. Physical risk analytics will continue growing as financial regulators expand stress testing requirements. Emissions factor databases, by contrast, face commoditization pressure and margin compression.

Q: What risks should organizations consider when adopting climate data APIs? A: Key risks include vendor lock-in through proprietary data formats, data quality degradation when factors are updated without notification, regulatory compliance gaps if API providers do not maintain audit trails, and cybersecurity exposure from connecting internal systems to external data feeds. Mitigation strategies include contractual data portability clauses, service-level agreements covering data quality and uptime, and security assessments of API provider infrastructure.

Sources

• Climate Policy Initiative. (2025). Global Landscape of Climate Finance 2025. San Francisco: CPI.
• McKinsey & Company. (2025). The Economic Potential of Climate Data Interoperability. London: McKinsey Global Institute.
• Financial Conduct Authority. (2025). Sustainability Disclosure Requirements: Implementation Guidance. London: FCA.
• International Sustainability Standards Board. (2025). IFRS S1 and S2: Implementation Progress Report. Frankfurt: IFRS Foundation.
• Carbon Trust. (2025). Scope 3 Data Collection: Costs, Challenges, and Technology Solutions. London: Carbon Trust.
• International Auditing and Assurance Standards Board. (2025). ISSA 5000: General Requirements for Sustainability Assurance Engagements. New York: IAASB.
• BloombergNEF. (2025). Climate Data and Analytics Market Sizing Report. New York: Bloomberg LP.