Climate Change Indicators

1. Outcome

This Circular provides guidance on compiling climate change indicators from ocean accounts, addressing the critical nexus between ocean ecosystems and global climate systems. Upon completing this Circular, readers will understand how to derive indicators for blue carbon sequestration and stocks from ecosystem accounts, compile ocean acidification indicators from condition accounts, calculate emission intensity indicators by ocean-related economic sector, and develop climate risk and adaptation indicators relevant to coastal and marine systems. The guidance integrates the carbon accounting frameworks of the System of Environmental-Economic Accounting Ecosystem Accounting (SEEA EA)^[1] with the air emissions accounting of the SEEA Central Framework (SEEA CF)^[2], supporting the Sustainable Development Goals (SDG 13: Climate Action and SDG 14: Life Below Water)^[3], nationally determined contributions (NDCs) under the Paris Agreement^[4], Kunming-Montreal Global Biodiversity Framework Target 8 on minimising the impact of climate change on biodiversity^[5], and the greenhouse gas disclosure requirements of sustainability standards including IFRS S2^[6].

The indicators compiled through this Circular support four principal policy applications: (i) NDC tracking for ocean sectors -- enabling countries to quantify the contribution of blue carbon ecosystems and offshore renewable energy to national climate commitments, and to assess the emission intensity of ocean-dependent industries relative to economy-wide targets; (ii) blue carbon accounting for REDD+ and related mechanisms -- providing the physical flow and stock data required for carbon credit verification and monitoring of ecosystem-based mitigation projects; (iii) IFRS S2 corporate climate disclosure -- supplying the sectoral emission intensity benchmarks and physical risk metrics that ocean-dependent companies require for Scope 1, 2, and 3 emissions reporting and transition risk assessment; and (iv) climate resilience planning -- informing adaptation investments through indicators of coastal vulnerability, ecosystem-based adaptation deployment, and the protective services provided by marine ecosystems under climate scenarios.

This Circular builds on the aggregate indicator methodology in TG-2.1 Aggregate Biophysical Indicators, the asset accounting framework established in TG-3.1 Asset Accounts, and the residual flows accounting detailed in TG-3.4 Flows from Economy to Environment. It enables the policy integration addressed in TG-1.4 Climate Policy Integration.

2. Requirements

This Circular requires familiarity with:

• TG-0.1 General Introduction to Ocean Accounts -- for the conceptual framework and key components of Ocean Accounts
• TG-0.2 Overview of Relevant Statistical Standards -- for the methodological foundations provided by SNA 2025, SEEA CF, and SEEA EA
• TG-2.1 Aggregate Biophysical Indicators -- for the general methodology of deriving normalised indicators and composite indices from ecosystem condition accounts
• TG-3.4 Flows from Economy to Environment -- for the framework of air emissions accounts and attribution of residual flows to economic sectors

3. Guidance Material

Oceans play a fundamental role in the global climate system, absorbing approximately 90 per cent of excess heat and about 25 per cent of anthropogenic carbon dioxide emissions^[7]. This dual function as climate regulator creates both opportunities and vulnerabilities: marine ecosystems provide critical climate mitigation services through carbon sequestration, while simultaneously experiencing climate-driven changes including warming, acidification, and altered circulation patterns. Ocean accounts provide a systematic framework for measuring these ocean-climate interactions, enabling compilation of indicators that track both the climate services provided by marine ecosystems and the climate pressures affecting them.

The indicators presented in this Circular span five thematic areas: the overarching ocean-climate indicator framework (Section 3.1), blue carbon indicators derived from ecosystem carbon accounts (Section 3.2), ocean acidification indicators from condition accounts (Section 3.3), emission intensity indicators linked to ocean economic activity (Section 3.4), and climate risk and adaptation indicators (Section 3.5). Together, these indicators support national climate reporting, SDG monitoring, corporate sustainability disclosure, and evidence-based climate policy development for marine and coastal areas.

Readers should note that this Circular and TG-2.1 Aggregate Biophysical Indicators share certain oceanographic condition variables--notably sea surface temperature, dissolved oxygen, and salinity--that appear in both climate and biophysical contexts. This Circular treats these variables as climate state indicators when they are compiled for the purpose of tracking climate-driven change; TG-2.1 treats them as general ecosystem condition indicators when they are compiled for the purpose of assessing overall environmental state. Where both compilations draw on the same condition accounts, compilers should ensure consistent treatment of reference conditions, measurement methods, and spatial resolution to avoid duplication or contradiction.

3.1 Ocean-Climate Indicator Framework

The ocean-climate indicator framework organises the relationships between ocean accounts and climate-relevant statistics, establishing a coherent structure for indicator compilation^[8]. This framework distinguishes between indicators that measure the role of oceans in climate regulation (mitigation-related) and indicators that measure climate impacts on ocean systems (vulnerability and adaptation-related).

Indicator categories

Climate change indicators derived from ocean accounts can be organised into four principal categories:

1. Carbon flux indicators -- measuring the exchange of carbon between the atmosphere and ocean ecosystems, including sequestration by blue carbon ecosystems (mangroves, seagrasses, salt marshes) and carbon uptake by open ocean systems
2. Carbon stock indicators -- measuring the standing stock of carbon held in marine and coastal ecosystems, representing the climate mitigation capacity that would be released if ecosystems were degraded
3. Ocean state indicators -- measuring physical and chemical changes in ocean conditions attributable to climate change, including temperature, pH, dissolved oxygen, and sea level
4. Emission attribution indicators -- measuring the greenhouse gas emissions associated with ocean-related economic activities, supporting analysis of emission intensity and transition pathways

This four-category structure does not separately distinguish adaptation effectiveness indicators from ocean state indicators. While the UNFCCC Global Goal on Adaptation (GGA) framework is developing dedicated metrics for adaptation effectiveness, the indicators in this Circular that relate to adaptation outcomes--such as nature-based solution deployment and coastal protection services (Section 3.5)--are compiled from the same condition and extent accounts as the ocean state indicators. As the GGA indicator framework matures, compilers may wish to disaggregate adaptation effectiveness as a distinct reporting category while maintaining the underlying accounting structure described here.

Ocean-climate indicator-account alignment table

Table 1 maps indicator domains to their accounting basis and principal reporting frameworks, providing a quick reference for compilers seeking to connect ocean accounts with international climate and biodiversity reporting obligations.

Table 1: Ocean-Climate Indicator-Account Alignment

Links to international frameworks

Ocean-climate indicators support multiple international monitoring and reporting frameworks:

SDG monitoring: SDG indicator 14.3.1 (average marine acidity measured at agreed suite of representative sampling stations) directly addresses ocean acidification^[9]. SDG 13 indicators on climate action are supported by emission intensity data and climate risk assessments that can be derived from ocean accounts.

UNFCCC reporting: National greenhouse gas inventories include emissions and removals from coastal wetlands under the Agriculture, Forestry and Other Land Use (AFOLU) sector. The IPCC Wetlands Supplement provides methodologies for estimating carbon fluxes from mangroves, tidal marshes, and seagrass meadows that align with ocean accounting approaches^[10]. Many countries now include ocean-based mitigation and adaptation measures in their nationally determined contributions (NDCs) under the Paris Agreement, creating a direct policy demand for the indicators compiled through this Circular^[11].

Kunming-Montreal Global Biodiversity Framework: GBF Target 8 calls on parties to minimise the impact of climate change and ocean acidification on biodiversity and increase its resilience through mitigation, adaptation, and disaster risk reduction actions, including through nature-based solutions and ecosystem-based approaches^[5:1]. Blue carbon indicators provide quantitative measures of the nature-based mitigation contribution of marine ecosystems, supporting national reporting against this target.

Corporate sustainability disclosure: The IFRS S2 Climate-related Disclosures standard requires disclosure of Scope 1, 2, and 3 greenhouse gas emissions, climate-related physical and transition risks, and climate resilience assessments^[12]. Ocean accounts provide the data infrastructure to support such disclosures for ocean-dependent industries.

TNFD reporting: The Taskforce on Nature-related Financial Disclosures (TNFD) framework identifies climate-nature linkages as a priority area, with explicit attention to blue carbon ecosystems and ocean-climate interactions^[13].

Spatial and temporal considerations

Ocean-climate indicators require careful attention to spatial and temporal boundaries:

• Spatial scope: Indicators should align with the marine spatial framework established in TG-0.1 General Introduction, distinguishing between coastal waters, the Exclusive Economic Zone (EEZ), and where relevant, high seas areas and seabed beyond national jurisdiction
• Temporal resolution: Climate-relevant indicators may require annual or multi-year compilation periods, with attention to interannual variability in carbon fluxes and oceanographic conditions
• Reference conditions: Changes in ocean state should be assessed against appropriate baselines, acknowledging that pre-industrial reference conditions may not be directly observable and must be estimated from historical data or models. The approach to reference conditions should follow the general methodology described in TG-2.1 Section 3.2

3.2 Blue Carbon Indicators

Blue carbon refers to the carbon captured and stored by coastal and marine ecosystems, particularly mangroves, tidal salt marshes, and seagrass meadows^[14]. These ecosystems are exceptionally efficient carbon sinks, sequestering carbon at rates two to four times greater than terrestrial forests per unit area and storing carbon in sediments for millennia under undisturbed conditions^[15]. Ocean accounts provide the framework for measuring blue carbon stocks and flows, enabling compilation of indicators for climate mitigation policy and carbon market mechanisms.

The blue carbon indicators in this section are closely related to the ecosystem service measurements in TG-6.2 Mangrove and Coastal Wetland Accounting, which addresses blue carbon services in detail. In particular, TG-6.2 Section 3.3 (Blue Carbon Services) describes the service measurement approaches from which several indicators below are derived. The carbon sequestration rate indicator corresponds to the regulating service flow recorded in ecosystem service supply tables; the carbon stock indicator corresponds to the carbon stock account in the asset balance sheet; and the carbon retention indicator corresponds to the ongoing service of maintaining existing stocks. Compilers should consult TG-6.2 for the detailed accounting methodology underlying these indicators.

Carbon sequestration indicators

Carbon sequestration indicators measure the rate at which blue carbon ecosystems remove carbon dioxide from the atmosphere and transfer it to long-term storage. Key indicators include:

Annual carbon sequestration rate (tonnes CO2 equivalent per hectare per year): The net carbon uptake by blue carbon ecosystems, comprising:

• Gross primary production (carbon fixed through photosynthesis)
• Minus autotrophic respiration (carbon released by living biomass)
• Minus heterotrophic respiration (carbon released through decomposition)
• Minus carbon losses from the ecosystem (exports, erosion)

The SEEA EA framework for ecosystem services recognises carbon sequestration as a regulating service, recording the net ecosystem carbon balance as the measure of service supply^[16]. For ocean accounting, this service flow should be recorded by ecosystem type and spatial unit, enabling attribution to specific marine areas and ecosystem assets.

Ecosystem-specific sequestration rates: Compilation should distinguish sequestration by ecosystem type, recognising substantial variation in rates:

• Mangroves: approximately 6-8 tonnes CO2 per hectare per year
• Salt marshes: approximately 5-8 tonnes CO2 per hectare per year
• Seagrass meadows: approximately 1.5-3 tonnes CO2 per hectare per year^[17]

These rates vary substantially with ecosystem condition, latitude, and local environmental conditions, and should be derived from local measurements or regionally calibrated estimates where available. Compilers should note that uncertainty in sequestration rate estimates is substantial and should be documented following the guidance in the 2013 IPCC Wetlands Supplement^[10:1]. Uncertainty quantification is particularly important when estimates are used for carbon credit verification or national inventory reporting, where the confidence interval directly affects the credibility of reported removals.

National blue carbon sequestration: The aggregate carbon sequestration across all blue carbon ecosystems within national marine areas, expressed in tonnes CO2 equivalent per year. This indicator supports national climate reporting and assessment of nature-based solutions to climate change.

Carbon stock indicators

Carbon stock indicators measure the accumulated carbon held in blue carbon ecosystem pools, representing both the climate mitigation asset and the emission liability if ecosystems are degraded.

Total ecosystem carbon stock (tonnes carbon per hectare): The carbon stored across all pools within the ecosystem, comprising:

• Aboveground biomass (trees, shrubs, vegetation)
• Belowground biomass (roots)
• Dead organic matter (litter, dead wood)
• Soil organic carbon (the largest pool, often extending metres deep in coastal sediments)

The SEEA EA carbon stock account provides the accounting structure for recording these stocks by ecosystem type and tracking changes between accounting periods^[18]. Table 13.3 of SEEA EA presents the structure of carbon stock accounts, disaggregating stocks into geocarbon, biocarbon, carbon in oceans, and carbon accumulated in the economy.

Ecosystem carbon stock by type: Carbon stocks should be compiled separately for each blue carbon ecosystem type, recognising substantial variation:

• Mangroves: approximately 1,000-1,500 tonnes carbon per hectare (including deep sediments)
• Salt marshes: approximately 200-400 tonnes carbon per hectare
• Seagrass meadows: approximately 100-300 tonnes carbon per hectare^[19]

Carbon stock change indicators: Changes in ecosystem carbon stocks between accounting periods provide indicators of net carbon accumulation or release:

• Increase in carbon stocks (positive) indicates net carbon removal from atmosphere
• Decrease in carbon stocks (negative) indicates net carbon emission to atmosphere

Stock changes may result from ecosystem extent changes (conversion, restoration), condition changes (degradation, improvement), or natural dynamics. The SEEA EA framework for ecosystem condition accounts enables tracking of the drivers of stock change. When blue carbon ecosystems are converted or degraded, not all stored carbon is released immediately. Decay rates vary by pool--aboveground biomass may decompose within years, while deep sediment carbon may remain stable for decades or longer depending on the nature of the disturbance. Compilers should apply pool-specific emission factors that reflect these differential release rates, drawing on the guidance in Chapter 4 of the IPCC 2013 Wetlands Supplement^[20] and, where available, locally calibrated emission factors. This distinction is particularly important for policy analyses comparing the climate impact of different types of ecosystem degradation.

Carbon retention services

Beyond annual sequestration, blue carbon ecosystems provide carbon retention services by maintaining existing carbon stocks that would otherwise be released to the atmosphere^[21]. This service concept recognises that:

• Ecosystems with high carbon stocks (such as old-growth mangroves) provide high retention value even if their current sequestration is low due to equilibrium conditions
• Degradation or conversion of carbon-rich ecosystems results in substantial emissions
• The retention service is an ongoing service flow, distinct from the one-time sequestration that accumulated the stock

SEEA EA provides guidance on valuing carbon retention services using the annuity approach, which spreads the value of the carbon stock across expected future periods^[22]. This approach sends appropriate policy signals regarding the importance of conserving existing blue carbon stocks.

Data sources and compilation

Blue carbon indicators require integration of multiple data sources:

• Extent data: Remote sensing products for mangrove, salt marsh, and seagrass distribution, including the Global Mangrove Watch^[23] for standardised mangrove extent mapping and the Allen Coral Atlas for reef-associated habitat mapping. Detailed methodology for remote sensing-based extent compilation is provided in TG-4.1 Remote Sensing.
• Carbon density estimates: From field sampling, literature synthesis, or ecosystem models
• Flux measurements: From eddy covariance towers, sediment cores, or modelled estimates
• Stock-change detection: From repeated extent mapping and condition assessment

The IPCC Guidelines for National Greenhouse Gas Inventories and the 2013 Wetlands Supplement provide Tier 1 default values for carbon stocks and sequestration rates that can be applied where local data are unavailable^[24]. These global datasets are particularly important for countries with limited national monitoring capacity, providing a baseline from which national estimates can be progressively refined as local data become available.

3.3 Ocean Acidification Indicators

Ocean acidification--the reduction in seawater pH caused by absorption of anthropogenic carbon dioxide--represents a fundamental change in ocean chemistry with significant ecological and economic consequences^[25]. The SEEA EA framework for ecosystem condition accounts provides the structure for recording pH and related carbonate chemistry variables as condition indicators, supporting compilation of ocean acidification indicators for climate monitoring and policy.

pH-based indicators

Mean surface ocean pH: The average pH of surface ocean waters within the accounting area, measured at representative sampling stations. SDG indicator 14.3.1 specifies this measurement approach, requiring pH data from an agreed suite of representative sampling stations^[26].

pH change from reference period: The change in mean pH relative to a baseline period (typically pre-industrial or a specified reference decade). Given the logarithmic pH scale, a decrease of 0.1 pH units represents approximately a 26 per cent increase in hydrogen ion concentration.

Aragonite saturation state: The saturation state of calcium carbonate minerals, particularly aragonite, which is critical for shell-forming organisms including corals, molluscs, and some plankton^[27]. Aragonite saturation (omega-a) below 1.0 indicates undersaturation and corrosive conditions for calcifying organisms.

Seasonal pH variability: The range and timing of pH variation within the accounting period, important for understanding biological exposure to acidification stress.

Measurement precision and accuracy are critical considerations for pH-based indicators. Spectrophotometric pH measurements typically achieve precision of plus or minus 0.001 pH units, while electrode-based measurements may be an order of magnitude less precise. The Global Ocean Acidification Observing Network (GOA-ON) best practices guide^[28] provides detailed quality assurance guidance for acidification observations, including requirements for certified reference materials, inter-laboratory comparisons, and metadata documentation. Compilers should document the measurement methods and associated uncertainty for all pH-based indicators to support comparability across stations and time periods.

Spatial distribution indicators

Ocean acidification varies substantially with location, creating spatial patterns that are important for ecosystem impact assessment:

• Coastal vs. open ocean: Coastal waters may experience more extreme pH variation due to upwelling, river inputs, and biological activity
• Depth gradients: pH generally decreases with depth, with acidification effects most pronounced in deeper waters
• Regional patterns: Some regions (high latitudes, upwelling zones) experience accelerated acidification

Condition accounts should record pH and acidification indicators at appropriate spatial resolution to capture these patterns.

Ecosystem impact indicators

The ecological significance of acidification depends on the sensitivity of resident organisms and ecosystems. Mapping these impacts to the SEEA EA ecosystem condition typology strengthens integration with broader condition accounting:

Coral calcification impact: Reduced calcification rates in reef-building corals, measurable through growth rates, skeletal density, and reef accretion rates. Within the SEEA EA condition typology, this maps to the "ecosystem structural state" characteristic, reflecting changes in the physical structure of the reef ecosystem. This indicator links to the coral reef condition assessment in TG-6.1 Coral Reef Accounts.

Shellfish production impact: Effects on commercially important molluscs and crustaceans, potentially measurable through aquaculture production data or wild stock assessments. This maps to the "species-based characteristics" of ecosystem condition, specifically the abundance and productivity of calcifying species.

Pteropod shell condition: Pteropods (swimming snails) are sentinel organisms for acidification, with shell dissolution providing an early warning indicator of ecosystem stress. Within the condition typology, pteropod shell condition serves as a "species-based characteristic" indicator of the chemical dimension of ecosystem condition.

Data sources and compilation

Ocean acidification indicators require specialised oceanographic measurements:

• Fixed monitoring stations: Time-series stations with continuous or regular pH measurement
• Research vessel surveys: Periodic hydrographic surveys with carbonate chemistry analysis
• Autonomous platforms: Profiling floats, gliders, and moorings with pH sensors
• Satellite-derived estimates: Algorithms relating sea surface temperature and other observable variables to pH (with significant uncertainty)

The Global Ocean Acidification Observing Network (GOA-ON) provides coordination and data access for acidification monitoring that can support national compilation^[28:1].

3.4 Emission Intensity Indicators

Emission intensity indicators link greenhouse gas emissions to economic activity, enabling assessment of the carbon footprint of ocean-related industries and tracking of decarbonisation progress. These indicators combine the air emissions accounts of the SEEA CF with the economic activity data described in TG-3.3 Economic Activity Relevant to the Ocean. The SEEA CF air emissions account methodology attributes emissions to the economic unit responsible for the direct release, which corresponds to Scope 1 emissions in the GHG Protocol terminology^[29]. The SNA 2025 reinforces this treatment through its framework for recording residual flows from the economy to the environment, providing the national accounting basis for emission attribution^[30].

Compilation procedure for ocean sector emission intensity

The derivation of emission intensity indicators from ocean accounts follows a structured procedure:

Step 1: Extract emissions data by industry -- From the air emissions account compiled under TG-3.4 Flows from Economy to Environment, identify the rows corresponding to ocean-related industries (fishing, aquaculture, maritime shipping, offshore energy, coastal tourism) using the ISIC concordance from TG-3.3 Table 2. Record the tonnes of CO2-equivalent emissions attributed to each industry for the accounting period.

Step 2: Extract activity data by industry -- From the ocean economy supply and use tables compiled under TG-3.3, extract the corresponding denominators: tonnes of production (for fishing and aquaculture), tonne-kilometres of freight (for shipping), units of energy produced (for offshore energy), or visitor-days (for coastal tourism). Alternatively, use gross value added (GVA) in monetary units as a common denominator across industries.

Step 3: Calculate intensity ratios -- Divide the emissions (Step 1) by the activity measure (Step 2) to derive the emission intensity for each industry. Express the result in appropriate units: kg CO2e per tonne of fish landed, g CO2e per tonne-kilometre, kg CO2e per unit of energy, or kg CO2e per visitor-day. For GVA-based intensity, express as kg CO2e per thousand currency units of value added.

Step 4: Disaggregate by sub-industry where feasible -- Where data permit, disaggregate intensity indicators by gear type (for fishing), vessel class (for shipping), fuel type (for offshore energy), or tourism segment (for coastal tourism). This disaggregation enables more targeted policy analysis and identification of transition opportunities.

Step 5: Compile time series -- Repeat Steps 1-4 for successive accounting periods to construct a time series showing trends in emission intensity. Declining intensity over time indicates relative decoupling of emissions from economic activity, a key indicator of progress toward climate targets.

Step 6: Document data sources and assumptions -- For each indicator, record the data sources for both the numerator (emissions) and denominator (activity), document any estimation methods or proxies used, and note any discontinuities in the time series due to methodological changes. This documentation is essential for quality assurance per TG-0.7 Quality Assurance.

Industry emission intensity

GHG emissions per unit of output (kg CO2 equivalent per unit of production or value added): The greenhouse gas intensity of specific ocean-related industries, enabling comparison across sectors and tracking over time. Table 2 maps the ocean industries referenced in this section to ISIC Rev.4 codes, following the classification established in TG-3.3 Section 3.3.

Table 2: Ocean Industry Emission Intensity -- ISIC Rev.4 Mapping

Industry-specific considerations include:

• Fishing industry: Emissions per tonne of landed catch or per unit of fish biomass provisioning service. Fuel combustion is the primary emission source, with intensity varying substantially by gear type and target species. For comprehensive guidance on fisheries accounting, see TG-6.8 Fisheries Accounts.
• Aquaculture: Emissions per tonne of production, including both direct emissions (fuel, heating) and embedded emissions in feed and other inputs
• Maritime shipping: Emissions per tonne-kilometre of freight or per passenger-kilometre, following IMO methodologies^[31]
• Offshore energy: Emissions per unit of energy produced, distinguishing between fossil fuel extraction and renewable energy generation. For detailed guidance, see TG-6.9 Offshore Energy.
• Coastal tourism: Emissions per visitor-day or per unit of tourism expenditure

SDG indicator 9.4.1 (CO2 emission per unit of value added) provides the general methodology for industry emission intensity that can be applied to ocean sectors^[32].

Sector-specific considerations

Maritime transport emissions: The International Maritime Organization (IMO) has established the Energy Efficiency Design Index (EEDI) for new ships and the Energy Efficiency Existing Ship Index (EEXI) and Carbon Intensity Indicator (CII) for existing vessels. These regulatory metrics complement accounting-based emission intensity indicators.

Fisheries fuel use intensity: Fuel use per tonne of catch varies substantially by:

• Fishing method (trawling is typically most fuel-intensive)
• Target species and distance to fishing grounds
• Vessel age and efficiency

Tracking fuel use intensity over time provides insight into fisheries sustainability from a climate perspective.

Blue economy transition indicators: The shift toward low-carbon ocean activities can be tracked through:

• Share of ocean energy from renewable sources (offshore wind, wave, tidal)
• Share of shipping using low-carbon fuels
• Carbon intensity of coastal and maritime tourism

Scope 1, 2, and 3 emissions

Following the IFRS S2 framework for climate disclosure, emission intensity indicators should distinguish between^[33]:

• Scope 1: Direct emissions from owned or controlled sources (e.g., vessel fuel combustion, facility operations)
• Scope 2: Indirect emissions from purchased electricity, steam, heating, and cooling
• Scope 3: All other indirect emissions in the value chain, including upstream (fuel production, equipment manufacture) and downstream (product use, end-of-life treatment)

For ocean-related industries, Scope 3 emissions are often substantial--for example, in aquaculture, emissions from feed production may exceed direct operational emissions. However, compilers should note that the SEEA CF air emissions account methodology, which underpins the emission data in ocean accounts, attributes emissions to the economic unit responsible for the direct release. This corresponds to Scope 1 emissions by definition. Ocean accounts therefore primarily capture Scope 1 and Scope 2 emissions attributed by industry, while Scope 3 analysis requires supplementary supply chain modelling using input-output techniques as described in TG-3.3 Section 3.4 on extended applications.

Data inputs for emission intensity compilation

Table 3 summarises the account-based data inputs required for ocean sector emission intensity indicators, specifying the account type, the unit of measure, and the typical source within the ocean accounting framework.

Table 3: Account-Based Inputs for Emission Intensity Indicators

3.5 Climate Risk and Adaptation Indicators

Climate risk indicators assess the exposure and vulnerability of ocean systems, coastal communities, and ocean-dependent economies to climate-related hazards. Adaptation indicators track responses to these risks, including ecosystem-based adaptation through conservation and restoration of coastal ecosystems.

This Circular and TG-2.9 Disaster Risk Indicators share common ground in the assessment of coastal hazard exposure and vulnerability. The distinction lies in temporal framing: this Circular addresses gradual, chronic climate risks (sea level rise, progressive acidification, long-term warming trends) and the indicators that track them, while TG-2.9 addresses acute event-based hazards (storm surge, tsunami, extreme weather events) and the indicators that measure preparedness and response. Where measurement approaches overlap--for example, coastal inundation mapping serves both gradual sea level rise assessment and acute storm surge modelling--compilers should ensure methodological consistency between the two indicator sets.

Physical risk indicators

Physical climate risks can be categorised following the IFRS S2 framework as either chronic (gradual, persistent changes) or acute (event-driven disruptions)^[34]. This distinction affects both measurement methodology and disclosure requirements.

Chronic physical risks:

Sea level rise exposure: The area of coastal land, infrastructure, and ecosystems exposed to projected sea level rise under various scenarios:

• Current elevation relative to mean sea level and high tide lines
• Projected inundation under 0.5m, 1.0m, and 2.0m rise scenarios
• Population and infrastructure within exposed zones

Coastal erosion rates: The rate of shoreline change, distinguishing between:

• Erosion (negative change, land loss)
• Accretion (positive change, land gain)
• Attributable to sea level rise, storm intensity, or other climate factors

Acute physical risks:

Marine heatwave exposure: Frequency, intensity, and duration of marine heatwave events affecting the accounting area:

• Number of marine heatwave days per year
• Maximum intensity (degrees above climatological mean)
• Ecosystem impact (coral bleaching, species displacement)

Storm and cyclone exposure: Frequency and intensity of extreme weather events affecting coastal and marine areas, with potential attribution to climate change. Indicators in this category should be compiled in coordination with the acute hazard indicators in TG-2.9 to ensure consistent treatment of event definitions and thresholds.

Ecosystem vulnerability indicators

Coral bleaching indices: The frequency and severity of coral bleaching events, linked to sea surface temperature anomalies and marine heatwaves. Repeated bleaching compromises reef resilience and recovery capacity.

Ecosystem condition change: Changes in ecosystem condition indicators attributable to climate factors, as recorded in condition accounts:

• Seagrass decline from thermal stress
• Mangrove die-off from altered hydrology
• Species range shifts from changing temperatures

Climate-vulnerable ecosystem extent: The area of ecosystems identified as highly vulnerable to climate impacts, based on sensitivity and adaptive capacity assessments.

Economic risk indicators

Climate-exposed ocean economy: The share of ocean economic activity (value added, employment) in sectors highly exposed to climate physical risks:

• Coastal tourism dependent on beach and reef conditions
• Fisheries dependent on climate-sensitive stocks
• Aquaculture in areas subject to marine heatwaves or extreme events

Projected production impacts: Modelled changes in ecosystem service provision (fisheries yield, coastal protection, carbon sequestration) under climate scenarios.

Adaptation indicators

Nature-based solution deployment: Area of ecosystem-based adaptation implemented:

• Mangrove restoration for coastal protection
• Seagrass restoration for carbon sequestration
• Coral reef restoration for biodiversity and tourism

The thematic guidance in TG-6.2 Mangrove and Coastal Wetland Accounting provides detailed methodology for accounting for these blue carbon ecosystems and their climate adaptation services.

Coastal protection ecosystem services: The value of natural coastal protection provided by coastal ecosystems, representing avoided damages from storm surge and flooding. This indicator links ecosystem condition to climate adaptation benefits.

Climate adaptation expenditure: Government and private sector expenditure on climate adaptation measures in coastal and marine areas, compiled from environmental protection expenditure accounts.

Resilience indicators: Composite indicators of ecosystem and community resilience to climate hazards, potentially including:

• Ecosystem integrity and biodiversity (enhancing adaptive capacity)
• Coastal protection infrastructure (both natural and built)
• Early warning systems and emergency response capacity

The Paris Agreement's Global Goal on Adaptation (GGA) framework is developing standardised metrics for assessing adaptation effectiveness at national and global scales^[35]. As the GGA indicator framework is progressively elaborated, compilers should monitor developments and align adaptation indicators with the emerging international framework where practicable, while maintaining consistency with the accounting structures described in this Circular.

3.6 Worked Example: Ocean Sector GHG Emission Intensity

This worked example demonstrates the compilation procedure for a specific emission intensity indicator--GHG emissions per unit of gross value added for the marine fishing industry. All figures are illustrative and designed to show the accounting logic; actual compilations would use observed data from national air emissions accounts and ocean economy accounts.

Scenario: National marine fishing emissions intensity

Context. A coastal State compiles ocean accounts including air emissions accounts for ocean industries and ocean economy supply-use tables. The compiler seeks to derive the GHG emission intensity indicator for the marine fishing industry (ISIC 0311) for use in national climate reporting and to track progress toward sectoral emission reduction targets.

Step 1: Extract emissions data. From the air emissions account for the accounting period (Year N), the compiler identifies the row for ISIC 0311 (Marine fishing) and records the total GHG emissions:

The emissions figure represents Scope 1 direct emissions from vessel fuel combustion (diesel, gasoline) during fishing operations, recorded at the point of release from the vessel.

Step 2: Extract activity data. From the ocean economy supply-use table for Year N, the compiler extracts two activity measures:

Step 3: Calculate intensity ratios. The compiler calculates two intensity indicators:

(a) Emissions per tonne of landed catch:

450,000 tonnes CO2e / 180,000 tonnes catch = 2.5 tonnes CO2e per tonne of catch

(b) Emissions per unit of GVA:

450,000 tonnes CO2e / 75,000,000 currency units = 0.006 tonnes CO2e per currency unit = 6.0 kg CO2e per thousand currency units of GVA

Step 4: Disaggregate by gear type (optional). Where data permit, the compiler disaggregates the intensity indicator by fishing method. Using supplementary data from the fisheries management authority on fleet composition and catch by gear type:

This disaggregation reveals that purse seine fishing has substantially lower emission intensity (1,333 kg CO2e per tonne) compared to bottom trawl (4,000 kg CO2e per tonne), informing policy discussions on transitioning to lower-emission fishing methods.

Step 5: Compile time series. The compiler repeats the calculation for Years N-4 through N to construct a five-year time series:

The time series shows declining emission intensity over the five-year period (from 2,941 to 2,500 kg CO2e per tonne), a 15 per cent reduction. This indicates relative decoupling of emissions from fishing production, potentially driven by fleet modernisation, fuel efficiency improvements, or shifts in gear composition.

Step 6: Document and report. The compiler documents:

• Data sources: Air emissions account (national statistics office), ocean economy accounts (marine agency), fleet composition (fisheries authority)
• Coverage: Emissions data cover Scope 1 direct emissions only; Scope 2 and 3 are not included
• Exclusions: Small-scale and subsistence fishing are excluded due to data limitations (estimated to represent 10 per cent of national catch)
• Uncertainty: Emissions data have an estimated uncertainty of plus or minus 8 per cent based on fuel consumption survey error
• Policy use: Indicator feeds into NDC sectoral analysis and is reported in the national inventory AFOLU sector

The indicator is published in the national climate reporting tables and the ocean accounts publication, with time series enabling trend analysis and assessment against national emission reduction targets.

4. Acknowledgements

This Circular has been approved for public circulation and comment by the GOAP Technical Experts Group in accordance with the Circular Publication Procedure.

Authors: Mikael JA Maes, Kristine Grimsrud, Taina Loureiro

5. References