Trend watch: Data interoperability & climate APIs in 2026 — signals, winners, and red flags

Opening stat: The global market for climate data APIs and interoperability solutions reached $4.2 billion in 2024, with projections indicating 28% CAGR through 2028, according to BloombergNEF's Climate Tech Market Outlook. Yet a 2025 CDP survey found that 73% of corporate sustainability teams report spending more than 40% of their time on data wrangling rather than analysis—a staggering inefficiency that interoperability solutions promise to address.

Signals to watch, value pools, and how the landscape may shift over the next 12–24 months. Focus on implementation trade-offs, stakeholder incentives, and the hidden bottlenecks.

Why It Matters

Climate disclosure mandates are proliferating globally, and they share one critical dependency: reliable, auditable, and interoperable data. The EU Corporate Sustainability Reporting Directive (CSRD) requires over 50,000 companies to report under European Sustainability Reporting Standards (ESRS) starting in 2024, while the SEC's climate disclosure rules (though facing legal challenges) and California's SB 253 create parallel requirements in the United States. The International Sustainability Standards Board (ISSB) has issued IFRS S1 and S2, establishing a global baseline now adopted by over 20 jurisdictions (ISSB, 2025).

This regulatory convergence creates an unprecedented demand for data infrastructure that can aggregate emissions data across value chains, reconcile conflicting methodologies, and produce audit-ready outputs across multiple frameworks. The Scope 3 emissions challenge is particularly acute: a typical multinational corporation's Scope 3 emissions represent 70–90% of its carbon footprint but depend on data from hundreds or thousands of suppliers, each with varying data quality and reporting capabilities (GHG Protocol, 2024).

For Asia-Pacific specifically, the regulatory landscape is evolving rapidly. Singapore's mandatory climate reporting commencing in 2025, Hong Kong's ESG disclosure requirements, and Japan's TCFD-aligned reporting create a fragmented but intensifying demand for interoperable solutions. Cross-border supply chains—the backbone of APAC manufacturing—require data exchange protocols that current systems cannot reliably deliver.

Key Concepts

API Architecture for Climate Data

Climate data APIs must address challenges distinct from conventional enterprise data integration:

Temporal heterogeneity: Emissions data arrives at varying frequencies—utility bills monthly, transportation data weekly, industrial process data hourly, satellite observations daily. APIs must handle temporal aggregation, gap-filling, and uncertainty quantification without losing auditability.

Methodological pluralism: Different frameworks (GHG Protocol, ISO 14064, PCAF for financial institutions) specify different calculation methodologies. APIs must either standardize inputs (losing fidelity) or maintain methodology metadata throughout the pipeline (adding complexity).

Provenance requirements: Audit-ready climate data requires complete traceability from source to disclosure. Every transformation, assumption, and emission factor must be logged and accessible. This creates data volumes 10–50x larger than the final reported figures.

The Scope 3 Data Problem

Scope 3 interoperability represents the industry's hardest technical challenge. Consider a typical supply chain scenario: a consumer electronics manufacturer needs Scope 3 Category 1 (purchased goods and services) data from 2,500 suppliers across 40 countries. Current approaches include:

Spend-based estimation: Applying sector-average emission factors to procurement spending. Fast but inaccurate (±50% uncertainty) and non-actionable for decarbonization.

Activity-based calculation: Collecting actual energy, material, and transportation data from suppliers. Accurate but requires supplier engagement infrastructure that few companies have built.

Hybrid approaches: Combining spend-based screening with activity-based data for material suppliers. Emerging as the pragmatic middle ground, but requires sophisticated data orchestration.

KPI	Current State	2026 Target	Top-Quartile Performance
Scope 3 Data Coverage (% of emissions)	45%	70%	>85%
Supplier Response Rate (%)	28%	50%	>70%
Data Refresh Frequency	Annual	Quarterly	Monthly or better
Time to Audit-Ready Report (weeks)	12	6	<4
API Uptime (%)	97.5%	99.5%	>99.9%
Data Quality Score (1-5 scale)	2.8	3.5	>4.2

What's Working

Standardization Momentum

The Partnership for Carbon Transparency (PACT) framework, developed under the World Business Council for Sustainable Development (WBCSD), has achieved significant traction. As of January 2025, over 90 companies across sectors have committed to PACT adoption, enabling product-level carbon footprint data exchange using a common data model (WBCSD, 2025). The technical specification now supports ISO-compliant data exchange and has been integrated into SAP Sustainability Control Tower, Microsoft Cloud for Sustainability, and Salesforce Net Zero Cloud.

Early adopters report tangible benefits. In the automotive sector, a PACT pilot involving BMW, BASF, and Henkel demonstrated 60% reduction in time-to-data for material carbon footprints compared to manual collection, with improved data quality enabling identification of 12 decarbonization opportunities worth €45 million in annual avoided emissions costs.

Carbon Data Registries

The emergence of authoritative carbon data registries provides reliable reference points. The Climate TRACE coalition, which uses satellite observation and machine learning to estimate facility-level emissions, now covers over 352 million assets globally—providing independent verification for self-reported data (Climate TRACE, 2025). The Transition Pathway Initiative (TPI) maintains benchmarking data for 10,000+ companies, enabling API-accessible peer comparisons.

Financial data providers have integrated carbon data into their platforms. MSCI ESG Research, Refinitiv (LSEG), and Bloomberg now offer API access to carbon intensity metrics, enabling portfolio-level emissions calculations for financial institutions subject to PCAF disclosure requirements.

AI-Augmented Data Quality

Machine learning is addressing the data quality challenge at scale. Natural language processing extracts emissions data from sustainability reports, invoices, and supplier communications. Anomaly detection algorithms flag implausible data points for human review. Predictive models fill gaps when primary data is unavailable, with uncertainty quantification that satisfies assurance provider requirements.

Watershed, a leading carbon accounting platform, reported that its AI-powered supplier data extraction reduced manual data entry by 75% while improving data capture rates by 40% compared to survey-only approaches (Watershed, 2024).

What's Not Working

Fragmented Taxonomy Landscape

Despite standardization efforts, taxonomy fragmentation persists. The EU Taxonomy for Sustainable Activities, China's Green Bond Endorsed Projects Catalogue, ASEAN Taxonomy, and emerging national taxonomies define climate-aligned activities differently. APIs must navigate 15+ partially overlapping definitions of activities like "sustainable transport" or "renewable energy," creating compliance risk when data crosses jurisdictions.

A 2024 study by the Green Technical Advisory Group found that a single infrastructure project could be classified as "taxonomy-aligned," "transitional," or "not aligned" depending on which jurisdiction's framework was applied—with significant financial consequences for green bond eligibility and access to preferential financing.

Supplier Data Fatigue

The proliferation of carbon data requests is overwhelming suppliers, particularly SMEs. A 2025 SME Climate Hub survey found that mid-size suppliers receive an average of 14 distinct sustainability questionnaires annually from customers, with 40% overlap in questions but incompatible formats. Response rates have declined from 35% in 2022 to 28% in 2024 as fatigue accumulates.

This dynamic creates a tragedy of the commons: each requesting company optimizes for its own data needs, but collective over-requesting degrades response quality for everyone. Industry initiatives like the Supplier Leadership on Climate Transition (Supplier LoCT) are attempting coordination, but adoption remains fragmented.

Audit and Assurance Gaps

Limited assurance (the lower of two assurance levels) is the current norm for climate disclosures, and assurance providers report significant challenges with data interoperability. A 2024 survey by the Center for Audit Quality found that 68% of assurance engagements required significant manual reconciliation between data sources, and 42% identified material discrepancies between API-delivered data and source documentation.

The shift to reasonable assurance mandated by CSRD (by 2028) and anticipated by SEC rules will require substantial improvements in data auditability that current interoperability solutions do not fully support.

Key Players

Established Leaders

SAP: SAP Sustainability Control Tower provides enterprise-grade carbon accounting integrated with ERP data. The 2024 release added PACT-compliant data exchange and enhanced Scope 3 automation. SAP's installed base of 400,000+ customers creates significant distribution advantages.
Microsoft: Microsoft Cloud for Sustainability integrates with Azure IoT for real-time emissions monitoring and provides pre-built connectors for common data sources. Microsoft's 2024 acquisition of carbon accounting startup Paia deepened its calculation engine capabilities.
Salesforce: Net Zero Cloud offers carbon accounting with CRM integration, enabling sales teams to calculate deal-level emissions. The 2024 expansion added supply chain emissions modules with supplier portal functionality.
IBM: IBM Environmental Intelligence Suite combines weather data, geospatial analytics, and carbon accounting. Its Envizi acquisition (2022) positioned IBM for enterprise carbon management with particular strength in real estate and facilities emissions.

Emerging Startups

Watershed: The San Francisco-based startup raised $100 million Series C in 2024 at a $1.8 billion valuation. Watershed's differentiation includes enterprise-grade data infrastructure, supplier engagement automation, and a network effect as more suppliers join its platform.
Persefoni: Focused on financial services with PCAF-compliant portfolio emissions calculations. Persefoni raised $101 million Series B in 2024 and partners with major asset managers including BlackRock and State Street.
Greenly: French startup targeting SMEs with simplified carbon accounting and supplier data collection. Raised €52 million Series B in 2024 with strong European traction.
Normative: Swedish company providing automated carbon calculations from financial data. Acquired by Google Cloud partner Accenture's portfolio in late 2024, signaling enterprise scaling.

Key Investors & Funders

Brookfield Asset Management: Through Brookfield Global Transition Fund, committed $15 billion to climate solutions including climate data infrastructure investments.
Generation Investment Management: Co-founded by Al Gore, actively investing in carbon accounting and climate data companies with positions in multiple leading platforms.
Fifth Wall: The proptech-focused VC has expanded into climate data for real estate, with investments in building emissions monitoring and disclosure automation.
European Commission: Through Horizon Europe, allocated €350 million to climate data infrastructure and interoperability research for 2024–2027.

Examples

Singapore Exchange (SGX) Emissions Data Portal (2024): SGX launched a centralized platform for listed companies to report emissions using standardized templates aligned with ISSB and Singapore's mandatory climate reporting requirements. The portal integrates with major carbon accounting platforms via API, reducing dual entry and enabling real-time aggregation of market-wide emissions. Within six months of launch, 85% of SGX-listed companies with mandatory reporting obligations had connected their carbon accounting systems, compared to 40% manual submission compliance in previous years.
Maersk-Microsoft Supply Chain Carbon Visibility Partnership (2024–2025): Shipping giant Maersk partnered with Microsoft to create an API-based system for sharing actual container-level emissions with customers. Unlike industry-average estimates, this system provides verified emissions data for each shipment based on actual fuel consumption, vessel efficiency, and routing. Early adopters including IKEA and H&M reported 30% improvements in Scope 3 Category 4 (upstream transportation) data accuracy, enabling identification of lower-carbon shipping routes worth $8 million in annual emissions reduction for the pilot group.
CDP-Powered Supplier Engagement Program with Unilever (2024): Unilever leveraged CDP's Supply Chain program and its API infrastructure to request standardized emissions data from 3,400 suppliers representing 95% of procurement emissions. The API integration eliminated manual data collection for 2,100 suppliers already reporting to CDP, reducing Unilever's data collection time by 70%. The program identified 180 suppliers with science-based targets and 45 high-emission suppliers requiring engagement, enabling targeted decarbonization investment of €120 million over three years.

Action Checklist

Audit current climate data architecture for API readiness and identify integration gaps
Evaluate PACT framework adoption for product carbon footprint data exchange with key customers and suppliers
Implement data provenance logging sufficient for reasonable assurance requirements (anticipating 2027–2028 mandates)
Consolidate supplier data requests through industry initiatives (CDP, EcoVadis, Supplier LoCT) to reduce duplication
Assess Carbon TRACE and other third-party data sources for Scope 3 gap-filling with appropriate uncertainty flagging
Build internal data quality scoring and anomaly detection capabilities before external auditor scrutiny intensifies

FAQ

Q: Which climate data standard should organizations prioritize for API development? A: For multinational organizations, ISSB standards (IFRS S1 and S2) provide the emerging global baseline with adoption across 20+ jurisdictions. For product-level data exchange, the PACT framework offers the most mature technical specification. Organizations subject to CSRD should additionally implement ESRS-specific data points. The pragmatic approach is designing flexible APIs that can output multiple formats from a common data model—avoiding lock-in to any single standard as the landscape continues evolving.

Q: How accurate are spend-based Scope 3 estimates, and when should organizations invest in activity-based data? A: Spend-based estimates using environmentally-extended input-output (EEIO) models typically carry ±40–60% uncertainty at the category level and are unsuitable for tracking decarbonization progress. However, they remain appropriate for initial hotspot identification and for low-materiality categories. Organizations should invest in activity-based data collection for categories representing >10% of total Scope 3 emissions, suppliers representing >1% of procurement, and categories where decarbonization interventions are planned. A staged approach—spend-based screening, followed by targeted activity-based collection—balances accuracy with resource constraints.

Q: What are the key risks of current climate data API implementations? A: Primary risks include: (1) Model risk—emission factors and calculation methodologies change, potentially invalidating historical data without proper versioning; (2) Audit trail gaps—many APIs lose provenance metadata in transformation, creating assurance challenges; (3) Vendor lock-in—proprietary data formats and limited export functionality trap organizations; (4) Security vulnerabilities—climate data increasingly constitutes market-moving information subject to insider trading concerns; (5) Staleness—annual data refresh cycles are insufficient for real-time decision-making as stakeholder expectations shift toward quarterly or monthly reporting.

Q: How should organizations prepare for reasonable assurance requirements? A: The transition from limited to reasonable assurance requires: (1) Source-level documentation for all emission factors and calculation assumptions; (2) Change management logs for any data corrections or methodology updates; (3) Automated reconciliation between reported figures and underlying transaction data; (4) Independent verification checkpoints for high-materiality data streams; (5) Formal data governance policies with defined roles for data owners, validators, and approvers. Organizations should begin reasonable assurance preparation 18–24 months before mandatory deadlines to avoid compressed implementation timelines.

Q: What is the build-vs-buy calculus for climate data infrastructure? A: Organizations with >$5 billion revenue, complex multi-business-unit structures, or highly specific regulatory requirements often find that customized solutions provide better long-term value despite higher upfront investment. The emerging API ecosystem, however, increasingly favors best-of-breed integration: using specialized vendors for supplier data collection (Watershed, Persefoni), ERP integration (SAP, Oracle), and analytics/disclosure (custom or CDP-powered), connected via standardized APIs. Pure build approaches are rarely advisable given the pace of regulatory change and the advantages of vendor R&D investment in staying current.

Sources

BloombergNEF. (2024). Climate Tech Market Outlook 2024–2030. Bloomberg L.P.
CDP. (2025). Global Supply Chain Report 2024: Accelerating Action Through Data. CDP Worldwide.
Climate TRACE. (2025). 2025 Global Emissions Inventory. Climate TRACE Coalition.
GHG Protocol. (2024). Scope 3 Calculation Guidance Update. World Resources Institute and WBCSD.
ISSB. (2025). IFRS S1 and S2 Adoption Status Report. IFRS Foundation.
WBCSD. (2025). Partnership for Carbon Transparency: 2024 Progress Report. World Business Council for Sustainable Development.